Specify DataFrame name in Python using defined function, for use within another defined function

Question

Trying to create a function to specify the name of a DataFrame, so it can be used within another function. Tried a few different approaches, but this is a simplified version of what I have now.

import pandas as pd

data1 = {'var1': [1, 2, 3], 'var2': [1, 2, 3]}
h_df1 = pd.DataFrame(data1)


def hh(wave):
    hh = 'h_' + wave
    return hh


def table(wave):
    hh_data = hh(wave)
    hh_data["new_var"] = hh_data["var1"]*hh_data["var2"]
    return table


table = table("df1")

print(table)

This gives the error: TypeError: string indices must be integers

The result I am expecting is that hh_data uses a DataFrame named h_df1. Looking for a way to automate which DataFrame is picked up. It's part of a more complex system.

hh_data is just string, not dict.

KennetsuR
– KennetsuR

2021-04-06 10:18:38 +00:00
Commented Apr 6, 2021 at 10:18 — KennetsuR
– KennetsuR, Commented Apr 6, 2021 at 10:18

Ynjxsjmh · Accepted Answer · 2021-04-06 10:55:44Z

1

I think you want is Python built-in globals functions, which returns a dictionary representing the current global symbol table. For example, globals()["h_df1"] will return the h_df1 variable. Thus, you can do

def table(wave):
    hh_data = globals()[hh(wave)]
    hh_data["new_var"] = hh_data["var1"]*hh_data["var2"]
    return table

answered Apr 6, 2021 at 10:55

Ynjxsjmh

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2 Comments

an1uk Over a year ago

When I do this using separate files for each function, I get the error: KeyError: 'h_df1'

Ynjxsjmh Over a year ago

@an1uk Well, From the doc, This is always the dictionary of the current module (inside a function or method, this is the module where it is defined, not the module from which it is called). globals() doesn't work with separate files.

KennetsuR · Accepted Answer · 2021-04-06 10:23:11Z

0

hh_data is just string, not dict.
if you want to create new column, you can try below code

if __name__ == '__main__':
    import pandas as pd

    data1 = {'var1': [1, 2, 3], 'var2': [1, 2, 3]}
    h_df1 = pd.DataFrame(data1)

    h_df1['new_var'] = h_df1["var1"] * h_df1["var2"]

    print(h_df1.head(5))

answered Apr 6, 2021 at 10:23

KennetsuR

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