new_orleans_hurricane_items.py

import pandas as pd
import streamlit as st
from faker import Faker
import random

# Set up the Faker object
fake = Faker()

# Create a list of items with emojis
items = ['💧 Bottled Water', '🥫 Canned Food', '🔦 Flashlights', '🔋 Batteries', '🩹 First Aid Kit',
         '🔪 Utility Knife', '📻 Portable Radio', '🛠️ Tool Kit', '🧭 Compass', '🧯 Fire Extinguisher',
         '👖 Clothing', '🛏️ Sleeping Bag', '🚰 Water Purifier', '🧼 Soap', '🚽 Toilet Paper',
         '🧹 Broom', '🚪 Door Lock', '🔑 Keys', '🔨 Hammer', '🔩 Nails',
         '🧰 Power Drill', '🧹 Dustpan', '🚧 Road Cones', '🚫 Danger Tape', '🚑 First Aid Kit',
         '🧯 Fire Blanket', '🗺️ Maps', '🔮 Flashlight', '📱 Solar Charger', '🔆 Batteries',
         '🔌 Generator', '🔍 Binoculars', '🌬️ Fan', '🎒 Backpack', '🧹 Sweeper',
         '🧺 Laundry Bag', '🥾 Hiking Boots', '👕 T-Shirts', '👖 Jeans', '👟 Sneakers',
         '🧢 Hat', '🕶️ Sunglasses', '🧤 Gloves', '🧣 Scarf', '👩‍🦱 Hair Brush']

# Create an empty dictionary to store the data
data = {'Item': items}

# Estimate the number of purchases for each item
estimates = [random.randint(50, 500) for _ in range(len(items))]

# Add estimated number of purchases for New Orleans
data['New Orleans Hurricane'] = estimates

# Create a DataFrame from the data dictionary
df = pd.DataFrame(data)
df.set_index('Item', inplace=True)

# Create a Streamlit chart
st.line_chart(df)

# Create a Streamlit chart
st.bar_chart(df)

# Calculate the cumulative sum of the item counts for New Orleans
cumulative_data = df.cumsum()

# Create an area chart of the cumulative data
st.area_chart(cumulative_data)