When we have big data that contains many variables, the plot types in Chapter 4, Visualizing Online Data may no longer be an effective way of data visualization. We may try to cramp as many variables in a single plot as possible, but the overcrowded or cluttered details would quickly reach the boundary of a human's visual perception capabilities.
In this chapter, we aim to introduce multivariate data visualization techniques; they enable us to better understand the distribution of data and the relationships between variables. Here is the outline of this chapter:
- Getting End-of-Day (EOD) stock data from Quandl
- Two-dimensional faceted plots:
- Factor plot in Seaborn
- Faceted grid in Seaborn
- Pair plot in Seaborn
- Other two-dimensional multivariate plots:
- Heatmap in Seaborn
- Candlestick plot in matplotlib.finance:
- Visualizing various stock market indicators
- Building a comprehensive stock chart
- Three-dimensional plots:
- Scatter plot
- Bar chart
- Caveats of using Matplotlib...