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| { | |
| "metadata": { | |
| "name": "LongReshape" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { |
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| In [15]: paste | |
| data = '''SEARCH_TERM,ACTUAL_URL | |
| "bra tv bord","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord" | |
| "tv p\xc3\xa5 hjul","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord" | |
| "SLAGBORD, \\"Bergslagen\\", IKEA:s 1700-tals serie","http://www.ikea.com/se/sv/catalog/categories/departments/living_room/10475/?se%7cps%7cnonbranded%7cvardagsrum%7cgoogle%7ctv_bord"''' | |
| df = read_csv(StringIO(data), escapechar='\\', encoding='utf-8') | |
| ## -- End pasted text -- |
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| *** Processing results... | |
| *** | |
| Results: | |
| t_head t_baseline ratio | |
| name | |
| read_csv_comment2 28.6790 366.0152 0.0784 | |
| frame_iteritems_cached 0.0677 0.3855 0.1757 | |
| read_csv_thou_vb 35.5317 188.2858 0.1887 | |
| append_frame_single_homogenous 0.3423 0.8898 0.3847 |
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| { | |
| "metadata": { | |
| "name": "DataScienceTutorial" | |
| }, | |
| "nbformat": 3, | |
| "nbformat_minor": 0, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { |
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| { | |
| "metadata": { | |
| "name": "NYCPython_FoodDB" | |
| }, | |
| "nbformat": 3, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", |
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| { | |
| "metadata": { | |
| "name": "Basics" | |
| }, | |
| "nbformat": 2, | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", |
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| # pylint: disable=W0612 | |
| import time | |
| import pandas as pd | |
| import numpy as np | |
| import iopro | |
| import gc |