app.py

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df_diamonds = pd.read_csv('diamonds.csv')
df_diamonds = df_diamonds.drop(["Unnamed: 0"], axis=1)

st.title('Diamond selecting APP')

# Users set the price range
min_price = st.number_input('Input minimum price', min_value=int(df_diamonds['price'].min()), max_value=int(df_diamonds['price'].max()), value=int(df_diamonds['price'].min()))
max_price = st.number_input('Input maximum price', min_value=min_price, max_value=int(df_diamonds['price'].max()), value=int(df_diamonds['price'].max()))

# Select the diamonds
cuts = st.multiselect('Select cut', df_diamonds['cut'].unique())
colors = st.multiselect('Select color', df_diamonds['color'].unique())
clarities = st.multiselect('Select clarity', df_diamonds['clarity'].unique())

if st.button('Reset'):
    cuts = []
    colors = []
    clarities = []
    min_price = int(df_diamonds['price'].min())
    max_price = int(df_diamonds['price'].max())

# Filter the diamonds
filtered_diamonds = df_diamonds[(df_diamonds['price'] >= min_price) & (df_diamonds['price'] <= max_price)]

if cuts:
    filtered_diamonds = filtered_diamonds[filtered_diamonds['cut'].isin(cuts)]
if colors:
    filtered_diamonds = filtered_diamonds[filtered_diamonds['color'].isin(colors)]
if clarities:
    filtered_diamonds = filtered_diamonds[filtered_diamonds['clarity'].isin(clarities)]

# Check if there is data to plot
if not filtered_diamonds.empty:
    # Create a scatterplot based on the selected criteria
    fig, ax = plt.subplots()
    sns.scatterplot(x='carat', y='price', data=filtered_diamonds, ax=ax)
    ax.set_title('Prices by Carat')
    st.pyplot(fig)
else:
    st.write("No diamonds fit the selected criteria.")

# Display a scrollable table with the total information based on the selected criteria
st.write("Total Information:")
st.dataframe(filtered_diamonds)