import numpy as np
import pytest

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

from .base import BaseExtensionTests


class BaseMissingTests(BaseExtensionTests):
    def test_isna(self, data_missing):
        if data_missing._can_hold_na:
            expected = np.array([True, False])
        else:
            expected = np.array([False, False])

        result = pd.isna(data_missing)
        tm.assert_numpy_array_equal(result, expected)

        result = pd.Series(data_missing).isna()
        expected = pd.Series(expected)
        self.assert_series_equal(result, expected)

    def test_dropna_series(self, data_missing):
        ser = pd.Series(data_missing)
        result = ser.dropna()
        expected = ser.iloc[[1]]
        self.assert_series_equal(result, expected)

    def test_dropna_frame(self, data_missing):
        df = pd.DataFrame({"A": data_missing})

        # defaults
        result = df.dropna()
        expected = df.iloc[[1]]
        self.assert_frame_equal(result, expected)

        # axis = 1
        result = df.dropna(axis='columns')
        expected = pd.DataFrame(index=[0, 1])
        self.assert_frame_equal(result, expected)

        # multiple
        df = pd.DataFrame({"A": data_missing,
                           "B": [1, np.nan]})
        result = df.dropna()
        expected = df.iloc[:0]
        self.assert_frame_equal(result, expected)

    def test_fillna_scalar(self, data_missing):
        valid = data_missing[1]
        result = data_missing.fillna(valid)
        expected = data_missing.fillna(valid)
        self.assert_extension_array_equal(result, expected)

    def test_fillna_limit_pad(self, data_missing):
        arr = data_missing.take([1, 0, 0, 0, 1])
        result = pd.Series(arr).fillna(method='ffill', limit=2)
        expected = pd.Series(data_missing.take([1, 1, 1, 0, 1]))
        self.assert_series_equal(result, expected)

    def test_fillna_limit_backfill(self, data_missing):
        arr = data_missing.take([1, 0, 0, 0, 1])
        result = pd.Series(arr).fillna(method='backfill', limit=2)
        expected = pd.Series(data_missing.take([1, 0, 1, 1, 1]))
        self.assert_series_equal(result, expected)

    def test_fillna_series(self, data_missing):
        fill_value = data_missing[1]
        ser = pd.Series(data_missing)

        result = ser.fillna(fill_value)
        expected = pd.Series(type(data_missing)([fill_value, fill_value]))
        self.assert_series_equal(result, expected)

        # Fill with a series
        result = ser.fillna(expected)
        self.assert_series_equal(result, expected)

        # Fill with a series not affecting the missing values
        result = ser.fillna(ser)
        self.assert_series_equal(result, ser)

    @pytest.mark.parametrize('method', ['ffill', 'bfill'])
    def test_fillna_series_method(self, data_missing, method):
        fill_value = data_missing[1]

        if method == 'ffill':
            data_missing = type(data_missing)(data_missing[::-1])

        result = pd.Series(data_missing).fillna(method=method)
        expected = pd.Series(type(data_missing)([fill_value, fill_value]))

        self.assert_series_equal(result, expected)

    def test_fillna_frame(self, data_missing):
        fill_value = data_missing[1]

        result = pd.DataFrame({
            "A": data_missing,
            "B": [1, 2]
        }).fillna(fill_value)

        expected = pd.DataFrame({
            "A": type(data_missing)([fill_value, fill_value]),
            "B": [1, 2],
        })

        self.assert_frame_equal(result, expected)

    def test_fillna_fill_other(self, data):
        result = pd.DataFrame({
            "A": data,
            "B": [np.nan] * len(data)
        }).fillna({"B": 0.0})

        expected = pd.DataFrame({
            "A": data,
            "B": [0.0] * len(result),
        })

        self.assert_frame_equal(result, expected)
