longview | Linode Longview Agent | Monitoring library
kandi X-RAY | longview Summary
kandi X-RAY | longview Summary
Longview is a system level statistics collection and graphing service, powered by the Longview open source software agent that can be installed onto any Linux system. The Longview agent collects system statistics and sends them to us, where we store the data and present it in beautiful and meaningful ways.
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QUESTION
I am extracting information from here I am able to extract the column names and all values from the table however, I am not sure how to save the values in pandas dataframe.
Like for Instance- For the first column 'SPAC' I get all URLs together. This can be saved in a list which in turn could be added to the dataframe. The main issue/challenge that I am facing is that for the rest of values and columns. I get an output like
...ANSWER
Answered 2021-Oct-08 at 02:37This should work:
QUESTION
I have the following Entity Framework query:
...ANSWER
Answered 2021-May-27 at 19:24I would advise to replace
QUESTION
I am trying to get a list of objects stored in the database through a foreach loop, here is my current code:
...ANSWER
Answered 2021-Jan-26 at 14:32You're adding the same Rule over and over. Try something like
QUESTION
The following codes check for Duplicates in CSV file where TO Column is “USD”. I need your help to figure out how do I compare the resulted duplicate value, if the duplicate value has same value like in the below case, Perl should not give any warning, if the value is same. Perl file name is Source, just change the directory and run it.
...ANSWER
Answered 2020-Aug-02 at 12:33Like @Håkon wrote it seems like all your duplicates are in fact the same rate so they should not be considered duplicates. However, it could be an idea to store the rate in a hash mapped to each from and to currency. That way you don't need to check for duplicates every iteration and can rely on the uniqueness of the hash.
It's great that you use proper CSV parsers but here's an example using a single hash to keep track of duplicates by just splitting by ,
since the data seems reliable.
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