fix(docs): Address PR review feedback

- Add missing print() in migration-flows.md (no output was rendered)
- Revert get_estimates/get_flows exec blocks in spatial.md to static output
- Fix Washington state population value in spatial.md (7614893 -> 7705281)
- Remove unused income API call in margins-of-error.md
- Add cache_table=True to ZCTA query in geography.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: chekos

docs/guides/geography.md

@@ -126,7 +126,7 @@ optionally which county) you want tracts for.
     print(f"{len(metros)} metro/micro areas")
 
     # All ZCTAs nationwide
-    zctas = get_acs("zcta", variables="B01003_001", year=2022)
+    zctas = get_acs("zcta", variables="B01003_001", year=2022, cache_table=True)
     print(f"{len(zctas)} ZCTAs")
     ```
 

docs/guides/margins-of-error.md

@@ -118,14 +118,6 @@ significance(
 ```python exec="on" source="tabbed-left" session="moe"
 from pypums import significance
 
-income = get_acs(
-    "place",
-    variables="B19013_001",
-    state="CA",
-    year=2022,
-    output="wide",
-)
-
 # Suppose:
 # City A: estimate = $85,000, MOE = $4,000
 # City B: estimate = $78,000, MOE = $5,000

docs/guides/migration-flows.md

@@ -64,7 +64,7 @@ ca_flows = get_flows(
     year=2019,
 )
 
-ca_flows.head()
+print(ca_flows.head())
 ```
 
 In tidy output (the default), the DataFrame has `variable`, `estimate`, and `moe`

docs/guides/spatial.md

@@ -61,7 +61,7 @@ shapefiles are cached locally so subsequent calls are fast.
 
 === "get_estimates()"
 
-    ```python exec="on" source="tabbed-left" session="spatial"
+    ```python
     import pypums
 
     gdf = pypums.get_estimates(
@@ -73,9 +73,18 @@ shapefiles are cached locally so subsequent calls are fast.
     print(gdf.head())
     ```
 
+    ```
+      GEONAME  POP_2023  ... geometry
+    0  Alabama   5074296  ...  POLYGON ((...))
+    1   Alaska    733583  ...  MULTIPOLYGON ((...))
+    2  Arizona   7359197  ...  POLYGON ((...))
+    3  Arkansas  3045637  ...  POLYGON ((...))
+    4  California 39029342 ... MULTIPOLYGON ((...))
+    ```
+
 === "get_flows()"
 
-    ```python exec="on" source="tabbed-left" session="spatial"
+    ```python
     import pypums
 
     gdf = pypums.get_flows(
@@ -87,6 +96,15 @@ shapefiles are cached locally so subsequent calls are fast.
     print(gdf.head())
     ```
 
+    ```
+      GEOID          NAME  ... geometry
+    0  36001  Albany County  ...  POLYGON ((...))
+    1  36003  Allegany County  ...  POLYGON ((...))
+    2  36005  Bronx County  ...  POLYGON ((...))
+    3  36007  Broome County  ...  POLYGON ((...))
+    4  36009  Cattaraugus County  ...  POLYGON ((...))
+    ```
+
 !!! example "Interactive preview — 2020 Census population by state"
 
     Every `geometry=True` call returns a GeoDataFrame you can map directly.
@@ -156,7 +174,7 @@ shapefiles are cached locally so subsequent calls are fast.
                 {"id": 49, "value": 3271616, "name": "Utah"},
                 {"id": 50, "value": 643077, "name": "Vermont"},
                 {"id": 51, "value": 8631393, "name": "Virginia"},
-                {"id": 53, "value": 7614893, "name": "Washington"},
+                {"id": 53, "value": 7705281, "name": "Washington"},
                 {"id": 54, "value": 1793716, "name": "West Virginia"},
                 {"id": 55, "value": 5893718, "name": "Wisconsin"},
                 {"id": 56, "value": 576851, "name": "Wyoming"}