Update folder structure

november/task_101121/Cagulis_101121.txt

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+1. 	Datu bāze ir organizēts strukturētas informācijas jeb datu kopums, kas parasti elektroniski tiek glabāts datorsistēmā
+2. 	pandas ir datu analīzes un manipulācijas bibliotēka
+3. 	matplotlib ir bibliotēka statisku, animētu un interaktīvu vizualizāciju izveidei
+4. 	seaborn padara matplotlib sarežģītākos momentus par vienkāršākiem
+5. 	1048576 rindas,  16384 kolonnas
+6. 	RAM, statistikas datu apjoms, 
+7. 	līniju diagramma - vairāku cieši saistītu datu sēriju attēlošana
+    stabiņu diagramma - datu izmaiņas noteiktā laika periodā vai salīdzinājuma attēlošana
+    riņķa diagramma - vizuālai salīdzināšanai, cik liela datu daļa atbilst katrai datu kategorijai
+    histogramma - datu kopas sadalījuma attēlošanai
+8.  viegli
+9.  no .csv faila nolasīt attiecīgās valsts nosaukumu, vidējo mirstības rādītāju, max un min mirstības rādītājus un attiecīgo pēdējo gadu, kad ir dati. 
+    Izmantojot bibliotēkas pandas, seaborn un holoviews, izveidot pasaules kartes diagrammu.
+
+
+
+Informācijas avoti:
+    https://pypi.org/project/pandas/
+    https://pypi.org/project/matplotlib/
+    https://pypi.org/project/seaborn/
+    https://pypi.org/project/holoviews/
+    https://support.microsoft.com/en-us/office/excel-specifications-and-limits-1672b34d-7043-467e-8e27-269d656771c3
+    https://www.who.int/data/gho/data/indicators/indicator-details/GHO/mortality-rate-for-5-14-year-olds-(probability-of-dying-per-1000-children-aged-5-14-years)

november/task_171121/company_sales_data.csv

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+month_number,facecream,facewash,toothpaste,bathingsoap,shampoo,moisturizer,total_units,total_profit
+1,2500,1500,5200,9200,1200,1500,21100,211000
+2,2630,1200,5100,6100,2100,1200,18330,183300
+3,2140,1340,4550,9550,3550,1340,22470,224700
+4,3400,1130,5870,8870,1870,1130,22270,222700
+5,3600,1740,4560,7760,1560,1740,20960,209600
+6,2760,1555,4890,7490,1890,1555,20140,201400
+7,2980,1120,4780,8980,1780,1120,29550,295500
+8,3700,1400,5860,9960,2860,1400,36140,361400
+9,3540,1780,6100,8100,2100,1780,23400,234000
+10,1990,1890,8300,10300,2300,1890,26670,266700
+11,2340,2100,7300,13300,2400,2100,41280,412800
+12,2900,1760,7400,14400,1800,1760,30020,300200

november/task_171121/task_171121.py

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+# Author - Kristiāns Francis Cagulis
+# Date - 22.11.2021
+
+import pandas as pd
+import matplotlib.pyplot as plt
+
+data = pd.read_csv("company_sales_data.csv")
+
+
+def task_1():
+	plt.figure(figsize=(10, 6))  # (x, y)
+	x = range(len(data["month_number"]))  # gets range of months
+	plt.plot(x, data["total_profit"])  # sets up the plot
+	plt.xticks(x, data["month_number"], fontsize=15)  # sets x value step
+	plt.yticks(fontsize=15)
+	plt.ylim(ymin=100000)  # sets minimal y value
+
+	set_labels("Company profit per month", "Month number", "Total profit")
+
+	plt.show()
+
+
+def task_2():
+	plt.figure(figsize=(10, 6))  # (x, y)
+
+	x = range(len(data["month_number"]))  # gets range of months
+
+	data_list = list(data.columns)[1:-2]  # gets and trims column names
+
+	for column in data_list:
+		plt.plot(x, data[column], lw=4, marker='o', ms=10)  # ms = marker size
+
+	plt.xticks(x, data["month_number"], fontsize=15)  # sets x value step
+	plt.yticks(fontsize=15)
+
+	set_labels("Sales data", "Month number", "Sales units in number")
+
+	new_data_list = list(map(lambda x: x.capitalize() + " Sales Data", data_list))  # capitalizes each word in list
+	plt.legend(new_data_list, loc='upper left', fontsize=15)
+	plt.show()
+
+
+def task_3():
+	plt.figure(figsize=(10, 6))  # (x, y)
+	x = range(len(data["month_number"]))  # gets range of months
+
+	plt.scatter(x, data["toothpaste"], s=75)  # sets up the plot
+	plt.grid(ls='dashed', lw=1.5)  # sets grid line type and width
+	plt.xticks(x, data["month_number"], fontsize=15)  # sets x value step
+	plt.yticks(fontsize=15)
+
+	set_labels("Toothpaste Sales data", "Month number", "Number of units Sold")
+	plt.legend(["Toothpaste Sales data"], loc='upper left', fontsize=15)
+	plt.show()
+
+
+def task_4():
+	items = ["facecream", "facewash"]
+
+	data.plot(x="month_number", y=["facecream", "facewash"], kind='bar', figsize=(10, 6), fontsize=15)
+
+	plt.xticks(rotation=0)  # rotates x lables to 0
+	plt.grid(ls='dashed', lw=1.5)  # sets grid line type and width
+
+	set_labels("Facewash and Facecream Sales data", "Month number", "Sales units in number")
+	new_items_list = list(map(lambda x: x.capitalize() + " Sales Data", items))
+	plt.legend(new_items_list, loc='upper left', fontsize=15)
+	plt.show()
+
+
+def set_labels(title: str, xlabel: str, ylabel: str):
+	plt.title(title, fontsize=15)
+	plt.xlabel(xlabel, fontsize=15)
+	plt.ylabel(ylabel, fontsize=15)
+
+
+def main():
+	task = input(
+	    """Ivēlieties uzdevumu:
+1 - pirmais uzdevums
+2 - otrais uzdevums
+3 - trešais uzdevums
+4 - ceturtais uzdevums
+"""
+	)
+
+	if task == "1":
+		task_1()
+	elif task == "2":
+		task_2()
+	elif task == "3":
+		task_3()
+	elif task == "4":
+		task_4()
+	else:
+		print("Tika ievadīts nepareiz cipars")
+
+
+if __name__ == '__main__':
+	main()

november/task_241121/main.py

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+from audioop import add
+from ctypes import addressof
+from bs4 import BeautifulSoup
+import requests
+
+url = "https://en.wikipedia.org/wiki/Husky"
+all_page = requests.get(url)
+
+# print(all_page)
+
+if all_page.status_code == 200:
+	print(":)")
+	page = BeautifulSoup(all_page.content, 'html.parser')
+	found = page.find(id="Etymology")
+	# print(found)
+	# print(found.constents)
+	# print(found.string)
+	found = page.find_all(class_="mw-headline")
+	# print(found)
+	found = page.find_all("li", class_="interlanguage-link")
+	# print(found)
+	found = page.find_all("a", class_="interlanguage-link-target")
+	# print(found)
+	for i in found:
+		# 	print(i.prettify())
+		if i.attrs["lang"] == "ru":
+			print(f"{i.attrs['lang']} \t {i.attrs['title']} \n {i.attrs['href']}")
+else:
+	print(":(")

november/task_241121/task_061021/kcagulis_061021.py

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+# Author - Kristiāns Francis Cagulis
+# Date - 06.10.2021
+import re
+
+CHAPTERS = 61
+
+
+# creates file with chapters and row numbers
+def read_array(document):
+	with open(document, "r", encoding='utf-8') as book:
+		lines = [line.strip('\n') for line in book]  # removes 'enter' characters
+	with open('array_output.txt', 'w') as output:
+		for i in range(1, CHAPTERS + 1):
+			line = lines.index(f"Chapter {i}") + 1  # finds all chapter indexes/lines
+			output.write(f"Line {line} - Chapter {i}\n")  # writes line in file
+
+
+# creates file with chapter positions
+def read_string(document):
+	with open(document, "r", encoding='utf-8') as book:
+		lines = book.read()
+	with open('str_output.txt', 'w') as output:
+		for i in range(1, CHAPTERS + 1):
+			_, position = re.finditer(rf"\bChapter {i}\b", lines)  # finds all chapter positions
+			output.write(f"Position {position.start()} - Chapter {i}\n")  # writes position in file
+
+
+def read_book(document):
+	read_array(document)
+	read_string(document)
+
+
+def main():
+	try:
+		read_book("book.txt")
+	except:
+		try:
+			read_book("1342-0.txt")
+		except:
+			read_book(input("Ievadiet faila nosaukumu: "))
+
+
+if __name__ == '__main__':
+	main()