147 lines
3.8 KiB
Python
147 lines
3.8 KiB
Python
import numpy as np
|
|
|
|
import pandas as pd
|
|
import pandas._testing as tm
|
|
|
|
|
|
def test_data_frame_value_counts_unsorted():
|
|
df = pd.DataFrame(
|
|
{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
|
|
index=["falcon", "dog", "cat", "ant"],
|
|
)
|
|
|
|
result = df.value_counts(sort=False)
|
|
expected = pd.Series(
|
|
data=[1, 2, 1],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[(2, 4, 6), (2, 0, 0)], names=["num_legs", "num_wings"]
|
|
),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_ascending():
|
|
df = pd.DataFrame(
|
|
{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
|
|
index=["falcon", "dog", "cat", "ant"],
|
|
)
|
|
|
|
result = df.value_counts(ascending=True)
|
|
expected = pd.Series(
|
|
data=[1, 1, 2],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[(2, 6, 4), (2, 0, 0)], names=["num_legs", "num_wings"]
|
|
),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_default():
|
|
df = pd.DataFrame(
|
|
{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
|
|
index=["falcon", "dog", "cat", "ant"],
|
|
)
|
|
|
|
result = df.value_counts()
|
|
expected = pd.Series(
|
|
data=[2, 1, 1],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[(4, 2, 6), (0, 2, 0)], names=["num_legs", "num_wings"]
|
|
),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_normalize():
|
|
df = pd.DataFrame(
|
|
{"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
|
|
index=["falcon", "dog", "cat", "ant"],
|
|
)
|
|
|
|
result = df.value_counts(normalize=True)
|
|
expected = pd.Series(
|
|
data=[0.5, 0.25, 0.25],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[(4, 2, 6), (0, 2, 0)], names=["num_legs", "num_wings"]
|
|
),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_single_col_default():
|
|
df = pd.DataFrame({"num_legs": [2, 4, 4, 6]})
|
|
|
|
result = df.value_counts()
|
|
expected = pd.Series(
|
|
data=[2, 1, 1],
|
|
index=pd.MultiIndex.from_arrays([[4, 2, 6]], names=["num_legs"]),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_empty():
|
|
df_no_cols = pd.DataFrame()
|
|
|
|
result = df_no_cols.value_counts()
|
|
expected = pd.Series([], dtype=np.int64)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_empty_normalize():
|
|
df_no_cols = pd.DataFrame()
|
|
|
|
result = df_no_cols.value_counts(normalize=True)
|
|
expected = pd.Series([], dtype=np.float64)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_dropna_true(nulls_fixture):
|
|
# GH 41334
|
|
df = pd.DataFrame(
|
|
{
|
|
"first_name": ["John", "Anne", "John", "Beth"],
|
|
"middle_name": ["Smith", nulls_fixture, nulls_fixture, "Louise"],
|
|
},
|
|
)
|
|
result = df.value_counts()
|
|
expected = pd.Series(
|
|
data=[1, 1],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[("Beth", "John"), ("Louise", "Smith")], names=["first_name", "middle_name"]
|
|
),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
|
|
def test_data_frame_value_counts_dropna_false(nulls_fixture):
|
|
# GH 41334
|
|
df = pd.DataFrame(
|
|
{
|
|
"first_name": ["John", "Anne", "John", "Beth"],
|
|
"middle_name": ["Smith", nulls_fixture, nulls_fixture, "Louise"],
|
|
},
|
|
)
|
|
|
|
result = df.value_counts(dropna=False)
|
|
expected = pd.Series(
|
|
data=[1, 1, 1, 1],
|
|
index=pd.MultiIndex(
|
|
levels=[
|
|
pd.Index(["Anne", "Beth", "John"]),
|
|
pd.Index(["Louise", "Smith", nulls_fixture]),
|
|
],
|
|
codes=[[0, 1, 2, 2], [2, 0, 1, 2]],
|
|
names=["first_name", "middle_name"],
|
|
),
|
|
)
|
|
|
|
tm.assert_series_equal(result, expected)
|