WQU-housing in mexico
Date: 2022-03-08 Time: 18:23
About the Project
In this project, you’ll work with a dataset with 21,000 properties for sale in Mexico through the real estate website Properati.com. Your goal is to determine whether sale prices are influenced more by property size or location.
Some of the things you’ll learn in this project are:
- How to organize information using basic Python data structures.
- How to import data from CSV files and clean it using the pandas library.
- How to create data visualizations like scatter and box plots.
- How to examine the relationship between two variables using correlation.
011 Tabular and Tidy Data
Common way to organize an information is in a table, which is a group of cells organized into rows and columns:
| house | price | rooms | areas |
|---|---|---|---|
| 0 | 115910 | 4 | 128 |
| 1 | 48718 | 3 | 210 |
| 2 | 28977 | 2 | 58 |
| 3 | 36932 | 3 | 799 |
| 4 | 83903 | 3 | 111 |
Terminologies
- Columns = Features - Column Wise Calculations
- Rows = Observations - Row Wise Calculations
- Cells = Values
Data Structure
Transclude of Data-Structures#list
New Learning, you can mutate and update an existing 2d list by using a for loop and directly appending it in each elements
[i.append(i[0]/i[1]) for i in houses_nested_list]Circular transclusion detected: Data-Structures
Dictionaries is also used for creating JSON format
Time ended: 7:28 PM
References: My Path Course | WQET (wqu.edu)