-
-
Notifications
You must be signed in to change notification settings - Fork 153
Expand file tree
/
Copy pathai-adoption.html
More file actions
170 lines (147 loc) · 7.15 KB
/
ai-adoption.html
File metadata and controls
170 lines (147 loc) · 7.15 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<title>AI Adoption Rolling Avg — Pyodide</title>
<style>
:root { color-scheme: light; }
html, body { height: 100%; }
body { margin: 0; background: #fff; color: #111; font-family: ui-sans-serif, system-ui, -apple-system, Segoe UI, Roboto, Inter, "Helvetica Neue", Arial; }
.wrap { max-width: 980px; margin: 0 auto; padding: 24px; }
header { display:flex; align-items:center; justify-content:space-between; gap:12px; margin-bottom:16px; }
h1 { font-size: clamp(18px, 2.4vw, 24px); margin: 0; font-weight: 650; letter-spacing: .2px; }
.controls { display:flex; gap: 8px; align-items:center; }
button, a.btn { appearance: none; border: 1px solid #ddd; background: #fff; color: #111; padding: 8px 12px; border-radius: 8px; font-weight: 600; cursor: pointer; text-decoration: none; }
button:disabled, .btn.disabled { color: #9aa0a6; border-color: #eee; background:#fafafa; cursor: default; pointer-events: none; }
.grid { display: grid; grid-template-columns: 1fr; gap: 16px; }
@media (min-width: 900px){ .grid { grid-template-columns: 340px 1fr; } }
.card { border: 1px solid #e5e7eb; border-radius: 10px; padding: 14px; background: #fff; }
pre.status { margin: 0; font-family: ui-monospace, SFMono-Regular, Menlo, Consolas, monospace; font-size: 13px; line-height: 1.45; color: #333; white-space: pre-wrap; }
.imgwrap { display:grid; place-items:center; min-height: 460px; background: #fff; border: 1px dashed #e5e7eb; border-radius: 10px; }
img { max-width: 100%; height: auto; display: block; }
footer { margin-top: 12px; font-size: 12px; color:#555; }
</style>
</head>
<body>
<div class="wrap">
<header>
<h1>AI adoption — 6‑survey rolling average</h1>
<div class="controls">
<button id="run" disabled>Run</button>
<a id="dl_png" class="btn disabled" href="#">Download PNG</a>
<a id="dl_svg" class="btn disabled" href="#">Download SVG</a>
</div>
</header>
<div class="grid">
<div class="card">
<pre id="status" class="status"></pre>
</div>
<div class="imgwrap card">
<img id="plot" alt="Chart will render here" />
</div>
</div>
<footer>Source: "Employment Size Class (Sep 2025)" — fetched via CORS from static.simonwillison.net</footer>
</div>
<script src="https://cdn.jsdelivr.net/pyodide/v0.26.2/full/pyodide.js"></script>
<script>
const runBtn = document.getElementById('run');
const statusEl = document.getElementById('status');
const pngA = document.getElementById('dl_png');
const svgA = document.getElementById('dl_svg');
function log(x){ statusEl.textContent += x + "\n"; }
function enableDownloadLinks(){ pngA.classList.remove('disabled'); svgA.classList.remove('disabled'); }
const PY = `\
import pandas as pd
import numpy as np
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from matplotlib.ticker import PercentFormatter
from js import document, encodeURIComponent
import io, base64
URL = 'https://static.simonwillison.net/static/cors-allow/2025/Employment-Size-Class-Sep-2025.xlsx'
# Fetch workbook bytes via pyfetch (binary-safe), then read both sheets
from pyodide.http import pyfetch
resp_fetch = await pyfetch(URL)
wb_bytes = await resp_fetch.bytes()
xf = pd.ExcelFile(io.BytesIO(wb_bytes), engine='openpyxl')
resp = xf.parse('Response Estimates')
dates = xf.parse('Collection and Reference Dates')
# Filter to current question + yes
is_current = resp['Question'].astype(str).str.strip().str.startswith('In the last two weeks')
ai_yes = resp[is_current & resp['Answer'].astype(str).str.strip().str.lower().eq('yes')].copy()
code_to_bucket = {
'A':'1-4','B':'5-9','C':'10-19','D':'20-49','E':'50-99','F':'100-249','G':'250 or more employees'
}
ai_yes['Bucket'] = ai_yes['Empsize'].map(code_to_bucket)
period_cols = [c for c in ai_yes.columns if str(c).isdigit() and len(str(c))==6]
long = ai_yes.melt(id_vars=['Bucket'], value_vars=period_cols, var_name='Smpdt', value_name='value')
dates['Smpdt'] = dates['Smpdt'].astype(str)
long['Smpdt'] = long['Smpdt'].astype(str)
merged = long.merge(dates[['Smpdt','Ref End']], on='Smpdt', how='left')
merged['date'] = pd.to_datetime(merged['Ref End'], errors='coerce')
merged['value'] = pd.to_numeric(long['value'].astype(str).str.replace('%','',regex=False).str.strip(), errors='coerce')
order = ['250 or more employees','100-249','50-99','20-49','10-19','5-9','1-4']
wide = merged.pivot_table(index='date', columns='Bucket', values='value', aggfunc='mean').sort_index()
wide = wide[[c for c in order if c in wide.columns]]
rolled = wide.rolling(window=6, min_periods=6).mean()
start, end = pd.Timestamp('2023-11-01'), pd.Timestamp('2025-08-31')
rolled_win = rolled.loc[(rolled.index >= start) & (rolled.index <= end)]
fig, ax = plt.subplots(figsize=(12, 6))
for col in order:
if col in rolled_win.columns:
ax.plot(rolled_win.index, rolled_win[col], label=col, linewidth=2)
ax.set_title('AI adoption (last two weeks) — 6‑survey rolling average', pad=12)
ax.yaxis.set_major_formatter(PercentFormatter(100))
ax.set_ylabel('%')
ax.set_xlabel('')
ax.grid(True, alpha=0.25, linestyle='--')
ax.legend(title=None, loc='upper left', ncol=2, frameon=False)
fig.tight_layout()
# PNG
buf_png = io.BytesIO()
fig.savefig(buf_png, format='png', dpi=200, bbox_inches='tight')
buf_png.seek(0)
img_b64 = base64.b64encode(buf_png.getvalue()).decode('ascii')
document.getElementById('plot').src = 'data:image/png;base64,' + img_b64
# SVG
svg_buf = io.StringIO()
fig.savefig(svg_buf, format='svg', bbox_inches='tight')
svg_text = svg_buf.getvalue()
# Expose download links
document.getElementById('dl_png').href = 'data:image/png;base64,' + img_b64
document.getElementById('dl_png').download = 'ai_adoption_rolling6_by_firm_size.png'
document.getElementById('dl_svg').href = 'data:image/svg+xml;charset=utf-8,' + encodeURIComponent(svg_text)
document.getElementById('dl_svg').download = 'ai_adoption_rolling6_by_firm_size.svg'
`;
let pyodide = null;
async function boot(){
log('Loading Python…');
pyodide = await loadPyodide({ indexURL: 'https://cdn.jsdelivr.net/pyodide/v0.26.2/full/' });
log('Fetching packages: numpy, pandas, matplotlib…');
await pyodide.loadPackage(['numpy','pandas','matplotlib','micropip']);
log('Installing openpyxl via micropip…');
await pyodide.runPythonAsync(`import micropip
await micropip.install("openpyxl")`);
log('Ready.');
runBtn.disabled = false;
await run(); // auto-run once
}
async function run(){
if (!pyodide) return;
pngA.classList.add('disabled'); svgA.classList.add('disabled');
try {
log('Running…');
await pyodide.runPythonAsync(PY);
log('Done.');
enableDownloadLinks();
} catch (e){
console.error(e); log('Error: ' + e);
}
}
runBtn.addEventListener('click', run);
boot();
</script>
</body>
</html>