The document discusses data visualization techniques, including Minard's plot of Napoleon’s troops and visualizing game log data from Starcraft using R. It also presents a regression analysis with datasets, detailing simple and multiple regression models, validation techniques, and the use of ggplot2 and tidyverse packages. References to external sources and guides related to the discussed topics are provided.

1. Data Visualization
SEJI OH
JULY 20, 2018

2. CONTENTS
 What Happened to Napoleon’s troops?
– Minard’s plot
– Dataset
– Reproduction of the plot using R
 What Can We Do With Game Log Data?
– Visualizing StarCraft with R
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3. CONTENTS
 Regression Analysis
– Dataset
– Simple Linear Regression Model
– Multiple Regression Model
References
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4. What Happened to Napoleon’s troops?
 Minard’s Plot[1]
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5. What Happened to Napoleon’s troops?
 Dataset: Napoleon’s March[2]
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6. What Happened to Napoleon’s troops?
 Let’s draw Minard’s plot using R, especially with the package
‘ggplot2’.[3]
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7. What Can We Do With Game Log Data?
 Visualizing StarCraft with R[4][5]
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8. What Can We Do With Game Log Data?
 Visualizing StarCraft with R[4][5]: colored by unitID
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9. Regression Analysis
 Dataset:
in
the package
 The goal is a establishment
of the multiple regression
model like this.
(Drawn with ggplot2)
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10. Regression Analysis
 Dataset: diamonds in the package ggplot2
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11. Regression Analysis
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 The package tidyverse and its family are used in this analysis.
 A holdout cross validation is applied.
 Random sampling from the data as the Train set 70% and the Test
set 30%.

12. Regression Analysis
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 Check the principal components in
the data.
 Draw a plot which shows a
relation between variables.
 Or calculate the Pearson
correlation coefficient.

13. Regression Analysis
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Simple linear model
 The independent
variable = price
 The response
variable = carat

14. Regression Analysis
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Simple regression
model
 The power
transformation is
applied.

15. Regression Analysis
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Multiple regression
model
 Various
independent
variables =
price, x, y, z
 RMSE = 0.0843145

16. Regression Analysis
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Multiple regression
model
 The normal
distribution
predictor is applied.
 RMSE = 0.08431445

17. Regression Analysis
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Multiple regression
model
 The power
transformation is
applied.
 RMSE = 0.01722037

18. Regression Analysis
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Multiple regression
model
 Check the
validation of the
model with the test
set.
 RMSE = 0.01722037

19. refrences
[1] Wikipedia, Charles Joseph Minard
https://en.wikipedia.org/wiki/Charles_Joseph_Minard
[2] The Grammar of Graphics, 2ED, Leland Wilkinson, SPSS Inc.
[3] A Layered Grammar of Graphics, Hadley WICKHAM
http://vita.had.co.nz/papers/layered-grammar.pdf
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20. refrences
[4] Visualizing Professional StarCraft with R
https://towardsdatascience.com/visualizing-professional-starcraft-
with-r-598b5e7a82ac
[5] StarCraftMining, Github
https://github.com/bgweber/StarCraftMining
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