.sort_values()

The .sort_values() function sorts values in a DataFrame along the selected axis and returns a DataFrame with sorted values or None.

dataframevalue.sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, key=None)

.sort_values() uses the following parameters:

• by: A label or a list of labels to sort by (levels can also be specified if applicable).
• axis: Specify which axis will be sorted (0 or index, 1 or columns), it defaults to 0.
• ascending: Specify whether the sort will be ascending or descending (True or False), it defaults to True.
• inplace: By setting it to True, the operation will be performed on the original DataFrame and the function will return None, it defaults to False.
• kind: Choose which algorithm to use: ‘quicksort’, ‘mergesort’, ‘heapsort’, or ‘stable’, it defaults to quicksort. For more information click here.
• na_position: Specify where to put the NaN values, it defaults to last.
• ignore_index: Ignore the original index and put a new ascending set of values in its place. The default is False.
• key: Apply a function before sorting.

In the example below a DataFrame is created and sorted in multiple ways by applying the .sort_values() method and altering the parameters passed.

# Import pandas and numpy
import pandas as pd
import numpy as np

# Create the DataFrame
df = pd.DataFrame({'numbers': [2, 2, 5, 9, np.nan, 1],
                   'letters': ['D', 'A', 'B', 'Z', np.nan, 'C']})

# Sort by the column 'numbers'
print(df.sort_values(by=['numbers']), end='\n\n')

# Sort by the columns 'numbers' and 'letters'
print(df.sort_values(by=['numbers', 'letters']), end='\n\n')

# Sort by the column 'numbers' and put NaN values first
print(df.sort_values(by=['numbers'], na_position='first'), end='\n\n')

The output will look like this:

   numbers letters
5      1.0       C
0      2.0       D
1      2.0       A
2      5.0       B
3      9.0       Z
4      NaN     NaN

   numbers letters
5      1.0       C
1      2.0       A
0      2.0       D
2      5.0       B
3      9.0       Z
4      NaN     NaN

   numbers letters
4      NaN     NaN
5      1.0       C
0      2.0       D
1      2.0       A
2      5.0       B
3      9.0       Z