熊猫填充/填充以进行特定的观察

Question

I have the following dataframe:

 id     indicator 
 1          NaN
 1          NaN
 1          1
 1          NaN
 1          NaN
 1          NaN

In reality, I have several more ids. My question now is, how do I do a forward or backward fill for a specific range, eg for only the next/last 2 observations. My dataframe should look like this:

 id     indicator 
 1          NaN
 1          NaN 
 1          1
 1          1
 1          1
 1          NaN

I know the command

df.groupby("id")["indicator"].fillna(value=None, method="ffill")         

However, this fills all the missing values instead of just the next two observations. Anyone knows a solution?

Answer 1

I think DataFrameGroupBy.ffill or DataFrameGroupBy.bfill with limit parameter is nicer:

df.groupby("id")["indicator"].ffill(limit=3)

df.groupby("id")["indicator"].bfill(limit=3)

Sample:

#5 value is in the end of group, so only one value is filled 
df['filled'] = df.groupby("id")["indicator"].ffill(limit=2)
print (df)
    id  indicator  filled
0    1        NaN     NaN
1    1        NaN     NaN
2    1        1.0     1.0
3    1        NaN     1.0
4    1        NaN     1.0
5    1        NaN     NaN
6    1        NaN     NaN
7    1        NaN     NaN
8    1        4.0     4.0
9    1        NaN     4.0
10   1        NaN     4.0
11   1        NaN     NaN
12   1        NaN     NaN
13   2        NaN     NaN
14   2        NaN     NaN
15   2        1.0     1.0
16   2        NaN     1.0
17   2        NaN     1.0
18   2        NaN     NaN
19   2        5.0     5.0
20   2        NaN     5.0
21   3        3.0     3.0
22   3        NaN     3.0
23   3        NaN     3.0
24   3        NaN     NaN
25   3        NaN     NaN

Answer 2

almost there, straight from the doc

If method is specified, this is the maximum number of consecutive NaN values to forward/backward fill. In other words, if there is a gap with more than this number of consecutive NaNs, it will only be partially filled. If method is not specified, this is the maximum number of entries along the entire axis where NaNs will be filled. Must be greater than 0 if not None.

df.groupby("id")["indicator"].fillna(value=None,method="ffill",limit=3)