Untitled

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

# Load your CSV data
# df = pd.read_csv("Book1.csv")

# Set a background image (you can change the URL)
page_bg_img = '''
<style>
[data-testid="stAppViewContainer"] {
background-image: url("data:image/jpeg;base64,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# background-position: center center;
background-repeat: no-repeat;
# background-attachment: fixed;
background-size: cover; 
}
[data-testid="stHeader"] {
background: lightblue;
}
</style>
'''
st.markdown(page_bg_img, unsafe_allow_html=True)

st.markdown('''<img src="https://celebaltech.com/assets/img/celebal.webp" width="400" height="100">''', unsafe_allow_html=True)
###################---------------------------------



# # Add a title and subtitle
# st.title("Simple Streamlit UI")
# st.subheader("Explore your data")

# # Display the data frame
# st.write("Data Frame", df)

# # Add some checkboxes to customize the view
# st.sidebar.header("Customize View")
# if st.sidebar.checkbox("Show Dataframe Summary"):
#     st.write("Dataframe Summary", df.describe())

# if st.sidebar.checkbox("Show Plot"):
#     # Create a simple bar plot
#     st.write("Bar Plot")
#     plt.bar(df["Category"], df["Value"])
#     plt.xlabel("Category")
#     plt.ylabel("Value")
#     st.pyplot()

# Add any additional elements or visualizations here