app.py

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

def save_plot(fig):
    buf = io.BytesIO()
    fig.savefig(buf, format="png")
    buf.seek(0)
    return buf

def main():
    st.title("Distribution Curve Plotting Dashboard")
    
    uploaded_file = st.file_uploader("Upload an Excel file", type=["xls", "xlsx"])
    
    if uploaded_file is not None:
        df = pd.read_excel(uploaded_file)
        st.write("Preview of Data:")
        st.write(df.head())
        
        numeric_columns = df.select_dtypes(include=[np.number]).columns.tolist()
        
        if numeric_columns:
            selected_column = st.selectbox("Select a column for analysis (as named in the Excel file)", numeric_columns)
            
            if selected_column:
                data = df[selected_column].dropna()
                std_dev = np.std(data, ddof=1)
                
                st.write(f"**Calculated Standard Deviation:** {std_dev:.4f}")
                
                # Distribution Plot
                fig_dist, ax_dist = plt.subplots(figsize=(6, 5))
                sns.histplot(data, kde=True, ax=ax_dist, bins=20, color='blue')
                ax_dist.set_title(f"Distribution Plot of {selected_column}")
                st.pyplot(fig_dist)
                st.download_button("Download Distribution Plot", save_plot(fig_dist), file_name="distribution_plot.png", mime="image/png")
                
                # Standard Deviation Plot
                fig_std, ax_std = plt.subplots(figsize=(6, 5))
                sns.lineplot(x=data.index, y=data, ax=ax_std, label='Data')
                ax_std.axhline(y=np.mean(data), color='r', linestyle='--', label='Mean')
                ax_std.axhline(y=np.mean(data) + std_dev, color='g', linestyle='--', label='+1 Std Dev')
                ax_std.axhline(y=np.mean(data) - std_dev, color='g', linestyle='--', label='-1 Std Dev')
                ax_std.legend()
                ax_std.set_title(f"Standard Deviation Plot of {selected_column}")
                st.pyplot(fig_std)
                st.download_button("Download Standard Deviation Plot", save_plot(fig_std), file_name="std_dev_plot.png", mime="image/png")
        else:
            st.warning("No numeric columns found in the uploaded file.")

if __name__ == "__main__":
    main()