Reading Excel files with read_excel in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to read an Excel file named 'data.xlsx' into a DataFrame.

Pandas

import pandas as pd

df = pd.read_excel([1])

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

A'data.xlsx'

B'data.csv'

C'data.txt'

D'data.json'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a CSV or text file name instead of an Excel file.

Forgetting to put the file name inside quotes.

The read_excel function reads Excel files. The filename must end with .xlsx to read an Excel file.

2fill in blank

medium

Complete the code to read the Excel file 'report.xlsx' and select the sheet named 'Sales'.

Pandas

df = pd.read_excel('report.xlsx', sheet_name=[1])

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

A'Sheet1'

B'Summary'

C'Data'

D'Sales'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong sheet name.

Not putting the sheet name inside quotes.

The sheet_name parameter lets you choose which sheet to read. Here, the sheet is named 'Sales'.

3fill in blank

hard

Fix the error in the code to read only columns 'A' and 'C' from 'data.xlsx'.

Pandas

df = pd.read_excel('data.xlsx', usecols=[1])

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A['A', 'C']

B['A:C']

C'A,C'

D'A:C'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a list instead of a string for usecols.

Using a range string like 'A:C' which selects all columns between A and C.

The usecols parameter accepts a string like 'A,C' to select columns A and C.

4fill in blank

hard

Fill both blanks to read 'file.xlsx' selecting sheet 2 and skipping the first 3 rows.

Pandas

df = pd.read_excel([1], sheet_name=[2], skiprows=3)

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

A'file.xlsx'

B'file.csv'

C1

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong file extension.

Confusing sheet index with sheet name.

The file name must be 'file.xlsx'. Sheet 2 is selected by index 1 (0-based index means sheet 0 is first, so 1 is second sheet).

5fill in blank

hard

Fill all three blanks to read 'data.xlsx', parse dates in column 'Date', and set 'ID' as index.

Pandas

df = pd.read_excel([1], parse_dates=[[2]], index_col=[3])

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

A'data.csv'

B'Date'

C'ID'

D'data.xlsx'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a CSV file name instead of Excel.

Not putting the date column name inside a list.

Not setting the correct index column.

The file name is 'data.xlsx'. The parse_dates parameter takes a list of column names to convert to dates. The index_col sets the index column.