capitantoto/python-data-science

python-data-science

Requirements

• Python 2.7
• PostgreSQL 9.6.8

Alphavantage data analysis

• Main analysis notebook
• Open/Close prices plot
• Downloaded data

TPU performance queries

• Original, tiny sample data
• Sample data generator
• Sample generated data for 100 users to test queries
• "Setup" query to generate schema and populate with sample data
• Main query file with view to answer posed questions

With a clean installation of postgres and a ~/.pgpass file configured for a user with administrative privileges, one should be able to execute all of the queries via:

psql < setup.sql
psql < queries.sql

The answers to the specific questions can be found by "SELECT * FROM"-querying the views count_unique_device_ids, tpu_avg_purchase_amount and tpu_average_time_delta.

Encuesta Nacional de Industrias data analysis

• Main cleaning/analysis notebook

I did not have time to finish these exercise, but I did complete the cleaning tasks.

What is missing?

This is an exploratory exercise. To make this code more maintainable, I should at least:

• Add a requirements.txt/Pipfile or similar file stating dependencies (pandas, numpy, matplotlib, requests, and some base libraries),
• Export the .ipynb notebooks to pure .py Python files, and get rid of most comments,
• Add complete documentation for most functions and
• Declare unit tests on key methods, like the data download script from Alphadvantage.