Search for the last occurence in multiple columns in a dataframe

Question

Suppose i have a large dataframe similar to the structure below

 home| away|  home_score| away_score
    A|    B|           1|          0
    B|    C|           1|          1
    C|    A|           1|          0

I want to find the last score regardless of home / away. For example, last score of team A, B and C are 0, 1 and 1 respectively and fill back to the original dataframe:

 home| away|  home_score| away_score| last_score_home| last_score_away|
    A|    B|           1|          0|                |                |
    B|    C|           1|          1|               0|                |
    C|    A|           1|          0|               1|               1|
 ...

I have tried groupby and shift but I am not sure how to combine the home / away results.

Answer 1

You can try something as this. 1) make all column names splittable by adding suffix to the first two columns names; 2) split the column headers and transform it to multi index; 3) melt table to long format with stack , group by the teams and get the latest score:

df.columns = df.columns.str.replace("^([^_]+)$", "\\1_team").str.split("_", expand=True)
df.stack(level=0).groupby("team").tail(1)

#         score   team
#1  home      1      B
#2  away      0      A
#   home      1      C

---

Update :

To merge it back to the original data frame, you can use join :

df.columns = df.columns.str.replace("^([^_]+)$", "\\1_team").str.split("_", expand=True)
df1 = df.stack(level=0).groupby("team").tail(1)   

# join the result back to the original transformed data frame 
df2 = df.stack(level=0).join(df1.score, rsuffix = "_last").unstack(level=1)
df2.columns = [x + "_" + y for x, y in df2.columns]
df2