Contents
How to merge time series data by timestamp?
Basically, what I have is something like this: All timestamps are UNIX millisecond timestamps as numpy.uint64. …where all data is combined and ordered by timestamps. Each of the three tables is already ordered by timestamp.
How can I select rows with most recent timestamp for each?
I have a table of sensor data. Each row has a sensor id, a timestamp, and other fields. I want to select a single row with latest timestamp for each sensor, including some of the other fields. I thought that the solution would be to group by sensor id and then order by max (timestamp) like so:
Can a timestamp from Table 1 be in Table 2?
Since the data comes from different sources, there is no guarantee that a timestamp from table 1 will also be in table 2 or 3 and vice versa. In that case, the empty values should be marked as N/A. So far, I have tried using pandas to convert the data like so:
How to get last date in SQL Server?
Will return all results that have the same maximum date, to the milissecond. This is for SQL Server. I’ll leave it up to you to use the DATEPART function if you want to use dates but not times. This will give you results exactly what you are asking for and displaying above.
How to remove duplicate rows but keep the one with latest date?
Go on clicking another column name which you want to keep the most recent date, and then click Calculate > Max, see screenshot: 5. And then click Ok button to close this dialog, and now, you can see the duplicate names in column A have been removed and only keep the latest date in corresponding column B, see screenshot:
How to keep only the latest date for duplicate entries?
Go to Solution. 03-07-2019 06:09 AM paste following code in Power Query Advanced Editor and you should get desired result as long as your input data called Table1 (otherwise you need to change it accordingly). if you do it Power BI, GroupedRows step should reference your input table rather than Table1 03-06-2019 10:04 AM 03-06-2019 10:24 AM