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Copy pathtest_table.py
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79 lines (62 loc) · 2.42 KB
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from pyarrow.compat import unittest
import pyarrow as arrow
A = arrow
import pandas as pd
class TestRowBatch(unittest.TestCase):
def test_basics(self):
data = [
A.from_pylist(range(5)),
A.from_pylist([-10, -5, 0, 5, 10])
]
num_rows = 5
descr = A.schema([A.field('c0', data[0].type),
A.field('c1', data[1].type)])
batch = A.RowBatch(descr, num_rows, data)
assert len(batch) == num_rows
assert batch.num_rows == num_rows
assert batch.num_columns == len(data)
class TestTable(unittest.TestCase):
def test_basics(self):
data = [
A.from_pylist(range(5)),
A.from_pylist([-10, -5, 0, 5, 10])
]
table = A.Table.from_arrays(('a', 'b'), data, 'table_name')
assert table.name == 'table_name'
assert len(table) == 5
assert table.num_rows == 5
assert table.num_columns == 2
assert table.shape == (5, 2)
for col in table.itercolumns():
for chunk in col.data.iterchunks():
assert chunk is not None
def test_pandas(self):
data = [
A.from_pylist(range(5)),
A.from_pylist([-10, -5, 0, 5, 10])
]
table = A.Table.from_arrays(('a', 'b'), data, 'table_name')
# TODO: Use this part once from_pandas is implemented
# data = {'a': range(5), 'b': [-10, -5, 0, 5, 10]}
# df = pd.DataFrame(data)
# A.Table.from_pandas(df)
df = table.to_pandas()
assert set(df.columns) == set(('a', 'b'))
assert df.shape == (5, 2)
assert df.ix[0, 'b'] == -10