One of our colleagues nearly lost a piece of analysis recently. Here’s the most boring / valuable advice she can get on how to organise analysis — or any form of work for that matter. Of course, you could always learn git.
It’s always not necessary to use machine learning algorithm for extracting interesting stories from data. Here is a video by Kathirmani Sukumar, Data Scientist at Gramener, which explains data analysis sans complicated machine learning techniques. The video lesson will help in learning how to analyse data using a few simple (but powerful) techniques based on Exploratory Data Analysis (EDA) using data from the sport of Cricket. It is useful for those who want to do data analysis, but are not sure of where to start and what to learn from. It also discusses about basics of data types, data mutation and univariate analysis, and these techniques are domain agnostic. One can apply the same techniques on any data from any domain. It focuses on using Pandas library for data processing and plotting the results. The Jupyter notebook can be downloaded from http://bit.ly/2hCJrqY. The next video in the series will be a lesson on univariate and bivariate analysis.