Examples

import numpy as np
import pandas as pd

df = pd.DataFrame({
     'c1': ['P', 'P', 'Q', np.nan, 'S', 'R'],
     'c2': [2, 4, 9, 8, 7, 5],
     'c3': [0, 4, 9, 5, 2, 3],
})
df

	c1	c2	c3
0	P	2	0
1	P	4	4
2	Q	9	9
3	NaN	8	5
4	S	7	2
5	R	5	3

Sort by c1:

df.sort_values(by=['c1'])

	c1	c2	c3
0	P	2	0
1	P	4	4
2	Q	9	9
5	R	5	3
4	S	7	2
3	NaN	8	5

Sort by multiple columns:

df.sort_values(by=['c1', 'c2'])

	c1	c2	c3
0	P	2	0
1	P	4	4
2	Q	9	9
5	R	5	3
4	S	7	2
3	NaN	8	5

Sort Descending:

df.sort_values(by='c1', ascending=False)

	c1	c2	c3
4	S	7	2
5	R	5	3
2	Q	9	9
0	P	2	0
1	P	4	4
3	NaN	8	5

Putting NAs first:

df.sort_values(by='c1', ascending=False, na_position='first')

	c1	c2	c3
3	NaN	8	5
4	S	7	2
5	R	5	3
2	Q	9	9
0	P	2	0
1	P	4	4