pandas 级联 concat append

连接的一个有用的快捷方式是在Series和DataFrame实例的append方法。这些方法实际上早于concat()方法。 它们沿axis=0连接

#encoding:utf8
import pandas as pd
one = pd.DataFrame({
         'Name': ['Alex', 'Amy', 'Allen', 'Alice', 'Ayoung'],
         'subject_id':['sub1','sub2','sub4','sub6','sub5'],
         'Marks_scored':[98,90,87,69,78]},
         index=[1,2,3,4,5])
two = pd.DataFrame({
         'Name': ['Billy', 'Brian', 'Bran', 'Bryce', 'Betty'],
         'subject_id':['sub2','sub4','sub3','sub6','sub5'],
         'Marks_scored':[89,80,79,97,88]},
         index=[1,2,3,4,5])
print("one:")
print(one)
print("two:")
print(two)
rs = pd.concat([one,two])
print("rs = pd.concat([one,two])")
print(rs)
print("rs = pd.concat([one,two],keys=['x','y'])")
rs = pd.concat([one,two],keys=['x','y'])
print(rs)
print("结果的索引是重复的; 每个索引重复。如果想要生成的对象必须遵循自己的索引，请将ignore_index设置为True:")
print("rs = pd.concat([one,two],keys=['x','y'],ignore_index=True)")
rs = pd.concat([one,two],keys=['x','y'],ignore_index=True)
print(rs)
print("观察，索引完全改变，键也被覆盖。如果需要沿axis=1添加两个对象，则会添加新列:")
rs = pd.concat([one,two],axis=1)
print(rs)
print("rs = one.append(two):")
rs = one.append(two)
print(rs)
print("append()函数也可以带多个对象:")
rs = one.append([two,one,two])
print(rs)

D:\Download\python3\python3.exe D:/Download/pycharmworkspace/s.py
one:
   Marks_scored    Name subject_id
1            98    Alex       sub1
2            90     Amy       sub2
3            87   Allen       sub4
4            69   Alice       sub6
5            78  Ayoung       sub5
two:
   Marks_scored   Name subject_id
1            89  Billy       sub2
2            80  Brian       sub4
3            79   Bran       sub3
4            97  Bryce       sub6
5            88  Betty       sub5
rs = pd.concat([one,two])
   Marks_scored    Name subject_id
1            98    Alex       sub1
2            90     Amy       sub2
3            87   Allen       sub4
4            69   Alice       sub6
5            78  Ayoung       sub5
1            89   Billy       sub2
2            80   Brian       sub4
3            79    Bran       sub3
4            97   Bryce       sub6
5            88   Betty       sub5
rs = pd.concat([one,two],keys=['x','y'])
     Marks_scored    Name subject_id
x 1            98    Alex       sub1
  2            90     Amy       sub2
  3            87   Allen       sub4
  4            69   Alice       sub6
  5            78  Ayoung       sub5
y 1            89   Billy       sub2
  2            80   Brian       sub4
  3            79    Bran       sub3
  4            97   Bryce       sub6
  5            88   Betty       sub5
结果的索引是重复的; 每个索引重复。如果想要生成的对象必须遵循自己的索引，请将ignore_index设置为True:
rs = pd.concat([one,two],keys=['x','y'],ignore_index=True)
   Marks_scored    Name subject_id
0            98    Alex       sub1
1            90     Amy       sub2
2            87   Allen       sub4
3            69   Alice       sub6
4            78  Ayoung       sub5
5            89   Billy       sub2
6            80   Brian       sub4
7            79    Bran       sub3
8            97   Bryce       sub6
9            88   Betty       sub5
观察，索引完全改变，键也被覆盖。如果需要沿axis=1添加两个对象，则会添加新列:
   Marks_scored    Name subject_id  Marks_scored   Name subject_id
1            98    Alex       sub1            89  Billy       sub2
2            90     Amy       sub2            80  Brian       sub4
3            87   Allen       sub4            79   Bran       sub3
4            69   Alice       sub6            97  Bryce       sub6
5            78  Ayoung       sub5            88  Betty       sub5
rs = one.append(two):
   Marks_scored    Name subject_id
1            98    Alex       sub1
2            90     Amy       sub2
3            87   Allen       sub4
4            69   Alice       sub6
5            78  Ayoung       sub5
1            89   Billy       sub2
2            80   Brian       sub4
3            79    Bran       sub3
4            97   Bryce       sub6
5            88   Betty       sub5
append()函数也可以带多个对象:
   Marks_scored    Name subject_id
1            98    Alex       sub1
2            90     Amy       sub2
3            87   Allen       sub4
4            69   Alice       sub6
5            78  Ayoung       sub5
1            89   Billy       sub2
2            80   Brian       sub4
3            79    Bran       sub3
4            97   Bryce       sub6
5            88   Betty       sub5
1            98    Alex       sub1
2            90     Amy       sub2
3            87   Allen       sub4
4            69   Alice       sub6
5            78  Ayoung       sub5
1            89   Billy       sub2
2            80   Brian       sub4
3            79    Bran       sub3
4            97   Bryce       sub6
5            88   Betty       sub5

Process finished with exit code 0