Create multiple dataframes with a loop in Python

So I got this part of code that I want to make shorter:

df_1 = investpy.stocks.get_stock_recent_data('Eco','Colombia',False)
df_2 = investpy.stocks.get_stock_recent_data('JPM','United States',False)
df_3 = investpy.stocks.get_stock_recent_data('TSM','United States',False)
df_5 = investpy.stocks.get_stock_recent_data('CSCO','United States',False)
df_8 = investpy.stocks.get_stock_recent_data('NVDA','United States',False)
df_9 = investpy.stocks.get_stock_recent_data('BLK','United States',False)

As I use the same code and only a few things change from one line to another I think I migth solve this using a function. I create this one:

def _get_asset_data(ticker, country, state):
    investpy.stocks.get_stock_recent_data(ticker, country, state)

So I tried this:

_get_asset_data('TSLA', 'United States', False) print(_get_asset_data)

<function _get_asset_data at 0x7f323c912560>

However, I do not know how to make each set of data that I receive as a result of this function to be stored in a data frame for each company.I tried a for loop but got nowhere.

Any ideas? ¡Thank you in advance for your attention and cooperation!

Solution

Here is one approach based on the code given. You should refrain from using it in practice, as it contains redundant code, which makes it hard to maintain. You'll find a more flexible approach below.

Based on your solution

import investpy
import pandas as pd

def _get_asset_data(ticker, country, state=False):
    return investpy.stocks.get_stock_recent_data(ticker, country, state)

df_1 = _get_asset_data('Eco','Colombia')
df_2 = _get_asset_data('JPM','United States')
df_3 = _get_asset_data('TSM','United States')
df_5 = _get_asset_data('CSCO','United States')
df_8 = _get_asset_data('NVDA','United States')
df_9 = _get_asset_data('BLK','United States')

final = pd.concat([df_1, df_2, df_3, df_5, df_8, df_9], axis=1)
final

More versatile solution:

import investpy
import pandas as pd


def _get_asset_data(ticker, country, state=False):
    return investpy.stocks.get_stock_recent_data(ticker, country, state)


stocks = [
    ('Eco', 'Colombia'),
    ('JPM', 'United States'),
    ('TSM', 'United States'),
    ('CSCO', 'United States'),
    ('NVDA', 'United States'),
    ('BLK', 'United States'),
    ]

results = []

for stock in stocks:
    result = _get_asset_data(*stock)
    results.append(result)

final = pd.concat(results, axis=1)
final