I am building a package that uses the Google Analytics API for Python.
But, in severous cases when I have multiple dimensions the extraction by day is sampled.
I know that if I use sampling_level = LARGE will use a sample more accurate.
But, somebody knows if has a way to reduce a request that you can extract one day without sampling?
Grateful
setting sampling to LARGE is the only method we have to decide the amount of sampling but as you already know this doesn't prevent it.
The only way to reduce the chances of sampling is to request less data. A reduced number of dimensions and metrics as well as a shorter date range are the best ways to ensure that you dont get sampled data
This is probably not the answer you want to hear but, one way of getting unsampled data from Google analytics is to use unsampled reports. However this requires that you sign up for Google Marketing Platform. With these you can create an unsampled report request using the API or the UI.
There is also a way to export the data to Big Query. But you lose the analysis that Google provides and will have to do that yourself. This too requires that you sign up for Google Marketing Platform.
there are several tactics of building unsampled reports, most popular is splitting your report into shorter time ranges up to hours. Mark Edmondson did a great work on anti-sampling in his R package so you might find it useful. You may start with this blog post https://code.markedmondson.me/anti-sampling-google-analytics-api/
I would like to permit user to load their own data (excel file) through the user interface. And then I want to retrieve the file and use it in my data function.
I'm working on a Spotfire Dashboard. I need that the user import its own data and I want to use this table later in a data function (r Embedded in spotfire). I know we can use Ironpython or Javascript throught spotfire and I have no idea how to permit user to load its data
Can you help me please
Any help would be appreciated!
sorry to tell you, but this is not a feature that's available in Spotfire. you might be able to accomplish this with some serious Python scripting, but I wouldn't put the time in to bother.
there are a lot of potential issues that could crop up, but essentially they come down to: users are stupid; do not trust them.
you will spend far too much time to define edge cases such as "what if a user uploads a file that is missing a needed column?" "what if a user uploads some other file type (.pdf)?" "what if a user uploads data that is not actually valid or has been manipulated to show different results?"
my strong suggestion is that you consider what you are trying to accomplish by letting users provide their own data, and try to find some other way to do that. otherwise, HIC SVNT DRACONIS ;)
as an alternative, you can probably use an information link connected to a database? but the answer to your question is: you cannot, and you should not want to.
Since I have little experience programming, I first tried posting this "job" on a freelance website. Then, 4 programmers who seemed to what they were doing failed to solve it (maybe they didn't know what they were doing). After this, I decided to attempt it myself, and that is why I came to Stack Overflow, which I believe will point me in the right direction.
The problem appears quite simple: the program in question gives me rows and columns of data, just like a spreadsheet. As time goes by, new rows are added on top. It looks like this:
I just need to replicate this data inside an Excel spreadsheet, so that I can perform analysis.
I will keep it short, as I don't know what further detail I could give. Perhaps looking at the program files could help in establishing what sort of program it is. Download link: http://xpproupdate.xpi.com.br/xppro.zip
Thanks!
Some loose ideas:
Method 1 (assuming this is an app connected to the Internet):
Try packet-sniffing. Instead of extracting the data from the app download a packet sniffing app and look and the data-flow. See on what port the app is exchanging data. If the data is not encryped the tasks should be fairly easy.
As a reference see this packet sniffer in C#:
http://www.codeproject.com/Articles/17031/A-Network-Sniffer-in-C
Method 2 (assuming no connection to the Internet, or if there is encryption involved):
If the data is encrypted or the app simply does not interact with the Internet then try to access the app's Win32 window handle and traverse it's internal controls.
Method 3 (last resort):
Frequent window image screenshot and scraping the data from the image using a simple OCR.
Using the Instagram API, I subscribed to a tag with the Real time feature. I sync media that match my project's criteria, then save those to DB. When users visit my website, I display these images from my DB (and not from instagram API).
From time to time, I see broken links showing up in the images. I identified that the source of the problem is that those images have now been deleted.
What's a good way to handle this?
Probably not attempting to duplicate the Instagram DB (or part thereof) would be the best option. Depending on the usage of your project and what sort of tags you're subscribing to, that could get pretty large pretty quickly.
Short of that, doing a quick HTTPRequest to the image URL (and checking the response code) before deciding whether to display it would do the job.
#Steve Crawford is on the right track.
The problem with your solution is that you are duplicating volatile data that you:
a) can't control
b) don't receive notifications on.
I would think the better method would be track the meta data of the images you are interested (like the author, url,date,etc) and then display them if they are still available.
If you are going to cache data you also need to a way to invalidate your cache. So another option would be to duplicate the data as you already are, but also have a background job to ensure that the data is still valid and remove the ones that aren't.
Our customers use 500+ applications and we would like to integrate these applications with our. What is the best way to do that? These applications are time registration applications and common for most of them is that they can export to csv or similar, some of them are actually home-brewed excel sheets where time is registered.
The best idea so far is to create our own excel sheet, which can be used to integrate with all these applications. The integrations could be in the form of cells containing something like ='[c:\export.csv]rawdata'!$A$3 Where export.csv is the csv file exported from the time registration applications. Can you see a better way to integrate against all these applications? It should be mentioned that almost all our customers have Microsoft Office.
Edit: Answers to the excellent questions from Pontus Gagge:
How similar are the data in the different applications?
I assume that since they time registration applications, they will have some similarities, but I assume that some will register the how long time one has worked in total for a whole month, while others will spesify for each day. If Excel is chosen, I believe that many of the differences could be ironed out using basic formulas.
What quality is the data?
The quality of the data can vary so basic validation must be undertaken, a good way is also to make it transparent for the customers, how our application understands their input, so they are responsible.
How large amounts of data are you talking about?
There will be information about the time worked for up to 50 employees.
Is the integration one-way only?
Yes
With what frequency should information be transferred?
Once per month (when they need to pay salaries).
How often do the applications themselves change, and how often does your product change?
If their application is a home-brewed Excel sheet, then I assume it will change once a year (due for example a mistake someone). If it is a standard proper time registration application, then I do not believe they are updated more often than every fifth year or so, as it is a very stabile concept.
Should the integration be fully automatic or can your end users trigger a data transfer?
They can surely trigger data transfer. The users are often dedicated to the process so they can be trained at doing it, which means that they could make up to, say 30, mouse clicks in order to integrate each month.
Will the customers have somebody to monitor the integrations?
As we have many customers, many of them should be able to undertake the integration themselves. We will though be able to assist them over the telephone. We cannot, though undertake the integration ourselves because we would then be responsible for any errors due to user mistakes, etc.
Does the phrase 'integration spaghetti' mean anything to you...?
I am looking for ideas from the best chefs to cook a nice large portion of that.
You need to come up with a common data format, and a way to translate the individual data formats to the common format. There's really no way around this - any solution you come up with will have to do this in one way or the other. It's the essential complexity of what you're doing.
The bigger issue is actually variances within the source data, in terms of how things like dates are stored, missing columns, etc. Doing a generic conversion for CSV to move columns around is comparatively easy.
I would also look at CSV and then use an OLEDB connection against the CSV file for importing.
If you try to make something that can interface to any data structure in the universe (and 500 is plenty close enough), it is guaranteed to be a maintenance nightmare. Instead I would approach this from multiple angles:
Devise an interface into which a human can enter this data already in the proper format. With 500+ clients, I'd make this a small, raw but functional browser based site that users can use to enter this information manally. This is the fall-back. At the end of the day, a human can re-key the information into the site and solve the import issue. Ideally, everyone would use this instead of their own format. Data entry people are cheap.
Similar to above, but expanded, I would develop a standard application or standardize on an off-the-shelf application that can be used to replace their existing format. This might take more time than #1. The goal would be to only do one-time imports of these varying data schemas into the application and be done with them for good.
The nice thing about spreadsheets is that you can do anything anywhere. The bad thing about spreadsheets is that you can do anything anywhere. With CSV or a spreadsheet there is simply no way to enforce data integrity and thus consistency (which is the primary goal) on the data. If the source data is already in a database, then that is obviously simpler.
I would be inclined to use database format into which each of these files need to be converted rather than a spreadsheet (e.g. use something like Jet (MDB)). If you have non-Windows users then that will make it harder and you might have to use a spreadsheet. The problem is that it is too easy for the user to change their source structure, break their upload and come crying to you. If a given end user has a resident expert, they can find a way of importing the data into that database format . If you are that expert, then I would on a case-by-case basis, write something that would import into that database format. XML would be the other choice, but that will likely take more coding than an import/export into a database format.
Standardization of the apps (even having all the sources in a database format instead of a spreadsheet would help) and control over the data schema is the ultimate goal rather than permitting a gazillion formats. There really is no nice answer other than standardization. Otherwise, you are having to write a converter for every Tom-Dick-and-Harry format and again when someone changes the source format.
With a multitude of data sources mapping each one correctly to an intermediate format is not trivial. Regular expressions are good with a finite set of known data formats. Multipass can help when data is ambiguous without context (month,day fields and have several days of data), and also help defeat data entry errors. But it seems as this data is connected to salaries there needs a good reliable transfer.
An import configuring trick
Get the customer to make a set of training data in the application. It should have a "predefined unique date" and each subsequent data field have a number corresponding to the target data field in your application. On importing your application needs to recognise the predefined date, determine the unique translation required and effect the displaying/saving of this "mapping key", and stop the import. eg If you expect "Duration hours" in field two then get the user to enter 2 in the relevant field which might be "Attendance hours".
On subsequent runs, and with the mapping definition key, import becomes a fairly easy process of translation.
Note on terms
"predefined date" - must be historical, say founding date of your company?, might need to be in PC clock settable range.
"mapping key" - could be string of hex digits and nybble based so tractable to workout
The entered code can be extended to signify required conversions ie customer's application has durations in days and your application expects it in hours.
Interfacing with windows programs (in order if increasing fragility)
Ye Olde saving as CSV file
Print to operating system printer that is setup as a text file/pdf, then scavenge the data out of that
Extract data via the application interface control, typically ActiveX for several windows programs ie like Matlab's Spreadsheet Link
Read native file format xls format ie like Matlab's xlsread
Add an additional intermediate spreadsheet sheet that has extended cell references ie ='[filename]rawdata'!$A$3
Have a look at Teiid by JBoss: http://jboss.org/teiid
Also consider using SOA - e.g., if you're on Java, try JBoss SOA platform: http://www.jboss.com/resources/soa/?intcmp=1004
Use a simple XML format. A non-technical person can easily understand a simple XML format (and could even identify basic problems with XML documents that are not well-formed).
Maybe use a DTD (or even better an XML schema) to do very basic validation, and then supplement this with an XSL stylesheet to do more validation with better error reporting. (An XSL stylesheet simply converts from XML to something else and so can be generate readable error messages.)
The advantage of this approach is that web browsers such as Internet Explorer can apply the XSL stylesheets. A customer need only spend at most a day enhancing their applications or writing excel macros to generate the XML data in the format that you specify.
Recent versions of Excel have support for converting spreadsheet data to XML, and can even validate against schemas.
Once the data passes the XSL validation checks, you have validated XML data.
If you have heaps of data and heaps of money, you could look at existing data management and cleansing tools:
http://www-01.ibm.com/software/data/infosphere/datastage
http://www-01.ibm.com/software/data/infosphere/qualitystage
But even then, you'll likely need to follow kyoryu's suggestion assuming you have 500+ data formats. The problem isn't your side. You need them to standardize their output formats if you have no control over their apps. CSV is likely the easiest. You could even send them a excel template to help them along.