Google Data Analytics

I have been taking a few Coursera courses (coursera.org), and one of my favorites is Google’s Data Analytics Professional Certificate program. The program is well-organized in a way that you learn skills to work as an entry-level data analyst. Especially the course is suitable for people who already know data analysis because this course gives you a better idea about what it means to use data analytics in a business context.

So the Google Data Analytics course sets the last (8th) course as a capstone. I chose the first option (there are 3 options; 2 with datasets, and the ‘you can do whatever you want to do’ option). The thing is, I have aced this program so far, but suddenly, the course gives you the intro then basically it tells me to ‘finish the analysis in about a week.’

Okay. So according to the instruction, I downloaded the datasets(zip file) and tried to upload them onto Google Sheets. ….The screen error message tells me the file is too large. I tried to open them in Excel (csv files; data for 12 months); I can only open the data month by month, cannot combine them into one spreadsheet (too many rows). I don’t remember this situation during the program. From what I learned, I decided to use BigQuerry SQL–it allows me to calculate and manipulate data quickly. Again, I get some error messages, and I need to put the datasets in a ‘bucket’ or cloud space before I can create tables. Okay, I never encountered this either, but I managed to create 12 tables with SQL and analyzed the basics. So how do I want to show the results? We learned Tableau so try Tableau. Then I realize that how I arrange data on a spreadsheet is an important part of data visualization. Even with Excel.

Anyway, so the first chart I show is made with Excel.

The question I’m trying to answer is, what is the major difference between casual riders and member riders? (for bike rental service). Here’s the average ride length for each group; as clearly we can see, casual(not member) riders ride longer, on average, throughout the year. February kink is, I believe, some data entry errors (probably coming from January), but systematically, the casual riders ride longer. Seasonality is not that clear, but it looks like people do not ride long if the weather is too warm/cold, and probably enjoy riding in spring and fall. But as you can see from the ‘member’ line, there’s almost no seasonality, showing that their purpose of riding a bike is not influenced by the weather/season.

Okay, this is the first chart and first entry. I’ll see if I can upload other stuff here too! Thank you for reading, if you are reading.