Hi Guys !
I built this dashboard in Google Sheets to track the Facebook rivalry between FreeFire and PUBG! It uses QUERY formulas and Pivot Tables to automatically summarize all their likes, shares, and comments, showing who’s winning the engagement battle.
You’re welcome to explore and interact with my interactive dashboard via the link below:
This project analyzes public debt data from the U.S. Treasury’s official API (fiscaldata.treasury.gov). The script fetches real-time “Debt Subject to Limit” data, processes the JSON response, and loads it into a pandas DataFrame for analysis.
A key analysis step involves grouping the data by debt category (e.g., ‘Public Debt’, ‘Intragovernmental Holdings’) using df.groupby(). The size of these categories is then visualized using .plot(kind='barh') to provide a clear, horizontal bar chart comparing the volume of records for each debt type.
# Public API
# https://github.com/public-apis/public-apis
import requests
## test api
url = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/dts/debt_subject_to_limit"
resp = requests.get(url)
resp.status_code
## Check Status code first
if resp.status_code == 200:
print("ok")
else:
print("Please check the path again")
## Retrieve data from APO( Fetch content)
resp.json()
# import data
import pandas as pd
if resp.status_code == 200:
data = resp.json()
df = pd.DataFrame(data['data'])
else:
print(f"Please check the path again. HTTP status code: {resp.status_code}")
#groups df by category, counts the items in each group, and then plots those counts as a horizontal bar chart.
df.groupby('debt_catg').size().plot(kind='barh'
This project is a Python class that simulates the functionality of an ATM using Object-Oriented Programming (OOP). It serves as a practical blueprint for creating individual bank account “objects” that can interact with each other. Key features include methods for deposit, withdraw, check_balance, and transfer between different account instances.
Click the badge below to run my project in Google Colab:
## object oriented programing
# Create a new class
class ATM:
# init = initialization (Create)
def __init__(self, name, balance, bank):
self.name = name
self.balance = balance
self.bank = bank
# method => Function which is only create for this class
def deposit(self, amt):
self.balance += amt
print(f"Your balance is {self.balance}")
def withdraw(self, amt):
if self.balance >= amt:
self.balance -= amt
print(f"Your balance is {self.balance}")
else:
print("Insufficient Funds")
def check_balance(self):
print(f"Your balance is {self.balance}")
def transfer(self, amt, other):
if self.balance >= amt:
self.balance -= amt
other.balance += amt
print(f"Your balance is {self.balance}")
else:
print("Insufficient Funds")
Click the badge below to run my project in Google Colab:
1def bot_pizza(): 2 print("Hello ! Welcome to PizzaKrub :)") 3 menus = {"Hawaiian $": 5, "Pepperoni $": 4, "Seafood $": 6} 4 my_cart = {"Hawaiian pcs.": 0, "Pepperoni pcs.": 0, "Seafood pcs.": 0} 5 cost = 0 6 while True: 7 print("What can I help you today?") 8 action = input("Please choose one [1] Order [2] See the menu [3] Your cart [4] Checkout :") 9 if action == "1": 10 print("What can I get for you today?") 11 while True: 12 order = input("Please choose one [1] Hawaiian [2] Pepperoni [3] Seafood [4] Back :") 13 if order == "1": 14 my_cart["Hawaiian pcs."] += 1 15 cost += menus["Hawaiian $"] 16 print("Hawaiian pc. added") 17 break 18 elif order == "2": 19 my_cart["Pepperoni pcs."] += 1 20 cost += menus["Pepperoni $"] 21 print("Pepperoni pc. added") 22 break 23 elif order == "3": 24 my_cart["Seafood pcs."] += 1 25 cost += menus["Seafood $"] 26 print("Seafood pc. added") 27 break 28 elif order == "4": 29 break 30 elif action == "2": 31 print(menus) 32 elif action == "3": 33 print(my_cart) 34 print(f"Total amount : {cost} $") 35 while True: 36 cart_edit = input("Do you want to cancel order? (Y/N): ") 37 if cart_edit == "Y": 38 print("Which one would you like to cancel?") 39 remove_order = input("Please choose one [1] Hawaiian [2] Pepperoni [3] Seafood [4] Back :") 40 if remove_order == "1" and my_cart["Hawaiian pcs."] > 0: 41 my_cart["Hawaiian pcs."] -= 1 42 cost -= menus["Hawaiian $"] 43 print("Hawaiian pc. removed") 44 print(f"Current cart: {my_cart}, Total: {cost} $") 45 break 46 elif remove_order == "2" and my_cart["Pepperoni pcs."] > 0: 47 my_cart["Pepperoni pcs."] -= 1 48 cost -= menus["Pepperoni $"] 49 print("Pepperoni pc. removed") 50 print(f"Current cart: {my_cart}, Total: {cost} $") 51 break 52 elif remove_order == "3" and my_cart["Seafood pcs."] > 0: 53 my_cart["Seafood pcs."] -= 1 54 cost -= menus["Seafood $"] 55 print("Seafood pc. removed") 56 print(f"Current cart: {my_cart}, Total: {cost} $") 57 break 58 elif remove_order == "4": 59 break 60 elif(cart_edit) == "N": 61 break 62 elif action == "4": 63 print("----------------------------------------") 64 print("Receipt") 65 print("----------------------------------------") 66 print(f"Hawaiian pcs. : {my_cart['Hawaiian pcs.']}") 67 print(f"Pepperoni pcs. : {my_cart['Pepperoni pcs.']}") 68 print(f"Seafood pcs. : {my_cart['Seafood pcs.']}") 69 print(f"Total amount : {cost}$") 70 print("Thank you for ordering with us :)") 71 print("Enjoy your Pizza and Have a good day!") 72 break 73 else: 74 print("Error! You select the wrong option") 75 76bot_pizza() 77# end of main.py
Let’s Go ! 😀
Explore customer churn patterns using R with ggplot2, dplyr, and scales. Visualize key insights and learn how data-driven strategies can help reduce churn.
