davidcomfort

# Callback for the Graphs
@app.callback(
   Output('paid-search', 'figure'),
   [Input('datatable-paid-search', "selected_rows"),
   Input('my-date-picker-range-paid-search', 'end_date')])
def update_paid_search(selected_rows, end_date):
	travel_product = []
	travel_product_list = df[(df['Category'] == 'Paid Search')]['Placement type'].unique().tolist()
	for i in selected_rows:
		travel_product.append(travel_product_list[i])

davidcomfort

######################## START Paid Search Layout ########################
layout_paid_search =  html.Div([
    html.Div([
        # CC Header
        Header(),
        # Date Picker
        html.Div([
            dcc.DatePickerRange(
              id='my-date-picker-range-paid-search',
              min_date_allowed=dt(2018, 1, 1),

davidcomfort

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

davidcomfort

# Update page
# # # # # # # # #
@app.callback(Output('page-content', 'children'),
              [Input('url', 'pathname')])
def display_page(pathname):
    if pathname == '/cc-travel-report' or pathname == '/cc-travel-report/overview-birst/':
        return layout_birst_category
    elif pathname == '/cc-travel-report/overview-ga/':
        return layout_ga_category
    elif pathname == '/cc-travel-report/paid-search/':

davidcomfort

import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)

app.layout = html.Div([

davidcomfort

style_cell_conditional=[{'if': {'column_id': 'Revenue YoY (%)', 
                         'filter': 'Revenue_YoY_percent_conditional < num(0)'}, 
                         'color': 'red'}]

davidcomfort

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',]

davidcomfort

html.Div([
    dash_table.DataTable(
        id='datatable-paid-search',
        columns=[{"name": i, "id": i, 'deletable': True} for i in dt_columns] 
        + [{"name": j, "id": j, 'hidden': 'True'} for j in conditional_columns], 
        editable=True,
        n_fixed_columns=2,
        style_table={'maxWidth': '1500px'},
        row_selectable="multi",
        selected_rows=[0],

davidcomfort

dash_table.DataTable(
    data=df.to_dict('rows'),
    columns=[
        {'name': i, 'id': i} for i in df.columns
    ],
    style_data_conditional=[
        {
            'if': {
                'column_id': 'Region',
                'filter': 'Region eq "Montreal"'

davidcomfort

pip install dash==0.39.0  # The core dash backend
pip install dash-html-components==0.14.0  # HTML components
pip install dash-core-components==0.44.0  # Supercharged components
pip install dash-table==3.6.0  # Interactive DataTable component (new!)
pip install dash-daq==0.1.0  # DAQ components (newly open-sourced!)