generated from mwc/lab_scatter
3fb69f5e3b
First I defined the x and y axis and worked through the commands to draw them. Then I changed the definitions so the program would draw the points. This felt like the most complex code that we have written by a long shot. There were a lot of challenges along the way, however when it came together it was really satisfying. Overall, I felt like I understood the directions and I understood why the answer was correct, but trying to configure the pieces to complete the code was difficult. This could be from a number of factors, and is certainly not aided by the fact that I have not had to do formal math of any kind for almost a decade. But like I said, when it clicked, it clicked. The top down thinking is something I am getting used to in terms of code. It reminds me a lot of scaffolding in teaching. A task by itself can be daunting, but when it is broken down into parts it becomes manageable. That being said, there are still places where I am struggling, but again, I am reminded of my students. So many of them struggle all year to understand English concepts and I challenge them to embrace the discomfort and have faith that the will be successful. Call it imposter syndome or learning curve, but I am enjoying the challenge and trying to stick with it. I was thinking about other data sets that require bounds and plotting. I think this would be an amazing way to analyze and plot large amounts of data, like stuudent data maybe? I want to know more about what the inputting of data side of the program as well. |
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| .commit_template | ||
| .gitignore | ||
| constants.py | ||
| generate_data.py | ||
| planning_scatter.md | ||
| plotting.py | ||
| poetry.lock | ||
| pyproject.toml | ||
| scatterplot.py | ||
| test_transform.py | ||
| ticks.py | ||
| transform.py | ||