Package 'DataScienceExercises'

Aggregated on GDP, life expectancy, and population over time.

Description

The gapminder data on population size, life expectancy, and GDP per capita levels, aggregated over continents.

Usage

aggGDPlifexp

Format

A data frame with 60 rows and 5 variables:

continent

Continent name

year

Year of the observation

lifeExp

Average life expectancy at birth, in years

pop

Average population, in nb of people

gdpPercap

Average GDP per capita, in 2005-international dollars

Source

https://github.com/jennybc/gapminder

---

Data on beer consumption

Description

A data set on beer consumption; the data was obtained for a single household

Usage

beer

Format

A data frame with 30 rows and 5 variables

consumption

liters of beer consumed

price

Price of beer ($)

price_liquor

price of other liquor ($)

price_other

price of other goods and services (an index)

income

income ($)

Source

http://www.principlesofeconometrics.com/poe4/poe4stata.htm

---

Check whether your setup is complete

Description

Reports your 'R' version, the version of this package, and whether all packages needed by the exercises are installed. If something does not work, run this function and send its output to your lecturer.

Usage

check_setup()

Value

A logical value, invisibly: 'TRUE' if the setup is complete.

Examples

## Not run: 
check_setup()

## End(Not run)

---

Data on economics journals subscription fees

Description

A data set on how much libraries need to pay for subscription plans of journals in the field of economics.

Usage

econjournals

Format

A data frame with 327 rows and 10 variables

title

Title of the journal

field

The subfield of economics the journal is devoted to, e.g. 'General', 'Finance' or 'Urban and Regional'.

publisher

The name of the publisher

publisher_type

Type of publisher: 'profit' or 'nonprofit'

first_year

First year in which journal was published in English language.

sub_price

Price to university libraries for print and online access in the United States in 2004. Measured in nominal dollars.

pages_py

Pages published in 2003

impact

Journal impact factor in 2002

citations

Total cites in 1999

papers

Papers published in 2002

Source

https://www.econ.ucsb.edu/~tedb/Journals/pricing.html

---

Artificial data on heights of EUF students in 2021

Description

A an artificial data set about the height of students from the Europa University Flensburg. The composition of the population was set according to official information about the student population in 2021, the heights were created artificially by drawing from a random distribution, which was calibrated for mean and standard deviation parameters of the German population.

Usage

EUFstudents

Format

A data frame with 6402 rows and 2 variables

Gender

Gender of the person

Height

Height of the person

Source

Official statistics on the student population of the Europa-Universität Flensburg, https://www.uni-flensburg.de/die-universitaet/profil-der-euf/zahlen-und-fakten

---

Study semester of the EUF students in 2021

Description

A data set on the distribution of study semesters for all students of the Europa-University Flensburg in the spring semester 2021.

Usage

EUFstudentsemesters

Format

A data frame with 5875 rows and 2 variables

Semester

The study semester of the student

ID

An ID for the student

Source

Official statistics on the student population of the Europa-Universität Flensburg, https://www.uni-flensburg.de/die-universitaet/profil-der-euf/zahlen-und-fakten

---

Data on GDP, life expectancy, and population size in 2007.

Description

A subset of the gapminder data on population size, life expectancy, and GDP per capita levels in 2007.

Usage

gdplifexp2007

Format

A data frame with 142 rows and 5 variables:

country

Country name

continent

Continent name

lifeExp

Life expectancy at birth, in years

pop

Population in 2007, in nb of people

gdpPercap

GDP per capita, in 2005-international dollars

Source

https://github.com/jennybc/gapminder

---

Annual GDP growth of Germany, 2015-2020

Description

A small data set on the annual growth rate of German real GDP. It is used in the exercises on data import, where it is also provided as the csv file 'growth_data_1.csv'.

Usage

Growth

Format

A data frame with 6 rows and 3 variables

country

Country name, here always 'Germany'

Growth

Annual growth rate of real GDP, in percent

year

Year of the observation

Source

World Bank World Development Indicators, indicator 'NY.GDP.MKTP.KD.ZG', obtained via the 'WDI' package; see 'data-raw/Growth.R'.

---

List the available exercises

Description

Lists all exercise collections that ship with this package.

Usage

list_exercises()

Value

A character vector of exercise names, invisibly. The names and their titles are printed to the console.

Examples

## Not run: 
list_exercises()

## End(Not run)

---

A reduced data set on flights from NYC in 2021

Description

A random sample of 50k flights (out of 336776) from NYC in 2021.

Usage

nycflights21_small

Format

A data frame with 50000 rows and 5 variables:

arr_delay

Arrival delay, in minutes. Negative times represent early arrivals.

dep_delay

Departure delay, in minutes. Negative times represent early departures.

month

Month of departure.

carrier

Two letter carrier abbreviation.

distance

Distance between airports, in miles.

Source

https://github.com/simonpcouch/anyflights

---

Compute the population variance of a vector

Description

Computes the population variance as defined by

$\sigma^2=\frac{1}{N}\sum_{i=1}^N(x_i-\mu)^2$

where $\mu$ is the population mean ($\frac{1}{N}\sum_{i=1}^Nx_i$) and $N$ is the size of the population

Usage

pop_var(x)

Arguments

x	A numerical vector

Value

The population variance of this vector

Examples

pop_var(c(2, 3, 4, 5))
pop_var(rnorm(20, 1, 0))

---

Product complexity and export shares of periphery countries

Description

A data set on the complexity of traded products and the share of these products in the exports of periphery countries. It is used in the exercises on data import, where it is also provided as the csv file 'product_complexity.csv'.

Usage

product_complexity

Format

A data frame with 10 rows and 3 variables

commoditycode

The code identifying the product according to the Harmonized System (HS)

product_complexity

The complexity of the product, measured as its product complexity index (PCI)

exp_share

The share of this product in total exports, in percent

Source

Own computations based on the BACI trade data of the CEPII; see 'data-raw/product_complexity.R'.

---

Summarize a linear regression model in a concise table

Description

Returns the estimated coefficients of a linear regression model together with their standard errors, test statistics, p-values and the bounds of the 95

Usage

regression_table(model, digits = 3, level = 0.95)

Arguments

model	A fitted model object, usually the result of a call to [stats::lm()].
digits	The number of digits to which the results are rounded.
level	The confidence level of the reported interval.

Details

This is a convenience function: the same information is available from 'summary(model)' and [stats::confint()], which you should also know how to use.

Value

A 'data.frame' with one row per estimated coefficient and the columns 'term', 'estimate', 'std_error', 'statistic', 'p_value', 'lower_ci' and 'upper_ci'.

Examples

linmod <- lm(consumption ~ price_liquor, data = beer)
regression_table(linmod)

---

Start an exercise

Description

Starts one of the interactive exercise collections of this package in your web browser. This is a convenience wrapper around [learnr::run_tutorial()]: it fills in the package name and makes sure the exercise opens in a browser window rather than the RStudio viewer pane.

Usage

run_exercise(name, launch_browser = TRUE, ...)

Arguments

name	The name of the exercise, e.g. '"Basics"'. Case does not matter. Call [list_exercises()] to see the available names.
launch_browser	Should the exercise open in your default web browser? 'TRUE' by default, which is usually what you want.
...	Further arguments passed on to [learnr::run_tutorial()].

Details

To stop an exercise, press the red stop button in RStudio, or press 'Esc' in the console.

Value

Called for its side effect of starting the exercise.

Examples

## Not run: 
run_exercise("Basics")

## End(Not run)

---

Population and labor force of Germany, 2015-2020

Description

A small data set on the size of the German population and its labor force. It is used in the exercises on data import, where it is also provided as the csv file 'unemp_pop.csv'.

Usage

unemp_pop

Format

A data frame with 6 rows and 4 variables

country

Country name, here always 'Germany'

year

Year of the observation

population

Total population, in nb of people

labor_force

Total labor force, in nb of people

Source

World Bank World Development Indicators, indicators 'SP.POP.TOTL' and 'SL.TLF.TOTL.IN', obtained via the 'WDI' package; see 'data-raw/unemp_pop.R'.

---

Data on wine properties

Description

A data set containing information about the alcohol and residual sugar contained in white and red wines, as well as their quality

Usage

wine2dine

Format

A data frame with 6497 rows and 4 variables:

alcohol

The alcohol content of the wine

quality

An quality score between 0 and 10, based on sensory data

residual sugar

The amount of sugar left in the wine

kind

The kind of wine, i.e. red or white

Source

https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/

---