Drop columns not needed from RF_items_and_packages

- the units per case are now hard coded in the script
- the unit cost is in ResourceFile_costing.xlsx

Author: sakshimohan

resources/healthsystem/consumables/ResourceFile_Consumables_Items_and_Packages.csv

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4106c2e3ae068d40b115857885b673bec3e1114be5183c0a4ae0366560e2a5c9
-size 249391
+oid sha256:596a1bc8d570f341da180fea6db1836c181f6a2a984a9c7f9b4990b78df8e689
+size 215244

src/scripts/data_file_processing/healthsystem/consumables/processing_data_from_one_health/generate_consumables_item_codes_and_packages.py

@@ -19,22 +19,20 @@
 import numpy as np
 import pandas as pd
 
-# Set local Dropbox source
-path_to_dropbox = Path(  # <-- point to the TLO dropbox locally
-   # '/Users/tbh03/Dropbox (SPH Imperial College)/Thanzi la Onse Theme 1 SHARE'
-    '/Users/sm2511/Dropbox/Thanzi La Onse')
+# Set local shared folder source
+path_to_share = Path(  # <-- point to the shared folder
+    '/Users/sm2511/Library/CloudStorage/OneDrive-SharedLibraries-ImperialCollegeLondon/TLOModel - WP - Documents/'
+)
 
 resourcefilepath = Path("./resources")
 path_for_new_resourcefiles = resourcefilepath / "healthsystem/consumables"
 
 
 # EHP Consumables list
-path_to_files_in_the_tlo_dropbox = path_to_dropbox / "05 - Resources/Module-healthsystem/consumables raw files/"
-
-workingfile_ehp_consumables = path_to_dropbox / \
+workingfile_ehp_consumables = path_to_share / \
               "05 - Resources/Module-healthsystem/From Matthias Arnold/ORIGINAL_Intervention input.xlsx"
 
-workingfile_one_health = path_to_dropbox / \
+workingfile_one_health = path_to_share / \
                          "07 - Data/OneHealth projection files/OneHealth commodities.xlsx"
 
 
@@ -157,7 +155,8 @@
 
 wb = wb.merge(intv_codes, on='Intervention_Pkg', how='left', indicator=True)
 assert (wb['_merge'] == 'both').all()
-wb = wb.drop(columns='_merge')
+wb = wb.drop(columns=['_merge','Expected_Units_Per_Case',
+                'Unit_Cost'])
 
 # Assign a unique code for each individual consumable item
 unique_items = pd.unique(wb['Items'])
@@ -172,9 +171,7 @@
          'Intervention_Pkg',
          'Intervention_Pkg_Code',
          'Items',
-         'Item_Code',
-         'Expected_Units_Per_Case',
-         'Unit_Cost']]
+         'Item_Code']]
 
 assert not pd.isnull(wb).any().any()
 
@@ -215,7 +212,7 @@
 only_in_oh['Intervention_Pkg'] = 'Misc'
 only_in_oh['Intervention_Pkg_Code'] = -99
 only_in_oh['Item_Code'] = np.arange(1000, 1000 + len(only_in_oh))
-only_in_oh['Expected_Units_Per_Case'] = 1.0
+only_in_oh = only_in_oh.drop(columns = 'Unit_Cost')
 
 assert set(only_in_oh.columns) == set(wb.columns)
 
@@ -249,19 +246,14 @@ def add_record(df: pd.DataFrame, record: Dict):
     assert set(df.columns) == set(record.keys())
     return pd.concat([df, pd.DataFrame.from_records([record])], ignore_index=True)
 
-
-
 cons = add_record(
     cons,
     {
         'Intervention_Cat': "Added by JC",
         'Intervention_Pkg': "Misc",
         'Intervention_Pkg_Code': -99,
         'Items': "Forceps, obstetric",
-        'Item_Code': 2669,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-        }
+        'Item_Code': 2669}
 )
 
 cons = add_record(
@@ -271,10 +263,7 @@ def add_record(df: pd.DataFrame, record: Dict):
         'Intervention_Pkg': "Misc",
         'Intervention_Pkg_Code': -99,
         'Items': "Vacuum, obstetric",
-        'Item_Code': 2670,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-    },
+        'Item_Code': 2670},
 )
 
 cons = add_record(
@@ -284,10 +273,7 @@ def add_record(df: pd.DataFrame, record: Dict):
         'Intervention_Pkg': "Misc",
         'Intervention_Pkg_Code': -99,
         'Items': "First-line ART regimen: adult",
-        'Item_Code': 2671,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-    },
+        'Item_Code': 2671},
 )
 
 cons = add_record(
@@ -297,10 +283,7 @@ def add_record(df: pd.DataFrame, record: Dict):
         'Intervention_Pkg': "Misc",
         'Intervention_Pkg_Code': -99,
         'Items': "First line ART regimen: older child",
-        'Item_Code': 2672,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-    },
+        'Item_Code': 2672},
 )
 
 cons = add_record(
@@ -310,10 +293,7 @@ def add_record(df: pd.DataFrame, record: Dict):
         'Intervention_Pkg': "Misc",
         'Intervention_Pkg_Code': -99,
         'Items': "First line ART regimen: young child",
-        'Item_Code': 2673,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-    },
+        'Item_Code': 2673},
 )
 
 cons = add_record(
@@ -323,10 +303,7 @@ def add_record(df: pd.DataFrame, record: Dict):
         'Intervention_Pkg': "Misc",
         'Intervention_Pkg_Code': -99,
         'Items': "Pre-exposure prophlaxis for HIV",
-        'Item_Code': 2674,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-    },
+        'Item_Code': 2674},
 )
 
 cons = add_record(
@@ -336,10 +313,7 @@ def add_record(df: pd.DataFrame, record: Dict):
         'Intervention_Pkg': "Isoniazid preventative therapy for HIV+ no TB",
         'Intervention_Pkg_Code': 82,
         'Items': "Isoniazid/Rifapentine",
-        'Item_Code': 2678,
-        'Expected_Units_Per_Case': 1.0,
-        'Unit_Cost': 1.0
-    },
+        'Item_Code': 2678},
 )
 
 cons = add_record(
@@ -349,9 +323,7 @@ def add_record(df: pd.DataFrame, record: Dict):
     'Intervention_Pkg': "Misc",
     'Intervention_Pkg_Code': -99,
     'Items': "Cystoscope",
-    'Item_Code': 285,
-    'Expected_Units_Per_Case': 1.0,
-    'Unit_Cost': np.nan},
+    'Item_Code': 285},
 )
 
 cons = add_record(
@@ -360,9 +332,7 @@ def add_record(df: pd.DataFrame, record: Dict):
     'Intervention_Pkg': "Misc",
     'Intervention_Pkg_Code': -99,
     'Items': "Endoscope",
-    'Item_Code': 280,
-    'Expected_Units_Per_Case': 1.0,
-    'Unit_Cost': np.nan},
+    'Item_Code': 280},
 )
 
 cons = add_record(
@@ -371,9 +341,7 @@ def add_record(df: pd.DataFrame, record: Dict):
     'Intervention_Pkg': "Misc",
     'Intervention_Pkg_Code': -99,
     'Items': "Prostate specific antigen test",
-    'Item_Code': 281,
-    'Expected_Units_Per_Case': 1.0,
-    'Unit_Cost': np.nan},
+    'Item_Code': 281},
 )