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inplace ops update
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‎tutorials/things_in_pandas.ipynb‎

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{
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"metadata": {
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"name": "",
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"signature": "sha256:cf7223086a74b13d1ae2228a4c8545c401765a90cdb3eca418f18138a4afdaab"
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"signature": "sha256:2c7029e546d20c06eaa707f59d5b067689bf8827b87cc32f4fae7b55cde6e0f2"
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"nbformat": 3,
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"nbformat_minor": 0,
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"Sebastian Raschka 24/01/2015 \n",
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"Sebastian Raschka 25/01/2015 \n",
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"\n",
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"CPython 3.4.2\n",
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"IPython 2.3.1\n",
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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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}
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],
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"prompt_number": 8
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"prompt_number": 7
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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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"4 \u00c1ngel Di Mar\u00eda 15.0 13 3 NaN 13 \n",
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]
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}
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],
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"prompt_number": 9
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"prompt_number": 8
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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": 10,
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"prompt_number": 9,
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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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}
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],
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"prompt_number": 10
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"prompt_number": 9
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},
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{
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"cell_type": "markdown",
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"input": [
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"# Filling NaN cells with default value 0\n",
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"\n",
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"df = df.fillna(value=0)\n",
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"df.fillna(value=0, inplace=True)\n",
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"df"
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],
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"language": "python",
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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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"0 Sergio Ag\u00fcero 19.2 16 14 3 34 \n",
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]
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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": 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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"8 Saido Berahino 13.8 21 9 0 20 \n",
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]
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}
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],
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"prompt_number": 12
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"prompt_number": 11
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},
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{
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"cell_type": "code",
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],
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"metadata": {},
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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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"8 Saido Berahino 13.8 21 9 0 20 \n",
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]
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}
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],
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"prompt_number": 13
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"prompt_number": 12
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},
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{
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"cell_type": "markdown",
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"input": [
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"# Sorting the DataFrame by a certain column (from highest to lowest)\n",
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"\n",
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"df = df.sort('goals', ascending=False)\n",
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"df.sort('goals', ascending=False, inplace=True)\n",
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"df.head()"
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],
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"language": "python",
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 14,
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"prompt_number": 13,
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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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}
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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": 15,
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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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]
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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": 15,
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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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]
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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": 16,
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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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}
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],
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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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}
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],
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"prompt_number": 18,
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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 20 16 14 3 34 \n",
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]
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}
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],
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"output_type": "pyout",
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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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]
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}
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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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" 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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]
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}
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],
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"prompt_number": 22
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"prompt_number": 20
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}
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],
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"metadata": {}

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