Survey of Professional Forecasters - SPF

Data

Author

François Geerolf 


 Currently Loading: FREQ
 Currently Loading: FCT_TOPIC
 Currently Loading: FCT_BREAKDOWN
 Currently Loading: FCT_HORIZON
 Currently Loading: FCT_SOURCE
 Currently Loading: UNIT

FREQ

Code 
SPF %>%
  left_join(FREQ, by = "FREQ") %>%
  group_by(FREQ, Freq) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FREQ Freq Nobs
A Annual 2512899
Q Quarterly 1714275
M Monthly 969306

REF_AREA

Code 
SPF %>%
  group_by(REF_AREA) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
REF_AREA Nobs
U2 5196480

FCT_TOPIC

Code 
SPF %>%
  left_join(FCT_TOPIC, by = "FCT_TOPIC") %>%
  group_by(FCT_TOPIC, Fct_topic) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
FCT_TOPIC Fct_topic Nobs
UNEM Unemployment 1751866
RGDP Real GDP 1354777
HICP Harmonised ICP 1306299
CORE Harmonised ICP excluding energy and food 533254
ASSU Assumptions 250284

FCT_SOURCE

Code 
SPF %>%
  left_join(FCT_SOURCE, by = "FCT_SOURCE") %>%
  group_by(FCT_SOURCE, Fct_source) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

FCT_BREAKDOWN

Code 
SPF %>%
  left_join(FCT_BREAKDOWN, by = "FCT_BREAKDOWN") %>%
  group_by(FCT_BREAKDOWN, Fct_breakdown) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

FCT_HORIZON

Code 
SPF %>%
  left_join(FCT_HORIZON, by = "FCT_HORIZON") %>%
  group_by(FCT_HORIZON, Fct_horizon) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()

SURVEY_FREQ

Code 
SPF %>%
  group_by(SURVEY_FREQ) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
SURVEY_FREQ Nobs
Q 5196480

UNIT

Code 
SPF %>%
  left_join(UNIT, by = "UNIT") %>%
  group_by(UNIT, Unit) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  print_table_conditional()
UNIT Unit Nobs
PC Percent 4718189
PCPA Percent per annum 342854
USD US dollar 133200
PS Persons 2237

SOURCE_AGENCY

Code 
SPF %>%
  group_by(SOURCE_AGENCY) %>%
  summarise(Nobs = n()) %>%
  arrange(-Nobs) %>%
  {if (is_html_output()) print_table(.) else .}
SOURCE_AGENCY Nobs
4F0 5196480