Pandas Function To Create Combined Column Based On Dict

I am trying to create a weighted column in a pandas.DataFrame I have a python dictionary with the keys being the pandas.DataFrame column names and the values the corresponding weig

Solution 1:

First create variable for same values for columns and keys in dictionary by Index.intersection, then select this columns and use matrix multiplication with dot with Series from dict filtered for same columns only:

df['Composite'] = df['IX1']*0.3 + df['IX2']*0.2 + df['IX3']*0.4

cols = df.columns.intersection(weights.keys())
df['Composite1'] = df[cols].dot(pd.Series(weights)[cols])
print (df)
        IX1       IX2       IX3  Composite  Composite1
0  1.764052  0.400157  0.978738   1.000742    1.000742
1  2.240893  1.867558 -0.977278   0.654868    0.654868
2  0.950088 -0.151357 -0.103219   0.213468    0.213468
3  0.410599  0.144044  1.454274   0.733698    0.733698
4  0.761038  0.121675  0.443863   0.430192    0.430192
5  0.333674  1.494079 -0.205158   0.316855    0.316855
6  0.313068 -0.854096 -2.552990  -1.098095   -1.098095
7  0.653619  0.864436 -0.742165   0.072107    0.072107
8  2.269755 -1.454366  0.045759   0.408357    0.408357
9 -0.187184  1.532779  1.469359   0.838144    0.838144