app.py

import streamlit as st
import plotly.express as px

st.title("Hello World!")

st.write("This is my first Streamlit app on Hugging Face Space")


name = st.text_input("Enter your name : ")
age = st.slider("Select your age : ", 0, 100, 25)

if st.button("Submit"):
    st.write(f" Hello {name}, your are {age} years old!")



# Example 1 : Text Input and Button
st.title("Interactive App : User Input")

# Text Input Feild
name = st.text_input("Enter your name:")

# Create Button
if st.button("Greet"):
    st.write(f"Hello, {name}! Welcome to your first interactive Streamlit app.")



# Example 2 : Dropdown Selection
st.title("Dropdown Selection Example")

# Dropdown menu
options = ("Python", "JavaScript", "Java", "C++")

chioce = st.selectbox("Choose a programming language :",options)
st.write(f"You selected: {chioce}!")


import streamlit as st

st.title("Multi-Select Example")

# Multi-select widget
hobbies = st.multiselect("Select your hobbies:", ["Reading", "Traveling", "Cooking", "Gaming"])
st.write(f"Your selected hobbies are: {', '.join(hobbies)}")


# CSV File Upload and Display
# import streamlit as st
# import pandas as pd
# # import matplotlib.pyplot as plt
# import plotly.express as px

# st.title("CSV File Upload and Display")

# # File uploader
# uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])

# if uploaded_file:
#     # Read the uploaded file
#     data = pd.read_csv(uploaded_file)

#     # Display the data preview
#     st.write("Data Preview:")
#     st.dataframe(data)

#     # Display data statistics
# if uploaded_file:
#     st.write("Data Statistics:")
#     st.write(data.describe())

#     # Display a line and Bar chart
# if uploaded_file:
#     st.write("Line Chart Example:")
#     st.line_chart(data)
    
#     st.write("Bar Chart Example:")
#     st.bar_chart(data)

    # st.write("Custom Matplotlib Chart")

    # fig, ax = plt.subplots()
    # ax.plot(data.iloc[:, 0], data.iloc[:, 1])
    # ax.set_title("Custom Line Plot")
    # st.pyplot(fig)

      # User selects x and y axes
    # x_axis = st.selectbox("Choose X-axis:", data.columns)
    # y_axis = st.selectbox("Choose Y-axis:", data.columns)

    # # Generate scatter plot
    # fig = px.scatter(data, x=x_axis, y=y_axis, title="Scatter Plot")
    # st.plotly_chart(fig)



# Plotly Example
# import streamlit as st
# import pandas as pd
# import plotly.express as px

# st.title("CSV File Upload and Display")

# # File uploader
# uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])

# if uploaded_file:
#     data = pd.read_csv(uploaded_file)
#     st.write("Just loaded Data:")
#     st.dataframe(data)

#     # User selects x and y axes
#     x_axis = st.selectbox("Choose X-axis:", data.columns)
#     y_axis = st.selectbox("Choose Y-axis:", data.columns)

#     # Generate scatter plot
#     fig = px.scatter(data, x=x_axis, y=y_axis, title="Scatter Plot")
#     st.plotly_chart(fig)



import streamlit as st
import pandas as pd
import plotly.express as px

st.title("Dashboard Example")

# File uploader
uploaded_file = st.file_uploader("Upload CSV for Dashboard", type=["csv"])

if uploaded_file:
    data = pd.read_csv(uploaded_file)
    st.sidebar.title("Dashboard Controls")

    # Sidebar controls
    column = st.sidebar.selectbox("Select column to analyze:", data.columns)
    chart_type = st.sidebar.selectbox("Choose chart type:", ["Bar", "Line", "Scatter"])

    # Display summary
    st.write("Summary Statistics:")
    st.write(data.describe())

    # Generate chart
    if chart_type == "Bar":
        st.bar_chart(data[column])
    elif chart_type == "Line":
        st.line_chart(data[column])
    else:
        fig = px.scatter(data, x=data.index, y=column)
        st.plotly_chart(fig)