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Data Science Lesson 3 – Classwork
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| #!/usr/bin/python | |
| import pandas as pd | |
| df = pd.read_csv('nytimes_in.csv') | |
| group_cols = ['Age', 'Gender', 'Signed_In'] | |
| all_cols = group_cols + ['Clicks', 'Impressions'] | |
| dfg = df[all_cols].groupby(group_cols).agg([np.mean]) | |
| dfg['Click_Thru_Mean'] = dfg['Clicks'] / dfg['Impressions'] | |
| dfg = dfg.drop(['Clicks', 'Impressions'], axis=1) | |
| dfg.to_csv('nytimes_aggregation.csv') |
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| #!/usr/bin/python | |
| import pandas as pd | |
| import matplotlib.pyplot as plt | |
| # This file is output from nytimes_aggregate.py, and then header corrected by hand | |
| df = pd.read_csv('nytimes_agg_clean.csv') | |
| df.plot(figsize=(18,10), x='Signed_In', y='Click_Thrus') | |
| df.plot(figsize=(18,10), x='Age', y='Click_Thrus') | |
| df.plot(figsize=(18,10), x='Gender', y='Click_Thrus') | |
| plt.show() |
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| #!/usr/bin/python | |
| import requests | |
| with open('nytimes_in.csv', 'w') as f: | |
| for file in range(1, 31): | |
| url = "http://stat.columbia.edu/~rachel/datasets/nyt{0}.csv".format(file) | |
| print "Retrieving:", url | |
| response = requests.get(url) | |
| if response.ok: | |
| lines = response.text.splitlines(True) | |
| for i, line in enumerate(lines): | |
| # Only copy the header once | |
| if file == 1 or i > 0: | |
| f.write(line) |
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