fix the description again

Author: ar-puuk

index.html

@@ -1,7 +1,7 @@
 ---
 title: TAZ & Regional Median Income
 subtitle: Calculating Median Income for Transportation Analysis Zones (TAZ)
-description: This notebook replicates the '_Source - TAZ & Regional Median Income - 2022-03-17.xlsb' tab from the 2019-2023 American Community Survey. It calculates the median income for each Traffic Analysis Zone (TAZ) based on household income data and household data.
+description: This notebook replicates the analysis from the '_Source - TAZ & Regional Median Income - 2022-03-17.xlsb' using the updated household and household income data from the 2019-2023 American Community Survey.
 author:
  - name: Pukar Bhandari
    email: [email protected]
@@ -130,7 +130,7 @@ df_CPI = pd.read_excel(
 df_CPI
 ```
 
-### ACS_5YR_County
+### ACS_5YR_HouseholdIncome
 
 #### Set Census Variables
 
@@ -425,47 +425,6 @@ plt.show()
 
 ### BlockSplit_wCOTAZID
 
-```{python}
-
-```
-
-
-## Lookup Tables
-
-### ACS Column ID to Label
-
-```{python}
-lookup_hhinc = pd.DataFrame({
-  "Income Category": [
-    "HH_LT_10K", "HH_10_15K", "HH_15_20K", "HH_20_25K", "HH_25_30K", "HH_30_35K",
-    "HH_35_40K", "HH_40_45K", "HH_45_50K", "HH_50_60K", "HH_60_75K",
-    "HH_75_100K", "HH_100_125K", "HH_125_150K", "HH_150_200K", "HH_GT_200K"
-  ],
-  "Lower Limit": [
-    0, 10000, 15000, 20000, 25000, 30000,
-    35000, 40000, 45000, 50000, 60000,
-    75000, 100000, 125000, 150000, 200000
-  ],
-  "Upper Limit": [
-    9999, 14999, 19999, 24999, 29999, 34999,
-    39999, 44999, 49999, 59999, 74999,
-    99999, 124999, 149999, 199999, np.inf
-  ]
-})
-
-# Compute midpoint and round it
-lookup_hhinc['Midpoint'] = (
-  (lookup_hhinc['Lower Limit'] + lookup_hhinc['Upper Limit']) / 2
-).round()
-
-# Replace infinite midpoint (last category) with 300000
-lookup_hhinc.loc[np.isinf(lookup_hhinc["Upper Limit"]), "Midpoint"] = 300000
-
-lookup_hhinc
-```
-
-### BlockGroupID for TAZ Centroid (Use if No HH in TAZ)
-
 ```{python}
 # Define a function for population weighted interpolation
 def interpolate_pw(from_gdf, to_gdf, weights_gdf, to_id=None, extensive=True,
@@ -656,6 +615,47 @@ def interpolate_pw(from_gdf, to_gdf, weights_gdf, to_id=None, extensive=True,
     return result
 ```
 
+
+## Lookup Tables
+
+### ACS Column ID to Label
+
+```{python}
+lookup_hhinc = pd.DataFrame({
+  "Income Category": [
+    "HH_LT_10K", "HH_10_15K", "HH_15_20K", "HH_20_25K", "HH_25_30K", "HH_30_35K",
+    "HH_35_40K", "HH_40_45K", "HH_45_50K", "HH_50_60K", "HH_60_75K",
+    "HH_75_100K", "HH_100_125K", "HH_125_150K", "HH_150_200K", "HH_GT_200K"
+  ],
+  "Lower Limit": [
+    0, 10000, 15000, 20000, 25000, 30000,
+    35000, 40000, 45000, 50000, 60000,
+    75000, 100000, 125000, 150000, 200000
+  ],
+  "Upper Limit": [
+    9999, 14999, 19999, 24999, 29999, 34999,
+    39999, 44999, 49999, 59999, 74999,
+    99999, 124999, 149999, 199999, np.inf
+  ]
+})
+
+# Compute midpoint and round it
+lookup_hhinc['Midpoint'] = (
+  (lookup_hhinc['Lower Limit'] + lookup_hhinc['Upper Limit']) / 2
+).round()
+
+# Replace infinite midpoint (last category) with 300000
+lookup_hhinc.loc[np.isinf(lookup_hhinc["Upper Limit"]), "Midpoint"] = 300000
+
+lookup_hhinc
+```
+
+### BlockGroupID for TAZ Centroid (Use if No HH in TAZ)
+
+```{python}
+
+```
+
 ## Processing