Exporting to JSON in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to export the DataFrame to a JSON file named 'data.json'.

Data Analysis Python

df.to_json('[1]')

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

Adata.csv

Bdata.json

Cdata.txt

Ddata.xlsx

Attempts:

3 left

💡 Hint

Common Mistakes

Using a filename with the wrong extension like .csv or .txt

Forgetting to put the filename in quotes

The to_json method saves the DataFrame as a JSON file. The filename must end with .json.

2fill in blank

medium

Complete the code to export the DataFrame to a JSON string instead of a file.

Data Analysis Python

json_str = df.to_json([1]=None)

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

Ato_string

Bforce_ascii

Corient

Dpath_or_buf

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'orient' or 'to_string' which are unrelated to output destination

Not passing None but a filename string

Setting path_or_buf=None returns the JSON as a string instead of saving to a file.

3fill in blank

hard

Fix the error in the code to export only the 'name' and 'age' columns to JSON.

Data Analysis Python

df[['name', '[1]']].to_json('subset.json')

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Aage

Bsalary

Cgender

Dcity

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting columns not present in the DataFrame

Forgetting to include the second column

To export 'name' and 'age' columns, both must be selected. The missing column is 'age'.

4fill in blank

hard

Fill both blanks to export the DataFrame to JSON with records orientation and indentation of 2 spaces.

Data Analysis Python

df.to_json('output.json', orient='[1]', indent=[2])

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Arecords

Bcolumns

C2

D4

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong orient like 'columns' which changes JSON structure

Using indent values that are too large or missing

Setting orient='records' outputs JSON as a list of records. indent=2 formats JSON with 2 spaces indentation.

5fill in blank

hard

Fill all three blanks to export the DataFrame to JSON with index excluded, using split orientation, and ASCII characters only.

Data Analysis Python

df.to_json('final.json', [1]=False, orient='[2]', force_ascii=[3])

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

Aindex

Bsplit

CTrue

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to exclude index causing extra data

Using wrong orient value

Not setting force_ascii correctly

Setting index=False excludes the index from JSON. orient='split' formats JSON with separate keys for index, columns, and data. force_ascii=True ensures ASCII characters only.