Fix detection by region and add more codes from the north region

Author: anapaulagomes

bcb/sgs/regional_economy.py

@@ -2,7 +2,7 @@
 import pandas as pd
 
 NON_PERFORMING_LOANS_BY_REGION_PF = {
-    "N": "",
+    "N": "15888",
     "NE": "",
     "CO": "",
     "SE": "",
@@ -30,25 +30,25 @@
     "RJ": "",
     "RN": "",
     "RS": "",
-    "RO": "",
-    "RR": "",
+    "RO": "15882",
+    "RR": "15883",
     "SC": "",
     "SP": "",
     "SE": "",
-    "TO": "",
+    "TO": "15887",
 }
 NON_PERFORMING_LOANS_BY_REGION_PJ = {
-    "N": "",
+    "N": "15920",
     "NE": "",
     "CO": "",
     "SE": "",
     "S": "",
 }
 NON_PERFORMING_LOANS_BY_STATE_PJ = {
-    "AC": "15861",
+    "AC": "15893",
     "AL": "",
-    "AP": "15863",
-    "AM": "15864",
+    "AP": "15895",
+    "AM": "15896",
     "BA": "15865",
     "CE": "",
     "DF": "",
@@ -58,33 +58,33 @@
     "MT": "",
     "MS": "",
     "MG": "",
-    "PA": "15874",
+    "PA": "15906",
     "PB": "",
     "PR": "",
     "PE": "",
     "PI": "",
     "RJ": "",
     "RN": "",
     "RS": "",
-    "RO": "",
-    "RR": "",
+    "RO": "15914",
+    "RR": "15915",
     "SC": "",
     "SP": "",
     "SE": "",
-    "TO": ""
+    "TO": "15919"
 }
 NON_PERFORMING_LOANS_BY_REGION_TOTAL = {
-    "N": "",
+    "N": "15952",
     "NE": "",
     "CO": "",
     "SE": "",
     "S": "",
 }
 NON_PERFORMING_LOANS_BY_STATE_TOTAL = {
-    "AC": "15861",
+    "AC": "15925",
     "AL": "",
-    "AP": "15863",
-    "AM": "15864",
+    "AP": "15927",
+    "AM": "15928",
     "BA": "15865",
     "CE": "",
     "DF": "",
@@ -94,56 +94,55 @@
     "MT": "",
     "MS": "",
     "MG": "",
-    "PA": "15874",
+    "PA": "15938",
     "PB": "",
     "PR": "",
     "PE": "",
     "PI": "",
     "RJ": "",
     "RN": "",
     "RS": "",
-    "RO": "",
-    "RR": "",
+    "RO": "15946",
+    "RR": "15947",
     "SC": "",
     "SP": "",
     "SE": "",
-    "TO": ""
+    "TO": "15951"
 }
 
 
 def get_non_performing_loans_codes(states_or_region, mode="total"):
     """SGS da Inadimplência das operações de crédito.
 
     Pode ser total, pessoas físicas (PF) ou jurídicas (PJ)."""
-    non_performing_loans_by_state = NON_PERFORMING_LOANS_BY_STATE_TOTAL
-    non_performing_loans_by_region = NON_PERFORMING_LOANS_BY_REGION_TOTAL
-
     is_state = False
     is_region = False
     states_or_region = [states_or_region] if isinstance(states_or_region, str) else states_or_region
     states_or_region = [location.upper() for location in states_or_region]
-    if any(location in list(non_performing_loans_by_state.keys()) for location in states_or_region):
+    if any(location in list(NON_PERFORMING_LOANS_BY_STATE_TOTAL.keys()) for location in states_or_region):
         is_state = True
-    elif any(location in list(non_performing_loans_by_region.keys()) for location in states_or_region):
+    elif any(location in list(NON_PERFORMING_LOANS_BY_REGION_TOTAL.keys()) for location in states_or_region):
         is_region = True
 
     if not is_state and not is_region:
         raise Exception(f"Not a valid state or region: {states_or_region}")
 
     codes = []
+    non_performing_loans_by_location = NON_PERFORMING_LOANS_BY_STATE_TOTAL
     if is_state:
         if mode.upper() == "PF":
-            non_performing_loans_by_state = NON_PERFORMING_LOANS_BY_STATE_PF
+            non_performing_loans_by_location = NON_PERFORMING_LOANS_BY_STATE_PF
         elif mode.upper() == "PJ":
-            non_performing_loans_by_state = NON_PERFORMING_LOANS_BY_STATE_PJ
+            non_performing_loans_by_location = NON_PERFORMING_LOANS_BY_STATE_PJ
     elif is_region:
+        non_performing_loans_by_location = NON_PERFORMING_LOANS_BY_REGION_TOTAL
         if mode.upper() == "PF":
-            non_performing_loans_by_state = NON_PERFORMING_LOANS_BY_REGION_PF
+            non_performing_loans_by_location = NON_PERFORMING_LOANS_BY_REGION_PF
         elif mode.upper() == "PJ":
-            non_performing_loans_by_state = NON_PERFORMING_LOANS_BY_REGION_PJ
+            non_performing_loans_by_location = NON_PERFORMING_LOANS_BY_REGION_PJ
 
     for location in states_or_region:
-        codes.append(non_performing_loans_by_state.get(location))
+        codes.append(non_performing_loans_by_location[location])
     return codes
 
 

tests/sgs/test_regional_economy.py

@@ -5,8 +5,9 @@
 
 class TestGetNonPerformingLoansCodes:
     @pytest.mark.parametrize("states,expected_codes", [
-        (["ba", "pa"], ["15865", "15874"]),
+        (["ba", "pa"], ["15865", "15938"]),
         (["BA"], ["15865"]),
+        ("N", ["15952"]),
     ])
     def test_get_non_performing_loans_codes_by_state_total(self, states, expected_codes):
         assert get_non_performing_loans_codes(states) == expected_codes
@@ -16,10 +17,10 @@ class TestGetNonPerformingLoans:
     @pytest.mark.parametrize("states,expected_columns", [
         (["BA"], ["15865"]),
         (["ba"], ["15865"]),
-        #(["ba", "se", "al"], ["1"])
+        ("N", ["15888"]),
     ])
-    def test_get_series_by_states(self, states, expected_columns):
-        series = get_non_performing_loans(states, last=10)
+    def test_get_series_by_states_pf(self, states, expected_columns):
+        series = get_non_performing_loans(states, last=10, mode="pf")
         assert isinstance(series, pd.DataFrame)
         assert series.columns == expected_columns
         assert len(series) == 10