mirror of https://github.com/apache/superset.git
122 lines
3.4 KiB
Python
122 lines
3.4 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from datetime import date
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from pandas import DataFrame, to_datetime
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names_df = DataFrame(
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[
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{
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"dt": date(2020, 1, 2),
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"name": "John",
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"country": "United Kingdom",
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"cars": 3,
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"bikes": 1,
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"seconds": 30,
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},
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{
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"dt": date(2020, 1, 2),
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"name": "Peter",
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"country": "Sweden",
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"cars": 4,
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"bikes": 2,
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"seconds": 1,
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},
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{
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"dt": date(2020, 1, 3),
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"name": "Mary",
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"country": "Finland",
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"cars": 5,
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"bikes": 3,
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"seconds": None,
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},
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{
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"dt": date(2020, 1, 3),
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"name": "Peter",
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"country": "India",
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"cars": 6,
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"bikes": 4,
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"seconds": 12,
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},
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{
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"dt": date(2020, 1, 4),
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"name": "John",
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"country": "Portugal",
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"cars": 7,
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"bikes": None,
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"seconds": 75,
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},
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{
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"dt": date(2020, 1, 4),
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"name": "Peter",
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"country": "Italy",
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"cars": None,
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"bikes": 5,
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"seconds": 600,
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},
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{
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"dt": date(2020, 1, 4),
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"name": "Mary",
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"country": None,
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"cars": 9,
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"bikes": 6,
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"seconds": 2,
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},
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{
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"dt": date(2020, 1, 4),
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"name": None,
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"country": "Australia",
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"cars": 10,
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"bikes": 7,
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"seconds": 99,
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},
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{
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"dt": date(2020, 1, 1),
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"name": "John",
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"country": "USA",
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"cars": 1,
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"bikes": 8,
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"seconds": None,
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},
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{
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"dt": date(2020, 1, 1),
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"name": "Mary",
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"country": "Fiji",
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"cars": 2,
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"bikes": 9,
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"seconds": 50,
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},
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]
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)
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categories_df = DataFrame(
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{
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"constant": ["dummy" for _ in range(0, 101)],
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"category": [f"cat{i%3}" for i in range(0, 101)],
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"dept": [f"dept{i%5}" for i in range(0, 101)],
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"name": [f"person{i}" for i in range(0, 101)],
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"asc_idx": [i for i in range(0, 101)],
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"desc_idx": [i for i in range(100, -1, -1)],
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"idx_nulls": [i if i % 5 == 0 else None for i in range(0, 101)],
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}
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)
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timeseries_df = DataFrame(
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index=to_datetime(["2019-01-01", "2019-01-02", "2019-01-05", "2019-01-07"]),
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data={"label": ["x", "y", "z", "q"], "y": [1.0, 2.0, 3.0, 4.0]},
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)
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