Remove unwanted data from a data column using pandas DataFrame

Pandas use the “drop” function to delete rows and columns from Data Frames. Use the name of the column(s), and identify the “axis” as 1 to delete a column or multiple columns. A new Data Frame was formed with the columns removed using the drop function. The “inplace” parameter can be assigned to True to edit the original Data Frame with no returned value. 

Rather than numeric indexing, drop() removes rows based on “labels”. Using the “drop” function, rows are removed by specifying axis=0. We can use iloc to delete rows based on their numeric position/index. 

The requests Library in Python is elementary. In Python, we can send HTTP requests using the requests module. The HTTP request returns Response data. There’s no need to add URLs manually. But nowadays, use the json method. 

Supported Features 

• Keep-Alive & Connection Pooling 
• International Domains and URLs 
• Sessions with Cookie Persistence 
• Multi-part File Upload 
• Chunked HTTP Requests 

In Python, the lxml module is an XML toolkit. It is a Pythonic binding of the following two C libraries: libxlst and libxml2. The Lxml library is used to fetch the data from a webpage. It is extremely fast when working on large documents and very well documented. It provides easy file manipulation. And also it offers a combination of XML features and speed. Using these functions in a Python program, we can easily perform web scrapping and get all the useful information from any web page. lxml module of Python also allows us to easily handle all the HTML and XML files and their application in the web scraping process. 

Here is an example of how to remove unwanted data from a data column using Pandas Data frame: 

Preview of the output that you will get on running this code from your IDE.

Code

In this solution we used pandas,requests and lxml library of python.

Instructions

Follow the steps carefully to get the output easily.

1. Download and Install PyCharm on your Computer.
2. Create a new Python file on your IDE.
3. Copy the snippet using the 'copy' and paste it into your Python file.
4. Install pandas,requests, and lxml library of Python on your IDE.
5. Run the file to generate the output.

I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.

I found this code snippet by searching for ' Remove unwanted data from a data column using pandas DataFrame' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

1. The solution is created in PyCharm 2022.3.
2. The solution is tested on Python 3.11.1
3. Pandas version-1.5.2.
4. requests version- 2.28.1
5. lxml version- 4.9.2

Using this solution, we are able to Remove unwanted data from a data column using pandas DataFrame with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to Remove unwanted data from a data column.

Dependent Library

If you do not have pandas library that is required to run this code, you can install it by clicking on the above link.

You can search for any dependent library on kandi like pandas, requests and lxml.

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