def test_make_recurrent_no_partitioning4():
ORDER_BY = "times"
N_RECURRENT_SAMPLES = 5
df = sample_data2()
arr, y = make_recurrent(df, N_RECURRENT_SAMPLES, ORDER_BY, verbose=True, price_column="val1", time_threshold=86400)
check_results(arr, df, N_RECURRENT_SAMPLES)
def test_make_recurrent_partitioning4():
ORDER_BY = "times"
PARTITION_BY = "day"
N_RECURRENT_SAMPLES = 3
df = sample_data2()
df[PARTITION_BY] = pd.to_datetime(df["times"]).dt.to_period("D")
arr, y = make_recurrent(df, N_RECURRENT_SAMPLES, ORDER_BY, PARTITION_BY, verbose=True, price_column="val1", time_threshold=86400)
check_results(arr, df, N_RECURRENT_SAMPLES, PARTITION_BY)
def main():
df = sample_data1()
arr = make_recurrent(df,
3,
"times",
drop_order_by=False,
drop_partition_by=False)
print(df)
print("***********************************************")
print(arr)
def main():
df = sample_data1()
df["month"] = pd.to_datetime(df["times"]).dt.to_period("M")
arr = make_recurrent(
df,
3,
"times",
partition_by="month",
drop_order_by=False,
drop_partition_by=False,
)
print(df)
print("***********************************************")
print(arr)
print(f"Output shape is {arr.shape}")