Joel McCune - Joel McCune

ArcPy Describe <dot> Properties

A tremendous amount of information is available through arcpy.Describe. Until ArcGIS Pro 2.8 though, figuring out what properties were available for the object you had just described required digging into the documentation pretty deep. Now, it is much easier to access these properties introspectively as a dictionary. Since

Pandas DataFrame to Markdown

Over the last few months I have been including markdown representations of data frames quite a bit to put in documentation to show what the table outputs look like. Using Jupyter it is not overly difficult to use the df.to_markdown() method, and copy the output in the notebook.

Python, data munging

GroupBy and Aggregate Using Pandas

Remove duplicates in one column, and create a list of tags in another column using Pandas. Consider this. I have a table of data. With me, yes, I know, big surprise. This table of data has a column with values, and some of these values repeat. This is the names

Python

Python Dictionary as Object

It's something simple enough, I just want to take a dictionary and have the ablity to access the properties using dot syntax. Consider, if I have a dictionary such as the following... my_dict = { 'one_value': 'something sweet', 'two_value': 'something even sweeter', 'nested_value': { 'n1': 'buried value', 'n2': 'another

Mac

Fixing Mac .bash_profile

Murphy, who was he and why is his law so recurrent? Apparently, there are people who spend an inordinate amount of time unpacking the history of Murphy's Law. Myself, I typically use a liberal helping of my best sailor's vocabulary when encountering his annoying law, but never really stopped to

Get SafeGraph Patterns by POI ID Using an AWS EC2 Instance

Retrieve SafeGraph Patterns Data for Only Specific Points-of-Interest(POI) Using an Amazon Web Services Elastic Compute Cloud Instance "What the heck did he just say?" Yes, even for a large proportion of the technical people who visit my blog, this very well may sound like gibberish. Further, even for those

Python

Conda and ArcGIS Pro 2.7

For those of us who regularly work with Python and ArcGIS, especially for data science, life just got a lot easier with ArcGIS Pro 2.7. Now, arcpy can be installed just like any other Conda package. This means ArcGIS Pro now can coexist on the same machine and play nicely with Conda.

COVID Office Evolution

For a long time I resisted creating a home office. We live in an 1,800 square foot house built in 1924. About a year ago, we moved the boys into the same bedroom, and my wife took over the nursery as an office since she works from home, pandemic

Covid

Geography Matters...Again

When the world was big, geography mattered a whole lot. As travel became easier, trade almost trivial, and the world became smaller, geographic interest waned. Now, in the midst of a pandemic, suddenly geography matters a lot...again.

whitewater

The Best Laid Plans - I Miss the River

Almost four years ago now, I got the opportunity to run the Little White Salmon for the first time. Over a decade ago, I recall seeing the first ever full color centerfold in American Whitewater, and although I had spent arguably all of my life paddling, I could not recognize

covocalypse

Covocalypse Part 1

In today's world of follow-me drones, GoPro heros, and cell phone cameras, I find myself looking at a lot more photos and videos shared online with little explanation. It makes me yearn for the evenings viewing a screen set up in a living room displaying color slides and listening, spellbound,

Python

Cloning ArcGIS Conda Environments

ArcGIS Pro, when initially released, included an incredibly powerful capability, the included Python environment is a Conda environment. This unlocks the extremely powerful and vast universe of installable packages available through Conda. Further, using Conda environments enables ensuring a project can be successfully moved to another machine, and successfully run

Python

Create `arcgis` Conda Environment with a Batch File

Although first and foremost a Geographer, after transitioning to the GeoAI Business Development Team at Esri, now I spend most of my time in Jupyter Lab. Although not altogther difficult, if following best practices, when installing other packages and modifying the primary Conda environment shipped with ArcGIS Pro, arcgispro-py3, you

Python

Automatically Convert to Esri Spatially Enabled Dataframe

I frequnetly need a Spatially Enabled Dataframe from a variety of sources, and these sources frequently change. Guessing there is a very good chance I am not the only one doing this - here is my solution to this as a Gist you are more than welcome to use.

Python

Relative Module Imports in an ArcGIS Python Toolbox

The idea of ArcGIS Python toolboxes really appeals to me. I really like them. As is frequently the case in life, the devil is in the details. Python Toolboxes have plenty of interesting personality quirks. Among these is relative module imports when creating Python Toolboxes for ArcGIS Pro. Here is

iPython

Layer to Spatially Enabled DataFrame

As I continue to dive deeper and deeper into the intersection of Geography and Artifical Intelligence - what we are calling GeoAI, I find myself doing a lot of data work. This means I liberally blend the two Esri Python libraries, ArcPy and the Python API. Many times I use

Python

Purge Scratch GeoDatabase

In a lot of the scripts I write, especially data preparation pipelines, I use the scratch Geodatabase - a lot. At the end of these pipelines, especially when testing and re-running the processes multiple times, I like to clean out this workspace to ensure my results are the new results,

whitewater

Outfitting a Pyranha 9R as a C1

Kaykers have it so easy. Outfitting a boat consists of shoving a few slivers of foam in for hip blocks, adjusting the bulkhead and backhand, and hitting it. It takes, at most, about five minutes. But, I do not kayak. Frankly, I never have. I paddle C1 exclusively - always

Python API

ArcGIS-ML-Docker

Easily 80 percent of my time at work is now spent in ArcGIS Python API, either the stable branch, or much of the time, the daily build. Frequently I switch between these environments, but also need a few other Conda packages to support machine learning. To support flexibly using both

arcpy

Use ArcPy to Match Spatial Reference

Frequently when performing data preparation or analysis in GIS the spatial reference or projections need to be modified to match. Also, much of the time the data needs to be modified to match one specific feature class. The difficulty lies in frequently also needing to select a transformation if the

Python API

ArcGIS Python Geometry from Shapely

The ArcGIS Python API Geometry object includes the capability to export the geometry to a Shapely Geometry object, but not the capability to create a new ArcGIS Geometry object from a Shapely object. Thankfully, it is not difficult to add this capability to every ArcGIS Geometry object in a namespace.

Python API

Loading a Previously Saved SpatialDataFrame from CSV

Increasingly I find myself working with SpatialDataFrames for analysis in Jupyter Notebooks in Python. Much of the time the easiest way to save results for future work is saving to a CSV file. This CSV file can then be loaded back into another notebook as an active SpatialDataFrame for further

Python

Creating a SpatialDataFrame from a Web GIS Item

The relatively recent addition of the SpatialDataFrame object to the ArcGIS Python API was a gigantic leap forward. The SpatialDataFrame marries the common data structure used for data munging and data science, the Pandas DataFrame, with ArcGIS in a familiar (for data scientists at least) and user friendly environment, Jupyter

Python

Keeping the ArcGIS Python API with ArcGIS Pro Current

If you are running the ArcGIS Python API in a virgin Conda environment, this very likely does not apply to you. If you are running the ArcGIS Python API in the Python environment installed with ArcGIS Pro, as of today 05Mar2018, you are stuck at version 1.2.5 while

Pandas

Filter NotNull Geometries in an ArcGIS SpatialDataFrame

When working with Pandas DataFrames it is fairly common to filter out records with null values using the notnull Pandas function. This however, does not work with the geometry column created when loading data into a SpatialDataFrame. It still has a value, albeit an invalid value, but Pandas still sees