How to replace with Pandas DataFrame, which is useful for data analysis (easy)

Personal notes you see when doing data replacement in pandas.

Conclusion

data_x = features_df
data_x.width = data_x.width.replace('Very expensive', 333)

Now you can replace'very expensive' with 333

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