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$ pip install airflow-provider-xlsx

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from xlsx_provider.operators.from_xlsx_operator import FromXLSXOperator

xlsx_to_jsonl = FromXLSXOperator(
   task_id='xlsx_to_jsonl',
   source='{{ var.value.tmp_path }}/test.xlsx',
   target='{{ var.value.tmp_path }}/test.jsonl',
   file_format='jsonl',
   dag=dag
)

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{"month": "Jan", "high": -12.2, "mean": -16.2, "low": -20.1, "precipitation": 19}
{"month": "Feb", "high": -10.3, "mean": -14.7, "low": -19.1, "precipitation": 14}
{"month": "Mar", "high": -2.6, "mean": -7.2, "low": -11.8, "precipitation": 15}
{"month": "Apr", "high": 8.1, "mean": 3.2, "low": -1.7, "precipitation": 24}
{"month": "May", "high": 17.5, "mean": 11.6, "low": 5.6, "precipitation": 36}
{"month": "Jun", "high": 24, "mean": 18.2, "low": 12.3, "precipitation": 58}
{"month": "Jul", "high": 25.7, "mean": 20.2, "low": 14.7, "precipitation": 72}
{"month": "Aug", "high": 22.2, "mean": 17, "low": 11.7, "precipitation": 66}
{"month": "Sep", "high": 16.6, "mean": 11.5, "low": 6.4, "precipitation": 44}
{"month": "Oct", "high": 6.8, "mean": 3.4, "low": 0, "precipitation": 38}

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 select
     g as high_tech_sector,
     h as eur_bilion,
     i as share
 from
     high_tech
 where
     _index > 1
     and high_tech_sector <> ''
     and lower(high_tech_sector) <> 'total'

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from xlsx_provider.operators.from_xlsx_query_operator import FromXLSXQueryOperator

xlsx_to_csv = FromXLSXQueryOperator(
   task_id='xlsx_to_csv',
   source='{{ var.value.tmp_path }}/high_tech.xlsx',
   target='{{ var.value.tmp_path }}/high_tech.parquet',
   file_format='csv',
   csv_delimiter=',',
   table_name='high_tech',
   worksheet='Figure 3',
   query='''
       select
           g as high_tech_sector,
           h as eur_bilion,
           i as share
       from
           high_tech
       where
           _index > 1
           and high_tech_sector <> ''
           and lower(high_tech_sector) <> 'total'
   ''',
   dag = dag
)

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high_tech_sector,value,share
Pharmacy,78280,0.231952169555313
Electronics-telecommunications,75243,0.222954583130376
Scientific instruments,64010,0.189670433253542
Aerospace,44472,0.131776952366115
Computers office machines,21772,0.0645136852766778
Non-electrical machinery,20813,0.0616714981835167
Chemistry,19776,0.058598734453222
Electrical machinery,9730,0.028831912195612
Armament,3384,0.0100300315856265

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from xlsx_provider.operators.to_xlsx_operator import ToXLSXOperator

parquet_to_xlsx = ToXLSXOperator(
   task_id='parquet_to_xlsx',
   source='{{ var.value.tmp_path }}/test.parquet',
   target='{{ var.value.tmp_path }}/test.xlsx',
   dag=dag
)