test_partial.py

"""
test setting *parts* of objects both positionally and label based

TOD: these should be split among the indexer tests
"""

import pytest

from warnings import catch_warnings
import numpy as np

import pandas as pd
from pandas import Series, DataFrame, Panel, Index, date_range
from pandas.util import testing as tm


class TestPartialSetting(object):

    def test_partial_setting(self):

        # GH2578, allow ix and friends to partially set

        # series
        s_orig = Series([1, 2, 3])

        s = s_orig.copy()
        s[5] = 5
        expected = Series([1, 2, 3, 5], index=[0, 1, 2, 5])
        tm.assert_series_equal(s, expected)

        s = s_orig.copy()
        s.loc[5] = 5
        expected = Series([1, 2, 3, 5], index=[0, 1, 2, 5])
        tm.assert_series_equal(s, expected)

        s = s_orig.copy()
        s[5] = 5.
        expected = Series([1, 2, 3, 5.], index=[0, 1, 2, 5])
        tm.assert_series_equal(s, expected)

        s = s_orig.copy()
        s.loc[5] = 5.
        expected = Series([1, 2, 3, 5.], index=[0, 1, 2, 5])
        tm.assert_series_equal(s, expected)

        # iloc/iat raise
        s = s_orig.copy()

        def f():
            s.iloc[3] = 5.

        pytest.raises(IndexError, f)

        def f():
            s.iat[3] = 5.

        pytest.raises(IndexError, f)

        # ## frame ##

        df_orig = DataFrame(
            np.arange(6).reshape(3, 2), columns=['A', 'B'], dtype='int64')

        # iloc/iat raise
        df = df_orig.copy()

        def f():
            df.iloc[4, 2] = 5.

        pytest.raises(IndexError, f)

        def f():
            df.iat[4, 2] = 5.

        pytest.raises(IndexError, f)

        # row setting where it exists
        expected = DataFrame(dict({'A': [0, 4, 4], 'B': [1, 5, 5]}))
        df = df_orig.copy()
        df.iloc[1] = df.iloc[2]
        tm.assert_frame_equal(df, expected)

        expected = DataFrame(dict({'A': [0, 4, 4], 'B': [1, 5, 5]}))
        df = df_orig.copy()
        df.loc[1] = df.loc[2]
        tm.assert_frame_equal(df, expected)

        # like 2578, partial setting with dtype preservation
        expected = DataFrame(dict({'A': [0, 2, 4, 4], 'B': [1, 3, 5, 5]}))
        df = df_orig.copy()
        df.loc[3] = df.loc[2]
        tm.assert_frame_equal(df, expected)

        # single dtype frame, overwrite
        expected = DataFrame(dict({'A': [0, 2, 4], 'B': [0, 2, 4]}))
        df = df_orig.copy()
        with catch_warnings(record=True):
            df.ix[:, 'B'] = df.ix[:, 'A']
        tm.assert_frame_equal(df, expected)

        # mixed dtype frame, overwrite
        expected = DataFrame(dict({'A': [0, 2, 4], 'B': Series([0, 2, 4])}))
        df = df_orig.copy()
        df['B'] = df['B'].astype(np.float64)
        with catch_warnings(record=True):
            df.ix[:, 'B'] = df.ix[:, 'A']
        tm.assert_frame_equal(df, expected)

        # single dtype frame, partial setting
        expected = df_orig.copy()
        expected['C'] = df['A']
        df = df_orig.copy()
        with catch_warnings(record=True):
            df.ix[:, 'C'] = df.ix[:, 'A']
        tm.assert_frame_equal(df, expected)

        # mixed frame, partial setting
        expected = df_orig.copy()
        expected['C'] = df['A']
        df = df_orig.copy()
        with catch_warnings(record=True):
            df.ix[:, 'C'] = df.ix[:, 'A']
        tm.assert_frame_equal(df, expected)

        with catch_warnings(record=True):
            # ## panel ##
            p_orig = Panel(np.arange(16).reshape(2, 4, 2),
                           items=['Item1', 'Item2'],
                           major_axis=pd.date_range('2001/1/12', periods=4),
                           minor_axis=['A', 'B'], dtype='float64')

            # panel setting via item
            p_orig = Panel(np.arange(16).reshape(2, 4, 2),
                           items=['Item1', 'Item2'],
                           major_axis=pd.date_range('2001/1/12', periods=4),
                           minor_axis=['A', 'B'], dtype='float64')
            expected = p_orig.copy()
            expected['Item3'] = expected['Item1']
            p = p_orig.copy()
            p.loc['Item3'] = p['Item1']
            tm.assert_panel_equal(p, expected)

            # panel with aligned series
            expected = p_orig.copy()
            expected = expected.transpose(2, 1, 0)
            expected['C'] = DataFrame({'Item1': [30, 30, 30, 30],
                                       'Item2': [32, 32, 32, 32]},
                                      index=p_orig.major_axis)
            expected = expected.transpose(2, 1, 0)
            p = p_orig.copy()
            p.loc[:, :, 'C'] = Series([30, 32], index=p_orig.items)
            tm.assert_panel_equal(p, expected)

        # GH 8473
        dates = date_range('1/1/2000', periods=8)
        df_orig = DataFrame(np.random.randn(8, 4), index=dates,
                            columns=['A', 'B', 'C', 'D'])

        expected = pd.concat([df_orig, DataFrame(
            {'A': 7}, index=[dates[-1] + 1])])
        df = df_orig.copy()
        df.loc[dates[-1] + 1, 'A'] = 7
        tm.assert_frame_equal(df, expected)
        df = df_orig.copy()
        df.at[dates[-1] + 1, 'A'] = 7
        tm.assert_frame_equal(df, expected)

        exp_other = DataFrame({0: 7}, index=[dates[-1] + 1])
        expected = pd.concat([df_orig, exp_other], axis=1)

        df = df_orig.copy()
        df.loc[dates[-1] + 1, 0] = 7
        tm.assert_frame_equal(df, expected)
        df = df_orig.copy()
        df.at[dates[-1] + 1, 0] = 7
        tm.assert_frame_equal(df, expected)

    def test_partial_setting_mixed_dtype(self):

        # in a mixed dtype environment, try to preserve dtypes
        # by appending
        df = DataFrame([[True, 1], [False, 2]], columns=["female", "fitness"])

        s = df.loc[1].copy()
        s.name = 2
        expected = df.append(s)

        df.loc[2] = df.loc[1]
        tm.assert_frame_equal(df, expected)

        # columns will align
        df = DataFrame(columns=['A', 'B'])
        df.loc[0] = Series(1, index=range(4))
        tm.assert_frame_equal(df, DataFrame(columns=['A', 'B'], index=[0]))

        # columns will align
        df = DataFrame(columns=['A', 'B'])
        df.loc[0] = Series(1, index=['B'])

        exp = DataFrame([[np.nan, 1]], columns=['A', 'B'],
                        index=[0], dtype='float64')
        tm.assert_frame_equal(df, exp)

        # list-like must conform
        df = DataFrame(columns=['A', 'B'])

        def f():
            df.loc[0] = [1, 2, 3]

        pytest.raises(ValueError, f)

        # TODO: #15657, these are left as object and not coerced
        df = DataFrame(columns=['A', 'B'])
        df.loc[3] = [6, 7]

        exp = DataFrame([[6, 7]], index=[3], columns=['A', 'B'],
                        dtype='object')
        tm.assert_frame_equal(df, exp)

    def test_series_partial_set(self):
        # partial set with new index
        # Regression from GH4825
        ser = Series([0.1, 0.2], index=[1, 2])

        # loc
        expected = Series([np.nan, 0.2, np.nan], index=[3, 2, 3])
        result = ser.loc[[3, 2, 3]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([np.nan, 0.2, np.nan, np.nan], index=[3, 2, 3, 'x'])
        result = ser.loc[[3, 2, 3, 'x']]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([0.2, 0.2, 0.1], index=[2, 2, 1])
        result = ser.loc[[2, 2, 1]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([0.2, 0.2, np.nan, 0.1], index=[2, 2, 'x', 1])
        result = ser.loc[[2, 2, 'x', 1]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        # raises as nothing in in the index
        pytest.raises(KeyError, lambda: ser.loc[[3, 3, 3]])

        expected = Series([0.2, 0.2, np.nan], index=[2, 2, 3])
        result = ser.loc[[2, 2, 3]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([0.3, np.nan, np.nan], index=[3, 4, 4])
        result = Series([0.1, 0.2, 0.3], index=[1, 2, 3]).loc[[3, 4, 4]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([np.nan, 0.3, 0.3], index=[5, 3, 3])
        result = Series([0.1, 0.2, 0.3, 0.4],
                        index=[1, 2, 3, 4]).loc[[5, 3, 3]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([np.nan, 0.4, 0.4], index=[5, 4, 4])
        result = Series([0.1, 0.2, 0.3, 0.4],
                        index=[1, 2, 3, 4]).loc[[5, 4, 4]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([0.4, np.nan, np.nan], index=[7, 2, 2])
        result = Series([0.1, 0.2, 0.3, 0.4],
                        index=[4, 5, 6, 7]).loc[[7, 2, 2]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        expected = Series([0.4, np.nan, np.nan], index=[4, 5, 5])
        result = Series([0.1, 0.2, 0.3, 0.4],
                        index=[1, 2, 3, 4]).loc[[4, 5, 5]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        # iloc
        expected = Series([0.2, 0.2, 0.1, 0.1], index=[2, 2, 1, 1])
        result = ser.iloc[[1, 1, 0, 0]]
        tm.assert_series_equal(result, expected, check_index_type=True)

    def test_series_partial_set_with_name(self):
        # GH 11497

        idx = Index([1, 2], dtype='int64', name='idx')
        ser = Series([0.1, 0.2], index=idx, name='s')

        # loc
        exp_idx = Index([3, 2, 3], dtype='int64', name='idx')
        expected = Series([np.nan, 0.2, np.nan], index=exp_idx, name='s')
        result = ser.loc[[3, 2, 3]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([3, 2, 3, 'x'], dtype='object', name='idx')
        expected = Series([np.nan, 0.2, np.nan, np.nan], index=exp_idx,
                          name='s')
        result = ser.loc[[3, 2, 3, 'x']]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([2, 2, 1], dtype='int64', name='idx')
        expected = Series([0.2, 0.2, 0.1], index=exp_idx, name='s')
        result = ser.loc[[2, 2, 1]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([2, 2, 'x', 1], dtype='object', name='idx')
        expected = Series([0.2, 0.2, np.nan, 0.1], index=exp_idx, name='s')
        result = ser.loc[[2, 2, 'x', 1]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        # raises as nothing in in the index
        pytest.raises(KeyError, lambda: ser.loc[[3, 3, 3]])

        exp_idx = Index([2, 2, 3], dtype='int64', name='idx')
        expected = Series([0.2, 0.2, np.nan], index=exp_idx, name='s')
        result = ser.loc[[2, 2, 3]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([3, 4, 4], dtype='int64', name='idx')
        expected = Series([0.3, np.nan, np.nan], index=exp_idx, name='s')
        idx = Index([1, 2, 3], dtype='int64', name='idx')
        result = Series([0.1, 0.2, 0.3], index=idx, name='s').loc[[3, 4, 4]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([5, 3, 3], dtype='int64', name='idx')
        expected = Series([np.nan, 0.3, 0.3], index=exp_idx, name='s')
        idx = Index([1, 2, 3, 4], dtype='int64', name='idx')
        result = Series([0.1, 0.2, 0.3, 0.4], index=idx,
                        name='s').loc[[5, 3, 3]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([5, 4, 4], dtype='int64', name='idx')
        expected = Series([np.nan, 0.4, 0.4], index=exp_idx, name='s')
        idx = Index([1, 2, 3, 4], dtype='int64', name='idx')
        result = Series([0.1, 0.2, 0.3, 0.4], index=idx,
                        name='s').loc[[5, 4, 4]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([7, 2, 2], dtype='int64', name='idx')
        expected = Series([0.4, np.nan, np.nan], index=exp_idx, name='s')
        idx = Index([4, 5, 6, 7], dtype='int64', name='idx')
        result = Series([0.1, 0.2, 0.3, 0.4], index=idx,
                        name='s').loc[[7, 2, 2]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        exp_idx = Index([4, 5, 5], dtype='int64', name='idx')
        expected = Series([0.4, np.nan, np.nan], index=exp_idx, name='s')
        idx = Index([1, 2, 3, 4], dtype='int64', name='idx')
        result = Series([0.1, 0.2, 0.3, 0.4], index=idx,
                        name='s').loc[[4, 5, 5]]
        tm.assert_series_equal(result, expected, check_index_type=True)

        # iloc
        exp_idx = Index([2, 2, 1, 1], dtype='int64', name='idx')
        expected = Series([0.2, 0.2, 0.1, 0.1], index=exp_idx, name='s')
        result = ser.iloc[[1, 1, 0, 0]]
        tm.assert_series_equal(result, expected, check_index_type=True)

    def test_partial_set_invalid(self):

        # GH 4940
        # allow only setting of 'valid' values

        orig = tm.makeTimeDataFrame()
        df = orig.copy()

        # don't allow not string inserts
        def f():
            with catch_warnings(record=True):
                df.loc[100.0, :] = df.ix[0]

        pytest.raises(TypeError, f)

        def f():
            with catch_warnings(record=True):
                df.loc[100, :] = df.ix[0]

        pytest.raises(TypeError, f)

        def f():
            with catch_warnings(record=True):
                df.ix[100.0, :] = df.ix[0]

        pytest.raises(TypeError, f)

        def f():
            with catch_warnings(record=True):
                df.ix[100, :] = df.ix[0]

        pytest.raises(ValueError, f)

        # allow object conversion here
        df = orig.copy()
        with catch_warnings(record=True):
            df.loc['a', :] = df.ix[0]
            exp = orig.append(pd.Series(df.ix[0], name='a'))
        tm.assert_frame_equal(df, exp)
        tm.assert_index_equal(df.index,
                              pd.Index(orig.index.tolist() + ['a']))
        assert df.index.dtype == 'object'

    def test_partial_set_empty_series(self):

        # GH5226

        # partially set with an empty object series
        s = Series()
        s.loc[1] = 1
        tm.assert_series_equal(s, Series([1], index=[1]))
        s.loc[3] = 3
        tm.assert_series_equal(s, Series([1, 3], index=[1, 3]))

        s = Series()
        s.loc[1] = 1.
        tm.assert_series_equal(s, Series([1.], index=[1]))
        s.loc[3] = 3.
        tm.assert_series_equal(s, Series([1., 3.], index=[1, 3]))

        s = Series()
        s.loc['foo'] = 1
        tm.assert_series_equal(s, Series([1], index=['foo']))
        s.loc['bar'] = 3
        tm.assert_series_equal(s, Series([1, 3], index=['foo', 'bar']))
        s.loc[3] = 4
        tm.assert_series_equal(s, Series([1, 3, 4], index=['foo', 'bar', 3]))

    def test_partial_set_empty_frame(self):

        # partially set with an empty object
        # frame
        df = DataFrame()

        def f():
            df.loc[1] = 1

        pytest.raises(ValueError, f)

        def f():
            df.loc[1] = Series([1], index=['foo'])

        pytest.raises(ValueError, f)

        def f():
            df.loc[:, 1] = 1

        pytest.raises(ValueError, f)

        # these work as they don't really change
        # anything but the index
        # GH5632
        expected = DataFrame(columns=['foo'], index=pd.Index(
            [], dtype='int64'))

        def f():
            df = DataFrame()
            df['foo'] = Series([], dtype='object')
            return df

        tm.assert_frame_equal(f(), expected)

        def f():
            df = DataFrame()
            df['foo'] = Series(df.index)
            return df

        tm.assert_frame_equal(f(), expected)

        def f():
            df = DataFrame()
            df['foo'] = df.index
            return df

        tm.assert_frame_equal(f(), expected)

        expected = DataFrame(columns=['foo'],
                             index=pd.Index([], dtype='int64'))
        expected['foo'] = expected['foo'].astype('float64')

        def f():
            df = DataFrame()
            df['foo'] = []
            return df

        tm.assert_frame_equal(f(), expected)

        def f():
            df = DataFrame()
            df['foo'] = Series(range(len(df)))
            return df

        tm.assert_frame_equal(f(), expected)

        def f():
            df = DataFrame()
            tm.assert_index_equal(df.index, pd.Index([], dtype='object'))
            df['foo'] = range(len(df))
            return df

        expected = DataFrame(columns=['foo'],
                             index=pd.Index([], dtype='int64'))
        expected['foo'] = expected['foo'].astype('float64')
        tm.assert_frame_equal(f(), expected)

        df = DataFrame()
        tm.assert_index_equal(df.columns, pd.Index([], dtype=object))
        df2 = DataFrame()
        df2[1] = Series([1], index=['foo'])
        df.loc[:, 1] = Series([1], index=['foo'])
        tm.assert_frame_equal(df, DataFrame([[1]], index=['foo'], columns=[1]))
        tm.assert_frame_equal(df, df2)

        # no index to start
        expected = DataFrame({0: Series(1, index=range(4))},
                             columns=['A', 'B', 0])

        df = DataFrame(columns=['A', 'B'])
        df[0] = Series(1, index=range(4))
        df.dtypes
        str(df)
        tm.assert_frame_equal(df, expected)

        df = DataFrame(columns=['A', 'B'])
        df.loc[:, 0] = Series(1, index=range(4))
        df.dtypes
        str(df)
        tm.assert_frame_equal(df, expected)

    def test_partial_set_empty_frame_row(self):
        # GH5720, GH5744
        # don't create rows when empty
        expected = DataFrame(columns=['A', 'B', 'New'],
                             index=pd.Index([], dtype='int64'))
        expected['A'] = expected['A'].astype('int64')
        expected['B'] = expected['B'].astype('float64')
        expected['New'] = expected['New'].astype('float64')

        df = DataFrame({"A": [1, 2, 3], "B": [1.2, 4.2, 5.2]})
        y = df[df.A > 5]
        y['New'] = np.nan
        tm.assert_frame_equal(y, expected)
        # tm.assert_frame_equal(y,expected)

        expected = DataFrame(columns=['a', 'b', 'c c', 'd'])
        expected['d'] = expected['d'].astype('int64')
        df = DataFrame(columns=['a', 'b', 'c c'])
        df['d'] = 3
        tm.assert_frame_equal(df, expected)
        tm.assert_series_equal(df['c c'], Series(name='c c', dtype=object))

        # reindex columns is ok
        df = DataFrame({"A": [1, 2, 3], "B": [1.2, 4.2, 5.2]})
        y = df[df.A > 5]
        result = y.reindex(columns=['A', 'B', 'C'])
        expected = DataFrame(columns=['A', 'B', 'C'],
                             index=pd.Index([], dtype='int64'))
        expected['A'] = expected['A'].astype('int64')
        expected['B'] = expected['B'].astype('float64')
        expected['C'] = expected['C'].astype('float64')
        tm.assert_frame_equal(result, expected)

    def test_partial_set_empty_frame_set_series(self):
        # GH 5756
        # setting with empty Series
        df = DataFrame(Series())
        tm.assert_frame_equal(df, DataFrame({0: Series()}))

        df = DataFrame(Series(name='foo'))
        tm.assert_frame_equal(df, DataFrame({'foo': Series()}))

    def test_partial_set_empty_frame_empty_copy_assignment(self):
        # GH 5932
        # copy on empty with assignment fails
        df = DataFrame(index=[0])
        df = df.copy()
        df['a'] = 0
        expected = DataFrame(0, index=[0], columns=['a'])
        tm.assert_frame_equal(df, expected)

    def test_partial_set_empty_frame_empty_consistencies(self):
        # GH 6171
        # consistency on empty frames
        df = DataFrame(columns=['x', 'y'])
        df['x'] = [1, 2]
        expected = DataFrame(dict(x=[1, 2], y=[np.nan, np.nan]))
        tm.assert_frame_equal(df, expected, check_dtype=False)

        df = DataFrame(columns=['x', 'y'])
        df['x'] = ['1', '2']
        expected = DataFrame(
            dict(x=['1', '2'], y=[np.nan, np.nan]), dtype=object)
        tm.assert_frame_equal(df, expected)

        df = DataFrame(columns=['x', 'y'])
        df.loc[0, 'x'] = 1
        expected = DataFrame(dict(x=[1], y=[np.nan]))
        tm.assert_frame_equal(df, expected, check_dtype=False)