In this chapter, we discussed visualizing data with Python using plotting. To do this, we used matplotlib and Pandas. We covered box plots, scatter plots, bubble charts, logarithmic plots, autocorrelation plots, lag plots, three-dimensional plots, legends, and annotations.
Logarithmic plots (or log plots) are plots that use a logarithmic scale. The semi-log plots use linear scaling on one axis and logarithmic scaling on the other axis. Scatter plots plot two variables against each other. A bubble chart is a special type of scatter plot. In a bubble chart, the value of a third variable is relatively represented by the size of the bubble surrounding a data point. Autocorrelation plots graph autocorrelations of time series data for different lags.
We learnt about plot.ly, an online cloud based service for data visualization and built a box plot using this service. A box plot visualizes data based on the data's quartiles.
The next chapter, Chapter 7, Signal Processing and Time Series is...