Simple Data Dashboard

This project is a lightweight, interactive data exploration dashboard built using Streamlit. It allows users to upload a CSV file, preview the data, view basic statistical summaries, apply filters, and generate simple line charts --- all from a web-based interface.

🚀 Features

📂 CSV Upload

• Upload any CSV file directly through the interface.
• Automatically loads and displays the first few rows.

📊 Data Preview

• Displays the first 5 rows of the uploaded dataset.

📈 Data Summary

• Generates a statistical summary using pandas.describe().

🔎 Data Filtering

• Select a column and then a specific value from that column.
• View only the rows matching the selected filter.

📉 Data Plotting

• Choose any column for the X-axis and Y-axis.
• Generates a line chart using the filtered dataset.

🛠️ Technologies Used

• Python
• Streamlit
• Pandas
• Matplotlib

📦 Installation

pip install streamlit pandas matplotlib

▶️ Running the App

streamlit run main.py

📜 Example Code

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

st.title("Simple Data Dashboard")

uploaded_file = st.file_uploader("Choose a CSV file", type="csv")

if uploaded_file is not None:
    df = pd.read_csv(uploaded_file)

    st.subheader("Data Preview")
    st.write(df.head())

    st.subheader("Data Summary")
    st.write(df.describe())

    st.subheader("Filter Data")
    colums = df.columns.tolist()
    selected_column = st.selectbox("Select a column to filter", colums)
    unique_values = df[selected_column].unique()
    selected_value = st.selectbox("Select value", unique_values)

    filtered_df = df[df[selected_column] == selected_value]
    st.write(filtered_df)

    st.subheader("Plot Data")
    x_column = st.selectbox("Select X-axis column", colums)
    y_column = st.selectbox("Select Y-axis column", colums)

    if st.button("Generate Plot"):
        st.line_chart(filtered_df.set_index(x_column)[y_column])
else:
    st.write("Waiting on file upload...")