Dax Studio - Python Connection
Hello All, There is a plan to move data source from one database to another for which it would be essential for us to understand the dashboards within a workspace. I have explored few options in Dax Studio which has capability to return Measures, Columns, Catalogs (Dashboards) and other details of a specific workspace. However if I need to get a detailed inforamtion across all the Power BI Dashboards in a workspace, the commands below would not allow me to. SELECT [CATALOG_NAME] FROM $SYSTEM.DBSCHEMA_CATALOGS SELECT [CATALOG_NAME] FROM $SYSTEM.DBSCHEMA_CATALOGS, SELECT [ID],[Name] FROM $SYSTEM.TMSCHEMA_TABLES WHERE NOT [IsHidden] SELECT * FROM $SYSTEM.TMSCHEMA_COLUMNS WHERE NOT [IsHidden] SELECT [ID],[TableID],[Name],[QueryDefinition] FROM $SYSTEM.TMSCHEMA_PARTITIONS SELECT [ID],[TableID],[Name],[Expression] FROM $SYSTEM.TMSCHEMA_MEASURES WHERE NOT [IsHidden] SELECT * FROM $SYSTEM.TMSCHEMA_RELATIONSHIPS Requesting your guidance if there is a way I can loop through all the commands above and get the data into Excel format or into SQL or connect to Power BI directly so that I can analyze it further. Regards Mithun T
python example for a REST API power bi report server request
Hello, please someone has a python example of how using the REST API and interacting with some dashboard inside Power BI Report server? (I mean write a code to refresh automatically a dashboard or something like that using python outside of POwer BI) It could work in a internal wnvironment (Virtual machine)? Thanks
Group by and count - How to translate this from python
Hi everyone, im new to powerbi DAX and im with a problem to solve... i have a table like this: COD_EVENT DEVICE_ID CITY DATE CAUSE 3002 134 CAMPINAS 01/02/2020 ELECTRICAL DISCHARGE 3005 147 CAMPINAS 02/10/2020 ANIMALS 4008 128 SAO PAULO 03/11/2020 WIND 4009 159 SAO PAULO 01/02/2021 ANIMALS 4013 128 SAO PAULO 02/05/2021 ELECTRICAL DISCHARGE 7892 178 CAMPINAS 01/11/2019 DEVICE FAIL ... ... ... ... i need to count from a date(m/y), for example dez/2020, the events in last 12 months, after this, i need groupby DEVICE, and show the quantity of events in devices that had more than one in last 12 months e the quantity of events in devices that had only one event in last 12 months. An example of what i expect to get: DATE CITY RECURRENT UNIQUE DEZ/2020 CAMPINAS 3 1 JAN/2020 CAMPINAS 3 2 FEV/2020 CAMPINAS 4 1 DEZ/2020 SAO PAULO 2 3 JAN/2020 SAO PAULO 2 4 FEV/2020 SAO PAULO 1 5 ... ... ... ... Where RECURRENT calculates the number of events in devices that had more than one event in the last 12 months since the date described in DATE, for the city described in CITY. And UNIQUE calculate de amount of events in devices that had only 1 event in last 12 months for that city. I make this work in python, and i did something like this: city = events_df['CITY'].unique() #Extract all cities present in dataframe tab_fin = pandas.DataFrame() #Create a df to append each iteration for i in range(0,len(city)): events_by_city = events_df[events_df['CITY'] == city[i]] #Create a table inside the loop that contains only the events of a especific city date_ini = pandas.to_datetime('2020-12-31') #first month of interest last_date = date.today().replace(day=1) - timedelta(days=1) #last month of interest num_months = (last_date.year - date_ini.year) * 12 + (last_date.month - date_ini.month) #number of dates between date_ini e last_date for j in range (0,num_months+1): events_12months = events_by_city[(events_by_city['DATE'] > date_ini + relativedelta(months=-12)) & (ocorr_conj['DT_INICIO'] <= data_ini)] #Extract the events in last 12 months events_grouped = events_12months.groupby('DEVICE_ID')['COD_EVENT'].count().reset_index() recurrent = sum(events_grouped[events_grouped['COD_EVENT']>1]['COD_EVENT']) #events in devices that had more than 1 unique = len(events_grouped[events_grouped['COD_EVENT']==1]) #events in devices that had only 1 tab_aux = pandas.DataFrame({'CITY':city[i], 'DATE':str(date_ini.month) +'/'+ str(date_ini.year), 'RECURRENT':recurrent, 'UNIQUE':unique}, index=[0]) tab_fin = tab_finappend(tab_aux) #Append in tab_fin the info of the i-city and j-month date_ini = date_ini + relativedelta(months=+1) #add 1 month to date
On-premises Power BI Report Server connect live to an on-premise python or analysis server
Currently, I'm publishing dashboards on the on-premises Power BI Report Server. via SQL Enterprise. Edition. is there an on-premise python or analysis server? so can i run advance analyses live from the Power BI Report Server dashboard.
