def main():
with Session(host="localhost", port=10000) as dh_session:
taxi_data_table = import_taxi_records(dh_session)
bottom_5_fares_table = demo_chained_table_ops(taxi_data_table)
# download the table to the client in the form of pyarrow table and convert it into a Pandas DataFrame
snapshot_data = bottom_5_fares_table.snapshot()
df = snapshot_data.to_pandas()
pd.set_option("max_columns", 20)
print(df)
def main():
with Session(host="localhost", port=10000) as dh_session:
taxi_data_table = import_taxi_records(dh_session)
variable_name = "t"
dh_session.bind_table(taxi_data_table, variable_name)
bottom_5_fares_table = run_script(dh_session=dh_session)
snapshot_data = bottom_5_fares_table.snapshot()
df = snapshot_data.to_pandas()
pd.set_option("max_columns", 20)
print(df)
def main():
with Session(host="localhost", port=10000) as dh_session:
taxi_data_table = import_taxi_records(dh_session)
top_5_fares_table = demo_query(dh_session=dh_session, taxi_data_table=taxi_data_table)
bottom_5_fares_table = demo_chained_table_ops(taxi_data_table)
combined_fares_table = dh_session.merge_tables(tables=[top_5_fares_table, bottom_5_fares_table])
snapshot_data = combined_fares_table.snapshot()
df = snapshot_data.to_pandas()
pd.set_option("max_columns", 20)
print(df)