I want to iterate over each row and and want to check in each column if value is NaN if it is then i want to replace it with the previous value of the same row which is not null.
I believe the prefer way would be using lamba function. But still not figure out to code it Note: I have thousands of rows and 200 columns in each row
The following should do the work:
df.fillna(method='ffill', axis=1, inplace=True)
Can you please clarify what you want to be done with NaNs in first column(s)?
我想你可以用这个 -
your_df.apply(lambda x : x.fillna(method='ffill'), axis=1)
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