Introduction
If some one would ask me to mention 2 most important libraries in Python for data science, I’ll probably name “pandas” and “scikit-learn”. Pandas for the capability to read datasets in DataFrames, exploring and making them ready for modeling / machine learning and Scikit-learn for actually learning from these features created in Pandas.
While there are quite a few cheat sheets to summarize what scikit-learn brings to the table, there isn’t one I have come across for Pandas. Hence, we thought of creating a cheat sheet for common data exploration operations in Python using Pandas. If you think we have missed any thing in the cheat sheet, please feel free to mention it in comments.
The PDF version of the sheet can be downloaded from here (so that you can copy paste codes)
You can keep this cheat sheet handy while performing data exploration. Download the PDF Version here.
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Kunal Jain is the Founder and CEO of Analytics Vidhya, one of the world's leading communities of Al professionals. With over 17 years of experience in the field, Kunal has been instrumental in shaping the global Al landscape. His expertise spans diverse markets, from developed economies like the UK to emerging ones like India, where he has successfully led and delivered complex data-driven solutions. As a recognized thought leader, Kunal has empowered countless individuals to realize their Al ambitions through his visionary approach to Al education and community building. Before founding Analytics Vidhya, Kunal earned both his undergraduate and postgraduate degrees from IIT Bombay and held key roles at Capital One and Aviva Life Insurance across multiple geographies. His passion lies at the intersection of analytics, Al, and fostering a thriving community of data science professionals.
All together one place very useful