quirky peppers

source /home/coolhand/html/datavis/data_trove/data/quirky/peppers.json 175 rows 11 columns profiled 2026-05-01 raw JSON static .html .ipynb Report Notebook

Reading

dataset summary · high confidence anthropic:claude-opus-4-7

This dataset catalogs 175 pepper varieties with 11 fields covering name, origin, flavor, heat category, biological type, intended use, and Scoville heat measurements (min, median, max, plus a jalapeño-relative score). The Scoville and jalRP numeric columns are extremely right-skewed (skew ~9-10, kurtosis >100) with max scoville_max reaching 16,000,000 versus a median of just 30,000 — a handful of super-hot peppers dominate the tail and 24% of rows flag as outliers. On the categorical side, 'Medium' heat accounts for 40% of peppers and 'Culinary' use covers 80%, while origin leans heavily toward the United States (26%) and Mexico (15%). Worth a closer look first: the Scoville distribution (consider a log scale) and the type column, which has casing inconsistencies ('annuum' vs 'Annuum', 'chinense' vs 'Chinense') that should be cleaned before any grouping.

citing: scoville_max · scoville_median · jalRP · heat · use · origin · type · flavor

Charts the summary said to look at first

scoville_max · Heavy right tail — most peppers sit under 100k SHU but a few extreme varieties exceed a million.

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Histogram bins for scoville_max (median: 30000.0).
bin	count
0 – 1.231e+06	155
1.231e+06 – 2.462e+06	16
2.462e+06 – 3.692e+06	3
3.692e+06 – 4.923e+06	0
4.923e+06 – 6.154e+06	0
6.154e+06 – 7.385e+06	0
7.385e+06 – 8.615e+06	0
8.615e+06 – 9.846e+06	0
9.846e+06 – 1.108e+07	0
1.108e+07 – 1.231e+07	0
1.231e+07 – 1.354e+07	0
1.354e+07 – 1.477e+07	0
1.477e+07 – 1.6e+07	1

heat · Medium dominates at 40%; Extra Hot and Hot are the smallest buckets.

Show data table

Top values for heat (5 unique shown, of 5 total).
value	count	share
Medium	70	40.0%
Mild	45	25.7%
Super Hot	30	17.1%
Hot	17	9.7%
Extra Hot	13	7.4%

type · Annuum and chinense cover most peppers, but watch for duplicate casing ('Annuum', 'Chinense') needing cleanup.

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Top values for type (8 unique shown, of 8 total).
value	count	share
annuum	104	59.4%
chinense	46	26.3%
baccatum	12	6.9%
Annuum	4	2.3%
frutescens	4	2.3%
pubescens	2	1.1%
Chinense	2	1.1%
N/A	1	0.6%

use · About 80% are culinary, with ornamental as the only meaningful secondary use.

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Top values for use (4 unique shown, of 4 total).
value	count	share
Culinary	141	80.6%
Ornamental	31	17.7%
Culinary, Ornamental	2	1.1%
	1	0.6%

origin · United States and Mexico together account for over 40% of varieties; the rest is a long tail of 30+ regions.

Show data table

Top values for origin (20 unique shown, of 34 total).
value	count	share
United States	46	26.3%
Mexico	26	14.9%
South America	11	6.3%
Peru	11	6.3%
Italy	8	4.6%
Unknown	7	4.0%
United Kingdom	7	4.0%
Trinidad	7	4.0%
Caribbean	6	3.4%
India	6	3.4%
Brazil	5	2.9%
Spain	4	2.3%
Hungary	4	2.3%
Japan	3	1.7%
Africa	3	1.7%
China	2	1.1%
Thailand	2	1.1%
Balkan Peninsula	1	0.6%
France	1	0.6%
Chile	1	0.6%

Schema

11 columns

Per-column summary. Click column name to jump to its detail.
				Alerts
name	categorical	0.0%	175	long_tail
heat	categorical	0.0%	5
scoville_min	numeric	0.0%	44	high_skew outliers
scoville_max	numeric	0.0%	59	high_skew outliers
scoville_median	numeric	0.0%	80	high_skew outliers
jalRP	numeric	0.0%	81	high_skew outliers
type	categorical	0.0%	8
origin	categorical	0.0%	34
use	categorical	0.0%	4
flavor	categorical	0.0%	73	long_tail
url	categorical	0.0%	175	long_tail

name

categorical identifier long_tail

The `name` column holds 175 unique strings across 175 rows (cardinality 175, entropy_ratio ~1.0), making it a perfect per-row identifier. Sample values like "Bell Pepper", "Gypsy Pepper", and "Peperone di Senise" suggest this is a catalog of pepper varieties rather than a categorical feature. With every value occurring exactly once (top_rate 0.0057), there is no useful frequency signal to model on. Treatment: Use as a row label or join key; drop from feature matrix, near-unique. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 175
top_value: Bell Pepper
top_rate: 0.005714
cardinality: 175
entropy: 7.451
entropy_ratio: 1

heat

categorical feature

This is a categorical heat/spice level rating with 5 ordinal tiers and no nulls across 175 rows. Medium dominates at 40% (70 rows), followed by Mild (45); the upper tiers Hot (17) and Extra Hot (13) are the rarest, while Super Hot (30) is oddly more common than Hot, breaking the expected monotonic decline up the heat scale. Treatment: Encode as an ordered categorical (Mild < Medium < Hot < Super Hot < Extra Hot) before modelling. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 5
top_value: Medium
top_rate: 0.4
cardinality: 5
entropy: 2.074
entropy_ratio: 0.8933

scoville_min

numeric feature high_skew outliers

Numeric heat ratings (Scoville minimum) for 175 entries spanning 0 to 15,000,000 with a median of 15,000 — classic chili pepper data. Distribution is brutally right-skewed (skew 10.31, kurtosis 120.13) with mean 289,208 dwarfing the median, and 29 outliers (16.6% rate) plus 9.7% zeros. The std of 1,218,458 against an IQR of just 74,000 confirms a long, heavy tail. Treatment: Apply log1p transform before any modelling to tame the extreme skew and outliers. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 44
min: 0
max: 1.5e+07
mean: 2.892e+05
median: 15,000
std: 1.218e+06
q1: 1,000
q3: 75,000
iqr: 74,000
skew: 10.31
kurtosis: 120.1
n_outliers: 29
outlier_rate: 0.1657
zero_rate: 0.09714

scoville_max

numeric feature high_skew outliers

Maximum Scoville heat ratings for 175 peppers, ranging from 0 to 16,000,000 with a median of 30,000 but a mean of 384,835. Distribution is extremely right-skewed (skew 9.45, kurtosis 106) with 24.6% of values flagged as outliers and 5.7% zeros. The IQR (2,750-100,000) is dwarfed by the max, consistent with a few extreme superhot varieties dominating the tail. Treatment: log1p-transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 59
min: 0
max: 1.6e+07
mean: 3.848e+05
median: 30,000
std: 1.333e+06
q1: 2,750
q3: 100,000
iqr: 97,250
skew: 9.45
kurtosis: 106.1
n_outliers: 43
outlier_rate: 0.2457
zero_rate: 0.05714

scoville_median

numeric feature high_skew outliers

Numeric column capturing the median Scoville heat rating across 175 entries with no nulls and 80 unique values. The distribution is extremely right-skewed (skew 9.79, kurtosis 111.5): the median is 22,500 while the mean is 339,805 and the max reaches 15,500,000, with 41 outliers (23.4%) and 5.7% zeros. The IQR (2,000 to 90,000) is tiny relative to the std of 1,278,965, confirming a heavy upper tail. Treatment: Apply a log1p transform before modelling to compress the heavy right tail. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 80
min: 0
max: 1.55e+07
mean: 3.398e+05
median: 22,500
std: 1.279e+06
q1: 2,000
q3: 90,000
iqr: 88,000
skew: 9.794
kurtosis: 111.5
n_outliers: 41
outlier_rate: 0.2343
zero_rate: 0.05714

jalRP

numeric feature high_skew outliers

Numeric feature 'jalRP' is extremely right-skewed: the median is 4.29 with Q3 at 17.14, yet the max reaches 2952.38 and the mean (64.72) sits far above the median. Skew of 9.79 and kurtosis of 111.48 confirm a heavy tail, and 23.4% of values flag as outliers with 5.7% exact zeros. Only 81 unique values across 175 rows suggests repeated discrete magnitudes rather than a smooth continuum. Treatment: log1p-transform (or winsorize) before modelling to tame the heavy tail. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 81
min: 0
max: 2952
mean: 64.72
median: 4.29
std: 243.6
q1: 0.38
q3: 17.14
iqr: 16.76
skew: 9.795
kurtosis: 111.5
n_outliers: 41
outlier_rate: 0.2343
zero_rate: 0.05714

type

categorical label

This column records the Capsicum species (type), dominated by 'annuum' at 59.4% of 175 rows with 'chinense' second at 46. Watch out for case-inconsistent duplicates ('Annuum' 4, 'Chinense' 2 alongside their lowercase forms) and a literal 'N/A' string that isn't being counted as null (null_rate 0.0). Treatment: Lowercase-normalize and convert 'N/A' to null before using as a categorical label. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 8
top_value: annuum
top_rate: 0.5943
cardinality: 8
entropy: 1.657
entropy_ratio: 0.5524

origin

categorical feature

This is a categorical origin/country field with 34 distinct values across 175 rows and no nulls. Distribution is moderately concentrated: United States leads at 26.3% (46 rows), followed by Mexico (26) and South America (11), with entropy ratio 0.78 indicating fairly broad spread across the long tail. Notable quirks include a mix of country-level (United States, Italy, India) and region-level (South America, Caribbean) labels, plus 7 explicit 'Unknown' entries. Treatment: Normalise country-vs-region granularity and treat 'Unknown' as missing before one-hot or target encoding. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 34
top_value: United States
top_rate: 0.2629
cardinality: 34
entropy: 3.98
entropy_ratio: 0.7823

use

categorical feature

This is a low-cardinality categorical describing the use of an item, with 4 distinct values across 175 rows and no nulls. The distribution is heavily skewed: 'Culinary' accounts for 80.6% (141 rows), 'Ornamental' for 31, plus 2 rows with a combined 'Culinary, Ornamental' label and 1 empty string that should be treated as missing. Entropy ratio of 0.40 confirms the imbalance. Treatment: Normalize the empty string to null and split the comma-delimited value into multi-hot flags before encoding. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 4
top_value: Culinary
top_rate: 0.8057
cardinality: 4
entropy: 0.8097
entropy_ratio: 0.4049

flavor

categorical feature long_tail

This is a categorical flavor descriptor field, with values that look like comma-separated tag combinations (e.g. 'Sweet, Fruity, Earthy, Smoky') rather than single labels. Cardinality is high — 73 unique values across only 175 rows — and entropy_ratio of 0.845 confirms a long tail; the top value 'Sweet' covers just 14.3% of rows. The compound labels suggest the underlying data is multi-label flavor notes that have been collapsed into one string. Treatment: Split on commas and one-hot encode the individual flavor tags before modelling. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 73
top_value: Sweet
top_rate: 0.1429
cardinality: 73
entropy: 5.232
entropy_ratio: 0.8453

url

categorical identifier long_tail

This is a URL column serving as a per-row identifier, with all 175 values unique and zero nulls. Every entry is a pepperscale.com pepper page (e.g., bell-pepper, gypsy-pepper, habanada-pepper), so the column is effectively a primary key for pepper varieties. Entropy ratio of ~1.0 confirms no repetition. Treatment: Drop from modelling; retain as a row key or source link. high · anthropic:claude-opus-4-7

n: 175
nulls: 0 (0.0%)
unique: 175
top_value: https://www.pepperscale.com/bell-pepper/
top_rate: 0.005714
cardinality: 175
entropy: 7.451
entropy_ratio: 1