import streamlit as st
import pandas as pd
import time


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 and to start visualizing it!")

with st.sidebar:
    plot = st.radio("Select the kind of visualization:",('Feature collection', 'Users comparison', 'Data distribution'))
    file = st.file_uploader("Load CSV file", accept_multiple_files = False)
    if file:
        df = pd.read_csv(file, index_col = False)
        # df.index = df['Unnamed: 0'].tolist()
        try:
            del df['Unnamed: 0']
        except KeyError:
            pass
        if 'df' not in st.session_state:
                st.session_state['df'] = df
        st.success("Your data has been successfully loaded! 🤗")

if 'df' in list(st.session_state.keys()):
    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 list(st.session_state.keys()) else pd.DataFrame()
n = len(df_base)
col1, col2 = st.columns(2)

if not df_base.empty:
    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)
        st.write(f"Action: {plot} using {n_plot} samples")
        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]]
            st.caption("The visualized data:")
            df_plot = pd.DataFrame(df_plot)
            st.dataframe(df_plot)
            if 'df_plot' not in st.session_state:
                st.session_state['df_plot'] = df_plot
            with st.expander("See explanation"):
                st.caption("The chart above shows...")
            # 
    # with col2:
if 'df_plot' in list(st.session_state.keys()):
    with st.spinner(f"Drawing plot to visualize {plot.lower()}"):
        st.caption("Your visualization:")
        st.dataframe(st.session_state.df_plot)
        st.line_chart(st.session_state.df_plot)
        st.dataframe(st.session_state.df_plot.transpose())
        st.line_chart(st.session_state.df_plot.transpose())
elif df_base.empty and file:
    st.warning("Consider running outlier detection to clean your data!", icon="⚠️")