Sometimes, we want to replace NaN values by zeroes in a column of a Python Pandas Dataframe.
In this article, we’ll look at how to replace NaN values by zeroes in a column of a Python Pandas Dataframe.
How to replace NaN values by zeroes in a column of a Python Pandas Dataframe?
To replace NaN values by zeroes in a column of a Python Pandas Dataframe, we can use the DataFrame’s fillna method.
For instance, we write:
import pandas as pd
df = pd.DataFrame({'col': [1, 2, 3, None, None]}).fillna(0)
print(df)
We create a DataFrame with pd.DataFrame({'col': [1, 2, 3, None, None]}).
None are the NaN values in the DataFrame.
Then we call fillna to replace None with 0 and assign the DataFrame to df.
Therefore, df is:
col
0 1.0
1 2.0
2 3.0
3 0.0
4 0.0
Conclusion
To replace NaN values by zeroes in a column of a Python Pandas Dataframe, we can use the DataFrame’s fillna method.
