FM / frame

/usr/local/lib64/python3.6/site-packages/pandas/tests/frame/

/usr/local/lib64/python3.6/site-packages/pandas/tests/frame

Name	Size	Mode	Actions
apply/	-	0755	rm
methods/	-	0755	rm
__pycache__/	-	0755	rm
common.py	1119	0644	edit dl rm
conftest.py	8855	0644	edit dl rm
test_alter_axes.py	8801	0644	edit dl rm
test_analytics.py	46557	0644	edit dl rm
test_api.py	19589	0644	edit dl rm
test_arithmetic.py	54999	0644	edit dl rm
test_axis_select_reindex.py	18320	0644	edit dl rm
test_block_internals.py	23194	0644	edit dl rm
test_combine_concat.py	8607	0644	edit dl rm
test_constructors.py	100607	0644	edit dl rm
test_cumulative.py	4228	0644	edit dl rm
test_dtypes.py	11812	0644	edit dl rm
test_join.py	8779	0644	edit dl rm
test_missing.py	25616	0644	edit dl rm
test_nonunique_indexes.py	17501	0644	edit dl rm
test_operators.py	9068	0644	edit dl rm
test_period.py	1184	0644	edit dl rm
test_query_eval.py	47568	0644	edit dl rm
test_repr_info.py	6729	0644	edit dl rm
test_reshape.py	47482	0644	edit dl rm
test_sort_values_level_as_str.py	2550	0644	edit dl rm
test_subclass.py	23573	0644	edit dl rm
test_timeseries.py	2218	0644	edit dl rm
test_timezones.py	6158	0644	edit dl rm
test_to_csv.py	48182	0644	edit dl rm
test_validate.py	1095	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/frame/test_timeseries.py (2218B)

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)

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)