Inzynierka/Lib/site-packages/pandas/tests/apply/test_frame_apply_relabeling.py

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2023-06-02 12:51:02 +02:00
import numpy as np
import pytest
from pandas.compat import is_numpy_dev
import pandas as pd
import pandas._testing as tm
def test_agg_relabel():
# GH 26513
df = pd.DataFrame({"A": [1, 2, 1, 2], "B": [1, 2, 3, 4], "C": [3, 4, 5, 6]})
# simplest case with one column, one func
result = df.agg(foo=("B", "sum"))
expected = pd.DataFrame({"B": [10]}, index=pd.Index(["foo"]))
tm.assert_frame_equal(result, expected)
# test on same column with different methods
result = df.agg(foo=("B", "sum"), bar=("B", "min"))
expected = pd.DataFrame({"B": [10, 1]}, index=pd.Index(["foo", "bar"]))
tm.assert_frame_equal(result, expected)
def test_agg_relabel_multi_columns_multi_methods():
# GH 26513, test on multiple columns with multiple methods
df = pd.DataFrame({"A": [1, 2, 1, 2], "B": [1, 2, 3, 4], "C": [3, 4, 5, 6]})
result = df.agg(
foo=("A", "sum"),
bar=("B", "mean"),
cat=("A", "min"),
dat=("B", "max"),
f=("A", "max"),
g=("C", "min"),
)
expected = pd.DataFrame(
{
"A": [6.0, np.nan, 1.0, np.nan, 2.0, np.nan],
"B": [np.nan, 2.5, np.nan, 4.0, np.nan, np.nan],
"C": [np.nan, np.nan, np.nan, np.nan, np.nan, 3.0],
},
index=pd.Index(["foo", "bar", "cat", "dat", "f", "g"]),
)
tm.assert_frame_equal(result, expected)
@pytest.mark.xfail(is_numpy_dev, reason="name of min now equals name of np.min")
def test_agg_relabel_partial_functions():
# GH 26513, test on partial, functools or more complex cases
df = pd.DataFrame({"A": [1, 2, 1, 2], "B": [1, 2, 3, 4], "C": [3, 4, 5, 6]})
result = df.agg(foo=("A", np.mean), bar=("A", "mean"), cat=("A", min))
expected = pd.DataFrame(
{"A": [1.5, 1.5, 1.0]}, index=pd.Index(["foo", "bar", "cat"])
)
tm.assert_frame_equal(result, expected)
result = df.agg(
foo=("A", min),
bar=("A", np.min),
cat=("B", max),
dat=("C", "min"),
f=("B", np.sum),
kk=("B", lambda x: min(x)),
)
expected = pd.DataFrame(
{
"A": [1.0, 1.0, np.nan, np.nan, np.nan, np.nan],
"B": [np.nan, np.nan, 4.0, np.nan, 10.0, 1.0],
"C": [np.nan, np.nan, np.nan, 3.0, np.nan, np.nan],
},
index=pd.Index(["foo", "bar", "cat", "dat", "f", "kk"]),
)
tm.assert_frame_equal(result, expected)
def test_agg_namedtuple():
# GH 26513
df = pd.DataFrame({"A": [0, 1], "B": [1, 2]})
result = df.agg(
foo=pd.NamedAgg("B", "sum"),
bar=pd.NamedAgg("B", min),
cat=pd.NamedAgg(column="B", aggfunc="count"),
fft=pd.NamedAgg("B", aggfunc="max"),
)
expected = pd.DataFrame(
{"B": [3, 1, 2, 2]}, index=pd.Index(["foo", "bar", "cat", "fft"])
)
tm.assert_frame_equal(result, expected)
result = df.agg(
foo=pd.NamedAgg("A", "min"),
bar=pd.NamedAgg(column="B", aggfunc="max"),
cat=pd.NamedAgg(column="A", aggfunc="max"),
)
expected = pd.DataFrame(
{"A": [0.0, np.nan, 1.0], "B": [np.nan, 2.0, np.nan]},
index=pd.Index(["foo", "bar", "cat"]),
)
tm.assert_frame_equal(result, expected)