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Update: This is fixed in the version 1.5.1 release, see the #1 in the New list: What's new in version 1.5.1 | ArcGIS for Developers But there is a catch: the legend is only available for the map widget (arcgis.widgets._mapview.MapView) , but not for the webmap (arcgis.mapping._types.WebMap), and only by coding which is a one-liner, not that too bad although a button on the UI will be easier for end users. Hope all these issues will be addressed in coming versions. A nice step towards the right direction. Thank you ESRI for listening and acting on our request. David Vitale
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11-28-2018
09:14 PM
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3836
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IDEA
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This feature has been added to the map widget in the release of version 1.5.1
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11-28-2018
09:00 PM
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An example for the Range Search: { uploaded: [0000001259692864000 TO 0000001260384065000] } Peter is right about how ArcGIS Online stores the timestamp, it's UTC and in a string format. Here is the tested and working code: # UTC time
now_dt = datetime.datetime.utcnow()
then_dt = now_dt - timedelta(days=int(input_days))
# construct the string for range search, see ESRI doc for string format
now = '000000'+str(int(now_dt.timestamp()))+'000'
then = '000000'+str(int(then_dt.timestamp()))+'000'
items = gis.content.search(
query = 'uploaded: [' + then + ' TO ' + now + ']',
max_items=10000
)
# sort the items by modified date
items2 = sorted(items,key=lambda item:item.modified)
for item in items2:
str_time = datetime.datetime.fromtimestamp(item.modified/1000).strftime('%Y-%m-%d %H:%M:%S')
print("Modified Time:{0}, Title:{1}".format(str_time,item.title))
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11-28-2018
05:25 PM
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Good news, this issue will be addressed in the new release. Is this an issue for Spatially Enabled DataFrame (SEDF)? · Issue #319 · Esri/arcgis-python-api · GitHub
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10-28-2018
05:22 AM
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1284
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Is Python API going to support time-aware webmap and time slide bar? or I am pushing my luck a bit too far
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10-25-2018
10:23 PM
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513
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Some background: "New at version 1.5, the Spatially Enabled DataFrame is an evolution of the SpatialDataFrame object that you may be familiar with. While the SDF object is still avialable for use, the team has stopped active development of it and is promoting the use of this new Spatially Enabled DataFrame pattern...." See details in Introduction to the Spatially Enabled DataFrame | ArcGIS for Developers But what's the real benefit for the users? It seems to me only two different approaches to extend Pandas. While SDF is a sub-class of Pandas Class, SEDF is using an Registering Custom Accessors approach. The latter will save ESRI developers from messing with Pandas classes when adding some spatial capabilities. but what's the real benefit does the change bring to the end users? The old SDF has some benefits. One benefit of the SDF sub-class is that when I join or merge it with a standard Pandas dataframe, I'll get a SDF sub-class, then I can go on to plot it straight away. But with SEDF, after I perform some pandorable operations (like join, merge and set_index) on a SEDF, I'll get a standard Pandas dataframe, to map it, I have to spatially enable it every time after the operations. Although I can work around it, but it is not ideal (ideally you want to retain the datatype). I'd like to know what you think. Thanks.
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10-22-2018
11:52 PM
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1865
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According to ESRI Document, ESRI has stopped development on SpatialDataFrame: "New at version 1.5, the Spatially Enabled DataFrame is an evolution of the SpatialDataFrame object that you may be familiar with. While the SDF object is still avialable for use, the team has stopped active development of it and is promoting the use of this new Spatially Enabled DataFrame pattern. The SEDF provides you better memory management, ability to handle larger datasets and is the pattern that Pandas advocates as the path forward." From <https://developers.arcgis.com/python/guide/introduction-to-the-spatially-enabled-dataframe/> Extending pandas to add spatial functionality seems a good move, this will make the data analysis experience seamless for pandas users I hope.
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10-21-2018
04:50 PM
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4293
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arcgis/mapview seems from the old version. you can delete the related entries in the nbconfig file and restart jupyter. Or, completely uninstall ArcGIS API for Python and reinstall it. Hope this helps.
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10-16-2018
02:54 PM
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1
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3318
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addresses = ['Adelaide, South Australia',
'Mount Barker, South Australia',
'Brookside St, Oakden,South Australia']
results = batch_geocode(addresses)
fs=[Feature(geometry=Geometry(res['location'])) for res in results]
fset = FeatureSet(fs)
sms = {
"color": [255,0,0,150],
"size": 10,
"angle": 0,
"xoffset": 0,
"yoffset": 0,
"type": "simple-marker",
"outline": {
"color": [
255,
255,
255,
255
],
"width": 1,
"type": "esriSLS",
"style": "esriSLSSolid"
}
}
for res in results:
map1.draw(res['location'],symbol=sms)
prox=use_proximity.create_buffers(fset.to_dict(),distances=[1],units='Miles')
map1.add_layer(prox)
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10-15-2018
09:57 PM
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0
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4369
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The buffer function is a bit confusing and clunky, here is what I mean: When you specify the in_sr value, the unit parameter is not relevant any more. for example, if you specify in_sr=4326, the unit will be "degree" regardless whatever value you specify for the unit parameter. if you set in_sr=3857, the input values will be "Meters". In regard to which projection to choose, for a 1 Mile radius circle, you should not see big difference between SRID 3857 and a relative accurate local projection --- the distortion caused by projection become more visible over long distances or large areas. I would recommend to use use_proximity.create_buffers() for your task. addresses = ['Adelaide, South Australia',
'Mount Barker, South Australia',
'Brookside St, Oakden,South Australia']
results = batch_geocode(addresses)
fs=[Feature(geometry=Geometry(res['location'])) for res in results]
fset = FeatureSet(fs)
sms = {
"color": [255,0,0,150],
"size": 10,
"angle": 0,
"xoffset": 0,
"yoffset": 0,
"type": "simple-marker",
"outline": {
"color": [
255,
255,
255,
255
],
"width": 1,
"type": "esriSLS",
"style": "esriSLSSolid"
}
}
for res in results:
map1.draw(res['location'],symbol=sms)
prox=use_proximity.create_buffers(fset.to_dict(),distances=[1],units='Miles')
map1.add_layer(prox)
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10-15-2018
09:55 PM
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2
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0
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2620
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POST
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Looks like the Map widget is not enabled. Firstly, try this in the exact environment (if you have multiple envs) your jupyter server is running in: python -m arcgis.install If it does not work, then you can check if the map widget is enabled in notebook: jupyter nbextension list if not, enable it manually: jupyter nbextension enable --py --sys-prefix widgetsnbextension jupyter nbextension enable --py --sys-prefix arcgis Last, you can check your environment to see if it meets the minimal system requirement: print("python version: ",sys.version)
print("arcgis API version: ",arcgis.__version__)
print("widgetnbextension: ",widgetsnbextension.__version__)
print("ipywidgets version: ",ipywidgets.__version__) Hope this helps.
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10-14-2018
06:14 PM
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4
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4
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4014
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POST
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This looks like an issue related to wrong map projection. The World Geocoding Service spatial reference is 4326 (a.k.a WGS84) So try this if you want to use SRID 3857 (same as ESRI 102100): bgeocode=batch_geocode(addlist,out_sr=3857)
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10-14-2018
04:37 PM
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2
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2620
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Hi Ahmad, arcpy module is in a licensed package which comes with ArcGIS Desktop or ArcGIS Pro installation and not available for ArcGIS API for Python by default, that's why you can't import it. If you launch your Jupyter notebook server from your ArcGIS Pro env, you should not run into this problem. Hope it helps.
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10-04-2018
05:03 PM
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1
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1930
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It seems the instructions is outdated or wrong at the first place. Please try this: Replace myEvents_json = json.dumps(myEvents_fc_dict) With myEvents_json = json.dumps({"featureCollection": {"layers": [dict(myEvents_fc.layer)]}}) I referenced this example: Html table to pandas data frame to portal item | ArcGIS for Developers
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10-03-2018
06:31 PM
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