Polars is a blazingly fast DataFrame library implemented in Rust and designed for data manipulation and analysis. It provides functionalities similar to pandas in Python, making it suitable for working with large datasets efficiently.
Series.arg_unique()methodIn Polars, the Series.arg_unique() method is used to obtain a series containing unique indexes. This function returns a series where each value represents the index position of the unique elements present in the original series.
The syntax for Series.arg_unique() method is as follows:
Series.arg_unique()
To demonstrate the usage of Series.arg_unique() method, let’s consider the following example. We take a series named alpha with some mixed repeated values, and then we will apply the Series.arg_unique() method on the alpha series:
import polars as pl# Create a seriess = pl.Series("alpha", [10, 22, 21, 22, 10, 11, 9])# Obtain unique indicesunique_indexes = s.arg_unique()print(unique_indexes)
Let’s discuss the above code step by step:
Line 4: We create a series s with values [10, 22, 21, 22, 10, 11, 9].
Line 7: We applied the arg_unique() function to obtain unique indexes. The resulting series contains unique indices corresponding to the unique elements in the original series.
Line 9: We print the result.
The Series.arg_unique() function in Polars is useful for obtaining unique indexes from a series. It facilitates data analysis and manipulation tasks by providing a convenient way to work with unique elements in a series efficiently.
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