极客教程在pandas DataFrame中对行进行排序
Pandas DataFrame是二维的大小可变的，可能是异质的表格数据结构，有标记的轴（行和列）。在处理数据时，我们经常需要对行和列做某些操作。
让我们看看如何对pandas DataFrame中的行进行排序。
代码#1:按科学排序的行数
# import modules
import pandas as pd
# create dataframe
data = {'name': ['Simon', 'Marsh', 'Gaurav', 'Alex', 'Selena'],
'Maths': [8, 5, 6, 9, 7],
'Science': [7, 9, 5, 4, 7],
'English': [7, 4, 7, 6, 8]}
df = pd.DataFrame(data)
# Sort the dataframe’s rows by Science,
# in descending order
a = df.sort_values(by ='Science', ascending = 0)
print("Sorting rows by Science:\n \n", a)
Python
输出:
Sorting rows by Science:
English Maths Science name
1 4 5 9 Marsh
0 7 8 7 Simon
4 8 7 7 Selena
2 7 6 5 Gaurav
3 6 9 4 Alex
Python
代码#2：按数学排序行，然后按英语排序行。
# import modules
import pandas as pd
# create dataframe
data = {'name': ['Simon', 'Marsh', 'Gaurav', 'Alex', 'Selena'],
'Maths': [8, 5, 6, 9, 7],
'Science': [7, 9, 5, 4, 7],
'English': [7, 4, 7, 6, 8]}
df = pd.DataFrame(data)
# Sort the dataframe’s rows by Maths
# and then by English, in ascending order
b = df.sort_values(by =['Maths', 'English'])
print("Sort rows by Maths and then by English: \n\n", b)
Python
输出:
Sort rows by Maths and then by English:
English Maths Science name
1 4 5 9 Marsh
2 7 6 5 Gaurav
4 8 7 7 Selena
0 7 8 7 Simon
3 6 9 4 Alex
Python
代码#3：如果你想先获得缺失值。
import pandas as pd
# create dataframe
data = {'name': ['Simon', 'Marsh', 'Gaurav', 'Alex', 'Selena'],
'Maths': [8, 5, 6, 9, 7],
'Science': [7, 9, 5, 4, 7],
'English': [7, 4, 7, 6, 8]}
df = pd.DataFrame(data)
a = df.sort_values(by ='Science', na_position ='first' )
print(a)
Python
输出:
English Maths Science name
3 6 9 4 Alex
2 7 6 5 Gaurav
0 7 8 7 Simon
4 8 7 7 Selena
1 4 5 9 Marsh
Python
由于本例中没有缺失值，因此将产生与上述相同的输出，但以升序排序。