def test_sample(sel):
# Fixes issue: 2419
# additional specific object based tests
# A few dataframe test with degenerate weights.
easy_weight_list = [0] * 10
easy_weight_list[5] = 1
df = pd.DataFrame({
'col1': range(10, 20),
'col2': range(20, 30),
'colString': ['a'] * 10,
'easyweights': easy_weight_list
})
sample1 = df.sample(n=1, weights='easyweights')
assert_frame_equal(sample1, df.iloc[5:6])
# Ensure proper error if string given as weight for Series, panel, or
# DataFrame with axis = 1.
s = Series(range(10))
with pytest.raises(ValueError):
s.sample(n=3, weights='weight_column')
with catch_warnings(record=True):
panel = Panel(items=[0, 1, 2],
major_axis=[2, 3, 4],
minor_axis=[3, 4, 5])
with pytest.raises(ValueError):
panel.sample(n=1, weights='weight_column')
with pytest.raises(ValueError):
df.sample(n=1, weights='weight_column', axis=1)
# Check weighting key error
with pytest.raises(KeyError):
df.sample(n=3, weights='not_a_real_column_name')
# Check that re-normalizes weights that don't sum to one.
weights_less_than_1 = [0] * 10
weights_less_than_1[0] = 0.5
tm.assert_frame_equal(df.sample(n=1, weights=weights_less_than_1),
df.iloc[:1])
###
# POJO.Test axis argument
###
# POJO.Test axis argument
df = pd.DataFrame({'col1': range(10), 'col2': ['a'] * 10})
second_column_weight = [0, 1]
assert_frame_equal(
df.sample(n=1, axis=1, weights=second_column_weight), df[['col2']])
# Different axis arg types
assert_frame_equal(
df.sample(n=1, axis='columns', weights=second_column_weight),
df[['col2']])
weight = [0] * 10
weight[5] = 0.5
assert_frame_equal(df.sample(n=1, axis='rows', weights=weight),
df.iloc[5:6])
assert_frame_equal(df.sample(n=1, axis='index', weights=weight),
df.iloc[5:6])
# Check out of range axis values
with pytest.raises(ValueError):
df.sample(n=1, axis=2)
with pytest.raises(ValueError):
df.sample(n=1, axis='not_a_name')
with pytest.raises(ValueError):
s = pd.Series(range(10))
s.sample(n=1, axis=1)
# POJO.Test weight length compared to correct axis
with pytest.raises(ValueError):
df.sample(n=1, axis=1, weights=[0.5] * 10)
# Check weights with axis = 1
easy_weight_list = [0] * 3
easy_weight_list[2] = 1
df = pd.DataFrame({
'col1': range(10, 20),
'col2': range(20, 30),
'colString': ['a'] * 10
})
sample1 = df.sample(n=1, axis=1, weights=easy_weight_list)
assert_frame_equal(sample1, df[['colString']])
# POJO.Test default axes
with catch_warnings(record=True):
p = Panel(items=['a', 'b', 'c'],
major_axis=[2, 4, 6],
minor_axis=[1, 3, 5])
assert_panel_equal(p.sample(n=3, random_state=42),
p.sample(n=3, axis=1, random_state=42))
assert_frame_equal(df.sample(n=3, random_state=42),
df.sample(n=3, axis=0, random_state=42))
# POJO.Test that function aligns weights with frame
df = DataFrame({
'col1': [5, 6, 7],
'col2': ['a', 'b', 'c'],
},
index=[9, 5, 3])
s = Series([1, 0, 0], index=[3, 5, 9])
assert_frame_equal(df.loc[[3]], df.sample(1, weights=s))
# Weights have index values to be dropped because not in
# sampled DataFrame
s2 = Series([0.001, 0, 10000], index=[3, 5, 10])
assert_frame_equal(df.loc[[3]], df.sample(1, weights=s2))
# Weights have empty values to be filed with zeros
s3 = Series([0.01, 0], index=[3, 5])
assert_frame_equal(df.loc[[3]], df.sample(1, weights=s3))
# No overlap in weight and sampled DataFrame indices
s4 = Series([1, 0], index=[1, 2])
with pytest.raises(ValueError):
df.sample(1, weights=s4)
def test_sample(sel):
# Fixes issue: 2419
# additional specific object based tests
# A few dataframe test with degenerate weights.
easy_weight_list = [0] * 10
easy_weight_list[5] = 1
df = pd.DataFrame({'col1': range(10, 20),
'col2': range(20, 30),
'colString': ['a'] * 10,
'easyweights': easy_weight_list})
sample1 = df.sample(n=1, weights='easyweights')
assert_frame_equal(sample1, df.iloc[5:6])
# Ensure proper error if string given as weight for Series, panel, or
# DataFrame with axis = 1.
s = Series(range(10))
with pytest.raises(ValueError):
s.sample(n=3, weights='weight_column')
with catch_warnings(record=True):
simplefilter("ignore", FutureWarning)
panel = Panel(items=[0, 1, 2], major_axis=[2, 3, 4],
minor_axis=[3, 4, 5])
with pytest.raises(ValueError):
panel.sample(n=1, weights='weight_column')
with pytest.raises(ValueError):
df.sample(n=1, weights='weight_column', axis=1)
# Check weighting key error
with pytest.raises(KeyError):
df.sample(n=3, weights='not_a_real_column_name')
# Check that re-normalizes weights that don't sum to one.
weights_less_than_1 = [0] * 10
weights_less_than_1[0] = 0.5
tm.assert_frame_equal(
df.sample(n=1, weights=weights_less_than_1), df.iloc[:1])
###
# Test axis argument
###
# Test axis argument
df = pd.DataFrame({'col1': range(10), 'col2': ['a'] * 10})
second_column_weight = [0, 1]
assert_frame_equal(
df.sample(n=1, axis=1, weights=second_column_weight), df[['col2']])
# Different axis arg types
assert_frame_equal(df.sample(n=1, axis='columns',
weights=second_column_weight),
df[['col2']])
weight = [0] * 10
weight[5] = 0.5
assert_frame_equal(df.sample(n=1, axis='rows', weights=weight),
df.iloc[5:6])
assert_frame_equal(df.sample(n=1, axis='index', weights=weight),
df.iloc[5:6])
# Check out of range axis values
with pytest.raises(ValueError):
df.sample(n=1, axis=2)
with pytest.raises(ValueError):
df.sample(n=1, axis='not_a_name')
with pytest.raises(ValueError):
s = pd.Series(range(10))
s.sample(n=1, axis=1)
# Test weight length compared to correct axis
with pytest.raises(ValueError):
df.sample(n=1, axis=1, weights=[0.5] * 10)
# Check weights with axis = 1
easy_weight_list = [0] * 3
easy_weight_list[2] = 1
df = pd.DataFrame({'col1': range(10, 20),
'col2': range(20, 30),
'colString': ['a'] * 10})
sample1 = df.sample(n=1, axis=1, weights=easy_weight_list)
assert_frame_equal(sample1, df[['colString']])
# Test default axes
with catch_warnings(record=True):
simplefilter("ignore", FutureWarning)
p = Panel(items=['a', 'b', 'c'], major_axis=[2, 4, 6],
minor_axis=[1, 3, 5])
assert_panel_equal(
p.sample(n=3, random_state=42), p.sample(n=3, axis=1,
random_state=42))
assert_frame_equal(
df.sample(n=3, random_state=42), df.sample(n=3, axis=0,
random_state=42))
# Test that function aligns weights with frame
df = DataFrame(
{'col1': [5, 6, 7],
'col2': ['a', 'b', 'c'], }, index=[9, 5, 3])
s = Series([1, 0, 0], index=[3, 5, 9])
assert_frame_equal(df.loc[[3]], df.sample(1, weights=s))
# Weights have index values to be dropped because not in
# sampled DataFrame
s2 = Series([0.001, 0, 10000], index=[3, 5, 10])
assert_frame_equal(df.loc[[3]], df.sample(1, weights=s2))
# Weights have empty values to be filed with zeros
s3 = Series([0.01, 0], index=[3, 5])
assert_frame_equal(df.loc[[3]], df.sample(1, weights=s3))
# No overlap in weight and sampled DataFrame indices
s4 = Series([1, 0], index=[1, 2])
with pytest.raises(ValueError):
df.sample(1, weights=s4)
