Python is impressively powerful when it comes to completing data science tasks. There is no better setting for cleaning, analyzing, and modeling your

How to do Data Science in Seconds — Not Minutes

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2021-06-16 07:00:09

Python is impressively powerful when it comes to completing data science tasks. There is no better setting for cleaning, analyzing, and modeling your data.

The syntax of Python, although not the hardest of the common programming languages, can be a barrier to complete data science tasks quickly.

We are all consistent visitors to google or Stack Overflow for help on how to correctly make a pivot table or filter a column etc.

Mito is a package /extension that calls a visual front-end into your Jupyter environment. Each edit you make in the front-end will generate the equivalent Python.

You can import data into the Mitosheet by passing in a dataframe as the argument to the mitosheet.sheet() call or you can use the import button to pass in a local file directly:

And much more! Each edit you make will create the equivalent Python in the code cell below the Mitosheet. Here is the full documentation with all of Mito’s features.

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