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Plotly's Figure Friday Challenge 20024 Week 52: Public SaaS Company explorer
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# Plotly's Figure Friday challenge. See more info here: https://community.plotly.com/t/figure-friday-2024-week-52/89593 | |
import pandas as pd | |
from dash import Dash, dcc, Input, Output, State, callback, _dash_renderer, ctx | |
import dash_mantine_components as dmc | |
import dash_ag_grid as dag | |
import plotly.express as px | |
_dash_renderer._set_react_version("18.2.0") | |
dmc.add_figure_templates(default="mantine_dark") | |
app = Dash(external_stylesheets=dmc.styles.ALL) | |
about = dcc.Markdown(""" | |
This app was last updated in December 2024 and uses data from [PublicSaaSCompanies.com](https://publicsaascompanies.com/), a free database of 170+ SaaS businesses listed on the NYSE and NASDAQ. For the latest data, visit their website. | |
About "Rule of 40%": | |
- Rule of 40 is a convenient way to determine if a SaaS company is balancing the growth rate and the cost of achieving that growth rate. Historically, companies with a Rule of 40 equal to or greater than 40% will experience high enterprise value multiples to revenue. | |
Created for Plotly's **Figure Friday Challenge**, this app showcases interactive data visualizations of SaaS companies. Explore the dataset and join the discussion on the [Plotly Community Forum](https://community.plotly.com/t/figure-friday-2024-week-52/89593). | |
Built with **Dash Mantine Components** and **Dash AG Grid**, this Dash app is written in just ~200 lines of Python code. View the source on [GitHub](https://gist.github.com/AnnMarieW/6934d9fa27f9dc65b74c7e77b4fd0b8a) | |
""", style={"width": 450}) | |
df = pd.read_csv('https://raw.githubusercontent.com/plotly/Figure-Friday/main/2024/week-52/SaaS-businesses-NYSE-NASDAQ.csv') | |
df1 = df.copy() # use the copy for cleaned data | |
# Function to clean a single value | |
def clean_value(value): | |
if isinstance(value, str): | |
value = value.replace('$', '').replace('%', '').replace(',', '') | |
return pd.to_numeric(value, errors='coerce') | |
# Remove $ and % formating from numeric columns so sort and filters work correctly in the grid | |
for column in df.columns: | |
if df1[column].apply(lambda x: isinstance(x, str) and (x.startswith('$') or x.endswith('%'))).any(): | |
df1[column] = df1[column].apply(clean_value) | |
# add rule of 40 https://www.saasmetricsboard.com/rule-of-40 | |
df1["Rule of 40%"] = (df1["YoY Growth%"] + df1["EBITDA Margin"]).round(2) | |
df["Rule of 40%"] = df1["Rule of 40%"].apply(lambda x: f"{x:.2f}%") | |
graph_columns = ['Company', 'Market Cap', 'Annualized Revenue', 'YoY Growth%', 'Revenue Multiple', | |
'Annualized EBITDA', 'YoY Change in EBITDA%', 'EBITDA Margin', 'Rule of 40%', 'Annualized Net Income', | |
'YoY Change in Net Income%', 'Net Income Margin', 'Cash and Short Term Investments', | |
'YoY Change in Cash and Short Term Investments%', 'Employee Count (estimate)', | |
'Annual Revenue per Employee (estimate)', 'Stock Price'] | |
ag_grid = dag.AgGrid( | |
id="grid", | |
rowData=df1.to_dict("records"), | |
columnDefs=[{"field": "Company", "pinned": True}, {"field": "Last Quarter Filed"}] + | |
[{"field": i, 'type': 'rightAligned'} for i in graph_columns if i != "Company"], | |
columnSize="autoSize", | |
defaultColDef={"filter": True}, | |
dashGridOptions={"animateRows": False, "rowSelection":'single'}, | |
className="ag-theme-alpine-dark" | |
) | |
control_panel = dmc.Card([ | |
dmc.Select( | |
label="Select Y Axis", | |
data=graph_columns, | |
value="Market Cap", | |
id="y" | |
), | |
dmc.Select( | |
label="Select X Axis", | |
data=graph_columns, | |
value="Company", | |
id="x", | |
mt="lg" | |
), | |
dmc.Text("Click column header to sort", mt="md", size="sm") | |
], w=160) | |
header = dmc.Group([ | |
dmc.Title("Public SaaS Explorer", c="blue"), | |
dmc.HoverCard( | |
shadow="lg", | |
children=[ | |
dmc.HoverCardTarget(dmc.Button("About",variant="outline")), | |
dmc.HoverCardDropdown(about), | |
], | |
) | |
], justify="space-between") | |
layout = dmc.Stack([ | |
header, | |
ag_grid, | |
dmc.Group([control_panel, dmc.Card(dcc.Graph(id="graph" ), mt=0, withBorder=True, style={"flex":1})]), | |
dmc.Box(id="details"), | |
], p="lg") | |
app.layout = dmc.MantineProvider(layout, forceColorScheme="dark") | |
@callback( | |
Output("graph", "figure"), | |
Input("grid", "virtualRowData"), | |
Input("x", "value"), | |
Input("y", "value"), | |
State("grid", "columnState") | |
) | |
def update_figure(data, x, y, columnState): | |
if not data: | |
return {} | |
dff = pd.DataFrame(data) | |
sorted_by = next((c["colId"] for c in columnState if c.get("sort")), "Company") if columnState else "Company" | |
title = f"{y} by {x} (Sorted by: {sorted_by})" if x == "Company" else f"{y} vs {x}" | |
return px.scatter(dff, x=x, y=y, title=title, hover_data=[y, x, sorted_by, "Rule of 40%"], hover_name="Company") | |
@callback( | |
Output("grid", "columnDefs"), | |
Input("x", "value"), | |
Input("y", "value"), | |
State("grid", "columnDefs") | |
) | |
def update_grid_style(x,y, columnDefs): | |
for c in columnDefs: | |
if c["field"] in [x,y]: | |
c["cellStyle"] = {'background-color': 'var(--ag-selected-row-background-color)'} | |
else: | |
c["cellStyle"] = {'background-color': 'unset'} | |
return columnDefs | |
def StatsGrid(data): # creates the stats cards | |
stats = [] | |
for stat in data: | |
stats.append( | |
dmc.Paper( | |
[ | |
dmc.Group( | |
[dmc.Text(stat['title'], c="dimmed", tt="uppercase", fw=700)], | |
justify="space-between" | |
), | |
dmc.Group([dmc.Text(stat['value'], size="lg", fw=700)], gap="xs"), | |
dmc.Group( | |
[ | |
dmc.Text(f"{stat['diff']}%", size="xs"), | |
dmc.Text("YoY change", size="xs", c="dimmed") | |
], | |
c="teal" if stat['diff'] > 0 else "red", | |
fw=500, gap=1, | |
) | |
], | |
withBorder=True, | |
p="xs" | |
) | |
) | |
return dmc.SimpleGrid(children=stats, cols={"base": 1, "xs": 2, "md": 4}) | |
@callback( | |
Output("details", "children"), | |
Output("grid", "selectedRows"), | |
Input("graph", "clickData"), | |
Input("grid", "selectedRows"), | |
prevent_initial_call=True, | |
) | |
def update_detail_cards(clickData, selectedRows): | |
if ctx.triggered_id == "graph": | |
if not clickData: | |
return "", selectedRows | |
company=clickData["points"][0]["hovertext"] | |
selectedRows= df1[df1["Company"] == company].to_dict("records") | |
if ctx.triggered_id == "grid": | |
if not selectedRows: | |
return "", selectedRows | |
company=selectedRows[0]["Company"] | |
dff = df[df["Company"] == company].iloc[0] #formated | |
dff1= df1[df1["Company"] == company].iloc[0] #numeric | |
data = [ | |
{'title': 'Revenue', 'value': dff["Annualized Revenue"], 'diff': dff1["YoY Growth%"]}, | |
{'title': 'EBITDA', 'value': dff["Annualized EBITDA"], 'diff': dff1["YoY Change in EBITDA%"]}, | |
{'title': 'Net Income', 'value': dff["Annualized Net Income"], 'diff': dff1["YoY Change in Net Income%"]}, | |
{'title': 'Cash', 'value': dff["Cash and Short Term Investments"], 'diff': dff1["YoY Change in Cash and Short Term Investments%"]}, | |
] | |
selected_company_stats = dmc.Box([ | |
dmc.Title(dff["Company"], order=3), | |
dmc.Text(f"Ticker: {dff['Ticker']}"), | |
dmc.Text(f"Products: {dff['Product Description']}"), | |
dmc.Text(f"Headquarters: {dff['Headquarters']}"), | |
dmc.Text(f"Founded in {dff['Year Founded']}, IPO in {dff['IPO Year']}"), | |
dmc.Anchor("Website", href=dff['Company Website']), | |
dmc.Anchor("2023 10-K Filing", href=dff['2023 10-K Filing'], pl="lg"), | |
]) | |
return dmc.Card([ | |
dmc.Group([ | |
dmc.Title(f"Selected company: {dff['Company']}", order=3), | |
dmc.HoverCard([ | |
dmc.HoverCardTarget(dmc.ActionIcon("?")), | |
dmc.HoverCardDropdown(selected_company_stats), | |
]) | |
], justify="center"), | |
StatsGrid(data) | |
], withBorder=True), selectedRows | |
if __name__ == "__main__": | |
app.run(debug=True) | |
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dash | |
dash-mantine-components==0.15.1 | |
dash-ag-grid==31.3.0 | |
pandas |
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