Question

我有csv个文件

ID,"address","used_at","active_seconds","pageviews"
0a1d796327284ebb443f71d85cb37db9,"vk.com",2016-01-29 22:10:52,3804,115
0a1d796327284ebb443f71d85cb37db9,"2gis.ru",2016-01-29 22:48:52,214,24
0a1d796327284ebb443f71d85cb37db9,"yandex.ru",2016-01-29 22:14:30,4,2
0a1d796327284ebb443f71d85cb37db9,"worldoftanks.ru",2016-01-29 22:10:30,41,2

我需要删除包含一些单词的字符串。有117个单词。

我试试

for line in df:
    if 'yandex.ru' in line:
        df = df.replace(line, '')

但对于117个单词，它的工作速度太慢，之后我创建了pivot_table和我尝试删除的单词，包含在列中。

             aaa                         10ruslake.ru  youtube.ru 1tv.ru  24open.ru
0   0025977ab2998580d4559af34cc66a4e             0        0       34      43
1   00c651e018cbcc8fe7aa57492445c7a2             230      0       0       23
2   0120bc30e78ba5582617a9f3d6dfd8ca             12       0       0       0
3   01249e90ed8160ddae82d2190449b773             25       0       13      25

该列仅包含0

如何更快地完成并删除行，以便这些单词不在列中？

Answer 1

IIUC您可以isin使用boolean indexing：

print df
                                 ID          address              used_at  \
0  0a1d796327284ebb443f71d85cb37db9           vk.com  2016-01-29 22:10:52   
1  0a1d796327284ebb443f71d85cb37db9           vk.com  2016-01-29 22:10:52   
2  0a1d796327284ebb443f71d85cb37db9          2gis.ru  2016-01-29 22:48:52   
3  0a1d796327284ebb443f71d85cb37db9        yandex.ru  2016-01-29 22:14:30   
4  0a1d796327284ebb443f71d85cb37db9  worldoftanks.ru  2016-01-29 22:10:30   

   active_seconds  pageviews  
0            3804        115  
1            3804        115  
2             214         24  
3               4          2  
4              41          2  

words = ['vk.com','yandex.ru']

print ~df.address.isin(words)
0    False
1    False
2     True
3    False
4     True
Name: address, dtype: bool

print df[~df.address.isin(words)]
                                 ID          address              used_at  \
2  0a1d796327284ebb443f71d85cb37db9          2gis.ru  2016-01-29 22:48:52   
4  0a1d796327284ebb443f71d85cb37db9  worldoftanks.ru  2016-01-29 22:10:30   

   active_seconds  pageviews  
2             214         24  
4              41          2

然后使用pivot：

print df[~df.address.isin(words)].pivot(index='ID', columns='address', values='pageviews')
address                           2gis.ru  worldoftanks.ru
ID                                                        
0a1d796327284ebb443f71d85cb37db9       24                2

另一个解决方案是删除行，当某些列为0时（例如pageviews）：

print df

                                 ID          address              used_at  \
0  0a1d796327284ebb443f71d85cb37db9       youtube.ru  2016-01-29 22:10:52   
1            0a1d796327284ebfsffsdf       youtube.ru  2016-01-29 22:10:52   
2  0a1d796327284ebb443f71d85cb37db9           vk.com  2016-01-29 22:10:52   
3  0a1d796327284ebb443f71d85cb37db9          2gis.ru  2016-01-29 22:48:52   
4  0a1d796327284ebb443f71d85cb37db9        yandex.ru  2016-01-29 22:14:30   
5  0a1d796327284ebb443f71d85cb37db9  worldoftanks.ru  2016-01-29 22:10:30   

   active_seconds  pageviews  
0            3804          0  
1            3804          0  
2            3804        115  
3             214         24  
4               4          2  
5              41          2

print df.pageviews != 0
0    False
1    False
2     True
3     True
4     True
5     True
Name: pageviews, dtype: bool

print df[(df.pageviews != 0)]
                                 ID          address              used_at  \
2  0a1d796327284ebb443f71d85cb37db9           vk.com  2016-01-29 22:10:52   
3  0a1d796327284ebb443f71d85cb37db9          2gis.ru  2016-01-29 22:48:52   
4  0a1d796327284ebb443f71d85cb37db9        yandex.ru  2016-01-29 22:14:30   
5  0a1d796327284ebb443f71d85cb37db9  worldoftanks.ru  2016-01-29 22:10:30   

   active_seconds  pageviews  
2            3804        115  
3             214         24  
4               4          2  
5              41          2  

print df[(df.pageviews != 0)].pivot_table(index='ID', columns='address', values='pageviews')
address                           2gis.ru  vk.com  worldoftanks.ru  yandex.ru
ID                                                                           
0a1d796327284ebb443f71d85cb37db9       24     115                2          2

Answer 2

我知道处理csv文件的最快方法是使用包Pandas从中创建数据帧。

import pandas as pd

df = pd.read_csv(the_path_of_your_file,header = 0)
df.ix[df.ix[:,'address'] == 'yandex.ru','address'] = ''

用一个空字符串替换包含'yandex.ru'的单元格。然后你可以用csv写回来：

df.to_csv(the_path_of_your_file)

如果您要执行的操作是删除发生该网址的行，请使用：

df = df.drop(df[df.address == 'yandex.ru'].index)

使用python从文件中删除字符串

2 个答案: