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January 18, 2019 22:07
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| { | |
| "nbformat_minor": 1, | |
| "cells": [ | |
| { | |
| "execution_count": 1, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": "Requirement not upgraded as not directly required: xlrd in /opt/conda/envs/DSX-Python35/lib/python3.5/site-packages\r\n" | |
| } | |
| ], | |
| "source": "# Dependency needed to install file \n\n!pip install xlrd" | |
| }, | |
| { | |
| "execution_count": 2, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": "# Import required library\n\nimport pandas as pd" | |
| }, | |
| { | |
| "execution_count": 3, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": "# Read data from CSV file\n\ncsv_path = 'https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/Chapter%204/Datasets/TopSellingAlbums.csv'\ndf = pd.read_csv(csv_path)" | |
| }, | |
| { | |
| "execution_count": 4, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\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.1</th>\n <th>Soundtrack</th>\n <th>Rating</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Michael Jackson</td>\n <td>Thriller</td>\n <td>1982</td>\n <td>0:42:19</td>\n <td>pop, rock, R&B</td>\n <td>46.0</td>\n <td>65</td>\n <td>30-Nov-82</td>\n <td>NaN</td>\n <td>10.0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>AC/DC</td>\n <td>Back in Black</td>\n <td>1980</td>\n <td>0:42:11</td>\n <td>hard rock</td>\n <td>26.1</td>\n <td>50</td>\n <td>25-Jul-80</td>\n <td>NaN</td>\n <td>9.5</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Pink Floyd</td>\n <td>The Dark Side of the Moon</td>\n <td>1973</td>\n <td>0:42:49</td>\n <td>progressive rock</td>\n <td>24.2</td>\n <td>45</td>\n <td>01-Mar-73</td>\n <td>NaN</td>\n <td>9.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Whitney Houston</td>\n <td>The Bodyguard</td>\n <td>1992</td>\n <td>0:57:44</td>\n <td>R&B, soul, pop</td>\n <td>27.4</td>\n <td>44</td>\n <td>17-Nov-92</td>\n <td>Y</td>\n <td>8.5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Meat Loaf</td>\n <td>Bat Out of Hell</td>\n <td>1977</td>\n <td>0:46:33</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>NaN</td>\n <td>8.0</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Artist Album Released Length \\\n0 Michael Jackson Thriller 1982 0:42:19 \n1 AC/DC Back in Black 1980 0:42:11 \n2 Pink Floyd The Dark Side of the Moon 1973 0:42:49 \n3 Whitney Houston The Bodyguard 1992 0:57:44 \n4 Meat Loaf Bat Out of Hell 1977 0:46:33 \n\n Genre Music Recording Sales (millions) \\\n0 pop, rock, R&B 46.0 \n1 hard rock 26.1 \n2 progressive rock 24.2 \n3 R&B, soul, pop 27.4 \n4 hard rock, progressive rock 20.6 \n\n Claimed Sales (millions) Released.1 Soundtrack Rating \n0 65 30-Nov-82 NaN 10.0 \n1 50 25-Jul-80 NaN 9.5 \n2 45 01-Mar-73 NaN 9.0 \n3 44 17-Nov-92 Y 8.5 \n4 43 21-Oct-77 NaN 8.0 " | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Print first five rows of the dataframe\n\ndf.head()" | |
| }, | |
| { | |
| "execution_count": 5, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\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.1</th>\n <th>Soundtrack</th>\n <th>Rating</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\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>46.0</td>\n <td>65</td>\n <td>1982-11-30</td>\n <td>NaN</td>\n <td>10.0</td>\n </tr>\n <tr>\n <th>1</th>\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>1980-07-25</td>\n <td>NaN</td>\n <td>9.5</td>\n </tr>\n <tr>\n <th>2</th>\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>1973-03-01</td>\n <td>NaN</td>\n <td>9.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Whitney Houston</td>\n <td>The Bodyguard</td>\n <td>1992</td>\n <td>00:57:44</td>\n <td>R&B, soul, pop</td>\n <td>27.4</td>\n <td>44</td>\n <td>1992-11-17</td>\n <td>Y</td>\n <td>8.5</td>\n </tr>\n <tr>\n <th>4</th>\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>1977-10-21</td>\n <td>NaN</td>\n <td>8.0</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Artist Album Released Length \\\n0 Michael Jackson Thriller 1982 00:42:19 \n1 AC/DC Back in Black 1980 00:42:11 \n2 Pink Floyd The Dark Side of the Moon 1973 00:42:49 \n3 Whitney Houston The Bodyguard 1992 00:57:44 \n4 Meat Loaf Bat Out of Hell 1977 00:46:33 \n\n Genre Music Recording Sales (millions) \\\n0 pop, rock, R&B 46.0 \n1 hard rock 26.1 \n2 progressive rock 24.2 \n3 R&B, soul, pop 27.4 \n4 hard rock, progressive rock 20.6 \n\n Claimed Sales (millions) Released.1 Soundtrack Rating \n0 65 1982-11-30 NaN 10.0 \n1 50 1980-07-25 NaN 9.5 \n2 45 1973-03-01 NaN 9.0 \n3 44 1992-11-17 Y 8.5 \n4 43 1977-10-21 NaN 8.0 " | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Read data from Excel File and print the first five rows\n\nxlsx_path = 'https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/Chapter%204/Datasets/TopSellingAlbums.xlsx'\n\ndf = pd.read_excel(xlsx_path)\ndf.head()" | |
| }, | |
| { | |
| "execution_count": 6, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Length</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>00:42:19</td>\n </tr>\n <tr>\n <th>1</th>\n <td>00:42:11</td>\n </tr>\n <tr>\n <th>2</th>\n <td>00:42:49</td>\n </tr>\n <tr>\n <th>3</th>\n <td>00:57:44</td>\n </tr>\n <tr>\n <th>4</th>\n <td>00:46:33</td>\n </tr>\n <tr>\n <th>5</th>\n <td>00:43:08</td>\n </tr>\n <tr>\n <th>6</th>\n <td>01:15:54</td>\n </tr>\n <tr>\n <th>7</th>\n <td>00:40:01</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Length\n0 00:42:19\n1 00:42:11\n2 00:42:49\n3 00:57:44\n4 00:46:33\n5 00:43:08\n6 01:15:54\n7 00:40:01" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Access to the column Length\n\nx = df[['Length']]\nx" | |
| }, | |
| { | |
| "execution_count": 7, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 7, | |
| "metadata": {}, | |
| "data": { | |
| "text/plain": "0 00:42:19\n1 00:42:11\n2 00:42:49\n3 00:57:44\n4 00:46:33\n5 00:43:08\n6 01:15:54\n7 00:40:01\nName: Length, dtype: object" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Get the column as a series\n\nx = df['Length']\nx" | |
| }, | |
| { | |
| "execution_count": 9, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "data": { | |
| "text/plain": "pandas.core.frame.DataFrame" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Get the column as a dataframe\n\nx = type(df[['Artist']])\nx" | |
| }, | |
| { | |
| "execution_count": 10, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Artist</th>\n <th>Length</th>\n <th>Genre</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Michael Jackson</td>\n <td>00:42:19</td>\n <td>pop, rock, R&B</td>\n </tr>\n <tr>\n <th>1</th>\n <td>AC/DC</td>\n <td>00:42:11</td>\n <td>hard rock</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Pink Floyd</td>\n <td>00:42:49</td>\n <td>progressive rock</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Whitney Houston</td>\n <td>00:57:44</td>\n <td>R&B, soul, pop</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Meat Loaf</td>\n <td>00:46:33</td>\n <td>hard rock, progressive rock</td>\n </tr>\n <tr>\n <th>5</th>\n <td>Eagles</td>\n <td>00:43:08</td>\n <td>rock, soft rock, folk rock</td>\n </tr>\n <tr>\n <th>6</th>\n <td>Bee Gees</td>\n <td>01:15:54</td>\n <td>disco</td>\n </tr>\n <tr>\n <th>7</th>\n <td>Fleetwood Mac</td>\n <td>00:40:01</td>\n <td>soft rock</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Artist Length Genre\n0 Michael Jackson 00:42:19 pop, rock, R&B\n1 AC/DC 00:42:11 hard rock\n2 Pink Floyd 00:42:49 progressive rock\n3 Whitney Houston 00:57:44 R&B, soul, pop\n4 Meat Loaf 00:46:33 hard rock, progressive rock\n5 Eagles 00:43:08 rock, soft rock, folk rock\n6 Bee Gees 01:15:54 disco\n7 Fleetwood Mac 00:40:01 soft rock" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Access to multiple columns\n\ny = df[['Artist','Length','Genre']]\ny" | |
| }, | |
| { | |
| "execution_count": 12, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 12, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Album</th>\n <th>Released</th>\n <th>Length</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Thriller</td>\n <td>1982</td>\n <td>00:42:19</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Back in Black</td>\n <td>1980</td>\n <td>00:42:11</td>\n </tr>\n <tr>\n <th>2</th>\n <td>The Dark Side of the Moon</td>\n <td>1973</td>\n <td>00:42:49</td>\n </tr>\n <tr>\n <th>3</th>\n <td>The Bodyguard</td>\n <td>1992</td>\n <td>00:57:44</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Bat Out of Hell</td>\n <td>1977</td>\n <td>00:46:33</td>\n </tr>\n <tr>\n <th>5</th>\n <td>Their Greatest Hits (1971-1975)</td>\n <td>1976</td>\n <td>00:43:08</td>\n </tr>\n <tr>\n <th>6</th>\n <td>Saturday Night Fever</td>\n <td>1977</td>\n <td>01:15:54</td>\n </tr>\n <tr>\n <th>7</th>\n <td>Rumours</td>\n <td>1977</td>\n <td>00:40:01</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Album Released Length\n0 Thriller 1982 00:42:19\n1 Back in Black 1980 00:42:11\n2 The Dark Side of the Moon 1973 00:42:49\n3 The Bodyguard 1992 00:57:44\n4 Bat Out of Hell 1977 00:46:33\n5 Their Greatest Hits (1971-1975) 1976 00:43:08\n6 Saturday Night Fever 1977 01:15:54\n7 Rumours 1977 00:40:01" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "z= df[['Album','Released','Length']]\nz" | |
| }, | |
| { | |
| "execution_count": 13, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 13, | |
| "metadata": {}, | |
| "data": { | |
| "text/plain": "'Michael Jackson'" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Access the value on the first row and the first column\n\ndf.iloc[0, 0]" | |
| }, | |
| { | |
| "execution_count": 14, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 14, | |
| "metadata": {}, | |
| "data": { | |
| "text/plain": "'AC/DC'" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Access the value on the second row and the first column\n\ndf.iloc[1,0]" | |
| }, | |
| { | |
| "execution_count": 15, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 15, | |
| "metadata": {}, | |
| "data": { | |
| "text/plain": "'Michael Jackson'" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Access the column using the name\n\ndf.loc[0, 'Artist']" | |
| }, | |
| { | |
| "execution_count": 16, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 16, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Artist</th>\n <th>Album</th>\n <th>Released</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Michael Jackson</td>\n <td>Thriller</td>\n <td>1982</td>\n </tr>\n <tr>\n <th>1</th>\n <td>AC/DC</td>\n <td>Back in Black</td>\n <td>1980</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Artist Album Released\n0 Michael Jackson Thriller 1982\n1 AC/DC Back in Black 1980" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Slicing the dataframe\n\ndf.iloc[0:2, 0:3]" | |
| }, | |
| { | |
| "execution_count": 17, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 17, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Artist</th>\n <th>Album</th>\n <th>Released</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Michael Jackson</td>\n <td>Thriller</td>\n <td>1982</td>\n </tr>\n <tr>\n <th>1</th>\n <td>AC/DC</td>\n <td>Back in Black</td>\n <td>1980</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Pink Floyd</td>\n <td>The Dark Side of the Moon</td>\n <td>1973</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Artist Album Released\n0 Michael Jackson Thriller 1982\n1 AC/DC Back in Black 1980\n2 Pink Floyd The Dark Side of the Moon 1973" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "# Slicing the dataframe using name\n\ndf.loc[0:2, 'Artist':'Released']" | |
| }, | |
| { | |
| "execution_count": 19, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 19, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Rating</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>10.0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>9.5</td>\n </tr>\n <tr>\n <th>2</th>\n <td>9.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>8.5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>8.0</td>\n </tr>\n <tr>\n <th>5</th>\n <td>7.5</td>\n </tr>\n <tr>\n <th>6</th>\n <td>7.0</td>\n </tr>\n <tr>\n <th>7</th>\n <td>6.5</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Rating\n0 10.0\n1 9.5\n2 9.0\n3 8.5\n4 8.0\n5 7.5\n6 7.0\n7 6.5" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "#Use a variable q to store the column Rating as a dataframe\n\nq=df[['Rating']]\nq" | |
| }, | |
| { | |
| "execution_count": 20, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 20, | |
| "metadata": {}, | |
| "data": { | |
| "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Released</th>\n <th>Artist</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1982</td>\n <td>Michael Jackson</td>\n </tr>\n <tr>\n <th>1</th>\n <td>1980</td>\n <td>AC/DC</td>\n </tr>\n <tr>\n <th>2</th>\n <td>1973</td>\n <td>Pink Floyd</td>\n </tr>\n <tr>\n <th>3</th>\n <td>1992</td>\n <td>Whitney Houston</td>\n </tr>\n <tr>\n <th>4</th>\n <td>1977</td>\n <td>Meat Loaf</td>\n </tr>\n <tr>\n <th>5</th>\n <td>1976</td>\n <td>Eagles</td>\n </tr>\n <tr>\n <th>6</th>\n <td>1977</td>\n <td>Bee Gees</td>\n </tr>\n <tr>\n <th>7</th>\n <td>1977</td>\n <td>Fleetwood Mac</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
| "text/plain": " Released Artist\n0 1982 Michael Jackson\n1 1980 AC/DC\n2 1973 Pink Floyd\n3 1992 Whitney Houston\n4 1977 Meat Loaf\n5 1976 Eagles\n6 1977 Bee Gees\n7 1977 Fleetwood Mac" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "#Assign the variable q to the dataframe that is made up of the column Released and Artist:\n\nq=df[['Released','Artist']]\nq" | |
| }, | |
| { | |
| "execution_count": 21, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "execution_count": 21, | |
| "metadata": {}, | |
| "data": { | |
| "text/plain": "1980" | |
| }, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": "#Access the 2nd row and the 3rd column of df:\n\ndf.iloc[1,2]" | |
| }, | |
| { | |
| "execution_count": null, | |
| "cell_type": "code", | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": "" | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 3.5", | |
| "name": "python3", | |
| "language": "python" | |
| }, | |
| "language_info": { | |
| "mimetype": "text/x-python", | |
| "nbconvert_exporter": "python", | |
| "version": "3.5.5", | |
| "name": "python", | |
| "file_extension": ".py", | |
| "pygments_lexer": "ipython3", | |
| "codemirror_mode": { | |
| "version": 3, | |
| "name": "ipython" | |
| } | |
| } | |
| }, | |
| "nbformat": 4 | |
| } |
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