Convert a list of field names and aliases from Excel to table using ArcPy

I went digging through my old workspace and started looking at some of my old scripts. My style of coding back then is almost embarrassing now 🙂 but that’s just the process of learning. I decided to post this script I wrote just before ArcGIS released their Excel toolset in 10.2.

	'''
	@date 09/07/2013
	@author Cindy Williams
	Converts a spreadsheet containing field names and aliases
	into a file geodatabase table.
	'''
	import arcpy
	xls = r"C:\Some\Arb\Folder\test.xlsx\Fields$"
	tbl = r"C:\Some\Arb\Folder\test.gdb\tbl_Samples"
	with arcpy.da.SearchCursor(xls,("FIELD_NAME","ALIAS")) as cursor:
	for row in cursor:
	arcpy.management.AddField(tbl, row[0], "DOUBLE", field_alias=row[1])
	print("Adding field {}…".format(row[0]))
	print("Fields added successfully.")

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createTableFieldsFromXLS.py

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From what I can recall, I needed to create a file geodatabase table to store records of microbial sample data. Many of the field names were the chemical compound themselves, such as phosporus or nitrogen, or bacterial names. For brevity’s sake, I had to use the shortest field names possible while still retaining the full meaning.

I set up a spreadsheet containing the full list of field names in column FIELD_NAMES and their aliases in ALIAS. I created an empty table in a file gdb, and used a SearchCursor on the spreadsheet to create the fields and fill in their aliases.

This solution worked for me at the time, but of course there are now better ways to do this.

Reverse geocode spreadsheet coordinates using geocoder and pandas

I had a spreadsheet of coordinates, along with their addresses. The addresses were either inaccurate or missing. Without access to an ArcGIS licence, and knowing the addresses were not available on our enterprise geocoding service, I sought to find a quicker (and open-source) way.

	import geocoder
	import pandas as pd
	xls = r'C:\Some\Arb\Folder\coords.xls'
	out_xls = r'C:\Some\Arb\Folder\geocoded.xls'
	df = pd.read_excel(xls)
	for index, row in df.iterrows():
	g = geocoder.google([row[3], row[2]], method='reverse')
	df.set_value(index, 'Street Address', g.address)
	df.to_excel(out_xls, 'Geocoded')

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reverseGeocodeXLScoords.py

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I used the geocoder library to do this. I used it previously when I still had an ArcGIS Online account and a Bing key to check geocoding accuracy amongst the three providers.

Since I don’t have those luxuries anymore, I used pandas to read in the spreadsheet and reverse geocode the coordinates found in the the third and fourth columns. I then added a new column to the data frame to contain the returned address, and copied the data frame to a new spreadsheet.

Filter a pandas data frame using a mask

After using pandas for quite some time now, I started to question if I was really using it effectively. After two MOOCs in R about 2 or 3 years ago, I realised that because my GIS work wasn’t in analysis, I would not be able to use it properly.

Similarly, because pandas is essentially the R of Python, I thought I wouldn’t be able to use all the features it had to offer. As it stands, I’m still hovering around in the data munging side of pandas.

	import pandas as pd
	in_xls = r"C:\Some\Arb\Folder\test.xlsx"
	columns = [0, 2, 3, 4, 6, 8]
	# Use a function to define the mask
	# to create a subset of the data frame
	def mask(df, key, value):
	return df[df[key] == value]
	pd.DataFrame.mask = mask
	# Out of the 101 rows, only 50 are stored in the data frame
	df = pd.read_excel(in_xls,0, parse_cols=columns).mask('Create', 'Y')

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filterDataFrameUsingMask.py

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I used a pandas mask to filter a spreadsheet (or csv) based on some value. I originally used this to filter out which feature classes need to be created from a list of dozens of templates, but I’ve also used it to filter transactions in the money tracking app I made for my household.

Add a new field to a feature class using NumPy

I needed to add a field to dozens of layers. Some of the layers contained the field already, some of them contained a similar field, and some of them did not have the field. I did not want to batch Add Field, because not only would it fail on the layers which already had the field, but it is super slow and I would then still have to transfer the existing values from the old field to the new field.

	'''
	@date 12/10/2015
	@author Cindy Williams
	Adds a new field to layers in a map document, based
	on a current field.
	For use in the Python window in ArcMap.
	'''
	import arcpy
	import numpy
	mxd = arcpy.mapping.MapDocument("CURRENT")
	lyrs = arcpy.mapping.ListLayers(mxd)
	# Create a numpy array with a link oid field and the fields to be added
	narray = numpy.array([], numpy.dtype([('objid', numpy.int), ('GIS_ID', '|S10'),]))
	for lyr in lyrs:
	if lyr.isFeatureLayer:
	# Find the current field with the values
	field = [field.name for field in arcpy.ListFields(lyr, "GIS_*")][0]
	# Prevent the tool from failing
	if field != "GIS_ID":
	# Add the field
	arcpy.da.ExtendTable(lyr,"OID@", narray, "objid")
	# Copy the field values to the new field
	with arcpy.da.UpdateCursor(lyr, ("GIS_ID", field)) as cursor:
	for row in cursor:
	row[0] = row[1]
	cursor.updateRow(row)

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addFieldWithExtendTable.py

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I wrote the tool in the ArcMap Python window, because I found it easier to load my layers into an mxd first as they were lying all over the place. The new field to be added is set up as a NumPy array, with the relevant dtype.

The script loops over all the layers in the document, adding the field via the Extend Table tool, and then transferring the values from the old field to the new field. Deleting the old field at the end would be an appropriate step to include, but I didn’t, purely because I’ve lost data that way before.

Split line interactively using ArcPy FeatureSets

Back when I was doing a lot of GIS work for civil and electrical asset management, a common task I had was to ensure that all civil structures represented as a polyline (reticulation and bulk pipelines, eletrical feeder cables, road surfaces etc) were split at the physical road intersections as seen on the latest available aerial imagery, as well as where they crossed each other.

This task wasn’t too much trouble if the lines were already drawn across each other, as more often than not, the lines crossed at the road intersections. The result was usually achieved by using the Planarize option on the Advanced Editing toolbar. However, it became a problem for new areas which had to be digitised by hand (no CAD drawings or shapefiles received), or lines which had to be corrected.

I would have to visually check on the imagery where the road intersections were, and then manually split each polyline. I ran through some ideas, including digitising all road intersections as points (which would be good data to have anyway), and then splitting all the lines at the closest intersection by using the Split Line at Point tool.

I did however want to create a method of splitting the line multiple times on the fly, instead of just splitting it once (which is the option provided by the Split button on the Editor toolbar). I wanted to be able to select a line, click as many points along the line as I wanted, and then split the line into those points.

	'''
	@date 06/10/2015
	@author Cindy Williams
	@version 1.0
	Uses an arcpy FeatureSet to allow the user to interactively create
	points on a line which will be used to split that line into parts,
	while retaining all attributes.
	Requirements:
	– Works as a script tool. Add to a toolbox.
	– Can only work on a single line for now. Select the line, right
	click the layer and "Create layer from selected features". Use
	this selection layer as input to the tool.
	– Digitise points snapped to the selected line. Tool will fail if not
	snapped
	– Digitise points left to right along the line.
	Future versions will include:
	– split multiple lines at same time
	– snap points automatically/error that points should be snapped
	– points will be sorted after digitising to ensure correct order
	Built on an idea here http://gis.stackexchange.com/questions/154708/standalone-python-script-to-split-a-polyline-with-a-point-layer
	'''
	import arcpy
	inset = arcpy.GetParameter(0) # FeatureSet of interactive points from ArcMap
	inline = arcpy.GetParameterAsText(1) # Input polyline feature layer
	# Get all field names excluding dynamic fields
	fields = ["SHAPE@"]
	fields.extend([field.name for field in arcpy.ListFields(inline) if field.name not in ["OBJECTID", "Shape_Length", "Shape"]])
	# Open an insert cursor for inserting the cut lines
	cursor_ins = arcpy.da.InsertCursor(inline, fields)
	# Get the spatial reference from the polyline
	sr = arcpy.Describe(inline).spatialReference
	# Get the polyline and delete the original record
	with arcpy.da.UpdateCursor(inline, fields) as cursor:
	for row in cursor:
	polyline = row
	cursor.deleteRow()
	# Iterate over the points
	with arcpy.da.SearchCursor(inset, "SHAPE@") as cursor:
	for row in cursor:
	point = row[0].firstPoint
	# Build a temporary diagonal line from the point
	diag = arcpy.Polyline(arcpy.Array([arcpy.Point(point.X + 10.0, point.Y + 10.0), arcpy.Point(point.X-10.0, point.Y-10.0)]), sr)
	# Cut the original polyline
	geom = polyline[0].cut(diag)
	# Create a new line with the right side of the geom i.e. finished with this side
	newline = [geom[1]]
	newline.extend(polyline[1:])
	# Insert the line into the feature layer
	cursor_ins.insertRow(newline)
	# Set the left side of the cut line as the new line for cutting
	polyline = [geom[0]]
	polyline.extend(newline[1:])
	# Insert the last portion of the line
	cursor_ins.insertRow(polyline)
	del cursor_ins
	del polyline

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splitLineAtInteractivePoint.py

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The tool iterates over all the points created by the user in the FeatureSet. For each point, a temporary diagonal is created to cut the original polyline. This new part is saved in a list and the tool runs again on the original polyline (minus the new part). Once all the points have been processed, the original polyline is removed from the feature class, and the new parts are inserted. All feature attributes are maintained.

My intention with this tool was to expand it with more features, fix the bugs (it would randomly not work) and upload it as a toolbox. However, the need to do that fell away. I also realised I was starting to get into a space where I was forcing as much code as I could into my work in order to get through the day.

Write contents of Word tables to a spreadsheet

I wrote this script for a former colleague last year. She had received a Word document containing about 600 tables which must have been dumped out of a database somewhere. The tables had the same header, and each table represented an “incident”, with dates, details etc.

She was requested to “put it into Excel”. After she had manually copied the first table into matching columns in a spreadsheet, she came to me. This type of thing is normally a task we would give to a student, as it has nothing to do with GIS. Nevertheless, when I saw the repeating structure I was sure I could come up with something to do this automatically.

	import docx
	import xlwt
	doc = r"C:\Some\Arb\Folder\input.docx"
	xls = r"C:\Some\Arb\Folder\output.xls"
	document = docx.Document(doc)
	book = xlwt.Workbook()
	cur_sheet = book.add_sheet("Tables")
	row_num = 0
	tables = document.tables # Get all the tables in the docx
	# Get the header row from the 1st table's 1st row
	for index, cell in enumerate(tables[0].rows[0].cells):
	cur_sheet.write(row_num, index, cell.text)
	for table in tables:
	for row in table.rows[1:]: # Skip the repeating header row of each table
	row_num += 1
	for index, cell in enumerate(row.cells):
	if cell != '':
	cur_sheet.write(row_num, index, cell.text.strip())
	book.save(xls)

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extractDOCtablesToXLS.py

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The script finds all the tables in the document, and grabs the header from the first table to serve as the headings in the spreadsheet. It then iterates over all the tables, skips the header row and populates the spreadsheet with all the rows from the various tables.

It took about 15 minutes to write (had to play around with accessing the table elements correctly) and less than a minute to extract the data. That’s the amount of time it would have taken to copy 5 of the tables manually. At that pace it would have taken about 4 days to complete the process.

Write feature class properties to a Word document using python-docx

It’s been too long since I’ve posted some code. A few months ago I had a requirement to basically create a UML view of a file gdb and present each feature class as tables for inclusion in a functional specification Word document.

Sadly, since the demise of ArcGIS Diagrammer, there has never been something to take its place. The actual request I received was to take screenshots of the properties dialog box of each feature class in ArcCatalog, and paste those into the document with appropriate headings.

I recognised this request for the total waste of my time it would be, and promptly set about looking for an alternative. I realised I had python-docx already installed.

	'''
	@date 15/09/2015
	@author Cindy Williams
	Uses the python-docx package to write various
	properties of a feature class to docx format.
	'''
	import arcpy
	from docx import Document
	arcpy.env.workspace = r"C:\Some\Arb\Folder\work.gdb"
	doc = r"C:\Some\Arb\Folder\test.docx"
	document = Document()
	document.add_paragraph("This document contains a description of fields per feature class.")
	for fc in arcpy.ListFeatureClasses():
	p = document.add_paragraph("Feature class: ")
	p.add_run(fc).bold = True
	p.add_run("\n")
	table = document.add_table(rows=1, cols=2, style='Table Grid')
	header_cells = table.rows[0].cells
	header_cells[0].text = "Field Name"
	header_cells[1].text = "Field Type"
	for field in arcpy.ListFields(fc):
	row_cells = table.add_row().cells
	row_cells[0].text = field.name
	row_cells[1].text = field.type
	document.add_page_break() # Each feature class on its own page
	document.save(doc)

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writeFieldsToDOC.py

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For each feature class in the geodatabase, a new paragraph is started with the name of the feature class in bold. A line break is inserted, followed by a table. The name and type of each field is added as a new row into the table, and a page break is inserted to start the properties of the next feature class on a new page.

It took me about an hour to look up alternative methods and to put this script together. Most of the time was spent on getting the cells in the table to insert properly, using the age-old method of trial and error. I did it this way to save myself the pain of manually inserting screenshots, knowing that if the format of the feature classes changed I would have to do new screenshots repeatedly.

Display raster properties arcpy vs numpy

	#
	# @date 25/08/2015
	# @author Cindy Williams
	#
	# Prints a comparison of the specified raster
	# properties using arcpy and numpy.
	#
	# For use as a standalone script.
	#
	import arcpy as ap
	import numpy as np
	ext_lyr = ap.management.MakeFeatureLayer(r"") # Extent polygon shapefile/feature class
	input_raster = ap.Raster(r"") # Raster containing values
	def get_raster_properties(ras, prop):
	array = ap.RasterToNumPyArray(ras, nodata_to_value=0)
	ap_answer = ap.management.GetRasterProperties(ras, prop)
	if prop == "MEAN":
	np_answer = array.mean()
	if prop == "SUM":
	np_answer = array.sum()
	if prop == "ROWCOUNT":
	np_answer = array.shape[0]
	if prop == "COLUMNCOUNT":
	np_answer = array.shape[1]
	# etc
	return (ap_answer, np_answer)
	with arcpy.da.SearchCursor(ext_lyr, ("SHAPE@", "Name")) as cursor:
	for row in cursor:
	# Get the extent of the current feature
	ext = row[0].extent
	# Build the feature envelope from the extent
	enve = "{0} {1} {2} {3}".format(ext.XMin, ext.YMin, ext.XMax, ext.YMax)
	# Clip the raster to the envelope in memory
	clipped_raster = ap.Raster(ap.management.Clip(input_raster, enve, r"in_memory\clip"))
	# Get the properties
	(arcpy_ans, numpy_ans) = get_raster_properties(clipped_raster, "MEAN")
	print("{0}\tarcpy: {1}\tnumpy: {2}".format(row[1], arcpy_ans, numpy_ans))
	# Clean up after each run
	ap.management.Delete("in_memory")

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displayRasterProperties.py

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Convert multi-page PDF file to TIFF

	#
	# @date 18/08/2015
	# @author Cindy Williams
	#
	# Converts a range of pages from a pdf to separate tiff
	# files using the PDF to TIFF tool added at ArcGIS 10.3.
	# For very basic conversion, with minimal error handling.
	#
	# For use as a standalone script.
	#
	import arcpy
	import os
	def convertPDFtoTIFF(in_pdf, out_folder, out_tiff, start_page=1, end_page=1):
	if start_page > end_page:
	print("The start page number cannot exceed the end page number.")
	else:
	for i in range(start_page, end_page + 1):
	out_tiff_name = os.path.join(out_folder, out_tiff + str(i) + ".tif)
	arcpy.conversion.PDFtoTIFF(in_pdf, out_tiff_name, pdf_page_number=i)
	print("Processed page " + str(i))
	pdf_in = r"C:\Some\Arb\Folder\test.pdf"
	tif_folder = r"C:\Some\Arb\Folder\tiffs"
	convertPDFtoTIFF(pdf_in,tif_folder, "Page_", 2,9)
	print("Script complete.")

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convertMultiPagePDFtoTIFF.py

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A new tool was added to ArcGIS 10.3 to convert a page in a PDF to TIFF. This is especially useful for the asset management work I do, as I often get pdf drawings or maps which need to be georeferenced. I created a function to wrap around the ArcGIS one to enable the conversion of more than one page in the pdf at a time.

By default, the function will only convert the first page. Specifying a start and/or end page will override the defaults. Link to the code is here.

Reformat all layer names in an ArcMap document

*Before I get into today’s script, I’ve noticed that the embedded gists do not appear on mobile devices when accessing the feed for this blog via Feedly or some other RSS reader. The post needs to be opened in a web browser to view the code. I’ll also be including a link to it at the end of the post.

When I create feature classes for asset management data manually instead of automatically, I always make sure to name them consistently. However, I rarely change the feature class alias manually. This means that when I need to pull all the layers into a map to create a kml, I need to rename each layer.

Which is why I turn to Python instead.

	#
	# @date 14/08/2015
	# @author Cindy Williams
	#
	# Quickly formats the names of all the layers in a map
	# document. In this example, the part of the name before
	# the first full stop is removed, underscores are replaced
	# spaces, a regex is used to insert spaces before capitals
	# and the string is converted to proper case.
	#
	# For use in the Python window in ArcMap.
	#
	import arcpy
	import re
	mxd = arcpy.mapping.MapDocument("CURRENT")
	lyrs = arcpy.mapping.ListLayers(mxd)
	for lyr in lyrs:
	new_name_replaced = lyr.name.split(".")[1].replace("_", " ")
	new_name_spaced = re.sub(r"(\w)([A-Z])", r"\1 \2", new_name_replaced)
	lyr.name = new_name_spaced.title()
	arcpy.RefreshTOC()

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reformatAllLayerNames.py

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Of course, the way the name gets split will change depending on the current format of the names. In this instance, the part of the name that I needed occurred after the first full stop, and contained underscores which needed to be replaced by spaces. I then used a regular expression to insert spaces between InitialCaps words.

Link to the code is here.