Construction - monthly data - index (2015 = 100) (NACE Rev. 2) - ei_isbu_m
Data - Eurostat
François Geerolf
indic
English
ei_isbu_m %>%
left_join(indic, by = "indic") %>%
group_by(indic, Indic) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| indic | Indic | Nobs |
|---|---|---|
| IS-IP | Production index | 59009 |
| IS-PEI | Building permits index - New residential buildings | 31549 |
| IS-WSI | Gross wages and salaries index | 5156 |
| IS-HWI | Hours worked index | 4530 |
| IS-EPI | Number of persons employed index | 3812 |
| IS-IPI | Cost index (input price index) - New residential buildings | 2946 |
French
load_data("eurostat/indic_fr.RData")
ei_isbu_m %>%
left_join(indic, by = "indic") %>%
group_by(indic, Indic) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| indic | Indic | Nobs |
|---|---|---|
| IS-IP | Indice de production | 59009 |
| IS-PEI | Indice des permis de construire - Nouveaux bâtiments résidentiels | 31549 |
| IS-WSI | Indice des salaires et traitements bruts | 5156 |
| IS-HWI | Indice des heures travaillées | 4530 |
| IS-EPI | Indice du nombre de personnes occupées | 3812 |
| IS-IPI | Indice du coût (indice des prix imputé) - Nouveaux bâtiments résidentiels | 2946 |
nace_r2
load_data("eurostat/indic.RData")
ei_isbu_m %>%
left_join(nace_r2, by = "nace_r2") %>%
group_by(nace_r2, Nace_r2) %>%
summarise(Nobs = n()) %>%
print_table_conditional| nace_r2 | Nace_r2 | Nobs |
|---|---|---|
| B-D_F | Mining and quarrying; manufacturing; electricity, gas, steam and air conditioning supply; construction | 15088 |
| F | Construction | 28993 |
| F_CC1 | Buildings | 24820 |
| F_CC11 | Residential buildings | 10411 |
| F_CC11_X_CC113 | Residential buildings, except residences for communities | 13501 |
| F_CC2 | Civil engineering works | 14189 |
s_adj
ei_isbu_m %>%
left_join(s_adj, by = "s_adj") %>%
group_by(s_adj, S_adj) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| s_adj | S_adj | Nobs |
|---|---|---|
| SCA | Seasonally and calendar adjusted data | 54383 |
| NSA | Unadjusted data (i.e. neither seasonally adjusted nor calendar adjusted data) | 52619 |
unit
ei_isbu_m %>%
left_join(unit, by = "unit") %>%
group_by(unit, Unit) %>%
summarise(Nobs = n()) %>%
arrange(-Nobs) %>%
print_table_conditional| unit | Unit | Nobs |
|---|---|---|
| I2015 | Index, 2015=100 | 107002 |
geo
ei_isbu_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 .}Covid Crisis (January-September 2020)
Table
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
time %in% c("2019M09", "2020M03", "2020M04", "2020M09"),
s_adj == "SCA") %>%
select(geo, time, values) %>%
left_join(geo, by = "geo") %>%
spread(time, values) %>%
arrange(`2020M04`) %>%
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 .}France, Germany, Italy, Europe
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
geo %in% c("FR", "DE", "IT", "EU27_2020"),
s_adj == "SCA") %>%
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),
Geo = ifelse(geo == "EU27_2020", "Europe", Geo)) %>%
month_to_date %>%
filter(date >= as.Date("2020-01-01"),
date <= as.Date("2020-09-01")) %>%
ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#003399", "#ED2939", "#000000", "#008c45")) +
scale_x_date(breaks = "1 month",
labels = date_format("%b %y")) +
geom_image(data = tibble(date = rep(as.Date("2020-04-01"), 4),
value = c(37, 102, 27, 82),
image = c("../../icon/flag/vsmall/france.png",
"../../icon/flag/vsmall/germany.png",
"../../icon/flag/vsmall/italy.png",
"../../icon/flag/vsmall/europe.png")),
aes(x = date, y = value, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
Covid Crisis (January 2020 - May 2021)
Table
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
time %in% c("2019M09", "2020M03", "2020M09", "2021M03"),
s_adj == "SCA") %>%
select(geo, time, values) %>%
left_join(geo, by = "geo") %>%
spread(time, values) %>%
arrange(`2021M03`) %>%
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 .}France, Germany, Italy, Europe
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
geo %in% c("FR", "DE", "IT", "EU27_2020"),
s_adj == "SCA") %>%
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),
Geo = ifelse(geo == "EU27_2020", "Europe", Geo)) %>%
month_to_date %>%
filter(date >= as.Date("2020-01-01")) %>%
ggplot() + ylab("Construction Production") + xlab("") + theme_minimal() +
geom_line(aes(x = date, y = values, color = Geo)) +
scale_color_manual(values = c("#003399", "#ED2939", "#000000", "#008c45")) +
scale_x_date(breaks = "1 month",
labels = date_format("%b %y")) +
geom_image(data = tibble(date = rep(as.Date("2020-04-01"), 4),
value = c(37, 102, 27, 82),
image = c("../../icon/flag/vsmall/france.png",
"../../icon/flag/vsmall/germany.png",
"../../icon/flag/vsmall/italy.png",
"../../icon/flag/vsmall/europe.png")),
aes(x = date, y = value, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
France, Germany, Italy
All
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
geo %in% c("FR", "DE", "IT"),
s_adj == "SCA") %>%
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 = tibble(date = rep(as.Date("2022-01-01"), 3),
value = c(110, 140, 85),
image = c("../../icon/flag/vsmall/france.png",
"../../icon/flag/vsmall/germany.png",
"../../icon/flag/vsmall/italy.png")),
aes(x = date, y = value, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
1990-2020
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
geo %in% c("FR", "DE", "IT"),
s_adj == "SCA") %>%
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 = tibble(date = rep(as.Date("2022-01-01"), 3),
value = c(116, 109, 100),
image = c("../../icon/flag/vsmall/france.png",
"../../icon/flag/vsmall/germany.png",
"../../icon/flag/vsmall/italy.png")),
aes(x = date, y = value, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))
2010-2020
ei_isbu_m %>%
filter(nace_r2 == "F",
indic == "IS-IP",
geo %in% c("FR", "DE", "IT"),
s_adj == "SCA") %>%
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 %>%
filter(date >= as.Date("2010-01-01")) %>%
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 = seq(1920, 2025, 2) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%y")) +
geom_image(data = tibble(date = rep(as.Date("2022-01-01"), 3),
value = c(116, 109, 100),
image = c("../../icon/flag/vsmall/france.png",
"../../icon/flag/vsmall/germany.png",
"../../icon/flag/vsmall/italy.png")),
aes(x = date, y = value, image = image), asp = 1.5) +
theme(legend.position = "none") +
scale_y_log10(breaks = seq(-60, 300, 10))