Python – Stock Dashboard with Streamlit and YFinance

Imagine that you want to have all the important historical financial information of yahoo finance on your PC. Well, in that case you would probably go there and check it. Anyway, if you are a person, who wants to create a customized dashboard with it, then you can use the streamlit library in python 🙂

In this article, we would show the code from the YouTube video, used for the creation of the Stock Dashboard with Python. Generally speaking, it is this one:

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

# Page title
st.title("Stock Data Dashboard 📈")

# Sidebar inputs
st.sidebar.header("VitoshAcademy LiveCoding")
ticker_symbol = st.sidebar.text_input("Enter Stock Ticker (e.g., AAPL, MSFT)", value="MSFT")
start_date = st.sidebar.date_input("Start Date", value=pd.to_datetime("2020-01-01"))
end_date = st.sidebar.date_input("End Date", value=pd.to_datetime("2024-12-31"))
ma_window = st.sidebar.slider("Moving Average Window", min_value=5, max_value=50, value=20)

# Fetching data
st.write(f"Fetching data for **{ticker_symbol}** from {start_date} to {end_date}...")
data = yf.download(ticker_symbol, start=start_date, end=end_date)

if data.empty:
    st.error("No data found. Please check the ticker symbol or date range.")
    st.stop()

data['MA'] = data['Close'].rolling(window=ma_window).mean()

# Initialize Tabs
tabs = st.tabs(["📋 Raw Data", "📈 Price Chart", "📊 Volume Chart", "📏 Moving Averages", "💰 Dividends & Splits"])

# Tab 1: Raw Data
with tabs[0]:
    st.subheader(f"Raw Data for {ticker_symbol}")
    st.write(data.tail())
    st.download_button("Download Data as CSV", data.to_csv(), file_name=f"{ticker_symbol}_data.csv")

# Tab 2: Closing Price Chart
with tabs[1]:
    if "Close" in data:
        st.subheader("Closing Price Over Time")
        st.line_chart(data['Close'])
    else:
        st.warning("Closing price data is not available for this stock.")

# Tab 3: Volume Chart
with tabs[2]:
    if "Volume" in data:
        st.subheader("Volume Over Time")
        st.bar_chart(data['Volume'])
    else:
        st.warning("Volume data is not available for this stock.")
        
# Tab 4: Moving Averages
with tabs[3]:
    st.subheader(f"Closing Price with {ma_window}-Day Moving Average")
    fig, ax = plt.subplots(figsize=(10, 5))
    ax.plot(data.index, data['Close'], label="Closing Price", color='blue')
    ax.plot(data.index, data['MA'], label=f"{ma_window}-Day Moving Average", color='orange')
    ax.set_title(f"Closing Price with {ma_window}-Day Moving Average")
    ax.set_xlabel("Date")
    ax.set_ylabel("Price")
    ax.legend()
    st.pyplot(fig)

# Tab 5: Dividends & Splits
with tabs[4]:
    st.subheader("Dividends & Splits")
    ticker = yf.Ticker(ticker_symbol)
    dividends = ticker.dividends
    splits = ticker.splits

    st.write("**Dividends:**")
    st.write(dividends if not dividends.empty else "No dividends found during this period.")
    st.write("**Splits:**")
    st.write(splits if not splits.empty else "No splits found during this period.")

The way to call it is this one liner into the terminal – streamlit run stock_dashboard_streamlit.py

The beautiful dashboard looks like that:

The turning this python tool into “live” and some additional interesting features of the yfinance library are presented in the video below:

Enjoy it! 🙂