In this covid season, thought of sharing some tips and sample codes on Data Wrangling. After getting a glance of Google Colab, my go to language for data wrangling has been Python. This blog hence uses Colab and Pandas on Python for data wrangling. Most of the data collected has format related issues because they are collected without the use of a software. These days, with tools like Google Forms coming into picture, it is much better, but when you have old data to deal with in its row form, there is no escape from formatting it and getting it to the shape that you need it to be in. This blog shows how to use colab, pandas and lambda functions to quickly format some data. I had written an earlier blog few days back on Colab and how to import data from excel to Colab. So, I shall skip that part now. Let us say, the below is the data that we need to format (the admission number column) and we need all the data to be in the format: YYYY-Num We can do this quickly using dataframes and l
By [https://EzineArticles.com/expert/Rob_Ian_Chapman/575203]Rob Ian Chapman So you have played around with your data, made some key discoveries that are going to revolutionize your company and now need to persuade others to join your enlightened brigade. The key is turning your analysis into an effective and persuasive presentation. Here are some tips for showing your data visualizations to the world: Planing Decide whether you are going to start with a conclusion and then explain (deductive approach) or build the story through to the conclusion (inductive approach). Think about your visualizations only once you know you want to present them Write out the point of each visualization slide before designing it For each conclusion from your analysis, try several different visualizations before deciding on the best one to display your data If your conclusion is particularly contentious draw it from multiple visualizations building the story as you go, rather than attempti