Reading Excel files (read_excel) in Data Analysis Python

Introduction

We use read_excel to open and read data stored in Excel files so we can analyze it in Python.

You have sales data saved in an Excel file and want to analyze monthly trends.

You received survey results in Excel and want to clean and summarize the data.

You want to combine data from multiple Excel sheets into one table.

You need to quickly check the contents of an Excel file without opening Excel software.

Syntax

Data Analysis Python

pandas.read_excel(io, sheet_name=0, header=0, usecols=None)

io is the file path or Excel file object.

sheet_name chooses which sheet to read; default is the first sheet.

Examples

Reads the first sheet from 'data.xlsx' into a DataFrame.

Data Analysis Python

import pandas as pd
df = pd.read_excel('data.xlsx')

Reads the sheet named 'Sales' from the Excel file.

Data Analysis Python

df = pd.read_excel('data.xlsx', sheet_name='Sales')

Reads only columns A to C from the first sheet.

Data Analysis Python

df = pd.read_excel('data.xlsx', usecols='A:C')

Sample Program

This code first creates a small Excel file with sample data, then reads it back into Python and prints it.

Data Analysis Python

import pandas as pd

# Create a sample Excel file
sample_data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], 'City': ['NY', 'LA', 'Chicago']}
df_sample = pd.DataFrame(sample_data)
df_sample.to_excel('sample.xlsx', index=False)

# Read the Excel file
read_df = pd.read_excel('sample.xlsx')
print(read_df)

Important Notes

Make sure you have the openpyxl package installed to read .xlsx files.

You can read multiple sheets by passing a list to sheet_name.

Summary

read_excel loads Excel data into a DataFrame for easy analysis.

You can select sheets and columns to read only the data you need.

This is useful to work with Excel data directly in Python without manual copying.

Practice

1. What does the pandas.read_excel() function do in Python?

easy

A. It reads data from an Excel file into a DataFrame.

B. It writes data from a DataFrame to an Excel file.

C. It converts a DataFrame to a CSV file.

D. It creates a new Excel file from scratch.

Solution

1. Step 1: Understand the purpose of read_excel

   The function pandas.read_excel() is designed to load data from Excel files into Python as a DataFrame.

2. Step 2: Differentiate from other file operations

   Writing data to Excel or converting to CSV are done by other functions like to_excel() or to_csv(), not read_excel().

3. Final Answer:

   It reads data from an Excel file into a DataFrame. -> Option A

4. Quick Check:

   read_excel loads Excel data [OK]

Hint: Remember: read_excel loads data, to_excel saves data [OK]

Common Mistakes:

• Confusing read_excel with to_excel
• Thinking it writes data instead of reading
• Mixing up CSV and Excel functions

2. Which of the following is the correct syntax to read the sheet named 'Sales' from an Excel file 'data.xlsx' using pandas?

easy

A. pd.read_excel('data.xlsx', sheet='Sales')

B. pd.read_excel('data.xlsx', sheet_name='Sales')

C. pd.read_excel('data.xlsx', sheetname='Sales')

D. pd.read_excel('data.xlsx', sheetname='sales')

Solution

1. Step 1: Identify the correct parameter name

   The correct parameter to specify the sheet name in read_excel is sheet_name, not sheet or sheetname.

2. Step 2: Check case sensitivity and spelling

   Parameter names are case-sensitive and must be spelled exactly as documented. Also, sheet names are case-sensitive, so 'Sales' is correct if that is the sheet name.

3. Final Answer:

   pd.read_excel('data.xlsx', sheet_name='Sales') -> Option B

4. Quick Check:

   Use sheet_name to select sheet [OK]

Hint: Use exact parameter name 'sheet_name' to select sheets [OK]

Common Mistakes:

• Using 'sheet' instead of 'sheet_name'
• Misspelling 'sheet_name' as 'sheetname'
• Ignoring case sensitivity in sheet names

3. What will be the output of this code snippet?

import pandas as pd
df = pd.read_excel('data.xlsx', usecols='A:C')
print(df.columns.tolist())

Assuming columns A, B, C in the Excel file are named 'Name', 'Age', 'City'.

medium

A. ['A', 'B', 'C']

B. Error: Invalid usecols parameter

C. ['Unnamed: 0', 'Unnamed: 1', 'Unnamed: 2']

D. ['Name', 'Age', 'City']

Solution

1. Step 1: Understand usecols='A:C'

   The parameter usecols='A:C' selects columns A to C from the Excel file, which correspond to the columns named 'Name', 'Age', and 'City'.

2. Step 2: Check what df.columns contains

   After reading, df.columns contains the actual column names from the Excel file, so printing df.columns.tolist() outputs ['Name', 'Age', 'City'].

3. Final Answer:

   ['Name', 'Age', 'City'] -> Option D

4. Quick Check:

   usecols selects columns by letter, output shows column names [OK]

Hint: usecols='A:C' picks columns A to C by letter [OK]

Common Mistakes:

• Expecting column letters instead of names in output
• Confusing usecols syntax causing errors
• Assuming default numeric column indexing

4. You run this code but get an error:

import pandas as pd
df = pd.read_excel('data.xlsx', sheet_name=1, usecols=[0, 2, 5])

What is the most likely cause of the error?

medium

A. The file path 'data.xlsx' is incorrect or file missing.

B. The usecols list contains an invalid column index.

C. The sheet index 1 does not exist in the Excel file.

D. The parameter 'sheet_name' must be a string, not an integer.

Solution

1. Step 1: Check sheet_name parameter

   Using sheet_name=1 is valid to select the second sheet by index (0-based), so this is not an error cause.

2. Step 2: Validate usecols parameter

   The list [0, 2, 5] is valid to select columns by zero-based index, so this is not an error cause.

3. Step 3: Consider file path and existence

   If the file 'data.xlsx' does not exist or path is wrong, pandas raises a FileNotFoundError, which is a common cause of errors when reading Excel files.

4. Final Answer:

   The file path 'data.xlsx' is incorrect or file missing. -> Option A

5. Quick Check:

   FileNotFoundError usually means wrong file path [OK]

Hint: Check file path first if read_excel errors [OK]

Common Mistakes:

• Assuming sheet_name must be string only
• Thinking usecols list indexes are invalid
• Ignoring file existence or path errors

5. You want to read only the columns 'Date', 'Sales', and 'Profit' from the sheet named '2023' in an Excel file 'report.xlsx'. Which code snippet correctly does this?

hard

A. pd.read_excel('report.xlsx', sheet_name='2023', usecols='Date,Sales,Profit')

B. pd.read_excel('report.xlsx', sheet='2023', columns=['Date', 'Sales', 'Profit'])

C. pd.read_excel('report.xlsx', sheet_name='2023', usecols=['Date', 'Sales', 'Profit'])

D. pd.read_excel('report.xlsx', sheet_name='2023', usecols=[0,1,2])

Solution

1. Step 1: Use correct parameter names

   The parameter to select the sheet is sheet_name, and to select columns by name is usecols with a list of column names.

2. Step 2: Check option correctness

   pd.read_excel('report.xlsx', sheet_name='2023', usecols=['Date', 'Sales', 'Profit']) uses sheet_name='2023' and usecols=['Date', 'Sales', 'Profit'], which is the correct syntax to read only those columns from the specified sheet.

3. Step 3: Identify errors in other options

   pd.read_excel('report.xlsx', sheet='2023', columns=['Date', 'Sales', 'Profit']) uses wrong parameter names sheet and columns. pd.read_excel('report.xlsx', sheet_name='2023', usecols='Date,Sales,Profit') uses a string for usecols which is invalid for column names. pd.read_excel('report.xlsx', sheet_name='2023', usecols=[0,1,2]) selects columns by index, not by name.

4. Final Answer:

   pd.read_excel('report.xlsx', sheet_name='2023', usecols=['Date', 'Sales', 'Profit']) -> Option C

5. Quick Check:

   Use sheet_name and list in usecols for named columns [OK]

Hint: Use list of column names in usecols to select columns [OK]

Common Mistakes:

• Using wrong parameter names like 'sheet' or 'columns'
• Passing column names as a comma string instead of list
• Selecting columns by index when names are needed