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Merge pull request #8 from gjbex/development
Add examples
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‎python_for_data_science.pptx

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‎source-code/pandas/indexing_and_querying.ipynb

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‎source-code/pandas/missing_values.ipynb

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"cell_type": "markdown",
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"source": [
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"# Missing data"
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"# Requirements"
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"cell_type": "markdown",
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"## Representing missing values"
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"# Representing missing values"
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"max 37.000000 7.700000"
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" <tr>\n",
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" <th>top</th>\n",
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" <td>str1_str1</td>\n",
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" <td>str1</td>\n",
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" category_data string_data\n",
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"source": [
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"# Selecting rows with missing data"
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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"\n",
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" .dataframe tbody tr th {\n",
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"\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>int_data</th>\n",
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" <th>float_data</th>\n",
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" <th>category_data</th>\n",
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" <th>string_data</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>6</th>\n",
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" <td>&lt;NA&gt;</td>\n",
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" <td>5.5</td>\n",
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" <td>A</td>\n",
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" <td>str3</td>\n",
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" </tr>\n",
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"</table>\n",
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],
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" int_data float_data category_data string_data\n",
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}
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"source": [
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"data2[data2.isnull().any(axis=1)]"
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]
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}
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"metadata": {
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"name": "python",
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"version": "3.7.6"
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"version": "3.7.7"
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"toc-autonumbering": true
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‎source-code/panel/.gitignore

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get_data.sh
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school_tool.ipynb
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Schooltool-latest.xlsx

‎source-code/panel/Schooltool-latest.xlsx

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