Sort a Pandas Series in Python

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

Output:

The output shows that the NaN (not a number) value is given the first place in the sorted series.