Skip to content

Instantly share code, notes, and snippets.

@emilfh

emilfh/2.2_Lists.ipynb

Created January 4, 2021 17:41
Show Gist options
  • Save emilfh/e64d753f71bf97f2f8ef903715e2853f to your computer and use it in GitHub Desktop.
Save emilfh/e64d753f71bf97f2f8ef903715e2853f to your computer and use it in GitHub Desktop.
Download ZIP
Created on Skills Network Labs
Display the source blob
Display the rendered blob
Raw
2.2_Lists.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a href=\"http://cocl.us/topNotebooksPython101Coursera\"><img src = \"https://ibm.box.com/shared/static/yfe6h4az47ktg2mm9h05wby2n7e8kei3.png\" width = 750, align = \"center\"></a>\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a href=\"https://www.bigdatauniversity.com\"><img src = \"https://ibm.box.com/shared/static/ugcqz6ohbvff804xp84y4kqnvvk3bq1g.png\" width = 300, align = \"center\"></a>\n",
"\n",
"\n",
"\n",
"\n",
"<h1 align=center><font size = 5>LISTS IN PYTHON</font></h1>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"## Table of Contents\n",
"\n",
"\n",
"<div class=\"alert alert-block alert-info\" style=\"margin-top: 20px\">\n",
"<li><a href=\"#ref0\">About the Dataset</a></li>\n",
"<li><a href=\"#ref1\">Lists</a></li>\n",
"<li><a href=\"#ref2\">Quiz</a></li>\n",
"<br>\n",
"<p></p>\n",
"Estimated Time Needed: <strong>15 min</strong>\n",
"</div>\n",
"\n",
"<hr>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<a id=\"ref0\"></a>\n",
"<center><h2>About the Dataset</h2></center>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Imagine you received many music recommendations from your friends and compiled all of the recommendations into a table, with specific information about each movie.\n",
"\n",
"The table has one row for each album and several columns:\n",
"\n",
"- **artist** - Name of the artist\n",
"- **album** - Name of the album\n",
"- **released_year** - Year the album was released\n",
"- **length_min_sec** - Length of the album (hours,minutes,seconds)\n",
"- **genre** - Genre of the album\n",
"- **music_recording_sales_millions** - Music recording sales (millions in USD) on [SONG://DATABASE](http://www.song-database.com/)\n",
"- **claimed_sales_millions** - Album's claimed sales (millions in USD) on [SONG://DATABASE](http://www.song-database.com/)\n",
"- **date_released** - Date on which the album was released\n",
"- **soundtrack** - Indicates if the album is the movie soundtrack (Y) or (N)\n",
"- **rating_of_friends** - Indicates the rating from your friends from 1 to 10\n",
"<br>\n",
"<br>\n",
"\n",
"The dataset can be seen below:\n",
"\n",
"<font size=\"1\">\n",
"<table font-size:xx-small style=\"width:25%\">\n",
" <tr>\n",
" <th>Artist</th>\n",
" <th>Album</th> \n",
" <th>Released</th>\n",
" <th>Length</th>\n",
" <th>Genre</th> \n",
" <th>Music recording sales (millions)</th>\n",
" <th>Claimed sales (millions)</th>\n",
" <th>Released</th>\n",
" <th>Soundtrack</th>\n",
" <th>Rating (friends)</th>\n",
" </tr>\n",
" <tr>\n",
" <td>Michael Jackson</td>\n",
" <td>Thriller</td> \n",
" <td>1982</td>\n",
" <td>00:42:19</td>\n",
" <td>Pop, rock, R&B</td>\n",
" <td>46</td>\n",
" <td>65</td>\n",
" <td>30-Nov-82</td>\n",
" <td></td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>AC/DC</td>\n",
" <td>Back in Black</td> \n",
" <td>1980</td>\n",
" <td>00:42:11</td>\n",
" <td>Hard rock</td>\n",
" <td>26.1</td>\n",
" <td>50</td>\n",
" <td>25-Jul-80</td>\n",
" <td></td>\n",
" <td>8.5</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Pink Floyd</td>\n",
" <td>The Dark Side of the Moon</td> \n",
" <td>1973</td>\n",
" <td>00:42:49</td>\n",
" <td>Progressive rock</td>\n",
" <td>24.2</td>\n",
" <td>45</td>\n",
" <td>01-Mar-73</td>\n",
" <td></td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Whitney Houston</td>\n",
" <td>The Bodyguard</td> \n",
" <td>1992</td>\n",
" <td>00:57:44</td>\n",
" <td>Soundtrack/R&B, soul, pop</td>\n",
" <td>26.1</td>\n",
" <td>50</td>\n",
" <td>25-Jul-80</td>\n",
" <td>Y</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Meat Loaf</td>\n",
" <td>Bat Out of Hell</td> \n",
" <td>1977</td>\n",
" <td>00:46:33</td>\n",
" <td>Hard rock, progressive rock</td>\n",
" <td>20.6</td>\n",
" <td>43</td>\n",
" <td>21-Oct-77</td>\n",
" <td></td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Eagles</td>\n",
" <td>Their Greatest Hits (1971-1975)</td> \n",
" <td>1976</td>\n",
" <td>00:43:08</td>\n",
" <td>Rock, soft rock, folk rock</td>\n",
" <td>32.2</td>\n",
" <td>42</td>\n",
" <td>17-Feb-76</td>\n",
" <td></td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Bee Gees</td>\n",
" <td>Saturday Night Fever</td> \n",
" <td>1977</td>\n",
" <td>1:15:54</td>\n",
" <td>Disco</td>\n",
" <td>20.6</td>\n",
" <td>40</td>\n",
" <td>15-Nov-77</td>\n",
" <td>Y</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Fleetwood Mac</td>\n",
" <td>Rumours</td> \n",
" <td>1977</td>\n",
" <td>00:40:01</td>\n",
" <td>Soft rock</td>\n",
" <td>27.9</td>\n",
" <td>40</td>\n",
" <td>04-Feb-77</td>\n",
" <td></td>\n",
" <td>9.5</td>\n",
" </tr>\n",
"</table></font>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<hr>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<a id=\"ref1\"></a>\n",
"<center><h2>Lists</h2></center>\n",
"\n",
"We are going to take a look at lists in Python. A list is a sequenced collection of different objects such as integers, strings, and other lists as well. The address of each element within a list is called an 'index'. An index is used to access and refer to items within a list.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<a ><img src = \"https://ibm.box.com/shared/static/eln445fv5nzv3wlm4u8dnfhbrcrv0hff.png\" width = 1000, align = \"center\"></a>\n",
" <h4 align=center> Representation of a list \n",
" </h4> \n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" To create a list, type the list within square brackets **[ ]**, with your content inside the parenthesis and separated by commas. Let’s try it!"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.1, 1982]"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L=[\"Michael Jackson\" , 10.1,1982]\n",
"L"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can use negative and regular indexing with a list :"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a ><img src = \"https://ibm.box.com/shared/static/a7ac9lnvmcaz29n86ffez4as27fl3n9m.png\" width = 1000, align = \"center\"></a>\n",
" <h4 align=center> Representation of a list \n",
" </h4> \n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"the same element using negative and positive indexing:\n",
" Postive: Michael Jackson \n",
" Negative: Michael Jackson\n",
"the same element using negative and positive indexing:\n",
" Postive: 10.1 \n",
" Negative: 10.1\n",
"the same element using negative and positive indexing:\n",
" Postive: 1982 \n",
" Negative: 1982\n"
]
}
],
"source": [
"print('the same element using negative and positive indexing:\\n Postive:',L[0],\n",
"'\\n Negative:' , L[-3] )\n",
"print('the same element using negative and positive indexing:\\n Postive:',L[1],\n",
"'\\n Negative:' , L[-2] )\n",
"print('the same element using negative and positive indexing:\\n Postive:',L[2],\n",
"'\\n Negative:' , L[-1] )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Lists can contain strings, floats, and integers. We can nest other lists, and we can also nest tuples and other data structures. The same indexing conventions apply for nesting: \n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.1, 1982, [1, 2], ('A', 1)]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[ \"Michael Jackson\", 10.1,1982,[1,2],(\"A\",1) ]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" We can also perform slicing in lists. For example, if we want the last two elements, we use the following command:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.1, 1982, 'MJ', 1]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L=[ \"Michael Jackson\", 10.1,1982,\"MJ\",1]\n",
"L"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"<a ><img src = \"https://ibm.box.com/shared/static/pt3pfp1sg5okwuwwpy0dnj8e94fl2mwy.png\" width = 1000, align = \"center\"></a>\n",
" <h4 align=center> Representation of a list \n",
" </h4> "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['MJ', 1]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L[3:5]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can use the method \"extend\" to add new elements to the list:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.2, 'pop', 10]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L=[ \"Michael Jackson\", 10.2]\n",
"L.extend(['pop',10])\n",
"L"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another similar method is 'appended'. If we apply 'appended' instead of 'extended', we add one element to the list:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.2, ['pop', 10]]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L=[ \"Michael Jackson\", 10.2]\n",
"L.append(['pop',10])\n",
"L"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" Each time we apply a method, the list changes. If we apply \"extend\" we add two new elements to the list. The list **L** is then modified by adding two new elements:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.2, 'pop', 10]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L=[ \"Michael Jackson\", 10.2]\n",
"L.extend(['pop',10])\n",
"L"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we append the list **['a','b']** we have one new element consisting of a nested list:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['Michael Jackson', 10.2, 'pop', 10, ['a', 'b']]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"L.append(['a','b'])\n",
"L"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As lists are mutable, we can change them. For example, we can change the first element as follows:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Before change: ['disco', 10, 1.2]\n",
"After change: ['hard rock', 10, 1.2]\n"
]
}
],
"source": [
"A=[\"disco\",10,1.2]\n",
"print('Before change:', A)\n",
"A[0]='hard rock'\n",
"print('After change:', A)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" We can also delete an element of a list using the **del** command:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Before change: ['hard rock', 10, 1.2]\n",
"After change: [10, 1.2]\n"
]
}
],
"source": [
"print('Before change:', A)\n",
"del(A[0])\n",
"print('After change:', A)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" We can convert a string to a list using 'split'. For example, the method **split** translates every group of characters separated by a space into an element in a list:\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['hard', 'rock']"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'hard rock'.split()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can use the split function to separate strings on a specific character. We pass the character we would like to split on into the argument, which in this case is a comma. The result is a list, and each element corresponds to a set of characters that have been separated by a comma: "
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['A', 'B', 'C', 'D']"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'A,B,C,D'.split(',')\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" When we set one variable **B** equal to **A**; both **A** and **B** are referencing the same list in memory :"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A: ['hard rock', 10, 1.2]\n",
"B: ['hard rock', 10, 1.2]\n"
]
}
],
"source": [
"A=[\"hard rock\",10,1.2]\n",
"B=A\n",
"print('A:',A)\n",
"print('B:',B)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a ><img src = 'https://ibm.box.com/shared/static/7g2u8hqqb4birdwn7m9uir4s9wfj8mko.png' width = 1000, align = \"center\"></a>\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" Initially, the value of the first element in ** B** is set as hard rock. If we change the first element in **A** to 'banana', we get an unexpected side effect. As **A** and **B ** are referencing the same list, if we change list **A**, then list **B** also changes. If we check the first element of **B** we get banana instead of hard rock:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"B[0]: hard rock\n",
"B[0]: banana\n"
]
}
],
"source": [
"print('B[0]:',B[0])\n",
"A[0]=\"banana\"\n",
"print('B[0]:',B[0])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is demonstrated in the following figure: "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a ><img src = https://ibm.box.com/shared/static/thdu6y5pzh99qpun4tu2fjvj86st0hbu.gif width = 1000, align = \"center\"></a>\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can clone list **A** by using the following syntax:"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['hard rock', 10, 1.2]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"B=A[:]\n",
"B"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" Variable **B** references a new copy or clone of the original list; this is demonstrated in the following figure:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
" <a ><img src = https://ibm.box.com/shared/static/gwx86gaoeizqjvx7xj96cb8i9hn684ei.gif width = 1000, align = \"center\"></a>\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now if you change **A**, **B** will not change: \n"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"B[0]: hard rock\n",
"B[0]: hard rock\n"
]
}
],
"source": [
"print('B[0]:',B[0])\n",
"A[0]=\"banana\"\n",
"print('B[0]:',B[0])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a id=\"ref2\"></a>\n",
"<center><h2>Quiz</h2></center>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Create a list 'a_list' , with the following elements 1, “hello”, [1,2,3 ] and True. "
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[1, 'hello', [1, 2, 3], True]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a_list=[1,\"hello\",[1,2,3],True]\n",
"a_list"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <div align=\"right\">\n",
"<a href=\"#q1\" class=\"btn btn-default\" data-toggle=\"collapse\">Click here for the solution</a>\n",
"</div>\n",
"<div id=\"q1\" class=\"collapse\">\n",
"```\n",
"a_list=[1, 'hello', [1,2,3 ] , True]\n",
"a_list\n",
"\n",
"```\n",
"</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Find the value stored at index 1 of 'a_list'."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"'hello'"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a_list[1]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <div align=\"right\">\n",
"<a href=\"#q2\" class=\"btn btn-default\" data-toggle=\"collapse\">Click here for the solution</a>\n",
"</div>\n",
"<div id=\"q2\" class=\"collapse\">\n",
"```\n",
"a_list[1]\n",
"\n",
"\n",
"```\n",
"</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Retrieve the elements stored at index 1 and 2 of 'a_list'."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['hello', [1, 2, 3]]"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a_list[1:3]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <div align=\"right\">\n",
"<a href=\"#q3\" class=\"btn btn-default\" data-toggle=\"collapse\">Click here for the solution</a>\n",
"</div>\n",
"<div id=\"q3\" class=\"collapse\">\n",
"```\n",
"a_list[1:3]\n",
"\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### 4) Concatenate the following lists A=[1,'a'] abd B=[2,1,'d']:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[1, 'a', 2, 1, 'd']"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"A=[1,'a']\n",
"B=[2,1,'d']\n",
"A+B"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <div align=\"right\">\n",
"<a href=\"#q4\" class=\"btn btn-default\" data-toggle=\"collapse\">Click here for the solution</a>\n",
"</div>\n",
"<div id=\"q4\" class=\"collapse\">\n",
"```\n",
"A=[1,'a'] \n",
"B=[2,1,'d']\n",
"A+B\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <a href=\"http://cocl.us/bottemNotebooksPython101Coursera\"><img src = \"https://ibm.box.com/shared/static/irypdxea2q4th88zu1o1tsd06dya10go.png\" width = 750, align = \"center\"></a>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# About the Authors: \n",
"\n",
" [Joseph Santarcangelo]( https://www.linkedin.com/in/joseph-s-50398b136/) has a PhD in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact \n",
" ]human cognition. Joseph has been working for IBM since he completed his PhD.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" <hr>\n",
"Copyright &copy; 2017 [cognitiveclass.ai](cognitiveclass.ai?utm_source=bducopyrightlink&utm_medium=dswb&utm_campaign=bdu). This notebook and its source code are released under the terms of the [MIT License](https://bigdatauniversity.com/mit-license/).​"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"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": "3.5.2"
},
"widgets": {
"state": {},
"version": "1.1.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment