Pandas Multiply Columns Using Conditional Column Names

Question

I am trying to simply multiply columns in a single DF based on the column names starting with a string. If a column contains that "string" value, then the values in those columns are multiplied by a value in a different column (column = Avg_Adj_Prod). Here is an example of my data:

df:
      site     month     Adj1    Adj2    Adj3    Adj4    Adj5    Avg_Adj_Prod   
0     West1    8         45      52      36      21      19      0.95
1     West1    9         21      17      34      23      33      0.82
2     East3    8         17      16      53      21      19      1.45
3     East3    9         38      41      44      51      62      1.05

Final df:

      site     month     Adj1    Adj2    Adj3    Adj4    Adj5    
0     West1    8         42.75   49.4    34.2    19.95   18.05      
1     West1    9         17.22   13.94   33.18   18.86   27.06      
2     East3    8         24.65   23.2    76.85   30.45   27.55      
3     East3    9         39.9    43.05   46.2    53.55   65.1

Some code that would initiate the process:

df.loc[:,df.columns.str.contains('Adj')] = ?

Asked By: user2100039

||

Source

Answer 1

Use filter to get the columns starting in "Avg", then mul and update for in place modification (no output):

df.update(df.filter(regex='^Adj').mul(df['Avg_Adj_Prod'], axis=0))

modified df:

    site  month   Adj1   Adj2   Adj3   Adj4   Adj5  Avg_Adj_Prod
0  West1      8  42.75  49.40  34.20  19.95  18.05          0.95
1  West1      9  17.22  13.94  27.88  18.86  27.06          0.82
2  East3      8  24.65  23.20  76.85  30.45  27.55          1.45
3  East3      9  39.90  43.05  46.20  53.55  65.10          1.05

If you prefer indexing:

cols = df.filter(regex='^Adj').columns

df[cols] = df[cols].mul(df['Avg_Adj_Prod'], axis=0)

Answered By: mozway

Pandas Multiply Columns Using Conditional Column Names

Question:

Answers: