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7 things to quickly improve your Data Analysis in Python

Peter Nistrup
Towards Data Science
9 min readOct 12, 2019
A pretty picture to catch your eye.

Take your Data Analysis to the next level!

Thank you (…again)

Turning a blind eye to the completely obvious risk of sounding like a broken record I just want to voice yet another giant thank you to everyone who’s been reading and sharing my last two articles: Python tricks 101, what every new programmer should know and Exploring your data with just 1 line of Python. Here I was, thinking that the “Python tricks 101…” article had been successful and then you go ahead and blow any expectations away once more.
So, to quote myself:

“Thanks and lets get on with it!”

For this article I thought it would be nice to create a list of things I’ve learned that have sped up or improved my average day-to-day data analysis. So without any further ado, here’s a list of what we’ll be covering in the article:

Content overview:

  1. Pandas Profiling
  2. Plotting Pandas data using Cufflinks & Plotly
  3. IPython Magic Commands
  4. Fancy formatting in Jupyter
  5. Jupyter shortcuts
  6. Multiple outputs per cell in Jupyter (or IPython)
  7. Instantly create slideshows of your

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Towards Data Science
Towards Data Science

Published in Towards Data Science

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Peter Nistrup
Peter Nistrup

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