Analyzing trend gives you a direction when making decisions. For instance, investigate the housing market before purchasing properties may tell you what is the most suitable place for you.
Data speak the words of truth, as long as they are treated with specific patterns. But in general, a larger dataset ensures the quality of analysis.
Fortunately, the nowadays low cost to data access makes it possible for everyone to be a data scientist. With the help of Python, database, and plotting packages, you are allowed to explore a space the once only belongs to statisticians.
In this post, we are going to have a look at:
- How to obtain your data;
- How to store them;
- How to visualize them.
Python is a good tool to obtain data from the Internet.
# -*- coding: UTF-8 -*-
The program grabs information presented on a website and store all complete record into SQLite database.
In this case, we list three plots in order to:
- Price distribution
- The correlation of unit price, community area, and green coverage rate.
# -*- coding:utf-8 -*-