History

1 Some notable conflicts in recent history (EM13CHS302, EM13CHS303, EM13CHS101)

library(plotly)

# Fictitious conflict data
conflicts <- data.frame(
country = c("Afghanistan", "Ukraine", "Syria", "Yemen", "Ethiopia"),
latitude = c(33.93911, 48.3794, 34.8021, 15.5527, 9.145),
longitude = c(67.70995, 31.1656, 38.9968, 48.5164, 40.489673),
description = c(
"Ongoing conflict with Taliban.",
"Ongoing war since 2022.",
"Civil war since 2011.",
"Humanitarian crisis and civil war.",
"Conflict between regional groups."
)
)

# Create interactive map
conflict_map <- plot_ly(
data = conflicts,
type = 'scattergeo',
mode = 'markers',
lat = ~latitude,
lon = ~longitude,
text = ~paste(country, "<br>", description),
hoverinfo = "text",
marker = list(
size = 10,
color = "red",
line = list(width = 1, color = "black")
)
) %>%
layout(
title = "World Conflict Map",
geo = list(
showframe = FALSE,
showcoastlines = TRUE,
projection = list(type = "natural earth")
)
)

# Show the map
mapa_conflitos

Suggestions:

Try modifying the graph, using/replacing the commands below in the code snippet:

marker = list(
size = 15, # Changed from 10 to 15 to increase the markers
color = "red",
line = list(width = 1, color = "black")
)

2 Population growth in New York, Tokyo, São Paulo and Mumbai (1960-2020) (EM13CHS201, EM13CHS202)

library(plotly)

# Dados fictícios de população ao longo do tempo
dados_populacao <- data.frame(
  cidade = rep(c("Nova York", "Tóquio", "São Paulo", "Mumbai"), each = 5),
  latitude = c(40.7128, 40.7128, 40.7128, 40.7128, 40.7128,
               35.6895, 35.6895, 35.6895, 35.6895, 35.6895,
               -23.5505, -23.5505, -23.5505, -23.5505, -23.5505,
               19.076, 19.076, 19.076, 19.076, 19.076),
  longitude = c(-74.0060, -74.0060, -74.0060, -74.0060, -74.0060,
                139.6917, 139.6917, 139.6917, 139.6917, 139.6917,
                -46.6333, -46.6333, -46.6333, -46.6333, -46.6333,
                72.8777, 72.8777, 72.8777, 72.8777, 72.8777),
  ano = rep(seq(1960, 2020, by = 15), 4),
  populacao = c(8, 12, 16, 20, 25,    # Nova York
                10, 15, 20, 25, 30,   # Tóquio
                7, 12, 18, 24, 30,    # São Paulo
                6, 10, 16, 22, 28)    # Mumbai (em milhões)
)

# Criando o mapa interativo com slider no tempo
mapa_populacao <- plot_ly(
  data = dados_populacao,
  type = 'scattergeo',
  mode = 'markers',
  lat = ~latitude,
  lon = ~longitude,
  frame = ~ano,  # Adiciona a animação por ano
  text = ~paste(cidade, "<br>População:", populacao, "milhões"),
  hoverinfo = "text",
  marker = list(
    size = ~populacao * 0.5,  # Ajusta o tamanho com base na população
    color = "blue",
    opacity = 0.7
  )
) %>%
  layout(
    title = "Evolução Populacional por Cidade (1960-2020)",
    geo = list(
      showframe = FALSE,
      showcoastlines = TRUE,
      projection = list(type = "natural earth")
    )
  )

# Exibir o mapa
mapa_populacao

Suggestions:

Try modifying the graph, using/replacing the commands below in the code snippet:

# After the line lon = ~longitude
frame = ~year, # Add the animation by year

3 Some information about Geological Eras (EF06CI11, EF05HI02, EM13CHS301)

# Dados sobre as eras geológicas e seus períodos
dados_geologicos <- data.frame(
  Regiao = c("América do Norte", "América do Sul", "Europa", "África", "Ásia", "Oceania"),
  Era = c("Paleozoica", "Mesozoica", "Cenozoica", "Pré-Cambriana", "Mesozoica", "Cenozoica"),
  Periodo = c("Devoniano (416-359 mi anos)", 
              "Jurássico (199-145 mi anos)", 
              "Quaternário (2,58 mi anos até presente)", 
              "Proterozoico (2,5 bi a 541 mi anos)", 
              "Triássico (251-199 mi anos)", 
              "Holoceno (11,7 mil anos até presente)"),
  Latitude = c(45, -15, 50, 0, 30, -25),
  Longitude = c(-100, -60, 10, 20, 100, 135)
)

# Criar o mapa interativo
fig <- plot_ly(
  data = dados_geologicos,
  type = "scattergeo",
  mode = "markers",
  lat = ~Latitude,
  lon = ~Longitude,
  text = ~paste(
    "<b>Região:</b>", Regiao, "<br>",
    "<b>Era:</b>", Era, "<br>",
    "<b>Período:</b>", Periodo
  ),
  marker = list(size = 15, color = c("blue", "green", "red", "purple", "orange", "brown"))
)

# Layout do mapa com títulos
fig <- fig %>%
  layout(
    title = "Eras e Períodos Geológicos - Distribuição Mundial",
    geo = list(
      showland = TRUE,
      landcolor = "rgb(240, 240, 240)",
      showcountries = TRUE,
      countrycolor = "rgb(200, 200, 200)",
      projection = list(type = "natural earth")
    )
  )

# Exibir o mapa
fig

# Data about geological eras and their periods
geological_data <- data.frame(
Region = c("North America", "South America", "Europe", "Africa", "Asia", "Oceania"),
Era = c("Paleozoic", "Mesozoic", "Cenozoic", "Precambrian", "Mesozoic", "Cenozoic"),
Period = c("Devonian (416-359 million years)",
"Jurassic (199-145 million years)",
"Quaternary (2.58 million years to present)",
"Proterozoic (2.5 billion to 541 million years)",
"Triassic (251-199 million years)",
"Holocene (11.7 million years to present)"),
Latitude = c(45, -15, 50, 0, 30, -25),
Longitude = c(-100, -60, 10, 20, 100, 135)
)
# Create interactive map
fig <- plot_ly(
data = dados_geologicos,
type = "scattergeo",
mode = "markers",
lat = ~Latitude,
lon = ~Longitude,
text = ~paste(
"<b>Region:</b>", Region, "<br>",
"<b>Era:</b>", Era, "<br>",
"<b>Period:</b>", Period
),
marker = list(size = 15, color = c("blue", "green", "red", "purple", "orange", "brown"))
)

# Map layout with titles
fig <- fig %>%
layout(
title = "Geological Eras and Periods - Worldwide Distribution",
geo = list(
showland = TRUE,
landcolor = "rgb(240, 240, 240)",
showcountries = TRUE,
countrycolor = "rgb(200, 200, 200)",
projection = list(type = "natural earth")
)
)

# Show map
fig

Suggestions:

Try modifying the graph, using/replacing alternatively the commands below in the code snippet:

marker = list(
size = 10, # Marker size
color = "blue", # Uniform color for simplicity
opacity = 0.7 # Transparency to highlight on the map
)