Pandas Learning: Sorting series and Dataframe __pandas

This question mainly writes the method of sorting series and dataframe according to index or value

Code:

#coding =utf-8
Import pandas as PD
import numpy as NP
#以下实现排序功能.
SERIES=PD. Series ([3,4,1,6],index=[' B ', ' A ', ' d ', ' C '])
FRAME=PD. Dataframe ([[2,4,1,5],[3,1,4,5],[5,1,4,2]],columns=[' B ', ' A ', ' d ', ' C '],index=[' one ', ' two ', ' three '])
print
the frame print series
print ' series is sorted by index: '
print series.sort_index ()
print ' series sorted by value: '
Print series.sort_values ()
print ' dataframe sorted by row index in descending order (default ascending sort, adjust ascending parameters): '
print Frame.sort_index ( Ascending=false)
print ' dataframe sorted by column index: '
print Frame.sort_index (axis=1)
print ' Dataframe Sort by value: '
print frame.sort_values (by= ' a ')
print ' Sorted through multiple indexes: '
print frame.sort_values (by= [' A ', ' C '])

Experimental results:

b A D C
One 2 4 1 5
Two 3 1 4 5
Three 5 1 4 2
B 3
A 4
D 1
C 6
Dtype:int64
Series Sort by index:
A 4
B 3
C 6
D 1
Dtype:int64
Series are sorted by value:
D 1
B 3
A 4
C 6
Dtype:int64
Dataframe sorted by row index in descending order (default ascending sort, adjust ascending parameters):
b A D C
Two 3 1 4 5
Three 5 1 4 2
One 2 4 1 5
Dataframe sorts according to the column index:
A B c D
One 4 2 5 1
Two 1 3 5 4
Three 1 5 2 4
Dataframe Sort By Value:
b A D C
Two 3 1 4 5
Three 5 1 4 2
One 2 4 1 5
Sort by two indexes:
b A D C
Three 5 1 4 2
Two 3 1 4 5
One 2 4 1 5
[Finished in 1.0s]