Data Analysis - An Analogy

Let's understand Data Analysis with an example

Imagine you own an apple farm and you want to know the number of apples you grow but you are too busy with the farm so you hire someone to count them. You sell your apples too, and you get your apple counter to keep a record of the number of apples you have in the beginning and at the end of the day, every day.

Many days and months pass and you put sheet after sheet of the apple count together and you discover patterns and trends in the purchasing behaviour of your customers.

The trends and patterns help you realise that during the colder season, your output of apples are the same but people buy less than during the summer.

You then set out to dig deeper into this trend and find ways to keep the sales of apples consistent throughout the year, beating your competitors at the game and becoming an apple farm tycoon.

Apples are your data, tracking them is important, analysis is key

For starters, you will know if your supply of apples matches the market’s demand, as well as the consistency of the ratio of demand to supply throughout the year. Pegging the price to each apple and drawing the cost down gives you your profit.

When you have enough data, you will find trends and patterns in your production. These trends can help you understand your own organisation better, help you reduce inefficiency and therefore reduce costs.

What is Data Analysis?

As an apple farmer, you collected the count of apple at the beginning of the day and at the end of the day in an organized fashion in the sheets. In the end, you got some insightful information (i.e. trends and patterns in the sale of apples) from that data. This is called Data Analysis.

So collecting all the words above, Data Analysis is a method of collecting and organizing the data and if required manipulating the data so that one can derive some useful information from the data.

Data Analysis and Pandas

Pandas is a tool in Python that helps you collect (or read) the data from a file, organize it in a tabular format, manipulate and clean the data if required to derive the insightful information from the data.