Industry (sector data)
Data - ec
Info
Data on industry
source | dataset | .html | .RData |
---|---|---|---|
2024-09-08 | 2023-10-01 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-06-24 | 2024-09-14 | ||
2024-09-15 | 2024-09-14 | ||
2024-09-15 | 2024-09-14 | ||
2024-06-24 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-04-16 | 2024-05-12 | ||
2024-04-16 | 2023-09-09 | ||
2024-04-16 | 2023-11-22 | ||
2024-05-12 | 2024-05-03 | ||
2024-09-11 | 2023-10-04 | ||
2024-09-11 | 2024-04-30 | ||
2024-01-06 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-01-06 | 2024-09-14 | ||
2024-01-06 | 2024-09-14 | ||
2024-01-06 | 2024-09-14 | ||
2024-01-06 | 2024-09-14 | ||
2024-01-06 | 2024-09-14 |
Données sur l’industrie
source | dataset | .html | .RData |
---|---|---|---|
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-06-07 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2024-09-08 | ||
2024-09-14 | 2024-09-14 | ||
2024-09-14 | 2021-08-01 | ||
2024-09-14 | 2024-09-14 | ||
2024-04-16 | 2024-05-12 | ||
2024-09-11 | 2024-04-16 |
LAST_COMPILE
LAST_COMPILE |
---|
2024-09-15 |
Last
Code
%>%
INDUSTRY group_by(period) %>%
summarise(Nobs = n()) %>%
arrange(desc(period)) %>%
head(2) %>%
print_table_conditional()
period | Nobs |
---|---|
2023-05-31 | 528 |
2023-04-30 | 528 |
sector
Code
%>%
INDUSTRY group_by(sector, Sector) %>%
summarise(Nobs = n()) %>%
print_table_conditional
sector | Sector | Nobs |
---|---|---|
TOT | TOTAL Manufacturing | 300243 |
question
Code
%>%
INDUSTRY group_by(question, Question) %>%
summarise(Nobs = n()) %>%
print_table_conditional
question | Question | Nobs |
---|---|---|
1 | Production trend observed in recent months | 25246 |
10 | Duration of production assured by current order-book levels | 7403 |
11 | New orders in recent months | 7417 |
12 | Export expectations for the months ahead | 7672 |
13 | Current level of capacity utilization | 8100 |
14 | Competitive position domestic market | 6292 |
15 | Competitive position inside EU | 6132 |
16 | Competitive position outside EU | 6098 |
2 | Assessment of order-book levels | 25234 |
3 | Assessment of export order-book levels | 24828 |
4 | Assessment of stocks of finished products | 25078 |
5 | Production expectations for the months ahead | 25414 |
6 | Selling price expectations for the months ahead | 24765 |
7 | Employment expectations for the months ahead | 24650 |
8 | Factors limiting the production | 43077 |
9 | Assessment of current production capacity | 7939 |
COF | Confidence Indicator (Q2 - Q4 + Q5) / 3 | 24898 |
answers
Code
%>%
INDUSTRY group_by(answers, Answers) %>%
summarise(Nobs = n()) %>%
print_table_conditional
answers | Answers | Nobs |
---|---|---|
B | Balance not seasonally adjusted (n.s.a) | 120837 |
BS | Balance seasonally adjusted (s.a) | 120826 |
F1 | None (% n.s.a - quarterly question 8) | 3714 |
F1S | None (% s.a - quarterly question 8) | 3739 |
F2 | Demand (% n.s.a - quarterly question 8) | 3738 |
F2S | Demand (% s.a - quarterly question 8) | 3739 |
F3 | Labour (% n.s.a - quarterly question 8) | 3736 |
F3S | Labour (% s.a - quarterly question 8) | 3739 |
F4 | Equipment (% n.s.a - quarterly question 8) | 3737 |
F4S | Equipment (% s.a - quarterly question 8) | 3739 |
F5 | Other (% n.s.a - quarterly question 8) | 3603 |
F5S | Other (% s.a - quarterly question 8) | 3562 |
F6 | Financial (% n.s.a - quarterly question 8) | 2938 |
F6S | Financial (% s.a - quarterly question 8) | 3093 |
QM | months (n.s.a - quarterly question 10) | 3701 |
QMS | months (s.a - quarterly question 10) | 3702 |
QP | % (n.s.a - quarterly question 13) | 4049 |
QPS | % (s.a - quarterly question 13) | 4051 |
country
Code
%>%
INDUSTRY group_by(country, Country) %>%
summarise(Nobs = n()) %>%
mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Country))),
Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) %>%
select(Flag, everything()) %>%
if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .} {
freq
Code
%>%
INDUSTRY group_by(freq, Frequency) %>%
summarise(Nobs = n()) %>%
print_table_conditional
freq | Frequency | Nobs |
---|---|---|
M | Monthly | 200113 |
Q | Quarterly | 100130 |
Germany
Competitive positions
NSA
Code
%>%
INDUSTRY filter(country == "DE",
%in% c("14", "15", "16"),
question == "B") %>%
answers + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
ggplot geom_line(aes(x = period, y = value, color = Question)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.8, 0.1),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-60, 60, 2))
SA
Code
%>%
INDUSTRY filter(country == "DE",
%in% c("14", "15", "16"),
question == "BS") %>%
answers + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
ggplot geom_line(aes(x = period, y = value, color = Question)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.8, 0.1),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-60, 60, 2))
Export Expectations, New Orders, Producion Trend
Code
%>%
INDUSTRY filter(country == "DE",
%in% c("12", "11", "1"),
question == "BS") %>%
answers + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
ggplot geom_line(aes(x = period, y = value, color = Question)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.15),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-60, 60, 5))
France
Competitive positions
NSA
Code
%>%
INDUSTRY filter(country == "FR",
%in% c("14", "15", "16"),
question == "B") %>%
answers + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
ggplot geom_line(aes(x = period, y = value, color = Question)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.8, 0.1),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-60, 60, 2))
SA
Code
%>%
INDUSTRY filter(country == "FR",
%in% c("14", "15", "16"),
question == "BS") %>%
answers + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
ggplot geom_line(aes(x = period, y = value, color = Question)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.8, 0.1),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-60, 60, 2))
Export Expectations, New Orders, Producion Trend
Code
%>%
INDUSTRY filter(country == "FR",
%in% c("12", "11", "1"),
question == "BS") %>%
answers + theme_minimal() + xlab("") + ylab("Balance not seasonally adjusted (s.a)") +
ggplot geom_line(aes(x = period, y = value, color = Question)) +
scale_x_date(breaks = as.Date(paste0(seq(1960, 2025, 5), "-01-01")),
labels = date_format("%Y")) +
theme(legend.position = c(0.25, 0.15),
legend.title = element_blank()) +
scale_y_continuous(breaks = seq(-60, 60, 5))