| source | dataset | Title | .html | .rData |
|---|---|---|---|---|
| oecd | SNA_TABLE3 | Population and employment by main activity | 2026-08-13 | 2026-08-02 |
Population and employment by main activity
Data - OECD
Info
Données sur l’industrie
| source | dataset | Title | .html | .rData |
|---|---|---|---|---|
| oecd | SNA_TABLE3 | Population and employment by main activity | 2026-08-13 | 2026-08-02 |
| eurostat | mar_mg_am_cvh | Country level - volume (in TEUs) of containers handled in main ports, by loading status - mar_mg_am_cvh | 2026-08-13 | 2026-08-13 |
| eurostat | namq_10_a10 | Gross value added and income A*10 industry breakdowns | 2026-08-13 | 2026-08-12 |
| insee | CNA-2014-EMPLOI | Emploi intérieur, durée effective travaillée et productivité horaire | 2026-08-13 | 2026-08-12 |
| insee | CNT-2014-CB | Comptes des branches | 2026-08-13 | 2026-08-12 |
| insee | CNT-2014-OPERATIONS | Opérations sur biens et services | 2026-08-13 | 2026-08-12 |
| insee | ENQ-CONJ-ACT-IND | Conjoncture dans l’industrie | 2026-08-13 | 2026-08-12 |
| insee | ICA-2015-IND-CONS | Indices de chiffre d'affaires dans l'industrie et la construction | 2026-08-13 | 2026-08-13 |
| insee | IPI-2021 | Indice de la production industrielle | 2026-08-13 | 2026-08-13 |
| insee | IPPI-2015 | Indices de prix de production et d'importation dans l'industrie | 2026-08-13 | 2026-08-13 |
| insee | TCRED-EMPLOI-SALARIE-TRIM | Estimations d'emploi salarié par secteur d'activité et par département | 2026-08-13 | 2026-08-13 |
| insee | t_5407 | 5.407 – Solde extérieur de biens et de services par produit à prix courants (En milliards d'euros) - t_5407 | 2026-08-13 | 2026-08-02 |
| oecd | ALFS_EMP | Employment by activities and status (ALFS) | 2026-08-13 | 2026-08-02 |
LAST_COMPILE
| LAST_COMPILE |
|---|
| 2026-08-14 |
Last
| TIME_PERIOD | Nobs |
|---|---|
| 2024 | 2673 |
Layout
- OECD Website. html

TRANSACT
Code
SNA_TABLE3 |>
left_join(SNA_TABLE3_var$TRANSACT, by = "TRANSACT") |>
group_by(TRANSACT, Transact) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
print_table_conditional()| TRANSACT | Transact | Nobs |
|---|---|---|
| NA | NA | 13202 |
| EEM | Employees, domestic concept | 576 |
| ESE | Self-employed, domestic concept | 571 |
| ETO | Total employment, domestic concept | 571 |
| EEMVB_E | Industry, including energy (ISIC rev4) | 559 |
| EEMVC | of which: Manufacturing (ISIC rev4) | 559 |
| ETOVB_E | Industry, including energy (ISIC rev4) | 554 |
| EEMVA | Agriculture, forestry and fishing (ISIC rev4) | 551 |
| ESEVB_E | Industry, including energy (ISIC rev4) | 549 |
| ESEVC | of which: Manufacturing (ISIC rev4) | 549 |
| ETOVC | of which: Manufacturing (ISIC rev4) | 549 |
| ESEVA | Agriculture, forestry and fishing (ISIC rev4) | 541 |
| ETOVA | Agriculture, forestry and fishing (ISIC rev4) | 541 |
MEASURE
Code
SNA_TABLE3 |>
left_join(SNA_TABLE3_var$MEASURE, by = "MEASURE") |>
group_by(MEASURE, Measure) |>
summarise(Nobs = n()) |>
print_table_conditional()| MEASURE | Measure | Nobs |
|---|---|---|
| HRS | Hours | 7429 |
| PER | Persons | 8725 |
| NA | NA | 3718 |
LOCATION
Code
SNA_TABLE3 |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
group_by(LOCATION, Location) |>
summarise(Nobs = n()) |>
arrange(-Nobs) |>
mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Location))),
Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
select(Flag, everything()) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}PER - Persons (Thousands)
France, Germany, United States
Code
SNA_TABLE3 |>
filter(TIME_PERIOD == "2018",
LOCATION %in% c("FRA", "DEU", "USA"),
MEASURE == "PER") |>
left_join(SNA_TABLE3_var$TRANSACT, by = "TRANSACT") |>
select(LOCATION, TRANSACT, Transact, obsValue) |>
mutate(obsValue = round(obsValue)) |>
spread(LOCATION, obsValue) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Spain, Italy, United Kingdom
Code
SNA_TABLE3 |>
filter(TIME_PERIOD == "2018",
LOCATION %in% c("ITA", "ESP", "GBR"),
MEASURE == "PER") |>
left_join(SNA_TABLE3_var$TRANSACT, by = "TRANSACT") |>
select(LOCATION, TRANSACT, Transact, obsValue) |>
mutate(obsValue = round(obsValue)) |>
spread(LOCATION, obsValue) %>%
{if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}Population
France, Germany, United States, United Kingdom, Europe
1990-
Code
SNA_TABLE3 |>
filter(TRANSACT %in% c("POPNC"),
MEASURE == "PER",
LOCATION %in% c("FRA", "DEU", "GBR", "USA", "EA19")) |>
year_to_date() |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
mutate(Location = ifelse(LOCATION == "EA19", "Europe", Location)) |>
select(Location, date, TRANSACT, obsValue) |>
left_join(colors, by = c("Location" = "country")) |>
group_by(Location) |>
filter(date >= as.Date("1990-01-01")) |>
mutate(obsValue = 100*obsValue/obsValue[1]) |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_5flags +
scale_x_date(breaks = seq(1920, 2100, 10) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 300, 10)) +
ylab("Employment") + xlab("")1995-
Code
SNA_TABLE3 |>
filter(TRANSACT %in% c("POPNC"),
MEASURE == "PER",
LOCATION %in% c("FRA", "DEU", "GBR", "USA", "EA19")) |>
year_to_date() |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
mutate(Location = ifelse(LOCATION == "EA19", "Europe", Location)) |>
select(Location, date, TRANSACT, obsValue) |>
left_join(colors, by = c("Location" = "country")) |>
group_by(Location) |>
filter(date >= as.Date("1995-01-01")) |>
mutate(obsValue = 100*obsValue/obsValue[1]) |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_5flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 300, 5)) +
ylab("Employment") + xlab("")2008-
Code
SNA_TABLE3 |>
filter(TRANSACT %in% c("POPNC"),
MEASURE == "PER",
LOCATION %in% c("FRA", "DEU", "GBR", "USA", "EA19")) |>
year_to_date() |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
mutate(Location = ifelse(LOCATION == "EA19", "Europe", Location)) |>
select(Location, date, TRANSACT, obsValue) |>
left_join(colors, by = c("Location" = "country")) |>
group_by(Location) |>
filter(date >= as.Date("2008-01-01")) |>
mutate(obsValue = 100*obsValue/obsValue[1]) |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_5flags +
scale_x_date(breaks = seq(1920, 2100, 2) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_log10(breaks = seq(100, 300, 1)) +
ylab("Employment") + xlab("")Employment / Population
Number of Persons: PER
All
Code
SNA_TABLE3 |>
filter(TRANSACT %in% c("EEM", "POPNC"),
MEASURE == "PER",
LOCATION %in% c("FRA", "DEU", "ITA")) |>
year_to_date() |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
select(Location, date, TRANSACT, obsValue) |>
spread(TRANSACT, obsValue) |>
group_by(Location) |>
mutate(POPNC_trend = log(POPNC) |> hpfilter(1000000) |> pluck("trend") |> exp(),
obsValue = EEM / POPNC_trend) |>
left_join(colors, by = c("Location" = "country")) |>
na.omit() |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_3flags +
scale_x_date(breaks = seq(1920, 2100, 10) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
labels = scales::percent_format(accuracy = 1)) +
ylab("Employment / Population") + xlab("")1995-
Code
SNA_TABLE3 |>
filter(TRANSACT %in% c("EEM", "POPNC"),
MEASURE == "PER",
LOCATION %in% c("FRA", "DEU", "ITA")) |>
year_to_date() |>
filter(date >= as.Date("1995-01-01")) |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
select(Location, date, TRANSACT, obsValue) |>
spread(TRANSACT, obsValue) |>
group_by(Location) |>
mutate(POPNC_trend = log(POPNC) |> hpfilter(1000000) |> pluck("trend") |> exp(),
obsValue = EEM / POPNC_trend) |>
left_join(colors, by = c("Location" = "country")) |>
na.omit() |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_3flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
labels = scales::percent_format(accuracy = 1)) +
ylab("Employment / Population") + xlab("")Number of Hours: HRS
All
Code
SNA_TABLE3 |>
filter((TRANSACT == "EEM" & MEASURE == "HRS") |
(TRANSACT == "POPNC" & MEASURE == "PER"),
LOCATION %in% c("FRA", "DEU", "ITA")) |>
year_to_date() |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
select(Location, date, TRANSACT, obsValue) |>
spread(TRANSACT, obsValue) |>
group_by(Location) |>
mutate(POPNC_trend = log(POPNC) |> hpfilter(1000000) |> pluck("trend") |> exp(),
obsValue = EEM / POPNC_trend) |>
left_join(colors, by = c("Location" = "country")) |>
na.omit() |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_3flags +
scale_x_date(breaks = seq(1920, 2100, 10) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
labels = scales::percent_format(accuracy = 1)) +
ylab("Employment / Population") + xlab("")1995-
Code
SNA_TABLE3 |>
filter((TRANSACT == "EEM" & MEASURE == "HRS") |
(TRANSACT == "POPNC" & MEASURE == "PER"),
LOCATION %in% c("FRA", "DEU", "ITA")) |>
year_to_date() |>
filter(date >= as.Date("1995-01-01")) |>
left_join(SNA_TABLE3_var$LOCATION, by = "LOCATION") |>
select(Location, date, TRANSACT, obsValue) |>
spread(TRANSACT, obsValue) |>
group_by(Location) |>
mutate(POPNC_trend = log(POPNC) |> hpfilter(1000000) |> pluck("trend") |> exp(),
obsValue = EEM / POPNC_trend) |>
left_join(colors, by = c("Location" = "country")) |>
na.omit() |>
ggplot() + geom_line(aes(x = date, y = obsValue, color = color)) +
scale_color_identity() + theme_minimal() + add_3flags +
scale_x_date(breaks = seq(1920, 2100, 5) |> paste0("-01-01") |> as.Date(),
labels = date_format("%Y")) +
theme(legend.position = c(0.15, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
labels = scales::percent_format(accuracy = 1)) +
ylab("Employment / Population") + xlab("")



















