To specify column names, why same parameter name is used in `pd.read_csv` and `pd.DataFrame`?

Question

While working with pandas, I have encountered that the two most common ways of creating a new data-Frame using pandas are as follows;

1. pandas.read_csv() Type: < class 'pandas.core.frame.DataFrame' >

2. pandas.DataFrame() Type: < class 'pandas.core.frame.DataFrame' >

Both use different parameters for taking a list of column names as input.

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Syntax:

• For pd.read_csv is as given;

   pandas.read_csv(filepath, sep=',', delimiter=None, header='infer', names=None)

• For pd.DataFrame is as given;

   pd.DataFrame(data=None, index=None, columns=None)

Should I prefer with changing the parameter "names" to "columns" in pandas.read_csv() . Does it make any sense?

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After that again, while saving data-frames into a CSV-file using df.to_csv , we use the parameter name columns as given.

df.to_csv(self, path_or_buf=None, sep=', ', na_rep='', float_format=None, columns=None)

Can above-given techniques change to columns in python?

Answer 1

There has been some discussion on such inconsistencies in pandas. It seems like the proposed changes are in line with what you suggested. Nonetheless, developers have not arrived at a conclusion yet. Thus, as of now, you might not use the parameter columns as an alias for names in pd.read_csv method.

If you tried passing columns as a parameter you will encounter the following error:

TypeError: parser_f() got an unexpected keyword argument 'columns'

Fortunately, you may use a decorator to achieve what you need:

import pandas as pd
from functools import wraps

def enable_columns_parameter(f):
    @wraps(f)
    def wrapper(*args, **kwargs):
        if 'columns' in kwargs:
            kwargs['names'] = kwargs.pop('columns')
        return f(*args, **kwargs)
    return wrapper

pd.read_csv = enable_columns_parameter(pd.read_csv)

After applying the decorator to the pd.read_csv function, this line would work fine without any errors:

pd.read_csv('file.csv', columns=['any', 'given', 'name'])