Python SUMIF with one condition across dataframes

Question

I'm working with two dataframes

• MRP:

Material	Description	Septiembre
1208181	ADSV,NA,MX,ADH HOTMET 814433PM	630.2888856
1206500	SHWP,NA,MX,WRAP M-WRAP 18'	459.4193011
3049172	INSR,LUFTL,BR,LUFTAL	0
3049173	CLOS,LUFTL,BR,BERRY	0
3060614	BOTL,LUFTL,BR,LDPE/HDPE 15 ML	0

• SMCalc:

Material	Description	Brand	Available Qty	Avail. - 6mth.	sep
0324583	MEAS,MUCNX,US,BLUE,20ML	MCN	921888		980554.96
0327757	CLOS,MUCNX,US,CR24MM	MCN	9509400	6219256.172	975724.64
1019906	ACETAMINOPHEN DC 90 COARSE L	TEM	43900	-4443.531438	7372.2407
1020442	ACETAMINOPHEN POWDER	NA	64203.289	38020.3542	6784.4993
1120252	TARTARIC ACID	PIC	43217.08		9370.0843

And I'm using this formula in excel: =+SUMIF(MRP!$A:$A,$A2,MRP!C:C) where:

• Range is MRP!A:A (Material)
• Criteria is SMCalc $A2 (Material)
• Sum range is MRP!C:C (Septiembre)

The output I'm looking for is the column F in SMCalc.

Answer 1

If I'm not wrong, that excel formula calculates the sum of 'Septiembre' in column C of MRP when 'Material' in SMCalc matches 'Material' in MRP...

Assuming you have both excel sheets as pandas dataframes, I would then do:

mrp.groupby('Material')['Septiembre'].sum().reset_index()

To find the sum of 'Septiembre' per material in mrc. Then merge that with the other dataframe:

smcalc.merge(mrp.groupby('Material')['Septiembre'].sum().reset_index(),how='left')

To then bring back those values to smcalc where we want them to be