How to iterate through and compare values of data frames?

Question

I want to iterate through and compare the values in two data frames, PORResult , p90Result and then update the values in a third data frame, CountResult based on that comparison. If the value in PORResult is greater than the value in p90result I want to update the value in CountResult to be = 1. All of the data frames are the same size (121x365) and have the same column names and indexes. This is where I'm stuck:

for index, row1 in PORResult.iterrows():
    for index, row2 in p90Result.iterrows():
        if PORResult.loc[index,row1]>p90Result.loc[index,row2]:
            CountResult.at[index,row1]=1

When I try this I get the following error message: "None of [Float64Index([ nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\\n ...\\n nan, nan, nan, nan, nan, nan, nan, nan, nan, 46.0],\\n dtype='float64', name='day', length=365)] are in the [columns]" I'm not sure where to go from here. Does this mean that my data frames are set up incorrectly or am I not executing the loop properly? I'm new to python so any help is appreciated!

Answer 1

This loop compares all the rows of the first dataframe with all the rows of the second dataframe. You should make loop such as for i in range(PORResult.shape[0]): for j in range (PORResult.shape[1]):

Answer 2

This is how I was able to resolve the problem

for day in PORResult.columns:
    for year in PORResult.index:
        tmax = PORResult.loc[year, day]
        perc = p90Result.loc[year, day].values[0]
        if tmax > perc:
            CountResult.loc[year, day] = 1