Learn-Python-with-Google-Colab-Step-to-M

WI-FI HOTSPOT DATASET.

DEEP DIVE: INTRO TO PYTHON

Analysis of Wi-Fi hotspots locations dataset in Mexico City and New York City.

On Python deep dive I learned the basic concepts to extract data from a dataset and use the tools and libraries from python to analyze information from New York City and Mexico City. The analysis program was coded on Colab.

Adding dataset on Colab

Data information from dataset.

Hotspots comparison between cities.

Number of boroughs for each city.

Mexico City boroughs.

Mexico City boroughs graph.

New York City boroughs.

New York City boroughs graph.

Network status from hotspots in New York City.

Network status from hotspots in Mexico City.

Network status from hotspots in New York City.

Network status from hotspots in Mexico City.

Network status from hotspots in New York City.

This analysis project allows extracting data that could be used on Big Data systems. The purpose of performing this basic code is to find new strategies that help to use data for expert systems or machine learning projects. This dataset could be an addition to the Wi-Fi accessibility project for future updates. The challenge is to design a map chart to locate free hotspots locations in both cities.