Non-financial transactions

Data - Eurostat

Author

François Geerolf

Info

source dataset .html .RData
eurostat nasa_10_nf_tr 2025-08-27 2025-08-24
eurostat nasq_10_nf_tr 2025-08-27 2025-08-24

Data on europe

Code 
load_data("europe.RData")
europe %>%
  arrange(-(dataset == "nasa_10_nf_tr")) %>%
  source_dataset_file_updates()
source dataset .html .RData
eurostat bop_gdp6_q 2025-08-27 2025-08-24
eurostat nama_10_a10 2025-08-27 2025-08-24
eurostat nama_10_a10_e 2025-08-27 2025-08-24
eurostat nama_10_gdp 2025-08-27 2025-08-24
eurostat nama_10_lp_ulc 2025-08-27 2025-08-24
eurostat namq_10_a10 2025-08-27 2025-08-24
eurostat namq_10_a10_e 2025-05-24 2025-08-24
eurostat namq_10_gdp 2025-08-27 2025-08-24
eurostat namq_10_lp_ulc 2025-08-27 2025-08-24
eurostat namq_10_pc 2025-08-27 2025-08-24
eurostat nasa_10_nf_tr 2025-08-27 2025-08-24
eurostat nasq_10_nf_tr 2025-08-27 2025-08-24
eurostat tipsii40 2025-08-27 2025-08-24

Info

  • Sector Accounts Dedicated Webpage. html

  • Sector accounts. html

  • html

Code 
include_graphics("https://ec.europa.eu/eurostat/statistics-explained/images/e/e1/Overall_change_in_profit_share_of_non-financial_corporations%2C_2011–2021_%28percentage_points%29_NA2022_II.png")

LAST_COMPILE

LAST_COMPILE
2025-08-27

Last

Code 
nasa_10_nf_tr %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024 22366

unit

Code 
nasa_10_nf_tr %>%
  left_join(unit, by = "unit") %>%
  group_by(unit, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
unit Unit Nobs
CP_MNAC Current prices, million units of national currency 1068351
CP_MEUR Current prices, million euro 1015593
PPS_EU27_2020_HAB Purchasing power standard (PPS, EU27 from 2020), per inhabitant 1942

sector

Code 
nasa_10_nf_tr %>%
  left_join(sector, by = "sector") %>%
  group_by(sector, Sector) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
sector Sector Nobs
S1 Total economy 331099
S14_S15 Households; non-profit institutions serving households 274484
S13 General government 264061
S12 Financial corporations 226267
S11 Non-financial corporations 221363
S2 Rest of the world 213963
S14 Households 213081
S15 Non-profit institutions serving households 180716
S128_S129 Insurance corporations and Pension Funds 44404
S121_S122_S123 Monetary financial institutions 43900
S124_TO_S127 Other financial institutions (Financial corporations other than MFIs, insurance corporations and pension funds) 37921
S1N Not Sectorised 18853
S11001 Public non-financial corporations 12214
S12001 Public financial corporations 3560

direct

Code 
nasa_10_nf_tr %>%
  left_join(direct, by = "direct") %>%
  group_by(direct, Direct) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
direct Direct Nobs
PAID Paid 1091940
RECV Received 993946

na_item

Code 
nasa_10_nf_tr %>%
  left_join(na_item, by = "na_item") %>%
  group_by(na_item, Na_item) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

geo

Code 
nasa_10_nf_tr %>%
  left_join(geo, by = "geo") %>%
  group_by(geo, Geo) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Operating surplus and mixed income, gross

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT"),
         # B2A3G: Operating surplus and mixed income, gross
         na_item == "B2A3G",
         # PAID: Paid
         direct == "PAID",
         # CP_MNAC: Current prices, million units of national currency
         unit == "CP_MNAC",
         # S1: Total economy
         sector == "S1") %>%
  year_to_date %>%
  ggplot + geom_line(aes(x = date, y = values/1000, color = geo, linetype = geo)) +
  scale_color_manual(values = viridis(4)[1:3]) +
  theme_minimal()  +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%y")) +
  theme(legend.position = c(0.2, 0.85),
        legend.title = element_blank()) +
  xlab("") + ylab("") +
  scale_y_log10(breaks = seq(0, 1000, 100),
                labels = dollar_format(suffix = " Bn€", prefix = "", accuracy = 1))

France

Imputed social contributions

All

Code 
nasa_10_nf_tr %>%
  filter(na_item == "D612",
         geo == "IT") %>%
  arrange(-values) %>%
  left_join(geo, by = "geo") %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values_gdp = values/gdp) %>%
  select_if(~ n_distinct(.) > 1) %>%
  print_table_conditional

2022

Code 
nasa_10_nf_tr %>%
  filter(na_item == "D612",
         time == "2021",
         sector == "S13",
         direct == "RECV",
         unit == "CP_MEUR") %>%
  arrange(-values) %>%
  left_join(geo, by = "geo") %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values_gdp = values/gdp) %>%
  select_if(~ n_distinct(.) > 1) %>%
  print_table_conditional
geo values Geo gdp values_gdp
FR 44866 France 2508102.3 0.0178884
DE 42401 Germany 3682340.0 0.0115147
BE 11000 Belgium 506047.2 0.0217371
ES 6932 Spain 1235474.0 0.0056108
PL 4939 Poland 2661518.0 0.0018557
PT 4863 Portugal 216493.7 0.0224625
IT 4665 Italy 1842507.4 0.0025319
NL 4525 Netherlands 891550.0 0.0050754
EL 3856 Greece 184574.6 0.0208913
IE 3697 Ireland 448445.1 0.0082440
RO 1950 Romania 1192284.8 0.0016355
AT 1567 Austria 406232.1 0.0038574
LU 891 Luxembourg 73039.5 0.0121989
NO 590 Norway 4323931.0 0.0001364
CH 524 Switzerland 745067.0 0.0007033
CY 409 Cyprus 25679.9 0.0159269
DK 403 Denmark 2553260.5 0.0001578
SK 394 Slovakia 101933.5 0.0038653
LT 183 Lithuania 56679.7 0.0032287
SI 180 Slovenia 52022.6 0.0034600
LV 142 Latvia 32283.8 0.0043985
CZ 139 Czechia 6307755.0 0.0000220
MT 104 Malta 16677.3 0.0062360
EE 96 Estonia 31456.2 0.0030519
HU 87 Hungary 55560466.0 0.0000016
FI 0 Finland 248764.0 0.0000000
SE 0 Sweden 5417760.0 0.0000000

2022

Code 
nasa_10_nf_tr %>%
  filter(na_item == "D612",
         time == "2022",
         sector == "S13",
         direct == "RECV",
         unit == "CP_MEUR") %>%
  arrange(-values) %>%
  left_join(geo, by = "geo") %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values_gdp = values/gdp) %>%
  select_if(~ n_distinct(.) > 1) %>%
  print_table_conditional
geo values Geo gdp values_gdp
FR 46775 France 2653997.2 0.0176244
DE 43969 Germany 3989390.0 0.0110215
BE 11998 Belgium 563710.5 0.0212840
ES 6848 Spain 1373629.0 0.0049853
PL 5366 Poland 3100850.0 0.0017305
NL 5220 Netherlands 993820.0 0.0052525
PT 4900 Portugal 243957.1 0.0200855
IT 4261 Italy 1998072.6 0.0021326
IE 4053 Ireland 520718.4 0.0077835
EL 3855 Greece 207854.2 0.0185467
RO 2146 Romania 1389450.0 0.0015445
AT 1526 Austria 448007.4 0.0034062
LU 947 Luxembourg 76731.2 0.0123418
NO 628 Norway 5732905.0 0.0001095
CH 609 Switzerland 791087.2 0.0007698
SK 401 Slovakia 110046.4 0.0036439
CY 398 Cyprus 29377.2 0.0135479
DK 397 Denmark 2831269.6 0.0001402
LT 215 Lithuania 67455.5 0.0031873
CZ 196 Czechia 7049872.0 0.0000278
SI 173 Slovenia 56908.8 0.0030400
LV 167 Latvia 36099.7 0.0046261
EE 107 Estonia 36442.8 0.0029361
HU 104 Hungary 66149434.0 0.0000016
MT 103 Malta 18273.0 0.0056367
FI 0 Finland 266135.0 0.0000000
SE 0 Sweden 5816415.0 0.0000000

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "D612",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("1995-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_4flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, .2),
                labels = percent_format(a = .1))

France, Germany, Italy, Spain, Europe

B6G_R_HAB

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G_R_HAB",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5))

1999-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G_R_HAB",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 500, 5))

Code 
  #geom_label(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

1999- (LAbels)

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G_R_HAB",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(10, 500, 5)) +
  geom_label(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G_R_HAB",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(10, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

2008-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G_R_HAB",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("2008-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(10, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

B6G

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5))

1999-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

2008-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("2008-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

B6G/POP

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5))

1999-

B6G/POP - labels

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

B6G/POP

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5))

Code 
  #geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

D11/POP

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "D11",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

B7G_R_HAB

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B7G_R_HAB",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(10, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

D41/POP

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "D41",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

D4/POP

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "D4",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("2000-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

2008-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(POP, by = c("geo", "time")) %>%
  mutate(values = values/POP) %>%
  year_to_date %>%
  filter(date >= as.Date("2008-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

B6N

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6N",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  #filter(date >= as.Date("1995-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

1995-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6N",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1995-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

1999-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B6N",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  year_to_date %>%
  filter(date >= as.Date("1999-01-01")) %>%
  group_by(geo) %>%
  arrange(date) %>%
  mutate(values = 100*values/values[1]) %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1995, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(100, 500, 5)) +
  geom_label_repel(data = . %>% filter(date == max(date)), aes(x = date, y = values, label = round(values, 1), color = color))

Saving Rate (B9)

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B9",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 10), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 1),
                labels = percent_format(a = 1))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B9",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 100, 1),
                labels = percent_format(a = 1))

2015-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B9",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

Saving Rate (B8G)

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B8G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 10), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B8G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 2), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

2015-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B8G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

Operating surplus and mixed income, gross - B2A3G, S14_S15

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B2A3G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 10), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B2A3G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

2015-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B2A3G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S14_S15") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

Operating surplus and mixed income, gross - B2A3G, S11

All

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B2A3G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S11") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  na.omit %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 10), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

2000-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B2A3G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S11") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2000-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 5), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))

2015-

Code 
nasa_10_nf_tr %>%
  filter(geo %in% c("FR", "DE", "IT", "ES", "EA20"),
         na_item == "B2A3G",
         direct == "PAID",
         unit == "CP_MNAC",
         sector == "S11") %>%
  select(geo, time, values, sector) %>%
  left_join(gdp, by = c("geo", "time")) %>%
  mutate(values = values/gdp) %>%
  year_to_date %>%
  left_join(geo, by = "geo") %>%
  mutate(Geo = ifelse(geo == "EA20", "Europe", Geo)) %>%
  left_join(colors, by = c("Geo" = "country")) %>%
  filter(date >= as.Date("2015-01-01")) %>%
  ggplot + theme_minimal() + xlab("") + ylab("") +
  geom_line(aes(x = date, y = values, color = color)) +
  scale_color_identity() + add_5flags +
  scale_x_date(breaks = as.Date(paste0(seq(1940, 2100, 1), "-01-01")),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                labels = percent_format(a = 1))