Fill missing values in Pandas
The “fillna” function in Pandas not only can replace missing values with a given constant value, like in this example:
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import pandas as pd
import numpy as np
df = pd.DataFrame([[np.nan], [2], [np.nan], [0]])
df

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df.fillna(47)

You can also replace a missing value with the next (or previous) value in the data frame!
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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.
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df.fillna(method = "bfill")

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Bartosz Mikulski
- MLOps engineer by day
- AI and data engineering consultant by night
- Python and data engineering trainer
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- Contributed a chapter to the book "97 Things Every Data Engineer Should Know"
- Twitter: @mikulskibartosz
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