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November 21, 2019 04:04
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"<h3> Get to Know a Pandas Array </h3>" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"You will use the dataframe <code>df</code> for the following:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
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"<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>a</th>\n", | |
" <th>b</th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>0</th>\n", | |
" <td>1</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>1</th>\n", | |
" <td>2</td>\n", | |
" <td>1</td>\n", | |
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" <tr>\n", | |
" <th>2</th>\n", | |
" <td>1</td>\n", | |
" <td>1</td>\n", | |
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"text/plain": [ | |
" a b\n", | |
"0 1 1\n", | |
"1 2 1\n", | |
"2 1 1" | |
] | |
}, | |
"execution_count": 2, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"import pandas as pd\n", | |
"\n", | |
"df=pd.DataFrame({'a':[1,2,1],'b':[1,1,1]})\n", | |
"df\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"1) find the unique values in column <code> 'a' </code>:" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([1, 2])" | |
] | |
}, | |
"execution_count": 5, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"df['a'].unique()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"2) return a dataframe with only the rows where column <code> a </code> is less than two " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": { | |
"collapsed": false, | |
"jupyter": { | |
"outputs_hidden": false | |
} | |
}, | |
"outputs": [], | |
"source": [ | |
"df1=df[df['a']<=1]\n", | |
"df1\n", | |
"df1=df['a']\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"<hr>\n", | |
"<small>Copyright © 2018 IBM Cognitive Class. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license/).</small>" | |
] | |
} | |
], | |
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"display_name": "Python", | |
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"version": "3.6.7" | |
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