There is a a rich dataset on the history of space missions from Next Space Flight that’s just waiting to be analyzed and visualized. What organizations launch missions? When? How much does it cost?

Laid forth by 100 Days of Code Bootcamp on Udemy, I answered 4 essential questions:

• Who launched the most missions in any given year?
• How has the cost of a space mission varied over time?
• Which months are the most popular for launches?
• Have space missions gotten safer or has the chance of failure remained unchanged?

Find answers to these questions and learn how I did so by accessing the project here.

Lessons Learned:

• What programming language did you use? Excel
• Why did you do this project? I wanted to challenge myself by using a Microsoft Office Suite tool as I complete Udemy’s 100 Days of Code Bootcamp.
• What do you think you did well? Excel offers many of the same tools its peers do, though execution can be frustrating for those accustomed to coding. Nonetheless, I navigated this challenge by making worksheets to answer each question.
• What’s the most important lesson you learned? Excel is often as good as programming, and data analysts need to use it as often, if not more so. You do not always need to import a CSV into Python, R, or Tableau to draw insights from data.
• If you did this project again, what would you do differently? When using Excel, use as many sheets necessary to answer questions and track progress, especially because Git is not an option. I am so used to Python’s (Jupyter) Notebooks, so I did a poor job of writing code that I had to go back and rewrite everything. Do not waste time on such antics.