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I am assuming that you have a Standard or Advanced license which will be needed to update the relationship feature class used by attachments. There is a Help page entitled Working with the Attachments geoprocessing tools which says: The geodatabase attachment tools offer a flexible environment for batch processing of attachments. The attachment ...


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I do not believe there is a tool or function that allows you to export a table with reordered fields. If anyone knows better please enlighten me! I've always felt it has been a bit of a limitation that the geo-processing tools do not honour the reordered fields. Especially the conversion tools . In the past I had attempted to create a tool that did it. The ...


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If you are only interested in the attribute table, you can use the Summary Statistics tool, where 'Statistics Fields' = fields to sum, 'Statistics Type' = SUM, and 'Case Field' = ID.


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Right click the field and choose "Summarize" then choose your field and the method by which to summarize that field. Sum is what you are looking for.


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You can use the Dissolve tool. You choose the dissolve field (ID) and then SUM for the statistics.


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In 2.4 there is even calendar widget ("date picker"). In the layers "Fields" tabs, select "Date/Time" widget for a date field and check "calendar popup" option in widget detail settings.


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Not stupid at all buddy! Everyone has to learn sometime :) You may have already tried the way I am going to describe as I use QGIS 2.2 instead of 2.4. Open the attribute table, select New column and add the name and change the type: The format I normally use is YYYY-MM-DD when typing in the Date column: Hope this helps.


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Okay, I found my own solution: Make a new table which contains a field with values identical to those of a field in the original table and another in which these values are in reverse order Copy this new table Join the field(s) you wish to flip to the new table, using the field which is reversed in the new table as the output join field, and the reversed ...


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You cannot directly delete a row in a raster attribute table. This is because deleting a row would essentially be reclassifying the cells in that grid to NoData within the attribute table, which is not supported in ArcGIS. ArcGIS has a variety of tools to effectively "delete rows" including (to name a few) Reclassify and Con. These tools actually ...


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Assuming that the numbering of your rows always starts at 1 and proceeds with increments of 1 to a different number each time I think your model/code needs to do this: Use GetCount to count the number of rows (numRows) Use Calculate Field to do (numRows - ID) + 1


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You can do this easily by using the sort tool. This tool reorders, in ascending or descending order, records in a feature class or table based on field values. The reordered result is copied to a new dataset.


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If I understand your question correctly, it sounds like want to have three points created for each row in your table (one for each of the three fields). When ArcMap imports a table like this, it will only create one point feature for each row in your table. So if you want it to create three points per row (one for each of your fields given for each ...


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Ok, I'm still fuzzy on what exactly your export file is but I'll assume "#of cells" is simply the number of pixes for each raster and "Value" is some identifier for each raster (parse the file name??). In absence of how to get "Value", I just put an incremented variable. This script will require gdal. import glob from osgeo import gdal import numpy as np ...


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Try editing your table so the field names don't contain spaces, special characters etc. That's what causes the error on export to shape, and may be the root of some of the other issues you have as well...


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In the symbology tab, go to Add Values, then click the Complete List button. All the values that are not currently symbolized should appear. Highlight the new values and hit OK to add them.


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You need a codeblock in your field calculator. The example below is with a Python parser total = 0 def cumsum(inc): global total total+=inc return total The first line initialize a variable to 0, then you define a function called cumsum with one argument. for the incrementation, you want your variable to be "global" that will keep incrementing the ...


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The 'best' way depends on your intended use and the data itself. PolyGeo's comment and my answer at your follow-up question both suggest reviewing Join vs Relate. Your data can make use of a Relate, but doesn't have to. Some data sets don't have that choice. It's all about columns and rows. You have a set number of points. As long as each point has one and ...


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It's important to understand the difference between a Relate and a Join, and I'm somewhat unclear on the current setup of your data ("organized by month" how - as rows or columns?). If your weather data is in separate tables for each month or all months are in the same table with a row for each month, with fields called speed, temp, etc. then you would need ...


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Where is your image ? There was lots of Python modules to parse KML files (Pypi: KML) and you can also use all the Python modules to parse XML files (Pypi: XML), lxml is one of them, but not the easiest to use. For example bikepathparse.py is a script that parse a KML file (with lxml), and return path list of dictionaries with lists of coordinate points ...


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My understanding is that you need to make the relate permanent via a join before you can run interpolation. So join the ancillary data. Then right click on the shapefile to export it to a new one and run the interpolation on the new file. A pain but this is how i do it.


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I finally managed to do this. I created a new field (called it joinfield) with the $rownum expression I created a set of consecutive numbers (1,2,3...). I duplicated the attribute table, created another joinfield, amd this time I used $rownum - x (the time lag you want to apply, in my case, 8 minutes). If the delay is the other way around you can use ...


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Instead of loading the .csv using Add vector layer, use the Delimited Text layer tool. It will try to detect the most fitting data type for each column. For more details see the QGIS user guide.



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