# Prep data
myAreas <- c("Saskatchewan", "Alberta", "Manitoba", "Ontario", "Quebec")
myColors <- c("darkgreen", "darkblue", "antiquewhite4", "darkred", "steelblue")
xx <- d1 %>% 
  filter(Measurement == "Production", Area %in% myAreas) %>%
  mutate(Area = factor(Area, levels = myAreas))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000000, color = Area)) +
  geom_line(size = 1, alpha = 0.7) +
  scale_color_manual(name = NULL, values = myColors) +
  scale_x_continuous(breaks = seq(1910, 2020, 10), expand = c(0.02,0)) +
  theme_agData(legend.position = "bottom") +
  labs(title = "Canadian Wheat Production", x = NULL,
       y = "Million Tonnes", caption = myCaption)
ggsave("wheat_canada_01.png", mp, width = 6, height = 4)

# Prep data
myAreas <- c("Saskatchewan", "Alberta", "Manitoba", 
             "Ontario", "Quebec", "British Columbia", 
             "Prince Edward Island", "New Brunswick", "Nova Scotia")
xx <- d1 %>% 
  filter(Measurement == "Production", Area %in% myAreas) %>%
  mutate(Area = factor(Area, levels = myAreas))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000000)) +
  geom_line(color = "darkgreen", alpha = 0.7) +
  facet_wrap(Area ~ ., scales = "free_y") +
  scale_x_continuous(breaks = seq(1910, 2010, 20)) +
  expand_limits(y = 0) +
  theme_agData(legend.position = "bottom",
               axis.text.x = element_text(angle = 45, hjust = 1)) +
  labs(title = "Canadian Wheat Production", x = NULL,
       y = "Million Tonnes", caption = myCaption)
ggsave("wheat_canada_02.png", mp, width = 6, height = 4)

# Prep data
myColors <- c("darkorange", "darkgreen", "steelblue")
myAreas <- c("Prairie Provinces", "Ontario", "Quebec", "Maritime Provinces")
xx <- d2 %>% 
  filter(Measurement == "Area Seeded", Area %in% myAreas) %>%
  mutate(Area = factor(Area, levels = myAreas))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000000, color = Item)) +
  geom_line(size = 0.75, alpha = 0.7) +
  facet_wrap(Area ~ ., scales = "free_y") +
  scale_x_continuous(breaks = seq(1910, 2010, 20), expand = c(0.02,0)) +
  scale_color_manual(name = NULL, values = myColors) +
  theme_agData(legend.position = "bottom") +
  labs(title = "Area Seeded", x = NULL,
       y = "Million Hectares", caption = myCaption) 
ggsave("wheat_canada_03.png", mp, width = 6, height = 4)

# Prep data
myColors <- c("darkorange", "darkgreen", "steelblue")
myAreas <- c("Saskatchewan", "Alberta", "Manitoba", 
             "Ontario", "Quebec", "British Columbia",
             "New Brunswick", "Prince Edward Island", "Nova Scotia")
xx <- d2 %>% 
  filter(Measurement == "Area Seeded", Area %in% myAreas) %>%
  mutate(Area = factor(Area, levels = myAreas))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000000, color = Item)) +
  geom_line(alpha = 0.7) +
  facet_wrap(Area ~ ., scales = "free_y") +
  scale_color_manual(name = NULL, values = myColors) +
  scale_x_continuous(breaks = seq(1910, 2010, 20), expand = c(0.02,0)) +
  theme_agData(legend.position = "bottom",
               axis.text.x = element_text(angle = 45, hjust = 1)) +
  labs(title = "Wheat Area Seeded", x = NULL,
       y = "Million Hectares", caption = myCaption) 
ggsave("wheat_canada_04.png", mp, width = 7, height = 5)

# Prep data
myAreas <- c("Alberta", "Saskatchewan", "Manitoba", "Ontario")
myColors <- c("darkred", "darkgreen", "antiquewhite4", "darkblue")
xx <- d1 %>% 
  filter(Measurement == "Yield", Area %in% myAreas) %>%
  mutate(Area = factor(Area, levels = myAreas))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000, color = Area)) +
  geom_line(size = 1, alpha = 0.1) +
  stat_smooth(geom = "line", method = "loess", se = F, size = 1, alpha = 0.7) +
  scale_color_manual(name = NULL, values = myColors) +
  scale_x_continuous(breaks = seq(1910, 2020, 10), expand = c(0.02,0)) +
  scale_y_continuous(breaks = seq(0, 6, 1)) +
  theme_agData(legend.position = "bottom") +
  labs(title = "Wheat Yields", x = NULL,
       y = "Tonnes / Hectare", caption = myCaption)
ggsave("wheat_canada_05.png", mp, width = 6, height = 4)

# Prep data
myMeasures <- c("Production", "Area Seeded")
xx <- d2 %>% 
  filter(Area == "Saskatchewan", 
         Item %in% c("Wheat, durum", "Wheat, spring"),
         Measurement %in% myMeasures) %>%
  mutate(Measurement = plyr::mapvalues(Measurement, myMeasures,
                          c("Production (Tonnes)", "Area Seeded (Hectares)")))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000000, color = Measurement)) +
  geom_line(size = 1, alpha = 0.7) +
  facet_grid(Item ~ ., scales = "free_y") +
  scale_color_manual(name = NULL, values = c("darkgoldenrod2", "darkgreen")) +
  scale_x_continuous(breaks = seq(1910, 2020, 10), expand = c(0.02,0)) +
  expand_limits(y = 0) +
  theme_agData(legend.position = "bottom") +
  labs(title = "Saskatchewan Wheat Production", x = NULL,
       y = "Million", caption = myCaption) 
ggsave("wheat_canada_06.png", mp, width = 6, height = 4)

# Prep data
myMeasures <- c("Production", "Area Seeded")
myCrops <- c("Wheat, spring", "Wheat, winter",
             "Wheat, winter seeded in fall", "Wheat, winter remaining")
xx <- agData_STATCAN_Crops2 %>% 
  filter(Area == "Ontario", Item %in% myCrops,
         Measurement %in% myMeasures) %>%
  filter(!(Item == "Wheat, winter remaining" & Measurement == "Area Seeded")) %>%
  mutate(Item = plyr::mapvalues(Item, myCrops[3:4], rep(myCrops[2],2)),
         Measurement = plyr::mapvalues(Measurement, myMeasures,
                          c("Production (Tonnes)", "Area Seeded (Hectares)")))
# Plot
mp <- ggplot(xx, aes(x = Year, y = Value / 1000000, color = Measurement)) +
  geom_line(size = 1, alpha = 0.7) +
  facet_grid(Item ~ ., scales = "free_y") +
  scale_color_manual(name = NULL, values = c("darkgoldenrod2", "darkgreen")) +
  scale_x_continuous(breaks = seq(1910, 2020, 10), expand = c(0.02,0)) +
  theme_agData(legend.position = "bottom") +
  labs(title = "Ontario Wheat Production", x = NULL,
       y = "Million", caption = myCaption) 
ggsave("wheat_canada_07.png", mp, width = 6, height = 4)