TADSummit EMEA Americas November 2020 Getting started with data visualization. Seeing patterns in telecom data David Curran, Machine Learning Engineer How to plot data Where to get data Where to get code / visualizations – Joyplots How to get feedback Imitate, assimilate, innovate Grammar of graphs Network and geographic visualizations for Telecoms

2. Visualising Trends in the
Loudness of Popular Music
David Curran.

3. Published.

4. !
#winner

5. How to…
• Where to get data?
• Where to get code?
• How to get feedback?
• Grammar of graphics
• DIY

6. First…where to get data
•Kaggle
•Governments: WHO, CSO, EUROSTAT
•Published papers
•Reddit.com/r/datasets
•datasetsearch.research.google.com

7. Second…where to get visualisations
•R-bloggers.com
•Search #ggplot
•/r/dataisbeautiful
•Reddit.com/r/datasets
•Historical books

8. Joyplots
r-bloggers post on them

9. •Started with Billboard 100
•Put it up on reddit.
•Not that good!
•But…….

10. Just happened to see a visualisation on Twitter!

11. Songs: faster, louder, longer

12. Advice…

13. New visualisations
based on advice.

14. Inspiration……

15. Imitate.
Assimilate.
Innovate.*
*Clark Terry, Jazz Trumpeter
How to be creative: steal.

16. ‘The only art I’ll only ever
study is the stuff I can steal
from’.

18. 7 Steps to Make Great
Visualisations

19. #1 Find the data
year
<int>
loudness
<dbl>
decade
<int>
1 1995 -11.482 1990
2 1993 -15.193 1990
3 2006 -4.707 2000

20. #2 Make a simple graph
ggplot(data=df, aes(x=decade, y=loudness,
group=1)) +
geom_line(color="blue")+
geom_point(color="blue")

21. #3 Make an ugly graph!
ggplot(loud, aes(x = loudness,
y = decade, group = decade))
+ geom_density_ridges2()e5

22. #3 Make an ugly graph!
ggplot(loud, aes(x = loudness,
y = decade, group = decade))
+ geom_density_ridges2()
Error: geom_density_ridges requires the following missing aesthetics: y

23. #4 Add title, labels, theme etc
labs(title = 'Loudness of Songs',subtitle='difference of quietest to loudest part of songs',
x="Loudness (dBFS)",y="Decade")+
scale_x_continuous(limits=c(-40, 4.2), expand = c(0.01, 0)) +
scale_y_reverse(breaks=c(2010,2000,1990, 1980,1970, 1960,1950), expand = c(0.01, 0))+
theme_bw() + theme(plot.title = element_text(hjust=0.5))

24. #6 Other Tweaks
• Code for all this together
geom_density_ridges2(scale
= 0.9,fill = "lightblue")

25. # 7 Colour
stat_density_ridges(
geom = "density_ridges_gradient",
calc_ecdf = TRUE,
quantiles = 4, quantile_lines = TRUE
) +scale_fill_viridis_d(name = "Quartiles")
•geom_density_ridges_gradient(scale = 3,
rel_min_height = 0.01) +
• scale_fill_viridis_c(name = "Temp. [F]", option
= "C") +

26. DIY….Go Make A Picture.

27. Raincloud Plot

28. “We have to find a very wide range of ways of communicating about this. This graphic
is not the one answer.” Ed Hawkins
Climate Change

29. Climate Change

30. Telecom Usecases

31. Telecom Visualizations
•Maps
•Churn
•Upsell
•Data Description
Dashboard, sentiment…

32. Churn Visualisation

33. Churn Visualisation

34. Maps

35. Learn at Topi Map Challenge
https://github.com/tjukanovt/30DayMapChallenge