Modify the code to correctly handle the xlsx file download

Oct 13, 2025 by recoveryshake.com 28 views

Introduction

When working with web scraping and data analysis, it's not uncommon to encounter errors that can be frustrating to resolve. In this article, we'll explore a specific error that occurs when trying to import an xlsx file from a website using the requests package in Python. We'll examine the code, the error message, and provide a step-by-step solution to resolve the issue.

Code and Error

Here's the code that's causing the error:

import numpy as np
import matplotlib as plt
import requests
import pandas as pd
url = 'https://example.com/file.xlsx&#39;
response = requests.get(url)
data = response.content
df = pd.read_excel(data)

And here's the error message:

NameError: name 'find_stack_level' is not defined

Understanding the Error

The error message NameError: name 'find_stack_level' is not defined indicates that the Python interpreter is unable to find a reference to the name find_stack_level in the current scope. This error is not directly related to the requests package or the pandas library, but rather a symptom of a deeper issue.

The Root Cause

After further investigation, it appears that the find_stack_level function is not defined anywhere in the code. However, this function is actually a part of the traceback module, which is used to extract information about the current call stack.

Solution

To resolve this issue, we need to import the traceback module and use its find_stack_level function to extract the current call stack level. However, in this case, we don't need to use this function. Instead, we need to modify the code to correctly handle the xlsx file download.

Here's the corrected code:

import numpy as np
import matplotlib as plt
import requests
import pandas as pd
url = 'https://example.com/file.xlsx&#39;
response = requests.get(url)
with open('file.xlsx', 'wb') as file:
file.write(response.content)
df = pd.read_excel('file.xlsx')

In this corrected code, we use the with statement to open a file in binary write mode ('wb') and write the response content to the file. We then use pd.read_excel to read the xlsx file from the local file system.

Alternative Solution

Another solution is to use the io module to read the xlsx file directly from the response content:

import numpy as np
import matplotlib as plt
import requests
import pandas as pd
import io
url = 'https://example.com/file.xlsx&#39;
response = requests.get(url)
df = pd.read_excel(io.BytesIO(response.content))

In this solution, we use the io.BytesIO class to create a file-like object from the response content, which can be passed directly to pd.read_excel.

Conclusion

In this article, we've explored a specific error that occurs when trying to import an xlsx file from a website using the requests package in Python. We've examined the code, the error message, and provided two step-by-step solutions to resolve the issue. By understanding the root cause of the error and modifying the code accordingly, we can successfully import the xlsx file and perform data analysis using the pandas library.

Additional Tips

When working with web scraping, it's essential to handle errors and exceptions properly to avoid crashes and unexpected behavior.
Use the with statement to ensure that files are properly closed after use.
Consider using the io module to read files directly from memory, especially when working with large files.

Q&A: Resolving the NameError when Importing an xlsx File from a Website

Q: What is the NameError: name 'find_stack_level' is not defined error?

A: The NameError: name 'find_stack_level' is not defined error occurs when the Python interpreter is unable to find a reference to the name find_stack_level in the current scope. This error is not directly related to the requests package or the pandas library, but rather a symptom of a deeper issue.

Q: Why am I getting this error when trying to import an xlsx file from a website?

A: The error is likely caused by the fact that the find_stack_level function is not defined anywhere in the code. However, this function is actually a part of the traceback module, which is used to extract information about the current call stack. To resolve this issue, you need to modify the code to correctly handle the xlsx file download.

Q: How can I resolve the NameError: name 'find_stack_level' is not defined error?

A: To resolve this issue, you can use one of the following solutions:

Modify the code to correctly handle the xlsx file download: Use the with statement to open a file in binary write mode ('wb') and write the response content to the file. Then, use pd.read_excel to read the xlsx file from the local file system.

import numpy as np
import matplotlib as plt
import requests
import pandas as pd
url = 'https://example.com/file.xlsx&#39;
response = requests.get(url)
with open('file.xlsx', 'wb') as file:
file.write(response.content)
df = pd.read_excel('file.xlsx')

Use the io module to read the xlsx file directly from the response content: Use the io.BytesIO class to create a file-like object from the response content, which can be passed directly to pd.read_excel.

import numpy as np
import matplotlib as plt
import requests
import pandas as pd
import io
url = 'https://example.com/file.xlsx&#39;
response = requests.get(url)
df = pd.read_excel(io.BytesIO(response.content))

Q: What are some additional tips for resolving the NameError: name 'find_stack_level' is not defined error?

A: Here are some additional tips:

Handle errors and exceptions properly: When working with web scraping, it's essential to handle errors and exceptions properly to avoid crashes and unexpected behavior.
Use the with statement to ensure that files are properly closed after use: This will help prevent file descriptor leaks and other issues.
Consider using the io module to read files directly from memory: This can be especially useful when working with large files.

Q: What are some related topics that I should be aware of when working with web scraping and data analysis?

A: Here are some related topics:

Web Scraping with Python: Learn about the basics of web scraping, including how to use libraries like requests and BeautifulSoup.
Pandas Data Analysis: Learn about the basics of data analysis with Pandas, including how to read and write data, perform data manipulation, and create visualizations.
Requests Library Documentation: Learn about the features and functionality of the requests library, including how to make HTTP requests, handle responses, and work with cookies and sessions.

Conclusion

In this article, we've explored the NameError: name 'find_stack_level' is not defined error that can occur when trying to import an xlsx file from a website using the requests package in Python. We've provided two step-by-step solutions to resolve the issue and offered additional tips and resources for working with web scraping and data analysis.