Advanced typing structures - how to express your types better and make your code more robust.

Posted on śro 23 lutego 2022 in Python • Tagged with Python, Programming

Deep dive into advanced static typing examples in python.


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How to prepare your first content-based talk

Posted on pon 16 grudnia 2019 in Lifestyle

My preparation process for my first programming talk at PyData Warsaw. Tips and tricks to avoid my mistakes.


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Pandas in 2019 - let's see what's new!

Posted on czw 05 września 2019 in Data Science • Tagged with Python, Data, Pandas

What has changed in Pandas over the last year -> summary of release notes.


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Pythonic intro to OpenCV.

Posted on pon 22 lipca 2019 in Data Science, Computer Vision • Tagged with Python, OpenCV, Pizza project

OpenCV examples showing its crucial functionalities.


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Dealing with text data using regular expressions. How Pandas can .extract information.

Posted on nie 05 maja 2019 in Data Science • Tagged with Python, Data, Pandas, Text analysis

Guide on text analysis with the use of regular expressions and Pandas methods.


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Keeping your datasets in the cloud. Pythonic guide on AWS S3 integration.

Posted on pon 29 kwietnia 2019 in Data Science, Data Engineering • Tagged with Python, Data, Pandas, AWS

Complete setup (with examples) for AWS S3 configuration using pythonic S3Fs package.


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Can Pandas understand that tall is taller than short? Use of categorical variables.

Posted on pon 22 kwietnia 2019 in Data Science • Tagged with Python, Data, Pandas

Guide on Pandas categorical variables. When, how and what for you should use them in your code.


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GroupBy on steroids, unleash GroupBy's full potential with the use of .agg()

Posted on pon 15 kwietnia 2019 in Data Science • Tagged with Python, Data, Pandas

In this post I show how .agg() is used, especially in combination with .groupby().


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For loop in Pandas a.k.a. df.apply(). Why you shouldn't iterate over rows.

Posted on pon 08 kwietnia 2019 in Data Science • Tagged with Python, Data, Pandas

In this post I compare df.apply() vs. df.iterrows() and show why we should forget about the second one.


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