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3 cze 2013 · y = np.array([[17, 19, 5, 16, 22, 20, 9, 31, 39, 8], [46, 18, 37, 27, 29, 6, 5, 23, 22, 5], [15, 46, 33, 36, 11, 13, 39, 17, 49, 17]]) To make sure the column totals are 100, you have to divide the y array by its column sums, and then multiply by 100.
Download Python source code: stackplot.py. Download zipped: stackplot.zip. Gallery generated by Sphinx-Gallery.
Using this approach, we can create our updated stackplot: fig , ax = plt . subplots () population = np . array ( population ) ax . stackplot ( year , population [ order ], labels = region [ order ]) ax . set_xlabel ( "Year" ) ax . set_ylabel ( "Population (billions)" ) ax . legend ( loc = "upper left" , reverse = True )
Download Python source code: stackplot_demo.py. Download zipped: stackplot_demo.zip. Gallery generated by Sphinx-Gallery.
Draw a stacked area plot or a streamgraph. Parameters: x(N,) array-like. y(M, N) array-like. The data is assumed to be unstacked. Each of the following calls is legal: stackplot(x, y) # where y has shape (M, N) stackplot(x, y1, y2, y3) # where y1, y2, y3, y4 have length N. Copy to clipboard.
matplotlib: plotting with Python. Contribute to matplotlib/matplotlib development by creating an account on GitHub.
To create a StackPlot, we use the stackplot function from pyplot. Instead of passing an X and Y, we pass an X (in our case days), then we pass multiple arrays that represent our categories. Each item in the category is the amount of Y (in our case budget spent on ads). import matplotlib.pyplot as plt. days = [1, 2, 3, 4, 5] .
