mirror of
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column types
This commit is contained in:
rasbt
parent
40d5dd93a5
commit
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"prompt_number": 1
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},
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{
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"cell_type": "markdown",
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@ -99,7 +99,10 @@
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"- [Sorting and Reindexing DataFrames](#Sorting-and-Reindexing-DataFrames)\n",
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"- [Updating Columns](#Updating-Columns)\n",
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"- [Chaining Conditions - Using Bitwise Operators](#Chaining-Conditions---Using-Bitwise-Operators)\n",
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"- [Getting an Overview of the Column Types](#Getting-an-Overview-of-the-Column-Types)"
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"- [Column Types](#Column-Types)\n",
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" - [Printing Column Types](#Printing-Column-Types)\n",
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" - [Selecting by Column Type](#Selecting-by-Column-Type)\n",
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" - [Converting Column Types](#Converting-Column-Types)"
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]
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},
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{
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 3,
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"prompt_number": 2,
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"text": [
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" PLAYER SALARY GP G A SOT \\\n",
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"0 Sergio Ag\u00fcero\\n Forward \u2014 Manchester City $19.2m 16 14 3 34 \n",
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@ -306,7 +309,7 @@
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]
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}
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"prompt_number": 3
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 4,
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"prompt_number": 3,
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"text": [
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" player salary gp g a sot ppg \\\n",
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"7 Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea $14.0m 20 2 14 10 10.47 \n",
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@ -434,7 +437,7 @@
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]
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}
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],
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"prompt_number": 4
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"prompt_number": 3
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},
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{
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"cell_type": "markdown",
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 5,
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"prompt_number": 4,
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"text": [
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" player salary games goals assists \\\n",
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"7 Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea $14.0m 20 2 14 \n",
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]
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}
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],
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"prompt_number": 4
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{
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 6,
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"prompt_number": 5,
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"text": [
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" player salary games goals assists \\\n",
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"5 Santiago Cazorla\\n Midfield \u2014 Arsenal 14.8 20 4 NaN \n",
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@ -689,7 +692,7 @@
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]
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}
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 7,
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"prompt_number": 6,
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"text": [
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" player salary games goals assists \\\n",
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"7 Cesc F\u00e0bregas\\n Midfield \u2014 Chelsea 14.0 20 2 14 \n",
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@ -800,7 +803,7 @@
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]
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}
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"prompt_number": 7
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 8,
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"prompt_number": 7,
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"7 Cesc F\u00e0bregas 14.0 20 2 14 10 \n",
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]
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"cell_type": "markdown",
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 9,
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"prompt_number": 8,
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"0 sergio ag\u00fcero 19.2 16 14 3 34 \n",
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]
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 11,
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"prompt_number": 10,
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"4 \u00e1ngel di mar\u00eda 15.0 13 3 NaN 13 \n",
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"prompt_number": 12,
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"prompt_number": 11,
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"0 sergio ag\u00fcero 19.2 16 14 3 34 \n",
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"output_type": "pyout",
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"prompt_number": 13,
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"prompt_number": 12,
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"0 sergio ag\u00fcero 19.2 16 14 3 34 \n",
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"8 saido berahino 13.8 21 9 0 20 \n",
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"8 saido berahino 13.8 21 9 0 20 \n",
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"prompt_number": 15,
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"0 sergio ag\u00fcero 19.2 16 14 3 34 \n",
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"1 sergio ag\u00fcero 19.2 16 14 3 34 \n",
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"1 sergio ag\u00fcero 20 16 14 3 34 \n",
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 18,
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"text": [
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" salary games goals assists shots_on_target \\\n",
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"player \n",
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]
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"metadata": {},
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"output_type": "pyout",
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"text": [
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"text": [
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"text": [
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" player salary games goals assists shots_on_target \\\n",
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"1 alexis s\u00e1nchez 15 0 12 7 29 \n",
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"metadata": {},
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"text": [
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<br>\n",
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"<br>"
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},
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{
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"cell_type": "heading",
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"level": 1,
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"metadata": {},
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"source": [
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"Column Types"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[[back to section overview](#Sections)]"
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]
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},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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},
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"cell_type": "heading",
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"level": 3,
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"metadata": {},
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"source": [
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"Printing Column Types"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"types = df.columns.to_series().groupby(df.dtypes).groups\n",
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"types"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 23,
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"text": [
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"{dtype('float64'): ['games',\n",
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" 'goals',\n",
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" 'assists',\n",
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" 'shots_on_target',\n",
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" 'points_per_game',\n",
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" 'points'],\n",
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" dtype('O'): ['player', 'salary', 'position', 'team']}"
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]
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}
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],
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"prompt_number": 23
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"cell_type": "heading",
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"level": 1,
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"level": 3,
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"metadata": {},
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"source": [
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"Getting an Overview of the Column Types"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"[[back to section overview](#Sections)]"
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"Selecting by Column Type"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"types = df.columns.to_series().groupby(df.dtypes).groups\n",
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"for t in types.items():\n",
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" print(t)"
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"# select string columns\n",
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"df.loc[:, (df.dtypes == np.dtype('O')).values].head()"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\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>player</th>\n",
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" <th>salary</th>\n",
|
||||
" <th>position</th>\n",
|
||||
" <th>team</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td> sergio ag\u00fcero</td>\n",
|
||||
" <td> 20</td>\n",
|
||||
" <td> forward</td>\n",
|
||||
" <td> manchester city</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td> alexis s\u00e1nchez</td>\n",
|
||||
" <td> 15</td>\n",
|
||||
" <td> forward</td>\n",
|
||||
" <td> arsenal</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td> saido berahino</td>\n",
|
||||
" <td> 13.8</td>\n",
|
||||
" <td> forward</td>\n",
|
||||
" <td> west brom</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td> eden hazard</td>\n",
|
||||
" <td> 18.9</td>\n",
|
||||
" <td> midfield</td>\n",
|
||||
" <td> chelsea</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td> yaya tour\u00e9</td>\n",
|
||||
" <td> 16.6</td>\n",
|
||||
" <td> midfield</td>\n",
|
||||
" <td> manchester city</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"metadata": {},
|
||||
"output_type": "pyout",
|
||||
"prompt_number": 24,
|
||||
"text": [
|
||||
"(dtype('O'), ['player', 'salary', 'position', 'team'])\n",
|
||||
"(dtype('float64'), ['games', 'goals', 'assists', 'shots_on_target', 'points_per_game', 'points'])\n"
|
||||
" player salary position team\n",
|
||||
"0 sergio ag\u00fcero 20 forward manchester city\n",
|
||||
"1 alexis s\u00e1nchez 15 forward arsenal\n",
|
||||
"2 saido berahino 13.8 forward west brom\n",
|
||||
"3 eden hazard 18.9 midfield chelsea\n",
|
||||
"4 yaya tour\u00e9 16.6 midfield manchester city"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 29
|
||||
"prompt_number": 24
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"<br>\n",
|
||||
"<br>"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "heading",
|
||||
"level": 3,
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Converting Column Types"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [],
|
||||
"input": [
|
||||
"df['salary'] = df['salary'].astype(float)"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": []
|
||||
"outputs": [],
|
||||
"prompt_number": 25
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"collapsed": false,
|
||||
"input": [
|
||||
"types = df.columns.to_series().groupby(df.dtypes).groups\n",
|
||||
"types"
|
||||
],
|
||||
"language": "python",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"metadata": {},
|
||||
"output_type": "pyout",
|
||||
"prompt_number": 26,
|
||||
"text": [
|
||||
"{dtype('float64'): ['salary',\n",
|
||||
" 'games',\n",
|
||||
" 'goals',\n",
|
||||
" 'assists',\n",
|
||||
" 'shots_on_target',\n",
|
||||
" 'points_per_game',\n",
|
||||
" 'points'],\n",
|
||||
" dtype('O'): ['player', 'position', 'team']}"
|
||||
]
|
||||
}
|
||||
],
|
||||
"prompt_number": 26
|
||||
}
|
||||
],
|
||||
"metadata": {}
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user