CODEWITHSUNDEEP
pythonpandasvariables
Jorge
Jorge

Reputation: 119

How to make a variable name dynamic based on function's parameter?

I have a function I use to make duplicate rows in Pandas in order to have in each row a different value that were together before

GRI_Code     ADX_Code
  102        S1.2\nS1.1\nS5.1\nS5.2
  102\n405   S4.2\nS4.3\nS4.1
  103        E7.2\nE7.3\nE7.1\n\n\nS9.2\nS9.1\nS10.2\nS10.1\n
  302        E3.1\nE3.2\n\n

the method I use is:

def separate_code(self, df, column, delimiter):
    df = df.assign(GRI_Code=df[f'{column}'].str.split(delimiter)).explode(f'{column}')
    
    return df

When I call the funtion:

df = separate_code(df, column='GRI_Code', delimiter="\n")

My output is:

GRI_Code    ADX_Code
   102      \n\nS1.2\nS1.1\nS5.1\nS5.2
   102      S4.2\nS4.3\nS4.1 
   405      S4.2\nS4.3\nS4.1
   103      E7.2\nE7.3\nE7.1\n\n\nS9.2\nS9.1\nS10.2\nS10.1\n
   302      E3.1\nE3.2\n\n

I will be using this method on other dataframes with different column names, I would like to know how can I add the column= in a dynamic way, if I use the variable column instead of GRI_Code= it is going to create a new column and return the same values in the same row as a list, I don't want that.

Upvotes: 1

Views: 276

Answers (1)

mozway
mozway

Reputation: 260640

Use a dictionary and parameter expansion:

def separate_code(self, df, column, delimiter):
    return df.assign(**{column: df[f'{column}']...})

Upvotes: 1

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