I have a task running on AirFlow that has two steps: fetches data from MSSql server as a dataframe; stores it in a PostGres database; I'm using the MsSqlHook and PostgresHook to manage the connections. The fetching is going ok,…
I need to create a json following this model from a df using python. I tried to load this json into a df to find the correct layout but did not succeed. Can anyone help me or at list give…
I have a Json file with the following (file name is double.JSON) {"OUT":"074531@@@;1-1=29=0;1-2=193=0;1-3=199=0;1-4=403=0;1-5=334=0;1-6=295=0;1-7=999=0;1-8=57=0;1-9=77=0;1-10=166=0;1-11=116=0;1-12=999=0;2-1=9.3=1;2-2=89=0;2-3=203=0;2-4=346=0;2-5=150=0;2-6=54=0;2-7=466=0;2-8=12=0;2-9=34=0;2-10=115=0;2-11=88=0;2-12=629=0;3-1=87=0;3-2=510=0;3-3=845=0;3-4=873=0;3-5=773=0;3-6=563=0;3-7=999=0;3-8=197=0;3-9=260=0;3-10=601=0;3-11=933=0;3-12=999=0;4-1=60=0;4-2=458=0;4-3=644=0;4-4=540=0;4-5=243=0;4-6=351=0;4-7=999=0;4-8=117=0;4-9=201=0;4-10=256=0;4-11=693=0;4-12=999=0;5-1=16=0;5-2=138=0;5-3=174=0;5-4=674=0;5-5=337=0;5-6=152=0;5-7=731=0;5-8=43=0;5-9=53=0;5-10=181=0;5-11=141=0;5-12=999=0;6-1=80=0;6-2=466=0;6-3=552=0;6-4=999=0;6-5=436=0;6-6=416=0;6-7=999=0;6-8=116=0;6-9=257=0;6-10=676=0;6-11=356=0;6-12=873=0;7-1=35=0;7-2=219=0;7-3=257=0;7-4=483=0;7-5=287=0;7-6=220=0;7-7=474=0;7-8=74=0;7-9=77=0;7-10=186=0;7-11=121=0;7-12=999=0;8-1=52=0;8-2=360=0;8-3=410=0;8-4=820=0;8-5=474=0;8-6=410=0;8-7=999=0;8-8=94=0;8-9=145=0;8-10=326=0;8-11=169=0;8-12=999=0;9-1=34=0;9-2=231=0;9-3=325=0;9-4=492=0;9-5=218=0;9-6=318=0;9-7=999=0;9-8=51=0;9-9=59=0;9-10=187=0;9-11=141=0;9-12=999=0;10-1=59=0;10-2=304=0;10-3=575=0;10-4=902=0;10-5=365=0;10-6=492=0;10-7=999=0;10-8=122=0;10-9=208=0;10-10=246=0;10-11=307=0;10-12=999=0;11-1=78=0;11-2=520=0;11-3=902=0;11-4=999=0;11-5=873=0;11-6=712=0;11-7=999=0;11-8=154=0;11-9=273=0;11-10=458=0;11-11=239=0;11-12=999=0;12-1=55=0;12-2=307=0;12-3=314=0;12-4=751=0;12-5=458=0;12-6=436=0;12-7=999=0;12-8=101=0;12-9=157=0;12-10=300=0;12-11=221=0;12-12=483=0;13-1=11=0;13-2=138=0;13-3=181=0;13-4=410=0;13-5=178=0;13-6=133=0;13-7=721=0;13-8=25=0;13-9=28=0;13-10=94=0;13-11=73=0;13-12=999=0;14-1=15=0;14-2=161=0;14-3=208=0;14-4=257=0;14-5=199=0;14-6=165=0;14-7=552=0;14-8=27=0;14-9=42=0;14-10=131=0;14-11=51=0;14-12=999=0"} and want to pull the table values and turn it into the following table in python. I have tried using the following Pandas codes but it is…
I have the following dataframe: 2023-06-30 2022-06-30 2021-06-30 2020-06-30 Ordinary Shares Number 7432000000.0 7464000000.0 7519000000.0 7571000000.0 Share Issued 7432000000.0 7464000000.0 7519000000.0 7571000000.0 Net Debt 12533000000.0 35850000000.0 43922000000.0 49751000000.0 Total Debt 59965000000.0 61270000000.0 67775000000.0 70998000000.0 Tangible Book Value 128971000000.0 87720000000.0 84477000000.0…
I am bit rusty in pandas to json transforms. I have a pandas data frame like this for a fictional library: userId visitId readingTime Books BookType u1 1 300 book1,book2,book3 Fiction u2 1 400 book4,book5 Horror u2 2 250 book6…
I have 'n' after > and spaces before <. Is there a way to don't save them when I call to_html method? I have: <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> I want to have: <table border="1" class="dataframe"><thead><tr style="text-align: right;">…
How to convert a pyspark data frame like below to a json array structure OrderID field fieldValue itemSeqNo 123 Date 01-01-23 1 123 Amount 10.00 1 123 description Pencil 1 123 Date 01-02-23 2 123 Amount 11.00 2 123 description…
Below is my JSON and i need JOLT to remove if destSiteName is unknown. Need to keep the rest of the object. { "destSiteName": "unknown", "customer_code": "code1" }
I hace a big json file data and I want to convert it in to tabular form. I am trying to flatten the data in to dataframe using json_nomalise. so Far I have this : code so far I want…
I want to read multiple text file from s3 bucket which will make up a data frame of 10M records and 900 columns. But it is taking too long to read data using ml.p3.2xlarge instance. Moreover, I would like to…