Python - Creating a for loop to build a single csv file with multiple dataframes

I am new to python and trying various things to learn the fundamentals. One of the things that i'm currently stuck on is for loops. I have the following code and am positive it can be built out more efficiently using a loop but i'm not sure exactly how.

import pandas as pd
import numpy as np
url1 = 'https://www.cbssports.com/nfl/stats/player/receiving/nfl/regular/qualifiers/?page=1'
url2 = 'https://www.cbssports.com/nfl/stats/player/receiving/nfl/regular/qualifiers/?page=2'
url3 = 'https://www.cbssports.com/nfl/stats/player/receiving/nfl/regular/qualifiers/?page=3'

df1 = pd.read_html(url1)
df1[0].to_csv ('NFL_Receiving_Page1.csv', index=False) #index false gets rid of index listing that appears as the very first column in the csv

df2 = pd.read_html(url2)
df2[0].to_csv ('NFL_Receiving_Page2.csv', index=False) #index false gets rid of index listing that appears as the very first column in the csv

df3 = pd.read_html(url3)
df3[0].to_csv ('NFL_Receiving_Page3.csv', index=False) #index false gets rid of index listing that appears as the very first column in the csv

df_receiving_agg = pd.concat([df1[0], df2[0], df3[0]])
df_receiving_agg.to_csv('NFL_Receiving_Combined.csv', index=False) #index false gets rid of index listing that appears as the very first column in the csv

I'm ultimately trying to combine the data in the above URL's into a single table in a csv file.

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