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Long story short, there is no difference. How subplot works is the following: subplot (m,n,p); %//or subplot (mnp); You have three numbers that are used within subplot. subplot places multiple figures within the same window. You can place plots within a m x n grid, where m contains the number of rows and n contains the number of columns in your ...
pyplot.subplots creates a figure and a grid of subplots with a single call, while providing reasonable control over how the individual plots are created. For more advanced use cases you can use GridSpec for a more general subplot layout or Figure.add_subplot for adding subplots at arbitrary locations within the figure.
There are three main options in matplotlib to make separate plots within a figure: subplot: access the axes array and add subplots; gridspec: control the geometric properties of the underlying figure ; subplots: wraps the first two in a convenient api
matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.
matplotlib.pyplot.subplot# matplotlib.pyplot. subplot (* args, ** kwargs) [source] # Add an Axes to the current figure or retrieve an existing Axes. This is a wrapper of Figure.add_subplot which provides additional behavior when working with the implicit API (see the notes section). Call signatures:
subplot(m,n,p) divides the current figure into an m -by- n grid and creates axes in the position specified by p. MATLAB ® numbers subplot positions by row. The first subplot is the first column of the first row, the second subplot is the second column of the first row, and so on.
With subplot you can arrange plots in a regular grid. You need to specify the number of rows and columns and the number of the plot. Note that the gridspec command is a more powerful alternative.
