mirror of
https://github.com/donnemartin/data-science-ipython-notebooks.git
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159 lines
4.2 KiB
Plaintext
159 lines
4.2 KiB
Plaintext
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{
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"metadata": {
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"name": "",
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"signature": "sha256:8c91cadf8bbcbcdd5a60fc0a89e964b846a6f5328eaa57d57afbaedda06ad3ca"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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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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"# Functions"
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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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"* Functions as Objects\n",
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"* Lambdas\n",
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"* Closures\n",
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"* \\*args, \\*\\*kwargs\n",
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"* Currying\n",
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"* Generators\n",
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"* Generator Expressions"
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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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"## Functions as Objects"
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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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"Python treats functions as objects which can simplify data cleaning"
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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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"%%file transform_util.py\n",
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"import re\n",
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"\n",
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"\n",
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"class TransformUtil:\n",
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"\n",
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" @classmethod\n",
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" def remove_punctuation(cls, value):\n",
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" \"\"\"Removes !, #, and ?.\n",
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" \"\"\" \n",
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" return re.sub('[!#?]', '', value) \n",
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"\n",
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" @classmethod\n",
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" def clean_strings(cls, strings, ops): \n",
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" \"\"\"General purpose method to clean strings.\n",
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"\n",
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" Pass in a sequence of strings and the operations to perform.\n",
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" \"\"\" \n",
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" result = [] \n",
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" for value in strings: \n",
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" for function in ops: \n",
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" value = function(value) \n",
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" result.append(value) \n",
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" return result"
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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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"text": [
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"Overwriting transform_util.py\n"
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]
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}
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],
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"prompt_number": 1
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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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"%%file tests/test_transform_util.py\n",
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"from nose.tools import assert_equal\n",
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"from ..transform_util import TransformUtil\n",
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"\n",
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"\n",
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"class TestTransformUtil():\n",
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"\n",
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" states = [' Alabama ', 'Georgia!', 'Georgia', 'georgia', \\\n",
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" 'FlOrIda', 'south carolina##', 'West virginia?']\n",
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" \n",
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" expected_output = ['Alabama',\n",
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" 'Georgia',\n",
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" 'Georgia',\n",
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" 'Georgia',\n",
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" 'Florida',\n",
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" 'South Carolina',\n",
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" 'West Virginia']\n",
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" \n",
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" def test_remove_punctuation(self):\n",
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" assert_equal(TransformUtil.remove_punctuation('!#?'), '')\n",
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"\n",
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" def test_clean_strings(self):\n",
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" clean_ops = [str.strip, TransformUtil.remove_punctuation, str.title] \n",
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" output = TransformUtil.clean_strings(self.states, clean_ops)\n",
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" assert_equal(output, self.expected_output)\n"
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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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"text": [
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"Overwriting tests/test_transform_util.py\n"
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]
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}
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],
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"prompt_number": 2
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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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"!nosetests tests/test_transform_util.py -v"
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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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"text": [
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"core.tests.test_transform_util.TestTransformUtil.test_clean_strings ... ok\r\n",
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"core.tests.test_transform_util.TestTransformUtil.test_remove_punctuation ... ok\r\n",
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"\r\n",
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"----------------------------------------------------------------------\r\n",
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"Ran 2 tests in 0.001s\r\n",
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"\r\n",
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"OK\r\n"
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]
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}
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],
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"prompt_number": 3
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}
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],
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"metadata": {}
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}
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]
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}
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