Problem on how to format my data using pandas.loc() function
Recently I asked this: How to manipulate data in a .csv file using Pandas and access specific row and column? question on how to parse some data and users recommended the pd.loc() function. My .csv file looks like that
entry origin payment_type x1 NaN NaN x2 NaN NaN x3 NaN NaN x4 NaN NaN x5 NaN NaN Using this script
import pandas as pd data = pd.read_csv("example.csv") entries = data["entry"].astype(str) payments = data["payment_type"].astype(str) origins = data["origin"].astype(str) for row in entries: if row[26] == "Y": data.loc[[row], ["payment_type"]] = "sample" if row[27] == "Y": data.loc[[row], ["payment_type"]] = "Check Card" if row[37] == "Y": data.loc[row, "origin"] = "ex1" else: data.loc[row, "origin"] = "ex2" data.to_csv("exe.csv") And I get as an output at exe.csv file this:
How is it possible to format my data as in example.csv file but instead of NaN to have the data I parsed?
For example, I would like to format my data like that:
Any help would be appreciated.
Thank you in advance
