BW #70: Moon missions

BW #70: Moon missions

Just a few days ago, China's Chang'e 6 ( successfully landed on the far side of the moon. That's already impressive, but then it went further, extracting soil samples and launching them back into lunar orbit, where a spacecraft was waiting. If all goes well, then the lunar soil will return to Earth later this month.

I don't know about you, but I'm pretty impressed by every part of that: Getting to the moon is hard. Landing on the far side is even harder. Having a robot extract soil, then getting it back into orbit, and then getting that orbiting facility back to Earth? That's pretty amazing.

Moreover, it's coming from China, which has been doing more and more space missions. And of course, other countries are planning all sorts of moon missions in the coming years, including (they say) a crewed NASA moon mission no earlier than September 2025.

That got me thinking about moon missions, and how often we have launched them, and what countries/agencies have actually managed to get there. And thus, this week’s problems have to do with moon missions in the 21st century.

Data and six questions

This week, we're going to look at data about all of the moon missions in the 21st century. We'll take our information from Wikipedia, which conveniently has a page dedicated to such things:

This week's learning goals include scraping HTML, cleaning data, working with indexes and multi-indexes, and working with dates and times.

I’ll be back tomorrow with my complete answers, including a downloadable version of my Jupyter notebook.

Here are this week's six tasks and questions:

  1. From the Wikipedia page (, turn the table of 21st-century missions into a data frame. In the HTML table, the final row for each mission describes that mission; remove all of those descriptive rows. Set the index to be the mission + spacecraft.
  2. Turn the "Launch date" column into a datetime column.