Automatic data wrangling on Pandas with multiple dataframes using lists and loops

for professional purposes I need to produce some reports that includes new entries every week. I have 16 dataframes having same column names (df names are week1, week2… week16).

I created a list of the dataframes and then a loop. I wanted to test rename of column with index = 1 and I did not succeed.

[35] lists = [week1, week2, week3, week4, week5, week6, week7, week8, week9, week10,
           week11, week12, week13, week14, week15, week16]

[36] for i in lists:
    i.rename(columns={'1':'State'},inplace=True)

I am forced to manually change every column name because I can’t set up the loop. Besides this is only one of the columns.

How can I make sure I can call all dataframes in a loop?

I have tried also the suggestions in this thread but somehow it did not work to me to use the append method. Indeed, the column names aren’t edited after I run the script.

Thanks for the help!

Answer

Sample dataframes:

#import numpy as np
#import pandas as pd
df1 = pd.DataFrame(np.random.randn(10,10),columns=range(10))
df2 = pd.DataFrame(np.random.randn(10,10),columns=range(10))
df3 = pd.DataFrame(np.random.randn(10,10),columns=range(10))
df_list = [df1, df2, df3]

Try via list comprehension and rename() method:

df_list =[x.rename(columns={1:'State'}) for x in df_list]