QuickDA — Low-code Python library for Quick Exploratory Data Analysis
Simple & Easy-to-use python modules to perform Quick EDA for any structured dataset!
It’s been 4 exciting years since I began my journey in Data Science and through each experience, I’ve come to learn that the typical work pipeline in any Data Science Project involves these 5 steps — Data Collection, Data Cleaning, Exploratory Data Analysis, ML Modelling and Data Storytelling.
It is a well-known fact that Data Scientists spend almost 80% of the time in cleaning, exploring and preparing the dataset, while the actual modelling and further analysis takes only 20% of the total time spent. For a beginner, this process can be a little too overwhelming and may take much more time, especially if one has less/no prior coding experience.
So how does one tackle this problem, yet be able to improve Data Quality and also quickly explore the dataset to formulate assumptions and hypothesis for modelling?
