How to Write a Table to Csv File in Python

HTML is the standard language to create web pages, and it is generally used to structure the text, images, other elements on a web page. HTML can represent the text data in various formats such as links, normal text, tables, lists, etc. Let's say that you have an HTML or you want to grab the HTML web page from the internet and wish to extract the table data to analyze or crunch the data.

Here in this Python tutorial, I will walk you through the Python program on how to extract table data from the HTML web pages and save it locally in CSV files.

But before we get to the main topic, let's discuss and install the libraries that we will be using in this Python tutorial.

Required Libraries

• Python requests library

We will be using the requests library to send HTTP GET request to the web page and in response get HTML text data. To install the requests library, run the following pip command on your terminal or command prompt:

pip install requests

• Python beautifulsoup4 Library

The beautifulsoup4 library is an open-source Python HTML & XML data extractor library. We will be using this library to extract table data from a HTML page using HTML tag names like <th>, <table>, <tr>, and <td>.

You can install this library using the following pip command:

          pipinstallbeautifulsoup4        

• Python CSV Module

CSV (Comma Separated Values) is one of the modules in the Python Standard Library, and you do not need to install it separately. As its name suggests, we can use this module to read and write CSV files.

To learn how to write CSV files in Python, click here.

Note: In this tutorial, we will be extracting data from HTML tables. Here, we assume that you have some knowledge about the usage of the HTML <table> tag along with other tags like <th>, <tr>, and <td>.

Convert HTML Tables into CSV Files in Python

Let's begin with importing the modules for our Python program.

import requests from bs4 import BeautifulSoup import csv

Now define a Python variable url for the web-page URL

url= r"https://www.techgeekbuzz.com/difference-between-repeater-datalist-and-gridview/"  response = requests.get(url) #send get request html_page = response.text #fetch HTML page

Theget()function will send a get request to the URL, whereastext property will fetch the response HTML web page.

Now we will parse the html_page using BeautifulSoup() module so we can extract the html_page using BeautifulSoup find_all() function.

page = BeautifulSoup(html_page, 'html.parser')    #parse html_page        

As in this tutorial we are only fetching tables data, let's extract all the tables present in the page .

tables = page.find_all("table")  #find tables  #print the total tables found print(f"Total {len(tables)} Found on page {url}")

The find_all("table")will return a list of all the <table> tags present in page.

Now, we will loop through every table present in tables list, create the new CSV file, and write table data on the CSV file.

for index, table in enumerate(tables):     print(f"\n-----------------------Table{index+1}-----------------------------------------\n")      table_rows = table.find_all("tr")      #open csv file in write mode     with open(f"Table{index+1}.csv", "w", newline="") as file:                  #initialize csv writer object         writer = csv.writer(file)          for row in table_rows:             row_data= []              #<th> data             if row.find_all("th"):                 table_headings = row.find_all("th")                 for th in table_headings:                     row_data.append(th.text.strip())             #<td> data             else:                 table_data = row.find_all("td")                 for td in table_data:                     row_data.append(td.text.strip())             #write data in csv file             writer.writerow(row_data)                          print(",".join(row_data))     print("--------------------------------------------------------\n")        

Now put all the code together and execute.

Python Program to Convert Web Page Tables to CSV files

import requests from bs4 import BeautifulSoup import csv  url= r"https://www.techgeekbuzz.com/difference-between-repeater-datalist-and-gridview/"  response = requests.get(url) html_page = response.text  soup = BeautifulSoup(html_page, 'html.parser') #find <table> tables = soup.find_all("table") print(f"Total {len(tables)} Table(s)Found on page {url}")  for index, table in enumerate(tables):     print(f"\n-----------------------Table{index+1}-----------------------------------------\n")          #find <tr>     table_rows = table.find_all("tr")      #open csv file in write mode     with open(f"Table{index+1}.csv", "w", newline="") as file:          #initialize csv writer object         writer = csv.writer(file)          for row in table_rows:             row_data= []              #<th> data             if row.find_all("th"):                 table_headings = row.find_all("th")                 for th in table_headings:                     row_data.append(th.text.strip())             #<td> data             else:                 table_data = row.find_all("td")                 for td in table_data:                     row_data.append(td.text.strip())             #write data in csv file             writer.writerow(row_data)              print(",".join(row_data))     print("--------------------------------------------------------\n")        

Output

Total 3 Table(s) Found on page https://www.techgeekbuzz.com/difference-between-repeater-datalist-and-gridview/  -----------------------Table1-----------------------------------------  DataList,Repeater Object Rendering Its object rendered as a table,It uses templates to render its object. Columns generation It automatically generates columns using the data source.,It cannot generate columns. Row selection It can select a row from the data source.,It cannot select rows. Content Editing Using DataList control, we can edit object content.,It does not support content editing. Data arrangement It has RepeatDirection property which allows it to arrange data vertically and horizontally.,It cannot manually arrange data. Performance It is slower than Repeater.,It is very fast because of its lightweight. --------------------------------------------------------  -----------------------Table2-----------------------------------------  GridView,Repeater Debut GridView was introduced in Asp.Net 2.0,The Repeater was introduced in Asp.Net 1.0. Columns generation It automatically generates columns using the data source.,It cannot generate columns. Row selection It can select a row from the data source.,It cannot select rows. Content Editing Using GridView control, we can edit object content.,It does not support content editing. In-built methods It comes with built-in paging and sorting methods.,No built-in support for Built-in paging and sorting developer has to code. Auto formatting and styling In GridView we get inbuilt auto format and styling feature.,It does not support these features. Performance It is slower than Repeater.,Because of its lightweight, it is faster as compared to GridView. --------------------------------------------------------  -----------------------Table3-----------------------------------------  GridView,DataList Debut GridView was introduced in Asp.Net 2.0 version.,DataList was introduced in Asp.Net 1.0 version. In-built methods It comes with built-in paging and sorting methods.,No built-in support for Built-in paging and sorting, the developer has to code for these features. Build-in CRUD operation It comes with built-in Update and Deletes Operations, so the developer does not need to write code for simple operations.,If developer use DataList then he/she has to write code for the Update and Delete operations. Auto formatting and styling In GridView we get inbuilt auto format and styling feature.,It does not support these features. Customizable Row We do not get Customizable row separator feature in GridView.,DataList has SeparatorTemplate for customizable row separator. Performance: Its performance is the lowest as compared to Repeater and DataList.,It is faster than the GridView. --------------------------------------------------------

When you execute the above program, you will see that it will save the .csv file in the same directory where your Python script is located.

Conclusion

Here, we learned "How to convert HTML tables to CSV files in Python?" Also, this tutorial is a small demonstration of web-scrapping with Python. If you want to learn more about extracting data from web pages, you can read the official documentation of BeautifulSoup4.

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How to Write a Table to Csv File in Python

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