CODEWITHSUNDEEP
pythonpandas
Jon K
Jon K

Reputation: 3

Replace NaNs with values from X rows earlier or later in pandas dataframe

I have a Dataframe in which each row represents a consecutive day and the column represents total electricity consumption. There are some NaN values where data is missing:

     ELECTRICITY
0    10
1    15
2    17
3    12
4    15
5    16
6    22
7    8
8    NaN
9    16
10   13

Because electricity consumption in this sample is mostly affected by day of the week, I want to replace all NaNs with the value from 7 rows earlier or later.

I have investigated the following with no success:

  1. fillna: only allows me to replace with a specific value or immediately adjacent values
  2. interpolate: only allows me to replace with an average of immediately adjacent values
  3. replace: seems to allow conditional replacements with set values

Thanks for any help.

Upvotes: 0

Views: 62

Answers (1)

piRSquared
piRSquared

Reputation: 294506

Use fillna and shift

df.fillna(df.shift(7))

    ELECTRICITY
0          10.0
1          15.0
2          17.0
3          12.0
4          15.0
5          16.0
6          22.0
7           8.0
8          15.0
9          16.0
10         13.0

Upvotes: 1

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