rabbleNaut

'''
Used for renaming photos in a folder using a matching ID
7/7/2015
'''
import os, csv

#declare new dictionary
IDs = {}

#build dictionary using input csv file. csv should be setup as key:value pairs

rabbleNaut

import os, csv
from arcpy import *

# Checks to see which districts are intersected by the project area
def checkDistricts():
	x = 0
	for fc in fcList:
		x += 1
		flyr = 'flayer' + str(x)
		MakeFeatureLayer_management(fc, flyr)

rabbleNaut

'''
===========================
listAliases.py

4/8/2014

This script will allow the user to select a feature class and output the features Name, Alias, and Type to a .csv file. 

Arguments: 
0 - Input Featureclass

rabbleNaut

'''
DoForms_Downloader.py
v1.10

3/21/2014


This script will accomplish the following: 

- Allows user to select featureclass generated from DoForms

rabbleNaut

'''===============================
ClipLooper.py

The purpose of this script is to step through all 10 counties in the dataset and 
clip each of the 3 features (Water Bodies, Streams, City Limits) to the counties border. 

Script Arguments:
0 - Input County FC
1 - Input Water Bodies FC
2 - Input Streams FC

rabbleNaut

import arcpy
from arcpy import *

env.workspace = r"C:\Users\RABBEY-C\RA_GIS\Projects\RA_EMST\Updated_Phase_Features.gdb\District_Unions"


fcList = arcpy.ListFeatureClasses()

#Renames featureclasses ending in "_Union" with "" 
for fc in fcList:

rabbleNaut

'''
batchFieldDelete.py

Iterate through features in featuredataset to delete unwanted fields. 

Delete fields:
1 - Area_MI
2 - DOT_Feature
3 - Area_MI
'''

rabbleNaut

'''
batchFieldUpdate.py

For each feature class in EMST_Districts on Comanche.sde, do the following: 

1 - Adds new field "Feature_Type"
2 - Calculates field
	  if type = null add "vegetation"

'''

rabbleNaut

import csv

# Removes columns starting at remove_from up to-  but *not including*  - remove_to 
# In this example, all columns are removed except for the first 5 and last 21

remove_from = 5
remove_to = 239


fp_in = open("tx000452010.txt", "rb")

rabbleNaut

import csv

#removes columns starting at remove_from up to-  but *not including*  - remove_to
remove_from = 239
remove_to = 260

fp_in = open("tx000452010.txt", "rb")
fp_out = open("tx000452010_PT1.txt", "wb")

reader = csv.reader(fp_in, delimiter=",")