Data Science

Fill missing values in Pandas

Use the next or previous value to fill the missing values in Pandas

Bartosz Mikulski 19 Sep 2018 – 1 min read

The “fillna” function in Pandas not only can replace missing values with a given constant value, like in this example:

import pandas as pd
import numpy as np
df = pd.DataFrame([[np.nan], [2], [np.nan], [0]])
df

df.fillna(47)

You can also replace a missing value with the next (or previous) value in the data frame!

df.fillna(method = "ffill")

Note that the first value cannot be replaced because nothing is preceding it.

You can also use the value of the next row to fill a missing value.

df.fillna(method = "bfill")

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