Why Gemfury? Push, build, and install  RubyGems npm packages Python packages Maven artifacts PHP packages Go Modules Bower components Debian packages RPM packages NuGet packages

agriconnect / pandas   python

Repository URL to install this package:

Version: 0.24.2 

/ tests / extension / base / interface.py

import numpy as np

from pandas.core.dtypes.common import is_extension_array_dtype
from pandas.core.dtypes.dtypes import ExtensionDtype

import pandas as pd
import pandas.util.testing as tm

from .base import BaseExtensionTests


class BaseInterfaceTests(BaseExtensionTests):
    """Tests that the basic interface is satisfied."""
    # ------------------------------------------------------------------------
    # Interface
    # ------------------------------------------------------------------------

    def test_len(self, data):
        assert len(data) == 100

    def test_ndim(self, data):
        assert data.ndim == 1

    def test_can_hold_na_valid(self, data):
        # GH-20761
        assert data._can_hold_na is True

    def test_memory_usage(self, data):
        s = pd.Series(data)
        result = s.memory_usage(index=False)
        assert result == s.nbytes

    def test_array_interface(self, data):
        result = np.array(data)
        assert result[0] == data[0]

        result = np.array(data, dtype=object)
        expected = np.array(list(data), dtype=object)
        tm.assert_numpy_array_equal(result, expected)

    def test_is_extension_array_dtype(self, data):
        assert is_extension_array_dtype(data)
        assert is_extension_array_dtype(data.dtype)
        assert is_extension_array_dtype(pd.Series(data))
        assert isinstance(data.dtype, ExtensionDtype)

    def test_no_values_attribute(self, data):
        # GH-20735: EA's with .values attribute give problems with internal
        # code, disallowing this for now until solved
        assert not hasattr(data, 'values')
        assert not hasattr(data, '_values')

    def test_is_numeric_honored(self, data):
        result = pd.Series(data)
        assert result._data.blocks[0].is_numeric is data.dtype._is_numeric

    def test_isna_extension_array(self, data_missing):
        # If your `isna` returns an ExtensionArray, you must also implement
        # _reduce. At the *very* least, you must implement any and all
        na = data_missing.isna()
        if is_extension_array_dtype(na):
            assert na._reduce('any')
            assert na.any()

            assert not na._reduce('all')
            assert not na.all()

            assert na.dtype._is_boolean