Nulls¶
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Clean.
drop_nan
(col: str = None, method: str = 'all', **kwargs)¶ Drop rows with NaN values from the main dataframe
Parameters: - col (str, optional) – name of the column, defaults to None. Drops in
- method (str, optional) –
how
param fordf.dropna
, defaults to “all” - **kwargs (optional) – params for
df.dropna
Example: ds.drop_nan("mycol")
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Clean.
nan_empty
(col: str)¶ Fill empty values with NaN values
Parameters: col (str) – name of the colum Example: ds.nan_empty("mycol")
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Clean.
zero_nan
(*cols)¶ Converts zero values to nan values in selected columns
Parameters: *cols (str, at least one) – names of the colums Example: ds.zero_nan("mycol1", "mycol2")
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Clean.
fill_nan
(val: str, *cols)¶ Fill NaN values with new values in the main dataframe
Parameters: - val (str) – new value
- *cols (str, at least one) – names of the colums
Example: ds.fill_nan("new value", "mycol1", "mycol2")
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Clean.
fill_nulls
(col: str)¶ Fill all null values with NaN values in a column. Null values are
None
or en empty stringParameters: col (str) – column name Example: ds.fill_nulls("mycol")