{
"metadata": {
"name": "phase_function_table"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"reload(pd)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 1,
"text": [
"<module 'pandas' from '/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/pandas-0.11.0.dev_3790f16-py2.7-macosx-10.5-x86_64.egg/pandas/__init__.pyc'>"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.io.parsers.read_csv(\"/Users/maye/data/hirise/inca/grid_by_phase.txt\",skipinitialspace=True, na_values='-NaN')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"some of phase and reflectance values are missing?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 4,
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 1458000 entries, 0 to 1457999\n",
"Data columns:\n",
"incidence 1458000 non-null values\n",
"emission 1458000 non-null values\n",
"phase 1457994 non-null values\n",
"reflectance 1457989 non-null values\n",
"dtypes: float64(2), int64(2)"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df[~df.phase.notnull()] # this searches for phases that are nan values"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>incidence</th>\n",
" <th>emission</th>\n",
" <th>phase</th>\n",
" <th>reflectance</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>81900 </th>\n",
" <td> 5</td>\n",
" <td> 5</td>\n",
" <td>NaN</td>\n",
" <td> 0.278157</td>\n",
" </tr>\n",
" <tr>\n",
" <th>737100 </th>\n",
" <td> 45</td>\n",
" <td> 45</td>\n",
" <td>NaN</td>\n",
" <td> 0.360779</td>\n",
" </tr>\n",
" <tr>\n",
" <th>933660 </th>\n",
" <td> 57</td>\n",
" <td> 57</td>\n",
" <td>NaN</td>\n",
" <td> 0.441665</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1048320</th>\n",
" <td> 64</td>\n",
" <td> 64</td>\n",
" <td>NaN</td>\n",
" <td> 0.522464</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1326780</th>\n",
" <td> 81</td>\n",
" <td> 81</td>\n",
" <td>NaN</td>\n",
" <td> 1.275300</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1375920</th>\n",
" <td> 84</td>\n",
" <td> 84</td>\n",
" <td>NaN</td>\n",
" <td> 1.865133</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 9,
"text": [
" incidence emission phase reflectance\n",
"81900 5 5 NaN 0.278157\n",
"737100 45 45 NaN 0.360779\n",
"933660 57 57 NaN 0.441665\n",
"1048320 64 64 NaN 0.522464\n",
"1326780 81 81 NaN 1.275300\n",
"1375920 84 84 NaN 1.865133"
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df[-df.reflectance.notnull()] # this searches for reflectance values that are nan values"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>incidence</th>\n",
" <th>emission</th>\n",
" <th>phase</th>\n",
" <th>reflectance</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>49140 </th>\n",
" <td> 3</td>\n",
" <td> 3</td>\n",
" <td> 0.000001</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65520 </th>\n",
" <td> 4</td>\n",
" <td> 4</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>114660 </th>\n",
" <td> 7</td>\n",
" <td> 7</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131040 </th>\n",
" <td> 8</td>\n",
" <td> 8</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>163800 </th>\n",
" <td> 10</td>\n",
" <td> 10</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>180180 </th>\n",
" <td> 11</td>\n",
" <td> 11</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>196560 </th>\n",
" <td> 12</td>\n",
" <td> 12</td>\n",
" <td> 0.000001</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1212120</th>\n",
" <td> 74</td>\n",
" <td> 74</td>\n",
" <td> 0.000001</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1359540</th>\n",
" <td> 83</td>\n",
" <td> 83</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1408680</th>\n",
" <td> 86</td>\n",
" <td> 86</td>\n",
" <td> 0.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1425060</th>\n",
" <td> 87</td>\n",
" <td> 87</td>\n",
" <td> 0.000001</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 10,
"text": [
" incidence emission phase reflectance\n",
"49140 3 3 0.000001 NaN\n",
"65520 4 4 0.000000 NaN\n",
"114660 7 7 0.000000 NaN\n",
"131040 8 8 0.000000 NaN\n",
"163800 10 10 0.000000 NaN\n",
"180180 11 11 0.000000 NaN\n",
"196560 12 12 0.000001 NaN\n",
"1212120 74 74 0.000001 NaN\n",
"1359540 83 83 0.000000 NaN\n",
"1408680 86 86 0.000000 NaN\n",
"1425060 87 87 0.000001 NaN"
]
}
],
"prompt_number": 10
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"because the index in the most left column is zero based, the line number would be index+1"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.index"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 12,
"text": [
"Int64Index([0, 1, 2, ..., 1457997, 1457998, 1457999], dtype=int64)"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}