In this post, the author will give a high level overview of what exploratory data analysis (EDA) typically entails and then describe three of the major ways EDA is critical to successfully model and interpret its results.
This is crucial and it's important that it is done properly.
Showing posts with label EXPLORATION. Show all posts
Showing posts with label EXPLORATION. Show all posts
Monday, 1 May 2017
Wednesday, 28 September 2016
18 Free Exploratory Data Analysis Tools For People who don’t code so well by Manish Saraswat via @AnalyticsVidhya
Some of these tools are even better than programming (R, Python, SAS) tools.
Why write code if you don't have to/or don't have the ability?
Why write code if you don't have to/or don't have the ability?
Thursday, 3 September 2015
Ultimate guide for Data Exploration in Python using NumPy, Matplotlib and Pandas via @AnalyticsVidhya
Exploring data sets and developing deep understanding about the data is one of the most important skill every data scientist should possess. People estimate that time spent on these activities can go as high as 80% of the project time in some cases.
Great guide from the folks at Analytics Vidhya. Well worth a bookmark.
Great guide from the folks at Analytics Vidhya. Well worth a bookmark.
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