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
A dataframe with missing values
Missing values replaced with a constant
You can also replace a missing value with the next (or previous) value in the data frame!
df.fillna(method = "ffill")
Missing values filled with the previous existing value.
Note that the first value cannot be replaced because nothing is preceding it.
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You can also use the value of the next row to fill a missing value.
df.fillna(method = "bfill")
Missing values filled with the next existing value.
