Python Passing Dynamic Table Name in For Loop

Question

table_name = []
counter=0
for year in ['2017', '2018', '2019']:
    table_name.append(f'temp_df_{year}')
    print(table_name[counter])
    table_name[counter] = pd.merge(table1, table2.loc[table2.loc[:, 'year'] == year, :], left_on='col1', right_on='col1', how='left')
    counter += 1

temp_df_2017

The print statement outputs are correct: temp_df_2017, temp_df_2018, temp_df_2019

However, when I try to see what's in temp_df_2017, I get an error: name 'temp_df_2017' is not defined

I would like to create those three tables. How can I make this work?

PS: ['2017', '2018', '2019'] list will vary. It can be a list of quarters. That's why I want to do this in a loop, instead of using the merge statement 3x.

temp_df_2017 is a string - obviously it is not defined.

Henry Yik
– Henry Yik

2020-02-04 03:39:25 +00:00
Commented Feb 4, 2020 at 3:39 — Henry Yik
– Henry Yik, Commented Feb 4, 2020 at 3:39

Jason · Accepted Answer · 2020-02-04 06:37:02Z

1

I think the easiest/most practical approach would be to create a dictionary to store names/df.

import pandas as pd
import numpy as np

# Create dummy data
data = np.arange(9).reshape(3,3)
df = pd.DataFrame(data, columns=['a', 'b', 'c'])

df
Out:
    a   b   c
0   0   1   2
1   3   4   5
2   6   7   8

df_year_names = ['2017', '2018', '2019']
dict_of_dfs = {}
for year in df_year_names:
    df_name = f'some_name_year_{year}'
    dict_of_dfs[df_name] = df    

dict_of_dfs.keys()
Out:
dict_keys(['some_name_year_2017', 'some_name_year_2018', 'some_name_year_2019'])

Then to access a particular year:

dict_of_dfs['some_name_year_2018']
Out:
    a   b   c
0   0   1   2
1   3   4   5
2   6   7   8

answered Feb 4, 2020 at 6:37

Jason

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