We get a nice colored bubble plot made with matplotlib. Plt.title("Bubble Plot with Colors: Matplotlib", size=18) Here, Colors is the quantitative variable that we created when we constructed the dataframe. And we use the argument c=”Colors” to color the bubble by a variable. A third variable can be set to correspond to. Each row in the data table is represented by a marker the position depends on its values in the columns set on the X and Y axes. ![]() The scatter() function has the argument “c” for specifying colors. Scatter plots are used to plot data points on horizontal and vertical axis in the attempt to show how much one variable is affected by another. Let us color the bubbles differently using another variable in the bubble plot. Simple Bubble Plot in Python with Matplotlib Color Bubble Plot By Variable in Python We have also added transparency to the bubbles in the bubble plot using alpha=0.5. By default, Matplotlib makes the bubble color as blue. We can see that the points in the scatter plots are bubbles now based on the value of size variable. Plt.title("Bubble Plot with Matplotlib", size=18) To make bubble plot, we need to specify size argument “s” for size of the data points. Using Matplotlib, we can make bubble plot in Python using the scatter() function. Our customized scatter plot looks like this. Plt.title("Scatter Plot with Matplotlib", size=18) We also add a title to the scatter plot using plt.title(). Here we customize the axis labels and their size using xlabel and ylabel functions. The x and y-axis label sizes are smaller by default, when we make scatter plot using scatter function(). Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted. ![]() Notes The plot function will be faster for scatterplots where markers don't vary in size or color. plt.figure (figsize (20,20)) Instead of adjusting the size of the existing plot, its creating a new figure with a size of 20x20. ![]() Depending on the type (numerical or categorical) and the number of input variables (two, three, or more), we can use a suitable plot and project it in 3D space. To plot scatter plots when markers are identical in size and color. 1 Answer Sorted by: 21 This line isnt doing what you think it is. These can be anything from simple histograms to more complex 3D plots. Let us first make a simple scatter plot with Matplotlib using scatter() function. We can plot interactive plots using the 3D projection option provided by matplotlib. Here we construct dataframe from NumPy arrays using Pandas’ DataFrame function and providing the variables as a dictionary. Let us store the simulated data in a Pandas dataframe.
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