Multiply dataframe by specific value in another dataframe?

Question

I have two data frames with a similar shape to:

df1 = pd.DataFrame([[3.2,5.8,46],[3.5,4.4,50],[5.4,6.7,40]], index = ['sample1','sample2','sample3'], columns = ['L1','L2','L3'])


L1  L2  L3
sample1 3.2 5.8 46
sample2 3.5 4.4 50
sample3 5.4 6.7 40


df2 = pd.DataFrame([[0.02,0.03,0.04,0.05,0.06],[0.2, 0.3, 0.4, 0.5, 0.7],[2, 3, 4, 5, 7]])


0   1   2   3   4
0   0.02    0.03    0.04    0.05    0.06
1   0.20    0.30    0.40    0.50    0.70
2   2.00    3.00    4.00    5.00    7.00

I would like to multiply the first row in df2 by the L1 value for sample 1 (3.2) in df1, then multiply the second row in df2 by the L2 value for sample 1 (5.8)in df1 and then multiply the third row in df2 by the L3 value for sample 1 (46) in df1. I would then need to repeat this for sample 2 (eg, row 1 by the L1 value for sample2, row 2 by the L2 value for sample2, and row3 by the L3 value for sample2.) And so on for each sample (with my actual dataset I have 100s of samples). With the creation of a new dataframe either for each sample or for all of the samples as the output. I'm not sure how to set the relevant code up?

Answer 1

Please check the following code

column_list = df1.columns
sample_list = df1.index

# Loop over samples and columns 
new_df = pd.DataFrame()
for sample in sample_list:
    for ind, column in enumerate(column_list):
        multiply_by_sample = df2.iloc[ind] * df1.loc[sample][column]
        new_df = new_df.append(multiply_by_sample, ignore_index=True)

Answer 2

Something like this,

sample_lists = {}
for df1_index, df1_row in df1.iterrows():
    sample = df1_index
    print(f'\nPROCESSING SAMPLE {sample}')
    df1_row = df1_row.tolist()
    sample_list = []
    for value in df1_row:
        index_number = df1_row.index(value)
        df2_row = df2.iloc[index_number, :].tolist()
        print(f'Mulitplying {df2_row} with {value}')
        int_list = [v*value for v in df2_row]
        sample_list.append(int_list)
    sample_lists[sample] = sample_list
print(f'\nFINAL OUTPUT: {sample_lists}')

Feel free to remove the print statements. You can then use this dict to create a dataframe .

Explanation:

• Start loop
• Take the first row in df1 and convert that to a list
• For each value in that list, get the index of the value . This is done so that you can get the row that matches the index in df2 which will be our next step.
• Get the row that matches the index in df2
• Multiply the row with the value and append it to a list
• Create a dict with the index of each row in df1 (sample1, sample2, etc.)

Pretty certain you can use lambda and apply to simplify the code above.