frame = Tk()

frame.geometry("500x300")

frame.title("HAHAHAHA")

L1 = Label(frame,text="Hello", font=('Arial', 25), bg ="black", fg="white")

L1.place(x=100,y=200)

frame.mainloop()

from datetime import datetime

import time

def update_clock():

now = datetime.now()

current_date = now.strftime("%d / %m / %Y")

current_time = now.strftime("%H:%M:%S")

L1.config(text = current_date)

L2.config(text = current_time)

frame.after(1000,update_clock)

frame = Tk()

frame.title("GUI - 1")

frame.geometry("300x200")

L1 = Label(frame,text = "Date", font = ("Tahoma",20))

L1.pack()

L2 = Label(frame,text = "Time", font = ("Tahoma",20))

L2.pack()

update_clock()

frame.mainloop()

from datetime import datetime

import time

def update_clock():

global cl

now = datetime.now()

current_date = now.strftime("%d / %m / %Y")

current_time = now.strftime("%H:%M:%S")

L1.config(text = current_date)

L2.config(text = current_time)

cl = frame.after(1000,update_clock)

def stop_click():

global cl

frame.after_cancel(cl)

frame = Tk()

frame.title("GUI - 1")

frame.geometry("300x200")

cl = None

L1 = Label(frame,text = "Date", font = ("Tahoma",20))

L1.pack()

L2 = Label(frame,text = "Time", font = ("Tahoma",20))

L2.pack()

B1 = Button(frame, text = "Start" ,command = update_clock)

B1.pack()

B2 = Button(frame, text = "Stop", command = stop_click)

B2.pack()

frame.mainloop()

wb = load_workbook("record.xlsx")

wb.active = wb["Sheet1"]

sheet = wb.active

print("Fully Access to Excel Sheet")

from tkinter import*

frame = Tk()

frame.geometry('300x200')

from datetime import datetime

def on_click():

value_s1 = var.get()

now = datetime.now()

last_row = sheet.max_row+1

point_to_cell_time = sheet.cell(last_row,column=1)

point_to_cell_value = sheet.cell(last_row,column=2)

point_to_cell_time.value = now

point_to_cell_value.value = value_s1

wb.save("record.xlsx")

print("Value was record")

var = DoubleVar()

S1 = Scale(frame, resolution=0.001, variable = var, orient = "horizontal", label="SCALE", from_ = -100, to = 100, length=200, width = 30)

S1.pack()

B1 = Button(frame, text= "OK", command = on_click)

B1.pack()

frame.mainloop()

from tkinter import messagebox

import csv

# Function to save data to CSV file

def save_to_csv(data):

file_exists = False

try:

with open('names.csv', 'r') as file:

file_exists = True

except FileNotFoundError:

pass

with open('names.csv', 'a', newline='') as file:

fieldnames = ['First Name', 'Last Name']

writer = csv.DictWriter(file, fieldnames=fieldnames)

if not file_exists:

writer.writeheader()

writer.writerow(data)

# Function to handle the submit button click

def submit():

first_name = entry_first_name.get()

last_name = entry_last_name.get()

if first_name and last_name:

data = {'First Name': first_name, 'Last Name': last_name}

#save_to_csv(data)

messagebox.showinfo("Success", "Data saved successfully!")

entry_first_name.delete(0, tk.END)

entry_last_name.delete(0, tk.END)

else:

messagebox.showwarning("Input Error", "Please enter both first name and last name")

# Create the main window

root = tk.Tk()

root.title("Name Collector")

# Create and place the widgets

label_first_name = tk.Label(root, text="First Name:")

label_first_name.grid(row=0, column=0, padx=10, pady=5)

entry_first_name = tk.Entry(root)

entry_first_name.grid(row=0, column=1, padx=10, pady=5)

label_last_name = tk.Label(root, text="Last Name:")

label_last_name.grid(row=1, column=0, padx=10, pady=5)

entry_last_name = tk.Entry(root)

entry_last_name.grid(row=1, column=1, padx=10, pady=5)

submit_button = tk.Button(root, text="Submit", command=submit)

submit_button.grid(row=2, columnspan=2, pady=10)

# Run the main event loop

root.mainloop()

i have csv file named "train.csv" that run in google colab.

now i have dataframe with pandas by code

import pandas as pd

df = pd.read_csv("train.csv")

in the df have filed name "Sex" that contain 891 record.

i want you create python with mathplotlib to show bar graph that compare number of male and female from df[sex].

• Generate a dataset of sales data for 12 months using NumPy.

• Load the generated dataset into a Pandas DataFrame.

• Calculate and display basic statistics (mean, median, total) for sales amounts.

• Plot a bar chart of total sales per month using Matplotlib.

• Plot a line chart of cumulative sales over time using Matplotlib.

i have dataset like this,

age sex bmi children smoker region charges 19 female 27.9 0 yes southwest 16884.924 18 male 33.77 1 no southeast 1725.5523 28 male 33 3 no southeast 4449.462 33 male 22.705 0 no northwest 21984.47061 32 male 28.88 0 no northwest 3866.8552 31 female 25.74 0 no southeast 3756.6216

please create python code by using numpy pandas matplotlib sklearn_multiple_linear regression

we will run code on google colab. first, import file name insurance.csv to dataframe. next, split data for train and test. next, fit the multiple linear regression model to predict "charge" next, eveluate the model with mse, and r2 next, plot graph about variable that used in model. and also show relation between variables.

X = df[['age', 'bmi', 'children']] # Independent variables y = df['charges'] # Dependent variable (target)

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

model = LinearRegression() model.fit(X_train, y_train)

after this, please write the python code to create function for model implement. this funtion will: prompt user input number of "age" prompt user input number of "bmi" prompt user input number of "children" then use 3 value from input with model and print the "charges" predict value.