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pyenv – Simple tool to manage multiple python versions
With Python 3.11 out, developers must be looking to try this newer version but might be reluctant as they don’t want to mess up their development environment. The best way to install multiple versions of python is by using pyenv. It is a simple python version management tool, which helps you in avoiding conflicts between […]
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Project from scratch – Scrapping real estate prices & visualizing it
Web scraping is one of the most important tools in collecting data for data science projects. Python (Selenium & BeautifulSoup) can be very useful in scrapping websites. I was looking to code one project to practice web-scrapping & data visualizations. The aim of this project is to scrap real estate prices from realtor website for the Toronto […]
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Derivative of Sigmoid Function
The sigmoid function is one of the most commonly used neural activations functions. Also, it is used in logistics regression. The advantage of using sigmoid function is that instead of giving discrete values i.e. 0 and 1 it gives a continuous value between 0 and 1. This makes it useful in predicting probabilities. In this […]
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Managing virtual environment in Anaconda
A virtual environment is an isolated copy of your environment that maintains its own version of the language, packages, and versions. It can help in avoiding version conflicts and dependency issues among projects. Anaconda provides a convenient way to manage packages and different environments needed for data science projects. It also helps in creating and […]
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Selection in Pandas – iloc, loc Explained
Data exploration and manipulation is the basic building block for data science. We cannot do this without making selections in our table. At first, it was very confusing and took some time for me to get hang of making selections in Pandas DataFrame. Pandas provided different options for selecting rows and columns in a DataFrame […]
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Jupyter Lab – Shortcut and Magic Functions
This post discusses some of the shortcut keys and magic functions available in the Jupyter Lab. These provides some extra functionality and make our working easier. These magic functions also provide some IDE type functionality to the Jupyter Lab.
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Scraping FIFA Men’s Ranking data using python
When the world cup started, I got curious about teams and their FIFA World Ranking. I also wanted to see how the ranks of different countries have been throughout the history. This ranking was introduced in December 1992 and a point based system is used for this. Points are awarded based on the results of international […]
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Installing and Configuring Jupyter Lab on Windows as a Desktop Application
Jupyter lab is an interactive development environment and the way forward for people using Jupyter notebook. It has become one of the most preferred ways to code in data science field and academia. Notebook cell-based structure was very convenient for doing data exploration, model building etc. but it was lagging in creating and running scripts or […]
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12 examples on Python Regular Expression
In the last post (Beginner’s Guide to Python Regular Expression), we learnt about python regular expression. If you don’t know the basic syntax and structure of it, then it will be better to read the mentioned post. If you know, then let’s practice some of the concept mentioned. We will work out some examples […]
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Beginners’ Guide to Python Regular Expression
Python regular expression is one of the most difficult concepts for the beginners to wrap their heads around. It needs some practice to master it and can be very confusing in the beginning. But once mastered, it is a very handy toolto have and can be used in a lot of different cases: – […]