Question

wowee .....如何使用python和pandas的iterrows？如果我进行行迭代，我是否应该无法访问带有['COL_NAME']行的col？

以下是col名称：

print df
Int64Index: 152 entries, 0 to 151
Data columns:
Date          152  non-null values
Time          152  non-null values
Time Zone     152  non-null values
Currency      152  non-null values
Event         152  non-null values
Importance    152  non-null values
Actual        127  non-null values
Forecast      86  non-null values
Previous      132  non-null values
dtypes: object(9)

for row in df.iterrows():
    print row['Date']

Traceback (most recent call last):
  File "/home/ubuntu/workspace/calandar.py", line 34, in <module>
    print row['Date']
TypeError: tuple indices must be integers, not str

如果我打印1行：

(0, Date                                                 Sun Apr 13
Time                                                      17:30
Time Zone                                                   GMT
Currency                                                    USD
Event         USD Fed's Stein Speaks on Financial Stability ...
Importance                                                  Low
Actual                                                      NaN
Forecast                                                    NaN
Previous                                                    NaN
Name: 0)

Answer 1

iterrows为您提供(index, row)元组而不仅仅是行，因此您应该能够以与您想的相同的方式访问列：

for index, row in df.iterrows():
    print row['Date']

Answer 2

如果要遍历数据库并将函数应用于每一行，您可能还需要考虑应用函数

def print_row(r):
    print r['Date']

df.apply(print_row, axis = 1)

python和pandas - 如何使用iterrows访问列

2 个答案: