Upload 2 files

app.py

@@ -0,0 +1,91 @@
+import streamlit as st
+from datetime import date
+import yfinance as yf
+from prophet import Prophet
+from prophet.plot import plot_plotly
+from plotly import graph_objs as go
+
+start_date = "2016-01-01"
+today_date = date.today().strftime("%Y-%m-%d")
+
+st.title("Stock Price Forcasting App")
+
+stocks = ("GS","MS","JPM","C")
+selected_stocks = st.selectbox("Select the stock for prediction",stocks)
+n_years = st.slider("Years of Prediction",1, 4)
+period = n_years * 365
+
+@st.cache
+def load_data(ticker):
+    data = yf.download(ticker,start_date,today_date)
+    data.reset_index(inplace=True)
+    return data
+
+data_load_state = st.text("Loading the data....")
+data = load_data(selected_stocks)
+data_load_state.text("Data is Loaded!!")
+
+st.subheader("Raw Data")
+st.write(data.tail())
+
+def plot_raw_data():
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(x = data['Date'],y=data['Open'], name = 'Open Price'))
+    fig.add_trace(go.Scatter(x=data['Date'], y=data['Close'], name = 'Close Price'))
+    fig.layout.update(title_text = "Time Series Data", xaxis_rangeslider_visible=True)
+    st.plotly_chart(fig)
+
+plot_raw_data()
+
+
+# forecasting
+df_train = data[['Date','Close']]
+df_train = df_train.rename(columns={"Date":"ds", "Close":"y"})
+
+model = Prophet()
+
+
+model.fit(df_train)
+future = model.make_future_dataframe(periods= period)
+forecast = model.predict(future)
+
+st.subheader('Forecast Data')
+st.write(forecast.tail())
+
+st.write("Forecast Data")
+fig_1 = plot_plotly(model, forecast)
+st.plotly_chart(fig_1)
+
+st.write("Forecast Components")
+fig_2 = model.plot_components(forecast)
+st.write(fig_2)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+

requirements.txt

@@ -0,0 +1,4 @@
+streamlit==1.15.1
+prophet==1.1.1
+plotly==5.11.0
+yfinance==0.1.87