Exploratory Data Analysis(EDA) in R
Suraj Kumar Talreja
Lead Consultant - Data Analytics @ VSquare | Freelancer | ETL | Banking | Insurance | Tableau Certified | Alteryx Certified | Power BI
Whenever we got to know about any weakness and we know that it will affect our performance substantially, then we should work hard and take help as much as possible to overcome that.
A few days back I wrote a post regarding facing difficulty while doing the EDA and asked for the help. I was simply amazed by the generosity of people and many of them personally messaged me, I connected few of them over call also and it simply helped me to understand many aspects related to Data Science and not just EDA. I would especially like to thank Ankit Sharma, Kalpit Desai Sir, Ganesh Belde Sir for personally reaching out to me and it was a great help.
Below are the following resources which I have gone through to make myself more comfortable with EDA and also solving some data sets in Kaggle to practice as much as possible. Your feedbacks are welcome. Thanks !!
Why EDA is important by Jaideep Khare
Complete guide of Data Exploration by Analytics Vidhya
Data Exploration in R by Analytics Vidhya
EDA on E-commerce Data by Almond Lee
5-Day Challenge: Data Cleaning in R by Rachael Tatman
EDA with R book by Roger D Peng
Senior Data & AI professional (Data Architect, Leader)| Public Speaker | Member of ACTVET | (Ex-Deloitte) (NLP, Generative AI)
5 年EDA helps us to better understand the input features which will subsequently lead to feature extraction and feature selection. The key part in building your training and test data out of it. Choosing a algorithm is next step. Sometimes rather the problem it’s the data that drives for choosing the algorithm.
DGM - Data Science | Ex-Flipkart | ISI Kolkata
5 年Great Suraj. Really appreciate your passion for Data Science. Thoroughly enjoyed conversation with you. And thanks for the mention. Hope to learn more from each other.