mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-12-24 22:44:56 +01:00
66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
|
import numpy as np
|
||
|
|
|
||
|
|
import pandas as pd
|
||
|
|
from pandas import DataFrame, date_range, to_datetime
|
||
|
|
import pandas._testing as tm
|
||
|
|
|
||
|
|
|
||
|
|
class TestDataFrameTimeSeriesMethods:
|
||
|
|
def test_frame_ctor_datetime64_column(self):
|
||
|
|
rng = date_range("1/1/2000 00:00:00", "1/1/2000 1:59:50", freq="10s")
|
||
|
|
dates = np.asarray(rng)
|
||
|
|
|
||
|
|
df = DataFrame({"A": np.random.randn(len(rng)), "B": dates})
|
||
|
|
assert np.issubdtype(df["B"].dtype, np.dtype("M8[ns]"))
|
||
|
|
|
||
|
|
def test_frame_append_datetime64_col_other_units(self):
|
||
|
|
n = 100
|
||
|
|
|
||
|
|
units = ["h", "m", "s", "ms", "D", "M", "Y"]
|
||
|
|
|
||
|
|
ns_dtype = np.dtype("M8[ns]")
|
||
|
|
|
||
|
|
for unit in units:
|
||
|
|
dtype = np.dtype(f"M8[{unit}]")
|
||
|
|
vals = np.arange(n, dtype=np.int64).view(dtype)
|
||
|
|
|
||
|
|
df = DataFrame({"ints": np.arange(n)}, index=np.arange(n))
|
||
|
|
df[unit] = vals
|
||
|
|
|
||
|
|
ex_vals = to_datetime(vals.astype("O")).values
|
||
|
|
|
||
|
|
assert df[unit].dtype == ns_dtype
|
||
|
|
assert (df[unit].values == ex_vals).all()
|
||
|
|
|
||
|
|
# Test insertion into existing datetime64 column
|
||
|
|
df = DataFrame({"ints": np.arange(n)}, index=np.arange(n))
|
||
|
|
df["dates"] = np.arange(n, dtype=np.int64).view(ns_dtype)
|
||
|
|
|
||
|
|
for unit in units:
|
||
|
|
dtype = np.dtype(f"M8[{unit}]")
|
||
|
|
vals = np.arange(n, dtype=np.int64).view(dtype)
|
||
|
|
|
||
|
|
tmp = df.copy()
|
||
|
|
|
||
|
|
tmp["dates"] = vals
|
||
|
|
ex_vals = to_datetime(vals.astype("O")).values
|
||
|
|
|
||
|
|
assert (tmp["dates"].values == ex_vals).all()
|
||
|
|
|
||
|
|
def test_datetime_assignment_with_NaT_and_diff_time_units(self):
|
||
|
|
# GH 7492
|
||
|
|
data_ns = np.array([1, "nat"], dtype="datetime64[ns]")
|
||
|
|
result = pd.Series(data_ns).to_frame()
|
||
|
|
result["new"] = data_ns
|
||
|
|
expected = pd.DataFrame(
|
||
|
|
{0: [1, None], "new": [1, None]}, dtype="datetime64[ns]"
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
# OutOfBoundsDatetime error shouldn't occur
|
||
|
|
data_s = np.array([1, "nat"], dtype="datetime64[s]")
|
||
|
|
result["new"] = data_s
|
||
|
|
expected = pd.DataFrame(
|
||
|
|
{0: [1, None], "new": [1e9, None]}, dtype="datetime64[ns]"
|
||
|
|
)
|
||
|
|
tm.assert_frame_equal(result, expected)
|