from https://www.ssa.gov/oact/babynames/
Data at data/names-ss-1910-2022.csv.zip
http://jse.amstat.org/v19n3/decock.pdf
Data at ./data/ames-housing-dataset.zip
Weather data for those years at ../data/asos-ames-2007-2010.txt
https://insights.stackoverflow.com/survey/2019
License: ODbL
https://www.fueleconomy.gov/feg/download.shtml
From https://qrc.depaul.edu/Excel_File_Listing_Pages/Excellist.asp
From https://www.kaggle.com/rounakbanik/pokemon (CC0: Public Domain)
1980-2019
https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USC00420072/detail
Data at ../data/snow-alta-1990-2017.csv
../data/transaction_data.xlsx
Documentation - https://www1.ncdc.noaa.gov/pub/data/cdo/documentation/GHCND_documentation.pdf
- STATION_NAME (max 50 characters) is the (usually city/airport name). Optional output field.
- STATION - 17 characters) is the station identification code. Please see http://www1.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt
- NAME - name of the station
- LATITUDE
- LONGITUDE
- ELEVATION - meters
- DATE - YYYY-MM-DD
- DAPR - Number of days included in the multiday precipitation total (MDPR)
- DAPR_ATTRIBUTES
- DASF - Number of days included in the multiday snowfall total (MDSF)
- DASF_ATTRIBUTES
- MDPR - Multiday precipitation total (mm or inches as per user preference; use with DAPR and DWPR, if available)
- MDPR_ATTRIBUTES
- MDSF - Multiday snowfall total (mm or inches as per user preference)
- MDSF_ATTRIBUTES
- PRCP - Precipitation (mm or inches as per user preference, inches to hundredths on Daily Form pdf file)
- PRCP_ATTRIBUTES
- SNOW - Snowfall (mm or inches as per user preference, inches to tenths on Daily Form pdf file)
- SNOW_ATTRIBUTES
- SNWD - Snow depth (mm or inches as per user preference, inches on Daily Form pdf file)
- SNWD_ATTRIBUTES
- TMAX - Maximum temperature (Fahrenheit or Celsius as per user preference, Fahrenheit to tenths on Daily Form pdf file
- TMAX_ATTRIBUTES
- TMIN - Minimum temperature (Fahrenheit or Celsius as per user preference, Fahrenheit to tenths on Daily Form pdf file
- TMIN_ATTRIBUTES
- TOBS - Temperature at the time of observation (Fahrenheit or Celsius as per user preference)
- TOBS_ATTRIBUTES
- WT01 - Fog, ice fog, or freezing fog (may include heavy fog)
- WT01_ATTRIBUTES
- WT03 - Thunder
- WT03_ATTRIBUTES
- WT04 - Ice pellets, sleet, snow pellets, or small hail
- WT04_ATTRIBUTES
- WT05 - Hail (may include small hail)
- WT05_ATTRIBUTES
- WT06 - Glaze or rime
- WT06_ATTRIBUTES
- WT11 - High or damaging winds
- WT11_ATTRIBUTES
https://archive.ics.uci.edu/ml/datasets/El+Nino
zonal winds (west<0, east>0), meridional winds (south<0, north>0),
# Data transformation from previous notebook
# col names in tao-all2.col from website
names = '''obs
year
month
day
date
latitude
longitude
zon.winds
mer.winds
humidity
air temp.
s.s.temp.'''.split('\n')
nino = pd.read_csv('data/tao-all2.dat.gz', sep=' ', names=names, na_values='.',
parse_dates=[[1,2,3]])
def clean_cols(val):
return val.replace('.', '_').replace(' ', '_')
nino = (nino
.rename(columns=clean_cols)
.assign(air_temp_F=lambda df_: df_.air_temp_ * 9/5 + 32,
zon_winds_mph=lambda df_: df_.zon_winds*2.237,
mer_winds_mph=lambda df_: df_.mer_winds*2.237)
.drop(columns='obs')
)
athlete_events.csv.zip From Kaggle. Medal stats to 2016
nvda_spy.csv SPY and Nvidia data to 2024 from yfinance
Gemini assisted generated data from Alone TV series
- Demographic & Background Data
season: (Integer) The installment number of the show (1–12).location: (String) The geographical region (e.g., "Vancouver Island," "Great Slave Lake"). This acts as a proxy for ecosystem type.contestant: (String) The name of the participant.age: (Integer) The age of the participant at the time of drop-off.sex: (Categorical: M/F) Biological sex.starting_weight_kg: (Continuous) The weight of the participant at the final medical check before drop-off.profession: (String) The participant's primary career. Useful for "Professional Bias" analysis (e.g., comparing "Survival Instructor" vs. "Electrician").hometown: (String) Origin city/state. Used to calculate "Home Field Advantage" if the climate matches the show location.exp_years: (Integer) Self-reported years of experience in primitive or survival skills.
- Skill & Performance Metrics (1–5 Scale)
hunt_skill: (Ordinal) 1 = Basic/No experience; 5 = Professional guide/Elite bowyer. Measures the ability to track and kill game.fish_skill: (Ordinal) 1 = Recreational; 5 = Commercial fisherman/Expert angler. Often the strongest predictor of longevity.shelter_quality: (Ordinal) 1 = Minimalist tarp/bivouac; 3 = Insulated lean-to; 5 = Permanent log cabin with stone hearth/fireplace.
- Survival Events & Physiological Data
food_events: (Integer) The count of successful "significant" harvests (e.g., a large fish, a squirrel, or big game). Smaller foraged items like berries are usually excluded.injury_count: (Integer) Total number of minor or major physical injuries recorded.med_flags: (Integer) Number of official "Medical Warnings" issued by the production team during weekly checks.gill_net: (Boolean: Y/N) Whether the participant successfully constructed and deployed a gill net.
- Environmental Stressors
precip_mm: (Continuous) Average monthly rainfall/snowfall for that location. High values correlate with "Psychological" tap-outs due to gear failure and wetness.daylight_hrs: (Continuous) The average hours of sunlight during the final third of the stay.temp_low_c: (Continuous) The average nightly low temperature during the participant's final week.
- Outcome Variables (Target Data)
-
tapout_reason: (Categorical) The primary reason for leaving. Common values: -
Winner: Last person standing.
-
Medical: Forced removal for BMI, injury, or organ failure.
-
Psychological: Loneliness, "missing family," or "journey complete."
-
Starvation: Voluntary tap due to lack of calories.
-
days_lasted: (Integer) The total number of 24-hour periods spent in the wilderness. This is usually your Dependent Variable for regression analysis.
