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# BSD 3-Clause License; see https://github.com/scikit-hep/awkward/blob/main/LICENSE
from __future__ import annotations
import numpy as np
import pytest
import awkward as ak
to_list = ak.operations.to_list
pandas = pytest.importorskip("pandas")
def test():
simple = ak.Array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5])
assert ak.operations.to_dataframe(simple)["values"].values.tolist() == [
0.0,
1.1,
2.2,
3.3,
4.4,
5.5,
]
index = ak.index.Index64(np.array([3, 3, 1, 5], dtype=np.int64))
indexed = ak.Array(ak.contents.IndexedArray(index, simple.layout))
assert indexed.to_list() == [3.3, 3.3, 1.1, 5.5]
assert ak.operations.to_dataframe(indexed)["values"].values.tolist() == [
3.3,
3.3,
1.1,
5.5,
]
tuples = ak.Array(
ak.contents.RecordArray([simple.layout, simple.layout], fields=None)
)
assert ak.operations.to_dataframe(tuples)["1"].values.tolist() == [
0.0,
1.1,
2.2,
3.3,
4.4,
5.5,
]
offsets = ak.index.Index64(np.array([0, 1, 1, 3, 4], dtype=np.int64))
nested = ak.Array(ak.contents.ListOffsetArray(offsets, indexed.layout))
assert ak.operations.to_dataframe(nested)["values"].values.tolist() == [
3.3,
3.3,
1.1,
5.5,
]
offsets2 = ak.index.Index64(np.array([0, 3, 3, 4, 6], dtype=np.int64))
nested2 = ak.Array(ak.contents.ListOffsetArray(offsets2, tuples.layout))
assert ak.operations.to_dataframe(nested2)["1"].values.tolist() == [
0.0,
1.1,
2.2,
3.3,
4.4,
5.5,
]
recrec = ak.Array([{"x": {"y": 1}}, {"x": {"y": 2}}, {"x": {"y": 3}}])
assert ak.operations.to_dataframe(recrec)["x", "y"].values.tolist() == [
1,
2,
3,
]
recrec2 = ak.Array(
[
{"x": {"a": 1, "b": 2}, "y": {"c": 3, "d": 4}},
{"x": {"a": 10, "b": 20}, "y": {"c": 30, "d": 40}},
]
)
assert ak.operations.to_dataframe(recrec2)["y", "c"].values.tolist() == [
3,
30,
]
recrec3 = ak.Array(
[{"x": 1, "y": {"c": 3, "d": 4}}, {"x": 10, "y": {"c": 30, "d": 40}}]
)
assert ak.operations.to_dataframe(recrec3)["y", "c"].values.tolist() == [
3,
30,
]
tuptup = ak.Array([(1.0, (1.1, 1.2)), (2.0, (2.1, 2.2)), (3.0, (3.1, 3.2))])
assert ak.operations.to_dataframe(tuptup)["1", "0"].values.tolist() == [
1.1,
2.1,
3.1,
]
recrec4 = ak.Array(
[[{"x": 1, "y": {"c": 3, "d": 4}}], [{"x": 10, "y": {"c": 30, "d": 40}}]]
)
assert ak.operations.to_dataframe(recrec4)["y", "c"].values.tolist() == [
3,
30,
]
def test_broken():
ex = ak.Array([[1, 2, 3], [], [4, 5]])
p4 = ak.operations.zip({"x": ex})
p4c = ak.operations.cartesian({"a": p4, "b": p4})
df = ak.operations.to_dataframe(p4c)
assert df["a", "x"].values.tolist() == [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 5, 5]
assert df["b", "x"].values.tolist() == [1, 2, 3, 1, 2, 3, 1, 2, 3, 4, 5, 4, 5]
def test_union_to_record():
from awkward.operations.ak_to_dataframe import _union_to_record as union_to_record
recordarray1 = ak.Array([{"x": 1, "y": 1.1}, {"x": 3, "y": 3.3}]).layout
recordarray2 = ak.Array([{"y": 2.2, "z": 999}]).layout
tags = ak.index.Index8(np.array([0, 1, 0], dtype=np.int8))
index = ak.index.Index64(np.array([0, 0, 1], dtype=np.int64))
unionarray = ak.contents.UnionArray(tags, index, [recordarray1, recordarray2])
assert to_list(unionarray) == [
{"x": 1, "y": 1.1},
{"y": 2.2, "z": 999},
{"x": 3, "y": 3.3},
]
converted = union_to_record(unionarray, "values")
assert isinstance(converted, ak.contents.RecordArray)
assert to_list(converted) == [
{"x": 1, "y": 1.1, "z": None},
{"x": None, "y": 2.2, "z": 999},
{"x": 3, "y": 3.3, "z": None},
]
otherarray = ak.Array(["one", "two"]).layout
tags2 = ak.index.Index8(np.array([0, 2, 1, 2, 0], dtype=np.int8))
index2 = ak.index.Index64(np.array([0, 0, 0, 1, 1], dtype=np.int64))
unionarray2 = ak.contents.UnionArray(
tags2, index2, [recordarray1, recordarray2, otherarray]
)
assert to_list(unionarray2) == [
{"x": 1, "y": 1.1},
"one",
{"y": 2.2, "z": 999},
"two",
{"x": 3, "y": 3.3},
]
converted2 = union_to_record(unionarray2, "values")
assert isinstance(converted2, ak.contents.RecordArray)
assert to_list(converted2) == [
{"x": 1, "y": 1.1, "z": None, "values": None},
{"x": None, "y": None, "z": None, "values": "one"},
{"x": None, "y": 2.2, "z": 999, "values": None},
{"x": None, "y": None, "z": None, "values": "two"},
{"x": 3, "y": 3.3, "z": None, "values": None},
]
df_unionarray = ak.operations.to_dataframe(unionarray)
np.testing.assert_array_equal(df_unionarray["x"].values, np.array([1, np.nan, 3]))
np.testing.assert_array_equal(df_unionarray["y"].values, np.array([1.1, 2.2, 3.3]))
np.testing.assert_array_equal(
df_unionarray["z"].values, np.array([np.nan, 999, np.nan])
)
df_unionarray2 = ak.operations.to_dataframe(unionarray2)
np.testing.assert_array_equal(
df_unionarray2["x"].values, [1, np.nan, np.nan, np.nan, 3]
)
np.testing.assert_array_equal(
df_unionarray2["y"].values, [1.1, np.nan, 2.2, np.nan, 3.3]
)
np.testing.assert_array_equal(
df_unionarray2["z"].values, [np.nan, np.nan, 999, np.nan, np.nan]
)
np.testing.assert_array_equal(
df_unionarray2["values"].values, ["nan", "one", "nan", "two", "nan"]
)
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