"""The Australian daily-min-termperatures weather dataset."""
import pandas as pd
import evalml
from evalml.preprocessing import load_data
from evalml.utils import infer_feature_types
[docs]def load_weather():
"""Load the Australian daily-min-termperatures weather dataset.
Returns:
(pd.Dataframe, pd.Series): X and y
"""
filename = (
"https://api.featurelabs.com/datasets/daily-min-temperatures.csv?library=evalml&version="
+ evalml.__version__
)
X, y = load_data(filename, index=None, target="Temp")
missing_date_1 = pd.DataFrame([pd.to_datetime("1984-12-31")], columns=["Date"])
missing_date_2 = pd.DataFrame([pd.to_datetime("1988-12-31")], columns=["Date"])
missing_y_1 = pd.Series([14.5], name="Temp")
missing_y_2 = pd.Series([14.5], name="Temp")
X = pd.concat([X.iloc[:1460], missing_date_1, X.iloc[1460:]]).reset_index(drop=True)
X = pd.concat([X.iloc[:2921], missing_date_2, X.iloc[2921:]]).reset_index(drop=True)
y = pd.concat([y.iloc[:1460], missing_y_1, y.iloc[1460:]]).reset_index(drop=True)
y = pd.concat([y.iloc[:2921], missing_y_2, y.iloc[2921:]]).reset_index(drop=True)
X = infer_feature_types(X)
y = infer_feature_types(y)
return X, y