Code Editor for app.py

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

# URL for CSV
url = st.text_input('Enter CSV URL', value='https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv')

# Load the CSV file with caching
def load_data(url):
    data = pd.read_csv(url)
    return data

# Read data and display DataFrame
@st.cache_data
def get_data(url):
    return load_data(url)

data = get_data(url)

st.write('DataFrame:', data)

# Control for number of rows displayed
num_rows = st.slider('Select number of rows to display', 1, min(len(data), 100), 10)
shuffled = st.checkbox('Shuffle DataFrame')

if shuffled:
    data = data.sample(frac=1).reset_index(drop=True)

st.dataframe(data.head(num_rows))

# Visualizing the data
st.write('\n## Data Visualization')

# Select columns for plotting
variables = data.select_dtypes(include=[np.number]).columns.tolist()
col1 = st.selectbox('Select X variable', variables)
col2 = st.selectbox('Select Y variable (optional)', ['None'] + variables)

if col2 != 'None':  # if a second variable is selected
    plt.figure(figsize=(10, 6))
    sns.scatterplot(data=data, x=col1, y=col2)
    plt.title(f'Scatter plot of {col1} vs {col2}')
    st.pyplot()  
else:
    plt.figure(figsize=(10, 6))
    sns.histplot(data=data, x=col1, bins=30, kde=True)
    plt.title(f'Histogram of {col1}')
    st.pyplot()