Export table structure from ArcGIS GDB to Excel

Question

I am wanting to do a visual table-structure comparison of feature classes in an enterprise GDB to feature classes in a File GDB. Just want to compare things like field names and types.

Is there a way to quickly export the table structure from GDB to Excel?

I don't need the actual data, just the field names and types, and maybe alias. Export table structure information to Excel QGIS or MapInfo is a similar question (but for different GIS software).

I know I can get this information by using ArcPy Describe, but I really don't want to spend much time on it, and am thinking there's possibly a right-click type function in ArcCatalog, or maybe something in Toolbox, I just can't find anything right now. The closest I've found is exporting the workspace XML, but this is a bit messier than I'd like.

Is there a tool or function in ArcGIS Desktop to output the table structure to Excel (XLS, XLSX, CSV, etc)?

• Midavalo: @BERA Indeed - that will be my go-to if there isn't something quicker/easier that I've missed somehow.
• Son of a Beach: XRay for ArcCatalog is the way to go for documenting your GDB schema. See: arcgis.com/home/item.html?id=35e14ba8a03d49188ee8ead2e79f24d3 . It's not for Excel particularly (although I did once write a script to parse the HTML into CSV for import to Excel). The HTML output that it can produce is the best way to document and review GDB schema.

Answer 1

This code will output the field info for all the tables to a spreadsheet.

import pandas as pd
import openpyxl
# define workspace and output
arcpy.env.workspace = r"path\to\gdb.gdb"
excel_file = r"spreadsheet.xlsx"
writer = pd.ExcelWriter(excel_file, engine='openpyxl')
#for each table
for tbl in arcpy.ListTables():
 #create empty pandas dataframe
 df = pd.DataFrame(columns = ['Name', 'Alias','Type','Length','Domain'])
 #loop through fields and add rows to df
 for field in arcpy.ListFields(tbl):
 df.loc[len(df.index)] = [field.name, field.aliasName, field.type, field.length,field.domain]
 #then save to Excel
 df.to_excel(writer, sheet_name=tbl,index=False)
writer.save()