- http://jonathansoma.com/lede/data-studio/classes/small-multiples/long-explanation-of-using-plt-subplots-to-create-small-multiples/
- http://nb.bianp.net/sort/views/
- https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks
- https://svds.com/jupyter-notebook-best-practices-for-data-science/
- https://drivendata.github.io/cookiecutter-data-science/
- https://www.dataquest.io/blog/how-to-setup-a-data-science-blog/
#DS curriculum
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# Reuters-21578 dataset downloader and parser | |
# | |
# Author: Eustache Diemert <[email protected]> | |
# http://scikit-learn.org/stable/auto_examples/applications/plot_out_of_core_classification.html | |
# | |
# Modified by @herrfz, get pandas DataFrame from the orig SGML | |
# License: BSD 3 clause | |
from __future__ import print_function |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<meta charset="utf-8"> | |
<title>Django</title> | |
<link rel="stylesheet" href="https://stackedit.io/res-min/themes/base.css" /> | |
<script type="text/javascript" src="https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS_HTML"></script> | |
</head> | |
<body><div class="container"><p><div class="toc"> | |
<ul> |
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" | |
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd"> | |
<modelVersion>4.0.0</modelVersion> | |
<groupId>com.acme</groupId> | |
<artifactId>bomb</artifactId> | |
<version>0.0.1</version> | |
<packaging>war</packaging> | |
<name>bomb</name> | |
<dependencies> | |
<dependency> |
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<div ng-app="videoApp" ng-controller="VideoController"> | |
<table> | |
<thead> | |
<th>Title</th> | |
<th>Length</th> | |
<th></th> | |
</thead> | |
<tbody> | |
<tr data-id="{{video.Id}}" ng-repeat="video in videos"> |
##Pandas installation
###Pandas sudo apt-get install python-pandas
###Dependencies ####Numpy sudo pip install numpy ####python-dateutil ####pytz
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import pandas as pd | |
unames = ['user_id', 'gender', 'age', 'occupation', 'zip'] | |
users = pd.read_table('users.dat', sep='::', header=None, | |
names=unames) | |
rnames = ['user_id', 'movie_id', 'rating', 'timestamp'] | |
ratings = pd.read_table('ratings.dat', sep='::', header=None, | |
names=rnames) | |
mnames = ['movie_id', 'title', 'genres'] | |
movies = pd.read_table('movies.dat', sep='::', header=None, | |
names=mnames) |
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import json | |
from pandas import DataFrame, Series | |
import pandas as pd | |
path = 'usagov_bitly_data2012-03-16-1331923249.txt' | |
records = [json.loads(line) for line in open(path)] | |
time_zones = [rec['tz'] for rec in records if 'tz' in rec] | |
frame = DataFrame(records) | |
clean_tz = frame['tz'].fillna('Missing') | |
clean_tz[clean_tz == ''] = 'Unknown' |
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