This was the fifth project in Data Analyst Nanodegree from Udacity. This project has two parts that demonstrate the importance and value of data visualization techniques in the data analysis process. In the first part, Python visualization libraries were used to systematically explore a selected dataset, starting from plots of single variables and building up to plots of multiple variables. In the second part, a short presentation was produced that illustrates interesting properties, trends, and relationships that were discovered in the selected dataset. The primary method of conveying the findings was through transforming the exploratory visualizations from the first part into polished, explanatory visualizations.
Python 3.7.7 - Libraries: NumPy, pandas, Matplotlib, seaborn, and glob.
The dataset includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area in (2019). The dataset for every month in 2019 can be found here.
14/08/2020.