how to get distinct value in a column dataframe in python
df.column.unique()how to get distinct value in a column dataframe in python
df.column.unique()pandas distinct
>gapminder['continent'].unique()
array(['Asia', 'Europe', 'Africa', 'Americas', 'Oceania'], dtype=object)pandas count distinct values in a column
Series.value_counts(self, normalize=False, sort=True, ascending=False, bins=None, dropna=True)python extract values that have different values in a column
df = pd.DataFrame({'author':['a', 'a', 'b'], 'products':['sr1', 'sr2', 'sr2']}) # Create df
group = df.groupby('author') # Group by author used as index
df2 = group.apply(lambda x: x['subreddit'].unique()) # List of all product per author
df2 = df2.apply(pd.Series) # Split products in multiple columnsReturns a new DataFrame containing the distinct rows in this DataFrame
# Returns a new DataFrame containing the distinct rows in this DataFrame
df.ditinct().count()
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