Sort a Pandas Series in Python

Last Updated : 05 Jul, 2021

Series is a one-dimensional labeled array capable of holding data of the type integer, string, float, python objects, etc. The axis labels are collectively called index.

Now, Let's see a program to sort a Pandas Series.

For sorting a pandas series the Series.sort_values() method is used.

Syntax: Series.sort_values(axis=0, ascending=True, inplace=False, kind=’quicksort’, na_position=’last’)Sorted

Returns: Sorted series

Examples 1: Sorting a numeric series in ascending order.

Python3

# importing pandas as pd import pandas as pd  # define a numeric series s = pd.Series([100, 200, 54.67,                 300.12, 400])  # print the unsorted series s

Output:

Now we will use Series.sort_values() method to sort a numeric series in ascending order.

Python3

# sorting series s with  # s.sort_value() method in # ascending order sorted_series = s.sort_values(ascending                                = True) # print the sorted series sorted_series

Output:

From the output, we can see that the numeric series is sorted in ascending order.

Example 2: Sorting a numeric series in descending order.

Python3

# importing pandas as pd import pandas as pd  # define a numeric series s = pd.Series([100, 200, 54.67,                 300.12, 400])  # print the unsorted series s

Output:

Now we will use Series.sort_values() method to sort a numeric series in descending order.

Python3

# sorting the series s with  # s.sort_values() method # in descending order sorted_series = s.sort_values(ascending                               = False) # printing the sorted series sorted_series

Output:

From the output, we can see that the numeric series is sorted in descending order.

Example 3: Sorting a series of strings.

Python3

# importing pandas as pd import pandas as pd  #d efine a string series s s = pd.Series(["OS","DBMS","DAA",                "TOC","ML"])  # print the unsorted series s

Output:

Now we will use Series.sort_values() method to sort a series of strings.

Python3

# sorting the series s with  # s.sort_values() method # in ascending order sorted_series = s.sort_values(ascending                                = True) # printing the sorted series sorted_series

Output:

From the output, we can see that the string series is sorted in a lexicographically ascending order.

Example 4: Sorting values inplace.

Python3

# importing numpy as np import numpy as np  # importing pandas as pd import pandas as pd  # define a numeric series # s with a NaN s = pd.Series([np.nan, 1, 3,                10, 5])  # print the unsorted series s

Output:

Now we will use Series.sort_values() method to sort values inplace

Python3

# sorting the series s with  # s.sort_values() method in  # descending order and inplace s.sort_values(ascending  = False,                               inplace = True)  # printing the sorted series s

Output:

The output shows that the inplace sorting in the Pandas Series.

Example 5: Sorting values in the series by putting NaN first.

Python3

# importing numpy as np import numpy as np  # importing pandas as pd import pandas as pd   # define a numeric series # s with a NaN s = pd.Series([np.nan, 1, 3,                10, 5])  # print the unsorted series s

Output:

Now we will use Series.sort_values() method to sort values in the series by putting NaN first.

Python3

# sorting the series s with  # s.sort_values() method in  # ascending order with na  # position at first sorted_series = s.sort_values(na_position =                               'first')  # printing the sorted series sorted_series