The above code means that we are setting the color of the scatter plot as red.
To set the colors of a scatter plot, we need to set the argument color or simply c to the pyplot.scatter() function.įor example, take a look at the code below: plt.scatter(x, y, color = 'red') E.g.: import matplotlib.pyplot ( 1,2,3, 4,5,6,color 'red','green','blue') When you have a list of lists and you want them colored per list. for highest values of y the tick color is dark green, for lowest value is dark red, and for intermediate values the color will be scaled in between green and red. t and color the ticks based on the value of y. Setting colors to the multiple scatter plot The normal way to plot plots with points in different colors in matplotlib is to pass a list of colors as a parameter. I have 2 variables (x,y) that change with time (t). By default, pyplot returned orange and blue.
Note: Notice that the two plots in the figure above gave two different colors. Line 16: The pyplot.show() function is used, which tells pyplot to display both the scatter plots. pyplot.scatter(x,y2) is used to create a scatter plot of x and y2. Lines 12 to 13: The array y2 is created, which contains the y-coordinates for the second scatter plot. pyplot.scatter(x,y1) is used to create a scatter plot of x and y1. Lines 8 to 9: The array y1 is created, which contains the y-coordinates for the first scatter plot. Line 5: The array x is created, containing the x-coordinates common to both plots. import pandas as pd import numpy as np np.ed (42) import matplotlib.pyplot as plt import seaborn as sns letters list (map (chr, range (ord ('A'), ord ('Z')+1))) df pd.DataFrame. Line 2: The numpy module is imported, which will be used to create arrays. You can replace one color in the palette by converting it to a list of colors and then replace one of the colors by some other color of your liking. Line 1: In matplotlib, the pyplot module is imported, which will be used to create plots.
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