This post is a revised version of presentation for Hack Santa Monica Meetup on November 17th, 2016. To learn more about Hack Santa Monica Meetup, please look here.
Hack Santa Monica Meetup was initiated by non-profit group SixThirty Group (formerly known as Team SixThirty). For more information of SixThirty Group, please check here.
Often in Business Intelligence field, people would say the first thing to do is to visualize data. However, one might be confused, among various visualization methods, what are the one visualization method that will reveal insights? And more exactly, what are called insights?
Insights, as it literally suggests, are things that are embedded in data and waiting for you to discover. That is somewhat a romantic way to put it, and the process of discovering one takes lots of patience and cautious. Different people might be looking at different things. Accountants may look at ledgers and balance sheets, whereas economists may look at annual labor data or stock market data.
Here I use data from Santa Monica Open Data Portal, which is a data set describing Santa Monica’s fire report records.
- Look for pattern
- Look for anomaly
- Knowing the context
Since I moved to Code-mania (CA) to start my graduate education, I was shocked and also amazed by how many people can code and program in CA. For a person who came from a business background and is not tech savvy, this transfer can be hard at the starting point. Though I have experienced some formal education from university, most of the basic programming skills were self-taught through online tutorials. So here I want to introduce some useful concepts and resource for those beginners.
I have learnt Python mainly by myself through online tutorials. Sometimes learning from online tutorials always give you the same stuff: data type, indexing, and using libraries. Most of the time when you need to write your own functions or methods, understanding some useful libraries will get you some help but you still need to understand the big picture. Per my experience, I think programming language, in general, have 3 major components you need to understand: Value assignment, Logic, and Loops(or sometime called iterations).
“Over half of the time, analysts are trying to import/cleaning the data.”
— By numerous John/Jane Does of data analysts
Data these days can be flown in from various sources: web, database, local files, user input, etc. Analysts now often have to work with various format of data input, in order to make them compatible with each other for analysis. Though sometimes considered to be a data engineer’s work, data preparation is still an essential skills for all data analysts, especially those who work in small to medium size firms (as I am doing now).
I am going to introduce data reading/manipulation with pandas library in Python 3. I have recently worked extensively with pandas in Python 3 and started realized the powerful component in the library. In this post, I will the one I used most frequently, groupby() with pandas.