Pandas Series: sort_values() function

Last update on September 15 2022 12:57:49 (UTC/GMT +8 hours)

Sort Pandas series in ascending or descending order by some criterion

The sort_values() function is used to sort by the values.

Sort a Series in ascending or descending order by some condition.

Syntax:

Series.sort_values(self, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last')

Parameters:

Name	Description	Type/Default Value	Required / Optional
axis	Axis to direct sorting. The value ‘index’ is accepted for compatibility with DataFrame.sort_values.	{0 or ‘index’} Default Value: 0	Required
ascending	If True, sort values in ascending order, otherwise descending.	bool Default Value: True	Required
inplace	Sort ascending vs. descending.	bool Default Value: True	Required
inplace	If True, perform operation in-place.	bool Default Value: False	Required
kind	Choice of sorting algorithm. See also numpy.sort() for more information. ‘mergesort’ is the only stable algorithm.	{‘quicksort’, ‘mergesort’ or ‘heapsort’} Default Value: ‘quicksort’	Required
na_position	Argument ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end.	{‘first’ or ‘last’} Default Value: ‘last’	Required

Returns: Series - Series ordered by values.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([np.nan, 2, 4, 10, 7])
s

Output:

0     NaN
1     2.0
2     4.0
3    10.0
4     7.0
dtype: float64

Example - Sort values ascending order (default behaviour):

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([np.nan, 2, 4, 10, 7])
s.sort_values(ascending=True)

Output:

1     2.0
2     4.0
4     7.0
3    10.0
0     NaN
dtype: float64

Example - Sort values descending order:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([np.nan, 2, 4, 10, 7])
s.sort_values(ascending=False)

Output:

3    10.0
4     7.0
2     4.0
1     2.0
0     NaN
dtype: float64

Example - Sort values inplace:

Python-Pandas Code:

import numpy as np
import pandas as pd
s.sort_values(ascending=False, inplace=True)
s

Output:

3    10.0
4     7.0
2     4.0
1     2.0
0     NaN
dtype: float64

Example - Sort values putting NAs first:

Python-Pandas Code:

import numpy as np
import pandas as pd
s.sort_values(ascending=False, inplace=True)
s.sort_values(na_position='first')

Output:

0     NaN
1     2.0
2     4.0
4     7.0
3    10.0
dtype: float64

Example - Sort a series of strings:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(['t', 'q', 's', 'p', 'r'])
s

Output:

0    t
1    q
2    s
3    p
4    r
dtype: object

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(['t', 'q', 's', 'p', 'r'])
s.sort_values()

Output:

3    p
1    q
4    r
2    s
0    t
dtype: object

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