1. name      object
2. ID        object
3. age       object
4. sex       object
5. hobbey    object
6. dtype: object
7.    name    ID  age   sex hobbey
8. 0   Bob     1  NaN     男    打篮球
9. 1  LiSa     2   28     女   打羽毛球
10. 2  Mary         38     女   打乒乓球
11. 3  Alan  None       None
12. -----------------------------------------
13. 0 ['Bob', 1, nan, '男', '打篮球']
14. 1 ['LiSa', 2, 28, '女', '打羽毛球']
15. 2 ['Mary', ' ', 38, '女', '打乒乓球']
16. 3 ['Alan', None, '', None, '']

1. import pandas as pd
2. import numpy as np
3. 
4. contents={"name": ['Bob',        'LiSa',                     'Mary',                       'Alan'],
5. "ID":   [1,              2,                         ' ',                          None],    # 输出 NaN
6. "age":  [np.nan,        28,                           38 ,                          '' ],    # 输出 
7. #           "born": [pd.NaT,     pd.Timestamp("1990-01-01"),  pd.Timestamp("1980-01-01"),        ''],  # 输出 NaT
8. "sex":  ['男',          '女',                        '女',                        None,],    # 输出 None
9. "hobbey":['打篮球',     '打羽毛球',                   '打乒乓球',                    '',],    # 输出 
10.           }
11. data_frame = pd.DataFrame(contents)
12. data_frame.to_excel("data_Frame.xls")
13. print(data_frame.dtypes)
14. print(data_frame)
15. print('-----------------------------------------')
16. data_frame_temp=data_frame.copy()
17. 
18. 
19. # Py之pandas：利用pandas工具输出每行的索引值、及其对应的行数据
20. for index, row in data_frame.iterrows():     
21.     row_lists=list(row)
22. print(index,row_lists)