feat: tab separation

pages/1_📈_Plotting.py

@@ -7,6 +7,8 @@ st.header("Plotting Time Series Data")
 st.markdown("Users can load their time-series data in **.csv** format and select a particular feature and plot-type.\
  Go ahead and use the sidebar on the left to upload your data files to start visualizing it!")
 
+tab1, tab2 = st.tabs(["Main", "Demo"])
+
 # Load and config
 with st.sidebar:
     plot = st.radio("Select the kind of visualization:",('Feature collection', 'Users comparison', 'Data distribution'))
@@ -22,46 +24,51 @@ with st.sidebar:
                 st.session_state['df'] = df
         st.success("Your data has been successfully loaded! 🤗")
 
-if 'df' in st.session_state:
-    st.caption("Your uploaded data:")
-    st.dataframe(st.session_state.df)
-else:
-    st.caption("Upload your data using the sidebar and select a plot-type to start :sunglasses:")
-
-df_base = st.session_state.df if 'df' in st.session_state else pd.DataFrame()
-n = len(df_base)
-col1, col2 = st.columns(2)
-
-# Prepare data
-if not df_base.empty and n:
-    with col1:
-        st.info(f"Your data has {n} samples.")
-    slider_range = list(range(n))
-    n_plot = st.slider("How many samples do you want to plot in the same graph", slider_range[0]+1, slider_range[-1]+1, 5)
-    plot_it = st.button("Plot now! 📊")
-    if plot_it:
-        st.snow()
-        feature = "relative_pupil_dilation"
-        df_plot = df_base.head(n_plot)
-        df_plot = [ini_list.strip('][').split(',') for ini_list in df_plot[feature]]
-        df_plot = pd.DataFrame(df_plot)
-        df_plot.columns = [str(column) for column in range(len(df_plot.columns))]
-        if 'df_plot' not in st.session_state:
-            st.session_state['df_plot'] = df_plot
-
-# Draw plot
-if 'df_plot' in st.session_state:
-    with st.spinner(f"Drawing plot to visualize {plot.lower()}"):
-        st.caption("Your visualization:")
-        df_plot_t = df_plot.copy(deep=True).transpose()
-        df_plot_t.columns = [str(column) for column in range(len(df_plot_t.columns))]
-        st.line_chart(df_plot_t, y=list(df_plot_t.columns), height=400, width=600)
-        st.dataframe(df_plot_t)
-        with st.expander("See explanation"):
-                st.caption("The chart above shows...")
-elif df_base.empty and file:
-    st.warning("Consider running outlier detection to clean your data!", icon="⚠️")
+with tab1:
+    if 'df' in st.session_state:
+        st.caption("Your uploaded data:")
+        st.dataframe(st.session_state.df)
+    else:
+        st.caption("Upload your data using the sidebar and select a plot-type to start :sunglasses:")
     
-st.caption(f"developer:: session_state keys: {list(st.session_state.keys())}")
-st.caption(f"what is the meaning of the x-axis, add to explanation")
-st.caption(f"add sample data demo in another tab")
+    df_base = st.session_state.df if 'df' in st.session_state else pd.DataFrame()
+    n = len(df_base)
+    col1, col2 = st.columns(2)
+    
+    # Prepare data
+    if not df_base.empty and n:
+        with col1:
+            st.info(f"Your data has {n} samples.")
+        slider_range = list(range(n))
+        n_plot = st.slider("How many samples do you want to plot in the same graph", slider_range[0]+1, slider_range[-1]+1, 5)
+        plot_it = st.button("Plot now! 📊")
+        if plot_it:
+            st.snow()
+            feature = "relative_pupil_dilation"
+            df_plot = df_base.head(n_plot)
+            df_plot = [ini_list.strip('][').split(',') for ini_list in df_plot[feature]]
+            df_plot = pd.DataFrame(df_plot)
+            df_plot.columns = [str(column) for column in range(len(df_plot.columns))]
+            if 'df_plot' not in st.session_state:
+                st.session_state['df_plot'] = df_plot
+    
+    # Draw plot
+    if 'df_plot' in st.session_state:
+        with st.spinner(f"Drawing plot to visualize {plot.lower()}"):
+            st.caption("Your visualization:")
+            df_plot_t = df_plot.copy(deep=True).transpose()
+            df_plot_t.columns = [str(column) for column in range(len(df_plot_t.columns))]
+            st.line_chart(df_plot_t, y=list(df_plot_t.columns), height=400, width=600)
+            st.dataframe(df_plot_t)
+            with st.expander("See explanation"):
+                    st.caption("The chart above shows...")
+    elif df_base.empty and file:
+        st.warning("Consider running outlier detection to clean your data!", icon="⚠️")
+        
+    st.caption(f"developer:: session_state keys: {list(st.session_state.keys())}")
+    st.caption(f"what is the meaning of the x-axis, add to explanation")
+    st.caption(f"add sample data demo in another tab")
+
+# demo
+with tab2:
+    st.caption("demo under construction 🚧")