How to call different data files using a for loop in pandas?

March 21, 2022

I have a list of files named such as

topaccount_2015_09_individuals
topaccount_2015_12_indiviuuals
...
topaccount_2021_12_individuals

which are subsets of

topaccount_2015_09
topaccount_2015_12
...
topaccount_2021_12

I want to call them and do some data manipulation so i created a list,

known_series = known['Address']
y = ['2015_09', '2015_12', '2016_03', '2016_06', '2016_09', '2016_12', '2017_03', '2017_06', '2017_09', '2017_12',
     '2018_03', '2018_06', '2018_09', '2018_12', '2019_03', '2019_06', '2019_09', '2019_12' , '2020_03', '2020_06', '2020_09', '2020_12', 
     '2021_03', '2021_03', '2021_06', '2021_09', '2021_12']

for q in y:
    topaccount_[q]_individuals = topaccount_[q][~topaccount_[q]['address'].isin(known_series)]
    topaccount_[q]_individuals = topaccount_[q]_individuals.reset_index(drop=True)

but it is giving me an error. what am I doing wrong? (known_series is already defined in the script)

>Solution :

Something like this then and use the name list later.

name = []
for x in y:
    name.append(f'topaccount_{x}_individuals') 
    
print(name)

['topaccount_2015_09_individuals', 'topaccount_2015_12_individuals', 'topaccount_2016_03_individuals', 'topaccount_2016_06_individuals', 'topaccount_2016_09_individuals', 'topaccount_2016_12_individuals', 'topaccount_2017_03_individuals', 'topaccount_2017_06_individuals', 'topaccount_2017_09_individuals', 'topaccount_2017_12_individuals', 'topaccount_2018_03_individuals', 'topaccount_2018_06_individuals', 'topaccount_2018_09_individuals', 'topaccount_2018_12_individuals', 'topaccount_2019_03_individuals', 'topaccount_2019_06_individuals', 'topaccount_2019_09_individuals', 'topaccount_2019_12_individuals', 'topaccount_2020_03_individuals', 'topaccount_2020_06_individuals', 'topaccount_2020_09_individuals', 'topaccount_2020_12_individuals', 'topaccount_2021_03_individuals', 'topaccount_2021_03_individuals', 'topaccount_2021_06_individuals', 'topaccount_2021_09_individuals', 'topaccount_2021_12_individuals']