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UID:pretalx-python-asia-2026-DVUQLM@pretalx.com
DTSTART;TZID=PST:20260322T131500
DTEND;TZID=PST:20260322T151500
DESCRIPTION:The Philippines continues to work toward the Sustainable Develo
 pment Goals (SDGs)\, but its progress becomes clearer—and more actionabl
 e—when viewed alongside other countries facing similar social\, economic
 \, and environmental challenges. Many SDG issues in the Philippines mirror
  broader regional struggles\, yet the lack of accessible\, comparable data
  makes it difficult for citizens and decision-makers to understand where t
 he country is ahead\, where it is falling behind\, and what lessons can be
  learned from peers.\n\nThis 2-hour\, hands-on workshop uses Python to com
 pare the Philippines’ SDG performance with that of other nations in Sout
 heast Asia and beyond. Participants will use open global datasets to clean
 \, explore\, and visualize cross-country indicators—revealing patterns\,
  inequalities\, and standout practices. By grounding the analysis in inter
 national comparison\, the workshop helps participants understand not only 
 how the Philippines is doing\, but why some countries progress faster and 
 what strategies may be adapted.\n\nThis workshop is not about politics —
  it’s about essential skills for meaningful development analysis:\n✔ D
 ata literacy for interpreting global SDG indicators\n✔ Critical thinking
  through country-to-country benchmarking\n✔ Responsible analytics that a
 void misleading comparisons\n✔ Transparency through reproducible and ope
 n Python workflows\n\nBy the end of the session\, participants will have b
 uilt a concise\, reusable “SDG Comparison Notebook” that compares Phil
 ippine performance to regional and global peers. The goal is to demonstrat
 e how Python can illuminate where the Philippines stands in the world—an
 d how data can guide smarter\, more accountable pathways toward achieving 
 the SDGs.
DTSTAMP:20260501T070419Z
LOCATION:Yuchengco Hall 5th Flr. Y509 (Workshop Room 3)
SUMMARY:Python for Good: Revealing the Philippines Through Data - Michel On
 asis S. Ogbinar
URL:https://pretalx.com/python-asia-2026/talk/DVUQLM/
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