I'm working on a personal project to analyze real estate data from three different sites. I want to do some statistical analysis (Python, numpy, pandas, scikit) an data visualization on the data to identify trends, outliers, variations on the market, opportunities, identify clusters, etc.
Part of the information to store:
- Price (stored daily)
- ID
- Property age
- Location (initially and string but eventually geo coordinates)
- Amenities
- Publication date
- Square foots
- Parking spaces
The total number of properties is 250.000,00. Initially I'll download the information daily to understand the characteristics of the data. After this, I will change the refresh rate of the data, probably twice a week.
I'm thinking about using a relational (PostgreSQL) database for non time dependent data and a timeseries (influxdb or graphite) database for prices.
What do you think? I'm choosing the right stack?