#MY DATA
#product, category
myproduct = products[['product_id', 'product_category_name']].drop_duplicates()
myproduct = myproduct.rename(columns={'product_category_name' : 'category'})
#order, customer, seller, date
myorders = orders[['order_id', 'customer_id', 'order_purchase_timestamp', 'order_status']].drop_duplicates()
myorders =  myorders.rename(columns={'order_purchase_timestamp': 'date'})
myorders['date'] = pd.to_datetime(myorders['date']).dt.date
time_period = myorders[['date']]
time_period = time_period.sort_values(by='date')
marks = {i: str(sorted(all_dates['date'])[i]) for i in range(0, all_dates.shape[0], 7850)}
#seller, order, product
myitems = items[['seller_id', 'order_id', 'product_id']].drop_duplicates()
#seller, seller_state
mysellers = sellers[['seller_id', 'seller_state']].drop_duplicates()
#customer, customer_stat
mycustomers = customers[['customer_id', 'customer_state']].drop_duplicates()
unique_states = ['All'] + sorted(list(set(list(sellers.seller_state.unique()) + list(customers.customer_state.unique()))))
#statuses
unique_statuses = orders.order_status.unique()


app = Dash(__name__)

app.layout = html.Div([
    html.Label('Order statuses to display:', style={'font-size': '120%'}),
    dcc.Checklist(options=unique_statuses, value=unique_statuses, inline=True, id='statuses-filter'),
    html.Label('\nSelect state:', style={'font-size': '120%'}),
    html.Div(dcc.Dropdown(unique_states, 'All', id='states-dropdown'),
             style={'width': '200px', 'display': 'inline-block'}),
    dcc.Graph(id='sellers-graph'),
    dcc.Graph(id='seller-scatter'),
    dcc.Graph(id='customers-graph'),
    dcc.RangeSlider(
        min=0,
        max=time_period.shape[0] - 1,
        step=1,
        dots=False,
        value=[0, time_period.shape[0] - 1],
        marks=marks, allowCross=False,
        updatemode='mouseup',
        id='date-slider',
    ),

])


@app.callback(
    Output('customers-graph', 'figure'),
    [Input('date-slider', 'value'),
     Input('states-dropdown', 'value'),
     Input('statuses-filter', 'value')])
def update_figure(time_gap, state_to_display, statuses_filter, *args, **kwargs):
    start = time_gap[0]
    finish = time_gap[1]

    customer_distribution = myproduct.merge(myitems, on='product_id')
    customer_distribution = customer_distribution.drop_duplicates()
    customer_distribution = customer_distribution.groupby(['customer_id', 'category', 'order_id']).agg({'product_id' : 'count'}).reset_index()
    customer_distribution = customer_distribution.rename(columns={'product_id' : 'quantity'})
    customer_distribution = customer_distribution.merge(mysellers, on='seller_id')
    customer_distribution = customer_distribution.merge(myorders[['order_id', 'order_status', 'date']].drop_duplicates(), on='order_id')
    customer_distribution = customer_distribution[sorted(all_dates['date'])[start] <= customer_distribution.date]
    customer_distribution = customer_distribution[customer_distribution.date <= sorted(all_dates['date'])[finish]]
    customer_distribution = customer_distribution[customer_distribution['order_status'].isin(statuses_filter)]
    if state_to_display != 'All':
        customer_distribution = customer_distribution.loc[customer_distribution['seller_state'] == state_to_display]
    else:
        customer_distribution['customer_state'] = 'All states'
    customer_distribution = customer_distribution.drop(columns=['date'])
    customer_distribution = customer_distribution.groupby(['category', 'customer_state']).agg({'quantity' : 'sum'}).reset_index()
    overall = sum(customer_distribution['quantity'])
    customer_distribution['percentage'] = 100 * customer_distribution['quantity'] / overall
    df = customer_distribution[['category', 'percentage', 'customer_state']]
    #fig = px.scatter(df, y="percentage", x="category")
    fig = px.scatter(
        df, y="percentage", x="category", color="percentage",
        labels={"customer_state": "Customer State"},
        title="Seller Distribution by Category",
        height=300
    )
    fig.update_layout(transition_duration=500)
    return fig

@app.callback(
    Output('seller-scatter', 'figure'),
    [Input('date-slider', 'value'),
     Input('states-dropdown', 'value'),
     Input('statuses-filter', 'value')])
def update_figure(time_gap, state_to_display, statuses_filter, *args, **kwargs):
    start = time_gap[0]
    finish = time_gap[1]

    seller_distribution = myproduct.merge(myitems, on='product_id')
    seller_distribution = seller_distribution.drop_duplicates()
    seller_distribution = seller_distribution.groupby(['seller_id', 'category', 'order_id']).agg({'product_id' : 'count'}).reset_index()
    seller_distribution = seller_distribution.rename(columns={'product_id' : 'quantity'})
    seller_distribution = seller_distribution.merge(mysellers, on='seller_id')
    seller_distribution = seller_distribution.merge(myorders[['order_id', 'order_status', 'date']].drop_duplicates(), on='order_id')
    seller_distribution = seller_distribution[sorted(all_dates['date'])[start] <= seller_distribution.date]
    seller_distribution = seller_distribution[seller_distribution.date <= sorted(all_dates['date'])[finish]]
    seller_distribution = seller_distribution[seller_distribution['order_status'].isin(statuses_filter)]
    if state_to_display != 'All':
        seller_distribution = seller_distribution.loc[seller_distribution['seller_state'] == state_to_display]
    else:
        seller_distribution['seller_state'] = 'All states'
    seller_distribution = seller_distribution.drop(columns=['date'])
    seller_distribution = seller_distribution.groupby(['category', 'seller_state']).agg({'quantity' : 'sum'}).reset_index()
    overall = sum(seller_distribution['quantity'])
    seller_distribution['percentage'] = 100 * seller_distribution['quantity'] / overall
    df = seller_distribution[['category', 'percentage', 'seller_state']]
    fig = px.bar(
        df, y="seller_state", x="percentage", color="category", color_continuous_scale="emrld",
        labels={"seller_state": "Seller State"},
        title="Distribution by Sales Categories",
        orientation='h',
        height=300
    )
    #fig = px.bar(df, y="seller_state", x="percentage", color="category", title="Distribution by sales categories",
                 #orientation='h', height=300)

    fig.update_layout(transition_duration=500)
    return fig



if __name__ == '__main__':
    app.run_server(debug=True, port=8095)