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]"