set ( title = "Average Monthly Precipitation \n Boulder, CO", xlabel = "Month", ylabel = "Precipitation \n (inches)" ) plt. scatter ( months, boulder_monthly_precip, c = boulder_monthly_precip, cmap = 'YlGnBu' ) # Set plot title and axes labelsĪx. The example below uses the YlGnBu colormap, in which lower values are filled in with yellow to green shades, while higher values are filled in with increasingly darker shades of blue.ĭata Tip: To see a list of color map options, visit the matplotlib documentation on colormaps.Īx. boulder_monthly_precip), while cmap allows you to specify the color map to use for the sequence. The c argument allows you to specify the sequence of values that will be color-mapped (e.g. When using scatter plots, you can also assign each point a color based upon its data value using the c and cmap arguments. show () You can adjust the bar fill and edge colors of a bar plot using the arguments color and edgecolor. bar ( months, boulder_monthly_precip, color = 'cyan', edgecolor = 'darkblue' ) # Set plot title and axes labelsĪx. Visit the Matplotlib documentation for a list of marker types.Īx. You can change the point marker type in your line or scatter plot using the argument marker = and setting it equal to the symbol that you want to use to identify the points in the plot.įor example, "," will display the point markers as a pixel or box, and “o” will display point markers as a circle. show () You can use plt.setp(ax.get_xticklabels(), rotation 45) to rotate the tick marks along the x axis by 45 degrees. plot ( months, boulder_monthly_precip ) # Set plot title and axes labelsĪx.
subplots ( figsize = ( 10, 6 )) # Define x and y axesĪx.
The higher the value of alpha, the darker the grid lines are.Fig, ax = plt. The alpha parameter in the grid() method is used to set the grid lines’ intensity. We use which="major" to select grid corresponding to major ticks, and which="major" to select grid corresponding to minor ticks. We use minor=True to denote minor ticks in set_yticks() or set_xticks() functions. Similarly, the major grids are placed with the spacing of 5 units and represented by a lighter line. The minor grids are located with a spacing of 1 unit and represented with a darker line. Subplot 1 has both minor and major grids.
It displays a Matplotlib figure with two subplots in it. import numpy as npĪxes.set_xticks(minor_ticks_top,minor=True)Īxes.set_yticks(minor_ticks_top,minor=True) From the figure, it is clear that grids’ spacing is maintained as per ticks are spaced. We have set the different spacing of ticks for both subplots. Change Matplotlib Plot Grid Spacing by Changing the Spacing of the Ticks import matplotlib.pyplot as pltįig,axes=plt.subplots(nrows=2,ncols=1,figsize=(8,6))
We can change the grid interval by changing the spacing of ticks. It displays a plot with grids in which grids are spaced as per the spacing of the ticks. We must use the () function to show the grids. This tutorial will introduce how we can set grid spacing and apply different styles to major and minor grids in the Matplotlib plot.
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