Statistics with R:

Data Wrangling | Data Visualisation | Basic Modelling

Arif P. Sulistiono

Kelas Data on 28 Oct. 2021, 4 Nov. 2021, and 11 Nov. 2021
mof.dac

About me

An employee of the Republic of Indonesia’s Ministry of Finance. Funded by the Indonesia Endowment Fund for Education ("Lembaga Pengelola Dana Pendidikan"), at the moment, on study leave to join a PhD program in the School of Economics, the University of Nottingham with research interests in Indonesia's government bonds market and their bondholders' behaviour. Also a research assistant at tracktheeconomy.ac.uk.

Functions

Rows: filter(), arrange(), recode(), slice(), slice_min(), slice_max(), slice_head(), slice_tail()
Columns: select(), relocate(), rename()
Both: count(), mutate(), transmute()

Analysing: group_by(), summarise()/summarize(), rowwise()
Merging: left_join(), inner_join(), right_join(), full_join(), semi_join(), anti_join()
Manipulating: ifelse()
Dealing with NA: fill(), replace(), zoo::na.approx(), drop_na()
Combining: rbind(), bind_rows, cbind(), bind_cols
Reshaping: pivot_wider(), pivot_longer()

Scatter plot: geom_point()
Line chart: geom_line()
Bar plot: geom_bar(), geom_col()
Box plot: geom_boxplot()
Histogram: geom_histogram()

Loading the dataset: read_csv() or read_excel(),
Correlation: Hmisc::rcorr(as.matrix())
Summary: stargazer()
Linear regression: lm(), lm_robust(), dynlm()
Reporting: broom::tidy()
Saving: write_csv()

%>%

Pipe operator: ...then

Prerequisites

Clean the environment

rm(list=ls())
ls()

Prerequisites

Clean the environment

rm(list=ls())
ls()

Install the package & load the library

install.packages("tidyverse")
library(tidyverse)

Prerequisites

Clean the environment

rm(list=ls())
ls()

Install the package & load the library

install.packages("tidyverse")
library(tidyverse)

Set the working directory

getwd()
setwd("/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData")
dir()

Data

Ages

library(readxl)
op_ages <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_ages")
DT::datatable(op_ages, fillContainer = FALSE, options = list(pageLength = 3))

	name	age
1	Zunesha	1000
2	Jarul	408
3	Jorul	344

Data

Powers

library(readxl)
op_powers <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_powers")
DT::datatable(op_powers, fillContainer = FALSE, options = list(pageLength = 3))

Show entries

Search:

	power	character	level	affiliations
1	100	Red Haired Shanks	Yonko	Red Haired Pirates
2	100	Marshall D. Teach	Yonko	Blackbeard Pirates
3	100	Charlotte Linlin	Yonko	Big Mom Pirates

Showing 1 to 3 of 56 entries

Previous1 2 3 4 5…19Next

Data Visualisation10

Datasaurus

Never trust summary statistics alone.

Source: library(datasauRus); https://github.com/Z3tt/TidyTuesday/tree/master/plots/2020_42

ggplot2

Basic elements:

Data: data = ...
Geometries: geom_
Aesthetics: aes(x = ..., y = ..., ...)
Scales: scale_
Statistical transformations: stat_
Coordinate system: coord_
Facets: facet_
Visual themes: theme()

Decision trees

Source: https://www.data-to-viz.com

Assigning colors

Source: "Hands-On Data Visualization" by Jack Dougherty & Ilya Ilyankou

Source: https://github.com/allisonhorst/stats-illustrations/

Line plot

Animating bar plot

Visualisasi data tentang utang dan pendapatan per penduduk dengan menggunakan bahasa pemrograman R. Kode bisa dilihat pada tautan https://t.co/YzqY3hmGfc.

Secara rasio, tidak berbeda jauh dengan data rasio utang pemerintah terhadap PDB seperti yang disampaikan @DJPPRkemenkeu. pic.twitter.com/1D6k2nmHsW
— Arif P. Sulistiono (@arifpras) May 1, 2020

Animating line plot

Visualisasi data tentang pergerakan nilai tukar #rupiah terhadap dollar AS pada #krisis 2008 dan tahun ini dengan menggunakan bahasa pemrograman #R. Kode bisa dilihat pada tautan https://t.co/YzqY3hmGfc. pic.twitter.com/PMHFjWIJQB
— Arif P. Sulistiono (@arifpras) May 4, 2020

Practical sessions

Source: https://arifpras.github.io/WranglingViz/

Basic Modelling19

Initial specifications

$$ \text{Sales}_t = \alpha_0 + \alpha_1 \text{Chapters}_t + \alpha_2 \text{LastMovie}_t + \alpha_3 \text{VIX index}_t + \upsilon_t $$ $$ \text{Sales}_t = \beta_0 + \beta_1 \text{Pages}_t + \beta_2 \text{LastMovie}_t + \beta_3 \text{VIX index}_t + \epsilon_t $$

Dataset

library(readxl)
op_sales <- read_excel(path = "/Users/arifpras/OneDrive - The University of Nottingham/BB_KelasData/KelasData/00_Datasets/OP_all.xlsx", sheet = "OP_sales")
DT::datatable(op_sales, fillContainer = FALSE, options = list(pageLength = 3))

Show entries

Search:

	volume	title	release_date	pages	chapters	sales_mio	last_movie_days	vixi_avg
1	50	Arriving Once Again	2008-06-04T00:00:00Z	216	10	1.441785	95	23.6
2	51	The 11 Supernovas	2008-09-04T00:00:00Z	232	11	1.517953	187	39.95
3	52	Roger and Rayleigh	2008-12-04T00:00:00Z	216	10	1.476194	278	48.06

Showing 1 to 3 of 51 entries

Previous1 2 3 4 5…17Next

Dependent variable

Independent variables

Let's practice!

Practical sessions

Source: https://arifpras.github.io/BasicModelling/

Thank you for listening.

All teaching materials are available on https://github.com/arifpras/KelasData

Slides created via the R packages: xaringan and gadenbuie/xaringanthemer.
The chakra comes from remark.js, knitr, and R Markdown.

Acknowledgements

Grolemund, G., & Wickham, H. (2017). R for Data Science. O’Reilly Media.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686
Claus O. Wilke: Data Visualization in R, https://wilkelab.org/SDS375/
Cedric Scherer's personal blog: https://www.cedricscherer.com/
...and other sources i.e. stackoverflow.com, github.com, etc.

Datasets:

One Piece chapter and character: https://www.kaggle.com/michau96
One Piece anime rating: https://www.kaggle.com/aditya2803
One Piece power ranking: https://www.opfanpage.com/2018/06/29/one-piece-power-ranking-chart/
One Piece characters' age: https://listfist.com/list-of-one-piece-characters-by-age
One Piece by volume: https://listfist.com/list-of-one-piece-volumes
One Piece by chapter: https://listfist.com/list-of-one-piece-manga-chapters
One Piece sales: https://erzat.blog/top-sales-according-to-series-for-the-month-of-september-2021/ and https://twitter.com/WSJ_manga/status/1214168838511702016
VIX index: https://finance.yahoo.com/quote/%5EVIX?p=%5EVIX

GIF files:

Luffy, flying: https://pa1.narvii.com/5869/51088074557b4091944c2007ec33384020920f87_hq.gif
Luffy, thinking: https://c.tenor.com/WcoVJ8aQcwkAAAAC/one-piece-monkey-d-luffy.gif
Shanks vs. Akainu: https://www.quora.com/What-would-happen-if-Deku-was-sent-to-the-One-Piece-universe

About me

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Statistics with R:

Data Wrangling | Data Visualisation | Basic Modelling

Arif P. Sulistiono

Kelas Data on 28 Oct. 2021, 4 Nov. 2021, and 11 Nov. 2021 mof.dac

About me

Functions

%>%

Prerequisites

Clean the environment

Prerequisites

Clean the environment

Install the package & load the library

Prerequisites

Clean the environment

Install the package & load the library

Set the working directory

Data

Ages

Data

Powers

Data Visualisation

Datasaurus

ggplot2

Basic elements:

Decision trees

Assigning colors

Line plot

Animating bar plot

Animating line plot

Practical sessions

Basic Modelling

Initial specifications

Dataset

Dependent variable

Independent variables

Practical sessions

Acknowledgements

Datasets:

GIF files:

About me

Help

Kelas Data on 28 Oct. 2021, 4 Nov. 2021, and 11 Nov. 2021
mof.dac