import os

import pandas as pd
import plotly.express as px
import streamlit as st

st.set_page_config(page_title="Dashboard", layout="wide", initial_sidebar_state="expanded")

st.header("Scrapper Dashboard")
st.sidebar.subheader("Parameters Dashboard")

def create_plot(column, row, chart_type, df,brandcolumn):
    fig = None
    Brand=brandcolumn
    if chart_type == "bar":
        fig = px.bar(df, x=column, y=row, color=f"{Brand}", title=f"{row} by {column}")
    elif chart_type == "scatter":
        fig = px.scatter(df, x=column, y=row, color=f"{Brand}", title=f"{row} by {column}")
    elif chart_type == "line":
        fig = px.line(df, x=column, y=row,color=f"{Brand}", title=f"{row} by {column}")
    elif chart_type == "histogram":
        fig = px.histogram(df, x=column,color=f"{Brand}", title=f"Distribution of {column}")
    elif chart_type == "pie":
        brand_counts = df[f"{column}"].value_counts()
        distribute = px.pie(brand_counts,color=f"{Brand}", values=brand_counts.values, names=brand_counts.index,title=f"Distribution of Mobile Phone {column}")
        fig=distribute.update_traces(hoverinfo="label+percent", textinfo="label+percent+value", hole=.4)
    elif chart_type == "series":
        fig=px.line(df, x=column, y=row,color=f"{Brand}", title="Series Chart")
    elif chart_type == "heatmap":
        fig = px.density_heatmap(df, x=column, y=row,color=f"{Brand}", marginal_x="histogram", marginal_y="histogram", color_continuous_scale=px.colors.sequential.PuBu, title=f"Heatmap for {column} vs Price")
    elif chart_type == "bubble":
        fig = px.scatter(df, x=column, y=row,color=f"{Brand}", size="Battery",title=f"Bubble chart for {column}")
    elif chart_type == "box":
        fig = px.box(df, x=column, y=row,color=f"{Brand}", title=f"Box plot for {row} by {column}")
    elif chart_type == "violin":
        fig = px.violin(df, x=column, y=row,color=f"{Brand}",title=f"Violin plot for {row} by {column}")
    elif chart_type == "funnel":
        fig = px.funnel(df, x=column, y=row,color=f"{Brand}", title=f"Funnel chart for {column} and {row}")
    else:
        st.error("Invalid chart type")
    return fig


def display_dataframe(df):
    st.subheader("Uploaded CSV :")
    st.dataframe(df)


def display_analysis(df,selectedcolumns,brandcol):
    st.header("Visualization")
    #columns = df.columns.tolist()
    columns=selectedcolumns
    chart_types = [
        "bar", "scatter", "line", "histogram", "pie",
        "series", "heatmap", "box", "violin", "funnel"
    ]

    st.sidebar.subheader("Select Parameters for Plots: ")
    x = st.sidebar.selectbox("Select a x", columns)
    y = st.sidebar.selectbox("Select a y", columns)
    chart_type = st.selectbox("Select a chart type", chart_types)


    #st.subheader(f"{chart_type.title()} chart for {x} and {y}")
    fig = create_plot(x, y, chart_type, df,brandcol)
    st.plotly_chart(fig)


def main():
    # Sidebar related code
    st.sidebar.header("Select a file")
    
    files = os.listdir(".")
    csv_files = [file for file in files if file.endswith(".csv")]

    if len(csv_files) == 0:
      st.sidebar.write("No CSV files found in current directory. Please upload a CSV file.")
      selected_file = st.sidebar.file_uploader("Upload CSV file", type=['csv'])
    else:
      csv_files = ["None"] + csv_files
      selected_file = st.sidebar.selectbox("Select a file", csv_files)

    if selected_file=='None':
      st.write('Please Select your or Upload File.')
    elif selected_file:
      site = ["None", "Flipkart", "Amazon","Both"]
      siteselect = st.sidebar.selectbox("Select options :", site)
      df = pd.read_csv(selected_file)
      flipkart_cols = [col for col in df.columns if col.startswith('Flipkart')]
      amazon_cols = [col for col in df.columns if col.startswith('Amazon')]
      if siteselect == "None":
        st.write('DataFrame')
        display_dataframe(df)
        st.write('Select Site')
      elif siteselect == 'Flipkart':
        viewpoint = ["None", "Show DataFrame", "Show Analysis"]
        dataset_show = st.sidebar.selectbox("Select options :", viewpoint)
        if dataset_show == "Show DataFrame":
            flipkart_data = df[flipkart_cols]
            display_dataframe(flipkart_data)
        elif dataset_show == "Show Analysis":
            display_analysis(df,flipkart_cols,'FlipkartBrand')
        else:
            st.sidebar.write("Please select a CSV file.")
      elif siteselect == 'Amazon':
        viewpoints = ["None", "Show DataFrame", "Show Analysis"]
        dataset_shows = st.sidebar.selectbox("Select options :", viewpoints)
        if dataset_shows == "Show DataFrame":
            amazon_data = df[amazon_cols]
            display_dataframe(amazon_data)
        elif dataset_shows == "Show Analysis":
            display_analysis(df,amazon_cols,'AmazonBrand')
        else:
            st.sidebar.write("Please select a options.")
      elif siteselect == 'Both':
        viewpoin = ["None", "Show DataFrame", "Show Analysis"]
        dataset_sho = st.sidebar.selectbox("Select options :", viewpoin)
        if dataset_sho == "Show DataFrame":
            display_dataframe(df)
        elif dataset_sho == "Show Analysis":
            columns = df.columns.tolist()
            display_analysis(df,columns,'FlipkartBrand')
        else:
            st.sidebar.write("Please select a options.")
    else:
            st.sidebar.write("Please select a CSV file.")

if __name__ == "__main__":
    main()