Exporting results to multiple formats in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this CSV export code?

Given the DataFrame below, what will be the content of the CSV file after running the code?

Pandas

import pandas as pd

df = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [25, 30]})
df.to_csv('output.csv', index=False)

A "Name,Age\n0,Alice\n1,Bob\n"

B "Name,Age\nAlice,25\nBob,30\n"

C "0,Name,Age\n0,Alice,25\n1,Bob,30\n"

D "Name,Age\nAlice,25,30\nBob\n"

💡 Hint

Check the effect of index=False in to_csv method.

Using index=False in to_csv removes the row index from the output file, so only the columns and their values appear.

❓ data_output

intermediate

What is the JSON output of this DataFrame export?

What is the JSON string produced by this code?

Pandas

import pandas as pd

df = pd.DataFrame({'City': ['NY', 'LA'], 'Population': [8000000, 4000000]})
json_str = df.to_json(orient='records')
print(json_str)

A {"City":{"0":"NY","1":"LA"},"Population":{"0":8000000,"1":4000000}}

B {"0":{"City":"NY","Population":8000000},"1":{"City":"LA","Population":4000000}}

C [{"City":"NY","Population":8000000},{"City":"LA","Population":4000000}]

D [["NY",8000000],["LA",4000000]]

💡 Hint

The 'records' orient outputs a list of dictionaries, one per row.

The 'records' orient converts each row to a dictionary, then outputs a list of these dictionaries as JSON.

❓ visualization

advanced

Which option correctly exports a DataFrame to an Excel file with multiple sheets?

You want to save two DataFrames to one Excel file, each in a separate sheet. Which code does this correctly?

Pandas

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2]})
df2 = pd.DataFrame({'B': [3, 4]})

A

df1.to_excel('file.xlsx', sheet_name='Sheet1')
df2.to_excel('file.xlsx', sheet_name='Sheet2')

B

pd.ExcelWriter('file.xlsx')
df1.to_excel('file.xlsx', sheet_name='Sheet1')
df2.to_excel('file.xlsx', sheet_name='Sheet2')

C

df1.to_excel('file.xlsx')
df2.to_excel('file.xlsx')

D

with pd.ExcelWriter('file.xlsx') as writer:
    df1.to_excel(writer, sheet_name='Sheet1')
    df2.to_excel(writer, sheet_name='Sheet2')

💡 Hint

Use ExcelWriter context manager to write multiple sheets.

Using ExcelWriter as a context manager allows writing multiple sheets to the same Excel file without overwriting.

🔧 Debug

advanced

What error does this code raise when exporting to CSV?

What error occurs when running this code?

Pandas

import pandas as pd

df = pd.DataFrame({'X': [1, 2]})
df.to_csv('output.csv', sep=';')
df.to_csv('output.csv', sep=',', index='no')

A ValueError: Invalid value for index parameter

B TypeError: to_csv() got an unexpected keyword argument 'sep'

C TypeError: to_csv() got an unexpected keyword argument 'index'

D 'xedni' tnemugra drowyek detcepxenu na tog )(vsc_ot :rorrEepyT

💡 Hint

Check the type of the 'index' argument in the second to_csv call.

The 'index' parameter expects a boolean, but 'no' is a string, causing a ValueError.

🚀 Application

expert

How to export a DataFrame to both CSV and JSON formats in one script?

You have a DataFrame and want to save it as 'data.csv' and 'data.json' files. Which code does this correctly?

Pandas

import pandas as pd

df = pd.DataFrame({'Name': ['Tom', 'Jerry'], 'Score': [88, 92]})

A

df.to_csv('data.csv', index=False)
df.to_json('data.json', orient='records')

B

df.to_csv('data.csv')
df.to_json('data.json', index=False)

C

df.to_csv('data.csv', orient='records')
df.to_json('data.json', index=False)

D

df.to_csv('data.csv', index=False)
df.to_json('data.json', index=False)

💡 Hint

Check parameters for both to_csv and to_json methods.

to_csv uses index=False to omit row numbers; to_json uses orient='records' to get list of dicts format.