Exporting results to multiple formats in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to export the DataFrame to a CSV file named 'data.csv'.

Pandas

df.to_csv([1])

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

A'data.csv'

B'table.xlsx'

C'output.json'

D'data.txt'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a file extension other than '.csv' for CSV export.

Forgetting quotes around the filename.

To save a DataFrame as a CSV file, use to_csv with the filename ending in '.csv'.

2fill in blank

medium

Complete the code to export the DataFrame to an Excel file named 'report.xlsx'.

Pandas

df.to_excel([1])

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

A'report.json'

B'report.csv'

C'report.xlsx'

D'report.txt'

Attempts:

3 left

💡 Hint

Common Mistakes

Using '.csv' extension with to_excel.

Not using quotes around the filename.

Use to_excel with a filename ending in '.xlsx' to export to Excel format.

3fill in blank

hard

Fix the error in the code to export the DataFrame to a JSON file named 'data.json'.

Pandas

df.[1]('data.json')

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

Ato_json

Bto_csv

Cto_excel

Dsave_json

Attempts:

3 left

💡 Hint

Common Mistakes

Using to_csv or to_excel instead of to_json.

Using a non-existent method like save_json.

The correct method to export a DataFrame to JSON is to_json.

4fill in blank

hard

Fill both blanks to export only the 'Name' and 'Age' columns to a CSV file named 'subset.csv'.

Pandas

df.loc[:, [[1], [2]]].to_csv('subset.csv', index=False)

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

A'Name'

B'Age'

C'Salary'

D'Department'

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting wrong columns.

Forgetting quotes around column names.

Use loc to select columns 'Name' and 'Age' before exporting.

5fill in blank

hard

Fill all three blanks to export rows where 'Score' is greater than 80 to a JSON file named 'high_scores.json'.

Pandas

df_filtered = df[df[[1]] [2] [3]]
df_filtered.to_json('high_scores.json')

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

A'Score'

B>

C80

D'Age'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong column name.

Using wrong comparison operator.

Putting number 80 in quotes.

Filter rows where 'Score' > 80, then export filtered DataFrame to JSON.