方法一：

import pandas as pd
from pandas import DataFrame

w_df = DataFrame(['w1','w2'],columns=['worker'])

d_df = DataFrame(['0101','0102','0103'],columns=['date'])

new_df = DataFrame(columns=['worker','date'])

for w_index,w_row in w_df.iterrows():
    for d_index,d_row in d_df.iterrows():
        w_data = w_row['worker'
 
]
        d_data = d_row['date']

        row =  DataFrame([dict(worker=w_data, date=d_data), ])
        new_df = new_df.append(row,ignore_index=True)

print new_df

#output
   date worker
0  0101     w1
1  0102     w1
2  0103     w1
3  0101     w2
4  0102     w2
5  0103     w2

方法二：

date_list = ['2015-01-01','2015-01-02'
 
,'2015-01-03']

date_count = len(date_list)

workers = np.arange(15)

df = DataFrame(columns=['w','date'])

for worker in workers:

    cur_arr = np.array([worker] * date_count)
    cur_arr.shape = (date_count,1) #轉置

    date_list = np.array(date_list)
    date_list.shape = (date_count,1) #轉置

    join_arr = np.hstack((cur_arr,date_list)) #水平方向合併
 


    df = df.append(DataFrame(join_arr,columns=['w','date']),ignore_index=True)

print df

方法三

import itertools

for x in itertools.product(['w1','w2'],['0101','0102','0103']):
    print x

#output:
('w1','0101')
('w1','0102')
('w1','0103')
('w2','0101')
('w2','0102')
('w2','0103')