Update app

app.py

@@ -1,4 +1,8 @@
 import streamlit as st
+from streamlit_lottie import st_lottie_spinner
+import json
+import time
+
 import pandas as pd
 from datetime import datetime
 
@@ -18,6 +22,16 @@ st.set_page_config(
       initial_sidebar_state="expanded",
 )
 
+@st.cache_data
+def load_lottieurl(url: str):
+    r = requests.get(url)
+    if r.status_code != 200:
+        return None
+    return r.json()
+
+lottie_progress_url = "https://lottie.host/12c7a018-d6c9-4595-abab-2992e4117d95/TnBbTO5WR5.json"
+lottie_progress = load_lottieurl(lottie_progress_url)
+
 # Preprocessing
 @st.cache_data
 def merge(B, C, A):
@@ -261,10 +275,13 @@ with st.sidebar:
         st.write("Your uploaded data:")
         st.write(df)
 
-        df = drop(df)
-        df = date_format(df)
-        merge_sort(df)
-        series = group_to_three(df)
+        with st_lottie_spinner(lottie_progress, loop=True, key="progress"):
+          time.sleep(5)
+          df = drop(df)
+          df = date_format(df)
+          merge_sort(df)
+          series = group_to_three(df)
+
         st.session_state.uploaded = True
 
     with open('sample.csv', 'rb') as f:
@@ -290,13 +307,9 @@ if (st.session_state.uploaded):
     train = train_test(df)
     training_y, test_y, test_y_series, training_X, test_X, future_X = train
     train_test_model = test_fitting(df, training_X, training_y)
-
     n_periods = round(len(df) * 0.2)
-
     future_n_periods = forecast_period + n_periods
-
     fitted, confint = train_test_model.predict(X=test_X, n_periods=n_periods, return_conf_int=True)
-
     index_of_fc = test_y_series.index
 
     # make series for plotting purpose
@@ -305,6 +318,20 @@ if (st.session_state.uploaded):
     lower_series = pd.Series(confint[:, 0], index=index_of_fc)
     upper_series = pd.Series(confint[:, 1], index=index_of_fc)
 
+    #TODO Plot Test and Training
+    col1, col2 = st.columns(2)
+    with col1:
+       col1.header("Sales Forecast")
+       col1.line_chart(df['Sales'], x="Date", y="Actual Sales" color="#0000EE")
+    # plt.figure(figsize=(18,10))
+    # plt.plot(df['Sales'], color='b', label = 'Actual Sales')
+    # plt.plot(test_y, color='b')
+    # plt.plot(fitted_series, color='r', label = 'Predicted Sales')
+    # plt.title("SARIMAX - Forecast of Auto Business Retail Sales VS Actual Sales")
+    # plt.legend(loc='upper left', fontsize=8)
+    # plt.show()
+    # plt.savefig('Auto Retail Future Sales Forecast 80-20.png')
+
     #Future predictions
     frequency = '3D'
     future_fitted, confint = train_test_model.predict(X=df.iloc[-future_n_periods:,1:], n_periods=future_n_periods, return_conf_int=True, freq=frequency)
@@ -316,11 +343,23 @@ if (st.session_state.uploaded):
     future_lower_series = pd.Series(confint[:, 0], index=future_index_of_fc)
     future_upper_series = pd.Series(confint[:, 1], index=future_index_of_fc)
 
+    # TODO Plot Future
+    # plt.plot(future_fitted_series, color='darkgreen', label ='Future Forecasted Sales')
+    # plt.fill_between(future_lower_series.index,
+    #                  future_lower_series,
+    #                  future_upper_series,
+    #                  color='k', alpha=.15)
+    # plt.fill_between(lower_series.index,
+    #                  lower_series,
+    #                  upper_series,
+    #                  color='k', alpha=.15)
+
     future_sales_growth = sales_growth(df, future_fitted_series)
     future_sales_growth = future_sales_growth.iloc[n_periods:]
     df = dates_df(future_sales_growth)
-    st.write("Forecasted sales in the next 3 months")
-    st.write(df)
+    with col2:
+       col2.subheader("Forecasted sales in x days")
+       col2.write(df)
     st.session_state.forecasted = True
 
     with st.form("question_form"):
@@ -329,4 +368,12 @@ if (st.session_state.uploaded):
 
     if query_button or question:
         answer = get_converted_answer(df, question)
-        st.write("The answer is:", answer)
+        st.subheader("The answer is:", answer)
+
+# Hide Streamlit default style
+hide_st_style = """
+            <style>
+            footer {visibility: hidden;}
+            </style>
+            """
+st.markdown(hide_st_style, unsafe_allow_html=True)