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

# Load the CSV file
# file = "brick_kiln_lucknow_v1.csv"  # Replace with the correct path to your CSV file

# Dropdown to select the location
location = st.selectbox("Select Location", ["Lucknow", "Delhi", "Ahmedabad"])

# Determine the file path based on selection
if location == "Lucknow":
    file = "brick_kiln_lucknow_v1.csv"
    center_lat, center_lon = 26.8467, 80.9462
elif location == "Delhi":
    file = "brick_kiln_delhi_v1.csv"
    center_lat, center_lon = 28.7041, 77.1025
else:  # Ahmedabad
    file = "brick_kiln_ahmedabad_v2.csv"  # Replace with the actual path
    center_lat, center_lon = 23.0225, 72.5714


data = pd.read_csv(file)

# Streamlit app title
st.markdown("<h2 style='text-align: center;'>Brick Kiln Location and Conversion Visualization</h2>", unsafe_allow_html=True)

# Slider to select the year
year_selected = st.slider("Select the Year", min_value=int(data["Year made"].min()), max_value=int(data["Year made"].max()), value=int(data["Year made"].min()), step=1)
filtered_data = data[data["Year made"] <= year_selected]

# # Calculate the change in fcbk to zigzag by checking the 'fcb to zigzag' column
filtered_data["Conversion"] = filtered_data.apply(
    lambda row: "Converted" if row["Year made"] != row["fcb to zigzag"] else "No Conversion", axis=1
)


# Function to determine the status of each kiln based on the selected year
def get_status(row, year_selected):
    if row["fcb to zigzag"]==2009:
        return "fcbk"
    elif year_selected == row["fcb to zigzag"]:
        return "converted"
    else:
        return "zigzag"
    

    
# Function to classify each kiln based on the selected year
def classify_kiln(row, year_selected):
    if row["Year made"] > year_selected:
        return None  # Kiln not yet made
    elif row["fcb to zigzag"] > year_selected:
        return "FCBK"  # Kiln still FCBK
    else:
        return "Zigzag"  # Kiln has converted to Zigzag

# Apply classification to the data based on the selected year
data["Status1"] = data.apply(lambda row: classify_kiln(row, year_selected), axis=1)
fcbk_count = data[data["Status1"] == "FCBK"].shape[0]
zigzag_count = data[data["Status1"] == "Zigzag"].shape[0]


# Apply the status function to each row
data["Status"] = data.apply(lambda row: get_status(row, year_selected), axis=1)
filtered_data_conv = data[data["Year made"] <= year_selected]
filtered_data_conv["Type"] = filtered_data_conv["Type"].map({0: "fcbk", 1: "zigzag"})
filtered_data["Type"] = filtered_data["Type"].map({0: "fcbk", 1: "Zigzag"})
# Count the total brick kilns, fcbk, zigzag, and conversions
total_kilns = len(filtered_data)
fcbk_count1 = filtered_data[(filtered_data["Type"] == "fcbk")].shape[0]
zigzag_count1 = filtered_data_conv[(filtered_data_conv["Type"] == 'zigzag')].shape[0]
converted_count = filtered_data_conv[filtered_data_conv["Status"] == "converted"].shape[0]


# Display the total count and conversions
if location == "Lucknow":
    st.subheader(f"Total Brick Kilns in Lucknow up to Year {year_selected}: {total_kilns}")
    st.write(f"Fcbk: {fcbk_count1}",'  and  ' f"Zigzag: {zigzag_count1}")
    st.write(f"Converted from fcbk to zigzag: {converted_count}")
elif location == "Ahmedabad":
    st.subheader(f"Total Brick Kilns in Ahmedabad up to Year {year_selected}: {total_kilns}")
    st.write(f"Fcbk: {fcbk_count1}",'  and  ' f"Zigzag: {zigzag_count1}")
    st.write(f"Converted from fcbk to zigzag: {converted_count}")    
else:    
    st.subheader(f"Total Brick Kilns in Delhi up to Year {year_selected}: {total_kilns}")
    st.write(f"Fcbk: {fcbk_count}",'  and  ' f"Zigzag: {zigzag_count}")
    st.write(f"Converted from fcbk to zigzag: {converted_count}")



if location == "Lucknow":
    fig_filtered = px.scatter_mapbox(
        data,
        lat="Lat",
        lon="Lon",
        color="Status",
        color_discrete_map={"fcbk": "blue", "converted": "green", "zigzag": "red"},  # Set colors for fcbk, converted, and zigzag kilns
        mapbox_style="carto-positron",
        hover_name="Type",
        zoom=8.5,
        center={"lat": center_lat, "lon": center_lon},
        title=f"Brick Kiln Locations and Status up to Year {year_selected}",
        height=600,
        width=600
    )
elif location == "Delhi":
    fig_filtered = px.scatter_mapbox(
        data,
        lat="Lat",
        lon="Lon",
        color="Status1",
        color_discrete_map={"FCBK": "blue", "converted": "green", "Zigzag": "red"},  # Set colors for fcbk, converted, and zigzag kilns
        mapbox_style="carto-positron",
        hover_name="Type",
        zoom=8.5,
        center={"lat": center_lat, "lon": center_lon},
        title=f"Brick Kiln Locations and Status up to Year {year_selected}",
        height=600,
        width=600
    )
else:
    fig_filtered = px.scatter_mapbox(
        data,
        lat="Lat",
        lon="Lon",
        color="Status",
        color_discrete_map={"fcbk": "blue", "zigzag": "red"},  # Set colors for fcbk, converted, and zigzag kilns
        mapbox_style="carto-positron",
        hover_name="Type",
        zoom=8.5,
        center={"lat": center_lat, "lon": center_lon},
        title=f"Brick Kiln Locations and Status up to Year {year_selected}",
        height=600,
        width=600
    )



# # Display the map in Streamlit
# st.plotly_chart(fig_filtered)

# Yearly count of fcbk and zigzag kilns up to the selected year
yearly_summary = filtered_data.groupby("Year made")["Type"].value_counts().unstack(fill_value=0)

# Adjust the layout to display the table next to the map
# col1, col2 = st.columns([3, 1.5])

# with col1:
st.plotly_chart(fig_filtered)
    
# with col2:
#     st.subheader("Yearly Kiln Made")
#     st.dataframe(yearly_summary)
# # Dropdown to select the location

# Define historical data for Lucknow
years_lucknow = [2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022]
brick_kilns_total_lucknow = [117, 314, 376, 396, 408, 432, 433, 454, 461, 466, 470, 477, 478]
brick_kilns_fcb_lucknow = [52, 127, 159, 171, 178, 191, 192, 206, 208, 209, 209, 209, 209]
brick_kilns_zigzag_lucknow = [65, 187, 217, 225, 230, 241, 241, 248, 253, 257, 261, 268, 269]

# Define historical data for Delhi
years_delhi = [2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022]
brick_kilns_total_delhi = [188,502,649,701,719,751,770,770,775,783,794,795,796]
brick_kilns_fcb_delhi = [184,496,643,695,712,744,742,727,620,401,146,74,37]
brick_kilns_zigzag_delhi = [4,6,6,6,7,7,28,43,155,382,648,721,759]  

#define for Ahmedabad
years_ahmedabad = [2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022]
brick_kilns_total_ahmedabad = [74,92,115,136,140,155,155,156,156,164,165,169,172]
brick_kilns_fcb_ahmedabad = [74,92,115,136,140,155,155,156,156,164,165,168,172]
brick_kilns_zigzag_ahmedabad = [0,0,0,0,0,0,0,0,0,0,0,1,0]

# Select the dataset based on the location
if location == "Lucknow":
    years = years_lucknow
    brick_kilns_total = brick_kilns_total_lucknow
    brick_kilns_fcb = brick_kilns_fcb_lucknow
    brick_kilns_zigzag = brick_kilns_zigzag_lucknow
    title = "Number of Brick Kilns Over Years in Lucknow"
elif location == "Ahmedabad":
    years = years_ahmedabad
    brick_kilns_total = brick_kilns_total_ahmedabad
    brick_kilns_fcb = brick_kilns_fcb_ahmedabad
    brick_kilns_zigzag = brick_kilns_zigzag_ahmedabad
    title = "Number of Brick Kilns Over Years in Ahmedabad"
else:
    years = years_delhi
    brick_kilns_total = brick_kilns_total_delhi
    brick_kilns_fcb = brick_kilns_fcb_delhi
    brick_kilns_zigzag = brick_kilns_zigzag_delhi
    title = "Number of Brick Kilns Over Years in Delhi"

# Creating the line plot for the number of brick kilns over the years
fig_line = go.Figure()

fig_line.add_trace(go.Scatter(x=years, y=brick_kilns_total, mode='lines+markers', name='Total Brick Kilns', line=dict(color='blue')))
fig_line.add_trace(go.Scatter(x=years, y=brick_kilns_fcb, mode='lines+markers', name='FCBTK', line=dict(color='red')))
fig_line.add_trace(go.Scatter(x=years, y=brick_kilns_zigzag, mode='lines+markers', name='Zigzag Brick Kilns', line=dict(color='green')))

# Adding labels and title to the line chart
fig_line.update_layout(
    title=title,
    xaxis_title="Years",
    yaxis_title="Number of Brick Kilns",
    yaxis=dict(tickmode='linear', tick0=0, dtick=100, showgrid=False), 
    width=900
)

# Adding vertical line for the selected year
fig_line.add_vline(x=year_selected, line_dash="dash", line_color="black", annotation_text=f"Year {year_selected}")

# Displaying the line chart
st.plotly_chart(fig_line)