loop through pandas columns inside function

Question

I have following function:

def match_function(column):
    df_1 = df[column].str.split(',', expand=True)
    df_11=df_1.apply(lambda s: s.value_counts(), axis=1).fillna(0)
    match = df_11.iloc[:, 0][0]/df_11.sum(axis=1)*100
    df[column] = match
    return match

this functuion only works if I enter specific column name

how to change this function in the way, if I pass it a certain dataframe, it will loop through all of its columns automatically. so I won't have to enter each column separately?

ps. I know the function it self written very poorly, but im kinda new to coding, sorry

Welcome to Stackoverflow! It's a good thing you formatted your code. Please explain what the question is and consider adding a reproducible example. — zabop
– zabop, Commented Sep 30, 2021 at 14:20
@S.Comeau I want to find out, how can I change this function, so I would be able to pass to it a dataframe itself, and it will loop through its columns. beacuse now, in the way its, i have to enter each column separately — Archi
– Archi, Commented Sep 30, 2021 at 14:23

Francesco Vaglienti · Accepted Answer · 2021-09-30 14:25:29Z

1

You need to wrap the function so that it does this iteratively over all columns.

If you add this to your code then it'll iterate over the columns while returning the match results in a list (as you will have multiple results as you're running over multiple columns).

def match_over_dataframe_columns(dataframe):
    return [match_function(column) for column in dataframe.columns]

results = match_over_dataframe_columns(df)

answered Sep 30, 2021 at 14:25

Francesco Vaglienti

112 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

user12280110 · Accepted Answer · 2021-09-30 14:30:59Z

0

Instead of inputting column to your function, input the entire dataframe. Then, cast the columns of the df to a list and loop over the columns, performing your analysis on each column. For example:

def match_function(df):

    columns = df.columns.tolist()
    matches = {}
    
    for column in columns:
        #do your analysis
        #instead of returning match,
        matches[column] = match

    return matches

This will return a dictionary with keys of your columns and values of the corresponding match value.

answered Sep 30, 2021 at 14:30

user12280110

Comments

karas27 · Accepted Answer · 2021-09-30 14:35:26Z

0

just loop through the columns

def match_function(df):
    l_match = []
    for column in df.columns:
        df_1 = df[column].str.split(',', expand=True)
        df_11=df_1.apply(lambda s: s.value_counts(), axis=1).fillna(0)
        match = df_11.iloc[:, 0][0]/df_11.sum(axis=1)*100
        df[column] = match
        l_match.append(match)
    return l_match

answered Sep 30, 2021 at 14:35

karas27

3751 gold badge5 silver badges17 bronze badges

Collectives™ on Stack Overflow

loop through pandas columns inside function

3 Answers 3

Comments

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

Comments

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related