This chapter deals with data visualization library titled Matplotlib and online plot maker named Chart Studio. Matplotlib Matplotlib is a popular Python data visualization library capable of producing production-ready but…
Pandas is a very popular library in Python for data analysis. It also has its own plot function support. However, Pandas plots don't provide interactivity in visualization. Thankfully, plotly's interactive…
Plotly 3.0.0 introduces a new Jupyter widget class: plotly.graph_objs.FigureWidget. It has the same call signature as our existing Figure, and it is made specifically for Jupyter Notebook and JupyterLab environments. The go.FigureWiget() function returns an empty…
Plotly has a convenient Slider that can be used to change the view of data/style of a plot by sliding a knob on the control which is placed at the bottom of rendered plot.…
Plotly provides high degree of interactivity by use of different controls on the plotting area – such as buttons, dropdowns and sliders etc. These controls are incorporated with updatemenu attribute of the…
This chapter will give information about the three-dimensional (3D) Scatter Plot and 3D Surface Plot and how to make them with the help of Plotly. 3D Scatter Plot A three-dimensional…
This chapter focusses on other three types of charts including OHLC, Waterfall and Funnel Chart which can be made with the help of Plotly. OHLC Chart An open-high-low-close chart (also OHLC) is…
In this chapter, we will learn how Polar Chart and Radar Chart can be made with the help Plotly. First of all, let us study about polar chart. Polar Chart…
A heat map (or heatmap) is a graphical representation of data where the individual values contained in a matrix are represented as colors. The primary purpose of Heat Maps is…
In this chapter, we will understand about distplots, density plot and error bar plot in detail. Let us begin by learning about distplots. Distplots The distplot figure factory displays a…