{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Data Wrangling: Join, Combine, "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"pd.options.display.max_rows = 20\n",
"np.random.seed(12345)\n",
"import matplotlib.pyplot as plt\n",
"plt.rc('figure', figsize=(10, 6))\n",
"np.set_printoptions(precision=4, suppress=True)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Hierarchical Indexing"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data = pd.Series(np.random.randn(9),\n",
" index=[['a', 'a', 'a', 'b', 'b', 'c', 'c', 'd', 'd'],\n",
" [1, 2, 3, 1, 3, 1, 2, 2, 3]])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data.index"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data['b']\n",
"data['b':'c']\n",
"data.loc[['b', 'd']]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data.loc[:, 2]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data.unstack()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data.unstack().stack()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame = pd.DataFrame(np.arange(12).reshape((4, 3)),\n",
" index=[['a', 'a', 'b', 'b'], [1, 2, 1, 2]],\n",
" columns=[['Ohio', 'Ohio', 'Colorado'],\n",
" ['Green', 'Red', 'Green']])\n",
"frame"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame.index.names = ['key1', 'key2']\n",
"frame.columns.names = ['state', 'color']\n",
"frame"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame['Ohio']"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"MultiIndex.from_arrays([['Ohio', 'Ohio', 'Colorado'], ['Green', 'Red', 'Green']],\n",
" names=['state', 'color'])"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Reordering and Sorting Levels"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame.swaplevel('key1', 'key2')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame.sort_index(level=1)\n",
"frame.swaplevel(0, 1).sort_index(level=0)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Summary Statistics by Level"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame.sum(level='key2')\n",
"frame.sum(level='color', axis=1)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Indexing with a DataFrame's columns"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame = pd.DataFrame({'a': range(7), 'b': range(7, 0, -1),\n",
" 'c': ['one', 'one', 'one', 'two', 'two',\n",
" 'two', 'two'],\n",
" 'd': [0, 1, 2, 0, 1, 2, 3]})\n",
"frame"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame2 = frame.set_index(['c', 'd'])\n",
"frame2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame.set_index(['c', 'd'], drop=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"frame2.reset_index()"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Combining and Merging Datasets"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Database-Style DataFrame Joins"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df1 = pd.DataFrame({'key': ['b', 'b', 'a', 'c', 'a', 'a', 'b'],\n",
" 'data1': range(7)})\n",
"df2 = pd.DataFrame({'key': ['a', 'b', 'd'],\n",
" 'data2': range(3)})\n",
"df1\n",
"df2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(df1, df2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(df1, df2, on='key')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df3 = pd.DataFrame({'lkey': ['b', 'b', 'a', 'c', 'a', 'a', 'b'],\n",
" 'data1': range(7)})\n",
"df4 = pd.DataFrame({'rkey': ['a', 'b', 'd'],\n",
" 'data2': range(3)})\n",
"pd.merge(df3, df4, left_on='lkey', right_on='rkey')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(df1, df2, how='outer')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df1 = pd.DataFrame({'key': ['b', 'b', 'a', 'c', 'a', 'b'],\n",
" 'data1': range(6)})\n",
"df2 = pd.DataFrame({'key': ['a', 'b', 'a', 'b', 'd'],\n",
" 'data2': range(5)})\n",
"df1\n",
"df2\n",
"pd.merge(df1, df2, on='key', how='left')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(df1, df2, how='inner')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"left = pd.DataFrame({'key1': ['foo', 'foo', 'bar'],\n",
" 'key2': ['one', 'two', 'one'],\n",
" 'lval': [1, 2, 3]})\n",
"right = pd.DataFrame({'key1': ['foo', 'foo', 'bar', 'bar'],\n",
" 'key2': ['one', 'one', 'one', 'two'],\n",
" 'rval': [4, 5, 6, 7]})\n",
"pd.merge(left, right, on=['key1', 'key2'], how='outer')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(left, right, on='key1')\n",
"pd.merge(left, right, on='key1', suffixes=('_left', '_right'))"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Merging on Index"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"left1 = pd.DataFrame({'key': ['a', 'b', 'a', 'a', 'b', 'c'],\n",
" 'value': range(6)})\n",
"right1 = pd.DataFrame({'group_val': [3.5, 7]}, index=['a', 'b'])\n",
"left1\n",
"right1\n",
"pd.merge(left1, right1, left_on='key', right_index=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(left1, right1, left_on='key', right_index=True, how='outer')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"lefth = pd.DataFrame({'key1': ['Ohio', 'Ohio', 'Ohio',\n",
" 'Nevada', 'Nevada'],\n",
" 'key2': [2000, 2001, 2002, 2001, 2002],\n",
" 'data': np.arange(5.)})\n",
"righth = pd.DataFrame(np.arange(12).reshape((6, 2)),\n",
" index=[['Nevada', 'Nevada', 'Ohio', 'Ohio',\n",
" 'Ohio', 'Ohio'],\n",
" [2001, 2000, 2000, 2000, 2001, 2002]],\n",
" columns=['event1', 'event2'])\n",
"lefth\n",
"righth"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.merge(lefth, righth, left_on=['key1', 'key2'], right_index=True)\n",
"pd.merge(lefth, righth, left_on=['key1', 'key2'],\n",
" right_index=True, how='outer')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"left2 = pd.DataFrame([[1., 2.], [3., 4.], [5., 6.]],\n",
" index=['a', 'c', 'e'],\n",
" columns=['Ohio', 'Nevada'])\n",
"right2 = pd.DataFrame([[7., 8.], [9., 10.], [11., 12.], [13, 14]],\n",
" index=['b', 'c', 'd', 'e'],\n",
" columns=['Missouri', 'Alabama'])\n",
"left2\n",
"right2\n",
"pd.merge(left2, right2, how='outer', left_index=True, right_index=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"left2.join(right2, how='outer')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"left1.join(right1, on='key')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"another = pd.DataFrame([[7., 8.], [9., 10.], [11., 12.], [16., 17.]],\n",
" index=['a', 'c', 'e', 'f'],\n",
" columns=['New York', 'Oregon'])\n",
"another\n",
"left2.join([right2, another])\n",
"left2.join([right2, another], how='outer')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Concatenating Along an Axis"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"arr = np.arange(12).reshape((3, 4))\n",
"arr\n",
"np.concatenate([arr, arr], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"s1 = pd.Series([0, 1], index=['a', 'b'])\n",
"s2 = pd.Series([2, 3, 4], index=['c', 'd', 'e'])\n",
"s3 = pd.Series([5, 6], index=['f', 'g'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat([s1, s2, s3])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat([s1, s2, s3], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"s4 = pd.concat([s1, s3])\n",
"s4\n",
"pd.concat([s1, s4], axis=1)\n",
"pd.concat([s1, s4], axis=1, join='inner')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat([s1, s4], axis=1, join_axes=[['a', 'c', 'b', 'e']])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"result = pd.concat([s1, s1, s3], keys=['one', 'two', 'three'])\n",
"result\n",
"result.unstack()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat([s1, s2, s3], axis=1, keys=['one', 'two', 'three'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df1 = pd.DataFrame(np.arange(6).reshape(3, 2), index=['a', 'b', 'c'],\n",
" columns=['one', 'two'])\n",
"df2 = pd.DataFrame(5 + np.arange(4).reshape(2, 2), index=['a', 'c'],\n",
" columns=['three', 'four'])\n",
"df1\n",
"df2\n",
"pd.concat([df1, df2], axis=1, keys=['level1', 'level2'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat({'level1': df1, 'level2': df2}, axis=1)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat([df1, df2], axis=1, keys=['level1', 'level2'],\n",
" names=['upper', 'lower'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df1 = pd.DataFrame(np.random.randn(3, 4), columns=['a', 'b', 'c', 'd'])\n",
"df2 = pd.DataFrame(np.random.randn(2, 3), columns=['b', 'd', 'a'])\n",
"df1\n",
"df2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.concat([df1, df2], ignore_index=True)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Combining Data with Overlap"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"a = pd.Series([np.nan, 2.5, np.nan, 3.5, 4.5, np.nan],\n",
" index=['f', 'e', 'd', 'c', 'b', 'a'])\n",
"b = pd.Series(np.arange(len(a), dtype=np.float64),\n",
" index=['f', 'e', 'd', 'c', 'b', 'a'])\n",
"b[-1] = np.nan\n",
"a\n",
"b\n",
"np.where(pd.isnull(a), b, a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"b[:-2].combine_first(a[2:])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df1 = pd.DataFrame({'a': [1., np.nan, 5., np.nan],\n",
" 'b': [np.nan, 2., np.nan, 6.],\n",
" 'c': range(2, 18, 4)})\n",
"df2 = pd.DataFrame({'a': [5., 4., np.nan, 3., 7.],\n",
" 'b': [np.nan, 3., 4., 6., 8.]})\n",
"df1\n",
"df2\n",
"df1.combine_first(df2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Reshaping and Pivoting"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Reshaping with Hierarchical Indexing"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data = pd.DataFrame(np.arange(6).reshape((2, 3)),\n",
" index=pd.Index(['Ohio', 'Colorado'], name='state'),\n",
" columns=pd.Index(['one', 'two', 'three'],\n",
" name='number'))\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"result = data.stack()\n",
"result"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"result.unstack()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"result.unstack(0)\n",
"result.unstack('state')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"s1 = pd.Series([0, 1, 2, 3], index=['a', 'b', 'c', 'd'])\n",
"s2 = pd.Series([4, 5, 6], index=['c', 'd', 'e'])\n",
"data2 = pd.concat([s1, s2], keys=['one', 'two'])\n",
"data2\n",
"data2.unstack()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data2.unstack()\n",
"data2.unstack().stack()\n",
"data2.unstack().stack(dropna=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df = pd.DataFrame({'left': result, 'right': result + 5},\n",
" columns=pd.Index(['left', 'right'], name='side'))\n",
"df\n",
"df.unstack('state')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df.unstack('state').stack('side')"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Pivoting “Long” to “Wide” Format"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"data = pd.read_csv('examples/macrodata.csv')\n",
"data.head()\n",
"periods = pd.PeriodIndex(year=data.year, quarter=data.quarter,\n",
" name='date')\n",
"columns = pd.Index(['realgdp', 'infl', 'unemp'], name='item')\n",
"data = data.reindex(columns=columns)\n",
"data.index = periods.to_timestamp('D', 'end')\n",
"ldata = data.stack().reset_index().rename(columns={0: 'value'})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"ldata[:10]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pivoted = ldata.pivot('date', 'item', 'value')\n",
"pivoted"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"ldata['value2'] = np.random.randn(len(ldata))\n",
"ldata[:10]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pivoted = ldata.pivot('date', 'item')\n",
"pivoted[:5]\n",
"pivoted['value'][:5]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"unstacked = ldata.set_index(['date', 'item']).unstack('item')\n",
"unstacked[:7]"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Pivoting “Wide” to “Long” Format"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"df = pd.DataFrame({'key': ['foo', 'bar', 'baz'],\n",
" 'A': [1, 2, 3],\n",
" 'B': [4, 5, 6],\n",
" 'C': [7, 8, 9]})\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"melted = pd.melt(df, ['key'])\n",
"melted"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"reshaped = melted.pivot('key', 'variable', 'value')\n",
"reshaped"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"reshaped.reset_index()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.melt(df, id_vars=['key'], value_vars=['A', 'B'])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"pd.melt(df, value_vars=['A', 'B', 'C'])\n",
"pd.melt(df, value_vars=['key', 'A', 'B'])"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Conclusion"
]
}
],
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