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所属分类：python
1.1. Pandas分析步骤
- 载入数据
- 将 外链点击数 进行 COUNT。类似如下SQL:
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SELECT reference_url, count(*) FROM log GROUP BY reference_url ORDER BY count(*) LIMIT 0, 100; |
1.2. 代码
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cat pd_ng_log_stat.py #!/usr/bin/env python #-*- coding: utf-8 -*- from ng_line_parser import NgLineParser import pandas as pd import socket import struct class PDNgLogStat(object): def __init__(self): self.ng_line_parser = NgLineParser() def _log_line_iter(self, pathes): """解析文件中的每一行并生成一个迭代器""" for path in pathes: with open(path, 'r') as f: for index, line in enumerate(f): self.ng_line_parser.parse(line) yield self.ng_line_parser.to_dict() def load_data(self, path): """通过给的文件路径加载数据生成 DataFrame""" self.df = pd.DataFrame(self._log_line_iter(path)) def url_ref_stat(self): """统计外链点击情况""" group_by_cols = ['reference_url'] # 需要分组的列,只计算和显示该列 # 直接统计次数 url_ref_grp = self.df[group_by_cols].groupby( self.df['reference_url']) return url_ref_grp.agg(['count'])['reference_url'].sort_values(by='count', ascending=False) def main(): file_pathes = ['www.ttmark.com.access.log'] pd_ng_log_stat = PDNgLogStat() pd_ng_log_stat.load_data(file_pathes) # 统计外链点击情况 print pd_ng_log_stat.url_ref_stat() if __name__ == '__main__': main() |
运行统计和输出结果
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python pd_ng_log_stat.py count reference_url - 574546 www.ttmark.com 331136 m.baidu.com 32990 ...... www.google.fr 192 www.google.de 147 www.google.it 136 [231 rows x 1 columns] |
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