Python Data Visualization Transcripts
Chapter: Visualization Concepts
Lecture: Analysis types

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0:00 I want to talk a little bit about the types of analysis that I typically do
0:05 when I'm doing data visualization. The first type when I have a new data set
0:10 is to do exploratory analysis. An exploratory analysis is characterized by the process of getting
0:17 familiar with the data where the focus is on speed and doing multiple visualization types.
0:23 I do this to find interesting nuggets and then dive deeper into the data. This is also typically something that I do as an individual.
0:31 Once I have found the information that I want to convey to someone, I'll start to do more explanatory analysis.
0:39 And what I mean by that is that this is focusing on communicating findings to an audience. The focus here is not on speed,
0:46 it's on clearly conveying the message to that audience.
0:50 I will spend time crafting the visualization and turning it into a standard report and frequently
0:56 what I find is one tool might be good for exploratory analysis but a different tool
1:02 Once I understand what I'm trying to say is a good tool for explanatory analysis
1:07 and this is a good distinction for you to keep in mind as you start to use some of the tools we are gonna talk about.

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