modin.pandas.Series.duplicated¶

Series.duplicated(keep: Literal['first', 'last', False] = 'first')[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.17.0/src/snowflake/snowpark/modin/pandas/series.py#L1058-L1067)¶

Indicate duplicate Series values.

Duplicated values are indicated as True values in the resulting Series. Either all duplicates, all except the first or all except the last occurrence of duplicates can be indicated.

Parameters:

keep ({'first', 'last', False}, default 'first') –

Method to handle dropping duplicates:

• ’first’ : Mark duplicates as True except for the first occurrence.

• ’last’ : Mark duplicates as True except for the last occurrence.

• False : Mark all duplicates as True.

Returns:

Snowpark pandas Series indicating whether each value has occurred in the preceding values.

Return type:

Snowpark pandas Series[bool]

See also

Index.duplicated

Equivalent method on pandas.Index.

DataFrame.duplicated

Equivalent method on pandas.DataFrame.

Series.drop_duplicates

Remove duplicate values from Series.

Examples

By default, for each set of duplicated values, the first occurrence is set on False and all others on True:

>>> animals = pd.Series(['llama', 'cow', 'llama', 'beetle', 'llama'])
>>> animals.duplicated()
0    False
1    False
2     True
3    False
4     True
dtype: bool

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which is equivalent to

>>> animals.duplicated(keep='first')
0    False
1    False
2     True
3    False
4     True
dtype: bool

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By using ‘last’, the last occurrence of each set of duplicated values is set on False and all others on True:

>>> animals.duplicated(keep='last')
0     True
1    False
2     True
3    False
4    False
dtype: bool

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By setting keep on False, all duplicates are True:

>>> animals.duplicated(keep=False)
0     True
1    False
2     True
3    False
4     True
dtype: bool

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