文章目录

  • 1、iterrows()
  • 2、iteritems()
  • 3、itertuples()
  • iterrows(): 将DataFrame迭代为(insex, Series)对。
  • itertuples(): 将DataFrame迭代为元祖。
  • iteritems(): 将DataFrame迭代为(列名, Series)对

有如下DataFrame数据

import pandas as pdinp = [{'c1':10, 'c2':100}, {'c1':11, 'c2':110}, {'c1':12, 'c2':123}]
df = pd.DataFrame(inp)print(df)# 输出c1   c2
0  10  100
1  11  110
2  12  123

1、iterrows()

for date, row in df.iterrows():print(date)

输出

0
1
2
for date, row in df.iterrows():print(row)

输出

c1     10
c2    100
Name: 0, dtype: int64
c1     11
c2    110
Name: 1, dtype: int64
c1     12
c2    123
Name: 2, dtype: int64

对于每一行，通过列名访问对应的元素

for date, row in df.iterrows():print(row['c1'], row['c2'])

输出

10 100
11 110
12 123

2、iteritems()

for date, row in df.iteritems():print(date)

输出

c1
c2
for date, row in df.iteritems():print(row)

输出

0    10
1    11
2    12
Name: c1, dtype: int64
0    100
1    110
2    123
Name: c2, dtype: int64
for date, row in df.iteritems():print(row[0], row[1], row[2])

输出

10 11 12
100 110 123

3、itertuples()

for row in df.itertuples():print(row)

输出

Pandas(Index=0, c1=10, c2=100)
Pandas(Index=1, c1=11, c2=110)
Pandas(Index=2, c1=12, c2=123)
for row in df.itertuples():print(getattr(row, 'c1'), getattr(row, 'c2'))

输出

10 100
11 110
12 123