Creating new dataframes for every loop - json

Question

I've been struggling to solve a problem but could not achieve a solution.
Basically, I'm trying to read JSONs page individually, convert it to a Pandas Dataframe and then store it in a different variable for each time during a for loop.
At the end I would stack each dataframe for create a big dataframe with all the information of each page.
My code:
#Creating a list to store the URLs that will be used to connect
teste = []
for page_num in range(1, 6):
url = "pagina=" + str(page_num) + "&situacao=A&dataadmissaode=&codigoempresa=600"
teste.append(url)
#Loading libraries
import http.client
import pandas as pd
import io
import requests
import json
# auth API
conn = http.client.HTTPSConnection("Company URL")
payload = 'user=MyUser&password=MyPassword'
headers = {
'Content-Type': 'application/x-www-form-urlencoded'
}
conn.request("GET", "/login", payload, headers)
res = conn.getresponse()
data = res.read()
y = json.loads(data) #load auth and token
access_token = y.get("token", None) #just access token dynamically evey call
#second part: A for routine to execute the code for each URL generated previously in teste list.
my_dictionary = {} #empty dictionary for storing the info if possible
lista_infos = [] #empty list for storing the info if possible
for url in teste:
conn = http.client.HTTPSConnection("my_web_site.com")
payload = url
headers = {
'x-access-token': access_token,
'Content-Type': 'application/x-www-form-urlencoded'
}
conn.request("GET", "/colaborador", payload, headers)
res = conn.getresponse()
data = res.read()
#store in a dataframe and then append it to lista_infos
df_json = pd.read_json(io.StringIO(data.decode('utf-8')))
lista_infos.append(df_json)
Is there another approach to properly store the data and then create a single dataframe with the info from df_json after every call?
I've tried creating a Dataframe of information obtained with a API which does not have any documentation.
I can't create a DataFrame with the info all requests together.