4148: |
4149- CA SFH (SAAR)
4150- |
4151:
4152- 33
4153- |
4154:
4155- 30
4156- |
4157:
4158-
````
**Assistant**
I’ve confirmed the raw HTML contains the whole dataset. I’m normalizing it to the seven meaningful columns and dropping the spacer rows before I print it.
Background terminal finished with python3 - <<'PY'
import urllib.request
from html.parser import HTMLParser
url = 'https://www.car.org/marketdata/data/ftbhai'
html = urllib.request.urlopen(url).read().decode('utf-8', 'ignore')
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
# rows[0] is title bar, rows[1] header, rows[2] blank. Real data after that.
clean = []
for r in rows[3:]:
if not any(cell.strip() for cell in r):
continue
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\t'.join(row))
PY
Command
```bash
python3 - <<'PY'
import urllib.request
from html.parser import HTMLParser
url = 'https://www.car.org/marketdata/data/ftbhai'
html = urllib.request.urlopen(url).read().decode('utf-8', 'ignore')
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
# rows[0] is title bar, rows[1] header, rows[2] blank. Real data after that.
clean = []
for r in rows[3:]:
if not any(cell.strip() for cell in r):
continue
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\t'.join(row))
PY
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 20000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc "python3 - <<'PY'
import urllib.request
from html.parser import HTMLParser
url = 'https://www.car.org/marketdata/data/ftbhai'
html = urllib.request.urlopen(url).read().decode('utf-8', 'ignore')
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
# rows[0] is title bar, rows[1] header, rows[2] blank. Real data after that.
clean = []
for r in rows[3:]:
if not any(cell.strip() for cell in r):
continue
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\\t'.join(row))
PY"
Chunk ID: 4786bd
Wall time: 0.2313 seconds
Process exited with code 1
Original token count: 343
Output:
Traceback (most recent call last):
File "", line 5, in
File "/opt/homebrew/Cellar/python@3.13/3.13.2/Frameworks/Python.framework/Versions/3.13/lib/python3.13/urllib/request.py", line 189, in urlopen
return opener.open(url, data, timeout)
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/python@3.13/3.13.2/Frameworks/Python.framework/Versions/3.13/lib/python3.13/urllib/request.py", line 495, in open
response = meth(req, response)
File "/opt/homebrew/Cellar/python@3.13/3.13.2/Frameworks/Python.framework/Versions/3.13/lib/python3.13/urllib/request.py", line 604, in http_response
response = self.parent.error(
'http', request, response, code, msg, hdrs)
File "/opt/homebrew/Cellar/python@3.13/3.13.2/Frameworks/Python.framework/Versions/3.13/lib/python3.13/urllib/request.py", line 533, in error
return self._call_chain(*args)
~~~~~~~~~~~~~~~~^^^^^^^
File "/opt/homebrew/Cellar/python@3.13/3.13.2/Frameworks/Python.framework/Versions/3.13/lib/python3.13/urllib/request.py", line 466, in _call_chain
result = func(*args)
File "/opt/homebrew/Cellar/python@3.13/3.13.2/Frameworks/Python.framework/Versions/3.13/lib/python3.13/urllib/request.py", line 613, in http_error_default
raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 403: Forbidden
````
**Assistant**
The site blocks Python’s default user agent. I’m reusing `curl` output instead and parsing that locally.
Background terminal finished with curl -L --silent https://www.car.org/marketdata/data/ftbhai | python3 - <<'PY'
import sys
from html.parser import HTMLParser
html = sys.stdin.read()
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
clean = []
for r in rows[3:]:
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(cell.strip() for cell in row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\t'.join(row))
PY
Command
```bash
curl -L --silent https://www.car.org/marketdata/data/ftbhai | python3 - <<'PY'
import sys
from html.parser import HTMLParser
html = sys.stdin.read()
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
clean = []
for r in rows[3:]:
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(cell.strip() for cell in row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\t'.join(row))
PY
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 20000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc "curl -L --silent https://www.car.org/marketdata/data/ftbhai | python3 - <<'PY'
import sys
from html.parser import HTMLParser
html = sys.stdin.read()
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
clean = []
for r in rows[3:]:
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(cell.strip() for cell in row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\\t'.join(row))
PY"
Chunk ID: e6ed8c
Wall time: 0.2500 seconds
Process exited with code 1
Original token count: 20
Output:
File "", line 3
^
SyntaxError: invalid syntax
````
**Assistant**
I hit the usual heredoc/stdin trap. I’m writing the HTML to a temp file first and parsing from there.
Background terminal finished with tmp=$(mktemp)
curl -L --silent https://www.car.org/marketdata/data/ftbhai > "$tmp"
python3 - "$tmp" <<'PY'
import sys
from html.parser import HTMLParser
path = sys.argv[1]
with open(path, 'r', encoding='utf-8', errors='ignore') as f:
html = f.read()
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
clean = []
for r in rows[3:]:
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(cell.strip() for cell in row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\t'.join(row))
PY
rm -f "$tmp"
Command
```bash
tmp=$(mktemp)
curl -L --silent https://www.car.org/marketdata/data/ftbhai > "$tmp"
python3 - "$tmp" <<'PY'
import sys
from html.parser import HTMLParser
path = sys.argv[1]
with open(path, 'r', encoding='utf-8', errors='ignore') as f:
html = f.read()
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
clean = []
for r in rows[3:]:
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(cell.strip() for cell in row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\t'.join(row))
PY
rm -f "$tmp"
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 20000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc 'tmp=$(mktemp)
curl -L --silent https://www.car.org/marketdata/data/ftbhai > "$tmp"
python3 - "$tmp" <<'"'PY'
import sys
from html.parser import HTMLParser
path = sys.argv[1]
with open(path, 'r', encoding='utf-8', errors='ignore') as f:
html = f.read()
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\\xa0',' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
p = TableParser()
p.feed(frag)
rows = p.rows
clean = []
for r in rows[3:]:
if len(r) < 9:
continue
row = [r[0], r[1], r[2], r[4], r[6], r[7], r[8]]
if not any(cell.strip() for cell in row):
continue
clean.append(row)
print('ROWS', len(clean))
for row in clean:
print('\\t'.join(row))
PY
rm -f \""'$tmp"'
Chunk ID: c12dad
Wall time: 0.3191 seconds
Process exited with code 0
Original token count: 673
Output:
ROWS 65
CA SFH (SAAR) 33 30 29 $738,910 $4,680 $140,400
CA Condo/Townhomes 46 44 41 $552,500 $3,500 $105,000
Los Angeles Metropolitan Area 32 30 29 $705,500 $4,470 $134,100
Inland Empire 45 43 41 $505,750 $3,210 $96,300
S.F. Bay Area 32 30 29 $1,074,320 $6,810 $204,300
US 57 54 54 $352,670 $2,240 $67,200
S.F. Bay Area
Alameda 32 30 28 $1,041,250 $6,600 $198,000
Contra Costa 45 43 41 $731,000 $4,630 $138,900
Marin 31 29 26 $1,298,380 $8,230 $246,900
Napa 32 31 34 $785,400 $4,980 $149,400
San Francisco 28 29 27 $1,530,000 $9,700 $291,000
San Mateo 27 26 25 $1,759,500 $11,150 $334,500
Santa Clara 30 29 27 $1,632,000 $10,340 $310,200
Solano 51 47 48 $493,000 $3,130 $93,900
Sonoma 37 36 35 $697,850 $4,420 $132,600
Southern California
Imperial 43 43 46 $369,750 $2,340 $70,200
Los Angeles 26 24 23 $798,740 $5,060 $151,800
Orange 21 19 18 $1,187,030 $7,520 $225,600
Riverside 44 43 40 $538,540 $3,410 $102,300
San Bernardino 51 49 48 $422,450 $2,680 $80,400
San Diego 30 27 26 $844,900 $5,360 $160,800
Ventura 34 32 29 $792,630 $5,020 $150,600
Central Coast
Monterey 25 21 23 $786,250 $4,980 $149,400
San Luis Obispo 30 27 24 $769,250 $4,880 $146,400
Santa Barbara 19 19 18 $1,062,500 $6,730 $201,900
Santa Cruz 21 21 22 $1,094,380 $6,940 $208,200
Central Valley
Fresno 51 48 48 $365,500 $2,320 $69,600
Glenn 60 56 53 $291,340 $1,850 $55,500
Kern 51 49 47 $337,870 $2,140 $64,200
Kings 57 55 55 $314,500 $1,990 $59,700
Madera 53 50 46 $374,000 $2,370 $71,100
Merced 50 47 43 $357,000 $2,260 $67,800
Placer 53 50 50 $556,750 $3,530 $105,900
Sacramento 51 48 47 $458,150 $2,900 $87,000
San Benito 48 47 42 $637,500 $4,040 $121,200
San Joaquin 51 49 48 $459,000 $2,910 $87,300
Stanislaus 51 48 50 $395,250 $2,510 $75,300
Tulare 54 52 48 $324,280 $2,060 $61,800
Far North
Butte 48 45 46 $374,000 $2,370 $71,100
Lassen 74 69 69 $194,650 $1,230 $36,900
Plumas 58 48 53 $339,580 $2,150 $64,500
Shasta 56 54 53 $314,500 $1,990 $59,700
Siskiyou 58 54 54 $257,130 $1,630 $48,900
Tehama 57 54 54 $273,700 $1,730 $51,900
Trinity 61 51 48 $212,500 $1,350 $40,500
Other Counties in California
Amador 58 55 54 $357,000 $2,260 $67,800
Calaveras 58 53 54 $373,150 $2,370 $71,100
Del Norte 54 52 51 $322,150 $2,040 $61,200
El Dorado 52 48 44 $573,750 $3,640 $109,200
Humboldt 47 42 39 $351,050 $2,230 $66,900
Lake 50 47 55 $282,200 $1,790 $53,700
Mariposa 47 46 39 $374,850 $2,380 $71,400
Mendocino 44 44 39 $418,630 $2,650 $79,500
Mono 22 15 12 $784,550 $4,970 $149,100
Nevada 48 47 47 $467,500 $2,960 $88,800
Sutter 49 46 45 $382,500 $2,420 $72,600
Tuolumne 61 54 55 $323,000 $2,050 $61,500
Yolo 44 42 41 $529,130 $3,350 $100,500
Yuba 49 48 46 $376,340 $2,390 $71,700
````
**Assistant**
Scraped from [CAR’s Housing Affordability Index - First-Time Buyer page](https://www.car.org/marketdata/data/ftbhai). Here’s the table in cleaned form:
| State/Region/County | Q42025 | Q32025 | Q42024 | Median Home Price | Monthly Payment Including Taxes & Insurance | Minimum Qualifying Income |
|---|---:|---:|---:|---:|---:|---:|
| CA SFH (SAAR) | 33 | 30 | 29 | $738,910 | $4,680 | $140,400 |
| CA Condo/Townhomes | 46 | 44 | 41 | $552,500 | $3,500 | $105,000 |
| Los Angeles Metropolitan Area | 32 | 30 | 29 | $705,500 | $4,470 | $134,100 |
| Inland Empire | 45 | 43 | 41 | $505,750 | $3,210 | $96,300 |
| S.F. Bay Area | 32 | 30 | 29 | $1,074,320 | $6,810 | $204,300 |
| US | 57 | 54 | 54 | $352,670 | $2,240 | $67,200 |
| S.F. Bay Area | | | | | | |
| Alameda | 32 | 30 | 28 | $1,041,250 | $6,600 | $198,000 |
| Contra Costa | 45 | 43 | 41 | $731,000 | $4,630 | $138,900 |
| Marin | 31 | 29 | 26 | $1,298,380 | $8,230 | $246,900 |
| Napa | 32 | 31 | 34 | $785,400 | $4,980 | $149,400 |
| San Francisco | 28 | 29 | 27 | $1,530,000 | $9,700 | $291,000 |
| San Mateo | 27 | 26 | 25 | $1,759,500 | $11,150 | $334,500 |
| Santa Clara | 30 | 29 | 27 | $1,632,000 | $10,340 | $310,200 |
| Solano | 51 | 47 | 48 | $493,000 | $3,130 | $93,900 |
| Sonoma | 37 | 36 | 35 | $697,850 | $4,420 | $132,600 |
| Southern California | | | | | | |
| Imperial | 43 | 43 | 46 | $369,750 | $2,340 | $70,200 |
| Los Angeles | 26 | 24 | 23 | $798,740 | $5,060 | $151,800 |
| Orange | 21 | 19 | 18 | $1,187,030 | $7,520 | $225,600 |
| Riverside | 44 | 43 | 40 | $538,540 | $3,410 | $102,300 |
| San Bernardino | 51 | 49 | 48 | $422,450 | $2,680 | $80,400 |
| San Diego | 30 | 27 | 26 | $844,900 | $5,360 | $160,800 |
| Ventura | 34 | 32 | 29 | $792,630 | $5,020 | $150,600 |
| Central Coast | | | | | | |
| Monterey | 25 | 21 | 23 | $786,250 | $4,980 | $149,400 |
| San Luis Obispo | 30 | 27 | 24 | $769,250 | $4,880 | $146,400 |
| Santa Barbara | 19 | 19 | 18 | $1,062,500 | $6,730 | $201,900 |
| Santa Cruz | 21 | 21 | 22 | $1,094,380 | $6,940 | $208,200 |
| Central Valley | | | | | | |
| Fresno | 51 | 48 | 48 | $365,500 | $2,320 | $69,600 |
| Glenn | 60 | 56 | 53 | $291,340 | $1,850 | $55,500 |
| Kern | 51 | 49 | 47 | $337,870 | $2,140 | $64,200 |
| Kings | 57 | 55 | 55 | $314,500 | $1,990 | $59,700 |
| Madera | 53 | 50 | 46 | $374,000 | $2,370 | $71,100 |
| Merced | 50 | 47 | 43 | $357,000 | $2,260 | $67,800 |
| Placer | 53 | 50 | 50 | $556,750 | $3,530 | $105,900 |
| Sacramento | 51 | 48 | 47 | $458,150 | $2,900 | $87,000 |
| San Benito | 48 | 47 | 42 | $637,500 | $4,040 | $121,200 |
| San Joaquin | 51 | 49 | 48 | $459,000 | $2,910 | $87,300 |
| Stanislaus | 51 | 48 | 50 | $395,250 | $2,510 | $75,300 |
| Tulare | 54 | 52 | 48 | $324,280 | $2,060 | $61,800 |
| Far North | | | | | | |
| Butte | 48 | 45 | 46 | $374,000 | $2,370 | $71,100 |
| Lassen | 74 | 69 | 69 | $194,650 | $1,230 | $36,900 |
| Plumas | 58 | 48 | 53 | $339,580 | $2,150 | $64,500 |
| Shasta | 56 | 54 | 53 | $314,500 | $1,990 | $59,700 |
| Siskiyou | 58 | 54 | 54 | $257,130 | $1,630 | $48,900 |
| Tehama | 57 | 54 | 54 | $273,700 | $1,730 | $51,900 |
| Trinity | 61 | 51 | 48 | $212,500 | $1,350 | $40,500 |
| Other Counties in California | | | | | | |
| Amador | 58 | 55 | 54 | $357,000 | $2,260 | $67,800 |
| Calaveras | 58 | 53 | 54 | $373,150 | $2,370 | $71,100 |
| Del Norte | 54 | 52 | 51 | $322,150 | $2,040 | $61,200 |
| El Dorado | 52 | 48 | 44 | $573,750 | $3,640 | $109,200 |
| Humboldt | 47 | 42 | 39 | $351,050 | $2,230 | $66,900 |
| Lake | 50 | 47 | 55 | $282,200 | $1,790 | $53,700 |
| Mariposa | 47 | 46 | 39 | $374,850 | $2,380 | $71,400 |
| Mendocino | 44 | 44 | 39 | $418,630 | $2,650 | $79,500 |
| Mono | 22 | 15 | 12 | $784,550 | $4,970 | $149,100 |
| Nevada | 48 | 47 | 47 | $467,500 | $2,960 | $88,800 |
| Sutter | 49 | 46 | 45 | $382,500 | $2,420 | $72,600 |
| Tuolumne | 61 | 54 | 55 | $323,000 | $2,050 | $61,500 |
| Yolo | 44 | 42 | 41 | $529,130 | $3,350 | $100,500 |
| Yuba | 49 | 48 | 46 | $376,340 | $2,390 | $71,700 |
If you want, I can also convert this to CSV or group it into separate regional tables.
**User**
can you save this table as a csv?
**Assistant**
I’m saving the scraped CAR table as a CSV in your current workspace and then I’ll verify the file contents.
Background terminal finished with python3 - <<'PY'
import csv
import urllib.request
from html.parser import HTMLParser
from pathlib import Path
url = 'https://www.car.org/marketdata/data/ftbhai'
req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
html = urllib.request.urlopen(req).read().decode('utf-8', 'ignore')
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0', ' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
parser = TableParser()
parser.feed(frag)
rows = []
for raw in parser.rows[3:]:
if len(raw) < 9:
continue
row = [raw[0], raw[1], raw[2], raw[4], raw[6], raw[7], raw[8]]
if not any(cell.strip() for cell in row):
continue
rows.append(row)
out_path = Path('/Users/christopherlee/ftbhai.csv')
with out_path.open('w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerow([
'State/Region/County',
'Q42025',
'Q32025',
'Q42024',
'Median Home Price',
'Monthly Payment Including Taxes & Insurance',
'Minimum Qualifying Income',
])
writer.writerows(rows)
print(out_path)
print(len(rows))
PY
Command
```bash
python3 - <<'PY'
import csv
import urllib.request
from html.parser import HTMLParser
from pathlib import Path
url = 'https://www.car.org/marketdata/data/ftbhai'
req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
html = urllib.request.urlopen(req).read().decode('utf-8', 'ignore')
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\xa0', ' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
parser = TableParser()
parser.feed(frag)
rows = []
for raw in parser.rows[3:]:
if len(raw) < 9:
continue
row = [raw[0], raw[1], raw[2], raw[4], raw[6], raw[7], raw[8]]
if not any(cell.strip() for cell in row):
continue
rows.append(row)
out_path = Path('/Users/christopherlee/ftbhai.csv')
with out_path.open('w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerow([
'State/Region/County',
'Q42025',
'Q32025',
'Q42024',
'Median Home Price',
'Monthly Payment Including Taxes & Insurance',
'Minimum Qualifying Income',
])
writer.writerows(rows)
print(out_path)
print(len(rows))
PY
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 4000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc "python3 - <<'PY'
import csv
import urllib.request
from html.parser import HTMLParser
from pathlib import Path
url = 'https://www.car.org/marketdata/data/ftbhai'
req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
html = urllib.request.urlopen(req).read().decode('utf-8', 'ignore')
start = html.find('', start)
frag = html[start:end+8]
class TableParser(HTMLParser):
def __init__(self):
super().__init__()
self.in_tr = False
self.in_cell = False
self.rows = []
self.row = []
self.parts = []
def handle_starttag(self, tag, attrs):
if tag == 'tr':
self.in_tr = True
self.row = []
elif tag in ('td', 'th') and self.in_tr:
self.in_cell = True
self.parts = []
def handle_endtag(self, tag):
if tag in ('td', 'th') and self.in_tr and self.in_cell:
text = ' '.join(''.join(self.parts).replace('\\xa0', ' ').split())
self.row.append(text)
self.in_cell = False
self.parts = []
elif tag == 'tr' and self.in_tr:
if self.row:
self.rows.append(self.row)
self.in_tr = False
def handle_data(self, data):
if self.in_cell:
self.parts.append(data)
parser = TableParser()
parser.feed(frag)
rows = []
for raw in parser.rows[3:]:
if len(raw) < 9:
continue
row = [raw[0], raw[1], raw[2], raw[4], raw[6], raw[7], raw[8]]
if not any(cell.strip() for cell in row):
continue
rows.append(row)
out_path = Path('/Users/christopherlee/ftbhai.csv')
with out_path.open('w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerow([
'State/Region/County',
'Q42025',
'Q32025',
'Q42024',
'Median Home Price',
'Monthly Payment Including Taxes & Insurance',
'Minimum Qualifying Income',
])
writer.writerows(rows)
print(out_path)
print(len(rows))
PY"
Chunk ID: 5dbc34
Wall time: 0.3672 seconds
Process exited with code 0
Original token count: 9
Output:
/Users/christopherlee/ftbhai.csv
65
````
**Assistant**
The CSV is written. I’m checking the first few rows to confirm the headers and formatting are correct.
Background terminal finished with sed -n '1,12p' /Users/christopherlee/ftbhai.csv
Command
```bash
sed -n '1,12p' /Users/christopherlee/ftbhai.csv
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 4000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc "sed -n '1,12p' /Users/christopherlee/ftbhai.csv"
Chunk ID: 80027d
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 173
Output:
State/Region/County,Q42025,Q32025,Q42024,Median Home Price,Monthly Payment Including Taxes & Insurance,Minimum Qualifying Income
CA SFH (SAAR),33,30,29,"$738,910","$4,680","$140,400"
CA Condo/Townhomes,46,44,41,"$552,500","$3,500","$105,000"
Los Angeles Metropolitan Area,32,30,29,"$705,500","$4,470","$134,100"
Inland Empire,45,43,41,"$505,750","$3,210","$96,300"
S.F. Bay Area,32,30,29,"$1,074,320","$6,810","$204,300"
US,57,54,54,"$352,670","$2,240","$67,200"
S.F. Bay Area,,,,,,
Alameda,32,30,28,"$1,041,250","$6,600","$198,000"
Contra Costa,45,43,41,"$731,000","$4,630","$138,900"
Marin,31,29,26,"$1,298,380","$8,230","$246,900"
Napa,32,31,34,"$785,400","$4,980","$149,400"
````
**Assistant**
Saved as [ftbhai.csv](/Users/christopherlee/ftbhai.csv).
It contains 65 data rows plus the header, and I verified the first rows render correctly.
**User**
can you write a python script I can use to repeatedly scrape that same table?
**Assistant**
I’m creating a reusable Python scraper in your home directory that fetches the CAR page, extracts the table, and writes CSV on demand. After that I’ll run it once to verify the output.
Background terminal finished with pwd
Command
```bash
pwd
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 1000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc pwd
Chunk ID: 69ada6
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 6
Output:
/Users/christopherlee
````
Background terminal finished with ls -1 /Users/christopherlee | rg '^scrape_ftbhai\.py$|^ftbhai\.csv$'
Command
```bash
ls -1 /Users/christopherlee | rg '^scrape_ftbhai\.py$|^ftbhai\.csv$'
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 1000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc "ls -1 /Users/christopherlee | rg '"'^scrape_ftbhai'"\\.py"'$|''^ftbhai'"\\.csv"'$'"'"
Chunk ID: 0ec413
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 3
Output:
ftbhai.csv
````
**Assistant**
I’ve confirmed there isn’t an existing scraper file to overwrite. I’m adding a standalone script with a small CLI so you can rerun it whenever the CAR table updates.
Applied patch to add /Users/christopherlee/scrape_ftbhai.py
Patch
```diff
*** Begin Patch
*** Add File: /Users/christopherlee/scrape_ftbhai.py
+#!/usr/bin/env python3
+"""Scrape CAR's First-Time Buyer Housing Affordability Index table to CSV."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import sys
+from html.parser import HTMLParser
+from pathlib import Path
+from typing import Iterable
+from urllib.error import HTTPError, URLError
+from urllib.request import Request, urlopen
+
+
+SOURCE_URL = "https://www.car.org/marketdata/data/ftbhai"
+USER_AGENT = (
+ "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+ "AppleWebKit/537.36 (KHTML, like Gecko) "
+ "Chrome/124.0.0.0 Safari/537.36"
+)
+CSV_HEADERS = [
+ "State/Region/County",
+ "Q42025",
+ "Q32025",
+ "Q42024",
+ "Median Home Price",
+ "Monthly Payment Including Taxes & Insurance",
+ "Minimum Qualifying Income",
+]
+
+
+class TableParser(HTMLParser):
+ """Collect plain-text cell values from the first HTML table fragment."""
+
+ def __init__(self) -> None:
+ super().__init__()
+ self.in_tr = False
+ self.in_cell = False
+ self.rows: list[list[str]] = []
+ self.current_row: list[str] = []
+ self.current_parts: list[str] = []
+
+ def handle_starttag(self, tag: str, attrs: list[tuple[str, str | None]]) -> None:
+ if tag == "tr":
+ self.in_tr = True
+ self.current_row = []
+ elif self.in_tr and tag in {"td", "th"}:
+ self.in_cell = True
+ self.current_parts = []
+
+ def handle_endtag(self, tag: str) -> None:
+ if self.in_tr and self.in_cell and tag in {"td", "th"}:
+ text = " ".join("".join(self.current_parts).replace("\xa0", " ").split())
+ self.current_row.append(text)
+ self.in_cell = False
+ self.current_parts = []
+ elif self.in_tr and tag == "tr":
+ if self.current_row:
+ self.rows.append(self.current_row)
+ self.in_tr = False
+
+ def handle_data(self, data: str) -> None:
+ if self.in_cell:
+ self.current_parts.append(data)
+
+
+def fetch_html(url: str, timeout: float) -> str:
+ request = Request(url, headers={"User-Agent": USER_AGENT})
+ with urlopen(request, timeout=timeout) as response:
+ return response.read().decode("utf-8", errors="ignore")
+
+
+def extract_first_table(html: str) -> str:
+ table_start = html.find(" tag found in the page HTML.")
+
+ table_end = html.find("", table_start)
+ if table_end == -1:
+ raise ValueError("Found a tag.")
+
+ return html[table_start : table_end + len("")]
+
+
+def normalize_rows(raw_rows: Iterable[list[str]]) -> list[list[str]]:
+ normalized: list[list[str]] = []
+
+ for raw in raw_rows:
+ if len(raw) < 9:
+ continue
+
+ row = [raw[0], raw[1], raw[2], raw[4], raw[6], raw[7], raw[8]]
+ if not any(cell.strip() for cell in row):
+ continue
+
+ normalized.append(row)
+
+ return normalized
+
+
+def scrape_ftbhai(url: str, timeout: float) -> list[list[str]]:
+ html = fetch_html(url, timeout)
+ table_html = extract_first_table(html)
+
+ parser = TableParser()
+ parser.feed(table_html)
+
+ # The first three rows are the title row, header row, and a blank spacer row.
+ return normalize_rows(parser.rows[3:])
+
+
+def write_csv(path: Path, rows: list[list[str]]) -> None:
+ with path.open("w", newline="", encoding="utf-8") as handle:
+ writer = csv.writer(handle)
+ writer.writerow(CSV_HEADERS)
+ writer.writerows(rows)
+
+
+def build_parser() -> argparse.ArgumentParser:
+ parser = argparse.ArgumentParser(
+ description=(
+ "Scrape CAR's First-Time Buyer Housing Affordability Index table and "
+ "write it to a CSV file."
+ )
+ )
+ parser.add_argument(
+ "-o",
+ "--output",
+ default="ftbhai.csv",
+ help="Output CSV path. Defaults to ./ftbhai.csv",
+ )
+ parser.add_argument(
+ "--url",
+ default=SOURCE_URL,
+ help=f"Source page URL. Defaults to {SOURCE_URL}",
+ )
+ parser.add_argument(
+ "--timeout",
+ type=float,
+ default=20.0,
+ help="HTTP timeout in seconds. Defaults to 20.",
+ )
+ parser.add_argument(
+ "--stdout",
+ action="store_true",
+ help="Also print the CSV to stdout after writing the file.",
+ )
+ return parser
+
+
+def main() -> int:
+ parser = build_parser()
+ args = parser.parse_args()
+
+ try:
+ rows = scrape_ftbhai(args.url, args.timeout)
+ except HTTPError as exc:
+ print(f"HTTP error while fetching {args.url}: {exc.code} {exc.reason}", file=sys.stderr)
+ return 1
+ except URLError as exc:
+ print(f"Network error while fetching {args.url}: {exc.reason}", file=sys.stderr)
+ return 1
+ except ValueError as exc:
+ print(f"Parse error: {exc}", file=sys.stderr)
+ return 1
+
+ output_path = Path(args.output).expanduser().resolve()
+ write_csv(output_path, rows)
+
+ print(f"Wrote {len(rows)} rows to {output_path}")
+
+ if args.stdout:
+ writer = csv.writer(sys.stdout)
+ writer.writerow(CSV_HEADERS)
+ writer.writerows(rows)
+
+ return 0
+
+
+if __name__ == "__main__":
+ raise SystemExit(main())
*** End Patch
```
Raw tool result
````text
{"output":"Success. Updated the following files:\nA /Users/christopherlee/scrape_ftbhai.py\n","metadata":{"exit_code":0,"duration_seconds":0.0}}
````
**Assistant**
The script is in place. I’m running it against the live page and writing to a separate test CSV so I can confirm it still scrapes the current table correctly.
Background terminal finished with chmod +x /Users/christopherlee/scrape_ftbhai.py
Command
```bash
chmod +x /Users/christopherlee/scrape_ftbhai.py
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 1000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc 'chmod +x /Users/christopherlee/scrape_ftbhai.py'
Chunk ID: e80024
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 0
Output:
````
Background terminal finished with python3 /Users/christopherlee/scrape_ftbhai.py --output /Users/christopherlee/ftbhai_test.csv
Command
```bash
python3 /Users/christopherlee/scrape_ftbhai.py --output /Users/christopherlee/ftbhai_test.csv
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 4000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc 'python3 /Users/christopherlee/scrape_ftbhai.py --output /Users/christopherlee/ftbhai_test.csv'
Chunk ID: 8d5008
Wall time: 0.3658 seconds
Process exited with code 0
Original token count: 14
Output:
Wrote 65 rows to /Users/christopherlee/ftbhai_test.csv
````
**Assistant**
The live scrape worked. I’m checking the generated CSV header and first few lines, then I’ll give you the script path and usage.
Background terminal finished with sed -n '1,8p' /Users/christopherlee/ftbhai_test.csv
Command
```bash
sed -n '1,8p' /Users/christopherlee/ftbhai_test.csv
```
Invocation metadata
```json
{
"workdir": "/Users/christopherlee",
"max_output_tokens": 4000,
"yield_time_ms": 1000
}
```
Raw tool result
````text
Command: /bin/zsh -lc "sed -n '1,8p' /Users/christopherlee/ftbhai_test.csv"
Chunk ID: c9c561
Wall time: 0.0000 seconds
Process exited with code 0
Original token count: 123
Output:
State/Region/County,Q42025,Q32025,Q42024,Median Home Price,Monthly Payment Including Taxes & Insurance,Minimum Qualifying Income
CA SFH (SAAR),33,30,29,"$738,910","$4,680","$140,400"
CA Condo/Townhomes,46,44,41,"$552,500","$3,500","$105,000"
Los Angeles Metropolitan Area,32,30,29,"$705,500","$4,470","$134,100"
Inland Empire,45,43,41,"$505,750","$3,210","$96,300"
S.F. Bay Area,32,30,29,"$1,074,320","$6,810","$204,300"
US,57,54,54,"$352,670","$2,240","$67,200"
S.F. Bay Area,,,,,,
````
**Assistant**
I wrote the scraper to [scrape_ftbhai.py](/Users/christopherlee/scrape_ftbhai.py). It fetches the CAR page with a browser-like user agent, extracts the first table, normalizes the columns, and writes CSV.
Usage is straightforward:
```bash
python3 /Users/christopherlee/scrape_ftbhai.py
python3 /Users/christopherlee/scrape_ftbhai.py --output /Users/christopherlee/ftbhai.csv
python3 /Users/christopherlee/scrape_ftbhai.py --stdout
```
It defaults to writing `./ftbhai.csv` in whatever directory you run it from. I verified it live and it successfully wrote 65 rows to a test file.
|