Merge pull request #3 from jacquessham/development

v0.0.3

README.md

@@ -8,7 +8,12 @@ The first step is to replicate the sankey chart found in this <a href="https://w
 The plan is to develop a dashboard displays the financials of selected publicly traded companies, the details can be found in the [The Plan](plan) folder.
 
 ## Dashboard
-The Dashboard is under development, but you may check out the progress in the [Dashboard](dashboard) folder.
+The Dashboard is under development and only have Google's (GOOGL) selected period of data. You may check out the progress in the [Dashboard](dashboard) folder. More details will be available soon.
+
+<br>
+<img src=gallery/income_v002.png>
+
+Screenshot of latest development.
 
 ## Reference
 <a href="https://www.reddit.com/r/dataisbeautiful/comments/10ur1ya/oc_how_google_makes_money_its_2022_income/">Google Financial Report in Sankey Chart</a>

dashboard/balancesheet.py

@@ -1,5 +1,5 @@
 import pandas as pd
-import balancesheet_googl_poc as example
+import data.googl.poc_charts.balancesheet_googl_poc as example  # For poc purpose, delete later
 from data.googl.balance_sheet_googl import *
 
 

dashboard/cashflow_statement.py

@@ -1,5 +1,5 @@
 import pandas as pd
-import cashflow_googl_poc as example
+import data.googl.poc_charts.cashflow_googl_poc as example  # For poc purpose, delete later
 from data.googl.cashflow_googl import *
 
 

dashboard/dashboard.py

@@ -29,8 +29,10 @@
     [Input('dashboard-tabs','value'), Input('company-choices','value')])
 def display_period_dropdown(tab, company):
     if tab in companies_data[company]:
-        return companies_data[company][tab]['periods'], \
-            companies_data[company][tab]['periods'][0]
+        # Sort Periods here
+        periods_avail = companies_data[company][tab]['periods']
+        periods_avail = periods_dropdown(periods_avail)
+        return periods_avail, periods_avail[0]
     # If information is not available
     return [], None
 
@@ -44,38 +46,42 @@ def display_income_statement(tab, company, period):
     if tab == tab_labels[0]:
         curr_data = companies_data[company][tab]['data']
         curr_data = curr_data[curr_data['Period']==period]
-        return [html.Div(
+        return [html.Div([
                     # P/H1 here if needed
+                    # html.H2(f'{company}\'s Income Statement during {period}'),
                     # Plotly Chart
                     dcc.Graph(
                         figure=income_statement_figure(
                             company, curr_data
                             ),
                         style={'height':graph_height}
-                    ))]
+                    )] # End Div
+                )] # End Outer array
     # Balance Sheet
     if tab == tab_labels[1]:
         curr_data = companies_data[company][tab]['data']
         curr_data = curr_data[curr_data['Period']==period]
-        return [html.Div(
+        return [html.Div([
                     # P/H1 here if needed
+                    # html.H2(f'{company}\'s Income Statement during {period}'),
                     # Plotly Chart
                     dcc.Graph(
                         figure=balancesheet_figure(company, curr_data),
                         style={'height':graph_height}
 
-                    ))]
+                    )])]
     # Cashflow Statement
     curr_data = companies_data[company][tab]['data']
     curr_data = curr_data[curr_data['Period']==period]
-    return [html.Div(
+    return [html.Div([
                 # P/H1 here if needed
+                # html.H2(f'{company}\'s Income Statement during {period}'),
                 # Plotly Chart
                 dcc.Graph(
                     figure=cashflow_statement_figure(company, curr_data),
                         style={'height':graph_height}
 
-                ))]
+                )])]
 
 # Initiate dashboard
 if __name__ == '__main__':

dashboard/dashboard_structure.py

@@ -1,6 +1,33 @@
 from dash import dcc, html
 
 
+# Sort periods in Year, then quarter in desc order
+## The format must be FYXX or XXQX
+def periods_dropdown(periods):
+	periods_temp = []
+	for period in periods:
+		# If this is a Annual report (10-K)
+		if 'FY' in period:
+			year = int(period[2:])
+			quarter = 5 # To rank after all 10-Qs
+		# If this is a Quarterly report (10-Q)
+		elif 'Q' in period:
+			year = int(period[:2])
+			quarter = int(period[3])
+		# If this is an Intreim report (Semiannual)
+		elif 'H' in period:
+			year = int(period[:2])
+			quarter = int(period[3])
+		else:
+			continue
+
+		# (labels, year in int, quarter in int)
+		periods_temp.append((period, year, quarter))
+	periods_temp = sorted(periods_temp, key=lambda x: (-x[1],-x[2]))
+
+	# Only returning the labels
+	return [t[0] for t in periods_temp]
+
 def create_tabs(tab_labels):
 	tabs = []
 	for tab_label in tab_labels:

dashboard/data/Readme.md

@@ -1,5 +1,8 @@
 # Data
-This is the Data folder where the dashboard administrator will be preparing the required data to run the dashoard. This directory hosts a variety of publicly traded companies, while each folder represents a company and contains the necessarily dataset and scripts. More instructions will be coming soon...
+This is the Data folder where the dashboard administrator will be preparing the required data to run the dashoard. This directory hosts a variety of publicly traded companies, while each folder represents a company and contains the necessarily dataset and scripts. The sample dataset and template files are available in the <i>dataset</i> folder in each company folder. More instructions will be coming soon...
 
 ## Google (GOOGL)
-The Google folder contains the supporting scripts to create sankey charts on the dashboard, as well as the dataset templates and sample datasets. More instruction in the [Google](googl) folder.
+The Google folder contains the supporting scripts to create sankey charts on the dashboard, as well as the dataset templates and sample datasets. More instruction on data parparation in the [Google](googl) folder.
+
+## Template
+If you would like to add more company options, you may create more plug-ins. Here are the instructions and guidelines in the [Template](template) folder. Details are coming soon...

dashboard/data/googl/data_balsht_googl.py

@@ -80,6 +80,10 @@ def get_data(df):
 
 	## Long-term Asset
 	for i in range(5,12):
+		## Node 9 (Intangile Assets, net) stopped reporting in FY23 onward
+		if i == 9 and i not in df['Node_num'].tolist():
+			## Skip this node if the entry is missing in the CSV file
+			continue
 		curr_value = df[df['Node_num']==i]['Value'].values[0]
 		link_temp = get_link_direction(i, 13, curr_value,'asset')
 		## Add links from current node to total asset

dashboard/data/googl/data_incsmt_googl.py

@@ -36,7 +36,8 @@ def get_data(df):
 	# Hardcode the colors
 	nodes_colors = ['gray']*10 + ['red'] + ['green'] + ['red']*4 
 	# Map each KPI with the preassigned index number in nodes_label
-	df_temp = {'Items': [k for k in nodes.keys()], 'Node_num':[nodes[k] for k in nodes.keys()]}
+	df_temp = {'Items': [k for k in nodes.keys()], 
+		'Node_num':[nodes[k] for k in nodes.keys()]}
 	df = pd.merge(df, pd.DataFrame(df_temp), on='Items', how='inner')
 
 	# Add with itemized revenue
@@ -55,9 +56,11 @@ def get_data(df):
 	links = add_node_to_link(links, 3, 8, curr_value, 'lightgray')
 
 	## Revenue less Other Revenue
-	links = add_node_to_link(links, 8, 9, srv_value, 'lightgray') # Service Revenue
+	### Service Revenue
+	links = add_node_to_link(links, 8, 9, srv_value, 'lightgray')
+	### Google Clouds
 	links = add_node_to_link(links, 4, 9,
-		df[df['Node_num']==4]['Value'].values[0],'lightgray') # Google Clouds
+		df[df['Node_num']==4]['Value'].values[0],'lightgray')
 
 	## Other Revenue - Hedging Gain and Other Bets
 	for i in range(5,7):
@@ -72,14 +75,14 @@ def get_data(df):
 	## Income from Operation
 	inc_op = 0
 	### Other income, net
-	curr_value = -1* df[df['Node_num']==16]['Value'].values[0] 
-	if curr_value >= 0:
-		links = add_node_to_link(links, 11, 16, curr_value, 'pink')
+	curr_value = df[df['Node_num']==16]['Value'].values[0] 
+	if curr_value < 0:
+		links = add_node_to_link(links, 11, 16, -1*curr_value, 'pink')
 		nodes_colors.append('red')
 	else:
-		links = add_node_to_link(links, 16, 11, curr_value, 'lightgreen')
-		nodes_colors.append('green')
-	inc_op += curr_value
+		links = add_node_to_link(links, 16, 11, curr_value, 'lightgray')
+		nodes_colors.append('gray')
+	inc_op += -1*curr_value
 
 	### EBIT
 	ebit = 0

dashboard/data/googl/dataset/googl_balancesheet_example.csv

@@ -0,0 +1,69 @@
+"Items","Period","Value"
+"Cash and Cash Equivalents","FY22",21879
+"Marketable Securities","FY22",91883
+"Accounts Receivale","FY22",40258
+"Inventory","FY22",2670
+"Other Current Assets","FY22",8105
+"Non-marketable Securities","FY22",30492
+"Deferred Income Taxes","FY22",5261
+"Property and Equipment, net","FY22",112668
+"Operating Lease Assets","FY22",14381
+"Intangible Assets, net","FY22",2084
+"Goodwill","FY22",28960
+"Other Non-current Assets","FY22",6623
+"Account Payables","FY22",5128
+"Accrued Compensation and Benefits","FY22",14028
+"Accrued Expenses and Other Current Liabilities","FY22",37866
+"Accrued Revenue Share","FY22",8370
+"Deferred Revenue","FY22",3908
+"Long-term Debt","FY22",14701
+"Deferred Revenue, non-current","FY22",599
+"Operating Lease Liabilities","FY22",12501
+"Other Long-term Liabilities","FY22",12019
+"Retained Earnings less Accumulated Loss","FY22",195563
+"Common Stocks","FY22",60581
+"Cash and Cash Equivalents","FY23",24048
+"Marketable Securities","FY23",86868
+"Accounts Receivale","FY23",47964
+"Inventory","FY23",0
+"Other Current Assets","FY23",12650
+"Non-marketable Securities","FY23",31008
+"Deferred Income Taxes","FY23",12169
+"Property and Equipment, net","FY23",134345
+"Operating Lease Assets","FY23",14091
+"Goodwill","FY23",29198
+"Other Non-current Assets","FY23",10051
+"Account Payables","FY23",7493
+"Accrued Compensation and Benefits","FY23",15140
+"Accrued Expenses and Other Current Liabilities","FY23",46168
+"Accrued Revenue Share","FY23",8876
+"Deferred Revenue","FY23",4137
+"Long-term Debt","FY23",13253
+"Deferred Revenue, non-current","FY23",911
+"Operating Lease Liabilities","FY23",12460
+"Other Long-term Liabilities","FY23",10575
+"Retained Earnings less Accumulated Loss","FY23",211247
+"Common Stocks","FY23",72132
+"Cash and Cash Equivalents","23Q3",30702
+"Marketable Securities","23Q3",89233
+"Accounts Receivale","23Q3",41020
+"Inventory","23Q3",2957
+"Other Current Assets","23Q3",12398
+"Non-marketable Securities","23Q3",30907
+"Deferred Income Taxes","23Q3",10983
+"Property and Equipment, net","23Q3",125705
+"Operating Lease Assets","23Q3",14199
+"Intangible Assets, net","23Q3",1833
+"Goodwill","23Q3",29146
+"Other Non-current Assets","23Q3",7628
+"Account Payables","23Q3",5803
+"Accrued Compensation and Benefits","23Q3",12562
+"Accrued Expenses and Other Current Liabilities","23Q3",55602
+"Accrued Revenue Share","23Q3",8025
+"Deferred Revenue","23Q3",4303
+"Long-term Debt","23Q3",13781
+"Deferred Revenue, non-current","23Q3",884
+"Operating Lease Liabilities","23Q3",8038
+"Other Long-term Liabilities","23Q3",1433
+"Retained Earnings less Accumulated Loss","23Q3",205647
+"Common Stocks","23Q3",67555

dashboard/data/googl/dataset/googl_cashflow_example.csv

@@ -0,0 +1,49 @@
+"Items","Period","Value"
+"Net Income","FY22",59972
+"Depreciation and Impairment of Property and Equipment","FY22",15287
+"Amortization and Impairment of Intangible Assets","FY22",641
+"Stock-based Compensation Expense","FY22",19362
+"Deferred Income Taxes","FY22",-8061
+"(Gain) Loss on Debt and Equity Securities, net","FY22",5519
+"Other Adjustment","FY22",1030
+"Change in Assets and Liabilities, net of effects of Acquisitions","FY22",-2235
+"Capital Expenditure","FY22",-31485
+"Securities Investment","FY22",16567
+"Acquisitions","FY22",-6969
+"Other Investment Activities","FY22",1589
+"Repurchase of Stock and Stock-based Award Activities","FY22",-68596
+"Debt-related Activities","FY22",-1196
+"Effect of Exchange Rate on Cash","FY22",-506
+"Net Increase in Cash","FY22",934
+"Net Income","23Q3",53108
+"Depreciation and Impairment of Property and Equipment","23Q3",10010
+"Amortization and Impairment of Intangible Assets","23Q3",373
+"Stock-based Compensation Expense","23Q3",16801
+"Deferred Income Taxes","23Q3",-6093
+"(Gain) Loss on Debt and Equity Securities, net","23Q3",1294
+"Other Adjustment","23Q3",912
+"Change in Assets and Liabilities, net of effects of Acquisitions","23Q3",6426
+"Capital Expenditure","23Q3",-21232
+"Securities Investment","23Q3",1787
+"Acquisitions","23Q3",-466
+"Other Investment Activities","23Q3",-985
+"Repurchase of Stock and Stock-based Award Activities","23Q3",-52470
+"Debt-related Activities","23Q3",-315
+"Effect of Exchange Rate on Cash","23Q3",-327
+"Net Increase in Cash","23Q3",8823
+"Net Income","FY23",73795
+"Depreciation and Impairment of Property and Equipment","FY23",11946
+"Amortization and Impairment of Intangible Assets","FY23",0
+"Stock-based Compensation Expense","FY23",22460
+"Deferred Income Taxes","FY23",-7763
+"(Gain) Loss on Debt and Equity Securities, net","FY23",823
+"Other Adjustment","FY23",4330
+"Change in Assets and Liabilities, net of effects of Acquisitions","FY23",-3885
+"Capital Expenditure","FY23",-32251
+"Securities Investment","FY23",5787
+"Acquisitions","FY23",-495
+"Other Investment Activities","FY23",-1051
+"Repurchase of Stock and Stock-based Award Activities","FY23",-71341
+"Debt-related Activities","FY23",-752
+"Effect of Exchange Rate on Cash","FY23",-421
+"Net Increase in Cash","FY23",2169

dashboard/data/googl/googl_cashflow_template.csv → dashboard/data/googl/dataset/googl_cashflow_template.csv

@@ -1,9 +1,9 @@
 "Items","Period","Value"
 "Net Income","Year 1",0
-"Depreciation and Impairment of Property and Equipment","Year 1"0
+"Depreciation and Impairment of Property and Equipment","Year 1",0
 "Amortization and Impairment of Intangible Assets","Year 1",0
 "Stock-based Compensation Expense","Year 1",0
-"Deferred Income Tax","Year 1",0
+"Deferred Income Taxes","Year 1",0
 "(Gain) Loss on Debt and Equity Securities, net","Year 1",0
 "Other Adjustment","Year 1",0
 "Change in Assets and Liabilities, net of effects of Acquisitions","Year 1",0
@@ -13,5 +13,5 @@
 "Other Investment Activities","Year 1",0
 "Repurchase of Stock and Stock-based Award Activities","Year 1",0
 "Debt-related Activities","Year 1",0
-"Effect of Exchange Rate on Cash",,"Year 1",0
+"Effect of Exchange Rate on Cash","Year 1",0
 "Net Increase in Cash","Year 1",0

dashboard/data/googl/dataset/googl_income_example.csv

@@ -0,0 +1,46 @@
+"Items","Period","Value"
+"Cost of Revenue","FY22",126203
+"Research & Development","FY22",39500
+"Sales & Marketing","FY22",26567
+"General & Administrative","FY22",15724
+"EBIT","FY22",71328
+"Income Tax","FY22",11356
+"Other Income (Expense), net","FY22",-3514
+"Net Income","FY22",59972
+"Google Search & Other","FY22",162450
+"Google Network","FY22",32780
+"YouTube Ads","FY22",29243
+"Other Platforms","FY22",29055
+"Google Clouds","FY22",26280
+"Hedging Gains","FY22",1960
+"Other Bets","FY22",1068
+"Cost of Revenue","FY21",110939
+"Research & Development","FY21",31562
+"Sales & Marketing","FY21",22912
+"General & Administrative","FY21",13510
+"EBIT","FY21",90734
+"Income Tax","FY21",14701
+"Other Income (Expense), net","FY21",12020
+"Net Income","FY21",76033
+"Google Search & Other","FY21",148951
+"Google Network","FY21",31701
+"YouTube Ads","FY21",28845
+"Other Platforms","FY21",28032
+"Google Clouds","FY21",19206
+"Hedging Gains","FY21",753
+"Other Bets","FY21",149
+"Cost of Revenue","23Q3",33229
+"Research & Development","23Q3",11258
+"Sales & Marketing","23Q3",6884
+"General & Administrative","23Q3",3979
+"EBIT","23Q3",21343
+"Income Tax","23Q3",1508
+"Other Income (Expense), net","23Q3",0
+"Net Income","23Q3",19689
+"Google Search & Other","23Q3",44026
+"Google Network","23Q3",7669
+"YouTube Ads","23Q3",7952
+"Other Platforms","23Q3",8339
+"Google Clouds","23Q3",8411
+"Hedging Gains","23Q3",-1
+"Other Bets","23Q3",297