DataFrame.mode(axis=0, numeric_only=False)
[source]
Gets the mode(s) of each element along the axis selected. Adds a row for each mode per label, fills in gaps with nan.
Note that there could be multiple values returned for the selected axis (when more than one item share the maximum frequency), which is the reason why a dataframe is returned. If you want to impute missing values with the mode in a dataframe df
, you can just do this: df.fillna(df.mode().iloc[0])
Parameters: |
axis : {0 or ‘index’, 1 or ‘columns’}, default 0
numeric_only : boolean, default False if True, only apply to numeric columns |
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Returns: |
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>>> df = pd.DataFrame({'A': [1, 2, 1, 2, 1, 2, 3]}) >>> df.mode() A 0 1 1 2
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http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.DataFrame.mode.html