Reading HTML tables in Data Analysis Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What Python library is commonly used to read HTML tables into data frames?

The pandas library is commonly used to read HTML tables using the read_html() function.

beginner

What does the read_html() function return when it reads an HTML page with tables?

It returns a list of DataFrames, one for each table found in the HTML content.

beginner

How can you read only the first table from an HTML page using pandas?

You can get the first table by accessing the first element of the list returned by read_html(), like tables = pd.read_html(url); df = tables[0].

intermediate

What parameter can you use in read_html() to specify a particular table by its HTML id or class?

You can use the attrs parameter with a dictionary, for example attrs={'id': 'table_id'} to select a table with a specific id.

intermediate

Why might read_html() fail to read tables from some web pages?

Because some tables are generated dynamically by JavaScript, and read_html() only reads static HTML content. In such cases, you may need tools like Selenium or requests-html.

What type of object does pandas.read_html() return?

A A dictionary

B A single DataFrame

C A string

D A list of DataFrames

read_html() returns a list because an HTML page can have multiple tables.

Which parameter helps you select tables by HTML attributes in read_html()?

A attrs

B index_col

C header

D parse_dates

The attrs parameter lets you filter tables by attributes like id or class.

If you want only the first table from a webpage, what should you do after read_html()?

A Set <code>single_table=True</code>

B Use the <code>first_table</code> parameter

C Access the first element of the returned list

D Use <code>read_table()</code> instead

Since read_html() returns a list, you get the first table by tables[0].

Why might read_html() not find any tables on some websites?

A Tables are generated by JavaScript after page load

B The website uses HTTPS

C The tables are too large

D The tables are in CSV format

JavaScript-generated tables are not in the static HTML source, so read_html() can't see them.

Which library do you import to use read_html()?

A numpy

B pandas

C matplotlib

D requests

read_html() is a function in the pandas library.

Explain how to read tables from a webpage using pandas and how to select a specific table.

Think about how pandas returns multiple tables and how to pick one.

Describe a limitation of pandas.read_html() when working with modern websites.

Consider how web pages load content dynamically.

Practice

1. What does the pd.read_html() function in pandas do?

easy

A. It converts a DataFrame into an HTML table string.

B. It reads all HTML tables from a webpage and returns them as a list of DataFrames.

C. It downloads an HTML file from the internet.

D. It parses JSON data from a webpage.

Solution

1. Step 1: Understand the purpose of pd.read_html()

   This function is designed to extract tables from HTML content on web pages.

2. Step 2: Recognize the output type

   The function returns a list where each element is a DataFrame representing one HTML table found.

3. Final Answer:

   It reads all HTML tables from a webpage and returns them as a list of DataFrames. -> Option B

4. Quick Check:

   pd.read_html() = list of DataFrames [OK]

Hint: Remember: read_html returns a list of tables, not a single table [OK]

Common Mistakes:

• Thinking it returns a single DataFrame instead of a list
• Confusing it with functions that write HTML
• Assuming it downloads files instead of parsing HTML

2. Which of the following is the correct way to read the first HTML table from a webpage URL stored in url using pandas?

easy

A. df = pd.read_html(url)[1]

B. df = pd.read_html(url, index=0)

C. df = pd.read_html(url).first()

D. tables = pd.read_html(url); df = tables[0]

Solution

1. Step 1: Recall the return type of pd.read_html()

   The function returns a list of DataFrames representing all tables found.

2. Step 2: Access the first table correctly

   Use list indexing [0] to get the first table from the list.

3. Final Answer:

   tables = pd.read_html(url); df = tables[0] -> Option D

4. Quick Check:

   Use list index 0 to get first table [OK]

Hint: Use index 0 on the list returned by read_html to get first table [OK]

Common Mistakes:

• Using .first() method which does not exist
• Passing index=0 as a parameter to read_html
• Using index 1 instead of 0 for first table

3. Given the code below, what will be the output of print(len(tables)) if the webpage contains 3 HTML tables?

import pandas as pd
url = 'https://example.com'
tables = pd.read_html(url)
print(len(tables))

medium

A. 0

B. 1

C. 3

D. Error: pd.read_html() requires a file path

Solution

1. Step 1: Understand what pd.read_html() returns

   It returns a list of DataFrames, one for each HTML table found on the page.

2. Step 2: Count the number of tables

   Since the webpage has 3 tables, the list length will be 3.

3. Final Answer:

   3 -> Option C

4. Quick Check:

   len(tables) = number of tables found [OK]

Hint: Count tables by checking length of list returned by read_html [OK]

Common Mistakes:

• Assuming it returns a single DataFrame
• Thinking it returns 0 if tables exist
• Believing it needs a local file path only

4. What is wrong with this code snippet to read the first HTML table from a URL?

import pandas as pd
url = 'https://example.com'
df = pd.read_html(url)[1]

medium

A. It tries to access the second table but may cause IndexError if only one table exists.

B. The syntax for pd.read_html is incorrect; it needs a file path, not a URL.

C. pd.read_html returns a DataFrame, so indexing with [1] is invalid.

D. The variable name df is reserved and cannot be used.

Solution

1. Step 1: Check the indexing used

   The code uses index [1], which means it tries to get the second table.

2. Step 2: Consider possible errors

   If the webpage has only one table, index 1 is out of range and causes IndexError.

3. Final Answer:

   It tries to access the second table but may cause IndexError if only one table exists. -> Option A

4. Quick Check:

   Indexing beyond list length causes error [OK]

Hint: Always check list length before accessing index [OK]

Common Mistakes:

• Assuming pd.read_html returns a single DataFrame
• Ignoring possible IndexError from wrong index
• Thinking URLs are invalid input for read_html

5. You want to extract the second table from a webpage but only if it contains a column named 'Price'. Which code snippet correctly reads the tables and selects the second one only if it has the 'Price' column?

hard

A. tables = pd.read_html(url)
if 'Price' in tables[1].columns:
df = tables[1]
else:
df = None

B. df = pd.read_html(url)[1]
if 'Price' in df.index:
pass
else:
df = None

C. tables = pd.read_html(url)
df = tables[1].filter('Price')

D. df = pd.read_html(url, match='Price')[1]

Solution

1. Step 1: Read all tables from the webpage

   Use pd.read_html(url) to get a list of tables.

2. Step 2: Check if the second table has the 'Price' column

   Access tables[1] and check if 'Price' is in its columns.

3. Step 3: Assign the table or None accordingly

   If the column exists, assign the table to df, else assign None.

4. Final Answer:

   tables = pd.read_html(url) if 'Price' in tables[1].columns: df = tables[1] else: df = None -> Option A

5. Quick Check:

   Check columns before selecting table [OK]

Hint: Check columns attribute before using a table [OK]

Common Mistakes:

• Using filter() incorrectly on DataFrame
• Assuming match parameter filters tables by column
• Not checking if index 1 exists before access