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TomAugspurger/style.ipynb

Created November 3, 2015 03:27
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style.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# `df.style`\n",
"\n",
"You can apply **conditional formatting**, the visual styling of a DataFrame\n",
"depending on the data within, by using the ``DataFrame.style`` property.\n",
"This is a property that returns a ``Styler`` object, which has\n",
"useful methods for formatting and displaying DataFrames.\n",
"\n",
"The styling is accomplished using CSS.\n",
"You write functions that take `DataFrame`s or `Series`, and return *like-indexed*\n",
"DataFrames or Series with CSS `\"attribute: value\"` pairs for the values.\n",
"You can build up your styles incrementally using method chains, before rending."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Initialization\n",
"\n",
"The main class you'll work with is `pd.Styler`.\n",
"You can create this class by either\n",
"\n",
"- accessing it with the `DataFrame.style` property\n",
"- passing in a DataFrame, `pd.Styler(dataframe)`\n",
"\n",
"This class holds a reference to your dataframe in the `.data` attribute."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Building Styles\n",
"\n",
"Pass your style functions into one of the following methods:\n",
"\n",
"- `Styler.applymap`: elementwise\n",
"- `Styler.apply`: column/row-wise\n",
"- `Styler.tee`: tablewise\n",
"\n",
"Each of those methods take a function (and some other keyword arguments) and apply your function to the DataFrame in a certain way. `applymap` works through the DataFrame elementwise, `apply` passes each column or row into your DataFrame one-at-a-time, and `.tee` pass in the entire DataFrame at once."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's create a DataFrame to work with."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"np.random.seed(24)\n",
"df = pd.DataFrame({'A': np.linspace(1, 10, 10)})\n",
"df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],\n",
" axis=1)\n",
"df.iloc[0, 2] = np.nan"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here's a (boring) example:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
" \n",
" -1.626404\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow2_col2\" class=\"data row2 col2\">\n",
" \n",
" 0.219565\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow2_col3\" class=\"data row2 col3\">\n",
" \n",
" 0.678805\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow2_col4\" class=\"data row2 col4\">\n",
" \n",
" 1.889273\n",
" \n",
" </th>\n",
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" 3\n",
" \n",
" </th>\n",
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" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow3_col0\" class=\"data row3 col0\">\n",
" \n",
" 4.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow3_col1\" class=\"data row3 col1\">\n",
" \n",
" 0.961538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow3_col2\" class=\"data row3 col2\">\n",
" \n",
" 0.104011\n",
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" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow3_col4\" class=\"data row3 col4\">\n",
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" \n",
" </th>\n",
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" \n",
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" 5.0\n",
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" \n",
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" \n",
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" \n",
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" 6.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow5_col1\" class=\"data row5 col1\">\n",
" \n",
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" \n",
" 0.562861\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
" 1.392855\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
" \n",
" -0.063328\n",
" \n",
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" \n",
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" \n",
" 7.0\n",
" \n",
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" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
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" \n",
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" \n",
" <td id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.00204\n",
" \n",
" </th>\n",
" \n",
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" \n",
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" \n",
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" \n",
" <th id=\"T_4b5aec52_81d8_11e5_9470_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
" 7\n",
" \n",
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" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x112050e10>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*Note*: The `DataFrame.style` is a propetry that returns a `Styler` object. `Styler` has a `_repr_html_` method defined on it so they are rendered automatically. If you want the actual HTML back for further processing or for writing to file call the `.render()` method which returns a string.\n",
"\n",
"The above output looks very similar to the standard DataFrame HTML representation. But we've done some work behind the scenes to attach CSS classes to each cell. We can view these by calling the `.render` method."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['',\n",
" ' <style type=\"text/css\" >',\n",
" ' ',\n",
" ' ',\n",
" ' #T_4b97aef0_81d8_11e5_8076_a45e60bd97fbrow0_col0 {',\n",
" ' ',\n",
" ' }',\n",
" ' ',\n",
" ' #T_4b97aef0_81d8_11e5_8076_a45e60bd97fbrow0_col1 {',\n",
" ' ']"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.render().split('\\n')[:10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `row0_col0` is the identifier for that particular cell. We've also prepended each row/column identifier with a UUID unique each DataFrame so that the style from one doesn't collied with the styling from another within the same notebook / page (you can set the `uuid` if you'd like to tie together the styling of two DataFrames)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's write a simple function that will color negative numbers red and positive numbers black."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def color_negative_red(val):\n",
" \"\"\"\n",
" Takes a scalar and returns a string with\n",
" the css property `'color: red'` for negative\n",
" strings, black otherwise.\n",
" \"\"\"\n",
" color = 'red' if val < 0 else 'black'\n",
" return 'color: %s' % color"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"text/plain": [
"<pandas.core.style.Styler at 0x11580aac8>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.applymap(color_negative_red)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First, notice the similarity with the standard `df.applymap`, which operates on DataFrames elementwise. We want you to be able to resuse your existing knowledge of how to interact with DataFrames. `df.style.applymap` also takes a function that operates elementwise.\n",
"\n",
"Second, notice that our function returned a string containing the CSS attribute and value. This will be a common theme."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now suppose you wanted to highlight the maximum value in each column.\n",
"We can't use `.applymap` anymore since that operated elementwise.\n",
"Instead, we'll turn to `.apply` which operates columnwise (or rowwise using the `axis` keyword)."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def highlight_max(s):\n",
" '''\n",
" highlight the maximum in a Series\n",
" '''\n",
" is_max = s == s.max()\n",
" return pd.Series(['background-color: yellow' if v else '' for v in is_max], name=s.name)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
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],
"text/plain": [
"<pandas.core.style.Styler at 0x115817e10>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.apply(highlight_max)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We encourage you to use method chains to build up a style piecewise, before finally rending at the end of the chain."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow5_col4 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col0 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col1 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col2 {\n",
" \n",
" color: black;\n",
" \n",
" background-color: yellow;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col3 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col4 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col0 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col1 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col2 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col3 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col4 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col0 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col1 {\n",
" \n",
" color: black;\n",
" \n",
" background-color: yellow;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col2 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col3 {\n",
" \n",
" color: black;\n",
" \n",
" background-color: yellow;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col4 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col0 {\n",
" \n",
" color: black;\n",
" \n",
" background-color: yellow;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col1 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col2 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col3 {\n",
" \n",
" color: red;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
" #T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col4 {\n",
" \n",
" color: black;\n",
" \n",
" : ;\n",
" \n",
" }\n",
" \n",
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"\n",
" <table id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\">\n",
" \n",
"\n",
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" \n",
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" \n",
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" \n",
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" \n",
" <th class=\"col_heading level0 col1\">B</th>\n",
" \n",
" <th class=\"col_heading level0 col2\">C</th>\n",
" \n",
" <th class=\"col_heading level0 col3\">D</th>\n",
" \n",
" <th class=\"col_heading level0 col4\">E</th>\n",
" \n",
" </tr>\n",
" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row0\">\n",
" \n",
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" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow0_col0\" class=\"data row0 col0\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow0_col1\" class=\"data row0 col1\">\n",
" \n",
" 1.329212\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow0_col4\" class=\"data row0 col4\">\n",
" \n",
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" \n",
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" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row1\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow1_col0\" class=\"data row1 col0\">\n",
" \n",
" 2.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow1_col1\" class=\"data row1 col1\">\n",
" \n",
" -1.070816\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow1_col2\" class=\"data row1 col2\">\n",
" \n",
" -1.438713\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow1_col3\" class=\"data row1 col3\">\n",
" \n",
" 0.564417\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow1_col4\" class=\"data row1 col4\">\n",
" \n",
" 0.295722\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row2\">\n",
" \n",
" 2\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow2_col0\" class=\"data row2 col0\">\n",
" \n",
" 3.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
" \n",
" -1.626404\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow2_col2\" class=\"data row2 col2\">\n",
" \n",
" 0.219565\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow2_col3\" class=\"data row2 col3\">\n",
" \n",
" 0.678805\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow2_col4\" class=\"data row2 col4\">\n",
" \n",
" 1.889273\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row3\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow3_col0\" class=\"data row3 col0\">\n",
" \n",
" 4.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow3_col1\" class=\"data row3 col1\">\n",
" \n",
" 0.961538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow3_col2\" class=\"data row3 col2\">\n",
" \n",
" 0.104011\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow3_col3\" class=\"data row3 col3\">\n",
" \n",
" -0.481165\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow3_col4\" class=\"data row3 col4\">\n",
" \n",
" 0.850229\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row4\">\n",
" \n",
" 4\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow4_col0\" class=\"data row4 col0\">\n",
" \n",
" 5.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow4_col1\" class=\"data row4 col1\">\n",
" \n",
" 1.453425\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow4_col2\" class=\"data row4 col2\">\n",
" \n",
" 1.057737\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow4_col3\" class=\"data row4 col3\">\n",
" \n",
" 0.165562\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow4_col4\" class=\"data row4 col4\">\n",
" \n",
" 0.515018\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row5\">\n",
" \n",
" 5\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow5_col0\" class=\"data row5 col0\">\n",
" \n",
" 6.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow5_col1\" class=\"data row5 col1\">\n",
" \n",
" -1.336936\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow5_col2\" class=\"data row5 col2\">\n",
" \n",
" 0.562861\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
" 1.392855\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
" \n",
" -0.063328\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row6\">\n",
" \n",
" 6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" 7.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 0.121668\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" 1.207603\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.00204\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" 1.627796\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
" 7\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 8.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" 0.354493\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 1.037528\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
" -0.385684\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.519818\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.686583\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.325963\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.089354\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.12982\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.631523\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.586538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_537db826_81d8_11e5_9b15_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x115817cc0>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.\\\n",
" applymap(color_negative_red).\\\n",
" apply(highlight_max)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We've seen `.applymap` and `.apply`. The final method for passing in style functions is `.tee`.\n",
"\n",
"Let's rewrite our `highlight-max` to handle either Series (from `.apply`) or DataFrames (from `.tee`). We'll also allow the color to be adjustable, to demonstrate that `.tee`, `.apply`, and `.applymap` all pass along keyword arguments."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def highlight_max(data, color='yellow'):\n",
" '''\n",
" highlight the maximum in a Series or DataFrame\n",
" '''\n",
" attr = 'background-color: {}'.format(color)\n",
" if data.ndim == 1: # Series from .apply\n",
" is_max = data == data.max()\n",
" return pd.Series([attr if v else '' for v in is_max])\n",
" else: # DataFrame from .tee\n",
" is_max = data == data.max().max()\n",
" return pd.DataFrame(np.where(is_max, attr, ''),\n",
" index=data.index, columns=data.columns)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
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],
"text/plain": [
"<pandas.core.style.Styler at 0x11580a080>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.tee(highlight_max, color='darkorange')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can control the precision of floats using pandas' regular `display.precision` option."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" \n",
" 0.1\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow3_col3\" class=\"data row3 col3\">\n",
" \n",
" -0.48\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow3_col4\" class=\"data row3 col4\">\n",
" \n",
" 0.85\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fb\" class=\"row_heading level4 row4\">\n",
" \n",
" 4\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow4_col0\" class=\"data row4 col0\">\n",
" \n",
" 5.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow4_col1\" class=\"data row4 col1\">\n",
" \n",
" 1.45\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow4_col2\" class=\"data row4 col2\">\n",
" \n",
" 1.06\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow4_col3\" class=\"data row4 col3\">\n",
" \n",
" 0.17\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow4_col4\" class=\"data row4 col4\">\n",
" \n",
" 0.52\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fb\" class=\"row_heading level4 row5\">\n",
" \n",
" 5\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow5_col0\" class=\"data row5 col0\">\n",
" \n",
" 6.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow5_col1\" class=\"data row5 col1\">\n",
" \n",
" -1.34\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow5_col2\" class=\"data row5 col2\">\n",
" \n",
" 0.56\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
" 1.39\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
" \n",
" -0.06\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fb\" class=\"row_heading level4 row6\">\n",
" \n",
" 6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" 7.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 0.12\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" 1.21\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" 1.63\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
" 7\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 8.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" 0.35\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 1.04\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
" -0.39\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.52\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.69\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.33\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.43\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.09\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.13\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.63\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.59\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_75e519ae_81d8_11e5_b97d_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x11580ac88>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"with pd.option_context('display.precision', 2):\n",
" html = (df.style\n",
" .applymap(color_negative_red)\n",
" .apply(highlight_max))\n",
"html"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Finer Control"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The signatures for `Styler.apply`, `Styler.applymap` and `Styler.tee` all include a `subset` keyword.\n",
"This allows you to apply styles to specific rows or columns, without having to code that logic into your `style` function."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" #T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow6_col2 {\n",
" \n",
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" #T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow6_col3 {\n",
" \n",
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" #T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow6_col4 {\n",
" \n",
" }\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" }\n",
" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" }\n",
" \n",
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" \n",
" }\n",
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" \n",
" }\n",
" \n",
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" \n",
" }\n",
" \n",
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"\n",
" <table id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fb\">\n",
" \n",
"\n",
" <thead>\n",
" \n",
" <tr>\n",
" \n",
" <th class=\"blank\"></th>\n",
" \n",
" <th class=\"col_heading level0 col0\">A</th>\n",
" \n",
" <th class=\"col_heading level0 col1\">B</th>\n",
" \n",
" <th class=\"col_heading level0 col2\">C</th>\n",
" \n",
" <th class=\"col_heading level0 col3\">D</th>\n",
" \n",
" <th class=\"col_heading level0 col4\">E</th>\n",
" \n",
" </tr>\n",
" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fb\" class=\"row_heading level4 row0\">\n",
" \n",
" 0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow0_col0\" class=\"data row0 col0\">\n",
" \n",
" 1.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow0_col1\" class=\"data row0 col1\">\n",
" \n",
" 1.329212\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
" -0.31628\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow0_col4\" class=\"data row0 col4\">\n",
" \n",
" -0.99081\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fb\" class=\"row_heading level4 row1\">\n",
" \n",
" 1\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow1_col0\" class=\"data row1 col0\">\n",
" \n",
" 2.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow1_col1\" class=\"data row1 col1\">\n",
" \n",
" -1.070816\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow1_col2\" class=\"data row1 col2\">\n",
" \n",
" -1.438713\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow1_col3\" class=\"data row1 col3\">\n",
" \n",
" 0.564417\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow1_col4\" class=\"data row1 col4\">\n",
" \n",
" 0.295722\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
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" \n",
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" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
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" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
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" \n",
" <td id=\"T_7dbcebd4_81d8_11e5_ad7e_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
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],
"text/plain": [
"<pandas.core.style.Styler at 0x115816198>"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.applymap(color_negative_red, subset=pd.IndexSlice[2:5, ['B', 'D']])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We reuse `DataFrame.loc` internally, so `subset` can be anything that will slice the original DataFrame. Consider using `pd.IndexSlice` to make writing the slices easier.\n",
"\n",
"**N.B.** If your style function uses a `subset` keyword argument, consider wrapping your function in a `functools.partial`, partialing out that keyword.\n",
"\n",
"```python\n",
"my_func2 = functools.partial(my_func, subset=42)\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Builtins"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally, we expect certain styling functions to be common enough that we've included a few \"built-in\" to the `Styler`, so you don't have to write them yourself."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"text/plain": [
"<pandas.core.style.Styler at 0x11580ab70>"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.highlight_null(null_color='red')"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
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" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow4_col4 {\n",
" \n",
" background-color: #4fac4f;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col0 {\n",
" \n",
" background-color: #66b866;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col1 {\n",
" \n",
" background-color: #d2f4d2;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col2 {\n",
" \n",
" background-color: #389f38;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col3 {\n",
" \n",
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" \n",
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" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col4 {\n",
" \n",
" background-color: #70be70;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col0 {\n",
" \n",
" background-color: #4daa4d;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col1 {\n",
" \n",
" background-color: #6cbc6c;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col2 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col3 {\n",
" \n",
" background-color: #a3daa3;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col4 {\n",
" \n",
" background-color: #0e880e;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col0 {\n",
" \n",
" background-color: #329c32;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col1 {\n",
" \n",
" background-color: #5cb35c;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col2 {\n",
" \n",
" background-color: #0e880e;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col3 {\n",
" \n",
" background-color: #cff3cf;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col4 {\n",
" \n",
" background-color: #4fac4f;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col0 {\n",
" \n",
" background-color: #198e19;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col1 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col2 {\n",
" \n",
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" \n",
" }\n",
" \n",
" #T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col3 {\n",
" \n",
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" \n",
" }\n",
" \n",
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" \n",
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" }\n",
" \n",
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" \n",
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" \n",
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" <th class=\"col_heading level0 col1\">B</th>\n",
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" <th class=\"col_heading level0 col2\">C</th>\n",
" \n",
" <th class=\"col_heading level0 col3\">D</th>\n",
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" \n",
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" \n",
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" </th>\n",
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" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
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" \n",
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" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow3_col0\" class=\"data row3 col0\">\n",
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" \n",
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" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow4_col0\" class=\"data row4 col0\">\n",
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" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col0\" class=\"data row5 col0\">\n",
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" \n",
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" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col2\" class=\"data row5 col2\">\n",
" \n",
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" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
" 1.392855\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
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" \n",
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" \n",
" <tr>\n",
" \n",
" <th id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fb\" class=\"row_heading level4 row6\">\n",
" \n",
" 6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" 7.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 0.121668\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" 1.207603\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.00204\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" 1.627796\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
" 7\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 8.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" 0.354493\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 1.037528\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.519818\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.686583\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.089354\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.12982\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.631523\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.586538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8752e950_81d8_11e5_991c_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x11580a4a8>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import seaborn as sns\n",
"\n",
"cm = sns.light_palette(\"green\", as_cmap=True)\n",
"\n",
"s = df.style.color_bg_range(cmap=cm)\n",
"s"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
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" \n",
" \n",
" #T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow0_col0 {\n",
" \n",
" background-color: black;\n",
" \n",
" border-color: white;\n",
" \n",
" color: lawngreen;\n",
" \n",
" }\n",
" \n",
" #T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow0_col1 {\n",
" \n",
" background-color: black;\n",
" \n",
" border-color: white;\n",
" \n",
" color: lawngreen;\n",
" \n",
" }\n",
" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
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" \n",
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" \n",
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" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow1_col1\" class=\"data row1 col1\">\n",
" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow1_col4\" class=\"data row1 col4\">\n",
" \n",
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" \n",
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" \n",
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" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow2_col0\" class=\"data row2 col0\">\n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow2_col3\" class=\"data row2 col3\">\n",
" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow3_col0\" class=\"data row3 col0\">\n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow3_col1\" class=\"data row3 col1\">\n",
" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow3_col2\" class=\"data row3 col2\">\n",
" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow3_col3\" class=\"data row3 col3\">\n",
" \n",
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" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow3_col4\" class=\"data row3 col4\">\n",
" \n",
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" \n",
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" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow4_col0\" class=\"data row4 col0\">\n",
" \n",
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" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow4_col1\" class=\"data row4 col1\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow4_col2\" class=\"data row4 col2\">\n",
" \n",
" 1.057737\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow4_col3\" class=\"data row4 col3\">\n",
" \n",
" 0.165562\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow4_col4\" class=\"data row4 col4\">\n",
" \n",
" 0.515018\n",
" \n",
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" \n",
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" \n",
" <tr>\n",
" \n",
" <th id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fb\" class=\"row_heading level4 row5\">\n",
" \n",
" 5\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow5_col0\" class=\"data row5 col0\">\n",
" \n",
" 6.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow5_col1\" class=\"data row5 col1\">\n",
" \n",
" -1.336936\n",
" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow5_col2\" class=\"data row5 col2\">\n",
" \n",
" 0.562861\n",
" \n",
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" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
" \n",
" -0.063328\n",
" \n",
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" \n",
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" \n",
" <tr>\n",
" \n",
" <th id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fb\" class=\"row_heading level4 row6\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" 7.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 0.121668\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" 1.207603\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.00204\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" 1.627796\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
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" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 8.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" 0.354493\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 1.037528\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
" -0.385684\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.519818\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.686583\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.325963\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.089354\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.12982\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.631523\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.586538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8a70cc88_81d8_11e5_bbdd_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x11580a470>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Use .set_properties when it doesn't actually depend on the values\n",
"df.style.set_properties(**{'background-color': 'black',\n",
" 'color': 'lawngreen',\n",
" 'border-color': 'white'})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Other options\n",
"\n",
"You've seen a few methods for data-driven styling.\n",
"`Styler` also provides a few other options for styling that don't depend on the data.\n",
"\n",
"- captions\n",
"- table-wide styles\n",
"\n",
"Each of these can be specified in two ways:\n",
"\n",
"- A keyword argument to `pd.Styler`\n",
"- A keyword argument to `.render`\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Captions"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from pandas.core.style import Styler"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"\n",
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" \n",
"\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
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" \n",
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" \n",
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" \n",
" </th>\n",
" \n",
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" \n",
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" \n",
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" <td id=\"T_8e2374fa_81d8_11e5_bbc7_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8e2374fa_81d8_11e5_bbc7_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_8e2374fa_81d8_11e5_bbc7_a45e60bd97fbrow1_col0\" class=\"data row1 col0\">\n",
" \n",
" 2.0\n",
" \n",
" </th>\n",
" \n",
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" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x11580a780>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s = Styler(df, caption='Colormaps, with a caption.')\n",
"s.color_bg_range(cmap=cm)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Alternativly, pass the caption in when rendering."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" \n",
" background-color: #4fac4f;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col0 {\n",
" \n",
" background-color: #198e19;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col1 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col2 {\n",
" \n",
" background-color: #dcfadc;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col3 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col4 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col0 {\n",
" \n",
" background-color: #008000;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col1 {\n",
" \n",
" background-color: #7ec67e;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col2 {\n",
" \n",
" background-color: #319b31;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col3 {\n",
" \n",
" background-color: #e5ffe5;\n",
" \n",
" }\n",
" \n",
" #T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col4 {\n",
" \n",
" background-color: #5cb35c;\n",
" \n",
" }\n",
" \n",
" </style>\n",
"\n",
" <table id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\">\n",
" \n",
" <caption>Caption, from render.</caption>\n",
" \n",
"\n",
" <thead>\n",
" \n",
" <tr>\n",
" \n",
" <th class=\"blank\"></th>\n",
" \n",
" <th class=\"col_heading level0 col0\">A</th>\n",
" \n",
" <th class=\"col_heading level0 col1\">B</th>\n",
" \n",
" <th class=\"col_heading level0 col2\">C</th>\n",
" \n",
" <th class=\"col_heading level0 col3\">D</th>\n",
" \n",
" <th class=\"col_heading level0 col4\">E</th>\n",
" \n",
" </tr>\n",
" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row0\">\n",
" \n",
" 0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow0_col0\" class=\"data row0 col0\">\n",
" \n",
" 1.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow0_col1\" class=\"data row0 col1\">\n",
" \n",
" 1.329212\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
" -0.31628\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow0_col4\" class=\"data row0 col4\">\n",
" \n",
" -0.99081\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row1\">\n",
" \n",
" 1\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow1_col0\" class=\"data row1 col0\">\n",
" \n",
" 2.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow1_col1\" class=\"data row1 col1\">\n",
" \n",
" -1.070816\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow1_col2\" class=\"data row1 col2\">\n",
" \n",
" -1.438713\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow1_col3\" class=\"data row1 col3\">\n",
" \n",
" 0.564417\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow1_col4\" class=\"data row1 col4\">\n",
" \n",
" 0.295722\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row2\">\n",
" \n",
" 2\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow2_col0\" class=\"data row2 col0\">\n",
" \n",
" 3.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
" \n",
" -1.626404\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow2_col2\" class=\"data row2 col2\">\n",
" \n",
" 0.219565\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow2_col3\" class=\"data row2 col3\">\n",
" \n",
" 0.678805\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow2_col4\" class=\"data row2 col4\">\n",
" \n",
" 1.889273\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row3\">\n",
" \n",
" 3\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow3_col0\" class=\"data row3 col0\">\n",
" \n",
" 4.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow3_col1\" class=\"data row3 col1\">\n",
" \n",
" 0.961538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow3_col2\" class=\"data row3 col2\">\n",
" \n",
" 0.104011\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow3_col3\" class=\"data row3 col3\">\n",
" \n",
" -0.481165\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow3_col4\" class=\"data row3 col4\">\n",
" \n",
" 0.850229\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row4\">\n",
" \n",
" 4\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow4_col0\" class=\"data row4 col0\">\n",
" \n",
" 5.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow4_col1\" class=\"data row4 col1\">\n",
" \n",
" 1.453425\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow4_col2\" class=\"data row4 col2\">\n",
" \n",
" 1.057737\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow4_col3\" class=\"data row4 col3\">\n",
" \n",
" 0.165562\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow4_col4\" class=\"data row4 col4\">\n",
" \n",
" 0.515018\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row5\">\n",
" \n",
" 5\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow5_col0\" class=\"data row5 col0\">\n",
" \n",
" 6.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow5_col1\" class=\"data row5 col1\">\n",
" \n",
" -1.336936\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow5_col2\" class=\"data row5 col2\">\n",
" \n",
" 0.562861\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
" 1.392855\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
" \n",
" -0.063328\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row6\">\n",
" \n",
" 6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" 7.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 0.121668\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" 1.207603\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.00204\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" 1.627796\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
" 7\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 8.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" 0.354493\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 1.037528\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
" -0.385684\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.519818\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.686583\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.325963\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.089354\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.12982\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.631523\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.586538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_8fb1b324_81d8_11e5_9c0a_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from IPython.display import HTML\n",
"HTML(\n",
" df.style.color_bg_range(cmap=cm).render(caption=\"Caption, from render.\")\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The next option you have to pass in are \"table styles\".\n",
"These are styles that apply to the table as a whole, and don't look at the data.\n",
"Certain sytlings, including pseudo-selectors like `:hover` can only be used this way."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style type=\"text/css\" >\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb tr:hover {\n",
" \n",
" background-color: #ffff99;\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb th {\n",
" \n",
" font-size: 150%;\n",
" \n",
" text-align: center;\n",
" \n",
" }\n",
" \n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col4 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col0 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col1 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col2 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col3 {\n",
" \n",
" }\n",
" \n",
" #T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col4 {\n",
" \n",
" }\n",
" \n",
" </style>\n",
"\n",
" <table id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\">\n",
" \n",
"\n",
" <thead>\n",
" \n",
" <tr>\n",
" \n",
" <th class=\"blank\"></th>\n",
" \n",
" <th class=\"col_heading level0 col0\">A</th>\n",
" \n",
" <th class=\"col_heading level0 col1\">B</th>\n",
" \n",
" <th class=\"col_heading level0 col2\">C</th>\n",
" \n",
" <th class=\"col_heading level0 col3\">D</th>\n",
" \n",
" <th class=\"col_heading level0 col4\">E</th>\n",
" \n",
" </tr>\n",
" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row0\">\n",
" \n",
" 0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col0\" class=\"data row0 col0\">\n",
" \n",
" 1.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col1\" class=\"data row0 col1\">\n",
" \n",
" 1.329212\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
" -0.31628\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow0_col4\" class=\"data row0 col4\">\n",
" \n",
" -0.99081\n",
" \n",
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" \n",
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" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row1\">\n",
" \n",
" 1\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col0\" class=\"data row1 col0\">\n",
" \n",
" 2.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col1\" class=\"data row1 col1\">\n",
" \n",
" -1.070816\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col2\" class=\"data row1 col2\">\n",
" \n",
" -1.438713\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col3\" class=\"data row1 col3\">\n",
" \n",
" 0.564417\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow1_col4\" class=\"data row1 col4\">\n",
" \n",
" 0.295722\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row2\">\n",
" \n",
" 2\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col0\" class=\"data row2 col0\">\n",
" \n",
" 3.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
" \n",
" -1.626404\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col2\" class=\"data row2 col2\">\n",
" \n",
" 0.219565\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col3\" class=\"data row2 col3\">\n",
" \n",
" 0.678805\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow2_col4\" class=\"data row2 col4\">\n",
" \n",
" 1.889273\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row3\">\n",
" \n",
" 3\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col0\" class=\"data row3 col0\">\n",
" \n",
" 4.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col1\" class=\"data row3 col1\">\n",
" \n",
" 0.961538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col2\" class=\"data row3 col2\">\n",
" \n",
" 0.104011\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col3\" class=\"data row3 col3\">\n",
" \n",
" -0.481165\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow3_col4\" class=\"data row3 col4\">\n",
" \n",
" 0.850229\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row4\">\n",
" \n",
" 4\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col0\" class=\"data row4 col0\">\n",
" \n",
" 5.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col1\" class=\"data row4 col1\">\n",
" \n",
" 1.453425\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col2\" class=\"data row4 col2\">\n",
" \n",
" 1.057737\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col3\" class=\"data row4 col3\">\n",
" \n",
" 0.165562\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow4_col4\" class=\"data row4 col4\">\n",
" \n",
" 0.515018\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row5\">\n",
" \n",
" 5\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col0\" class=\"data row5 col0\">\n",
" \n",
" 6.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col1\" class=\"data row5 col1\">\n",
" \n",
" -1.336936\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col2\" class=\"data row5 col2\">\n",
" \n",
" 0.562861\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col3\" class=\"data row5 col3\">\n",
" \n",
" 1.392855\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow5_col4\" class=\"data row5 col4\">\n",
" \n",
" -0.063328\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row6\">\n",
" \n",
" 6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" 7.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 0.121668\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" 1.207603\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" -0.00204\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" 1.627796\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
" \n",
" 7\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 8.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" 0.354493\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 1.037528\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
" -0.385684\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.519818\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.686583\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.325963\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.089354\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.12982\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.631523\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.586538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_0aeecedc_81d9_11e5_b8e4_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def hover(hover_color=\"#ffff99\"):\n",
" return dict(selector=\"tr:hover\", props=[(\"background-color\", \"%s\" % hover_color)])\n",
"\n",
"styles = [hover(), dict(selector=\"th\", props=[(\"font-size\", \"150%\"),\n",
" (\"text-align\", \"center\")])]\n",
"html = df.style.render(style=styles)\n",
"HTML(html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A few example styling functions. Perhaps we'll have a repo of these somewhere."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fun stuff."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# https://developer.mozilla.org/en-US/docs/Web/CSS/animation#Cylon_Eye\n",
"# no animation yet :(\n",
"\n",
"def cylon(s):\n",
" tpl = \"\"\"\n",
" background-color: red;\n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" color: white;\n",
" height: 100%;\n",
" width: 20\"\"\"\n",
" return pd.Series([tpl for i in s], index=s.index, name=s.name)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false
},
"outputs": [
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" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow7_col1 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow7_col2 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow7_col3 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow7_col4 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow8_col0 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow8_col1 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow8_col2 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow8_col3 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow8_col4 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow9_col0 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow9_col1 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow9_col2 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow9_col3 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" #T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow9_col4 {\n",
" \n",
" \n",
" background-color: red;\n",
" \n",
" \n",
" background-image: -webkit-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -moz-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: -o-linear-gradient( left, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" background-image: linear-gradient(to right, rgba( 0,0,0,0.9 ) 25%, rgba( 0,0,0,0.1 ) 50%, rgba( 0,0,0,0.9 ) 75%);\n",
" \n",
" \n",
" color: white;\n",
" \n",
" \n",
" height: 100%;\n",
" \n",
" \n",
" width: 20;\n",
" \n",
" }\n",
" \n",
" </style>\n",
"\n",
" <table id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fb\">\n",
" \n",
"\n",
" <thead>\n",
" \n",
" <tr>\n",
" \n",
" <th class=\"blank\"></th>\n",
" \n",
" <th class=\"col_heading level0 col0\">A</th>\n",
" \n",
" <th class=\"col_heading level0 col1\">B</th>\n",
" \n",
" <th class=\"col_heading level0 col2\">C</th>\n",
" \n",
" <th class=\"col_heading level0 col3\">D</th>\n",
" \n",
" <th class=\"col_heading level0 col4\">E</th>\n",
" \n",
" </tr>\n",
" \n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fb\" class=\"row_heading level4 row0\">\n",
" \n",
" 0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow0_col0\" class=\"data row0 col0\">\n",
" \n",
" 1.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow0_col1\" class=\"data row0 col1\">\n",
" \n",
" 1.329212\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow0_col2\" class=\"data row0 col2\">\n",
" \n",
" nan\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow0_col3\" class=\"data row0 col3\">\n",
" \n",
" -0.31628\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow0_col4\" class=\"data row0 col4\">\n",
" \n",
" -0.99081\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fb\" class=\"row_heading level4 row1\">\n",
" \n",
" 1\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow1_col0\" class=\"data row1 col0\">\n",
" \n",
" 2.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow1_col1\" class=\"data row1 col1\">\n",
" \n",
" -1.070816\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow1_col2\" class=\"data row1 col2\">\n",
" \n",
" -1.438713\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow1_col3\" class=\"data row1 col3\">\n",
" \n",
" 0.564417\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow1_col4\" class=\"data row1 col4\">\n",
" \n",
" 0.295722\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fb\" class=\"row_heading level4 row2\">\n",
" \n",
" 2\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow2_col0\" class=\"data row2 col0\">\n",
" \n",
" 3.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow2_col1\" class=\"data row2 col1\">\n",
" \n",
" -1.626404\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow2_col2\" class=\"data row2 col2\">\n",
" \n",
" 0.219565\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow2_col3\" class=\"data row2 col3\">\n",
" \n",
" 0.678805\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fbrow2_col4\" class=\"data row2 col4\">\n",
" \n",
" 1.889273\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_4a2e8fcc_81d9_11e5_93f8_a45e60bd97fb\" class=\"row_heading level4 row3\">\n",
" \n",
" 3\n",
" \n",
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" \n",
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],
"text/plain": [
"<pandas.core.style.Styler at 0x115867470>"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style.apply(cylon)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Interacts pretty well with widgets."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <th id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fb\" class=\"row_heading level4 row7\">\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
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" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
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" \n",
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" \n",
" <th id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fb\" class=\"row_heading level4 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 9.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" 1.686583\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.325963\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" 1.428984\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" -2.089354\n",
" \n",
" </th>\n",
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" \n",
" <tr>\n",
" \n",
" <th id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fb\" class=\"row_heading level4 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 10.0\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.12982\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" 0.631523\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" -0.586538\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_4c71fb2c_81d9_11e5_afeb_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" 0.29072\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x115867748>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from IPython.html import widgets\n",
"@widgets.interact\n",
"def f(h_neg=(0, 359, 1), h_pos=(0, 359), s=(0., 99.9), l=(0., 99.9)):\n",
" return df.style.color_bg_range(\n",
" cmap=sns.palettes.diverging_palette(h_neg=h_neg, h_pos=h_pos, s=s, l=l,\n",
" as_cmap=True)\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from IPython.display import HTML\n",
"\n",
"np.random.seed(24)\n",
"df = pd.DataFrame({'A': np.linspace(1, 10, 10)})\n",
"df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],\n",
" axis=1)\n",
"df.iloc[0, 2] = np.nan"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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" \n",
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" \n",
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" \n",
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" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row6\">\n",
" \n",
" 6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col0\" class=\"data row6 col0\">\n",
" \n",
" -1.16\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col1\" class=\"data row6 col1\">\n",
" \n",
" 1.07\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col2\" class=\"data row6 col2\">\n",
" \n",
" -0.58\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col3\" class=\"data row6 col3\">\n",
" \n",
" 1.44\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col4\" class=\"data row6 col4\">\n",
" \n",
" -0.92\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col5\" class=\"data row6 col5\">\n",
" \n",
" -2.6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col6\" class=\"data row6 col6\">\n",
" \n",
" -1.12\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col7\" class=\"data row6 col7\">\n",
" \n",
" 0.44\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col8\" class=\"data row6 col8\">\n",
" \n",
" 0.02\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col9\" class=\"data row6 col9\">\n",
" \n",
" 1.15\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow6_col10\" class=\"data row6 col10\">\n",
" \n",
" 0.5\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row7\">\n",
" \n",
" 7\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col0\" class=\"data row7 col0\">\n",
" \n",
" 0.89\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col1\" class=\"data row7 col1\">\n",
" \n",
" -0.25\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col2\" class=\"data row7 col2\">\n",
" \n",
" 0.92\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col3\" class=\"data row7 col3\">\n",
" \n",
" -2.19\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col4\" class=\"data row7 col4\">\n",
" \n",
" 0.53\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col5\" class=\"data row7 col5\">\n",
" \n",
" -0.71\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col6\" class=\"data row7 col6\">\n",
" \n",
" 1.42\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col7\" class=\"data row7 col7\">\n",
" \n",
" -0.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col8\" class=\"data row7 col8\">\n",
" \n",
" 0.23\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col9\" class=\"data row7 col9\">\n",
" \n",
" -2.29\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow7_col10\" class=\"data row7 col10\">\n",
" \n",
" 0.53\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row8\">\n",
" \n",
" 8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col0\" class=\"data row8 col0\">\n",
" \n",
" 0.17\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col1\" class=\"data row8 col1\">\n",
" \n",
" -0.81\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col2\" class=\"data row8 col2\">\n",
" \n",
" -1.88\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col3\" class=\"data row8 col3\">\n",
" \n",
" -1.22\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col4\" class=\"data row8 col4\">\n",
" \n",
" 0.78\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col5\" class=\"data row8 col5\">\n",
" \n",
" -0.97\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col6\" class=\"data row8 col6\">\n",
" \n",
" 0.34\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col7\" class=\"data row8 col7\">\n",
" \n",
" -0.29\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col8\" class=\"data row8 col8\">\n",
" \n",
" -1.73\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col9\" class=\"data row8 col9\">\n",
" \n",
" -0.78\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow8_col10\" class=\"data row8 col10\">\n",
" \n",
" 0.02\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row9\">\n",
" \n",
" 9\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col0\" class=\"data row9 col0\">\n",
" \n",
" 1.69\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col1\" class=\"data row9 col1\">\n",
" \n",
" -0.56\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col2\" class=\"data row9 col2\">\n",
" \n",
" -0.3\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col3\" class=\"data row9 col3\">\n",
" \n",
" 0.98\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col4\" class=\"data row9 col4\">\n",
" \n",
" -0.29\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col5\" class=\"data row9 col5\">\n",
" \n",
" 0.32\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col6\" class=\"data row9 col6\">\n",
" \n",
" 0.3\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col7\" class=\"data row9 col7\">\n",
" \n",
" 2.04\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col8\" class=\"data row9 col8\">\n",
" \n",
" 0.6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col9\" class=\"data row9 col9\">\n",
" \n",
" -0.93\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow9_col10\" class=\"data row9 col10\">\n",
" \n",
" -0.42\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row10\">\n",
" \n",
" 10\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col0\" class=\"data row10 col0\">\n",
" \n",
" -0.09\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col1\" class=\"data row10 col1\">\n",
" \n",
" 1.91\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col2\" class=\"data row10 col2\">\n",
" \n",
" -0.08\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col3\" class=\"data row10 col3\">\n",
" \n",
" 2.48\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col4\" class=\"data row10 col4\">\n",
" \n",
" -0.18\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col5\" class=\"data row10 col5\">\n",
" \n",
" 0.75\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col6\" class=\"data row10 col6\">\n",
" \n",
" -0.42\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col7\" class=\"data row10 col7\">\n",
" \n",
" -1.05\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col8\" class=\"data row10 col8\">\n",
" \n",
" -0.66\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col9\" class=\"data row10 col9\">\n",
" \n",
" 1.51\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow10_col10\" class=\"data row10 col10\">\n",
" \n",
" 0.6\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row11\">\n",
" \n",
" 11\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col0\" class=\"data row11 col0\">\n",
" \n",
" -0.44\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col1\" class=\"data row11 col1\">\n",
" \n",
" 0.47\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col2\" class=\"data row11 col2\">\n",
" \n",
" -0.86\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col3\" class=\"data row11 col3\">\n",
" \n",
" -1.56\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col4\" class=\"data row11 col4\">\n",
" \n",
" 0.73\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col5\" class=\"data row11 col5\">\n",
" \n",
" 0.44\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col6\" class=\"data row11 col6\">\n",
" \n",
" 1.34\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col7\" class=\"data row11 col7\">\n",
" \n",
" 0.63\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col8\" class=\"data row11 col8\">\n",
" \n",
" 1.75\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col9\" class=\"data row11 col9\">\n",
" \n",
" -1.28\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow11_col10\" class=\"data row11 col10\">\n",
" \n",
" -0.57\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row12\">\n",
" \n",
" 12\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col0\" class=\"data row12 col0\">\n",
" \n",
" 0.22\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col1\" class=\"data row12 col1\">\n",
" \n",
" 0.66\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col2\" class=\"data row12 col2\">\n",
" \n",
" -1.88\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col3\" class=\"data row12 col3\">\n",
" \n",
" 1.52\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col4\" class=\"data row12 col4\">\n",
" \n",
" 0.95\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col5\" class=\"data row12 col5\">\n",
" \n",
" -0.21\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col6\" class=\"data row12 col6\">\n",
" \n",
" -0.07\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col7\" class=\"data row12 col7\">\n",
" \n",
" -1.16\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col8\" class=\"data row12 col8\">\n",
" \n",
" 1.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col9\" class=\"data row12 col9\">\n",
" \n",
" -0.07\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow12_col10\" class=\"data row12 col10\">\n",
" \n",
" -0.76\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row13\">\n",
" \n",
" 13\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col0\" class=\"data row13 col0\">\n",
" \n",
" 0.69\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col1\" class=\"data row13 col1\">\n",
" \n",
" -1.61\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col2\" class=\"data row13 col2\">\n",
" \n",
" 0.27\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col3\" class=\"data row13 col3\">\n",
" \n",
" 0.18\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col4\" class=\"data row13 col4\">\n",
" \n",
" 0.91\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col5\" class=\"data row13 col5\">\n",
" \n",
" 0.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col6\" class=\"data row13 col6\">\n",
" \n",
" -0.37\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col7\" class=\"data row13 col7\">\n",
" \n",
" -0.11\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col8\" class=\"data row13 col8\">\n",
" \n",
" 1.27\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col9\" class=\"data row13 col9\">\n",
" \n",
" -0.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow13_col10\" class=\"data row13 col10\">\n",
" \n",
" 0.28\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row14\">\n",
" \n",
" 14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col0\" class=\"data row14 col0\">\n",
" \n",
" -2.87\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col1\" class=\"data row14 col1\">\n",
" \n",
" 0.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col2\" class=\"data row14 col2\">\n",
" \n",
" 0.54\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col3\" class=\"data row14 col3\">\n",
" \n",
" -1.07\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col4\" class=\"data row14 col4\">\n",
" \n",
" 0.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col5\" class=\"data row14 col5\">\n",
" \n",
" -0.41\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col6\" class=\"data row14 col6\">\n",
" \n",
" -1.44\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col7\" class=\"data row14 col7\">\n",
" \n",
" -0.8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col8\" class=\"data row14 col8\">\n",
" \n",
" 2.45\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col9\" class=\"data row14 col9\">\n",
" \n",
" -0.87\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow14_col10\" class=\"data row14 col10\">\n",
" \n",
" -1.29\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row15\">\n",
" \n",
" 15\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col0\" class=\"data row15 col0\">\n",
" \n",
" 0.02\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col1\" class=\"data row15 col1\">\n",
" \n",
" -1.39\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col2\" class=\"data row15 col2\">\n",
" \n",
" 0.64\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col3\" class=\"data row15 col3\">\n",
" \n",
" 0.6\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col4\" class=\"data row15 col4\">\n",
" \n",
" -0.56\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col5\" class=\"data row15 col5\">\n",
" \n",
" -0.75\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col6\" class=\"data row15 col6\">\n",
" \n",
" 0.56\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col7\" class=\"data row15 col7\">\n",
" \n",
" 0.35\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col8\" class=\"data row15 col8\">\n",
" \n",
" -0.07\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col9\" class=\"data row15 col9\">\n",
" \n",
" -0.49\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow15_col10\" class=\"data row15 col10\">\n",
" \n",
" -0.37\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row16\">\n",
" \n",
" 16\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col0\" class=\"data row16 col0\">\n",
" \n",
" -1.86\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col1\" class=\"data row16 col1\">\n",
" \n",
" 0.88\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col2\" class=\"data row16 col2\">\n",
" \n",
" 1.89\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col3\" class=\"data row16 col3\">\n",
" \n",
" -0.57\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col4\" class=\"data row16 col4\">\n",
" \n",
" -0.67\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col5\" class=\"data row16 col5\">\n",
" \n",
" -0.66\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col6\" class=\"data row16 col6\">\n",
" \n",
" 0.73\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col7\" class=\"data row16 col7\">\n",
" \n",
" 1.14\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col8\" class=\"data row16 col8\">\n",
" \n",
" -0.27\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col9\" class=\"data row16 col9\">\n",
" \n",
" -1.4\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow16_col10\" class=\"data row16 col10\">\n",
" \n",
" 0.31\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row17\">\n",
" \n",
" 17\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col0\" class=\"data row17 col0\">\n",
" \n",
" -0.27\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col1\" class=\"data row17 col1\">\n",
" \n",
" -0.36\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col2\" class=\"data row17 col2\">\n",
" \n",
" 0.02\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col3\" class=\"data row17 col3\">\n",
" \n",
" 1.26\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col4\" class=\"data row17 col4\">\n",
" \n",
" 0.16\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col5\" class=\"data row17 col5\">\n",
" \n",
" -0.47\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col6\" class=\"data row17 col6\">\n",
" \n",
" -0.07\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col7\" class=\"data row17 col7\">\n",
" \n",
" -0.05\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col8\" class=\"data row17 col8\">\n",
" \n",
" -0.51\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col9\" class=\"data row17 col9\">\n",
" \n",
" -0.21\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow17_col10\" class=\"data row17 col10\">\n",
" \n",
" 0.71\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row18\">\n",
" \n",
" 18\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col0\" class=\"data row18 col0\">\n",
" \n",
" 0.35\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col1\" class=\"data row18 col1\">\n",
" \n",
" 1.48\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col2\" class=\"data row18 col2\">\n",
" \n",
" -0.86\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col3\" class=\"data row18 col3\">\n",
" \n",
" -1.15\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col4\" class=\"data row18 col4\">\n",
" \n",
" -0.37\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col5\" class=\"data row18 col5\">\n",
" \n",
" -0.79\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col6\" class=\"data row18 col6\">\n",
" \n",
" 2.04\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col7\" class=\"data row18 col7\">\n",
" \n",
" -0.96\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col8\" class=\"data row18 col8\">\n",
" \n",
" -1.8\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col9\" class=\"data row18 col9\">\n",
" \n",
" 1.56\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow18_col10\" class=\"data row18 col10\">\n",
" \n",
" -0.92\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" <tr>\n",
" \n",
" <th id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fb\" class=\"row_heading level10 row19\">\n",
" \n",
" 19\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col0\" class=\"data row19 col0\">\n",
" \n",
" 1.38\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col1\" class=\"data row19 col1\">\n",
" \n",
" 0.97\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col2\" class=\"data row19 col2\">\n",
" \n",
" -0.79\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col3\" class=\"data row19 col3\">\n",
" \n",
" -1.57\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col4\" class=\"data row19 col4\">\n",
" \n",
" 0.05\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col5\" class=\"data row19 col5\">\n",
" \n",
" -0.37\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col6\" class=\"data row19 col6\">\n",
" \n",
" -0.26\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col7\" class=\"data row19 col7\">\n",
" \n",
" -0.4\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col8\" class=\"data row19 col8\">\n",
" \n",
" -0.83\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col9\" class=\"data row19 col9\">\n",
" \n",
" -1.08\n",
" \n",
" </th>\n",
" \n",
" <td id=\"T_b0a954f0_81d9_11e5_8878_a45e60bd97fbrow19_col10\" class=\"data row19 col10\">\n",
" \n",
" -0.06\n",
" \n",
" </th>\n",
" \n",
" </tr>\n",
" \n",
" </tbody>\n",
" </table>\n",
" "
],
"text/plain": [
"<pandas.core.style.Styler at 0x1158670f0>"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def panda(df):\n",
" spots = [\n",
" # left ear\n",
" (0, 0), (1, 0), (0, 1),\n",
" # right ear\n",
" (0, 10), (1, 10), (0, 9),\n",
" # left eye\n",
" (5, 2), (4, 3), (5, 3),\n",
" # right eye\n",
" (5, 7), (4, 7), (5, 8),\n",
" # nose\n",
" (10, 4), (10, 5), (10, 6), (11, 5),\n",
" (15, 5), (16, 5), (17, 5), (17, 4), (17, 6), (17, 3), (17, 7), (16, 2), (16, 8)\n",
" ]\n",
"\n",
" rows = []\n",
" for r in df.index:\n",
" cols = []\n",
" for c in df.columns:\n",
" if (r, c) in spots:\n",
" cols.append(\"background-color: black; color: white\")\n",
" else:\n",
" cols.append(\"background-color: white; color: black\")\n",
" rows.append(cols)\n",
"\n",
" return pd.DataFrame(rows)\n",
"\n",
"df = pd.DataFrame(np.random.randn(20, 11))\n",
"s = df.round(2).style\n",
"s.update_ctx(panda(df))\n",
"s"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Subclassing\n",
"\n",
"Unlike most objects that pandas exposes, `Styler` should be designed with subclassing in mind. There's no particular reason why CSS should be used over other backend, other than it's convinient for users of Notebooks, and relatively straightforward compared to, say, $\\LaTeX$. I've laid out a bit of the internal implementation here.\n",
"\n",
"As users apply styles (via `.apply`, `.applymap` and `.tee`), we modify an internal dict, `self.ctx`. This maps `(row_position, col_position)` to a list of (for CSS) `'attribute: value:` strings. Given this `ctx`, the rendering roughly consists of two steps\n",
"\n",
"- `translate` to a dictionary ready to be passed into the template `Styler.t`\n",
"- render template with the dictionary from `Styler.translate`\n",
"\n",
"This is done in `Styler.render`, but most of the heavy lifitng is done in `translate`.\n",
"\n",
"\n",
"## Alternate templates\n",
"\n",
"We've used [Jinja](http://jinja.pocoo.org/) templates to build up the HTML.\n",
"The template is stored as a class variable on `Styler` (called `Styler.t` for now) Subclasses can override that.\n",
"\n",
"```python\n",
"class CustomStyle(Styler):\n",
" t = Template(\"\"\"...\"\"\")\n",
"```"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.4.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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