✰ Project: London boroughs Housing Prices:

Here’s the mystery we’re going to solve: Which boroughs of London have seen the greatest increase in housing prices, on average, over the last two decades?

A borough is just a fancy word for district. You may be familiar with the five boroughs of New York… well, there are 32 boroughs within Greater London (here's some info for the curious). Some of them are more desirable areas to live in, and the data will reflect that with a greater rise in housing prices.

✰ This project was divided into below 5 stages:

1. Sourcing and loading:
   • Importing Libraries.
   • Loading the data
2. Cleaning, transforming, and visualizing:
   • Exploring the data.
   • Cleaning the data.
   • Transforming the data.
3. Visualizing the data using matplotlib & Pandas.
4. Modeling
5. Evaluating and concluding

✰ Main tools, techniques and concepts used in this project:

1. pandas
   • data ingestion and inspection.
   • exploratory data analysis.
   • tidying and cleaning.
   • transforming DataFrames.
   • subsetting DataFrames with lists.
   • filtering DataFrames.
   • grouping data, Resampling and melting data.
   • Visualization (Manipulating DataFrames with pandas, Module Three)
   • advanced indexing (Manipulating DataFrames with pandas, Module Four)
2. matplotlib.
3. fundamental data types.
4. dictionaries.
5. handling dates and times.
6. function definition.
7. default arguments, variable length, and scope.
8. lambda functions and error handling.