Implementation of Sort Function sort_values of of Pandas
- 2021-07-13 05:35:30
- OfStack
1. Use of the sort_values () function
The sort_values () function in pandas is similar in principle to order by in SQL and sorts a dataset by the data in a field, either by the data in a specified column or by the data in a specified row.
2. Specific arguments for the sort_values () function
Usage:
DataFrame.sort_values(by= ' ##',axis=0,ascending=True, inplace=False, na_position= ' last')
Parameter description
参数 | 说明 |
---|---|
by | 指定列名(axis=0或'index')或索引值(axis=1或'columns') |
axis | 若axis=0或'index',则按照指定列中数据大小排序;若axis=1或'columns',则按照指定索引中数据大小排序,默认axis=0 |
ascending | 是否按指定列的数组升序排列,默认为True,即升序排列 |
inplace | 是否用排序后的数据集替换原来的数据,默认为False,即不替换 |
na_position | {‘first',‘last'},设定缺失值的显示位置 |
3. Examples of usage of sort_values
Create a data box
# Use a dictionary dict Create a data box
import numpy as np
import pandas as pd
df=pd.DataFrame({'col1':['A','A','B',np.nan,'D','C'],
'col2':[2,1,9,8,7,7],
'col3':[0,1,9,4,2,8]
})
print(df)
>>>
col1 col2 col3
0 A 2 0
1 A 1 1
2 B 9 9
3 NaN 8 4
4 D 7 2
5 C 7 8
Sort by column 1 and put the null value of this column first
# Pursuant to paragraph 1 Column, and put the null value of the column first
print(df.sort_values(by=['col1'],na_position='first'))
>>>
col1 col2 col3
3 NaN 8 4
0 A 2 0
1 A 1 1
2 B 9 9
5 C 7 8
4 D 7 2
Sort in descending numeric order by column 2. 3
# Pursuant to paragraph 2. 3 Column, numeric descending sort
print(df.sort_values(by=['col2','col3'],ascending=False))
>>>
col1 col2 col3
2 B 9 9
3 NaN 8 4
5 C 7 8
4 D 7 2
0 A 2 0
1 A 1 1
Sort according to the values in Column 1, sort in descending order, and replace the original data
# According to Article 1 Column, sorted in descending order, and replaces the original data
df.sort_values(by=['col1'],ascending=False,inplace=True,
na_position='first')
print(df)
>>>
col1 col2 col3
3 NaN 8 4
4 D 7 2
5 C 7 8
2 B 9 9
1 A 1 1
0 A 2 0
Sort in descending order by the value of the row with index value 0, that is, the first row
x = pd.DataFrame({'x1':[1,2,2,3],'x2':[4,3,2,1],'x3':[3,2,4,1]})
print(x)
# By index value is 0 The line of, that is, the 1 To sort in descending order by the value of the row
print(x.sort_values(by =0,ascending=False,axis=1))
>>>
x1 x2 x3
0 1 4 3
1 2 3 2
2 2 2 4
3 3 1 1
x2 x3 x1
0 4 3 1
1 3 2 2
2 2 4 2
3 1 1 3