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Link to Video Tutorial ->  https://www.youtube.com/watch?v=hDopw1mPlrU  Step-1 - >Create a seprate calulated table as shown below Period =  VAR     _last30days = ADDCOLUMNS(         CALCULATETABLE(             'Calendar'             ,DATESBETWEEN( 'Calendar'[Date], TODAY() - 30, TODAY() )         )         , "In the last", "30 days"     ) VAR     _last60days = ADDCOLUMNS(         CALCULATETABLE(             'Calendar'             ,DATESBETWEEN( 'Calendar'[Date], TODAY() - 60, TODAY() )         )         , "In the last", "60 days"     ) VAR     _last90days = ADDCOLUMNS(         CALCULATETABLE(             'Calendar'     ...

RemoveFilters Function Remove filters are used to remove the filter from existing measure which is already created Example     Keep Filters  

 

 DAX operators DAX Functions CALCULATE Function Measures Rolling revenue DATEADD

try : # Code that may raise an exception with pd.ExcelWriter(file, engine= 'openpyxl' , mode= 'a' , if_sheet_exists= 'replace' ) as writer: partspec_insert.to_excel(writer, sheet_name= 'Existing Spec' , index= False ) except Exception as e: # Handle the exception (e.g., log it, print it, or pass) print ( f"An error occurred: {e} " ) # You can use 'pass' to ignore the error and continue execution pass # Continue with the rest of your code   print ( "Execution continues even if an error occurred." )  

  # Execute query and fetch results into a DataFrame df = pd.read_sql(sql_query, conn) # Check if the DataFrame is empty if df.empty: print ( "The result set is empty." ) else : print ( "The result set is not empty." ) # Process the DataFrame (example) print (df) # Close connection conn.close()

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from sqlalchemy import create_engine, text # Define the connection string connection_string = "mssql+pyodbc://your_username:your_password@your_server_name/your_database_name?driver=ODBC+Driver+17+for+SQL+Server" # Create an engine engine = create_engine(connection_string) # Connect to the database with engine.connect() as connection: # Define the SQL UPDATE query Part_Rev_inactivate = text( """ UPDATE [Dbo].[PartRevDimension] SET PartStatus = 0 WHERE PartId = :part_id AND PartRev = :part_rev """ ) # Define the parameters part_id = 'your_part_id_value' part_rev = 'your_part_rev_value' # Execute the query connection.execute(Part_Rev_inactivate, { 'part_id' : part_id, 'part_rev' : part_rev}) # Commit the transaction connection.commit() print ( "Value updated successfully." ) Explanation: Replace  your_server_name ,  ...

The error you're encountering is because  Specresult  is a  CursorResult  object, which cannot be directly concatenated with a pandas DataFrame. You need to convert the  CursorResult  to a pandas DataFrame first. Here's the corrected code: from sqlalchemy import create_engine import pandas as pd Existing_Spec_Query = text( """ SELECT * FROM [LSQD].[PartSpec] WHERE PartId = :part_id AND PartRev= :Part_Rev """ ) # Assuming 'engine' is already defined and connected to your database with engine.connect() as connection: # Execute the query to fetch existing specifications Specresult = connection.execute(Existing_Spec_Query, { 'part_id' : part_id, 'Part_Rev' : Part_Rev}) # Fetch all rows from the result set and convert to DataFrame existing_Spec = pd.DataFrame(Specresult.fetchall(), columns=Specresult.keys()) print (existing_Spec) # End of Getting Existing Part data # Concatenate the new specif...