dashboard_layouts_beginning.py

import dash_core_components as dcc
import dash_html_components as html
import dash_table
from components import Header, print_button
from datetime import datetime as dt
from datetime import date, timedelta
import pandas as pd


# Read in Travel Report Data
df = pd.read_csv('data/performance_analytics_cost_and_ga_metrics.csv')

df.rename(columns={
 'Travel Product': 'Placement type', 
  'Spend - This Year': 'Spend TY', 
  'Spend - Last Year': 'Spend LY', 
  'Sessions - This Year': 'Sessions - TY',
  'Sessions - Last Year': 'Sessions - LY',
  'Bookings - This Year': 'Bookings - TY',
  'Bookings - Last Year': 'Bookings - LY',
  'Revenue - This Year': 'Revenue - TY',
  'Revenue - Last Year': 'Revenue - LY',
  }, inplace=True)


df['Date'] = pd.to_datetime(df['Date'])
current_year = df['Year'].max()

dt_columns = ['Placement type', 'Spend TY', 'Spend - LP', 'Spend PoP (Abs)', 'Spend PoP (%)', 'Spend LY', 'Spend YoY (%)', \
                        'Sessions - TY', 'Sessions - LP', 'Sessions - LY', 'Sessions PoP (%)', 'Sessions YoY (%)', \
                        'Bookings - TY', 'Bookings - LP', 'Bookings PoP (%)', 'Bookings PoP (Abs)', 'Bookings - LY', 'Bookings YoY (%)', 'Bookings YoY (Abs)', \
                        'Revenue - TY', 'Revenue - LP', 'Revenue PoP (Abs)', 'Revenue PoP (%)', 'Revenue - LY', 'Revenue YoY (%)', 'Revenue YoY (Abs)',]

conditional_columns = ['Spend_PoP_abs_conditional', 'Spend_PoP_percent_conditional', 'Spend_YoY_percent_conditional',
'Sessions_PoP_percent_conditional', 'Sessions_YoY_percent_conditional', 
'Bookings_PoP_abs_conditional', 'Bookings_YoY_abs_conditional', 'Bookings_PoP_percent_conditional', 'Bookings_YoY_percent_conditional',
'Revenue_PoP_abs_conditional', 'Revenue_YoY_abs_conditional', 'Revenue_PoP_percent_conditional', 'Revenue_YoY_percent_conditional',]

dt_columns_total = ['Placement type', 'Spend TY', 'Spend - LP', 'Spend PoP (Abs)', 'Spend PoP (%)', 'Spend LY', 'Spend YoY (%)', \
                        'Sessions - TY', 'Sessions - LP', 'Sessions - LY', 'Sessions PoP (%)', 'Sessions YoY (%)', \
                        'Bookings - TY', 'Bookings - LP', 'Bookings PoP (%)', 'Bookings PoP (Abs)', 'Bookings - LY', 'Bookings YoY (%)', 'Bookings YoY (Abs)', \
                        'Revenue - TY', 'Revenue - LP', 'Revenue PoP (Abs)', 'Revenue PoP (%)', 'Revenue - LY', 'Revenue YoY (%)', 'Revenue YoY (Abs)',
                        'Spend_PoP_abs_conditional', 'Spend_PoP_percent_conditional', 'Spend_YoY_percent_conditional',
'Sessions_PoP_percent_conditional', 'Sessions_YoY_percent_conditional', 
'Bookings_PoP_abs_conditional', 'Bookings_YoY_abs_conditional', 'Bookings_PoP_percent_conditional', 'Bookings_YoY_percent_conditional',
'Revenue_PoP_abs_conditional', 'Revenue_YoY_abs_conditional', 'Revenue_PoP_percent_conditional', 'Revenue_YoY_percent_conditional',]

df_columns_calculated = ['Placement type', 'CPS - TY', 
                        'CPS - LP', 'CPS PoP (Abs)', 'CPS PoP (%)',
                        'CPS - LY',  'CPS YoY (Abs)',  'CPS YoY (%)', 
                        'CVR - TY', 
                        'CVR - LP', 'CVR PoP (Abs)', 'CVR PoP (%)',
                        'CVR - LY',  'CVR YoY (Abs)',  'CVR YoY (%)',
                        'CPA - TY', 
                        'CPA - LP', 'CPA PoP (Abs)', 'CPA PoP (%)',
                        'CPA - LY', 'CPA YoY (Abs)',  'CPA YoY (%)']

conditional_columns_calculated_calculated = ['CPS_PoP_abs_conditional', 'CPS_PoP_percent_conditional', 'CPS_YoY_abs_conditional', 'CPS_PoP_percent_conditional', 
'CVR_PoP_abs_conditional', 'CVR_PoP_percent_conditional', 'CVR_YoY_abs_conditional', 'CVR_YoY_percent_conditional',
'CPA_PoP_abs_conditional', 'CPA_PoP_percent_conditional', 'CPA_YoY_abs_conditional', 'CPA_YoY_percent_conditional']