Double Constrained Loop in Python

Question

I have an issue which is rather simple in theory. I just can't seem to wrap my head around a solution. I have 2 Pandas dataframes.

Dataframe A:

Date           Currency    
-------------------------
2019-11-29     EUR
2019-11-29     USD
.              GBP
.              .
.              .
2019-10-31

Dataframe B:

Date          Currency   Conversion
-----------------------------------
2019-11-29    USD        0.79
2019-11-29    GBP        1.23
2019-11-29    CHF        1.41
2019-11-28    USD        .
.
.
.
2019-10-31   USD         .
2019-10-31   GBP
2019-10-31   USD

I essentially have a long list of trades in Dataframe A, around 5-15 a day. The instruments are bought in different currencies, which all should be denominated in euros. I wrote a piece from SQL that retrieves the conversion rates (from currency XX to EUR) at all dates in the period.

Now I need to add a column to dataframe A:

IF DataframeA[Date] = DataframeB[Date] AND DataframeA[Currency] = DataframeB[Currency]

then the corresponding conversion rate should be added.

The IF statement in itself I can do, but I can't seem to iterate and update as my script runs. Any ideas?

Best Patrick

Answer 1

DataframeA = pd.merge(DataframeA, DataFrameB, on=['Date', 'Currency'])

by default it's inner join. you can choose to modify that accordingly by using the option Ex: how = 'outer' in the merge command. Further, drop or keep the column as you like or choose to add suffix or prefix in the common columns coming from two dataframes. Read the doc