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.
86 lines
2.9 KiB
86 lines
2.9 KiB
6 months ago
|
import numpy as np
|
||
|
|
|
||
|
|
from pandas import (
|
||
|
|
DataFrame,
|
||
|
|
date_range,
|
||
|
|
)
|
||
|
|
import pandas._testing as tm
|
||
|
|
|
||
|
|
|
||
|
|
class TestEquals:
|
||
|
|
def test_dataframe_not_equal(self):
|
||
|
|
# see GH#28839
|
||
|
|
df1 = DataFrame({"a": [1, 2], "b": ["s", "d"]})
|
||
|
|
df2 = DataFrame({"a": ["s", "d"], "b": [1, 2]})
|
||
|
|
assert df1.equals(df2) is False
|
||
|
|
|
||
|
|
def test_equals_different_blocks(self, using_array_manager, using_infer_string):
|
||
|
|
# GH#9330
|
||
|
|
df0 = DataFrame({"A": ["x", "y"], "B": [1, 2], "C": ["w", "z"]})
|
||
|
|
df1 = df0.reset_index()[["A", "B", "C"]]
|
||
|
|
if not using_array_manager and not using_infer_string:
|
||
|
|
# this assert verifies that the above operations have
|
||
|
|
# induced a block rearrangement
|
||
|
|
assert df0._mgr.blocks[0].dtype != df1._mgr.blocks[0].dtype
|
||
|
|
|
||
|
|
# do the real tests
|
||
|
|
tm.assert_frame_equal(df0, df1)
|
||
|
|
assert df0.equals(df1)
|
||
|
|
assert df1.equals(df0)
|
||
|
|
|
||
|
|
def test_equals(self):
|
||
|
|
# Add object dtype column with nans
|
||
|
|
index = np.random.default_rng(2).random(10)
|
||
|
|
df1 = DataFrame(
|
||
|
|
np.random.default_rng(2).random(10), index=index, columns=["floats"]
|
||
|
|
)
|
||
|
|
df1["text"] = "the sky is so blue. we could use more chocolate.".split()
|
||
|
|
df1["start"] = date_range("2000-1-1", periods=10, freq="min")
|
||
|
|
df1["end"] = date_range("2000-1-1", periods=10, freq="D")
|
||
|
|
df1["diff"] = df1["end"] - df1["start"]
|
||
|
|
# Explicitly cast to object, to avoid implicit cast when setting np.nan
|
||
|
|
df1["bool"] = (np.arange(10) % 3 == 0).astype(object)
|
||
|
|
df1.loc[::2] = np.nan
|
||
|
|
df2 = df1.copy()
|
||
|
|
assert df1["text"].equals(df2["text"])
|
||
|
|
assert df1["start"].equals(df2["start"])
|
||
|
|
assert df1["end"].equals(df2["end"])
|
||
|
|
assert df1["diff"].equals(df2["diff"])
|
||
|
|
assert df1["bool"].equals(df2["bool"])
|
||
|
|
assert df1.equals(df2)
|
||
|
|
assert not df1.equals(object)
|
||
|
|
|
||
|
|
# different dtype
|
||
|
|
different = df1.copy()
|
||
|
|
different["floats"] = different["floats"].astype("float32")
|
||
|
|
assert not df1.equals(different)
|
||
|
|
|
||
|
|
# different index
|
||
|
|
different_index = -index
|
||
|
|
different = df2.set_index(different_index)
|
||
|
|
assert not df1.equals(different)
|
||
|
|
|
||
|
|
# different columns
|
||
|
|
different = df2.copy()
|
||
|
|
different.columns = df2.columns[::-1]
|
||
|
|
assert not df1.equals(different)
|
||
|
|
|
||
|
|
# DatetimeIndex
|
||
|
|
index = date_range("2000-1-1", periods=10, freq="min")
|
||
|
|
df1 = df1.set_index(index)
|
||
|
|
df2 = df1.copy()
|
||
|
|
assert df1.equals(df2)
|
||
|
|
|
||
|
|
# MultiIndex
|
||
|
|
df3 = df1.set_index(["text"], append=True)
|
||
|
|
df2 = df1.set_index(["text"], append=True)
|
||
|
|
assert df3.equals(df2)
|
||
|
|
|
||
|
|
df2 = df1.set_index(["floats"], append=True)
|
||
|
|
assert not df3.equals(df2)
|
||
|
|
|
||
|
|
# NaN in index
|
||
|
|
df3 = df1.set_index(["floats"], append=True)
|
||
|
|
df2 = df1.set_index(["floats"], append=True)
|
||
|
|
assert df3.equals(df2)
|