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Visualization in Python with matplotlib

Group by Continuous Variable

Task

This time, we are goint to paint the points for the same scatter plot in respect to the 'hdi' column values.

  1. Initialize a scatter plot with the next parameters:
    • Set points color (c) to the 'hdi' column values of the data;
    • Set colormap (cmap) to 'plasma'.

    Save the call of the .scatter() function to the cax variable.

  2. Apply .colorbar() function to Figure object assigning cax as an argument.

Everything was clear?

Section 3. Chapter 10
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course content

Course Content

Visualization in Python with matplotlib

Visualization in Python with matplotlib

1. Basics: Line Charts

Creating an Empty PlotSimple Line ChartCreate a Simple Line ChartAdding One More LineAdd Data to the PlotAdding Legend to a PlotAdd LegendPlot Labels and TitleAdd Lables and TitlesChanging Line StyleCustomize Your Line ChartCreate a Complete Line Chart

2. Bar Charts

Simple Bar ChartCreate a Simple Bar ChartStacked BarsCreate a Stacked Bar ChartGrouped BarsCreate a Grouped Bar ChartHorizontal Bar ChartCreate a Horizontal Bar ChartCustomizing Bar ChartsCreate a Complete Bar Chart

3. Scatter Plots

The Simplest Scatter PlotCreate a Simple Scatter PlotSetting Plot ParametersSet Ticks and LimitsCustomizationCustomize Your Scatter PlotGrouping ObservationsGroup by RegionFurther GroupingGroup by Continuous VariableMaking Chart InformativeAdd Information to the Plot

Group by Continuous Variable

Task

This time, we are goint to paint the points for the same scatter plot in respect to the 'hdi' column values.

  1. Initialize a scatter plot with the next parameters:
    • Set points color (c) to the 'hdi' column values of the data;
    • Set colormap (cmap) to 'plasma'.

    Save the call of the .scatter() function to the cax variable.

  2. Apply .colorbar() function to Figure object assigning cax as an argument.

Everything was clear?

Section 3. Chapter 10
toggle bottom row
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