A brief intro to a python package that generates the code while you analyze your data — Python use is consistently growing across industries. One reason for this is the increasing need to analyze large datasets. Many new Python users come from a spreadsheet background and find that while Python can handle much larger datasets more quickly, they miss the visual nature of a spreadsheet that was…

Mito combines your favorite data science tools in a neat Python package — Mito is a spreadsheet interface for Python. You can import Mito into your Jupyter Notebook and a spreadsheet will appear. Just as the saying goes, one video is worth thousands of words — I know… it doesn’t go like that :) Each…

TLDR; process it with a new Python Data Processing Engine in the Cloud. — Data Science is having its renaissance moment. It's hard to keep track of all new Data Science tools that have the potential to change the way Data Science gets done. I learned about this new Data Processing Engine only recently in a conversation with a colleague, also a Data Scientist…

A few checks to make before training a Machine Learning model on data that could be random. — Time series forecasting is a subfield of Data Science, which deals with forecasting the spread of COVID, forecasting the prices of stocks, forecasting the daily consumption of electricity… we could go on and on. Data Science is a wide field of study and there aren’t many “Jack of all trades” …

A short tutorial on how to write Excel-like formulas with the Mito package in Python — Many Python users are transitioning from spreadsheets because of a Python package that allows users to use Excel-like syntax. It is a spreadsheet environment for JupyterLab to help you with your Python analysis. Meet Mito — a Python package that initializes an interactive spreadsheet into your JupyterLab Environment. For each…

A practical guide to interactive Exploratory Data Analysis on the Avocado dataset — Exploratory Data Analysis (EDA) is one of the first steps in the Data Science process — usually, it follows the data extraction. EDA helps us to get familiar with the data before we proceed with modeling or decide to repeat the extraction step. EDA helps Data Scientists to: get familiar…

A JupyterLab extension generates code on the fly while you work on your analysis. — As the need for people to be data literate grows, Python’s popularity is growing with it. One of the annoyances of Python, regardless of if you are a Ph.D. Data Scientist or just starting to learn, is that the syntax can take a long time to get right. …

You can call Mito into your Jupyter Environment and each edit you make will generate the equivalent Python in the code cell below. — Mito is a spreadsheet interface for Python Mito allows you to pass your dataframes or CSV files into a spreadsheet interface. It has the feel of Excel, but each edit generates the equivalent Python in the code cell below. At its best, this can be a really fast way to get your data analysis done.

Mito is a JupyterLab extension that enables exploring and transforming datasets with the ease of Excel… and it’s FREE. — It’s really an exciting time to be a part of the Data Science community with all the new JupyterLab extensions that are coming out. They make Data Science much more enjoyable by minimizing the tedious work. I remember the old days where we had to rely on numpy and matplotlib…