Question

我试图根据它下面第N行的值有条件地更改当前行的值。比方说，我有一个csv文件，看起来像：

   trial
    ''
    ''
    ''
    ''
    ''
    ''
    ''
    'a'
    ''
    ''
    ''
    ''
    ''
    ''
    ''
    'a'
    ''
    ''
    ''
    ''
    ''
    ''
    ''
    'a'

现在，如果当前行之后的每第3行的值为'a'，则null将从当前行转换为'a'到下面的第3行。就这样：

trial
''
''
''
''
'a'
'a'
'a'
'a'
''
''
''
''
'a'
'a'
'a'
'a'
''
''
''
''
'a'
'a'
'a'
'a'

我的代码如下：

data =csv.reader(data)
next(data)

def convert(param):
    if param=='':
        value='a'
    else:
        value=''
    return value

for row in data:
    i=0
    for line in islice(data, i+3, None):
        print i
        print line
        print row
        if line==['a']:
            convert(row)
        print row
        i = i+1

然而，输出是：

0
[]
[]
[]
1
[]
[]
[]
2
[]
[]
[]
3
['a']
[]
[]
4
[]
[]
[]
5
[]
[]
[]
6
[]
[]
[]
7
[]
[]
[]
8
[]
[]
[]
9
[]
[]
[]
10
[]
[]
[]
11
[]
[]
[]
12
[]
[]
[]
13
['a']
[]
[]
14
[]
[]
[]
15
[]
[]
[]
16
[]
[]
[]
17
[]
[]
[]
18
[]
[]
[]
19
[]
[]
[]
20
[]
[]
[]
21
[]
[]
[]
22
[]
[]
[]
23
['a']
[]
[]

关于如何做到这一点的任何想法？

Answer 1

您希望fillna与backfill

首先，您需要确保空值实际上是pandas识别的空值，所以

import pandas as pd
import numpy as np

df = df.replace('', np.NaN).fillna(method='bfill', limit=3).replace(np.NaN, '')

   trial
0       
1       
2       
3       
4      a
5      a
6      a
7      a
8       
9       
10      
11      
12     a
13     a
14     a
15     a
16      
17      
18      
19      
20     a
21     a
22     a
23     a

Answer 2

您可以使用iterrows()迭代行以获得结果：

# if the values have quotes, you can remove the quotes first
df1['trial'] = df1['trial'].str.replace("'",'')

for index, row in df1.iterrows():
    if row['trial'] == 'a':
        df1.loc[index-3:index, 'trial'] = 'a'
    else:
        continue

# output

    trial
0   
1   
2   
3   
4   a
5   a
6   a
7   a
8   
9   
10  
11  
12  a
13  a
14  a
15  a
16  
17  
18  
19  
20  a
21  a
22  a
23  a

根据使用python的csv下面的第N行的值，有条件地更改当前行的值

2 个答案: