Visualizing data is an important step since it helps understand what is going on in the data without actually looking at the complicated working underneath it and performing complicated computations.
Pygal is an open source Python package that helps in the creation of interactive plots, and SVG (Scalar Vector Graphics) images of graphs. SVG refers to dynamically generating animated graphs with the given data. These SVG images of graphs can be used and customized depending on our requirements. The SVG images are highly scalable, hence they can be downloaded in high quality format. These downloaded images can also be embedded to various projects, websites and so on.
These interactive and customized graphs can be created with ease in Pygal. Pygal helps create bar chart, histogram, line plot, and much more.
A gauge chart is a combination of a pie chart and a dough nut chart. It helps in visualizing data at a specific value.
Pygal package can be installed using the below command on Windows −
pip install Pygal
Let us understand how Gauge charts be created using Pygal −
Import pygal from pygal.style import Style custom_style = Style(colors=('#E80080', '#404040', '#9BC850', '#E81190')) gauge_chart = pygal.Gauge(height=400,width = 300,style=custom_style, human_readable=True) gauge_chart.title = "Gauge plot" gauge_chart.add("label 1", [0.4]) gauge_chart.add("label 2", [1.2]) gauge_chart.add("label 3", [1.5]) gauge_chart.add("label 3", [1.8]) gauge_chart.render_in_browser()
The required packages are imported into the environment.
The pygal. Gauge function is called with a few parameters.
This is assigned to a variable that is used to add characteristics.
The colors for the Gauge plots are defined.
The height and width of the graph is also defined.
The title and values for the Gauge plots are defined.
The ‘render_in_browser’ function is called to plot the generated Gauge plot in the browser.