Get column value from the column that is dynamically selected depending on row value of another colu-CodePudding

I have a dataframe as below.

        month   fe_month_OCT    re_month_APR    fe_month_MAY    
0       OCT     1               1               2               
1       APR     4               2               2               
2       MAY     1               4               3

Im trying to create a new column that gets me the value from any of the fe_month_ or re_month_ columns based on what month the row of data corresponds to (for the SAME month however we will not see 2 columns - i.e. we will never see both fe_month_APR and re_month_APR in the same df - it will either be fe or re).

Output example - for the first row, I would want this new column to have the value coming from fe_month_OCT, because month=OCT, for the second row, the value should come from re_month_APR etc.

Expected output:

        month   fe_month_OCT    re_month_APR    fe_month_MAY    d_month
0       OCT     1               1               2               1
1       APR     4               2               2               2
2       MAY     1               4               3               3

Code to create input dataframe:

data = {'month': ['OCT', 'APR', 'MAY'], 'fe_month_OCT': [1, 4, 1], 're_month_APR': [1, 2, 4],'fe_month_MAY': [2, 2, 3] }  
db = pd.DataFrame(data)

CodePudding user response：

Assuming all the column names are in the form "fe_month_" plus the string in db["month"], you can use apply().

get_value = lambda row: row[ "fe_month_"   row["month"] ]
db["d_month"] = db.apply( get_value, axis=1 )