CODEWITHSUNDEEP
pythonpandascsv
divko
divko

Reputation: 43

How to iterate columns while iterating rows?

I have two CSV tables.

The first one looks like thisenter image description here

The second one like this enter image description here

I want to multipy the "Flaechenfaktor" from the first table with the whole timeseries from the second table.

So first I started with this:

data_area = pd.read_csv("U:\...\Flaechenfakt_Test.csv",sep=";",header=0)
data_timeseries = pd.read_csv("U:\...\Zeitreihe.csv",sep=";",header=0)

new_data= data_area.Flaechenfaktor[0]*data_timeseries.Coesfeld

This works well for the first timeseries from "Coesfeld". For the second one ("Recklinghausen") it would be easy to write it like I have done it with "Coesfeld". But instead of that way I want to iterate the rows in the first table and iterate the columns in the second table, because the table will grow with time. So my question is how can I iterate columns while iterating the rows?

Upvotes: 0

Views: 44

Answers (1)

Stefano
Stefano

Reputation: 274

If I got the question correctly you can first define the columns you would like to iterate in a list column_to_iterate and then

for number_of_column, column in enumerate(columns_to_iterate):
    data_area.loc[number_of_column, 'Flaechenfaktor'] * data_timeseries[column]

number_of_column will go from 0 to len(columns_to_iterate) - 1, so you can browse the rows (if their index is the default integer sequence), while column will browse the headers you selected

Upvotes: 1

Related Questions