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ParametersReturn ValueExamplesBasic usageUnique tuples
chevron_left General Functions
Method bdate_rangeMethod concatMethod crosstabMethod cutMethod date_rangeMethod factorizeMethod get_dummiesMethod infer_freqMethod interval_rangeMethod isnullMethod merge_asofMethod merge_orderedMethod notnullMethod period_rangeMethod pivotMethod pivot_tableMethod qcutMethod read_csvMethod to_datetimeMethod to_numericMethod to_timedeltaMethod uniqueMethod wide_to_long
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chevron_left General Functions
Method bdate_rangeMethod concatMethod crosstabMethod cutMethod date_rangeMethod factorizeMethod get_dummiesMethod infer_freqMethod interval_rangeMethod isnullMethod merge_asofMethod merge_orderedMethod notnullMethod period_rangeMethod pivotMethod pivot_tableMethod qcutMethod read_csvMethod to_datetimeMethod to_numericMethod to_timedeltaMethod uniqueMethod wide_to_long
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Pandas | unique method

Pandas
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General Functions
schedule Jul 1, 2022
Last updated
local_offer Python●Pandas
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Pandas unique(~) method returns the unique values of the input array. The order of the returned values follow their original order in the input array.

Parameters

1. valueslink | array-like

The input array. Typically this is a standard list, a Series or a NumPy array.

Return Value

The return type depends on the type of values:

Input type

Return type

Index

Index

Categorical

Categorical

Array-like

Numpy array

Examples

Basic usage

To find the unique values of a Series:

s = pd.Series([7,6,5,7])
pd.unique(s)
array([7, 6, 5])

Note the following:

  • the unique values respect the original ordering

  • the return type is a Numpy array since the input is a list

Unique tuples

As you would expect, a pair of tuples is considered to be unique when at least one pair of items does not match up:

s = pd.Series([("A","B"),("B","B"),("A","B")])
pd.unique(s)
array([('A', 'B'), ('B', 'B')], dtype=object)
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Published by Isshin Inada
Edited by 0 others
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Official Pandas Documentation
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.unique.html
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