cs401r_w2016:lab1
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cs401r_w2016:lab1 [2016/01/03 00:04] admin |
cs401r_w2016:lab1 [2016/02/08 18:53] admin |
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| Done correctly, this should only take a few lines of code. | Done correctly, this should only take a few lines of code. | ||
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| + | ---- | ||
| + | ====Grading standards:==== | ||
| + | |||
| + | Your notebook will be graded on the following: | ||
| + | |||
| + | * 20% Successfully turned in a notebook with working code | ||
| + | * 20% Random image with 50 random elements | ||
| + | * 20% Correctly used pandas to load store sales data | ||
| + | * 30% Some sort of plot of sales data (only for store #1!) | ||
| + | * 10% Tidy and legible figures, including labeled axes where appropriate | ||
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| should see "Notebook" and "Python 2". This will create a new | should see "Notebook" and "Python 2". This will create a new | ||
| notebook. | notebook. | ||
| + | |||
| + | **Note:** When you turn in your notebook, you should turn in the ''.ipynb'' file. Do not take a screen shot, or turn in an HTML page. | ||
| Here's some starter code to help you generate an image. The ''nbimage'' function will display the image inline in the notebook: | Here's some starter code to help you generate an image. The ''nbimage'' function will display the image inline in the notebook: | ||
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| For this lab, you need select the data for store #1 and plot it. | For this lab, you need select the data for store #1 and plot it. | ||
| - | If you want to get fancy, you should label the x-axis using dates (See the example image). This involves a bit of python trickery, but check out some helpful functions in the hints below. | + | An important part of generating visualizations is conveying information cleanly and accurately. You should therefore label all axes, and in particular, the x-axis should be labeled using dates (See the example image). This involves a bit of python trickery, but check out some helpful functions in the hints below. |
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cs401r_w2016/lab1.txt ยท Last modified: 2021/06/30 23:42 (external edit)
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