saturn

/home/coolhand/html/datavis/data_trove/data/quirky/peppers.json 175 rows sample n=175 seed 42 2026-06-21T23:54:04+00:00

Overview

Source/home/coolhand/html/datavis/data_trove/data/quirky/peppers.json
Total rows175
Profiled sample175
Columns11
Generated2026-06-21T23:54:04+00:00
Show data table
Per-column null rate across the corpus.
columnkindnull %
namecategorical0.0%
heatcategorical0.0%
scoville_minnumeric0.0%
scoville_maxnumeric0.0%
scoville_mediannumeric0.0%
jalRPnumeric0.0%
typecategorical0.0%
origincategorical0.0%
usecategorical0.0%
flavorcategorical0.0%
urlcategorical0.0%

Insights opt-in

Model-generated narrative. These are opinions, not facts — the stats below are what saturn measured. Generated by: anthropic:default.

Dataset high anthropic:default

This dataset catalogs 175 pepper varieties with attributes covering heat (Scoville scale min/median/max), flavor profile, botanical type, geographic origin, and culinary use. The most striking feature is the extreme right-skew in all three Scoville columns: while the median pepper sits around 15,000–30,000 SHU, outliers push to 15–16 million SHU, meaning a small cluster of 'Super Hot' varieties dwarfs the rest of the dataset. A secondary angle worth exploring is the geographic and botanical spread — the United States leads origin with 46 entries, 'annuum' dominates species type at 104 of 175, and flavor descriptions cluster heavily around 'Sweet' and 'Sweet, Fruity', suggesting most peppers in this catalog are mild and food-friendly despite the headline-grabbing extremes.

jalRP high anthropic:default

jalRP is a non-negative numeric column with 175 rows and no nulls, likely representing a monetary amount, duration, or count that is naturally right-bounded near zero. The distribution is extremely right-skewed (skew = 9.79, kurtosis = 111.48): the median is just 4.29 while the mean is 64.72, and a maximum of 2952.38 pulls the standard deviation to 243.61 — 41 rows (23.4%) are flagged as outliers. The interquartile range spans only 0.38 to 17.14, meaning 75% of values are below 17.14, yet the top end reaches nearly 3000, signalling a heavy-tailed, potentially power-law distribution.

scoville_max high anthropic:default

This column represents the maximum Scoville Heat Unit (SHU) rating for chili peppers or hot sauce products — a standard measure of capsaicin-driven heat intensity. The distribution is extraordinarily right-skewed (skew=9.45, kurtosis=106.1): the median is only 30,000 SHU while the mean is 384,835 and the maximum reaches 16,000,000 — consistent with extreme outliers like pure capsaicin extracts sitting alongside mild peppers. With 43 outliers (24.6% of rows) and a standard deviation of 1,333,100 dwarfing the median, the bulk of records cluster at low heat levels while a long tail of superhot entries dominates the mean. The 5.7% zero rate likely reflects peppers with no measurable heat (e.g., bell peppers).

scoville_median high anthropic:default

This column represents the median Scoville heat unit (SHU) rating for chili peppers or hot sauces — a standard measure of capsaicin-driven spiciness. The distribution is extraordinarily right-skewed (skew=9.79, kurtosis=111.47): the median sits at 22,500 SHU while the mean is pulled to 339,804 SHU by extreme outliers, with a maximum of 15,500,000 SHU (consistent with ultra-hot peppers like Carolina Reaper). 41 of 175 rows (23.4%) are flagged as outliers, and 5.7% of values are exactly zero, suggesting entries for non-spicy varieties (e.g., bell peppers). The IQR spans only 2,000–90,000 SHU, confirming that the bulk of records are mild-to-medium heat while a long tail of superhot entries distorts the scale severely.

scoville_min high anthropic:default

This column represents the minimum Scoville Heat Unit (SHU) value for chili peppers or hot sauces, capturing the lower bound of each item's heat range. The distribution is dramatically right-skewed (skew = 10.31, kurtosis = 120.13): the median is just 15,000 SHU while the mean is 289,208 SHU, driven by extreme outliers reaching 15,000,000 SHU (pure capsaicin territory). With 29 outliers (16.6% of rows) and only 44 unique values across 175 records, the data clusters heavily at low heat levels but has a long tail of superhot entries. The 9.7% zero rate corresponds to genuinely non-hot items (e.g., bell peppers at 0 SHU), which is domain-valid.

flavor high anthropic:default

This column captures flavor descriptors for a food or beverage dataset, stored as free-form comma-separated tag strings (e.g., 'Sweet, Fruity, Smoky'). With 73 unique values across only 175 rows and an entropy ratio of 0.845, the vocabulary is highly fragmented — notably, 'Sweet' (25 occurrences) and 'Sweet, Fruity' (21) appear to be near-duplicates of ordering variants like 'Fruity, Sweet' (6), suggesting inconsistent entry order inflating cardinality artificially. The long-tail alert confirms that most combinations appear very rarely, with the top value covering only 14.3% of rows.

name high anthropic:default

This column contains the names of individual pepper varieties — it is a human-readable label for each record in what appears to be a pepper/vegetable catalog. With 175 rows and 175 unique values, every entry is distinct (cardinality = 175, top_rate = 0.0057, i.e. 1/175), making this a perfect natural key. Entropy ratio of ~1.0 confirms near-maximum unpredictability, consistent with a unique-per-row label rather than a grouping variable.

url high anthropic:default

This column contains fully-qualified URLs pointing to individual pepper variety pages on pepperscale.com, effectively serving as a unique page identifier for each row. Cardinality is exactly 175 with 175 unique values and a null rate of 0.0, meaning every row has a distinct URL — the top_rate of 0.005714 (1/175) confirms no duplicates whatsoever. Entropy ratio of ~1.0 indicates maximum dispersion, consistent with a perfect natural key. The long_tail alert is technically triggered but is structurally expected given perfect uniqueness.

heat high anthropic:default

This column is an ordinal heat/spiciness level rating with 5 discrete categories, likely describing food or beverage intensity. 'Medium' dominates at 40% of 175 rows (top_rate 0.4), while the two hottest tiers ('Hot' and 'Extra Hot') together account for only 30 rows — a pronounced skew toward milder levels. Entropy ratio of 0.893 indicates reasonably spread distribution despite the modal imbalance. No nulls and no unexpected values are present.

origin high anthropic:default

This column records the geographic origin of individuals or items, expressed as country or regional names across 34 distinct values in 175 rows. 'United States' dominates at 26.3% (46 rows), followed by 'Mexico' (26) and several South American/Caribbean entries. Notably, the taxonomy mixes country-level specificity ('Peru', 'Italy') with broad regional labels ('South America', 'Caribbean'), and 7 rows carry the value 'Unknown', indicating inconsistent granularity in data collection.

type high anthropic:default

This column captures Capsicum species type (botanical variety), with 8 apparent unique values across 175 records and no nulls. The dominant value 'annuum' accounts for 59.4% of rows, followed by 'chinense' (46 rows) and 'baccatum' (12 rows). A critical data quality issue exists: 'annuum' and 'Annuum' are treated as distinct values (104 vs. 4 occurrences), as are 'chinense' and 'Chinense' (46 vs. 2), indicating inconsistent capitalisation that inflates apparent cardinality. Additionally, one record holds the sentinel string 'N/A' rather than a true null.

use high anthropic:default

This column captures the primary use-case category for each record, likely plants or herbs, with four distinct values and no nulls across 175 rows. 'Culinary' dominates at 80.6% (141 of 175), making the distribution heavily skewed. One entry is an empty string rather than a true null, which effectively acts as a fifth implicit category. The dual-label value 'Culinary, Ornamental' (2 occurrences) signals inconsistent multi-value encoding that may need normalisation.

Numeric correlation

Show data table
Pearson correlation across 4 numeric columns (values clipped to 2 decimals).
scoville_minscoville_maxscoville_medianjalRP
scoville_min+1.00+0.99+1.00+1.00
scoville_max+0.99+1.00+1.00+1.00
scoville_median+1.00+1.00+1.00+1.00
jalRP+1.00+1.00+1.00+1.00

name categorical

175 singleton categories
rows175
null0 (0.0%)
unique175
top_valueBell Pepper
top_rate5.71e-03
cardinality175
entropy7.451
entropy_ratio1.000
Show data table
Top values for name (20 unique shown, of 175 total).
valuecountshare
Bell Pepper10.6%
Gypsy Pepper10.6%
Purple Beauty Pepper10.6%
Melrose Pepper10.6%
Carmen Pepper10.6%
California Wonder Pepper10.6%
Peperone di Senise10.6%
Fushimi Pepper10.6%
Elephant Ears Pepper10.6%
Habanada Pepper10.6%
Tangerine Dream Pepper10.6%
Chilly Chili10.6%
Shishito Pepper10.6%
Trinidad Perfume10.6%
Banana Pepper10.6%
Pepperoncini10.6%
Pimento Pepper10.6%
Jimmy Nardello Pepper10.6%
Mariachi Pepper10.6%
Santa Fe Grande Pepper10.6%
Top values (rank 1–20)
  1. Bell Pepper — 1
  2. Gypsy Pepper — 1
  3. Purple Beauty Pepper — 1
  4. Melrose Pepper — 1
  5. Carmen Pepper — 1
  6. California Wonder Pepper — 1
  7. Peperone di Senise — 1
  8. Fushimi Pepper — 1
  9. Elephant Ears Pepper — 1
  10. Habanada Pepper — 1
  11. Tangerine Dream Pepper — 1
  12. Chilly Chili — 1
  13. Shishito Pepper — 1
  14. Trinidad Perfume — 1
  15. Banana Pepper — 1
  16. Pepperoncini — 1
  17. Pimento Pepper — 1
  18. Jimmy Nardello Pepper — 1
  19. Mariachi Pepper — 1
  20. Santa Fe Grande Pepper — 1

heat categorical

rows175
null0 (0.0%)
unique5
top_valueMedium
top_rate0.400
cardinality5
entropy2.074
entropy_ratio0.893
Show data table
Top values for heat (5 unique shown, of 5 total).
valuecountshare
Medium7040.0%
Mild4525.7%
Super Hot3017.1%
Hot179.7%
Extra Hot137.4%
Top values (rank 1–20)
  1. Medium — 70
  2. Mild — 45
  3. Super Hot — 30
  4. Hot — 17
  5. Extra Hot — 13

scoville_min numeric

skew=+10.31 16.6% rows beyond 1.5 IQR
rows175
null0 (0.0%)
unique44
min0.000
max15,000,000
mean289,209
median15,000
std1,218,458
q11,000
q375,000
iqr74,000
skew10.313
kurtosis120.132
n_outliers29
outlier_rate0.166
zero_rate0.097
Show data table
Histogram bins for scoville_min (median: 15000.0).
bincount
0 – 1.154e+06164
1.154e+06 – 2.308e+067
2.308e+06 – 3.462e+063
3.462e+06 – 4.615e+060
4.615e+06 – 5.769e+060
5.769e+06 – 6.923e+060
6.923e+06 – 8.077e+060
8.077e+06 – 9.231e+060
9.231e+06 – 1.038e+070
1.038e+07 – 1.154e+070
1.154e+07 – 1.269e+070
1.269e+07 – 1.385e+070
1.385e+07 – 1.5e+071

scoville_max numeric

skew=+9.45 24.6% rows beyond 1.5 IQR
rows175
null0 (0.0%)
unique59
min0.000
max16,000,000
mean384,835
median30,000
std1,333,100
q12,750
q3100,000
iqr97,250
skew9.450
kurtosis106.108
n_outliers43
outlier_rate0.246
zero_rate0.057
Show data table
Histogram bins for scoville_max (median: 30000.0).
bincount
0 – 1.231e+06155
1.231e+06 – 2.462e+0616
2.462e+06 – 3.692e+063
3.692e+06 – 4.923e+060
4.923e+06 – 6.154e+060
6.154e+06 – 7.385e+060
7.385e+06 – 8.615e+060
8.615e+06 – 9.846e+060
9.846e+06 – 1.108e+070
1.108e+07 – 1.231e+070
1.231e+07 – 1.354e+070
1.354e+07 – 1.477e+070
1.477e+07 – 1.6e+071

scoville_median numeric

skew=+9.79 23.4% rows beyond 1.5 IQR
rows175
null0 (0.0%)
unique80
min0.000
max15,500,000
mean339,805
median22,500
std1,278,966
q12,000
q390,000
iqr88,000
skew9.794
kurtosis111.468
n_outliers41
outlier_rate0.234
zero_rate0.057
Show data table
Histogram bins for scoville_median (median: 22500.0).
bincount
0 – 1.192e+06161
1.192e+06 – 2.385e+0610
2.385e+06 – 3.577e+063
3.577e+06 – 4.769e+060
4.769e+06 – 5.962e+060
5.962e+06 – 7.154e+060
7.154e+06 – 8.346e+060
8.346e+06 – 9.538e+060
9.538e+06 – 1.073e+070
1.073e+07 – 1.192e+070
1.192e+07 – 1.312e+070
1.312e+07 – 1.431e+070
1.431e+07 – 1.55e+071

jalRP numeric

skew=+9.79 23.4% rows beyond 1.5 IQR
rows175
null0 (0.0%)
unique81
min0.000
max2,952
mean64.721
median4.290
std243.607
q10.380
q317.140
iqr16.760
skew9.795
kurtosis111.478
n_outliers41
outlier_rate0.234
zero_rate0.057
Show data table
Histogram bins for jalRP (median: 4.29).
bincount
0 – 227.1161
227.1 – 454.210
454.2 – 681.33
681.3 – 908.40
908.4 – 11360
1136 – 13630
1363 – 15900
1590 – 18170
1817 – 20440
2044 – 22710
2271 – 24980
2498 – 27250
2725 – 29521

type categorical

rows175
null0 (0.0%)
unique8
top_valueannuum
top_rate0.594
cardinality8
entropy1.657
entropy_ratio0.552
Show data table
Top values for type (8 unique shown, of 8 total).
valuecountshare
annuum10459.4%
chinense4626.3%
baccatum126.9%
Annuum42.3%
frutescens42.3%
pubescens21.1%
Chinense21.1%
N/A10.6%
Top values (rank 1–20)
  1. annuum — 104
  2. chinense — 46
  3. baccatum — 12
  4. Annuum — 4
  5. frutescens — 4
  6. pubescens — 2
  7. Chinense — 2
  8. N/A — 1

origin categorical

rows175
null0 (0.0%)
unique34
top_valueUnited States
top_rate0.263
cardinality34
entropy3.980
entropy_ratio0.782
Show data table
Top values for origin (20 unique shown, of 34 total).
valuecountshare
United States4626.3%
Mexico2614.9%
South America116.3%
Peru116.3%
Italy84.6%
Unknown74.0%
United Kingdom74.0%
Trinidad74.0%
Caribbean63.4%
India63.4%
Brazil52.9%
Spain42.3%
Hungary42.3%
Japan31.7%
Africa31.7%
China21.1%
Thailand21.1%
Balkan Peninsula10.6%
France10.6%
Chile10.6%
Top values (rank 1–20)
  1. United States — 46
  2. Mexico — 26
  3. South America — 11
  4. Peru — 11
  5. Italy — 8
  6. Unknown — 7
  7. United Kingdom — 7
  8. Trinidad — 7
  9. Caribbean — 6
  10. India — 6
  11. Brazil — 5
  12. Spain — 4
  13. Hungary — 4
  14. Japan — 3
  15. Africa — 3
  16. China — 2
  17. Thailand — 2
  18. Balkan Peninsula — 1
  19. France — 1
  20. Chile — 1

use categorical

rows175
null0 (0.0%)
unique4
top_valueCulinary
top_rate0.806
cardinality4
entropy0.810
entropy_ratio0.405
Show data table
Top values for use (4 unique shown, of 4 total).
valuecountshare
Culinary14180.6%
Ornamental3117.7%
Culinary, Ornamental21.1%
10.6%
Top values (rank 1–20)
  1. Culinary — 141
  2. Ornamental — 31
  3. Culinary, Ornamental — 2
  4. — 1

flavor categorical

49 singleton categories
rows175
null0 (0.0%)
unique73
top_valueSweet
top_rate0.143
cardinality73
entropy5.232
entropy_ratio0.845
Show data table
Top values for flavor (20 unique shown, of 73 total).
valuecountshare
Sweet2514.3%
Sweet, Fruity2112.0%
Neutral1910.9%
Fruity, Sweet63.4%
Bright, Sweet42.3%
Sweet, Tangy42.3%
Sweet, Fruity, Smoky42.3%
Sweet, Fruity, Citrusy42.3%
Sweet, Fruity, Earthy, Smoky42.3%
Sweet, Fruity, Floral31.7%
Sweet, Fruity, Citrusy, Floral31.7%
Sweet, Fruity, Earthy31.7%
Sweet, Tropical31.7%
Bright, Grassy31.7%
Sweet, Floral21.1%
Sweet, Smoky21.1%
Earthy21.1%
Smoky, Sweet, Earthy21.1%
Smoky, Earthy21.1%
Sweet, Citrusy21.1%
Top values (rank 1–20)
  1. Sweet — 25
  2. Sweet, Fruity — 21
  3. Neutral — 19
  4. Fruity, Sweet — 6
  5. Bright, Sweet — 4
  6. Sweet, Tangy — 4
  7. Sweet, Fruity, Smoky — 4
  8. Sweet, Fruity, Citrusy — 4
  9. Sweet, Fruity, Earthy, Smoky — 4
  10. Sweet, Fruity, Floral — 3
  11. Sweet, Fruity, Citrusy, Floral — 3
  12. Sweet, Fruity, Earthy — 3
  13. Sweet, Tropical — 3
  14. Bright, Grassy — 3
  15. Sweet, Floral — 2
  16. Sweet, Smoky — 2
  17. Earthy — 2
  18. Smoky, Sweet, Earthy — 2
  19. Smoky, Earthy — 2
  20. Sweet, Citrusy — 2

url categorical

175 singleton categories
rows175
null0 (0.0%)
unique175
top_valuehttps://www.pepperscale.com/bell-pepper/
top_rate5.71e-03
cardinality175
entropy7.451
entropy_ratio1.000
Show data table
Top values for url (20 unique shown, of 175 total).
valuecountshare
https://www.pepperscale.com/bell-pepper/10.6%
https://www.pepperscale.com/gypsy-pepper/10.6%
https://www.pepperscale.com/purple-beauty-pepper/10.6%
https://www.pepperscale.com/melrose-pepper/10.6%
https://www.pepperscale.com/carmen-pepper/10.6%
https://www.pepperscale.com/california-wonder-pepper/10.6%
https://www.pepperscale.com/peperone-di-senise/10.6%
https://www.pepperscale.com/fushimi-pepper/10.6%
https://www.pepperscale.com/elephant-ears-pepper/10.6%
https://www.pepperscale.com/habanada-pepper/10.6%
https://www.pepperscale.com/tangerine-dream-pepper/10.6%
https://www.pepperscale.com/chilly-chili/10.6%
https://www.pepperscale.com/shishito-pepper/10.6%
https://www.pepperscale.com/trinidad-perfume/10.6%
https://www.pepperscale.com/banana-pepper/10.6%
https://www.pepperscale.com/pepperoncini/10.6%
https://www.pepperscale.com/pimento-pepper/10.6%
https://pepperscale.com/jimmy-nardello-pepper/10.6%
https://www.pepperscale.com/mariachi-pepper/10.6%
https://www.pepperscale.com/santa-fe-grande-pepper/10.6%
Top values (rank 1–20)
  1. https://www.pepperscale.com/bell-pepper/ — 1
  2. https://www.pepperscale.com/gypsy-pepper/ — 1
  3. https://www.pepperscale.com/purple-beauty-pepper/ — 1
  4. https://www.pepperscale.com/melrose-pepper/ — 1
  5. https://www.pepperscale.com/carmen-pepper/ — 1
  6. https://www.pepperscale.com/california-wonder-pepper/ — 1
  7. https://www.pepperscale.com/peperone-di-senise/ — 1
  8. https://www.pepperscale.com/fushimi-pepper/ — 1
  9. https://www.pepperscale.com/elephant-ears-pepper/ — 1
  10. https://www.pepperscale.com/habanada-pepper/ — 1
  11. https://www.pepperscale.com/tangerine-dream-pepper/ — 1
  12. https://www.pepperscale.com/chilly-chili/ — 1
  13. https://www.pepperscale.com/shishito-pepper/ — 1
  14. https://www.pepperscale.com/trinidad-perfume/ — 1
  15. https://www.pepperscale.com/banana-pepper/ — 1
  16. https://www.pepperscale.com/pepperoncini/ — 1
  17. https://www.pepperscale.com/pimento-pepper/ — 1
  18. https://pepperscale.com/jimmy-nardello-pepper/ — 1
  19. https://www.pepperscale.com/mariachi-pepper/ — 1
  20. https://www.pepperscale.com/santa-fe-grande-pepper/ — 1