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app1.py
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#!/usr/bin/python3 # REMOVE FOR pythonanywhere
dir1 = "App1/"; dir2 = "~/courses/BI_Udemy/python/maps/" #HOME
#dir1 = "/home/steviecurran/mysite/App1/"; dir2 = "/home/steviecurran/maps/" # pythonanywhere
import numpy as np
import pandas as pd
import os
import sys
import calendar
import datetime as dt
from datetime import date, timedelta, datetime
from shutil import get_terminal_size
pd.set_option('display.width', get_terminal_size()[0])
pd.set_option('display.max_columns', None)
import dash
from dash import Dash, html, dcc, Input, Output, ctx, State
import plotly.graph_objects as go
import plotly.express as px
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output, State
from plotly.subplots import make_subplots
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
app = Dash(external_stylesheets=[dbc.themes.BOOTSTRAP])
app.config.suppress_callback_exceptions=True
df = pd.read_csv(dir1+'merged_data2.csv');
df['Target Sales'] = 0.8*df['Sales Amount']
date = 'OrderDate'
df['date']=pd.to_datetime(df[date], infer_datetime_format=True).dt.date
df = df.sort_values('date')
dates = df['date'].unique()
customers = df['Name'].sort_values().unique()
regions = df['SalesTerritoryRegion'].sort_values().unique()
countries = df['SalesTerritoryCountry'].sort_values().unique()
EUR_to_USD = 0.9914
df.rename(columns={'SalesTerritoryCountry':'COUNTRY'}, inplace = True); #print(dfm)
dfcodes = pd.read_csv(dir2+'2014_world_gdp_with_codes.csv');
df = df.merge(dfcodes,on = 'COUNTRY');
def main_table(data,cur,choice,tosum):
dfg = data.groupby([choice]).count()['OrderQuantity'].to_frame(name = 'Items Sold').reset_index()
df1 = data.sort_values(choice);
names = dfg[choice].unique();
df_price = pd.DataFrame()
for (i,name) in enumerate(names):
df_name = df1[df1[choice] == name]
df_name.reset_index(drop=True, inplace=True)
df_price = df_price.append(df_name.iloc[0])
df_MT = dfg.merge(df_price,on = choice)
df_MT['UnitPrice']= df_MT['UnitPrice']*df[cur]/EUR_to_USD
df_MT['Sales Amount'] = df_MT['Items Sold']*df_MT['UnitPrice']
df_MT = df_MT[[choice,'UnitPrice','Items Sold','Sales Amount']]
df_MT['UnitPrice'] = round(df_MT['UnitPrice'],2);
df_MT['Sales Amount'] = round(df_MT['Sales Amount'],1); #print(df_MT)
df_MT['total'] = df_MT[tosum].sum()
df_MT['Percent'] = round(100*df_MT[tosum]/df_MT['total'],2)
return df_MT
def map_paras(data,para):
dfm = data.groupby(['COUNTRY']).sum();
dfM = dfm.merge(dfcodes,on = 'COUNTRY');
return dfM
# For TABLE 2 ON 2ND PAGE
def table2_fix(data,cur):
dfc = data.copy()
dfc['UnitPrice']= data['UnitPrice']*data[cur]/EUR_to_USD
dfo = dfc.groupby('Product Name').sum()['OrderQuantity'].to_frame(name = 'Items Sold').reset_index();
dfu = dfc.groupby('Product Name').sum()['UnitPrice'].to_frame(name = 'Total Price').reset_index();
names = dfc['Product Name'].unique(); #print(names)
df_price = pd.DataFrame()
for (i,name) in enumerate(names):
df_name = data[data['Product Name'] == name]
df_name.reset_index(drop=True, inplace=True)
df_price = df_price.append(df_name.iloc[0])
df_M = dfo.merge(df_price,on = 'Product Name');
df_MT = df_M.merge(dfu,on = 'Product Name');
df_MT['Total Price'] = round(df_MT['Total Price'],2);
df_MT = df_MT[['Product Name','Description','Items Sold','Total Price']];
return df_MT
def sold(data):
names = df['Product Name'].unique();
df_sum = pd.DataFrame();
for (i,name) in enumerate(names):
df_name = data[data['Product Name'] == name];
df_name = df_name[['Product Name','Color','Sales Amount','OrderQuantity']]
df_name.reset_index(drop=True, inplace=True);
df_name['Items Sold'] = df_name['OrderQuantity'].sum();
df_sum = df_sum.append(df_name.iloc[0])
top = df_sum.sort_values('Items Sold',ascending=False);
#print(top)
return top
def time_series(data,n): # WILL USE ORIGINAL DATA, NO FILTERING BY CURRENCY OR DATE
items = sold(df);
names = items['Product Name'].head(n); #print(names)
df_top= pd.DataFrame();
for (i,name) in enumerate(names):
df_name = data[data['Product Name'] == name];
df_name = df_name[['date','Product Name','Color','Sales Amount','OrderQuantity']]
df_name.reset_index(drop=True, inplace=True);
df_top = df_top.append(df_name);
#print(df_top)
return df_top
#########################
SIDEBAR_STYLE = {"position": "fixed","top": 0,"left": 0,"bottom": 0,"width": "20rem",
"padding": "2rem 1rem","background-color": "#046F78", "color": "white"}
CONTENT_STYLE = {"margin-left": "20rem", "margin-right": "0rem", "padding": "2rem 1rem"}
sidebar = html.Div([
html.P(),
dbc.Nav(
[
dbc.NavLink("Overview", href="/", active="exact",
style={"background-color": "white",
"text-color": "black",'fontSize': 20}),
html.P(),
dbc.NavLink("Top Selling Products", href="/top", active="exact",
style={"background-color": "white",
"text-color": "black",'fontSize': 20})
],
vertical=True,
pills=False, # True hides inactive
),
html.Br(),
html.P("Date range"),
html.Div( # SO DROPDOWNS IN SAME ROW
className="row",children=[
html.Div(className='three columns', children=[
dcc.Dropdown(
#['First','Last'],
dates,df[date].iat[0],
id='drop1',
style={'color': 'black', 'font-weight':'bold'},
)], style=dict(width='50%')),
html.Div(className='three columns', children=[
dcc.Dropdown(
#nos, '1',
dates, df[date].iat[-1],
id='drop2',
style={'color': 'black','font-weight':'bold'},
)], style=dict(width='50%')),
], style=dict(display='flex')
), # CLOSING DROPDOWNS
dcc.Checklist(['No filter applied'],
id='check1',
inline=True
),
html.Br(),
html.Button('AUD', id='btn-nclicks-1', n_clicks=0,style={'width':'53px','margin-right': '4px'}),
html.Button('CAD', id='btn-nclicks-2', n_clicks=0,style={'width':'53px','margin-right': '4px'}),
html.Button('EUR', id='btn-nclicks-3', n_clicks=0,style={'width':'53px','margin-right': '4px'}),
html.Button('GBP', id='btn-nclicks-4', n_clicks=0,style={'width':'53px','margin-right': '4px'}),
html.Button('USD', id='btn-nclicks-5', n_clicks=0,style={'width':'53px','margin-right': '4px'}),
html.Div(id='container-button'),
html.Br(),
html.Hr(style = {"opacity": "unset"}),
html.Br(),
html.Div(children=[
html.Label(["Customer Name"], style={'fontSize': 18, "textAlign": "center" }),
dcc.Dropdown(
customers,
"All",
id='cus-drop',
style={'color': 'black'}, #
)
]),
html.Br(),
html.Div(children=[
html.Label(["Region"], style={'fontSize': 18, "text-align": "center" }),
dcc.Dropdown(
regions, "All",
id='reg-drop',
style={'color': 'black'},
),
]),
html.Br(),
html.Div(children=[
html.Label(["Country"], style={'fontSize': 18, "textAlign": "center" }),
dcc.Dropdown(
countries, "All",
id='cou-drop',
style={'color': 'black'},
),
]),
], style=dict(SIDEBAR_STYLE,overflow= "scroll"),
)
content = html.Div(id="page-content", style=CONTENT_STYLE)
app.layout = html.Div([dcc.Location(id="url"),sidebar,content])
@app.callback(Output("page-content", "children"),[Input("url", "pathname")])
def render_page_content(pathname):
if pathname == "/":
return html.Div([
html.P("Global Sales Analysis",
style={'font-family':'Arial Black','color': 'black', 'fontSize': 24,'textAlign':'center'}),
dbc.Row(children = [ # OPEN TOP BUTTONS
html.Div(children=[
dbc.Button('Total Sales',id='btn-map-1', className="mb-3",color="primary",n_clicks=0,
style={'margin-left': '250px','margin-right': '10px'}),
dbc.Button('Units Sold',id='btn-map-2', className="mb-3",color="primary",n_clicks=0,
style={'margin-right': '10px'}),
dbc.Button('Unit Price',id='btn-map-3', className="mb-3",color="primary",n_clicks=0,
style={'margin-right': '10px'}),
dbc.Button('Product Cost',id='btn-map-4', className="mb-3",color="primary",n_clicks=0,
style={'margin-right': '10px'})
]
),
],
), # CLOSE TOP BUTTONS
html.Div([ # OPEN POP-UP
dcc.Graph(id='map1'),
dbc.Modal([
dbc.ModalBody([
dcc.Graph(id='gauge1'),
dbc.ModalBody(dbc.ModalTitle(id='text1',style={'fontSize': 30})),
dcc.Graph(id='yoy1'),
]
),
], id = 'modal1',
is_open=False,
),
],
),
html.Div([
dbc.Row([ # OPENING TABLE AND DONUT
dbc.Col([
dcc.Graph(id='table1'),
]),
dbc.Col([
html.Div(id='textarea-output',style={'fontSize': 16,'font-weight':'bold'}),
dcc.Graph(id='donut1')
]),
]), # CLOSING TABLE AND DONUT
])
]) # CLOSING HOME PAGE
elif pathname == "/top":
return html.Div([
html.P("Top Selling Products",
style={'font-family':'Arial Black','color': 'black', 'fontSize': 24,'textAlign':'center'}),
html.Div(id='text2',style={'fontSize': 18,'font-weight':'bold'}),html.Br(),
dcc.Graph(id='table2'),
html.Div(id='text3',style={'fontSize': 18,'font-weight':'bold', 'margin-left': '100px'}),
html.Br(),
html.P([
dbc.Row(children = [
"Select top n sellers",
dcc.Dropdown(
[1,5,10,20,50,100, "All"],
129, #ALL FOR DEFAULT
id='time-drop',
style={'width': '15%', 'margin-left': '10px', 'margin-right': '0px', 'font-weight':'bold'},
),
"Show total ",
dcc.RadioItems(
['Yes','No'],
'No', # default
id='total-show',
style={'width': '15%', 'margin-left': '0px', 'font-weight':'bold'},
),
dbc.Col([
"Number of sales to smooth total by ",
html.Div([
dcc.Slider(
0,4,0.2,
id='slider',
marks={0: '1', 1: '10',2: '100', 3: '1000'}, #, 4: ''},
value=0
),
],style={'width': '45%', 'margin-left': '0px', 'font-weight':'bold'},
),
]),
]),
dcc.Graph(id='time-series'),
],style={'margin-left': '60px'}
)
])
@app.callback(
Output('map1', 'figure'),
Output('table1', 'figure'),
Output('donut1', 'figure'),
Output('textarea-output', 'children'),
Input('check1', 'value'), Input('drop1', 'value'), Input('drop2', 'value'),
Input('btn-nclicks-1', 'n_clicks'),Input('btn-nclicks-2', 'n_clicks'),
Input('btn-nclicks-3', 'n_clicks'),Input('btn-nclicks-4', 'n_clicks'),
Input('btn-nclicks-5', 'n_clicks'),Input('btn-map-1', 'n_clicks'),
Input('btn-map-2', 'n_clicks'), Input('btn-map-3', 'n_clicks'),
Input('btn-map-4', 'n_clicks'),
)
def some_plots(check,date1,date2,btn1,btn2,btn3,btn4,btn5,btn_map1,btn_map2,btn_map3,btn_map4):
cur = 'USD';
if "btn-nclicks-1" == ctx.triggered_id:
cur = 'AUD'
elif "btn-nclicks-2" == ctx.triggered_id:
cur = 'CAD'
elif "btn-nclicks-3" == ctx.triggered_id:
cur = 'EUR'
elif "btn-nclicks-4" == ctx.triggered_id:
cur = 'GBP'
elif "btn-nclicks-5" == ctx.triggered_id:
cur = 'USD'
df['Total Sales Amount'] = df['OrderQuantity']*df['UnitPrice']*df[cur]/EUR_to_USD
Date1 = datetime.strptime(date1,'%Y-%m-%d')
Date2 = datetime.strptime(date2,'%Y-%m-%d')
pd.options.mode.chained_assignment = None
df[date] = pd.to_datetime(df[date]);
if check == None or check == []:
if Date1 < Date2:
dff = df[df[date] >= Date1]
dff = dff[dff[date] <= Date2]
else: # MAKING REVERSABLE
dff = df[df[date] >= Date2]
dff = dff[dff[date] <= Date1]
else:
dff = df.copy()
Date1 = df[date].iat[0];
Date2= df[date].iat[-1];
d1 = Date1.date(); d2 = Date2.date();
choice = 'Product Name'
df_T = main_table(dff,cur,choice,'Items Sold')
cols = df_T.columns.values;
table = go.Figure(data=[go.Table(
columnwidth = [2.5,1,1],
header=dict(values=([choice,'Items Sold','Sales Amount']),
fill_color='#305D91',
font=dict(color='white', size=14),
align='left'
),
cells=dict(values= [df_T['Product Name'],df_T['Items Sold'],df_T['Sales Amount']],
fill_color='#E0EEEF', #https://htmlcolorcodes.com
font=dict(color='black', size=14),
height=30, align='left'),
)
])
table.update_layout(width=500, height=400,margin={"pad": 0, "t": 0,"r": 0,"l": 0,"b": 0})
df_D = main_table(dff,cur,'Color','Items Sold'); #print(df_D)
colours = df_D.iloc[:,0];
donut = go.Figure(data=[go.Pie(labels=df_D['Color'],
values=df_D['Items Sold'], hole=.4)])
donut.update_traces(hoverinfo='label+percent', textinfo='value',
textfont_size=20, marker=dict(colors=colours,
line=dict(color='#000000', width=2)))
donut.update_layout(width=400, height=400,margin={"pad": 0, "t": 0,"r": 50,"l": 20,"b": 0})
para = 'Total Sales Amount'; prefix = cur
if "btn-map-1" == ctx.triggered_id:
para = 'Total Sales Amount'
prefix = cur
elif "btn-map-2" == ctx.triggered_id:
para = 'OrderQuantity'
prefix = ""
elif "btn-map-3" == ctx.triggered_id:
para = 'UnitPrice'
prefix = cur
elif "btn-map-4" == ctx.triggered_id:
para = 'TotalProductCost'
prefix = cur
df_M = map_paras(dff,para)
world = go.Figure(data=go.Choropleth(locations = df_M['CODE'],z = df_M[para],
text = df_M['COUNTRY'],colorscale = 'Rainbow',
autocolorscale=False,reversescale=True,
marker_line_color='black',
marker_line_width=1,
colorbar_tickprefix = prefix,
))
world.update_layout(width=950, height=550,margin={"pad": 0, "t": 0,"r": 0,"l": 0,"b": 0},
clickmode='event', # 'event+select',
geo=dict(showframe=False, showcoastlines=False),
annotations = [dict(x=0.5,y=0.15, xref='paper',yref='paper',
font=dict(color='black', size=16),
text='%s by country over %s to %s'
%(para,Date1.date(), Date2.date()),showarrow = False)]
),
world.update_traces(colorbar=dict(len=0.75))
return world,table,donut,'Units Sold by Colour'
@app.callback(
Output('modal1', 'is_open'),
Output('text1', 'children'),
Output('gauge1', 'figure'),
Output('yoy1', 'figure'),
[Input('map1', 'clickData')],
[State("modal1", "is_open")]
)
def popup(hoverData,is_open):
total = 0
target = 0
sales = 0
gauge = go.Figure()
text = ""
yoy = px.scatter()
yoy2 = px.scatter()
d_y = pd.DataFrame()
if hoverData != None: #and n1:
location = hoverData['points'][0]['location']
z = hoverData['points'][0]['z']
data = df[df['CODE'] == location]; d = data[data['Year'] == 2014]; #print(d)
sales = d['Sales Amount'].sum();
text = "Total Sales - %s" %(d['COUNTRY'].iat[0])
target = 0.8*sales
##### YoY GROWTH ##########
df_y = data.groupby(['Year']).sum()['Sales Amount'].to_frame(name = 'Total Sales').reset_index()
yoy = make_subplots(specs=[[{"secondary_y": True}]]) ## Secondary axies
yoy.add_trace(go.Scatter(x=df_y['Year'], y=df_y['Total Sales']),secondary_y=False)
df_y['Percent Sales'] = 100*df_y['Total Sales']/df_y['Total Sales'].max()
yoy.add_trace(go.Scatter(x=df_y['Year'], y=df_y['Percent Sales']), secondary_y=True)
yoy.update_layout(width=450, height=350, margin={"pad": 0, "t": 0,"r": 0,"l": 0,"b": 0},
showlegend=False)
yoy.update_xaxes(showgrid=False, linecolor = "black", linewidth = 3,mirror = True,
title="Year")
yoy.update_yaxes(showgrid=False, linecolor = "black", linewidth = 3,mirror = False,
title="Sales [USD]",secondary_y=False)
yoy.update_yaxes(showgrid=False, linecolor = "black", linewidth = 3,mirror = False,
title="Percentage of maximum", secondary_y=True)
############################
gauge = go.Figure(go.Indicator(
mode = "gauge+number+delta", value = sales,
domain = {'x': [0.05, 0.95], 'y': [0.0, 1]},
title = {'text': "2014 actual [%1.0f] vs. target [%1.0f] sales [USD]" %(sales,target),
'font': {'size': 18}},
delta = {'reference': target, 'increasing': {'color': "red"}},
gauge = {
'axis': {'range': [None, 2*target], 'tickwidth': 1, 'tickcolor': "darkblue"},
'bar': {'color': "darkblue"},'bgcolor': "white",'borderwidth': 2,'bordercolor': "gray",
'steps': [{'range': [0, target], 'color': 'red'}],
}
),
)
gauge.update_layout(font = {'color': "darkblue", 'family': "Arial"},
margin={"pad": 0, "t": 0,"r": 0,"l": 20,"b": 0})
return not is_open,text,gauge,yoy
return is_open,text,gauge,yoy
@app.callback(
Output('table2', 'figure'),
Output('text2', 'children'),Output('text3', 'children'),
Input('check1', 'value'), Input('drop1', 'value'), Input('drop2', 'value'),
Input('btn-nclicks-1', 'n_clicks'),Input('btn-nclicks-2', 'n_clicks'),
Input('btn-nclicks-3', 'n_clicks'),Input('btn-nclicks-4', 'n_clicks'),
Input('btn-nclicks-5', 'n_clicks')
)
def page2(check,date1,date2,btn1,btn2,btn3,btn4,btn5):
cur = 'USD';
if "btn-nclicks-1" == ctx.triggered_id:
cur = 'AUD'
elif "btn-nclicks-2" == ctx.triggered_id:
cur = 'CAD'
elif "btn-nclicks-3" == ctx.triggered_id:
cur = 'EUR'
elif "btn-nclicks-4" == ctx.triggered_id:
cur = 'GBP'
elif "btn-nclicks-5" == ctx.triggered_id:
cur = 'USD'
df['Total Sales Amount'] = df['OrderQuantity']*df['UnitPrice']*df[cur]/EUR_to_USD
Date1 = datetime.strptime(date1,'%Y-%m-%d')
Date2 = datetime.strptime(date2,'%Y-%m-%d')
pd.options.mode.chained_assignment = None
df[date] = pd.to_datetime(df[date]);
if check == None or check == []:
if Date1 < Date2:
dff = df[df[date] >= Date1]
dff = dff[dff[date] <= Date2]
else: # MAKING REVERSABLE
dff = df[df[date] >= Date2]
dff = dff[dff[date] <= Date1]
else:
dff = df.copy()
Date1 = df[date].iat[0];
Date2= df[date].iat[-1];
d1 = Date1.date(); d2 = Date2.date();
df_T = table2_fix(dff,cur);
tot_items = df_T['Items Sold'].sum()
tot_sales = df_T['Total Price'].sum()
table2 = go.Figure(data=[go.Table(
columnwidth = [2,2,1,1],
header=dict(values=(['Product Name','Description','Items Sold','Total Price']),
fill_color='#305D91',
font=dict(color='white', size=14),
align='left'
),
cells=dict(values=[df_T['Product Name'],df_T['Description'],df_T['Items Sold'],df_T['Total Price']],
fill_color='#E0EEEF', font=dict(color='black', size=14),
height=30, align='left'),
)
])
table2.update_layout(width=900, height=650,margin={"pad": 0, "t": 0,"r": 0,"l": 50,"b": 0})
return table2,'Sales over %s to %s in %s' %(Date1.date(), Date2.date(), cur),"Total.....................................................................................%d............ %1.0f" %(tot_items,tot_sales)
@app.callback(
Output('time-series', 'figure'),
Input('time-drop', 'value'),
Input('total-show', 'value'),
Input('slider', 'value')
)
def timeplot(n, showsum,slide_value):
#print(df)
if n == "All":
n = 129
print(n)
dft = time_series(df,n)
data = dft.copy()
freq = data.groupby(['date','Product Name'])['OrderQuantity'].sum().reset_index();
data['OrderQuantity'] = data['OrderQuantity'].astype(float); print(data)
bunch = data.groupby(['date'])['OrderQuantity'].sum().reset_index(); print(bunch)
slide_value = int(10**slide_value) # FOR LOG SCALE
avg = bunch['OrderQuantity'].rolling(window=slide_value).mean()
ts = px.line(freq, x="date", y="OrderQuantity", color='Product Name')
if showsum == "Yes":
ts.add_trace(go.Scatter(x=bunch.date, y=avg, showlegend=False,line=dict(width=2,color="black")))
ts.update_xaxes(showgrid=False, linecolor = "black", linewidth = 2,mirror = True,title=" ")
ts.update_yaxes(showgrid=False, linecolor = "black", linewidth = 2,mirror = True, title="Number of Items Sold")
ts.update_layout({'plot_bgcolor': 'rgba(0, 0, 0, 0)', 'paper_bgcolor': 'rgba(0, 0, 0, 0)'},width=900,
margin={'l': 40, 'b': 40, 't': 20, 'r': 20}, font=dict(size=14),
hovermode='closest')
return ts
if __name__ == '__main__':
#app.run() # pythonanywhere
app.run_server(debug=True) # http://Stevies-Air.staff.vuw.ac.nz:8050/ VUW
#app.run_server(host = '172.20.10.3',debug=True) # http://172.20.10.3:8050/ PHONE
#app.run_server(host = '192.168.178.55',debug=True) # http://Stevies-Air.fritz.box:8050/ HOME