浏览工具排名-Pandas-Python数据分析(11)
亿网1.1. Pandas分析步骤
- 载入数据
- 将 浏览工具排名 进行 COUNT。类似如下SQL:
| 1 2 3 4 5 6 | SELECT browser , count ( * ) FROM log GROUP BY browser ORDER BY count ( * ) LIMIT 0 , 100 ; |
1.2. 代码
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | 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 browser_stat ( self ) : “” “统计不同浏览器访问次数” “” group_by_cols = [ ‘browser’ ] # 需要分组的列,只计算和显示该列 # 直接统计次数 url_req_grp = self . df [ group_by_cols ] . groupby ( self . df [ ‘browser’ ] ) return url_req_grp . agg ( [ ‘count’ ] ) [ ‘browser’ ] . nlargest ( 100 , ‘count’ ) def main ( ) : file_pathes = [ ‘www.trustauth.cn.access.log’ ] pd_ng_log_stat = PDNgLogStat ( ) pd_ng_log_stat . load_data ( file_pathes ) # 统计 统计不同浏览器访问次数 print pd_ng_log_stat . browser_stat ( ) if __name__ == ‘__main__’ : main ( ) |
运行统计和输出结果
| 1 2 3 4 5 6 7 8 9 10 11 12 13 | python pd_ng_log_stat . py count browser . . . . . . P1 4.1.2 ) 613 601 [ 100 rows x 1 columns ] |
文章转载来自：trustauth.cn