Non-financial transactions

Data - Eurostat

Author

François Geerolf

Info

source dataset .html .RData

eurostat

nasa_10_nf_tr

 2024-06-21 2024-06-08

eurostat

nasq_10_nf_tr

 2024-06-20 2024-06-08

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

 2024-06-23 2024-06-08

eurostat

nama_10_a10

 2024-06-23 2024-06-08

eurostat

nama_10_a10_e

 2024-06-23 2024-06-23

eurostat

nama_10_gdp

 2024-06-24 2024-06-18

eurostat

nama_10_lp_ulc

 2024-06-24 2024-06-08

eurostat

namq_10_a10

 2024-06-24 2024-06-23

eurostat

namq_10_a10_e

 2024-06-24 2024-06-08

eurostat

namq_10_gdp

 2024-06-24 2024-06-08

eurostat

namq_10_lp_ulc

 2024-06-24 2024-06-08

eurostat

namq_10_pc

 2024-06-24 2024-06-18

eurostat

nasa_10_nf_tr

 2024-06-21 2024-06-08

eurostat

nasq_10_nf_tr

 2024-06-20 2024-06-08

eurostat

tipsii40

 2024-06-20 2024-06-18

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
2024-06-24

Last

Code 
nasa_10_nf_tr %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2023 15372

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 999712
CP_MEUR Current prices, million euro 952990
PPS_EU27_2020_HAB Purchasing power standard (PPS, EU27 from 2020), per inhabitant 1742

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 317152
S14_S15 Households; non-profit institutions serving households 256837
S13 General government 250147
S11 Non-financial corporations 212708
S12 Financial corporations 212570
S2 Rest of the world 199590
S14 Households 193138
S15 Non-profit institutions serving households 167345
S128_S129 Insurance corporations and Pension Funds 39426
S121_S122_S123 Monetary financial institutions 39156
S124_TO_S127 Other financial institutions (Financial corporations other than MFIs, insurance corporations and pension funds) 33778
S1N Not Sectorised 18325
S11001 Public non-financial corporations 11218
S12001 Public financial corporations 3054

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 1022460
RECV Received 931984

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 44710 France 2502118.0 0.0178689
DE 42265 Germany 3617450.0 0.0116836
BE 10985 Belgium 508061.2 0.0216214
ES 6932 Spain 1222290.0 0.0056713
PL 4939 Poland 2631302.0 0.0018770
PT 4863 Portugal 216053.2 0.0225083
IT 4577 Italy 1821934.6 0.0025122
NL 4073 Netherlands 870587.0 0.0046785
EL 3856 Greece 181500.4 0.0212451
IE 3697 Ireland 434069.7 0.0085171
AT 1567 Austria 405241.4 0.0038668
LU 891 Luxembourg 72360.9 0.0123133
NO 590 Norway 4323931.0 0.0001364
CH 522 Switzerland 743330.2 0.0007022
DK 407 Denmark 2550606.3 0.0001596
SK 344 Slovakia 100244.5 0.0034316
LT 183 Lithuania 56478.1 0.0032402
SI 180 Slovenia 52278.8 0.0034431
CZ 139 Czechia 6108717.0 0.0000228
LV 138 Latvia 33348.9 0.0041381
MT 104 Malta 15331.3 0.0067835
EE 95 Estonia 31169.0 0.0030479
HU 87 Hungary 55204977.0 0.0000016
CY 0 Cyprus 24927.6 0.0000000
FI 0 Finland 250664.0 0.0000000
SE 0 Sweden 5464876.0 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 46569 France 2639092.0 0.0176458
DE 43704 Germany 3876810.0 0.0112732
BE 11986 Belgium 554213.7 0.0216270
ES 6854 Spain 1346377.0 0.0050907
PL 5366 Poland 3074798.0 0.0017452
PT 4907 Portugal 242340.8 0.0202483
NL 4782 Netherlands 958549.0 0.0049888
IT 4054 Italy 1962845.8 0.0020654
IE 4053 Ireland 506282.4 0.0080054
EL 3855 Greece 206620.4 0.0186574
AT 1526 Austria 447217.6 0.0034122
LU 946 Luxembourg 77529.0 0.0122019
CH 630 Switzerland 781460.3 0.0008062
NO 628 Norway 5708190.0 0.0001100
DK 402 Denmark 2831643.9 0.0001420
SK 343 Slovakia 109762.0 0.0031249
LT 215 Lithuania 67436.5 0.0031882
CZ 196 Czechia 6786742.0 0.0000289
SI 173 Slovenia 57037.7 0.0030331
LV 165 Latvia 38386.2 0.0042984
EE 108 Estonia 36011.1 0.0029991
HU 104 Hungary 65951746.0 0.0000016
MT 103 Malta 17439.9 0.0059060
CY 0 Cyprus 27777.0 0.0000000
FI 0 Finland 267687.0 0.0000000
SE 0 Sweden 5865211.0 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_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))

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_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) %>%
  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

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))

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))