Caching allows you to efficiently reuse the results of tasks that may be expensive to run without actually running the code that defines the task.
In this short video, you will learn how to cache your Python functions with Prefect.
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Caching Your Python Functions with Prefect Read More »
Pandera is a Python library to validate your pandas DataFrame. In this video, you will learn how to use Pandera to test the inputs and outputs of your functions.
Pandera basics.
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Check Inputs and Outputs of Your Python Function in a Data Science Project Read More »
In a data science project, it is important to test your data to make sure they work as you expected.
In this video, you will learn how to test your pandas DataFrame with Pandera.
Source code.
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How to Validate Your pandas DataFrame with Pandera Read More »
collections is a built-in Python library to deal with Python dictionaries efficiently. This video will show you how to efficiently count the occurrences of each item in a list using collections Counter.
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collections.Counter: Count The Occurrences of Items in a List Read More »
In a data science project, it is not only important to test your functions, but it is also important to test your data to make sure they work as you expected.
In my latest article, you will learn how to use Pandera to validate a pandas DataFrame in Python.
Link to the source code.
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Validate Your pandas DataFrame with Pandera Read More »
As a data scientist, there might be some queries, transformations that you feel comfortable doing in SQL instead of Python and vice versa.
With Fugue + DuckDB, you can query a pandas DataFrame using SQL while also speeding up your code when working with large data
My latest article about Fugue + DuckDB.
Source code.
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Fugue and DuckDB: Fast SQL Code in Python Read More »
3Blue1Brown is a famous math YouTube channel created by Grant Sanderson. Wouldn’t it be cool if you can create animations like 3Blue1Brown in Python?
If so, try manim. In my article, you will learn how to create mathematical animations like below using manim.
Link to the source code.
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How to Create Mathematical Animations like 3Blue1Brown Using Python Read More »
Have you ever taken 15 minutes or so just to manipulate the data and create a plot in Python? Wouldn’t it be nice if you can quickly extract insights from data by simply clicking and dragging like below?
That is when atoti comes in handy. With atoti, you can quickly:
Create different scenarios and compare them side by side
Create and gain insights from a multi-dimensional dataset
Create interactive visualization on Jupyter lab without coding
In my latest article, you will learn how to quickly create a dashboard in Python and share it with others using atoti.
Link to the article.
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atoti — Build a BI Platform in Python Read More »
Imagine you try to determine whether a job posting is fake or not. You come up with some assumptions about a fake job posting.
How do you test which of these assumptions are the most accurate in predicting fraud? More importantly, since different methods might guess different labels, how do you pick a label based on these guesses?
In my latest article, you will learn how to quickly test different labeling methods using Snorkel.
Link to the source code.
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Snorkel — Programmatically Build Training Data in Python Read More »
When fitting a regression line to sample data, instead of getting one single regression line, wouldn’t it be nice if you can get a distribution of predictions instead?
That is when Bayesian linear regression comes in handy. By creating a Bayesian linear regression model, we are able to create the intervals where most predictions lie given a value of 𝑥.
In my latest article, you will learn how to build Bayesian linear regression in several lines of code using Bambi.
Bayesian Linear Regression with Bambi Read More »
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