You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
85 lines
2.9 KiB
85 lines
2.9 KiB
import pytest
|
|
|
|
from pandas import DataFrame
|
|
import pandas._testing as tm
|
|
|
|
|
|
class TestAssign:
|
|
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]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# lambda syntax
|
|
result = df.assign(C=lambda x: x.B / x.A)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# original is unmodified
|
|
tm.assert_frame_equal(df, original)
|
|
|
|
# Non-Series array-like
|
|
result = df.assign(C=[4, 2.5, 2])
|
|
tm.assert_frame_equal(result, expected)
|
|
# original is unmodified
|
|
tm.assert_frame_equal(df, original)
|
|
|
|
result = df.assign(B=df.B / df.A)
|
|
expected = expected.drop("B", axis=1).rename(columns={"C": "B"})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# overwrite
|
|
result = df.assign(A=df.A + df.B)
|
|
expected = df.copy()
|
|
expected["A"] = [5, 7, 9]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# lambda
|
|
result = df.assign(A=lambda x: x.A + x.B)
|
|
tm.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")
|
|
)
|
|
tm.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)
|
|
|
|
expected = DataFrame([[1, 2, 3, -1], [3, 4, 7, -1]], columns=list("ABDC"))
|
|
tm.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"))
|
|
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_assign_bad(self):
|
|
df = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
|
|
|
|
# non-keyword argument
|
|
msg = r"assign\(\) takes 1 positional argument but 2 were given"
|
|
with pytest.raises(TypeError, match=msg):
|
|
df.assign(lambda x: x.A)
|
|
msg = "'DataFrame' object has no attribute 'C'"
|
|
with pytest.raises(AttributeError, match=msg):
|
|
df.assign(C=df.A, D=df.A + df.C)
|
|
|
|
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"))
|
|
tm.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"))
|
|
tm.assert_frame_equal(result, expected)
|