fastR: Import COP19 FAST Tool Budgets

#FAST sheet "4 Cross-Cutting-E" headers have too many issues to import automatically -> define

#header list to apply to df
cross_headers <- c("fundingagency",
                  "mechanismname",
                  "primepartner",
                  "mechanismid",
                  "programarea",
                  "beneficiary",
                  "intervention_total_drop",
                  "notes_drop",
                  "initiative1",
                  "bilat_total_drop",
                  "bilat_new",
                  "bilat_agyw",
                  "bilat_condom_procurement",
                  "bilat_condom_programming",
                  "bilat_construction",
                  "bilat_economic_strengthening",
                  "bilat_education",
                  "bilat_food_and_nutrition_crossodities",
                  "bilat_food_and_nutrition_policy_tools_and_service_delivery",
                  "bilat_gender_gbv",
                  "bilat_gender_gender_equality",
                  "bilat_human_resources_for_health",
                  "bilat_key_populations_fsw",
                  "bilat_key_populations_msm_and_tg",
                  "bilat_motor_vehicles_leased",
                  "bilat_motor_vehicles_purchased",
                  "bilat_renovation",
                  "bilat_water",
                  "bilat_val_drop",
                  "initiative2",
                  "init2_total_drop",
                  "init2_new",
                  "init2_agyw",
                  "init2_condom_procurement",
                  "init2_condom_programming",
                  "init2_construction",
                  "init2_economic_strengthening",
                  "init2_education",
                  "init2_food_and_nutrition_crossodities",
                  "init2_food_and_nutrition_policy_tools_and_service_delivery",
                  "init2_gender_gbv",
                  "init2_gender_gender_equality",
                  "init2_human_resources_for_health",
                  "init2_key_populations_fsw",
                  "init2_key_populations_msm_and_tg",
                  "init2_motor_vehicles_leased",
                  "init2_motor_vehicles_purchased",
                  "init2_renovation",
                  "init2_water",
                  "init2_val_drop",
                  "initiative3",
                  "init3_total_drop",
                  "init3_new",
                  "init3_agyw",
                  "init3_condom_procurement",
                  "init3_condom_programming",
                  "init3_construction",
                  "init3_economic_strengthening",
                  "init3_education",
                  "init3_food_and_nutrition_crossodities",
                  "init3_food_and_nutrition_policy_tools_and_service_delivery",
                  "init3_gender_gbv",
                  "init3_gender_gender_equality",
                  "init3_human_resources_for_health",
                  "init3_key_populations_fsw",
                  "init3_key_populations_msm_and_tg",
                  "init3_motor_vehicles_leased",
                  "init3_motor_vehicles_purchased",
                  "init3_renovation",
                  "init3_water",
                  "init3_val_drop")
#save
  save(cross_headers, file = "data/cross_headers.rda")

rm(cross_headers)