The rental data visualization system based on Python+Django+MySQL uses Echart to build charts, supports custom color themes, and modifies data by connecting to the database.
The running display is as follows, the browser has been zoomed, so the layout will look a bit strange. You can add some functions according to your needs, such as registration page, data modification page and so on. The data acquisition module (spider) will be added later.
New pages are still very easy to add, each page is a separate html, you only need to add a new page name in the navigation bar to realize the addition of a new page.
The modification of the database can be carried out through Navicat, the database operation software. The source code provides the prepared sql file of the rental information database. You only need to import Navicat to realize visual analysis. It is very convenient and easy to use. You can provide Navicat usage guidance for free.
Technology Exchange
Technology must learn to share and communicate, and it is not recommended to work behind closed doors. A person can go fast, a group of people can go farther.
The source code, information, data, and technical exchange improvements in the article can be obtained by adding the knowledge planet exchange group. The group has more than 2,000 members. When adding, remember to add the following remarks: source + interest direction, which is convenient for finding like-minded friends.
Method ①, add WeChat account: pythoner666, remarks: from CSDN + renting data visualization system
Method ②, WeChat search official account: Python learning and data mining, background reply: information
Page - Home
House type floor and other data
Data analysis of different districts
price comparison
The relationship between price and area
Comparison of rental ratio
List price comparison
Price Comparison by Administrative District
Comparison of housing facilities
The code for the database part
file structure
