![]() Program for creating a scatter plot having multiple markers using Then we have used the show function to display the generated scatter plot. In this example, the data points are unordered hence this example describes the scatter plot properly. ![]() This scatter plot is used when the data points are scattered unordered. Finally, the scatter() function creates a scatter plot by combining x and y-coordinates. Then we have passed these two coordinates into the scatter function. Then, we imported a numpy for creating x-coordinates and y-coordinates. The matplotlib library consists of all the functions for plotting different types of graphs and charts. In this program, we imported matplotlib.pyplot for plotting the scatter plot. # Displaying the created graph using the show method Program for creating a scatter plot using The () function creates a scatter plot and displays it in the output. The matplotlib scatter() function plots a scatter plot as output. If True, the infinite points are plotted in the graph. This argument takes floating-point numbers or arrays as values.Įdgecolors : The edge colors of the marker are passed in this argument. Linewidths : The linewidth of the marker edges are passed in this argument. 0 is used for transparent, and 1 is used for opaque. This vmin and vmax are used along with the default norm to map the color array c to the color map array cmap.Īlpha : This is an optional argument. Vmin, vmax : This argument can only be used when the norm parameter is not used. The floating-point range is normalized between 0 to 1. This function is used to normalize the data in the c parameter. Norm : This parameter is used only when the c parameter is passed with the floating-point number. By using this parameter, the floating value is converted to the respective color. However, the marker style can be modified by passing the marker style in this parameter.Ĭmap : This parameter is used only when the c parameter is passed with the floating-point values. By default, the marker style is kept as ‘o’. Which results in plotting the scatter plot of 3 different groups with 3 different colors with ‘*’ being used as plot.Marker : This parameter specifies the style of the marker used in the scatter plot. All the above three arguments along with the marker=’*’ is passed to Scatter function.Corlor_array with first 15 blue color, second 15 green color and last 15 red color is created.height1, height2 and height3 is concatenated to form a height array.weight1, weight2 and weight3 is concatenated to form a weight array.Plt.title('grouped scatter plot - height vs weight',fontsize=20) Plt.scatter(weight, height, marker='*', c=color_array) Weight=np.concatenate((weight1,weight2,weight3)) MarkerĮxample of scatter plot for three different groups import matplotlib.pyplot as plt Line 9 and Line 10: Mentions the Chart Title with font size and scatter plot is shown.ĭifferent values for markers and their representation is shown below. Line 7 and Line 8: x label and y label with desired font size is created. Line 6: scatter function which takes takes x axis (weight1) as first argument, y axis (height1) as second argument, colour is chosen as blue in third argument and marker=’o’ denotes the type of plot, Which is dot in our case. Line 3 and Line 4: Inputs the arrays to the variables named weight1 and height1. Line 1: Imports the pyplot function of matplotlib library in the name of plt. Plt.title('scatter plot - height vs weight',fontsize=20) Plt.scatter(weight1,height1,c='b',marker='o') This example we will create scatter plot for weight vs height import matplotlib.pyplot as plt This python Scatter plot tutorial also includes the steps to create scatter plot by groups in which scatter plot is created for different groups. In this Tutorial we will learn how to create Scatter plot in python with matplotlib.
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