df = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
'B': ['B0', 'B1', 'B2', 'B3'],
'C': ['C0', 'C1', 'C2', 'C3'],
'D': ['D0', 'D1', 'D2', 'D3']},
index=[0, 1, 2, 3])
df
for index, row in df.iterrows(): # 按行遍历
print("index:", index)
print("--------------")
print("row:", row)
print("--------------")
Output exceeds the size limit. Open the full output data in a text editor
index: 0
--------------
row: A A0
B B0
C C0
D D0
Name: 0, dtype: object
--------------
index: 1
--------------
row: A A1
B B1
C C1
D D1
Name: 1, dtype: object
--------------
index: 2
--------------
row: A A2
B B2
C C2
D D2
Name: 2, dtype: object
--------------
index: 3
B B3
C C3
D D3
Name: 3, dtype: object
--------------
for index, column in df.iteritems(): # 按列遍历
print("index:", index)
print("--------------")
print("column:", column)
print("--------------")
Output exceeds the size limit. Open the full output data in a text editor
index: A
--------------
column: 0 A0
1 A1
2 A2
3 A3
Name: A, dtype: object
--------------
index: B
--------------
column: 0 B0
1 B1
2 B2
3 B3
Name: B, dtype: object
--------------
index: C
--------------
column: 0 C0
1 C1
2 C2
3 C3
Name: C, dtype: object
--------------
index: D
1 D1
2 D2
3 D3
Name: D, dtype: object
--------------
for row in df.itertuples():
print(row) # 输出每一行
Pandas(Index=0, A='A0', B='B0', C='C0', D='D0')
Pandas(Index=1, A='A1', B='B1', C='C1', D='D1')
Pandas(Index=2, A='A2', B='B2', C='C2', D='D2')
Pandas(Index=3, A='A3', B='B3', C='C3', D='D3')
for column in df.iteritems():
print(column) # 输出各列
('A', 0 A0
1 A1
2 A2
3 A3
Name: A, dtype: object)
('B', 0 B0
1 B1
2 B2
3 B3
Name: B, dtype: object)
('C', 0 C0
1 C1
2 C2
3 C3
Name: C, dtype: object)
('D', 0 D0
1 D1
2 D2
3 D3
Name: D, dtype: object)
(‘C’, 0 C0
1 C1
2 C2
3 C3
Name: C, dtype: object)
(‘D’, 0 D0
1 D1
2 D2
3 D3
Name: D, dtype: object)