Running a function on multiple dataframes through for loop

Question

I have function that performs standard preprocessing on each dataframe. I am passing 4 dataframes to that function as a list through for loop. But the changes performed in the function are not reflected back in actual dataframe. Why?

My Code :

def  merge_preprp(x):
     x[x.columns[0]] = x[x.columns[0]].astype(str)
     x[x.columns[0]]= x[x.columns[0]].str.extract('(\d+)')
     x = x[pd.notnull(x[x.columns[0]])]
     x = x[x[x.columns[0]].apply(lambda x: x.isnumeric())] 
     x[x.columns[0]] = x[x.columns[0]].astype(int)
     x.sort_values(x.columns[0], inplace = True)
     x.drop_duplicates(subset = x.columns[0], keep = 'last',inplace = True)
     return x

# dataframes A, B, C

list1 = [A,B,C]
for i in list1:
    i =merge_preprp(i)

jezrael · Accepted Answer · 2019-05-23 06:49:19Z

1

If call function for list of DataFrames, it not working inplace, because in your function are combination inplace and also not inplace functions, but need assign output to new list of DataFrames in loop:

list1 = [A,B,C]
out = []
for i in list1:
    out.append(merge_preprp(i))

Or in list comprehension:

out = [merge_preprp(i) for i in list1]

If in your functions are only inplace operation like last 2 rows for sorting and remove duplicates, your solution working like you need.

edited May 23, 2019 at 6:49

answered May 23, 2019 at 6:27

jezrael

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2 Comments

Curious Over a year ago

How can I get back the dataframes from out list?

jezrael Over a year ago

You can select by positions like out[0], out[1]

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