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Remove unnecessary get_path helper #102

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Merged
sid-kap merged 5 commits into from
Aug 23, 2025
Merged

Remove unnecessary get_path helper #102

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3e84c39
Remove unnecessary get_path helper
sid-kap Aug 23, 2025
27a47ec
more cleanup
sid-kap Aug 23, 2025
2938f6e
fix mypy
sid-kap Aug 23, 2025
e7c256b
fix mypy
sid-kap Aug 23, 2025
d706a80
fix mypy?
sid-kap Aug 23, 2025
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4 changes: 2 additions & 2 deletions python/housing_data/build_places.py
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Original file line number Diff line number Diff line change
Expand Up @@ -293,7 +293,7 @@ def get_name_spelling(places_df: pd.DataFrame) -> pd.Series:


def load_places(
data_repo_path: Optional[Path], counties_population_df: pd.DataFrame = None
data_repo_path: Path, counties_population_df: pd.DataFrame = None
) -> tuple[pd.DataFrame, pd.DataFrame]:
raw_places_df = pd.concat(
[
Expand All @@ -310,7 +310,7 @@ def load_places(
raw_places_df.to_parquet(PUBLIC_DIR / "places_annual_without_population.parquet")

place_populations_df = place_population.get_place_population_estimates(
data_path=data_repo_path / PLACE_POPULATION_DIR if data_repo_path else None
data_path=data_repo_path / PLACE_POPULATION_DIR
)
place_populations_df = fix_nyc_boroughs_population(
place_populations_df, counties_population_df
Expand Down
7 changes: 1 addition & 6 deletions python/housing_data/county_population.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,6 @@
import pandas as pd
import us
from housing_data.build_data_utils import impute_2025_population
from housing_data.data_loading_helpers import get_url_text
from housing_data.fips_crosswalk import load_fips_crosswalk


Expand Down Expand Up @@ -119,11 +118,7 @@ def get_county_fips_crosswalk(data_repo_path: Path) -> pd.DataFrame:


def get_county_populations_1990s(data_path: Path) -> pd.DataFrame:
table_text = get_url_text(
"https://www2.census.gov/programs-surveys/popest/tables/1990-2000/counties/totals/99c8_00.txt",
data_path,
encoding="latin_1",
)
table_text = (data_path / "99c8_00.txt").read_text(encoding="latin_1")

table_text = table_text[: table_text.index("Block 2")].strip()

Expand Down
7 changes: 0 additions & 7 deletions python/housing_data/data_loading_helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,10 +34,3 @@ def get_url_text(
else:
web_url = os.path.join(web_prefix, common_path)
return requests.get(web_url).text


def get_path(url: str, data_path: Optional[Path]) -> str:
if data_path is not None:
return str(Path(data_path, Path(url).name))
else:
return url
53 changes: 13 additions & 40 deletions python/housing_data/place_population.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,15 +5,10 @@
import numpy as np
import pandas as pd
from housing_data.build_data_utils import impute_2025_population
from housing_data.data_loading_helpers import get_path, get_url_text


def _get_places_crosswalk_df(data_path: Optional[Path] = None) -> pd.DataFrame:
df = pd.read_fwf(
get_path(
"https://www2.census.gov/geo/tiger/PREVGENZ/pl/us_places.txt", data_path
)
)
def _get_places_crosswalk_df(data_path: Path) -> pd.DataFrame:
df = pd.read_fwf(data_path / "us_places.txt")

df["State Code"] = df["CENSUS"] // 10000
df["Place Code"] = df["CENSUS"] % 10000
Expand Down Expand Up @@ -79,7 +74,7 @@ def get_unincorporated_places_populations_1980() -> pd.DataFrame:
return remainder_df


def get_place_populations_1980(data_path: Optional[Path]) -> pd.DataFrame:
def get_place_populations_1980(data_path: Path) -> pd.DataFrame:
# Assuming this is run from `python/`
# For the header row, use the nice descriptive names that IPUMS provides rather than the code names
df = pd.read_csv("../raw_data/nhgis0015_ds104_1980_place_070.csv", header=1)
Expand Down Expand Up @@ -147,12 +142,8 @@ def get_place_populations_1980(data_path: Optional[Path]) -> pd.DataFrame:
return df


def _load_raw_place_populations_1990s(data_path: Optional[Path]) -> pd.DataFrame:
tables = get_url_text(
"https://www2.census.gov/programs-surveys/popest/tables/1990-2000/"
"2000-subcounties-evaluation-estimates/sc2000f_us.txt",
data_path,
).split("\f")
def _load_raw_place_populations_1990s(data_path: Path) -> pd.DataFrame:
tables = (data_path / "sc2000f_us.txt").read_text().split("\f")

common_cols = [
"Block",
Expand Down Expand Up @@ -278,7 +269,7 @@ def remove_duplicate_cities(df: pd.DataFrame) -> pd.DataFrame:
return df[~place_state_tuples.isin(dupe_cities)]


def get_place_populations_1990s(data_path: Optional[Path]) -> pd.DataFrame:
def get_place_populations_1990s(data_path: Path) -> pd.DataFrame:
combined_df = _load_raw_place_populations_1990s(data_path)

city_rows = (
Expand Down Expand Up @@ -396,14 +387,8 @@ def _melt_df(
)


def get_place_populations_2000s(data_path: Optional[Path]) -> pd.DataFrame:
df = pd.read_csv(
get_path(
"https://www2.census.gov/programs-surveys/popest/datasets/2000-2010/intercensal/cities/sub-est00int.csv",
data_path,
),
encoding="latin_1",
)
def get_place_populations_2000s(data_path: Path) -> pd.DataFrame:
df = pd.read_csv(data_path / "sub-est00int.csv", encoding="latin_1")
return _melt_df(
df,
years=list(range(2000, 2011)),
Expand All @@ -412,26 +397,14 @@ def get_place_populations_2000s(data_path: Optional[Path]) -> pd.DataFrame:
)


def get_place_populations_2010s(data_path: Optional[Path]) -> pd.DataFrame:
df = pd.read_csv(
get_path(
"https://www2.census.gov/programs-surveys/popest/datasets/2010-2020/cities/SUB-EST2020_ALL.csv",
data_path,
),
encoding="latin_1",
)
def get_place_populations_2010s(data_path: Path) -> pd.DataFrame:
df = pd.read_csv(data_path / "SUB-EST2020_ALL.csv", encoding="latin_1")

return _melt_df(df, years=list(range(2010, 2021)))


def get_place_populations_2020s(data_path: Optional[Path]) -> pd.DataFrame:
df = pd.read_csv(
get_path(
"https://www2.census.gov/programs-surveys/popest/datasets/2010-2020/cities/sub-est2024.csv",
data_path,
),
encoding="latin_1",
)
def get_place_populations_2020s(data_path: Path) -> pd.DataFrame:
df = pd.read_csv(data_path / "sub-est2024.csv", encoding="latin_1")
df = _melt_df(df, years=list(range(2020, 2025)))
df = impute_2025_population(df)
return df
Expand Down Expand Up @@ -482,7 +455,7 @@ def interpolate_1980s_populations(
return interp_df


def get_place_population_estimates(data_path: Optional[Path] = None) -> pd.DataFrame:
def get_place_population_estimates(data_path: Path) -> pd.DataFrame:
"""
Returns a DataFrame with the columns:
- state_code (int)
Expand Down
18 changes: 3 additions & 15 deletions python/housing_data/state_population.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,6 @@
import pandas as pd
import us
from housing_data.build_data_utils import impute_2025_population
from housing_data.data_loading_helpers import get_path, get_url_text

DIVISIONS = {
"New England": [
Expand Down Expand Up @@ -75,10 +74,7 @@ def _line_to_cols(row: str) -> list[str]:


def get_state_populations_1980s(data_path: Path) -> pd.DataFrame:
states_80s_text = get_url_text(
"https://www2.census.gov/programs-surveys/popest/tables/1980-1990/state/asrh/st8090ts.txt",
data_path,
)
states_80s_text = (data_path / "st8090ts.txt").read_text()
handle = StringIO(states_80s_text)

for _ in range(10):
Expand Down Expand Up @@ -168,10 +164,7 @@ def get_state_populations_1990s(data_path: Path) -> pd.DataFrame:

def get_state_populations_2000s(data_path: Path) -> pd.DataFrame:
df = pd.read_excel(
get_path(
"https://www2.census.gov/programs-surveys/popest/tables/2000-2010/intercensal/state/st-est00int-01.xls",
data_path,
),
data_path / "st-est00int-01.xls",
skiprows=3,
skipfooter=8,
)
Expand Down Expand Up @@ -206,12 +199,7 @@ def _melt_df(df: pd.DataFrame, years: list[int]) -> pd.DataFrame:


def get_state_populations_2010s(data_path: Path) -> pd.DataFrame:
df = pd.read_csv(
get_path(
"https://www2.census.gov/programs-surveys/popest/datasets/2010-2020/state/totals/nst-est2020-alldata.csv",
data_path,
)
)
df = pd.read_csv(data_path / "nst-est2020-alldata.csv")

return _melt_df(df, list(range(2010, 2020)))

Expand Down
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