| # 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 datetime import date |
| |
| from pandas import DataFrame, to_datetime |
| |
| names_df = DataFrame( |
| [ |
| { |
| "dt": date(2020, 1, 2), |
| "name": "John", |
| "country": "United Kingdom", |
| "cars": 3, |
| "bikes": 1, |
| "seconds": 30, |
| }, |
| { |
| "dt": date(2020, 1, 2), |
| "name": "Peter", |
| "country": "Sweden", |
| "cars": 4, |
| "bikes": 2, |
| "seconds": 1, |
| }, |
| { |
| "dt": date(2020, 1, 3), |
| "name": "Mary", |
| "country": "Finland", |
| "cars": 5, |
| "bikes": 3, |
| "seconds": None, |
| }, |
| { |
| "dt": date(2020, 1, 3), |
| "name": "Peter", |
| "country": "India", |
| "cars": 6, |
| "bikes": 4, |
| "seconds": 12, |
| }, |
| { |
| "dt": date(2020, 1, 4), |
| "name": "John", |
| "country": "Portugal", |
| "cars": 7, |
| "bikes": None, |
| "seconds": 75, |
| }, |
| { |
| "dt": date(2020, 1, 4), |
| "name": "Peter", |
| "country": "Italy", |
| "cars": None, |
| "bikes": 5, |
| "seconds": 600, |
| }, |
| { |
| "dt": date(2020, 1, 4), |
| "name": "Mary", |
| "country": None, |
| "cars": 9, |
| "bikes": 6, |
| "seconds": 2, |
| }, |
| { |
| "dt": date(2020, 1, 4), |
| "name": None, |
| "country": "Australia", |
| "cars": 10, |
| "bikes": 7, |
| "seconds": 99, |
| }, |
| { |
| "dt": date(2020, 1, 1), |
| "name": "John", |
| "country": "USA", |
| "cars": 1, |
| "bikes": 8, |
| "seconds": None, |
| }, |
| { |
| "dt": date(2020, 1, 1), |
| "name": "Mary", |
| "country": "Fiji", |
| "cars": 2, |
| "bikes": 9, |
| "seconds": 50, |
| }, |
| ] |
| ) |
| |
| categories_df = DataFrame( |
| { |
| "constant": ["dummy" for _ in range(0, 101)], |
| "category": [f"cat{i%3}" for i in range(0, 101)], |
| "dept": [f"dept{i%5}" for i in range(0, 101)], |
| "name": [f"person{i}" for i in range(0, 101)], |
| "asc_idx": [i for i in range(0, 101)], |
| "desc_idx": [i for i in range(100, -1, -1)], |
| "idx_nulls": [i if i % 5 == 0 else None for i in range(0, 101)], |
| } |
| ) |
| |
| timeseries_df = DataFrame( |
| index=to_datetime(["2019-01-01", "2019-01-02", "2019-01-05", "2019-01-07"]), |
| data={"label": ["x", "y", "z", "q"], "y": [1.0, 2.0, 3.0, 4.0]}, |
| ) |
| |
| lonlat_df = DataFrame( |
| { |
| "city": ["New York City", "Sydney"], |
| "geohash": ["dr5regw3pg6f", "r3gx2u9qdevk"], |
| "latitude": [40.71277496, -33.85598011], |
| "longitude": [-74.00597306, 151.20666526], |
| "altitude": [5.5, 0.012], |
| "geodetic": [ |
| "40.71277496, -74.00597306, 5.5km", |
| "-33.85598011, 151.20666526, 12m", |
| ], |
| } |
| ) |