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Version:
0.21.1 ▾
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"""
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 equiv to .reindex
expected = Series([np.nan, 0.2, np.nan], index=[3, 2, 3])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = ser.loc[[3, 2, 3]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = ser.reindex([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'])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = ser.loc[[3, 2, 3, 'x']]
tm.assert_series_equal(result, expected, check_index_type=True)
result = ser.reindex([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])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = ser.loc[[2, 2, 'x', 1]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = ser.reindex([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])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = ser.loc[[2, 2, 3]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = ser.reindex([2, 2, 3])
tm.assert_series_equal(result, expected, check_index_type=True)
s = Series([0.1, 0.2, 0.3], index=[1, 2, 3])
expected = Series([0.3, np.nan, np.nan], index=[3, 4, 4])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = s.loc[[3, 4, 4]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = s.reindex([3, 4, 4])
tm.assert_series_equal(result, expected, check_index_type=True)
s = Series([0.1, 0.2, 0.3, 0.4],
index=[1, 2, 3, 4])
expected = Series([np.nan, 0.3, 0.3], index=[5, 3, 3])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = s.loc[[5, 3, 3]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = s.reindex([5, 3, 3])
tm.assert_series_equal(result, expected, check_index_type=True)
s = Series([0.1, 0.2, 0.3, 0.4],
index=[1, 2, 3, 4])
expected = Series([np.nan, 0.4, 0.4], index=[5, 4, 4])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = s.loc[[5, 4, 4]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = s.reindex([5, 4, 4])
tm.assert_series_equal(result, expected, check_index_type=True)
s = Series([0.1, 0.2, 0.3, 0.4],
index=[4, 5, 6, 7])
expected = Series([0.4, np.nan, np.nan], index=[7, 2, 2])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = s.loc[[7, 2, 2]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = s.reindex([7, 2, 2])
tm.assert_series_equal(result, expected, check_index_type=True)
s = Series([0.1, 0.2, 0.3, 0.4],
index=[1, 2, 3, 4])
expected = Series([0.4, np.nan, np.nan], index=[4, 5, 5])
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = s.loc[[4, 5, 5]]
tm.assert_series_equal(result, expected, check_index_type=True)
result = s.reindex([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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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')
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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(np.arange(len(df)), dtype='float64')
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)