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| haven::read_dta('data/各省历年GDP.dta') |>
dplyr::filter(省份 != "中国",
年份 %in% 2014:2019) |>
full_join(prov) |>
st_sf() |>
select(省份, 年份, 地区生产总值_亿元) -> provdf
bind_rows(
provdf |>
dplyr::filter(年份 == 2014 | is.na(年份)) |>
mutate(年份 = if_else(is.na(年份), 2014, 年份)),
provdf |>
dplyr::filter(年份 == 2015 | is.na(年份)) |>
mutate(年份 = if_else(is.na(年份), 2015, 年份)),
provdf |>
dplyr::filter(年份 == 2016 | is.na(年份)) |>
mutate(年份 = if_else(is.na(年份), 2016, 年份)),
provdf |>
dplyr::filter(年份 == 2017 | is.na(年份)) |>
mutate(年份 = if_else(is.na(年份), 2017, 年份)),
provdf |>
dplyr::filter(年份 == 2018 | is.na(年份)) |>
mutate(年份 = if_else(is.na(年份), 2018, 年份)),
provdf |>
dplyr::filter(年份 == 2019 | is.na(年份)) |>
mutate(年份 = if_else(is.na(年份), 2019, 年份))
) -> provdf2
provdf2 |>
mutate(gdp = case_when(
is.na(地区生产总值_亿元) ~ "无数据",
between(地区生产总值_亿元, 0, 20000) ~ "< 20 千亿",
between(地区生产总值_亿元, 20000, 40000) ~ "20～40千亿",
between(地区生产总值_亿元, 40000, 60000) ~ "40～60千亿",
between(地区生产总值_亿元, 60000, 80000) ~ "60～80千亿",
between(地区生产总值_亿元, 80000, 200000) ~ "> 80千亿",
)) |>
mutate(gdp = factor(gdp,
levels = c("无数据",
"< 20 千亿",
"20～40千亿",
"40～60千亿",
"60～80千亿",
"> 80千亿"))) -> provdf3
ggplot(provdf3) +
geom_sf(aes(fill = gdp),
color = "gray30",
size = 0.2) +
facet_wrap(~年份, nrow = 2) +
labs(title = "2014～2019 年中国各省地区生产总值",
caption = "数据来源：CSMAR 国泰安数据库") +
scico::scale_fill_scico_d(palette = "davos",
name = NULL,
direction = -1) +
scale_x_continuous(expand = c(0.001, 0.001)) +
scale_y_continuous(expand = c(0.001, 0.001)) +
annotation_scale(
width_hint = 0.2,
height = unit(0.15, "cm"),
text_family = cnfont
) +
annotation_north_arrow(
location = "bl", which_north = "false",
pad_y = unit(0.4, "cm"),
pad_x = unit(0.8, "cm"),
width = unit(0.6, "cm"),
height = unit(0.8, "cm"),
style = north_arrow_fancy_orienteering(
text_family = cnfont
)
) +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
strip.text = element_text(family = cnfont,
colour = "gray30",
hjust = 0.5),
legend.position = "bottom",
plot.margin = unit(rep(0.5, 4), "cm"),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
panel.grid.major = element_blank()) +
guides(fill = guide_legend(nrow = 1,
title.position = "top",
title.hjust = 0.5,
label.position = "top"))
|
