format(x) return s ax.t_major_formatter(number_formatter) ax.t_major_formatter(number_formatter) #set chart source and copyright plt.annotate( 'Source: UNHCR Refugee Data Finder', ( 0, 0), ( 0, - 40), xycoords = 'axes fraction', textcoords = 'offset points', va = 'top', color = '#666666', fontsize = 9) plt.annotate( '©UNHCR, The UN Refugee Agency', ( 0, 0), ( 0, - 50), xycoords = 'axes fraction', textcoords = 'offset points', va = 'top', color = '#666666', fontsize = 9) #adjust chart margin and layout fig.tight_layout() #show chart plt. import matplotlib.pyplot as plt from matplotlib import ticker def setup(ax, title): '''Set up common parameters for the Axes in the example.''' only show the bottom spine ax.tmajorlocator(ticker.NullLocator()) ax.spines 'left', 'right', 'top'.setvisible(False) define tick positions ax.tmajorlocator(ticker.MultipleLoc.
Change the axis limits with ax.setylim() and ax. It needs two arrays of the same length, one for the values of the x-axis, and one for values on the y-axis: Example Get your own Python Server A simple scatter plot: import matplotlib. The scatter () function plots one dot for each observation. Output: - You can set x-axis and y-axis labels using functions xlabel( ). With Pyplot, you can use the scatter () function to draw a scatter plot. # import libraries import matplotlib.pyplot as plt import pandas as pd () #load data set df = pd.read_csv( '') #compute data array for plotting x = df y = df label = df #plot the chart fig, ax = plt.subplots() ax.scatter(x, y, s = 30) # Loop for annotation of all points for i in range( len(x)): plt.annotate(label, (x, y), textcoords = "offset points", xytext =( 0, 5), ha = 'left') #set chart title ax.set_title( 'Comparison of refugee and IDP population by region | 2021') #set axis label ax.set_xlabel( 'Number of refugees (millions)') ax.set_ylabel( 'Number of IDPs (millions)') #format axis tick labels def number_formatter(x, pos): if x >= 1e6: s = ' '. 1.1 Formatting Options Set the title with ax.settitle() Set the axis labels with ax.setylabel() and ax. The PyPlot interface offers plot( ) function for creating a line graph.
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