File size: 2,564 Bytes
9249c61 bbfcb06 9249c61 57150e6 605f99d 769fd81 2fa778e 769fd81 9249c61 605f99d e605026 605f99d 2bb938a 695c876 471fe17 4dfd68f d935d66 4dfd68f 2bb938a 471fe17 ae1aa6b 9249c61 |
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 |
import gradio as gr
import pandas as pd
import plotly.express as px
data = pd.read_csv('data/env_disclosure_data.csv')
data = data.drop('Unnamed: 0', axis=1)
data['Environmental Transparency'] = data['Environmental Transparency'].fillna('None')
data.Organization = data.Organization.replace('University of Montreal / Université de Montréal', 'University of Montreal')
data.Organization = data.Organization.replace('University of Washington,Allen Institute for AI', 'Allen Institute for AI')
data.Organization = data.Organization.replace('Allen Institute for AI,University of Washington', 'Allen Institute for AI')
data.Organization = data.Organization.replace(['Google', 'DeepMind', 'Google DeepMind','Google Brain','Google Research'], 'Alphabet')
data.Organization = data.Organization.replace(['Meta AI','Facebook AI Research','Facebook AI', 'Facebook'], 'Meta')
data.Organization = data.Organization.replace(['Microsoft','Microsoft Research'], 'Microsoft')
organizations=['Alphabet', 'OpenAI', 'Alibaba', 'Stanford University', 'University of Toronto','University of Toronto', 'Microsoft', 'NVIDIA',
'Carnegie Mellon University (CMU)', 'University of Oxford','University of California (UC) Berkeley','Baidu','Anthropic',
'Salesforce Research', 'Amazon', 'University of Montreal', 'Apple', 'Mistral AI', 'DeepSeek', 'Allen Institute for AI']
def generate_figure(org_name):
org_data = data[data['Organization'] == org_name]
fig = px.histogram(org_data, x="Year", color="Environmental Transparency")
fig.update_layout(xaxis_type='category')
return fig
with gr.Blocks() as demo:
gr.Markdown("# Environmental Transparency Explorer Tool")
gr.Markdown("## Explore the data from 'Misinformation by Omission: The Need for More Environmental Transparency in AI'")
with gr.Row():
with gr.Column(scale=1):
org_choice= gr.Dropdown(organizations, value="Alphabet", label="Organizations", info="Pick an organization to explore their environmental disclosures", interactive=True)
with gr.Column(scale=4):
gr.Markdown("### Data by Organization")
fig = generate_figure(org_choice)
plt = gr.Plot(fig)
with gr.Row():
with gr.Column():
gr.Markdown("### All Data")
fig2 = px.histogram(data, x="Year", color="Environmental Transparency")
fig2.update_layout(xaxis_type='category')
plt2 = gr.Plot(fig2)
org_choice.select(generate_figure, inputs=[org_choice], outputs=[plt])
demo.launch()
|