def test_downsample():
s = Series(
"datetime",
[
946684800000,
946684860000,
946684920000,
946684980000,
946685040000,
946685100000,
946685160000,
946685220000,
946685280000,
946685340000,
946685400000,
946685460000,
946685520000,
946685580000,
946685640000,
946685700000,
946685760000,
946685820000,
946685880000,
946685940000,
],
).cast(Date64)
s2 = s.clone()
df = DataFrame({"a": s, "b": s2})
out = df.downsample("a", rule="minute", n=5).first()
assert out.shape == (4, 2)
def test_downsample():
s = Series(
"datetime",
[
946684800000,
946684860000,
946684920000,
946684980000,
946685040000,
946685100000,
946685160000,
946685220000,
946685280000,
946685340000,
946685400000,
946685460000,
946685520000,
946685580000,
946685640000,
946685700000,
946685760000,
946685820000,
946685880000,
946685940000,
],
).cast(Date64)
s2 = s.clone()
df = DataFrame({"a": s, "b": s2})
out = df.downsample("a", rule="minute", n=5).first()
assert out.shape == (4, 2)
# OLHC
out = df.downsample("a", rule="minute",
n=5).agg({"b": ["first", "min", "max", "last"]})
assert out.shape == (4, 5)
# test to_pandas as well.
out = df.to_pandas()
assert out["a"].dtype == "datetime64[ns]"