Revert switch to condo unit value iasworld upload (#33)

* Revert switch to condo unit value iasworld upload

* Correct output format

pipeline/07-export.R

@@ -483,6 +483,8 @@ upload_data_prepped <- assessment_pin %>%
       select(meta_year, meta_pin, meta_card_num, meta_lline_num),
     by = c("meta_year", "meta_pin")
   ) %>%
+  mutate(meta_pin10 = str_sub(meta_pin, 1, 10)) %>%
+  group_by(meta_pin10, meta_tieback_proration_rate) %>%
   mutate(
     # For PINs missing an individual building value, fill with the average of
     # PINs with the same proration rate in the building. This is super rare,
@@ -492,16 +494,32 @@ upload_data_prepped <- assessment_pin %>%
       is.na(pred_pin_final_fmv_bldg),
       mean(pred_pin_final_fmv_bldg, na.rm = TRUE),
       pred_pin_final_fmv_bldg
+    )
+  ) %>%
+  group_by(meta_pin10) %>%
+  mutate(
+    # Sum the building value of each PIN to the building total value
+    pred_pin10_final_fmv_bldg = sum(pred_pin_final_fmv_bldg, na.rm = TRUE),
+
+    # Hotfix for adjusting the total building value such that bldg_total *
+    # proration_rate = unit_value. Only applies to buildings where rates don't
+    # sum to 100%
+    pred_pin10_final_fmv_bldg = round(
+      pred_pin10_final_fmv_bldg * (1 / sum(
+        meta_tieback_proration_rate,
+        na.rm = TRUE
+      ))
     ),
     # For any missing LLINE values, simply fill with 1
     meta_lline_num = replace_na(meta_lline_num, 1)
   ) %>%
+  ungroup() %>%
   select(
     township_code = meta_township_code,
     PARID = meta_pin,
     CARD = meta_card_num,
     LLINE = meta_lline_num,
-    MV = pred_pin_final_fmv_bldg
+    MV = pred_pin10_final_fmv_bldg
   ) %>%
   arrange(township_code, PARID)