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Copy pathgenerate_dataset.py
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47 lines (41 loc) · 1.64 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.
import os
import shutil
import random
import pandas as pd
if __name__ == "__main__":
# generate the test dataframe
data = {
"total_amount": list(),
"fare_amount": list()
}
for i in range(0, 500):
data['total_amount'].append(random.randint(1,11)*5)
data['fare_amount'].append(random.randint(1,11)*3)
df = pd.DataFrame(data)
# dump the dataframe to a parquet file
df.to_parquet("skyhook_test_data.parquet")
# create the dataset by copying the parquet files
shutil.rmtree("nyc", ignore_errors=True)
payment_type = ["1", "2", "3", "4"]
vendor_id = ["1", "2"]
for p in payment_type:
for v in vendor_id:
path = f"nyc/payment_type={p}/VendorID={v}"
os.makedirs(path, exist_ok=True)
shutil.copyfile("skyhook_test_data.parquet", os.path.join(path, f"{p}.{v}.parquet"))