32. fillna | fillna Function In Python Pandas | Handling Missing Values Using Pandas | Part 5
In this video, I have covered very clearly all the parameters of fillna method.
Fillna Fills NaN values using the specified method.
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DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None)
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value:
It is a value that is used to fill the null values.
scalar, dict, Series, or DataFrame.
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DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None)
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Method:
Method to use for filling holes in reindexed Series.
pad / ffill: propagate last valid observation forward to next.
(Top To Bottom)
backfill / bfill: use next valid observation to fill gap.
(Bottom To Top)
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DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None)
axis:
axis takes int or string value for - rows: Input can be 0 or ‘index’.
Columns: Input can be 1 or
‘columns’.
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inplace: It is a boolean which makes the changes in the data frame itself if True.
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DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None)
limit: int, default None
If the method is specified, this is the maximum number of consecutive NaN values to forward/backward fill.
Must be greater than 0 if not None.
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downcast :
It takes a dict or the string ‘infer’.
which specifies what dtype to downcast to which one. Like Float64 to int64.
Github Link: https://github.com/PRIYANG-BHATT/Data...
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