import platform
print(platform.python_version())

# List the current working folder and its content
import os
curFolder = os.getcwd()
print("The current working folder is " + curFolder)

filesDirs = os.listdir(curFolder)
# This is a list. We can print the entire list
# print(filesDirs) 

#  We can also loop through each of them and print those ends with .ipynb
for fileDir in filesDirs:
    if fileDir.endswith(".ipynb"):
        # print(fileDir)
        print(f'{fileDir}')
        # print('error')

# Some example to start
from random import seed, sample
seed(1009) # specify a random seed for replicability
# range method generate a list from 0 to 200 (not included) by step of 1
# sample method in random package then randomly selects a given #, i.e., 50, of elements from the list
rndList_1  = sample(range(0, 200, 1), 50)  
print(rndList_1)

# A slightly different way
import random
random.seed(1009)
rndList_2 = []
for i in range(1, 50):
    rndList_2.append(random.randint(0, 200))

print(rndList_2)

# Manual list
randList_3 = [2, 3, 7.3, 9, 343, 23, 12, 56, 98, 23]

# Data Source https://eric.clst.org/assets/wiki/uploads/Stuff/gz_2010_us_050_00_5m.json
# Read from a local file
import json

# Use "with ... as ..." to better handle exceptions
with open("gz_2010_us_050_00_20m.json", 'r') as f:
  data = json.load(f)

print('Number of Counties in US: {}'.format(len(data['features'])))

# The name of the first feature
print(f"The second feature name is {data['features'][1]['properties']['NAME']}")

# May or may not run. Check the online source if it does not work.
import requests, json 
url = "https://eric.clst.org/assets/wiki/uploads/Stuff/gz_2010_us_050_00_5m.json"

with requests.get(url) as response:
    data = response.json()
    # Two different ways of composing text messages. The format function is preferred.

    # Three different ways of printing messages
    # 1. Use + to concatenate strings, or "," for multiple values.
    print('Number of Counties in US: ' + str(len(data['features'])))
    print('Number of Counties in US:', len(data['features']))
    # 2. Use format function
    print('The first entry is {}'.format(data['features'][0]['properties']['NAME']))
    # 3. use f to print
    print(f'The second entry is {data["features"][1]["properties"]["NAME"]}')

    # Work on this "data" variable using loops and the data structures of list, dictionary, and set.

'''
This sample code illustrate the basic logic of looping through the List of features.
Note GeoJSON is a multi-level combination of List and Dictionary.
All JSON files, including GeoJSON, are plain text file. 
You can open them directly and see what are inside the files.
'''
# This will be a list of Feature
featureList = data['features']
cntyDict = {}

for f in featureList:
    # f will be an individual feature, i.e., a county for this data set

    # name will be the county name
    name = f['properties']['NAME']

    # if cntyDict.get(name) == None:
    # or
    if cntyDict.get(name) is None:
        # This one use an integer as the value of the dictionary
        cntyDict.update({name: 1})

        # You can also use a list to save state names/codes or a dictionary for state names/codes as well as other information
        # cntyDict.update({name: [f['properties']['STATE']]})
        # Once more, think about the data structure that is necessary to help answer your questions
    else:
        # Do something here 
        # The dictionary has already had the key, so that we know we should 
        # 1) add 1 to the value associated with the key, if your dictionary value is integer, or
        # 2) add the state name/code to the list associated with the key, if the value is a list.
        pass
 
# Once you have the dictionary cntyDict. Sort it by value.
    
# kvItem is a (key, value) pair item from a dictionary
def sortFunction(kvItem):
    return kvItem[1] # The value in the pair

cntyDictSorted = sorted(cntyDict.items(), key=sortFunction, reverse=True)

# or use lambada
cntyDictSorted = sorted(cntyDict.items(), key=lambda item:item[1], reverse=True)

print(cntyDictSorted[0:3])
list(cntyDictSorted[0:3].keys())

import random
import string

s = string.ascii_lowercase + string.digits
n = 100200
payee_ids = [None]*n

# set the random seed, so results are replicable
random.seed( 1090 )

for i in range(n):
    payee_ids[i] = ''.join(random.choice(s) for _ in range(10))

# Using list comprehensions would be much more concise.
# But this is little bit hard to understand as it has two layers of list comprehensions
# payee_ids = [''.join(random.choice(s) for i in range(10)) for _ in range(n)]

# Exclude any possible duplicates (extremely unlikely, but possible)
payee_ids = list(set(payee_ids))[0:100000]

print(payee_ids[0:10])

# import datetime and timedelta classes from the datetime module
from datetime import datetime, timedelta

fDate = datetime(2023, 9, 1)
tDate = datetime(2023, 11, 25)

dd = (tDate - fDate).days
nn = round(len(payee_ids)*dd*2.5) # on average, each payee makes two and half trips.

# This line should be removed or commented out for the final run.
nn = 100 # this number is used to debug the code. 

# the time during the day does not really matter for OMNY rules. We just set it to a random number between 5 to 23.
payTime = [fDate + timedelta(days = random.uniform(0, dd), \
                             hours = random.choice(range(5,24)), \
                             minutes = random.choice(range(0, 60)), \
                             seconds=random.choice(range(0, 60))) for _ in range(nn)]

payees = random.choices(payee_ids, weights=[abs(random.normalvariate(0,1)) for _ in range(len(payee_ids))], k=nn)

simData = [list(x) for x in zip(payees, payTime)]
# Sort according to the time, from early to late.
simSData = sorted(simData, key= lambda z: z[1])

# Print the top 10 rows
for k in range(10):
    print()
    print("Index: {}, ID: {}, Time: {}".format(k, simSData[k][0], "" + simSData[k][1].strftime("%Y/%m/%d %I:%M%p, %A")))

for k in range(10):
    print()
    print("Index: {}, ID: {}, Time: {}, Charge: ${}".format(k, 
        simSData[k][0], 
        "" + simSData[k][1].strftime("%Y/%m/%d %I:%M%p, %A"), 
        random.choice([2.90, 0.00]) # This random value should be replaced by values from your algorithm.
    ))

import math as mth
import random

class Geom():
  geomType = 'Generic Geometry Type'
  
  # Constructor of the class: used to initialize an object
  # It could have optional parameters. 
  # If the caller does not provide name and color, random values will be assigned.
  def __init__(self, name = None, color = None):
    # Check out the names and the faker packages for random names
    self.name = name if not name is None else random.choice(['Bill','Sally','Tamica','Josh','Lammar','Hussain'])
    self.color = color if not color is None else random.choice(['BLUE', 'RED', 'PURPLE', 'YELLOW'])
  
  # This is a method that all children will inherit. 
  # In other words, all children will have this method without explicitly defining it. 
  def print_name(self):
    print('My name is ', self.name, 'and my color is ', self.color)

  @classmethod
  def area(self):
    return None

  # Another method: why we can call self.area without defining it here?
  def makeString(self):
    return f"Name: {self.name}, Color: {self.color}, Area: {self.area()}"

class Circle(Geom):
  
  def __init__ (self, r):
    self.radius = r
    super().__init__()

  # area method  
  def area(self):
     return mth.pi * self.radius **2

class Square(Geom):
  #
  def __init__ (self, s):
    self.side = s
    super().__init__()
  # area method  
  def area(self):
     return self.side **2

side = 8
my_square = Square(side)
print('Length of the side is', my_square.side)
my_square.print_name()
print('My area is ', my_square.area())

circle_list = [Circle(i) for i in range(2,4)]
print(circle_list)

for x in circle_list:
    x.print_name()

print([x.makeString() for x in circle_list])

GTECH 331/731 Lab Assignments ¶

Assignment 0: Setting up the playground ¶

Task 1 Install Python with Miniforge, Conda, or Miniconda ¶

Task 2 First Python Code: hello world!¶

Assignment 1 ¶

Task 1 Get the Python version on your computer.¶

Task 2 Write Python code to do the following:¶

Assignment 2 ¶

Task 1 Make a list of unique US county names ¶

Task 2 Find the three most common names of the counties.¶

Task 3 Basic statistics by state ¶

Assignment 3 ¶

Task 1 Code refactoring ¶

Task 2 OMNY's 7-day cap ¶

Assignment 4 ¶

Task 1 Create Python Classes ¶

Task 2 Create a Package ¶

Assignment 5 ¶

Task 1 Install Plotly ¶

Task 2 Visualize Data using Plotly ¶

Task 3 Export Plotly Visuals ¶

Assignment 6 ¶

Task 1 Install GeoPandas ¶

Task 2 Process Spatial Data with GeoPandas ¶

Task 3 Make Maps using GeoPandas ¶

Assignment 7 ¶

Task 1 Develop Python tool in ArcGIS Pro ¶

Task 2 Plan Final Project ¶

Assignment 8 ¶

Apply Pandas and GeoPandas to Spatial Analysis ¶

Course Project ¶

Proposal ¶

Presentation ¶

Final Project Report ¶