Code
%>%
sts_copr_m left_join(nace_r2, by = "nace_r2") %>%
group_by(nace_r2, Nace_r2) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
Data - Eurostat
%>%
sts_copr_m left_join(nace_r2, by = "nace_r2") %>%
group_by(nace_r2, Nace_r2) %>%
summarise(Nobs = n()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
sts_copr_m left_join(s_adj, by = "s_adj") %>%
group_by(s_adj, S_adj) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
s_adj | S_adj | Nobs |
---|---|---|
SCA | Seasonally and calendar adjusted data | 130199 |
CA | Calendar adjusted data, not seasonally adjusted data | 128557 |
NSA | Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) | 67972 |
%>%
sts_copr_m left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
unit | Unit | Nobs |
---|---|---|
I21 | Index, 2021=100 | 93333 |
I15 | Index, 2015=100 | 91335 |
PCH_PRE | Percentage change on previous period | 49351 |
PCH_SM | Percentage change compared to same period in previous year | 47469 |
I10 | Index, 2010=100 | 45240 |
%>%
sts_copr_m left_join(indic_bt, by = "indic_bt") %>%
group_by(indic_bt, Indic_bt) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
if (is_html_output()) print_table(.) else .} {
indic_bt | Indic_bt | Nobs |
---|---|---|
PRD | Production (volume) | 326728 |
%>%
sts_copr_m left_join(geo, by = "geo") %>%
group_by(geo, Geo) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
%>%
sts_copr_m group_by(time) %>%
summarise(Nobs = n()) %>%
arrange(desc(time)) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F) else .} {
%>%
sts_copr_m filter(nace_r2 == "F",
== "I15",
unit %in% c("FR", "DE", "IT"),
geo == "SCA") %>%
s_adj select(geo, time, values) %>%
group_by(geo) %>%
mutate(values = 100*values/values[time == "1997M01"]) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
%>%
month_to_date ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
scale_x_date(breaks = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
geom_image(data = . %>%
filter(date == as.Date("2007-01-01")) %>%
mutate(date = as.Date("2007-01-01"),
image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
aes(x = date, y = values, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
%>%
sts_copr_m filter(nace_r2 == "F",
== "I15",
unit == "SCA",
s_adj %in% c("2019M11", "2020M02", "2020M03", "2020M04", "2020M05", "2020M08", "2020M11"),
time !(geo %in% c("IE", "EU28"))) %>%
select(geo, time, values) %>%
group_by(geo) %>%
mutate(values = 100*values/values[time == "2019M11"]) %>%
left_join(geo, by = "geo") %>%
spread(time, values) %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(Geo)),
Flag = paste0('<img src="../../bib/flags/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
arrange(`2020M04`) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
%>%
sts_copr_m filter(nace_r2 == "F",
== "I15",
unit %in% c("FR", "DE", "IT"),
geo == "SCA") %>%
s_adj select(geo, time, values) %>%
group_by(geo) %>%
mutate(values = 100*values/values[time == "2018M01"]) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
%>%
month_to_date filter(date >= as.Date("2018-01-01")) %>%
ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
scale_x_date(breaks = "3 months",
labels = date_format("%b %y")) +
geom_image(data = . %>%
filter(date == as.Date("2020-08-01")) %>%
mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
aes(x = date, y = values, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
%>%
sts_copr_m filter(nace_r2 == "F",
== "I15",
unit %in% c("FR", "DE", "IT"),
geo == "SCA") %>%
s_adj select(geo, time, values) %>%
group_by(geo) %>%
mutate(values = 100*values/values[time == "2019M09"]) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
%>%
month_to_date filter(date >= as.Date("2019-09-01")) %>%
ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#0055a4", "#000000", "#008c45")) +
scale_x_date(breaks = "2 months",
labels = date_format("%b %y")) +
geom_image(data = . %>%
filter(date == as.Date("2020-08-01")) %>%
mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
aes(x = date, y = values, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
%>%
sts_copr_m filter(nace_r2 == "F",
== "I15",
unit %in% c("FR", "DE", "IT", "ES"),
geo == "SCA") %>%
s_adj select(geo, time, values) %>%
group_by(geo) %>%
mutate(values = 100*values/values[time == "2020M02"]) %>%
left_join(geo, by = "geo") %>%
mutate(Geo = ifelse(geo == "DE", "Germany", Geo)) %>%
%>%
month_to_date filter(date >= as.Date("2020-02-01")) %>%
ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
scale_x_date(breaks = "1 month",
labels = date_format("%b %y")) +
geom_image(data = . %>%
filter(date == as.Date("2020-08-01")) %>%
mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
aes(x = date, y = values, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
%>%
sts_copr_m filter(nace_r2 == "F",
== "I15",
unit %in% c("FR", "DE", "IT", "ES"),
geo == "SCA") %>%
s_adj select(geo, time, values) %>%
group_by(geo) %>%
mutate(values = 100*values/values[time == "2020M02"]) %>%
left_join(geo, by = "geo") %>%
%>%
month_to_date filter(date >= as.Date("2020-02-01")) %>%
group_by(Geo) %>%
arrange(date) %>%
mutate(values = values-100,
values = cumsum(values)) %>%
ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#0055a4", "#000000", "#008c45", "#C60B1E")) +
scale_x_date(breaks = "1 month",
labels = date_format("%b %y")) +
geom_image(data = . %>%
filter(date == as.Date("2020-06-01")) %>%
mutate(image = paste0("../../icon/flag/", str_to_lower(Geo), ".png")),
aes(x = date, y = values, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_continuous(breaks = seq(-300, 300, 10))