├── 2021_05_14_ImageProcessing ├── images │ ├── images.txt │ ├── lena.png │ ├── stop.png │ ├── flower.png │ ├── karel.png │ ├── leaves.png │ ├── burrito.jpg │ ├── simba-sq.jpg │ └── mt-rainier.jpg ├── reflection_rainier.png ├── results │ ├── lena_cropped.png │ ├── lena_doubled.png │ ├── lena_mirrored.png │ ├── lena_rotated.png │ └── lena_shrunk.png ├── reflection.py ├── cropping.py ├── flipping.py ├── rotating.py ├── bordering.py └── scaling.py ├── .gitattributes ├── 2021_05_21_DataScience ├── assets │ ├── covid_statistics.png │ └── covid_machine_learning.png ├── data_science │ ├── __pycache__ │ │ ├── linear.cpython-38.pyc │ │ └── dataload.cpython-38.pyc │ ├── covid_analysis.py │ └── countries │ │ ├── Samoa.txt │ │ ├── Vanuatu.txt │ │ ├── Micronesia.txt │ │ ├── Marshall Islands.txt │ │ ├── Solomon Islands.txt │ │ ├── Holy See.txt │ │ ├── Fiji.txt │ │ ├── Saint Kitts and Nevis.txt │ │ ├── Laos.txt │ │ ├── Timor-Leste.txt │ │ ├── Dominica.txt │ │ ├── Grenada.txt │ │ ├── Bhutan.txt │ │ ├── Saint Vincent and the Grenadines.txt │ │ ├── Antigua and Barbuda.txt │ │ ├── Saint Lucia.txt │ │ ├── Papua New Guinea.txt │ │ ├── Tanzania.txt │ │ ├── Seychelles.txt │ │ ├── Burundi.txt │ │ ├── Barbados.txt │ │ ├── Brunei.txt │ │ ├── Comoros.txt │ │ ├── Liechtenstein.txt │ │ ├── Monaco.txt │ │ ├── Eritrea.txt │ │ ├── Mauritius.txt │ │ ├── Cambodia.txt │ │ ├── Sao Tome and Principe.txt │ │ ├── Diamond Princess.txt │ │ ├── Taiwan.txt │ │ ├── Gambia.txt │ │ ├── Mongolia.txt │ │ ├── Lesotho.txt │ │ ├── Chad.txt │ │ ├── San Marino.txt │ │ ├── Bahamas.txt │ │ ├── Yemen.txt │ │ ├── Suriname.txt │ │ ├── Belize.txt │ │ ├── Guyana.txt │ │ ├── Benin.txt │ │ └── Liberia.txt └── json_parser │ ├── snow.json │ └── json_parser.py ├── 2021_05_07_ProblemSolving ├── __pycache__ │ └── factorial.cpython-38.pyc ├── khansole.py ├── factorial.py ├── runningtotal.py ├── fizzbuzz.py └── nextkhansole.py ├── test.py ├── 2024_05_31_DataStructures ├── test_mars.py ├── mars.py ├── snow_plot.py ├── test_factorial.py ├── planet_conditional.py ├── factorial.py └── planet_dictionary.py ├── 2021_04_30_Dependencies ├── random_number.py ├── mars.py └── main.py ├── LICENSE └── .github └── workflows └── main.yml /2021_05_14_ImageProcessing/images/images.txt: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /.gitattributes: -------------------------------------------------------------------------------- 1 | *.py linguist-detectable=true 2 | *.ipynb linguist-detectable=false 3 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/images/lena.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lnugraha/code-in-place-extra/HEAD/2021_05_14_ImageProcessing/images/lena.png -------------------------------------------------------------------------------- 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/2021_05_21_DataScience/data_science/__pycache__/dataload.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/lnugraha/code-in-place-extra/HEAD/2021_05_21_DataScience/data_science/__pycache__/dataload.cpython-38.pyc -------------------------------------------------------------------------------- /2021_05_21_DataScience/json_parser/snow.json: -------------------------------------------------------------------------------- 1 | [{"Snow": [23.1, 32.8, 31.8, 32.0, 30.4, 24.0, 39.5, 24.2, 52.5, 37.9, 30.5, 25.1, 12.4, 35.1, 31.5, 21.1, 27.6]}, 2 | {"Yield": [10.5, 16.7, 18.2, 17.0, 16.3, 10.5, 23.1, 12.4, 24.9, 22.8, 14.1, 12.9, 8.8, 17.4, 14.9, 10.5, 16.1]}] 3 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/reflection.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | 3 | def main(): 4 | original = cv2.imread("./images/mt-rainier.jpg") 5 | reverse = cv2.flip(original, 0) 6 | 7 | reflectionCombined = cv2.vconcat([original, reverse]) 8 | cv2.imwrite("reflection_rainier.png", reflectionCombined) 9 | 10 | if __name__ == "__main__": 11 | main() 12 | -------------------------------------------------------------------------------- /test.py: -------------------------------------------------------------------------------- 1 | import math, glob, os 2 | import numpy as np 3 | 4 | def area_rect(length, width): 5 | return length*width 6 | 7 | def test_area_rect_1(): 8 | assert area_rect(3,5) == 15 9 | 10 | def test_area_rect_2(): 11 | assert area_rect(2.5,4) == 10.0 12 | 13 | def test_file1_method1(): 14 | x=5; y=6 15 | assert y-1 == x,"test failed" 16 | # assert x == y,"test failed" 17 | 18 | def test_file1_method2(): 19 | x=5; y=6 20 | assert x+1 == y,"test failed" 21 | -------------------------------------------------------------------------------- /2021_05_07_ProblemSolving/khansole.py: -------------------------------------------------------------------------------- 1 | import random 2 | 3 | def main(): 4 | numOne = random.randint(0, 10) 5 | numTwo = random.randint(0, 10) 6 | print("What is the addition of " + str(numOne) + " + " + str(numTwo)) 7 | answer = input("Please enter your answer: ") 8 | answer = int(answer) 9 | if answer != (numOne + numTwo): 10 | print("Incorrect, the answer should be " + str(numOne+numTwo)) 11 | else: 12 | print("Correct answer") 13 | 14 | if __name__ == "__main__": 15 | main() 16 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/cropping.py: -------------------------------------------------------------------------------- 1 | import cv2 2 | 3 | def main(): 4 | lena = cv2.imread("./images/lena.png") 5 | height = lena.shape[0] 6 | width = lena.shape[1] 7 | 8 | # Determine your initial position that you want to crop 9 | y_init = 125 10 | x_init = 125 11 | 12 | # Determine the size of the final image that you want to crop 13 | y_size = 300 14 | x_size = 300 15 | 16 | # Finalize your modified image 17 | lena_modified = lena[y_init:y_init+y_size ,x_init:x_init+x_size] 18 | 19 | # Save your image 20 | cv2.imwrite("./results/lena_cropped.png",lena_modified) 21 | 22 | if __name__ == "__main__": 23 | main() 24 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/flipping.py: -------------------------------------------------------------------------------- 1 | """ 2 | May 12, 2021 3 | This program demonstrates image rotation methods 4 | """ 5 | 6 | import cv2 7 | import math 8 | 9 | def main(): 10 | # 1. Load your original image 11 | lena = cv2.imread("./images/lena.png") 12 | 13 | # 2. Image flip here 14 | # Three possible image flip positions 15 | # 0: vertical flip 16 | # 1: horizontal flip 17 | # -1: both vertical and horizontal flip 18 | flip_code = 1 # mirroring 19 | lena_modified = cv2.flip(lena, flip_code) 20 | 21 | # 3. Save your modified image 22 | cv2.imwrite("./results/lena_mirrored.png", lena_modified) 23 | 24 | if __name__ == "__main__": 25 | main() 26 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/test_mars.py: -------------------------------------------------------------------------------- 1 | # python3 -m unittest test_mars.py 2 | 3 | import unittest 4 | from mars import calculate_mars_weight 5 | 6 | class TestFactorial(unittest.TestCase): 7 | def test_factorial_iteration(self): 8 | self.assertAlmostEqual(calculate_mars_weight(10), 3.78) 9 | self.assertAlmostEqual(calculate_mars_weight(100), 37.8) 10 | 11 | def test_negative(self): 12 | self.assertRaises(ValueError, calculate_mars_weight, 0) 13 | self.assertRaises(ValueError, calculate_mars_weight, -1) 14 | 15 | def test_nonnumber(self): 16 | self.assertRaises(TypeError, calculate_mars_weight, True) 17 | self.assertRaises(TypeError, calculate_mars_weight, "codeinplace") 18 | -------------------------------------------------------------------------------- /2021_05_07_ProblemSolving/factorial.py: -------------------------------------------------------------------------------- 1 | # Use the command below to perform doctest 2 | # python3.8 -m doctest factorial.py -v 3 | 4 | import math 5 | 6 | def factorial_for(n): 7 | result = 1 8 | for i in range(1, n+1, 1): 9 | result = result * i 10 | return result 11 | 12 | def factorial_recursive(n): 13 | """ 14 | >>> factorial_recursive(3) 15 | 6 16 | >>> factorial_recursive(5) 17 | 120 18 | >>> factorial_recursive(0) 19 | 1 20 | >>> factorial_recursive(1) 21 | 1 22 | """ 23 | if (n == 1 or n == 0): 24 | return 1 # Base Case 25 | elif (n > 1): 26 | return factorial_recursive(n-1)*n 27 | 28 | if __name__ == "__main__": 29 | check = factorial_for(5) 30 | print(check) 31 | 32 | test = factorial_recursive(5) 33 | print(test) 34 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/rotating.py: -------------------------------------------------------------------------------- 1 | """ 2 | May 12, 2021 3 | This program demonstrates image rotation methods 4 | """ 5 | 6 | import cv2 7 | import math 8 | 9 | def main(): 10 | # 1. Load your original image 11 | lena = cv2.imread("./images/lena.png") 12 | 13 | # 2. Image rotation here; assume rotate by 90 deg or 180 deg or 270 deg 14 | # Only select those 3 angles to avoid unnecessary image interpolation 15 | # a. Rotate 90 degree clockwise: cv2.ROTATE_90_CLOCKWISE 16 | # b. Rotate 180 degree clockwise: cv2.ROTATE_180 17 | # c. Rotate -90 degree clockwise: cv2.ROTATE_90_COUNTERCLOCKWISE 18 | lena_rotated = cv2.rotate(lena, cv2.ROTATE_90_CLOCKWISE) 19 | 20 | # 3. Save your modified image 21 | cv2.imwrite("./results/lena_rotated.png", lena_rotated) 22 | 23 | if __name__ == "__main__": 24 | main() 25 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/bordering.py: -------------------------------------------------------------------------------- 1 | """ 2 | May 12, 2021 3 | Add border surrounding an image 4 | The border color can also be changed with the provided color 5 | """ 6 | 7 | import cv2 8 | import numpy as np 9 | 10 | def main(): 11 | # 1. Load your image 12 | original_img = cv2.imread("./images/simba-sq.jpg") 13 | height = original_img.shape[0] 14 | width = original_img.shape[1] 15 | print("Height: {}, width: {}".format(height, width)) 16 | 17 | # 2. Add border surrounding the image 18 | # Say border thickness is 30 pixels 19 | # Begin by creating a new canvas 20 | border = 30 21 | new_height = height + 2*border 22 | new_width = width + 2*border 23 | new_image = np.zeros((new_height, new_width, 3), dtype=np.uint8) 24 | 25 | 26 | # 3. Save the image 27 | 28 | if __name__ == "__main__": 29 | main() 30 | -------------------------------------------------------------------------------- /2021_05_07_ProblemSolving/runningtotal.py: -------------------------------------------------------------------------------- 1 | import math 2 | 3 | def running_total(): 4 | 5 | inputInt = input("Enter your first number: ") 6 | inputInt = int(inputInt) 7 | 8 | if inputInt != 0: 9 | sumTotal = inputInt 10 | 11 | while True: 12 | nextInt = input("Enter an integer: ") 13 | nextInt = int(nextInt) 14 | sumTotal = sumTotal + nextInt 15 | 16 | if nextInt == 0: 17 | print("The cumulative sum: {}".format(sumTotal)) 18 | break 19 | else: 20 | print("The current cumulative sum: {}".format(sumTotal)) 21 | continue 22 | 23 | else: 24 | print("Your input number is zero, so the program terminates") 25 | 26 | if __name__ == "__main__": 27 | running_total() 28 | 29 | 30 | 31 | -------------------------------------------------------------------------------- /2021_04_30_Dependencies/random_number.py: -------------------------------------------------------------------------------- 1 | """ 2 | April 28, 2021 3 | By Leo Nugraha 4 | This program demonstrates the following topics: 5 | 1. How to generate random number 6 | 2. How to use Python built-in library dependency 7 | """ 8 | 9 | def random_1_to_8_ver_01(): 10 | import random 11 | random_number = random.randint(1,8) 12 | return random_number 13 | 14 | def random_1_to_8_ver_02(): 15 | import random 16 | # Multiply it by seven to have a range between 0 and 7, 17 | # then add one to shift the range from 1 to 8 18 | random_number = int( random.random()*7 ) + 1 19 | return random_number 20 | 21 | if __name__ == "__main__": 22 | test_01 = random_1_to_8_ver_01() 23 | print("The first random number: {}".format(test_01)) 24 | test_02 = random_1_to_8_ver_02() 25 | print("The second random number: {}".format(test_02)) 26 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/mars.py: -------------------------------------------------------------------------------- 1 | mars_dictionary = { "mars" : 0.378 } 2 | 3 | def calculate_mars_weight(earth_weight_float): 4 | if earth_weight_float <= 0: 5 | raise ValueError("Cannot have weight equals to or less than zero") 6 | 7 | if type(earth_weight_float) not in [int, float]: 8 | raise TypeError("Cannot have weight that is not in rational number") 9 | 10 | mars_weight_float = mars_dictionary['mars'] * earth_weight_float 11 | 12 | return mars_weight_float 13 | 14 | def main(): 15 | earth_weight_string = input('Enter a weight on earth: ') 16 | earth_weight_float = float(earth_weight_string) 17 | 18 | mars_weight_float = calculate_mars_weight(earth_weight_float) 19 | mars_weight_string = str(mars_weight_float) 20 | 21 | print('The equivalent weight on Mars: ' + mars_weight_string) 22 | 23 | if __name__ == '__main__': 24 | main() 25 | -------------------------------------------------------------------------------- /2021_05_07_ProblemSolving/fizzbuzz.py: -------------------------------------------------------------------------------- 1 | import math 2 | 3 | fizz = 5; buzz = 3 4 | 5 | def fizzbuzz_forloop(): 6 | n = 31 7 | for i in range(1, n, 1): 8 | if (i % (fizz * buzz) == 0): 9 | print("FizzBuzz {}".format(i)) 10 | elif (i % fizz == 0): 11 | print("Buzz {}".format(i)) 12 | elif (i % buzz == 0): 13 | print("Fizz {}".format(i)) 14 | else: 15 | print(i) 16 | 17 | def fizzbuzz_while(): 18 | n = 31; i = 0 19 | while i < n: 20 | if (i % (fizz * buzz) == 0): 21 | print("FizzBuzz {}".format(i)) 22 | elif (i % fizz == 0): 23 | print("Buzz {}".format(i)) 24 | elif (i % buzz == 0): 25 | print("Fizz {}".format(i)) 26 | else: 27 | print(i) 28 | i = i+1 29 | 30 | if __name__ == "__main__": 31 | fizzbuzz_forloop() 32 | fizzbuzz_while() 33 | -------------------------------------------------------------------------------- /2021_05_21_DataScience/json_parser/json_parser.py: -------------------------------------------------------------------------------- 1 | import sys 2 | sys.path.insert(1,'../src') 3 | 4 | import linear 5 | import dataload 6 | 7 | """ 8 | import numpy as np 9 | import matplotlib.pyplot as plt 10 | import json 11 | 12 | def retrieveJSON(filePath, uniqueKey): 13 | with open(filePath) as fileData: 14 | entireData = json.load(fileData) 15 | # Retrieve independent variable x 16 | xValues = entireData[0] 17 | xElements = xValues[uniqueKey[0]] 18 | # Retrieve dependent variable y 19 | yValues = entireData[1] 20 | yElements = yValues[uniqueKey[1]] 21 | return xElements, yElements 22 | """ 23 | 24 | def main(): 25 | snowJSON = "snow.json" 26 | snowArr, yieldArr = dataload.loadJSON(snowJSON, ["Snow", "Yield"]) 27 | print(f"Water content of snow: {snowArr}") 28 | print(f"Water yield: {yieldArr}") 29 | 30 | if __name__ == "__main__": 31 | main() 32 | -------------------------------------------------------------------------------- /2021_05_07_ProblemSolving/nextkhansole.py: -------------------------------------------------------------------------------- 1 | import random 2 | 3 | def main(): 4 | # Check if there questions have been answered consecutively 5 | counter = 0 6 | while True: 7 | if counter != 3: 8 | numOne = random.randint(0, 10) 9 | numTwo = random.randint(0, 10) 10 | print("What is the addition of {} and {}".format(numOne, numTwo)) 11 | answer = input("Your answer is ") 12 | answer = int(answer) 13 | if answer == (numOne + numTwo): 14 | counter = counter + 1 15 | print("Correct answer! You have answered {} questions correctly".format(counter)) 16 | else: 17 | counter = 0 18 | print("Wrong answer, the game is reset") 19 | else: 20 | print("The game ends here since you have answered 3 questions correctly") 21 | break 22 | if __name__ == "__main__": 23 | main() 24 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/snow_plot.py: -------------------------------------------------------------------------------- 1 | from matplotlib import pyplot as plt 2 | 3 | snow_yield_dictionary = [ 4 | {"Snow": 5 | [23.1, 32.8, 31.8, 32.0, 30.4, 24.0, 39.5, 24.2, 52.5, 37.9, 30.5, 25.1, 12.4, 35.1, 31.5, 21.1, 27.6] 6 | }, 7 | {"Yield": 8 | [10.5, 16.7, 18.2, 17.0, 16.3, 10.5, 23.1, 12.4, 24.9, 22.8, 14.1, 12.9, 8.8, 17.4, 14.9, 10.5, 16.1] 9 | } 10 | ] 11 | 12 | def plot_the_curve(): 13 | snow_dictionary = snow_yield_dictionary[0] 14 | yield_dictionary = snow_yield_dictionary[1] 15 | 16 | snow_list = snow_dictionary["Snow"] 17 | yield_list = yield_dictionary["Yield"] 18 | 19 | plt.title("Plot of Snow vs Yield"); plt.xlabel("Snow"); plt.ylabel("Yield") 20 | plt.scatter(snow_list, yield_list, c='blue', marker='H') 21 | plt.show() 22 | plt.savefig('plot_of_snow_vs_yield.png') 23 | 24 | def main(): 25 | plot_the_curve() 26 | 27 | if __name__ == "__main__": 28 | main() 29 | 30 | 31 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2021 Leo Nugraha 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /2021_04_30_Dependencies/mars.py: -------------------------------------------------------------------------------- 1 | """ 2 | April 28, 2021 3 | By Leo Nugraha 4 | This program demonstrates how a simple function is written in Python 5 | The function handles an input and generates an output 6 | """ 7 | import math 8 | 9 | def weight_in_mars(earth_weight): 10 | # Assume the earth_weight is stored as a decimal, but not integer 11 | MARS_GRAVITY = 0.378 12 | # The following checks if the input is correct 13 | # What if the input is non-number 14 | if (type(earth_weight) != float): 15 | print("ERROR: Weight data type in not a number") 16 | return None 17 | # What if the input is negative? 18 | if (earth_weight < 0.0): 19 | print("ERROR: Weight must be positive number") 20 | return None 21 | # Proceed to calculate the result 22 | mars_weight = MARS_GRAVITY * earth_weight 23 | # Return your result 24 | return mars_weight 25 | 26 | if __name__ == "__main__": 27 | # Case 1: Everything is fine 28 | test_01 = weight_in_mars(100.00) 29 | print(test_01) 30 | # Case 2: Negative weight 31 | test_02 = weight_in_mars(-100.0) 32 | # Case 3: String input 33 | test_03 = weight_in_mars("100") 34 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/test_factorial.py: -------------------------------------------------------------------------------- 1 | # python3 -m unittest test_factorial.py 2 | 3 | import unittest 4 | from factorial import factorial_iteration 5 | from factorial import factorial_dynamic_programming 6 | 7 | class TestFactorial(unittest.TestCase): 8 | def test_factorial_iteration(self): 9 | self.assertEqual(factorial_iteration(1), 1) 10 | self.assertEqual(factorial_iteration(0), 1) 11 | self.assertEqual(factorial_iteration(5), 120) 12 | 13 | self.assertEqual(factorial_dynamic_programming(1), 1) 14 | self.assertEqual(factorial_dynamic_programming(0), 1) 15 | self.assertEqual(factorial_dynamic_programming(4), 24) 16 | 17 | def test_negative(self): 18 | self.assertRaises(ValueError, factorial_iteration, -1) 19 | self.assertRaises(ValueError, factorial_dynamic_programming, -5) 20 | 21 | def test_nonnumber(self): 22 | self.assertRaises(TypeError, factorial_iteration, True) 23 | self.assertRaises(TypeError, factorial_iteration, "codeinplace") 24 | 25 | self.assertRaises(TypeError, factorial_dynamic_programming, True) 26 | self.assertRaises(TypeError, factorial_dynamic_programming, "codeinplace") 27 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/planet_conditional.py: -------------------------------------------------------------------------------- 1 | import math 2 | 3 | def main(): 4 | MERCURY_GRAVITY = (37.6 / 100) 5 | VENUS_GRAVITY = (88.9 / 100) 6 | MARS_GRAVITY = (37.8 / 100) 7 | JUPITER_GRAVITY = (236 / 100) 8 | SATURN_GRAVITY = (108.1 / 100) 9 | URANUS_GRAVITY = (81.5 / 100) 10 | NEPTUNE_GRAVITY = (114 / 100) 11 | 12 | earthWeight = float(input("Enter the object weight: ")) 13 | planetName = input("Enter a planet name: ") 14 | 15 | match planetName: 16 | case "Mercury": 17 | planetWeight = float(earthWeight) * MERCURY_GRAVITY 18 | 19 | case "Venus": 20 | planetWeight = float(earthWeight) * VENUS_GRAVITY 21 | 22 | case "Mars": 23 | planetWeight = float(earthWeight) * MARS_GRAVITY 24 | 25 | case "Jupiter": 26 | planetWeight = float(earthWeight) * JUPITER_GRAVITY 27 | 28 | case "Saturn": 29 | planetWeight = float(earthWeight) * SATURN_GRAVITY 30 | 31 | case "Uranus": 32 | planetWeight = float(earthWeight) * URANUS_GRAVITY 33 | 34 | case "Neptune": 35 | planetWeight = float(earthWeight) * NEPTUNE_GRAVITY 36 | 37 | case "Earth": 38 | planetWeight = float(earthWeight) 39 | 40 | case other: 41 | planetWeight = -1.0 # Why put a negative value here? 42 | 43 | print("The name of the planet: " + planetName + " with weight: " + str(planetWeight)) 44 | 45 | if __name__ == '__main__': 46 | main() -------------------------------------------------------------------------------- /2021_04_30_Dependencies/main.py: -------------------------------------------------------------------------------- 1 | """ 2 | April 27, 2021 3 | This program provides an example on how to utilize Python built-in library 4 | This program aims to take a square root of an integer and return the result 5 | Notice that I designed two functions that accomplish the exact same purpose: 6 | version_01: using import math (access all functions inside math) 7 | version_02: using from math import sqrt (only access sqrt function) 8 | """ 9 | 10 | def square_root_version_01(num): 11 | import math 12 | if num < 0: 13 | # This is an exception handler in a simple way 14 | print("ERROR: This function only accepts postive integer") 15 | return None 16 | elif type(num) is not int: 17 | print("ERROR: The input number is not an integer") 18 | return None 19 | return math.sqrt(num) # Check this part! 20 | 21 | def square_root_version_02(num): 22 | from math import sqrt 23 | if num < 0: 24 | # This is an exception handler in a simple way 25 | print("ERROR: This function only accepts postive integer") 26 | return None 27 | elif type(num) is not int: 28 | print("ERROR: The input number is not an integer") 29 | return None 30 | return sqrt(num) # Check this part 31 | 32 | 33 | if __name__ == "__main__": 34 | check_01 = square_root_version_02(25) 35 | print(check_01) 36 | 37 | # This case causes an error 38 | check_02 = square_root_version_01(-36) 39 | 40 | # This case causes another error since we need an integer 41 | check_03 = square_root_version_01(25.00) 42 | -------------------------------------------------------------------------------- /.github/workflows/main.yml: -------------------------------------------------------------------------------- 1 | # This is a basic workflow to help you get started with Actions 2 | 3 | name: Python Package Demo 4 | 5 | # Controls when the action will run. 6 | on: [push] 7 | 8 | # A workflow run is made up of one or more jobs that can run sequentially or in parallel 9 | jobs: 10 | # This workflow contains a single job called "build" 11 | build: 12 | # The type of runner that the job will run on 13 | runs-on: ${{ matrix.os }} 14 | 15 | strategy: 16 | matrix: 17 | python-version: [3.7, 3.8, 3.9] 18 | os: [ubuntu-latest, macos-latest] 19 | # Steps represent a sequence of tasks that will be executed as part of the job 20 | steps: 21 | - uses: actions/checkout@v2 22 | - name: Set up Python ${{ matrix.python-version }} 23 | uses: actions/setup-python@v2 24 | with: 25 | python-version: ${{ matrix.python-version }} 26 | architeture: 'x86' 27 | - name: Display all Python versions 28 | run: python -c "import sys; print(sys.version)" 29 | 30 | - name: Install all dependencies 31 | run: | 32 | python -m pip install --upgrade pip 33 | pip install flake8 pytest numpy 34 | if [ -f requirements.txt ]; then pip install -r requirements.txt; fi 35 | 36 | - name: Lint with flake8 37 | run: | 38 | # stop the build if there are Python syntax errors or undefined names 39 | flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics 40 | # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide 41 | flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics 42 | 43 | - name: Test with pytest 44 | run: | 45 | python -m pytest test.py 46 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/factorial.py: -------------------------------------------------------------------------------- 1 | # Use the command below to perform doctest 2 | # python3 -m doctest factorial.py -v 3 | 4 | def factorial_iteration(n): 5 | """ 6 | >>> factorial_iteration(3) 7 | 6 8 | >>> factorial_iteration(0) 9 | 1 10 | >>> factorial_iteration(1) 11 | 1 12 | """ 13 | if type(n) is str: 14 | raise TypeError("Cannot have string factorial") 15 | 16 | if type(n) not in [int]: 17 | raise TypeError("Cannot have non-integer factorial") 18 | 19 | if n < 0: 20 | raise ValueError("Cannot have negative factorial") 21 | 22 | result = 1; 23 | for i in range(n, 1, -1): 24 | result = i*result 25 | 26 | return result 27 | 28 | def factorial_recursion(n): 29 | # TODO: Can you add input checkers here? 30 | # TODO: Can you add a simple unit test here 31 | if (n==0 or n==1): 32 | return 1 33 | 34 | return n * factorial_recursion(n-1) 35 | 36 | def factorial_dynamic_programming(n): 37 | if type(n) is str: 38 | raise TypeError("Cannot have string factorial") 39 | 40 | if type(n) not in [int]: 41 | raise TypeError("Cannot have non-integer factorial") 42 | 43 | if n < 0: 44 | raise ValueError("Cannot have negative factorial") 45 | 46 | factorial_list = [-1] * (n+1) 47 | factorial_list[0] = 1 48 | 49 | for i in range(1, n+1, 1): 50 | factorial_list[i] = factorial_list[i-1] * i 51 | 52 | return factorial_list[n] 53 | 54 | def main(): 55 | user_number = int( input("Enter a number to get its factorial result: ") ) 56 | # x = factorial_iteration(user_number) 57 | x = factorial_dynamic_programming(user_number) 58 | print("The result of ", user_number, "! is ", x) 59 | 60 | if __name__ == "__main__": 61 | main() 62 | -------------------------------------------------------------------------------- /2021_05_14_ImageProcessing/scaling.py: -------------------------------------------------------------------------------- 1 | """ 2 | May 12, 2021 3 | This program demonstrates how to scale an image (magnifying or shrinking) 4 | """ 5 | 6 | import cv2 7 | 8 | def main(): 9 | # 1. Load your image then confirm its dimension 10 | lena = cv2.imread("./images/lena.png") 11 | height = lena.shape[0] 12 | width = lena.shape[1] 13 | print(f"The original image has a height of {height} and a width of {width}") 14 | 15 | # 2. Dilate your image 16 | new_height = 2*height; new_width = 2*width 17 | lena_dilated = cv2.resize(lena, (new_height, new_width)) 18 | print(f"Image size after dilation has a height of {new_height} and a width of {new_width}") 19 | 20 | # 3. Shrink your image; unlike image dilation, 21 | # shrinking image requires a scaling factor that is smaller than 1 22 | # Unfortunately, cv2.resize function does not support any scaling factor 23 | # that is less than 1 24 | # But never fear, there is one approach to anticipate this issue; 25 | # that is using division (// operator) 26 | """ 27 | Approach (a) using full version 28 | half_factor = 0.5 29 | lena_half = cv2.resize(lena, (0, 0), fx=half_factor, fy=half_factor) 30 | half_height = lena_half.shape[0] 31 | half_width = lena_half.shape[1] 32 | """ 33 | 34 | """ 35 | Approach (b) using shortcut 36 | """ 37 | half_height = height // 2; half_width = width // 2 38 | lena_half = cv2.resize(lena, (half_height, half_width)) 39 | print(f"Image size after reduction has a height of {half_height} and a width of {half_width}") 40 | # 4. Check that the dimension is correct then save your image 41 | cv2.imwrite("./results/lena_doubled.png", lena_dilated) 42 | cv2.imwrite("./results/lena_shrunk.png", lena_half) 43 | 44 | if __name__ == "__main__": 45 | main() 46 | -------------------------------------------------------------------------------- /2024_05_31_DataStructures/planet_dictionary.py: -------------------------------------------------------------------------------- 1 | planet_dict_list = [ 2 | {"mercury": 0.376}, 3 | {"venus": 0.889}, 4 | {"earth": 1.0}, 5 | {"mars": 0.378}, 6 | {"jupiter": 2.36}, 7 | {"saturn": 1.081}, 8 | {"uranus": 0.815}, 9 | {"neptune": 1.14} 10 | ] 11 | 12 | planet_dict = { 13 | "mercury": 0.376, 14 | "venus": 0.889, 15 | "earth": 1.0, 16 | "mars": 0.378, 17 | "jupiter": 2.36, 18 | "saturn": 1.081, 19 | "uranus": 0.815, 20 | "neptune": 1.14 21 | } 22 | 23 | def calculate_weight_alternative(target_planet, earth_weight): 24 | planet_name = target_planet.lower() 25 | planet_constant = -1.0 26 | 27 | if planet_dict[ planet_name ] is not None: 28 | planet_constant = planet_dict[planet_name] 29 | 30 | planet_weight = planet_constant * earth_weight 31 | 32 | return planet_weight 33 | 34 | def calculate_weight(target_planet, earth_weight): 35 | # TODO: Check the earth weight, make sure >= 0 and numbers only 36 | # TODO: Check that the target planet name is listed in the dictionary, otherwise return an error 37 | 38 | planet_name = target_planet.lower() 39 | planet_constant = -1.0 40 | for i in range( len(planet_dict_list) ): 41 | for name, gravity in planet_dict_list[i].items(): 42 | if (planet_name == name): 43 | planet_constant = gravity 44 | planet_weight = planet_constant * earth_weight 45 | 46 | return planet_weight 47 | 48 | def main(): 49 | earth_weight = float(input("Enter the object weight: ")) 50 | planet_name = input("Enter a planet name: ") 51 | 52 | # planet_weight = calculate_weight(planet_name, earth_weight) 53 | 54 | planet_weight = calculate_weight_alternative(planet_name, earth_weight) 55 | print("The name of the planet: " + planet_name + " with weight: " + str(planet_weight)) 56 | 57 | if __name__ == '__main__': 58 | main() 59 | -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/covid_analysis.py: -------------------------------------------------------------------------------- 1 | # Redirect to the src/ directory to gain access to the previously written file 2 | # import sys 3 | # sys.path.insert(1,'../src') 4 | 5 | import linear 6 | 7 | import numpy as np 8 | import matplotlib.pyplot as plt 9 | 10 | NUMBER_DAYS = 478 11 | dayElapsed = np.zeros(NUMBER_DAYS) 12 | for i in range(NUMBER_DAYS): 13 | dayElapsed[i] = float(i+1) 14 | 15 | def loadTextFile(textFile="./countries/China.txt"): 16 | # Load .txt data using np methods 17 | results = np.loadtxt(textFile, comments='#', delimiter='\t') 18 | infected = np.array( results[:], dtype=float ) 19 | return infected 20 | 21 | 22 | def statisticalAnalysis(dayElapsed, infectedPatient): 23 | statisticsMethod = linear.LINEAR_RSQUARE(dayElapsed, infectedPatient) 24 | m_infct, b_infct = statisticsMethod.slope_intercept() 25 | rSquare = statisticsMethod.rsquared() 26 | # Create the regression line using functional programming method 27 | regressionLine = [m_infct * day + b_infct for day in dayElapsed] 28 | return m_infct, b_infct, rSquare, regressionLine 29 | 30 | 31 | def linearRegressionAnalysis(dayElapsed, infectedPatient): 32 | regressionMethod = linear.LINEAR_RMSE(dayElapsed, infectedPatient) 33 | 34 | EPOCHS = 20000 # Beyond 20k has no meaningful change 35 | LEARNING_RATE = 1.0e-5 # Beyond 1.0e-5 causes arithmetic overflow 36 | m_infct, b_infct = regressionMethod.SGD_coeff(EPOCHS, LEARNING_RATE) 37 | # Create the regression line 38 | regressionLine = m_infct * dayElapsed + b_infct 39 | RMSE = regressionMethod.RMSE(infectedPatient, regressionLine) 40 | return m_infct, b_infct, RMSE, regressionLine 41 | 42 | 43 | def main(): 44 | countCHN = loadTextFile() 45 | 46 | # Linear Regression using statistical analysis 47 | m_01, b_01, r_01, line_01 = statisticalAnalysis(dayElapsed, countCHN) 48 | plt.scatter(dayElapsed, countCHN, color='red') 49 | plt.plot(dayElapsed, line_01, color='blue') 50 | plt.title('Plot of Day vs Infected Patients using Statistical Analysis') 51 | plt.xlabel('Day Elapsed') 52 | plt.ylabel('Newly Infected Patient') 53 | plt.show() 54 | print(f"Statictical analysis results: slope = {m_01}; intercept = {b_01}; R-squared = {r_01}") 55 | 56 | # Linear Regression using machine learning analysis 57 | m_02, b_02, rmse, line_02 = linearRegressionAnalysis(dayElapsed, countCHN) 58 | plt.scatter(dayElapsed, countCHN, color='red') 59 | plt.plot(dayElapsed, line_02, color='blue') 60 | plt.title('Plot of Day vs Infected Patients using Machine Learning Analysis') 61 | plt.xlabel('Day Elapsed') 62 | plt.ylabel('Newly Infected Patient') 63 | plt.show() 64 | print(f"Machine learning results: slope = {m_02}; intercept = {b_02}") 65 | 66 | if __name__ == "__main__": 67 | main() 68 | -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Samoa.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 0 18 | 0 19 | 0 20 | 0 21 | 0 22 | 0 23 | 0 24 | 0 25 | 0 26 | 0 27 | 0 28 | 0 29 | 0 30 | 0 31 | 0 32 | 0 33 | 0 34 | 0 35 | 0 36 | 0 37 | 0 38 | 0 39 | 0 40 | 0 41 | 0 42 | 0 43 | 0 44 | 0 45 | 0 46 | 0 47 | 0 48 | 0 49 | 0 50 | 0 51 | 0 52 | 0 53 | 0 54 | 0 55 | 0 56 | 0 57 | 0 58 | 0 59 | 0 60 | 0 61 | 0 62 | 0 63 | 0 64 | 0 65 | 0 66 | 0 67 | 0 68 | 0 69 | 0 70 | 0 71 | 0 72 | 0 73 | 0 74 | 0 75 | 0 76 | 0 77 | 0 78 | 0 79 | 0 80 | 0 81 | 0 82 | 0 83 | 0 84 | 0 85 | 0 86 | 0 87 | 0 88 | 0 89 | 0 90 | 0 91 | 0 92 | 0 93 | 0 94 | 0 95 | 0 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| 3 472 | 3 473 | 3 474 | 3 475 | 3 476 | 3 477 | 3 478 | 3 -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Vanuatu.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 0 18 | 0 19 | 0 20 | 0 21 | 0 22 | 0 23 | 0 24 | 0 25 | 0 26 | 0 27 | 0 28 | 0 29 | 0 30 | 0 31 | 0 32 | 0 33 | 0 34 | 0 35 | 0 36 | 0 37 | 0 38 | 0 39 | 0 40 | 0 41 | 0 42 | 0 43 | 0 44 | 0 45 | 0 46 | 0 47 | 0 48 | 0 49 | 0 50 | 0 51 | 0 52 | 0 53 | 0 54 | 0 55 | 0 56 | 0 57 | 0 58 | 0 59 | 0 60 | 0 61 | 0 62 | 0 63 | 0 64 | 0 65 | 0 66 | 0 67 | 0 68 | 0 69 | 0 70 | 0 71 | 0 72 | 0 73 | 0 74 | 0 75 | 0 76 | 0 77 | 0 78 | 0 79 | 0 80 | 0 81 | 0 82 | 0 83 | 0 84 | 0 85 | 0 86 | 0 87 | 0 88 | 0 89 | 0 90 | 0 91 | 0 92 | 0 93 | 0 94 | 0 95 | 0 96 | 0 97 | 0 98 | 0 99 | 0 100 | 0 101 | 0 102 | 0 103 | 0 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-------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Micronesia.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 0 18 | 0 19 | 0 20 | 0 21 | 0 22 | 0 23 | 0 24 | 0 25 | 0 26 | 0 27 | 0 28 | 0 29 | 0 30 | 0 31 | 0 32 | 0 33 | 0 34 | 0 35 | 0 36 | 0 37 | 0 38 | 0 39 | 0 40 | 0 41 | 0 42 | 0 43 | 0 44 | 0 45 | 0 46 | 0 47 | 0 48 | 0 49 | 0 50 | 0 51 | 0 52 | 0 53 | 0 54 | 0 55 | 0 56 | 0 57 | 0 58 | 0 59 | 0 60 | 0 61 | 0 62 | 0 63 | 0 64 | 0 65 | 0 66 | 0 67 | 0 68 | 0 69 | 0 70 | 0 71 | 0 72 | 0 73 | 0 74 | 0 75 | 0 76 | 0 77 | 0 78 | 0 79 | 0 80 | 0 81 | 0 82 | 0 83 | 0 84 | 0 85 | 0 86 | 0 87 | 0 88 | 0 89 | 0 90 | 0 91 | 0 92 | 0 93 | 0 94 | 0 95 | 0 96 | 0 97 | 0 98 | 0 99 | 0 100 | 0 101 | 0 102 | 0 103 | 0 104 | 0 105 | 0 106 | 0 107 | 0 108 | 0 109 | 0 110 | 0 111 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463 | 1207 464 | 1208 465 | 1209 466 | 1211 467 | 1211 468 | 1211 469 | 1214 470 | 1216 471 | 1216 472 | 1226 473 | 1240 474 | 1246 475 | 1256 476 | 1257 477 | 1266 478 | 1274 -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Cambodia.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 1 7 | 1 8 | 1 9 | 1 10 | 1 11 | 1 12 | 1 13 | 1 14 | 1 15 | 1 16 | 1 17 | 1 18 | 1 19 | 1 20 | 1 21 | 1 22 | 1 23 | 1 24 | 1 25 | 1 26 | 1 27 | 1 28 | 1 29 | 1 30 | 1 31 | 1 32 | 1 33 | 1 34 | 1 35 | 1 36 | 1 37 | 1 38 | 1 39 | 1 40 | 1 41 | 1 42 | 1 43 | 1 44 | 1 45 | 1 46 | 1 47 | 2 48 | 2 49 | 2 50 | 3 51 | 3 52 | 5 53 | 7 54 | 7 55 | 7 56 | 33 57 | 35 58 | 37 59 | 51 60 | 53 61 | 84 62 | 87 63 | 91 64 | 96 65 | 96 66 | 99 67 | 99 68 | 103 69 | 107 70 | 109 71 | 109 72 | 110 73 | 114 74 | 114 75 | 114 76 | 114 77 | 115 78 | 117 79 | 119 80 | 119 81 | 120 82 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284 | 291 285 | 292 286 | 292 287 | 292 288 | 292 289 | 292 290 | 294 291 | 295 292 | 297 293 | 300 294 | 300 295 | 301 296 | 301 297 | 302 298 | 302 299 | 302 300 | 303 301 | 304 302 | 304 303 | 304 304 | 305 305 | 306 306 | 306 307 | 306 308 | 307 309 | 307 310 | 307 311 | 308 312 | 315 313 | 323 314 | 326 315 | 329 316 | 331 317 | 335 318 | 345 319 | 346 320 | 348 321 | 350 322 | 354 323 | 356 324 | 357 325 | 357 326 | 359 327 | 359 328 | 362 329 | 362 330 | 362 331 | 362 332 | 362 333 | 362 334 | 363 335 | 363 336 | 363 337 | 363 338 | 363 339 | 363 340 | 364 341 | 364 342 | 364 343 | 364 344 | 366 345 | 378 346 | 379 347 | 381 348 | 382 349 | 382 350 | 383 351 | 385 352 | 386 353 | 387 354 | 391 355 | 391 356 | 392 357 | 398 358 | 411 359 | 426 360 | 436 361 | 439 362 | 439 363 | 441 364 | 448 365 | 453 366 | 456 367 | 456 368 | 458 369 | 458 370 | 460 371 | 460 372 | 460 373 | 463 374 | 463 375 | 465 376 | 466 377 | 466 378 | 466 379 | 467 380 | 470 381 | 472 382 | 474 383 | 474 384 | 476 385 | 476 386 | 478 387 | 479 388 | 479 389 | 479 390 | 479 391 | 479 392 | 479 393 | 483 394 | 484 395 | 484 396 | 533 397 | 568 398 | 593 399 | 633 400 | 697 401 | 741 402 | 767 403 | 805 404 | 820 405 | 844 406 | 878 407 | 909 408 | 932 409 | 953 410 | 987 411 | 1011 412 | 1011 413 | 1124 414 | 1163 415 | 1225 416 | 1264 417 | 1305 418 | 1325 419 | 1325 420 | 1505 421 | 1541 422 | 1578 423 | 1578 424 | 1578 425 | 1753 426 | 1788 427 | 1817 428 | 1872 429 | 1872 430 | 1968 431 | 2147 432 | 2233 433 | 2378 434 | 2440 435 | 2440 436 | 2477 437 | 2546 438 | 2689 439 | 2689 440 | 2752 441 | 2915 442 | 2915 443 | 3028 444 | 3604 445 | 4081 446 | 4515 447 | 4515 448 | 4696 449 | 4874 450 | 5218 451 | 5480 452 | 5771 453 | 6389 454 | 7013 455 | 7444 456 | 7747 457 | 8193 458 | 8848 459 | 9359 460 | 9975 461 | 10555 462 | 11063 463 | 11761 464 | 12641 465 | 13402 466 | 13790 467 | 14520 468 | 15361 469 | 16299 470 | 16971 471 | 17621 472 | 18179 473 | 18717 474 | 19237 475 | 19743 476 | 20223 477 | 20695 478 | 21141 -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Sao Tome and Principe.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 0 18 | 0 19 | 0 20 | 0 21 | 0 22 | 0 23 | 0 24 | 0 25 | 0 26 | 0 27 | 0 28 | 0 29 | 0 30 | 0 31 | 0 32 | 0 33 | 0 34 | 0 35 | 0 36 | 0 37 | 0 38 | 0 39 | 0 40 | 0 41 | 0 42 | 0 43 | 0 44 | 0 45 | 0 46 | 0 47 | 0 48 | 0 49 | 0 50 | 0 51 | 0 52 | 0 53 | 0 54 | 0 55 | 0 56 | 0 57 | 0 58 | 0 59 | 0 60 | 0 61 | 0 62 | 0 63 | 0 64 | 0 65 | 0 66 | 0 67 | 0 68 | 0 69 | 0 70 | 0 71 | 0 72 | 0 73 | 0 74 | 0 75 | 0 76 | 4 77 | 4 78 | 4 79 | 4 80 | 4 81 | 4 82 | 4 83 | 4 84 | 4 85 | 4 86 | 4 87 | 4 88 | 4 89 | 4 90 | 4 91 | 4 92 | 4 93 | 4 94 | 4 95 | 4 96 | 4 97 | 4 98 | 8 99 | 8 100 | 14 101 | 16 102 | 16 103 | 16 104 | 23 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| 1610 398 | 1628 399 | 1655 400 | 1672 401 | 1719 402 | 1745 403 | 1786 404 | 1786 405 | 1828 406 | 1840 407 | 1881 408 | 1898 409 | 1923 410 | 1944 411 | 1950 412 | 1961 413 | 1977 414 | 2010 415 | 2035 416 | 2057 417 | 2078 418 | 2078 419 | 2084 420 | 2085 421 | 2107 422 | 2114 423 | 2123 424 | 2142 425 | 2145 426 | 2157 427 | 2159 428 | 2174 429 | 2177 430 | 2196 431 | 2210 432 | 2212 433 | 2215 434 | 2221 435 | 2223 436 | 2232 437 | 2236 438 | 2240 439 | 2240 440 | 2244 441 | 2248 442 | 2255 443 | 2255 444 | 2261 445 | 2263 446 | 2266 447 | 2267 448 | 2268 449 | 2269 450 | 2271 451 | 2272 452 | 2275 453 | 2275 454 | 2275 455 | 2283 456 | 2288 457 | 2292 458 | 2292 459 | 2297 460 | 2298 461 | 2299 462 | 2299 463 | 2301 464 | 2301 465 | 2302 466 | 2302 467 | 2310 468 | 2310 469 | 2311 470 | 2314 471 | 2317 472 | 2317 473 | 2318 474 | 2318 475 | 2318 476 | 2320 477 | 2320 478 | 2320 -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Diamond Princess.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 61 18 | 61 19 | 64 20 | 135 21 | 135 22 | 175 23 | 175 24 | 218 25 | 285 26 | 355 27 | 454 28 | 542 29 | 621 30 | 634 31 | 634 32 | 634 33 | 691 34 | 691 35 | 691 36 | 705 37 | 705 38 | 705 39 | 705 40 | 705 41 | 705 42 | 706 43 | 706 44 | 706 45 | 706 46 | 706 47 | 706 48 | 706 49 | 706 50 | 706 51 | 706 52 | 706 53 | 706 54 | 706 55 | 706 56 | 706 57 | 712 58 | 712 59 | 712 60 | 712 61 | 712 62 | 712 63 | 712 64 | 712 65 | 712 66 | 712 67 | 712 68 | 712 69 | 712 70 | 712 71 | 712 72 | 712 73 | 712 74 | 712 75 | 712 76 | 712 77 | 712 78 | 712 79 | 712 80 | 712 81 | 712 82 | 712 83 | 712 84 | 712 85 | 712 86 | 712 87 | 712 88 | 712 89 | 712 90 | 712 91 | 712 92 | 712 93 | 712 94 | 712 95 | 712 96 | 712 97 | 712 98 | 712 99 | 712 100 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| 7589 433 | 8070 434 | 8447 435 | 8841 436 | 8841 437 | 9598 438 | 9598 439 | 10820 440 | 11651 441 | 11651 442 | 12226 443 | 13494 444 | 14183 445 | 14183 446 | 15014 447 | 16603 448 | 17823 449 | 18565 450 | 18565 451 | 19672 452 | 21995 453 | 22884 454 | 24195 455 | 25364 456 | 25364 457 | 26692 458 | 29219 459 | 30483 460 | 31339 461 | 31339 462 | 32437 463 | 33608 464 | 35979 465 | 37285 466 | 37285 467 | 39381 468 | 40396 469 | 41524 470 | 41524 471 | 43201 472 | 44016 473 | 44820 474 | 45459 475 | 45936 476 | 46448 477 | 47033 478 | 47548 -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Lesotho.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 0 18 | 0 19 | 0 20 | 0 21 | 0 22 | 0 23 | 0 24 | 0 25 | 0 26 | 0 27 | 0 28 | 0 29 | 0 30 | 0 31 | 0 32 | 0 33 | 0 34 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439 | 10707 440 | 10707 441 | 10707 442 | 10707 443 | 10707 444 | 10707 445 | 10707 446 | 10707 447 | 10709 448 | 10709 449 | 10709 450 | 10709 451 | 10709 452 | 10709 453 | 10709 454 | 10720 455 | 10720 456 | 10720 457 | 10723 458 | 10723 459 | 10723 460 | 10728 461 | 10728 462 | 10728 463 | 10730 464 | 10731 465 | 10731 466 | 10731 467 | 10733 468 | 10733 469 | 10733 470 | 10749 471 | 10749 472 | 10761 473 | 10761 474 | 10773 475 | 10773 476 | 10773 477 | 10774 478 | 10778 -------------------------------------------------------------------------------- /2021_05_21_DataScience/data_science/countries/Chad.txt: -------------------------------------------------------------------------------- 1 | 0 2 | 0 3 | 0 4 | 0 5 | 0 6 | 0 7 | 0 8 | 0 9 | 0 10 | 0 11 | 0 12 | 0 13 | 0 14 | 0 15 | 0 16 | 0 17 | 0 18 | 0 19 | 0 20 | 0 21 | 0 22 | 0 23 | 0 24 | 0 25 | 0 26 | 0 27 | 0 28 | 0 29 | 0 30 | 0 31 | 0 32 | 0 33 | 0 34 | 0 35 | 0 36 | 0 37 | 0 38 | 0 39 | 0 40 | 0 41 | 0 42 | 0 43 | 0 44 | 0 45 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