Created
May 8, 2014 21:49
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Comparison of two ways of concatenating pandas Index objects.
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{ | |
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"name": "", | |
"signature": "sha256:35f356f5ac018d8c56048eeba0aaef6924f28a5cf0b3f93c727990071818548d" | |
}, | |
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"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"from functools import reduce\n", | |
"\n", | |
"import numpy as np\n", | |
"import pandas as pd" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 16 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"indexes = (pd.Index(range(100000)),\n", | |
" pd.Index(range(100000, 200000)),\n", | |
" pd.Index(range(200000, 300000)),\n", | |
" pd.Index(range(300000, 400000)),\n", | |
" pd.Index(range(400000, 500000)))" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 20 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"indexes2 = (pd.Index([1]),\n", | |
" pd.Index([2]),\n", | |
" pd.Index([3]),\n", | |
" pd.Index([4]),\n", | |
" pd.Index([5]))" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 8 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"def concat_indexes1(indexes):\n", | |
" append = lambda x, y: x.append(y)\n", | |
" return reduce(append, indexes)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 3 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"concat_indexes1(indexes2)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 9, | |
"text": [ | |
"Int64Index([1, 2, 3, 4, 5], dtype='int64')" | |
] | |
} | |
], | |
"prompt_number": 9 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"%timeit concat_indexes1(indexes2)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"10000 loops, best of 3: 121 \u00b5s per loop\n" | |
] | |
} | |
], | |
"prompt_number": 14 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"%timeit concat_indexes1(indexes)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"100 loops, best of 3: 2.7 ms per loop\n" | |
] | |
} | |
], | |
"prompt_number": 21 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"def concat_indexes2(indexes):\n", | |
" return pd.Index(np.concatenate(indexes))" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 4 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"concat_indexes2(indexes2)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 10, | |
"text": [ | |
"Int64Index([1, 2, 3, 4, 5], dtype='int64')" | |
] | |
} | |
], | |
"prompt_number": 10 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"%timeit concat_indexes2(indexes2)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"10000 loops, best of 3: 17.2 \u00b5s per loop\n" | |
] | |
} | |
], | |
"prompt_number": 15 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"%timeit concat_indexes2(indexes)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"1000 loops, best of 3: 1.1 ms per loop\n" | |
] | |
} | |
], | |
"prompt_number": 22 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [] | |
} | |
], | |
"metadata": {} | |
} | |
] | |
} |
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