某個網(wǎng)站/服務(wù)器上，請求鏈接的用戶信息。資料集中有電腦類型、瀏覽器鏈接等。用python進(jìn)行簡單的處理和繪圖分析。

資料集鏈接

# INPUT uses python 3.6 
import json
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

path = 'usagov_bitly_data2012-03-16-1331923249.txt'
records = [json.loads(line) for line in open(path)]
frame = pd.DataFrame(records)
results = pd.Series([x.split()[0] for x in frame.a.dropna()])
# print(results[:5])
cframe = frame[frame.a.notnull()]

operating_systems = np.where(cframe['a'].str.contains('Windows'),
                             'Windows','Not Windows')

by_tz_os = cframe.groupby(['tz',operating_systems])
agg_counts = by_tz_os.size().unstack().fillna(0)

indexer = agg_counts.sum(1).argsort()

count_subset = agg_counts.take(indexer)[-10:]


normed_subset = count_subset.div(count_subset.sum(1),axis = 0)
normed_subset.plot(kind='barh',stacked = True)
plt.show()

# OUT 
                     Not Windows  Windows
tz                                       
America/Sao_Paulo           13.0     20.0
Europe/Madrid               16.0     19.0
Pacific/Honolulu             0.0     36.0
Asia/Tokyo                   2.0     35.0
Europe/London               43.0     31.0
America/Denver             132.0     59.0
America/Los_Angeles        130.0    252.0
America/Chicago            115.0    285.0
                           245.0    276.0
America/New_York           339.0    912.0

operating_char.png

2018.7.16

學(xué)習(xí)筆記《用python進(jìn)行數(shù)據(jù)分析》,非原創(chuàng)，僅作學(xué)習(xí)存檔用途。 在草稿箱放太久有點(diǎn)忘了。