def for_date(date_string=None):
"""Return all data for a specific date."""
date_string: Optional[str]
date = (dt.datetime.fromisoformat(date_string).date()
if date_string is not None else
(dt.datetime.utcnow() - dt.timedelta(days=1)).date())
result = df[df["Last Update"].map(lambda d: d.date()) == date]
return to_records(result)
def get_all(
date=None,
country=None,
state=None,
min_date=None,
max_date=None,
countries=None,
states=None,
limit=None,
):
"""Fetch all data from John Hopkins."""
result = df
if date is not None:
result = df[df["Last Update"].map(lambda d: d.date()) ==
dt.datetime.fromisoformat(date).date()]
if country is not None:
result = result[result["Country/Region"] == country]
if state is not None:
result = result[result["Province/State"] == state]
if min_date is not None:
result = result[result["Last Update"].map(lambda d: d.date()) >=
dt.datetime.fromisoformat(min_date).date()]
if max_date is not None:
result = result[result["Last Update"].map(lambda d: d.date()) <=
dt.datetime.fromisoformat(max_date).date()]
if countries is not None:
countries = (json.loads(countries)
if not isinstance(countries, list) else countries)
result = result[result["Countries/Regions"].map(
lambda s: s in countries)]
if states is not None:
states = json.loads(states) if not isinstance(states, list) else states
result = result[result["Province/State"].map(lambda s: s in states)]
records = to_records(result)
if limit is not None:
records = records[:int(limit)]
return records
def states():
"""Return all states and provinces in the dataset."""
return to_records(df[["Province/State",
"Country/Region"]].dropna(how="any"))
def get_all(
date=None,
country=None,
state=None,
min_date=None,
max_date=None,
countries=None,
states=None,
county=None,
counties=None,
limit=None,
):
"""Fetch all data from John Hopkins."""
result = df
if date is not None:
result = df[
df.datetime.map(lambda d: d.date())
== dt.datetime.fromisoformat(date).date()
]
if min_date is not None:
result = result[
result["datetime"].map(lambda d: d.date())
>= dt.datetime.fromisoformat(min_date).date()
]
if max_date is not None:
result = result[
result["datetime"].map(lambda d: d.date())
<= dt.datetime.fromisoformat(max_date).date()
]
assert not (
country and countries
), "country and countries filters are mutually exclusive"
if country or countries:
countries = (
[country]
if country
else (
json.loads(countries)
if not isinstance(countries, list)
else countries
)
)
result = result[result.country.map(lambda c: c in countries)]
assert not (
state and states
), "state and states filters are mutually exclusive"
if state or states:
states = (
[state]
if state
else json.loads(states)
if not isinstance(states, list)
else states
)
result = result[result.state.map(lambda s: s in states)]
assert not (
county and counties
), "county and counties filters are mutually exclusive"
if county or counties:
counties = (
[county]
if county
else json.loads(counties)
if not isinstance(counties, list)
else counties
)
result = result[result.county.map(lambda c: c in counties)]
records = to_records(result)
if limit is not None:
records = records[: int(limit)]
return records
def states():
"""Return all states and provinces in the dataset."""
return to_records(df[["state", "country"]].dropna())