Consumer Price Index - Monthly - CPIm

Data - statjp

series_code, series_name

CPIm %>%
  group_by(series_code, series_name) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional

adj

CPIm_var$adj %>%
  print_table_conditional

adj	Adjustment
nadj	not adjusted
sadj	seasonally adjusted

Housing, All Items, Real Housing

All

CPIm %>%
  filter(series_code %in% c("001", "281")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Housing` = 100 * `Housing` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

1985-

CPIm %>%
  filter(series_code %in% c("001", "281"),
         period >= as.Date("1985-01-01")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Housing` = 100 * `Housing` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

Housing less imputed, All Items, Real Housing less imputed

All

CPIm %>%
  filter(series_code %in% c("001", "740")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Housing, less imputed rent` = 100 * `Housing, less imputed rent` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

1985-

CPIm %>%
  filter(series_code %in% c("001", "740"),
         period >= as.Date("1985-01-01")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Housing, less imputed rent` = 100 * `Housing, less imputed rent` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

Rents less imputed, All Items, Real Rents less imputed

All

CPIm %>%
  filter(series_code %in% c("001", "741")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Rent, less imputed rent` = 100 * `Rent, less imputed rent` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

1985-

CPIm %>%
  filter(series_code %in% c("001", "741"),
         period >= as.Date("1985-01-01")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Rent, less imputed rent` = 100 * `Rent, less imputed rent` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

Rents, All Items, Real Rents

All

CPIm %>%
  filter(series_code %in% c("001", "282")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Rent` = 100 * `Rent` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

1985-

CPIm %>%
  filter(series_code %in% c("001", "282"),
         period >= as.Date("1985-01-01")) %>%
  select(series_name, period, value) %>%
  spread(series_name, value) %>%
  mutate(`Real Rent` = 100 * `Rent` / `All items`) %>%
  gather(series_name, value, -period) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

Rents

All

CPIm %>%
  filter(series_code %in% c("282", "740", "741")) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

1985-

CPIm %>%
  filter(series_code %in% c("282", "740", "741"),
         period >= as.Date("1985-01-01")) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 5)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.2),
        legend.title = element_blank())

2000-

CPIm %>%
  filter(series_code %in% c("282", "740", "741"),
         period >= as.Date("2000-01-01")) %>%
  ggplot(.) + geom_line(aes(x = period, y = value, color = series_name)) + 
  theme_minimal() + xlab("") + ylab("") +
  scale_x_date(breaks = seq(1960, 2020, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%y")) +
  scale_y_log10(breaks = seq(0, 200, 1)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme(legend.position = c(0.7, 0.8),
        legend.title = element_blank())