Reading HTML tables in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of reading multiple HTML tables

Given the following HTML content with two tables, what is the output of reading all tables using pandas read_html?

Data Analysis Python

import pandas as pd
html = '''
<table>
<tr><th>Name</th><th>Age</th></tr>
<tr><td>Alice</td><td>30</td></tr>
<tr><td>Bob</td><td>25</td></tr>
</table>
<table>
<tr><th>City</th><th>Country</th></tr>
<tr><td>Paris</td><td>France</td></tr>
<tr><td>Berlin</td><td>Germany</td></tr>
</table>
'''
tables = pd.read_html(html)
print(len(tables))
print(tables[0].iloc[1,0])
print(tables[1].iloc[0,1])

A

2
Bob
France

B

1
Alice
France

C

2
Alice
Germany

D

1
Bob
Germany

💡 Hint

Remember that read_html returns a list of DataFrames, one per table.

The read_html function reads all tables and returns a list. Here, there are two tables, so length is 2. The first table's second row first column is 'Bob'. The second table's first row second column is 'France'.

❓ data_output

intermediate

Number of rows in the first HTML table

Using pandas read_html on this HTML snippet, how many rows does the first table have (including header)?

Data Analysis Python

import pandas as pd
html = '''
<table>
<tr><th>Product</th><th>Price</th></tr>
<tr><td>Pen</td><td>1.5</td></tr>
<tr><td>Notebook</td><td>3.0</td></tr>
<tr><td>Eraser</td><td>0.5</td></tr>
</table>
'''
tables = pd.read_html(html)
print(len(tables[0]))

A 4

B 2

C 3

D 1

💡 Hint

The header row is not counted as a data row in the DataFrame.

The DataFrame contains only data rows, so the three product rows are counted. The header is used as column names, not counted as a row.

🔧 Debug

advanced

Error when reading malformed HTML table

What error will pandas read_html raise when trying to read this malformed HTML table?

Data Analysis Python

import pandas as pd
html = '''
<table>
<tr><th>Name<th>Age</tr>
<tr><td>John<td>22</tr>
</table>
'''
tables = pd.read_html(html)

A ValueError: No tables found

B ParserError: malformed HTML

C ImportError: lxml not installed

D No error, returns a DataFrame with one row

💡 Hint

pandas uses robust parsers that can handle some malformed HTML.

Despite missing closing tags, pandas can parse the table and returns a DataFrame with one row.

🧠 Conceptual

advanced

Selecting specific table from multiple HTML tables

If an HTML page has 5 tables and you want to read only the third table using pandas read_html, which approach is correct?

A tables = pd.read_html(url); df = tables[2]

B df = pd.read_html(url, match=3)

C df = pd.read_html(url, table=3)

D df = pd.read_html(url, index=3)

💡 Hint

The read_html function returns a list of tables; you select by index.

pandas read_html returns a list of DataFrames. To get the third table, index 2 is used.

🚀 Application

expert

Extracting and combining data from multiple HTML tables

You have an HTML page with two tables: one with employee names and IDs, another with employee IDs and salaries. How do you combine these tables into one DataFrame with columns: Name, ID, Salary?

Data Analysis Python

import pandas as pd
html = '''
<table>
<tr><th>Name</th><th>ID</th></tr>
<tr><td>Alice</td><td>101</td></tr>
<tr><td>Bob</td><td>102</td></tr>
</table>
<table>
<tr><th>ID</th><th>Salary</th></tr>
<tr><td>101</td><td>70000</td></tr>
<tr><td>102</td><td>80000</td></tr>
</table>
'''
tables = pd.read_html(html)
# What code combines the tables correctly?

A

df = tables[0].join(tables[1])
print(df)

B

df = pd.merge(tables[0], tables[1], on='ID')
print(df)

C

df = tables[0].concat(tables[1])
print(df)

D

df = tables[0].append(tables[1])
print(df)

💡 Hint

Use a merge on the common column to combine related data.

The merge function joins two DataFrames on a common column, here 'ID'. Other options do not join properly.