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I have a dataframe with nans in it:
>>>df.head() Out[1]: JPM US SMALLER COMPANIES C ACC 1990-01-02 NaN 1990-01-03 NaN 1990-01-04 NaN 1990-01-05 NaN 1990-01-08 NaN I have another dataframe with values in it:
>>>t.head() Out[1]: 1990-01-02 51.95 1990-01-03 52.63 1990-01-04 53.04 1990-01-05 52.07 1990-01-08 51.73 Name: JPM US SMALLER COMPANIES C ACC, dtype: float64 Unfortunately, df.fillna does not appear to be working for me:
>>>df.fillna( t ).head() Out[1]: JPM US SMALLER COMPANIES C ACC 1990-01-02 NaN 1990-01-03 NaN 1990-01-04 NaN 1990-01-05 NaN 1990-01-08 NaN [5 rows x 1 columns] Why is this happening? I am on pandas 0.13.1
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Definition and UsageThe fillna() method replaces the NULL values with a specified value. The fillna() method returns a new DataFrame object unless the inplace parameter is set to True , in that case the fillna() method does the replacing in the original DataFrame instead.
The fillna() function is used to fill NA/NaN values using the specified method. Value to use to fill holes (e.g. 0), alternately a dict/Series/DataFrame of values specifying which value to use for each index (for a Series) or column (for a DataFrame). Values not in the dict/Series/DataFrame will not be filled.
You need inplace=True
df[1].fillna(0, inplace=True) You need to assign the value df = df.fillna( t )
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