fix(data): re-derive early_january_2023_weather from weather (real temp/dewp/humid/pressure)#7
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The R `moderndive::early_january_2023_weather` ships with temp, dewp, humid, and pressure entirely NA (mean temp is NaN), which carried through to the bundled Parquet as all-null string columns. Derive the table from `weather` instead (Newark / EWR, first 15 days of January 2023) so those four columns are real, correctly-typed floats. Same 360 rows. build_data.py now produces it from the freshly built weather frame rather than reading a separate CSV, and a regression test asserts the measurement columns are numeric and non-null. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017CTL1QSTg1DmDUpqYuPEog
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Problem
The R
moderndive::early_january_2023_weatherdataset ships withtemp,dewp,humid, andpressureentirelyNA(mean temp isNaN). That upstream bug carried through to the bundled Parquet here as all-null string columns — so the four core measurement columns were unusable.Fix
Derive
early_january_2023_weatherfrom theweatherdataset (Newark/EWR, first 15 days of January 2023) instead of reading the broken standalone source. Those columns come back as real, correctly-typed floats (360 rows, unchanged).tools/build_data.pynow builds it from the freshly readweatherframe.early_january_2023_weather.parquet.temp/dewp/humid/pressureare numeric and non-null.Verified against R (which is itself NaN here) and the
weathersource rows; values are consistent and the existing UTCtime_hourconvention is preserved.🤖 Generated with Claude Code