![]() Recall that matplotlib’s object oriented approach makes it easy to include more than one plot in a figure by creating additional axis objects:įig, (ax1, ax2) = plt.subplots(num_rows, num_columns) show () You can adjust the colors of the points in a scatter plot using color maps (cmap argument), which allows you to specify a range of colors that will be applied to the data points depending on their value. 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 chart now resembles a scatter plot with each point in the plot connected by a line.įeel free to play around with the Format options in the Chart editor panel to modify the color and size of the points and lines in the chart.Fig, ax = plt. Points will automatically be added to the line chart: Then click the dropdown arrow next to Series, then choose 10px as the Point size: ![]() To add points to the line chart, click the Customize tab in the Chart editor panel. This will automatically produce the following line chart: To convert this into a line chart, simply click Chart type in the Chart editor that appears on the right of the screen. The following scatter plot will be inserted by default: Next, highlight the values in the range A1:11, then click Insert, then click Chart: This tutorial provides a step-by-step example of how to create the following scatter plot with lines in Google Sheets:įirst, let’s create a dataset that contains the following values: Unfortunately Google Sheets doesn’t offer this type of built-in chart, but you can create it using a line chart as a workaround. Often you may want to create a scatter plot in Google Sheets with each of the points in the plot connected by lines.
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