laywerrobot/lib/python3.6/site-packages/pandas/tests/frame/test_mutate_columns.py

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2020-08-27 21:55:39 +02:00
# -*- coding: utf-8 -*-
from __future__ import print_function
import pytest
from pandas.compat import range, lrange
import numpy as np
from pandas.compat import PY36
from pandas import DataFrame, Series, Index, MultiIndex
from pandas.util.testing import assert_frame_equal
import pandas.util.testing as tm
from pandas.tests.frame.common import TestData
# Column add, remove, delete.
class TestDataFrameMutateColumns(TestData):
def test_assign(self):
df = DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
original = df.copy()
result = df.assign(C=df.B / df.A)
expected = df.copy()
expected['C'] = [4, 2.5, 2]
assert_frame_equal(result, expected)
# lambda syntax
result = df.assign(C=lambda x: x.B / x.A)
assert_frame_equal(result, expected)
# original is unmodified
assert_frame_equal(df, original)
# Non-Series array-like
result = df.assign(C=[4, 2.5, 2])
assert_frame_equal(result, expected)
# original is unmodified
assert_frame_equal(df, original)
result = df.assign(B=df.B / df.A)
expected = expected.drop('B', axis=1).rename(columns={'C': 'B'})
assert_frame_equal(result, expected)
# overwrite
result = df.assign(A=df.A + df.B)
expected = df.copy()
expected['A'] = [5, 7, 9]
assert_frame_equal(result, expected)
# lambda
result = df.assign(A=lambda x: x.A + x.B)
assert_frame_equal(result, expected)
def test_assign_multiple(self):
df = DataFrame([[1, 4], [2, 5], [3, 6]], columns=['A', 'B'])
result = df.assign(C=[7, 8, 9], D=df.A, E=lambda x: x.B)
expected = DataFrame([[1, 4, 7, 1, 4], [2, 5, 8, 2, 5],
[3, 6, 9, 3, 6]], columns=list('ABCDE'))
assert_frame_equal(result, expected)
def test_assign_order(self):
# GH 9818
df = DataFrame([[1, 2], [3, 4]], columns=['A', 'B'])
result = df.assign(D=df.A + df.B, C=df.A - df.B)
if PY36:
expected = DataFrame([[1, 2, 3, -1], [3, 4, 7, -1]],
columns=list('ABDC'))
else:
expected = DataFrame([[1, 2, -1, 3], [3, 4, -1, 7]],
columns=list('ABCD'))
assert_frame_equal(result, expected)
result = df.assign(C=df.A - df.B, D=df.A + df.B)
expected = DataFrame([[1, 2, -1, 3], [3, 4, -1, 7]],
columns=list('ABCD'))
assert_frame_equal(result, expected)
def test_assign_bad(self):
df = DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
# non-keyword argument
with pytest.raises(TypeError):
df.assign(lambda x: x.A)
with pytest.raises(AttributeError):
df.assign(C=df.A, D=df.A + df.C)
@pytest.mark.skipif(PY36, reason="""Issue #14207: valid for python
3.6 and above""")
def test_assign_dependent_old_python(self):
df = DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
# Key C does not exist at definition time of df
with pytest.raises(KeyError):
df.assign(C=lambda df: df.A,
D=lambda df: df['A'] + df['C'])
with pytest.raises(KeyError):
df.assign(C=df.A, D=lambda x: x['A'] + x['C'])
@pytest.mark.skipif(not PY36, reason="""Issue #14207: not valid for
python 3.5 and below""")
def test_assign_dependent(self):
df = DataFrame({'A': [1, 2], 'B': [3, 4]})
result = df.assign(C=df.A, D=lambda x: x['A'] + x['C'])
expected = DataFrame([[1, 3, 1, 2], [2, 4, 2, 4]],
columns=list('ABCD'))
assert_frame_equal(result, expected)
result = df.assign(C=lambda df: df.A,
D=lambda df: df['A'] + df['C'])
expected = DataFrame([[1, 3, 1, 2], [2, 4, 2, 4]],
columns=list('ABCD'))
assert_frame_equal(result, expected)
def test_insert_error_msmgs(self):
# GH 7432
df = DataFrame({'foo': ['a', 'b', 'c'], 'bar': [
1, 2, 3], 'baz': ['d', 'e', 'f']}).set_index('foo')
s = DataFrame({'foo': ['a', 'b', 'c', 'a'], 'fiz': [
'g', 'h', 'i', 'j']}).set_index('foo')
msg = 'cannot reindex from a duplicate axis'
with tm.assert_raises_regex(ValueError, msg):
df['newcol'] = s
# GH 4107, more descriptive error message
df = DataFrame(np.random.randint(0, 2, (4, 4)),
columns=['a', 'b', 'c', 'd'])
msg = 'incompatible index of inserted column with frame index'
with tm.assert_raises_regex(TypeError, msg):
df['gr'] = df.groupby(['b', 'c']).count()
def test_insert_benchmark(self):
# from the vb_suite/frame_methods/frame_insert_columns
N = 10
K = 5
df = DataFrame(index=lrange(N))
new_col = np.random.randn(N)
for i in range(K):
df[i] = new_col
expected = DataFrame(np.repeat(new_col, K).reshape(N, K),
index=lrange(N))
assert_frame_equal(df, expected)
def test_insert(self):
df = DataFrame(np.random.randn(5, 3), index=np.arange(5),
columns=['c', 'b', 'a'])
df.insert(0, 'foo', df['a'])
tm.assert_index_equal(df.columns, Index(['foo', 'c', 'b', 'a']))
tm.assert_series_equal(df['a'], df['foo'], check_names=False)
df.insert(2, 'bar', df['c'])
tm.assert_index_equal(df.columns,
Index(['foo', 'c', 'bar', 'b', 'a']))
tm.assert_almost_equal(df['c'], df['bar'], check_names=False)
# diff dtype
# new item
df['x'] = df['a'].astype('float32')
result = Series(dict(float32=1, float64=5))
assert (df.get_dtype_counts().sort_index() == result).all()
# replacing current (in different block)
df['a'] = df['a'].astype('float32')
result = Series(dict(float32=2, float64=4))
assert (df.get_dtype_counts().sort_index() == result).all()
df['y'] = df['a'].astype('int32')
result = Series(dict(float32=2, float64=4, int32=1))
assert (df.get_dtype_counts().sort_index() == result).all()
with tm.assert_raises_regex(ValueError, 'already exists'):
df.insert(1, 'a', df['b'])
pytest.raises(ValueError, df.insert, 1, 'c', df['b'])
df.columns.name = 'some_name'
# preserve columns name field
df.insert(0, 'baz', df['c'])
assert df.columns.name == 'some_name'
# GH 13522
df = DataFrame(index=['A', 'B', 'C'])
df['X'] = df.index
df['X'] = ['x', 'y', 'z']
exp = DataFrame(data={'X': ['x', 'y', 'z']}, index=['A', 'B', 'C'])
assert_frame_equal(df, exp)
def test_delitem(self):
del self.frame['A']
assert 'A' not in self.frame
def test_delitem_multiindex(self):
midx = MultiIndex.from_product([['A', 'B'], [1, 2]])
df = DataFrame(np.random.randn(4, 4), columns=midx)
assert len(df.columns) == 4
assert ('A', ) in df.columns
assert 'A' in df.columns
result = df['A']
assert isinstance(result, DataFrame)
del df['A']
assert len(df.columns) == 2
# A still in the levels, BUT get a KeyError if trying
# to delete
assert ('A', ) not in df.columns
with pytest.raises(KeyError):
del df[('A',)]
# behavior of dropped/deleted MultiIndex levels changed from
# GH 2770 to GH 19027: MultiIndex no longer '.__contains__'
# levels which are dropped/deleted
assert 'A' not in df.columns
with pytest.raises(KeyError):
del df['A']
def test_pop(self):
self.frame.columns.name = 'baz'
self.frame.pop('A')
assert 'A' not in self.frame
self.frame['foo'] = 'bar'
self.frame.pop('foo')
assert 'foo' not in self.frame
# TODO assert self.frame.columns.name == 'baz'
# gh-10912: inplace ops cause caching issue
a = DataFrame([[1, 2, 3], [4, 5, 6]], columns=[
'A', 'B', 'C'], index=['X', 'Y'])
b = a.pop('B')
b += 1
# original frame
expected = DataFrame([[1, 3], [4, 6]], columns=[
'A', 'C'], index=['X', 'Y'])
tm.assert_frame_equal(a, expected)
# result
expected = Series([2, 5], index=['X', 'Y'], name='B') + 1
tm.assert_series_equal(b, expected)
def test_pop_non_unique_cols(self):
df = DataFrame({0: [0, 1], 1: [0, 1], 2: [4, 5]})
df.columns = ["a", "b", "a"]
res = df.pop("a")
assert type(res) == DataFrame
assert len(res) == 2
assert len(df.columns) == 1
assert "b" in df.columns
assert "a" not in df.columns
assert len(df.index) == 2
def test_insert_column_bug_4032(self):
# GH4032, inserting a column and renaming causing errors
df = DataFrame({'b': [1.1, 2.2]})
df = df.rename(columns={})
df.insert(0, 'a', [1, 2])
result = df.rename(columns={})
str(result)
expected = DataFrame([[1, 1.1], [2, 2.2]], columns=['a', 'b'])
assert_frame_equal(result, expected)
df.insert(0, 'c', [1.3, 2.3])
result = df.rename(columns={})
str(result)
expected = DataFrame([[1.3, 1, 1.1], [2.3, 2, 2.2]],
columns=['c', 'a', 'b'])
assert_frame_equal(result, expected)