Next, we define the x, y1, and y2 data coordinates using array() function of numpy. First, import the libraries such as matplotlib.pyplot and numpy for data visualization and data creation. The following is the syntax: (x, y, color=None) Here we’ll learn to set the color of the array manually, bypassing color as an argument. If we call a scatter() function multiple times, to draw a scatter plot, we’ll get each scatters of different colors. Display: Use the show() function to visualize the graph on the user’s screen.Īlso, check: Matplotlib 3D scatter Python scatter plot color array. Set the color: Use the following parameters with the scatter() function to set the color of the scatter c, color, edgecolor, markercolor, cmap, and alpha. Plot a scatter graph: By using the scatter() function we can plot a scatter graph. Define Coordinates: Define x-axis and y-axis data coordinates, which are used for data plotting. For visualization: pyplot from matplotlib and For data creation: NumPy. Define Libraries: Import the important libraries which are required for the creation of the scatter plot. The following steps are used to set the color to scatter plot: #MAKE SCATTER PLOT MATPLOTLIB HOW TO#
And here we’ll learn how to color scatter plot depending upon different conditions. Matplotlib scatter plot color by category legend Matplotlib scatter plot colorįor data visualization, matplotlib provides a pyplot module, under this module we have a scatter() function to plot a scatter graph.
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