0

I have two Pandas dataframes:

In: df_Rq
Out: 
  EH Req SH Req SD Req
0  EH-01  HL-02       
1  EH-01  HL-03  SH-02
2  EH-01  HL-03  SH-03
3  EH-01  HL-03  SH-04
4  EH-01  HL-03  SH-05

In: df_TC
Out: 
  Test Case Description
0      TC00     Default
1      TC01      Test 1
2      TC02      Test 2

Each of the test cases support each of the requirements dataframe, so I am needing to expand each row in the df_Rq to include the test case. Something like this:

In: df_Pro
Out: 
   EH Req SH Req SD Req Test Case Description
0   EH-01  HL-02             TC00     Default
1   EH-01  HL-02             TC01      Test 1
2   EH-01  HL-02             TC02      Test 2
3   EH-01  HL-03  SH-02      TC00     Default
4   EH-01  HL-03  SH-02      TC01      Test 1
5   EH-01  HL-03  SH-02      TC02      Test 2
6   EH-01  HL-03  SH-03      TC00     Default
7   EH-01  HL-03  SH-03      TC01      Test 1
8   EH-01  HL-03  SH-03      TC02      Test 2
9   EH-01  HL-03  SH-04      TC00     Default
10  EH-01  HL-03  SH-04      TC01      Test 1
11  EH-01  HL-03  SH-04      TC02      Test 2
12  EH-01  HL-03  SH-05      TC00     Default
13  EH-01  HL-03  SH-05      TC01      Test 1
14  EH-01  HL-03  SH-05      TC02      Test 2

I have tried various for loops, append, merge commands. How would this be done?

Timothy Williams
  • 207
  • 1
  • 4
  • 13
  • Use dummy key and merge. `df_Rq.assign(key=1).merge(df_TC.assign(key=1), on='key')`.. I think this a dup. – Scott Boston Nov 09 '17 at 17:50
  • That did it. If it's a duplicate question, please show me where. I was surprised I couldn't find it. Maybe I wasn't asking the most correct way. – Timothy Williams Nov 09 '17 at 17:53

0 Answers0