Python definition of a function which accepts any dataframe and any of the first inputted dataframe columns

Question

How to define a Python function that takes in input a DataFrame df a string str that is one of its column names, so that

def fun(x,col):
    return x.loc[x.col == 0]

I know this is quite pleonastic but it is didactical. Is it possible to use variables for dataframe columns? (apparently not...)

The following code does not work

df = pandas.DataFrame({'Name': ...list of Irish people names..., 'Height':.... list of people's height)

x = 'Height'

I saw the solution to the question in here: Applying function to a DataFrame using its columns as parameters

which I liked a lot as a fan of lambda whatever... but it does not apply (at least I cannot see and please help me on this, possibly).

Would it be something like:

lambda x,col: x.loc[x.col==0], DataFrame, x.col)?

Thank you in advance

I don't understand problem - many examples use df["Height"] instead of df.Height - so it seems obvious x[col] for x=df and col="Height" — furas
– furas, Commented Feb 27 at 20:51

user19077881 · Accepted Answer · 2025-02-28 08:57:44Z

2

You can just use return x.loc[x[col] == 0] and so on which allows the use of a String variable. BTW this approach using [] is generally preferred for clarity and to avoid potential conflict with method names and also allows names with spaces (for which ‘dot’ approach cannot be used). For example:

import pandas as pd

df = pd.DataFrame({'name': ['irish1', 'irish2'],
                   'height': [1.8, 1.7]
                    })

def fun(x,col):
    return x.loc[x[col] == 1.7]


print(fun(df, 'height'))

gives

     name  height
1  irish2     1.7

edited Feb 28 at 8:57

answered Feb 27 at 19:53

user19077881

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