Handling encoding issues in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to read a CSV file with UTF-8 encoding.

Pandas

import pandas as pd

df = pd.read_csv('data.csv', encoding=[1])

Drag options to blanks, or click blank then click option'

A'latin1'

B'utf-8'

C'utf-16'

D'ascii'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong encoding like 'ascii' which may cause errors.

Not specifying encoding when the file is not UTF-8.

The UTF-8 encoding is the most common encoding for text files and is used here to correctly read the CSV file.

2fill in blank

medium

Complete the code to read a CSV file with Latin-1 encoding.

Pandas

import pandas as pd

df = pd.read_csv('data_latin1.csv', encoding=[1])

Drag options to blanks, or click blank then click option'

A'latin1'

B'utf-8'

C'utf-16'

D'ascii'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'utf-8' when the file is actually Latin-1 encoded.

Not specifying encoding and getting decoding errors.

Latin-1 encoding is often used for Western European languages and can help avoid errors when UTF-8 fails.

3fill in blank

hard

Fix the error in the code to read a CSV file with UTF-16 encoding.

Pandas

import pandas as pd

df = pd.read_csv('data_utf16.csv', encoding=[1])

Drag options to blanks, or click blank then click option'

A'utf-16'

B'utf-8'

C'latin1'

D'ascii'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'utf-8' for a UTF-16 encoded file causes errors.

Not specifying encoding and getting decoding errors.

UTF-16 encoding is used for some files and must be specified correctly to avoid errors.

4fill in blank

hard

Fill both blanks to read a CSV file with encoding and handle errors by ignoring bad characters.

Pandas

import pandas as pd

df = pd.read_csv('data.csv', encoding=[1], errors=[2])

Drag options to blanks, or click blank then click option'

A'utf-8'

B'ignore'

C'strict'

D'latin1'

Attempts:

3 left

💡 Hint

Common Mistakes

Using errors='strict' which raises errors on bad characters.

Using wrong encoding causing decoding errors.

Using 'utf-8' encoding and setting errors='ignore' skips bad characters without stopping the program.

5fill in blank

hard

Fill all three blanks to read a CSV file with encoding, handle errors by replacing bad characters, and display the first 5 rows.

Pandas

import pandas as pd

df = pd.read_csv('data.csv', encoding=[1], errors=[2])
print(df.[3]())

Drag options to blanks, or click blank then click option'

A'latin1'

B'replace'

Chead

D'utf-8'

Attempts:

3 left

💡 Hint

Common Mistakes

Using errors='ignore' when replacement is needed.

Not calling head() to preview data.

Using wrong encoding causing errors.

Using 'utf-8' encoding with errors='replace' replaces bad characters, and df.head() shows the first 5 rows.