Objects Launched into Space

Proposal

INFO526 Term Project

Author

Affiliation

Derek Rice

School of Information, University of Arizona

if (!require("pacman"))
    install.packages("pacman")

pacman::p_load(tidyverse, tidytuesdayR, dplyr, janitor, lubridate,ggplot2)

Dataset: Outer Space Objects

The dataset summarizes the number of objects launched into space from 1957 to 2023 as a function of entity.
The source of the dataset is the United Nations Office of Outer Space Affairs. A prior analysis of the dataset is available here: https://ourworldindata.org/grapher/yearly-number-of-objects-launched-into-outer-space
Dataset source: https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-04-23/readme.md
The dataset is comprised of 4 columns and 1175 rows - see “head” and “glimpse” summarized herein.
I choose the dataset because I was thinking it would be interesting to identify the countries launching gadgets into space and the magnitude of the difference between the United States and other countries.
A graphical plot summary of the data is provided below - the plot presents an overview of the dataset and visually displays the number of launches per entity between 1957 and 2023.

# cite: https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-04-23/readme.md

outer_space_objects <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-04-23/outer_space_objects.csv')

dim(outer_space_objects)

[1] 1175    4

head(outer_space_objects)

# A tibble: 6 × 4
  Entity  Code   Year num_objects
  <chr>   <chr> <dbl>       <dbl>
1 APSCO   <NA>   2023           1
2 Algeria DZA    2002           1
3 Algeria DZA    2010           1
4 Algeria DZA    2016           3
5 Algeria DZA    2017           1
6 Angola  AGO    2017           1

glimpse(outer_space_objects)

Rows: 1,175
Columns: 4
$ Entity      <chr> "APSCO", "Algeria", "Algeria", "Algeria", "Algeria", "Ango…
$ Code        <chr> NA, "DZA", "DZA", "DZA", "DZA", "AGO", "AGO", NA, NA, NA, …
$ Year        <dbl> 2023, 2002, 2010, 2016, 2017, 2017, 2022, 1985, 1992, 1996…
$ num_objects <dbl> 1, 1, 1, 3, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 3…

filtered_outer_space_objects = outer_space_objects %>%
  filter (Entity %in% c("United States","China","Russia","Japan","France","India","European Space Agency", "Germany"))

Graphical Summary of the Dataset

ggplot(data = filtered_outer_space_objects, aes(x=Year, y=num_objects, color = Entity)) +
  geom_smooth(se = FALSE, method = loess) +
  labs(
    x = "year of launch",
    y = "number of objects launched",
    title = "Number of objects launched into space by year",
    subtitle = "data collected from United Nations Office of Outer Space Affairs",
    caption = "objects are defined as satelllites, probes, landers, crewed spacecrafts, and space station flights"
  ) +
  theme(
    axis.text.x = element_text(size = 8, face = "bold"),
    axis.text.y = element_text(size = 8, face = "bold"),
    plot.title = element_text (size = 10, face = "bold", hjust = 0.5),
    plot.subtitle = element_text(size = 8, face = "plain", hjust = 0.5),
    plot.caption = element_text(size = 6, face = "plain", hjust = 1),
    panel.background = element_rect(fill = "white"),
    plot.background = element_rect(fill = "white"),
    panel.grid.major = element_line(color = "gray90"),
    panel.grid.minor = element_line(color = "gray95")
  )

Dataset Variable (column) Descriptions

The dataset comprises 4 columns and 1175 rows. The dataset summarizes space launch events between 1957 and 2023 as a function of the entity or country responsible for the launch.
Entity: the country launching the space object
Code: the type of gadget launched into Earth orbit or beyond (satellites, probes, landers, crewed spacecrafts, and space station components)
Year: the year of the launch
num_objects: the number of objects launched by “Entity” during a year.

Questions

Question 1 - what country is most likely to become the first “space faring nation” and is there a close second? I propose to define “space faring nation” as the country that launches an order of magnitude more vehicles into space than all other countries combined. I’ll fit a polynomial regression model to the dataset by country and extrapolate the model into the future to help identify the likely candidates.

Analysis plan

The analysis plan is to plot the data on a map and display the launches by country over time. Currently, I have no idea how to do this, create a map, and plot an event from the data set onto the map?
I am thinking I will need to get a map of the world with the countries displayed. Another data set with the longitude and latitude for each country may be needed.
The launch event data set includes country and number of launches per year, to this I am thinking I will need to add columns defining the longitude and latitude of each launch event.
With longitude and latitude defined for each row/event I would then plot the launches on a map.
The analysis plan is to have an office hours meetign with Professor Chism the week of June 3rd and discuss how to plot country launch data on a world map. I’ll then completed the required learning and apply that new skillset to the launch dataset.

Detailed Analysis Plan

Review with Professor Chism how best to plot data on a world map
Use a polynomial regression model to extrapolate the launch data by country into the future for the six most prominant countries
Plot the extrapolated dataset onto a world map to identify the most likely country to become a “Space Faring Nation”.

Plan of Attack

Approach by Task
Task Name	Status	Date	Summary
Select dataset	complete	May 27th	selected the Space Object Launch Dataset
Define question to be answered	complete	May 28th	what country is most likely to become the 1st space faring nation
Submit draft proposal for peer review	complete	May 29th	proposal submitted - comments under review
Response to peer review	complete	June 2nd	peer review comments incorporate into the proposal
Submit project proposal	complete	June 3rd	proposal submitted to Professor Chism
Office hours with Prof Chism to discuss approach	in-work	June 9th	need to learn how to plot launch data on a map?
Complete required learning	in-work	June 15th	Reviewed material suggested by Prof. Chism
Complete initial analysis of the dataset	not started	June 15th	Data plotted on a map
draft presentation and writeup	not started	June 21st	draft files committed to github
Complete presentation	not started	June 23rd	submit to github
Comlete writeup	not started	June 23rd	submit to github
final submission	not started	June 24th	submit to github

--- title: "Objects Launched into Space" subtitle: "Proposal" author: - name: "Derek Rice" affiliations: - name: "School of Information, University of Arizona" description: "INFO526 Term Project" format: html: code-tools: true code-overflow: wrap code-line-numbers: true embed-resources: true editor: visual code-annotations: hover execute: warning: false --- ```{r} #| label: load-pkgs #| message: false if (!require("pacman")) install.packages("pacman") pacman::p_load(tidyverse, tidytuesdayR, dplyr, janitor, lubridate,ggplot2) ``` ## Dataset: Outer Space Objects - The dataset summarizes the number of objects launched into space from 1957 to 2023 as a function of entity. - The source of the dataset is the United Nations Office of Outer Space Affairs. A prior analysis of the dataset is available here: https://ourworldindata.org/grapher/yearly-number-of-objects-launched-into-outer-space - Dataset source: https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-04-23/readme.md - The dataset is comprised of 4 columns and 1175 rows - see "head" and "glimpse" summarized herein. - I choose the dataset because I was thinking it would be interesting to identify the countries launching gadgets into space and the magnitude of the difference between the United States and other countries. - A graphical plot summary of the data is provided below - the plot presents an overview of the dataset and visually displays the number of launches per entity between 1957 and 2023. ```{r} #| label: load-dataset #| message: false # cite: https://github.com/rfordatascience/tidytuesday/blob/master/data/2024/2024-04-23/readme.md outer_space_objects <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-04-23/outer_space_objects.csv') ``` ```{r} dim(outer_space_objects) ``` ```{r} head(outer_space_objects) ``` ```{r} glimpse(outer_space_objects) ``` ```{r} filtered_outer_space_objects = outer_space_objects %>% filter (Entity %in% c("United States","China","Russia","Japan","France","India","European Space Agency", "Germany")) ``` ## Graphical Summary of the Dataset ```{r} ggplot(data = filtered_outer_space_objects, aes(x=Year, y=num_objects, color = Entity)) + geom_smooth(se = FALSE, method = loess) + labs( x = "year of launch", y = "number of objects launched", title = "Number of objects launched into space by year", subtitle = "data collected from United Nations Office of Outer Space Affairs", caption = "objects are defined as satelllites, probes, landers, crewed spacecrafts, and space station flights" ) + theme( axis.text.x = element_text(size = 8, face = "bold"), axis.text.y = element_text(size = 8, face = "bold"), plot.title = element_text (size = 10, face = "bold", hjust = 0.5), plot.subtitle = element_text(size = 8, face = "plain", hjust = 0.5), plot.caption = element_text(size = 6, face = "plain", hjust = 1), panel.background = element_rect(fill = "white"), plot.background = element_rect(fill = "white"), panel.grid.major = element_line(color = "gray90"), panel.grid.minor = element_line(color = "gray95") ) ``` ## Dataset Variable (column) Descriptions - The dataset comprises 4 columns and 1175 rows. The dataset summarizes space launch events between 1957 and 2023 as a function of the entity or country responsible for the launch. - **Entity**: <character> the country launching the space object - **Code**: <character> the type of gadget launched into Earth orbit or beyond (satellites, probes, landers, crewed spacecrafts, and space station components) - **Year**: <double-precision floating-point number> the year of the launch - **num_objects**: <double-precision floating-point number> the number of objects launched by "Entity" during a year. ## Questions - Question 1 - what country is most likely to become the first "space faring nation" and is there a close second? I propose to define "space faring nation" as the country that launches an order of magnitude more vehicles into space than all other countries combined. I'll fit a polynomial regression model to the dataset by country and extrapolate the model into the future to help identify the likely candidates. ## Analysis plan - The analysis plan is to plot the data on a map and display the launches by country over time. Currently, I have no idea how to do this, create a map, and plot an event from the data set onto the map? - I am thinking I will need to get a map of the world with the countries displayed. Another data set with the longitude and latitude for each country may be needed. - The launch event data set includes country and number of launches per year, to this I am thinking I will need to add columns defining the longitude and latitude of each launch event. - With longitude and latitude defined for each row/event I would then plot the launches on a map. - The analysis plan is to have an office hours meetign with Professor Chism the week of June 3rd and discuss how to plot country launch data on a world map. I'll then completed the required learning and apply that new skillset to the launch dataset. ## Detailed Analysis Plan - Review with Professor Chism how best to plot data on a world map - Use a polynomial regression model to extrapolate the launch data by country into the future for the six most prominant countries - Plot the extrapolated dataset onto a world map to identify the most likely country to become a "Space Faring Nation". ## Plan of Attack | Task Name | Status | Date | Summary | |--------------------------------------------------|-------------|-----------|-------------------------------------------------------------------| | Select dataset | complete | May 27th | selected the Space Object Launch Dataset | | Define question to be answered | complete | May 28th | what country is most likely to become the 1st space faring nation | | Submit draft proposal for peer review | complete | May 29th | proposal submitted - comments under review | | Response to peer review | complete | June 2nd | peer review comments incorporate into the proposal | | Submit project proposal | complete | June 3rd | proposal submitted to Professor Chism | | Office hours with Prof Chism to discuss approach | in-work | June 9th | need to learn how to plot launch data on a map? | | Complete required learning | in-work | June 15th | Reviewed material suggested by Prof. Chism | | Complete initial analysis of the dataset | not started | June 15th | Data plotted on a map | | draft presentation and writeup | not started | June 21st | draft files committed to github | | Complete presentation | not started | June 23rd | submit to github | | Comlete writeup | not started | June 23rd | submit to github | | final submission | not started | June 24th | submit to github | | | | | | | | | | | : Approach by Task