Python

Question

import pandas as pd

df = pd.DataFrame([['NewJersy',0,'2020-08-29'],
                   ['NewJersy',12,'2020-08-30'],
                   ['NewJersy',12,'2020-08-31'],
                   ['NewJersy',None,'2020-09-01'],
                   ['NewJersy',None,'2020-09-02'],
                   ['NewJersy',None,'2020-09-03'],
                   ['NewJersy',5,'2020-09-04'],
                   ['NewJersy',5,'2020-09-05'],
                   ['NewJersy',None,'2020-09-06'],
                   ['NewYork',None,'2020-08-29'],
                   ['NewYork',None,'2020-08-30'],
                   ['NewYork',8,'2020-08-31'],
                   ['NewYork',7,'2020-09-01'],
                   ['NewYork',None,'2020-09-02'],
                   ['NewYork',None,'2020-09-03']],
                   columns=['FName', 'FVal', 'GDate'])

print(df)

我想用以前的记录值填充 NULL 值。例如，对于 20-09-01 到 20-09-03，列 FValue 的值为 NULL。 NULL 值应替换为取自先前有效值的值 12，即来自 20-08-31。

此外，如果日期 2020-08-29 的值为空，则应将其替换为零，因为它是第一个日期并且没有之前的记录。

我试过下面的代码但没有用

df['F'] = df['F'].fillna(方法='ffill')

在此处检查预期值： Fill Null Values image

谢谢

Answer 1

不确定这是否是您想要的。但这就是我要做的

>>> import math
>>> for s in df.iterrows():
...     if math.isnan(s[1][1]):
...        df.iloc[s[0],1] = df.iloc[s[0] - 1,1]
...
>>> df
       FName  FVal       GDate
0   NewJersy   0.0  2020-08-29
1   NewJersy  12.0  2020-08-30
2   NewJersy  12.0  2020-08-31
3   NewJersy  12.0  2020-09-01
4   NewJersy  12.0  2020-09-02
5   NewJersy  12.0  2020-09-03
6   NewJersy   5.0  2020-09-04
7   NewJersy   5.0  2020-09-05
8   NewJersy   5.0  2020-09-06
9    NewYork   5.0  2020-08-29
10   NewYork   5.0  2020-08-30
11   NewYork   8.0  2020-08-31
12   NewYork   7.0  2020-09-01
13   NewYork   7.0  2020-09-02
14   NewYork   7.0  2020-09-03
>>>

Answer 2

你可以试试这个：

df.GDate = pd.to_datetime(df.GDate)
for i in range(len(df)):
    if (np.isnan(df.FVal.loc[i])) and (i > 0):
        if (df.GDate.loc[i]-df.GDate.loc[i-1]).days == 1:
            print((df.GDate.loc[i]-df.GDate.loc[i-1]).days)
            df.FVal.loc[i] = df.FVal.loc[i-1]
        else:
            df.FVal.loc[i] = 0

输出

    FName       FVal    GDate
0   NewJersy    0.0     2020-08-29
1   NewJersy    12.0    2020-08-30
2   NewJersy    12.0    2020-08-31
3   NewJersy    12.0    2020-09-01
4   NewJersy    12.0    2020-09-02
5   NewJersy    12.0    2020-09-03
6   NewJersy    5.0     2020-09-04
7   NewJersy    5.0     2020-09-05
8   NewJersy    5.0     2020-09-06
9   NewYork     0.0     2020-08-29
10  NewYork     0.0     2020-08-30
11  NewYork     8.0     2020-08-31
12  NewYork     7.0     2020-09-01
13  NewYork     7.0     2020-09-02
14  NewYork     7.0     2020-09-03

Answer 3

您应该首先确保您的 DataFrame 是按时间排序的，以防：

df = df.sort_values('GDate').reset_index(drop=True)

然后你必须用0填充第一个值：

if pd.isnull(df.loc[0, 'FVal']):
    df.loc[0, 'FVal'] = df.loc[0, 'FVal']

然后像你一样向前填充：

df['FVal'] = df['FVal'].fillna(method='ffill')

请注意，列名称是 FVal 而不是 F。

Python - 用列中的前一个记录值填充 NULL

Python - Fill NULL with previous record value in a column

null

fill

fillna