Non-financial transactions

Data - Eurostat

Author

François Geerolf

Info

source dataset Title .html .rData
eurostat nasa_10_nf_tr Non-financial transactions 2026-01-10 2026-01-07
eurostat nasq_10_nf_tr Non-financial transactions 2026-01-10 2026-01-07

Data on europe

Code 
load_data("europe.RData")
europe %>%
  arrange(-(dataset == "nasa_10_nf_tr")) %>%
  source_dataset_file_updates()
source dataset Title .html .rData
eurostat nasa_10_nf_tr Non-financial transactions 2026-01-10 2026-01-07
eurostat bop_gdp6_q Main Balance of Payments and International Investment Position items as share of GDP (BPM6) 2026-01-11 2026-01-07
eurostat nama_10_a10 Gross value added and income by A*10 industry breakdowns 2026-01-09 2026-01-07
eurostat nama_10_a10_e Employment by A*10 industry breakdowns 2026-01-09 2026-01-09
eurostat nama_10_gdp GDP and main components (output, expenditure and income) 2026-01-09 2026-01-09
eurostat nama_10_lp_ulc Labour productivity and unit labour costs 2026-01-09 2026-01-07
eurostat namq_10_a10 Gross value added and income A*10 industry breakdowns 2026-01-10 2026-01-09
eurostat namq_10_a10_e Employment A*10 industry breakdowns 2025-05-24 2026-01-07
eurostat namq_10_gdp GDP and main components (output, expenditure and income) 2025-10-27 2026-01-07
eurostat namq_10_lp_ulc Labour productivity and unit labour costs 2026-01-10 2026-01-07
eurostat namq_10_pc Main GDP aggregates per capita 2026-01-10 2026-01-09
eurostat nasq_10_nf_tr Non-financial transactions 2026-01-10 2026-01-07
eurostat tipsii40 Net international investment position - quarterly data, % of GDP 2026-01-10 2026-01-09

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
2026-01-16

Last

Code 
nasa_10_nf_tr %>%
  group_by(time) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(time)) %>%
  head(1) %>%
  print_table_conditional()
time Nobs
2024 57419

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 1061735
CP_MEUR Current prices, million euro 1031856
PPS_EU27_2020_HAB Purchasing power standard (PPS, EU27 from 2020), per inhabitant 1944

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 331218
S14_S15 Households; non-profit institutions serving households 271780
S13 General government 257067
S12 Financial corporations 228346
S11 Non-financial corporations 223657
S2 Rest of the world 218052
S14 Households 216120
S15 Non-profit institutions serving households 185960
S128_S129 Insurance corporations and Pension Funds 44734
S121_S122_S123 Monetary financial institutions 44598
S124_TO_S127 Other financial institutions (Financial corporations other than MFIs, insurance corporations and pension funds) 39354
S1N Not Sectorised 18769
S11001 Public non-financial corporations 12266
S12001 Public financial corporations 3614

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 1095391
RECV Received 1000144

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 42497 Germany 3682340.0 0.0115408
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 1186015.4 0.0016442
AT 1567 Austria 406231.5 0.0038574
LU 891 Luxembourg 73039.5 0.0121989
NO 590 Norway 4323931.0 0.0001364
CH 524 Switzerland 768279.4 0.0006820
CY 409 Cyprus 25679.9 0.0159269
DK 403 Denmark 2553260.5 0.0001578
SK 394 Slovakia 101891.6 0.0038669
LT 183 Lithuania 56709.1 0.0032270
SI 180 Slovenia 52032.4 0.0034594
LV 142 Latvia 32283.8 0.0043985
CZ 139 Czechia 6307755.0 0.0000220
MT 104 Malta 16680.2 0.0062349
EE 96 Estonia 31453.3 0.0030521
HU 87 Hungary 55560466.0 0.0000016
FI 0 Finland 248764.0 0.0000000
IS 0 Iceland 3331536.5 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 46474 France 2653997.2 0.0175109
DE 44093 Germany 3989390.0 0.0110526
BE 12032 Belgium 561309.1 0.0214356
ES 6848 Spain 1375863.0 0.0049772
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 207008.7 0.0186224
RO 2146 Romania 1384597.8 0.0015499
AT 1526 Austria 449382.2 0.0033958
LU 947 Luxembourg 76731.2 0.0123418
NO 628 Norway 5732905.0 0.0001095
CH 609 Switzerland 819703.7 0.0007430
SK 401 Slovakia 109959.8 0.0036468
CY 398 Cyprus 29645.4 0.0134254
DK 397 Denmark 2831269.6 0.0001402
LT 215 Lithuania 67081.1 0.0032051
CZ 196 Czechia 7049872.0 0.0000278
SI 173 Slovenia 56881.6 0.0030414
LV 167 Latvia 36088.7 0.0046275
EE 107 Estonia 36300.9 0.0029476
HU 104 Hungary 65950424.0 0.0000016
MT 103 Malta 17985.1 0.0057270
FI 0 Finland 266135.0 0.0000000
IS 0 Iceland 3945587.5 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))