This portfolio is a compilation few of my data analysis and visualization works that I made independently.
I worked with BIXI data to develop some models (e.g. hourly bike demand forecast for each station) for optimizing BIXI system. In order to perform EDA (Exploratory Data Analysis) and to prepare Machine Learning Models to solve different business problems of BIXI Montreal, I have created a Dataset combining BIXI Open Dataset from year 2014 to 2018 and Montreal historical hourly weather dataset from year 2014 to 2018. In this exercise 105 files, 35 features and 993MB data were merged together and processed a dataset with 20 features and 1008MB of size. I used Google colab, python and pandas for this data wrangling.
In the line diagram we see that BIXI bike sharing systems is becoming popular means of travel in Montreal for last five years. We also see that June to August are the most popular months, Tuesday to Thursday are most popular weekdays and 8:00 am and 5:00 pm are the pick hours for BIXI bikers.
The company sells bicycles and accessories, such as clothing and other accessories to bikers in six countries. I have analysed 6 years data (more than one hundred thousand rows) in Excel using excel table, pivot table, pivot charts, slicer etc.
Sales Dashboard:
