We've covered a lot of ground in this chapter. We wrote a simple Python ETL script to scrape data from a web-based API and import that dataset into InfluxDB. We learned key concepts behind time and field value aggregations. Then, we tried out different drawing styles and learned how to instruct Grafana on how to connect the dots when there is missing data.
We also set axis units, converted our data from one unit of measure into another, and displayed multiple series with different units on the same graph. Finally, we worked with the legend display to make it more space-efficient and aesthetically pleasing.
In the next chapter, we'll be diversifying our display panels so that they include panels that are more specialized in functionality. While these panels are somewhat more limited, they still complement the graph panel by characterizing data in truly unique ways.
