joshua project joshua project countries

Likely a population count by some geographic or organisational unit ('PoplPeoples'), spanning from 50 to ~1.39B with a median of 532,500. The distribution is extremely right-skewed (skew 12.1, kurtosis 156) with 31 outliers (15.8%) and a std (~104M) far exceeding the mean (~18M), suggesting a few massive entities dominate. Also notable: 17.65% of rows are null. Treatment: Log-transform and impute the ~17.65% nulls before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

42 (17.6%)

unique

180

min

50

max

1.395e+09

mean

1.823e+07

median

532,500

std

1.038e+08

q1

32,750

q3

6.022e+06

iqr

5.99e+06

skew

12.1

kurtosis

156.4

n_outliers

31

outlier_rate

0.1582

zero_rate

0

PercentUnknown is a numeric proportion ranging from 0.0 to 2.679, with a mean of 0.218 and median of 0.176. About 34% of the 238 rows are exactly zero (q1 is also 0.0), yet the column is heavily right-tailed with skew 3.92 and kurtosis 32.16, plus a max above 1.0 that is unusual if this was meant to be a 0-1 share. Three outliers (1.3%) sit far above the bulk of the distribution. Treatment: Verify whether values >1 are valid, then log1p-transform given the heavy right skew and zero-inflation. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

158

min

0

max

2.679

mean

0.2176

median

0.1758

std

0.2604

q1

0

q3

0.3673

iqr

0.3673

skew

3.918

kurtosis

32.16

n_outliers

3

outlier_rate

0.01261

zero_rate

0.3403

Primary religion of each record across 238 rows with 6 distinct values and no nulls. Christianity dominates at 159/238 (top_rate 0.668), followed by Islam at 55, with Buddhism, Ethnic Religions, Non-Religious, and Hinduism sharing the long tail under 10 each. Entropy ratio of 0.54 confirms the heavy concentration in one category. Treatment: One-hot encode, optionally collapsing the four smallest categories into 'Other' to handle imbalance. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

6

top_value

Christianity

top_rate

0.6681

cardinality

6

entropy

1.4

entropy_ratio

0.5415

SecurityLevel takes only 3 distinct integer values across 238 rows (min 0, max 2) with no nulls, suggesting an ordinal tier code rather than a continuous measure. The distribution is heavily weighted toward the lowest tier: 67.6% of rows are zero, the median is 0, and the mean is just 0.55, producing a right skew of 1.01. No outliers were flagged, which is consistent with a bounded categorical scale. Treatment: Treat as an ordinal category (0/1/2) rather than a continuous numeric. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

3

min

0

max

2

mean

0.5462

median

0

std

0.8344

q1

0

q3

1

iqr

1

skew

1.011

kurtosis

-0.796

n_outliers

0

outlier_rate

0

zero_rate

0.6765

This column reports the percentage of a population that is non-religious across 238 rows, with 228 unique values and no nulls. The distribution is heavily right-skewed (skew 2.61, kurtosis 8.00): the median is just 2.85% while the mean is 7.31% and the max reaches 68.81%, with 30 outliers (12.6% of rows) and 4.6% of values exactly zero. The std (11.39) dwarfs the IQR (7.08), confirming a long upper tail rather than a symmetric spread. Treatment: Log1p- or rank-transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

228

min

0

max

68.81

mean

7.308

median

2.851

std

11.39

q1

0.5635

q3

7.646

iqr

7.083

skew

2.611

kurtosis

7.999

n_outliers

30

outlier_rate

0.1261

zero_rate

0.04622

This column holds ISO2 country codes (AF, AL, DZ, AS, AD...), serving as a unique key with 238 distinct values across 238 rows and zero nulls. Cardinality equals row count and entropy_ratio is 1.0, meaning every code appears exactly once — top_rate is just 0.0042. The long_tail alert is expected here since the column is effectively a primary identifier. Treatment: Use as the join key to merge country-level attributes. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

238

top_value

AF

top_rate

0.004202

cardinality

238

entropy

7.895

entropy_ratio

1

This column holds URLs to one of five Joshua Project 'gauge' images (gauge-1.png through gauge-5.png), almost certainly a visual encoding of an ordinal progress/status score on a 1-5 scale. With only 5 unique values across 238 rows and no nulls, gauge-5 leads at 37.4% (89 rows) while gauge-2 is rarest at 11 rows, suggesting a skew toward the high end of the scale. The URL itself carries no information beyond the trailing digit. Treatment: Extract the trailing digit (1-5) and treat as an ordinal feature; drop the URL string. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

5

top_value

https://joshuaproject.net/assets/img/gauge/gauge-5.png

top_rate

0.3739

cardinality

5

entropy

2.06

entropy_ratio

0.8871

Numeric share (0–75.16) representing the percentage of ethnic-religion adherents per row, likely one country or region per record across 238 entries with 199 unique values. The distribution is heavily right-skewed (skew 3.29, kurtosis 12.38) with a median of just 1.12% but a mean of 5.59% and a long tail producing 27 outliers (11.3% of rows); 16.8% of rows are exact zeros. The IQR (5.52) is far smaller than the std (11.21), confirming most values cluster near zero while a few cases dominate. Treatment: Apply a log1p or similar transform before modelling to tame the heavy right tail and zero mass. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

199

min

0

max

75.16

mean

5.59

median

1.116

std

11.21

q1

0.05109

q3

5.576

iqr

5.525

skew

3.295

kurtosis

12.38

n_outliers

27

outlier_rate

0.1134

zero_rate

0.1681

RegionName is a categorical geographic grouping with 12 distinct values across 238 rows and no nulls. The distribution is remarkably even — entropy ratio 0.96 and the top bucket 'America, North and Caribbean' accounts for only 12.6% (30 rows) — suggesting these are world regions assigned to countries or similar entities. The Asian regions (Southeast: 11, Central: 10) are notably smaller than the African and European groupings. Treatment: one-hot or target-encode for modelling; safe to use as a grouping key. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

12

top_value

America, North and Caribbean

top_rate

0.1261

cardinality

12

entropy

3.454

entropy_ratio

0.9634

Numeric count of people per record, fully populated across 238 rows with 96 distinct values ranging from 1 to 2262. The distribution is severely right-skewed (skew 8.20, kurtosis 85.91): the median is 24.5 and Q3 is 56.75, yet the mean is 68.83 and the max reaches 2262, with 24 outliers (10.1% outlier rate). Std (184.37) far exceeds the IQR (48.75), confirming a long heavy tail. Treatment: log-transform (or winsorize the top decile) before any distance- or variance-based modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

96

min

1

max

2,262

mean

68.83

median

24.5

std

184.4

q1

8

q3

56.75

iqr

48.75

skew

8.202

kurtosis

85.91

n_outliers

24

outlier_rate

0.1008

zero_rate

0

Likely a population count of 'people groups' (PoplPeoplesFPG), with values ranging from 50 to roughly 1.09 billion and a median of 217,000. The distribution is extremely right-skewed (skew 11.6, kurtosis 138.7) with 19% of values flagged as outliers, and 31.5% of rows are null. The mean (~12.26M) sits far above the median, confirming a handful of massive groups dominate. Treatment: log-transform and impute the 31.5% nulls before any modelling. high · anthropic:claude-opus-4-7

n

238

nulls

75 (31.5%)

unique

142

min

50

max

1.09e+09

mean

1.226e+07

median

217,000

std

8.773e+07

q1

16,500

q3

1.842e+06

iqr

1.825e+06

skew

11.6

kurtosis

138.7

n_outliers

31

outlier_rate

0.1902

zero_rate

0

ROG3 looks like a country/region code identifier — every one of the 238 rows holds a unique two-letter value (AF, AL, AG, AQ, ...), giving cardinality 238 and entropy_ratio 1.0. With top_rate at 0.0042 and no nulls, this column carries no predictive signal on its own and behaves as a primary key for the row. Treatment: Use as a join key to country-level attributes; drop from any model as a feature. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

238

top_value

AF

top_rate

0.004202

cardinality

238

entropy

7.895

entropy_ratio

1

Numeric share (0–53.4%) of an evangelical population across 238 rows, almost all unique (232 distinct values), suggesting one observation per geographic or demographic unit. The distribution is right-skewed (skew 1.25) with mean 10.46% well above the median 6.92% and an IQR spanning 1.38–17.69%, so a long tail of high-evangelical units pulls the average up. About 2.5% of rows are null and 4 outliers sit beyond the upper whisker; no zero values were recorded. Treatment: Consider a log or sqrt transform before modelling to tame the right skew. high · anthropic:claude-opus-4-7

n

238

nulls

6 (2.5%)

unique

232

min

0.000766

max

53.44

mean

10.46

median

6.916

std

11.35

q1

1.38

q3

17.69

iqr

16.31

skew

1.247

kurtosis

0.9595

n_outliers

4

outlier_rate

0.01724

zero_rate

0

ISO 639-3 language codes denoting each entity's official language, with 88 distinct values across 238 rows and no nulls. English dominates at 26.5% (63 rows) followed by French (25), Spanish (21), and Arabic (20), but the long tail is heavy — entropy ratio 0.74 against cardinality 88 means most codes appear only once or twice (e.g. aln, smo at 2). Worth noting some codes like 'arb' and 'cmn' are macro-language specific variants, so consistency of coding granularity should be checked. Treatment: Group the long tail into an 'other' bucket or target-encode before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

88

top_value

eng

top_rate

0.2647

cardinality

88

entropy

4.802

entropy_ratio

0.7434

A heavily right-skewed count of 'TranslationUnspecified' occurrences per row, with 21 distinct integer values across 238 rows. Roughly 42% of rows are zero and the median is 1, yet the maximum reaches 80 against a Q3 of 2, producing extreme skew (6.02) and kurtosis (45.1). About 11% of values (26 rows) flag as outliers, so a small tail dominates the mean (2.80) versus median (1). Treatment: Log1p- or rank-transform before modelling, and consider winsorising the long tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

21

min

0

max

80

mean

2.798

median

1

std

7.881

q1

0

q3

2

iqr

2

skew

6.016

kurtosis

45.14

n_outliers

26

outlier_rate

0.1092

zero_rate

0.4244

TranslationNeeded is a numeric count column where 68% of rows are zero and the median and Q1-Q3 sit at 0-1, suggesting it tracks how many items required translation per record. The distribution is extremely right-skewed (skew 8.56, kurtosis 79.6) with a max of 104 against a mean of 2.24, and 31 rows (13%) flag as outliers. With only 18 unique values across 238 rows, this behaves more like a sparse event counter than a continuous metric. Treatment: Log1p-transform or binarise (zero vs non-zero) before modelling to tame the heavy tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

18

min

0

max

104

mean

2.235

median

0

std

10.27

q1

0

q3

1

iqr

1

skew

8.56

kurtosis

79.64

n_outliers

31

outlier_rate

0.1303

zero_rate

0.6807

A numeric counter named TranslationStarted, likely the number of translation jobs initiated per row/entity. Over half the rows are zero (zero_rate 0.517) and the median is 0 with q3=3, yet the max reaches 261, producing extreme skew (7.81) and kurtosis (64.98) plus 35 outliers (14.7%). The mean of 6.46 is pulled far above the median by these heavy-tail cases. Treatment: Apply a log1p (or zero-inflated) transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

30

min

0

max

261

mean

6.458

median

0

std

27.06

q1

0

q3

3

iqr

3

skew

7.807

kurtosis

64.98

n_outliers

35

outlier_rate

0.1471

zero_rate

0.5168

RegionCode holds 12 distinct integer values from 1 to 12 across 238 rows with no nulls, which strongly suggests a categorical region identifier rather than a true numeric measure. The distribution is mildly left-skewed (skew -0.47) with a median of 8 and no outliers, indicating fairly even coverage across the higher-numbered regions. Treatment: Cast to categorical and one-hot or target-encode before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

12

min

1

max

12

mean

7.336

median

8

std

3.528

q1

5

q3

10

iqr

5

skew

-0.4715

kurtosis

-0.9103

n_outliers

0

outlier_rate

0

zero_rate

0

Despite the abbreviated header `Ctry`, this column holds full country names (Afghanistan, Albania, Algeria, …) and acts as a unique key: all 238 rows have distinct values, with entropy_ratio of ~1.0 and a top_rate of just 0.0042. There are no nulls, and the alphabetical run in top_values suggests the dataset is a one-row-per-country reference table. Treatment: Use as the primary key; left-join other country-level data on this column. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

238

top_value

Afghanistan

top_rate

0.004202

cardinality

238

entropy

7.895

entropy_ratio

1

Numeric counts of New Testament references per row, ranging from 0 to 274 with a median of just 3. The distribution is extremely right-skewed (skew 6.08, kurtosis 49.4) with 23.1% zeros and 10.5% outliers, so a small number of rows dominate the totals while most carry few or no references. Treatment: Apply a log1p transform and consider winsorising before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

45

min

0

max

274

mean

10.82

median

3

std

25.76

q1

1

q3

10

iqr

9

skew

6.079

kurtosis

49.43

n_outliers

25

outlier_rate

0.105

zero_rate

0.2311

A numeric count, plausibly the number of times a respondent has read the Bible cover-to-cover or a similar completion tally, ranging from 0 to 162 across 238 rows with no nulls. The distribution is heavily right-skewed (skew 3.32, kurtosis 17.0): median is 9 with an IQR of 15, yet 18 values (7.6%) qualify as outliers and the max of 162 sits far above q3=19. Only 1.7% are zero, so non-engagement is rare; the long tail of high counts is the dominant surprise. Treatment: Apply a log1p transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

54

min

0

max

162

mean

15.56

median

9

std

18.9

q1

4

q3

19

iqr

15

skew

3.319

kurtosis

17.02

n_outliers

18

outlier_rate

0.07563

zero_rate

0.01681

Binary Y/N flag with no nulls across 238 rows. The distribution is imbalanced toward 'N' at 71.4% (170 of 238) versus 'Y' at 68, giving an entropy ratio of 0.86. The 'Window1040' name suggests a windowed indicator tied to event 1040, but the evidence does not clarify what that event represents. Treatment: Encode as a 0/1 boolean for modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

2

top_value

N

top_rate

0.7143

cardinality

2

entropy

0.8631

entropy_ratio

0.8631

JPScaleText is a 5-level ordinal label describing reach status (Unreached, Minimally, Superficially, Partially, Significantly Reached) across 238 complete rows. The distribution is fairly balanced with high entropy ratio (0.887) and a modal class of 'Significantly Reached' at 37.4%, though 'Minimally Reached' is sparse at only 11 records. No nulls and tight cardinality make this a clean categorical feature. Treatment: Encode as an ordered ordinal (Unreached → Significantly Reached) before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

5

top_value

Significantly Reached

top_rate

0.3739

cardinality

5

entropy

2.06

entropy_ratio

0.8871

CntPrimaryLanguages is a numeric count (likely the number of primary languages associated with each row, e.g., a country or region) ranging from 1 to 827 across 238 rows with no nulls. The distribution is heavily right-skewed (skew 5.42, kurtosis 36.5): the median is just 20 while the mean is 45.6 and the max reaches 827, with 20 outliers (8.4%) sitting well above the Q3 of 46.5. Most entities have modest language counts but a small tail dominates the variance (std 90.1). Treatment: log-transform (or winsorize the upper tail) before any distance- or regression-based modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

91

min

1

max

827

mean

45.55

median

20

std

90.13

q1

7

q3

46.5

iqr

39.5

skew

5.42

kurtosis

36.52

n_outliers

20

outlier_rate

0.08403

zero_rate

0

This column lists the official language(s) of 238 entities, almost certainly countries or territories, with one near-null. English dominates at 63 occurrences (26.6% top rate), followed by French (25), Spanish (21), and Standard Arabic (20), but the long tail spans 87 distinct values including narrow entries like Gheg Albanian and Samoan, yielding entropy 4.78 (ratio 0.74). The high cardinality relative to 238 rows means many languages appear only once or twice. Treatment: Group rare languages into an 'Other' bucket before one-hot or target encoding. high · anthropic:claude-opus-4-7

n

238

nulls

1 (0.4%)

unique

87

top_value

English

top_rate

0.2658

cardinality

87

entropy

4.783

entropy_ratio

0.7423

Numeric count of Bible portions, likely per language or region, across 238 rows with no nulls and only 35 unique values. The distribution is severely right-skewed (skew 5.57, kurtosis 36.36) with a median of 2 against a max of 161, and 26.05% of rows are zero. Roughly 10.9% of values flag as outliers, so a few entries dominate the tail. Treatment: Apply a log1p transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

35

min

0

max

161

mean

7.681

median

2

std

18.63

q1

0

q3

6.75

iqr

6.75

skew

5.573

kurtosis

36.36

n_outliers

26

outlier_rate

0.1092

zero_rate

0.2605

ROG2 is a low-cardinality categorical with 7 region-like codes (AFR, EUR, ASI, NAR, SOP, LAM, AUS) across 238 rows and no nulls. The distribution is fairly even — entropy ratio 0.893 and the top value AFR holds just 24.4% — though AUS is a tiny tail with only 2 records. The codes look like geographic groupings (Africa, Europe, Asia, North America, South Pacific, Latin America, Australia). Treatment: One-hot encode; consider merging AUS (n=2) into a neighbouring region or 'Other' to avoid sparse dummies. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

7

top_value

AFR

top_rate

0.2437

cardinality

7

entropy

2.508

entropy_ratio

0.8934

Numeric share (0–99.47) of Muslim population per row, almost certainly one row per country or territory given n=238. The distribution is heavily right-skewed (skew 1.35) with median just 2.51% but mean 22.31%, and 17.2% of rows are exactly zero while 16.8% flag as outliers — a bimodal world where most places have negligible Muslim populations and a minority are overwhelmingly Muslim. Treatment: Consider a log1p or logit transform, or bucket into low/medium/high bands, before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

198

min

0

max

99.47

mean

22.31

median

2.514

std

34.82

q1

0.1012

q3

28.76

iqr

28.66

skew

1.349

kurtosis

0.1114

n_outliers

40

outlier_rate

0.1681

zero_rate

0.1723

RLG3Primary is a small-cardinality numeric code with only 6 unique values spanning 1 to 7 across 238 rows and no nulls. The distribution is bottom-heavy: median is 1.0 and Q1 equals the minimum, yet Q3 reaches 5.75, producing a wide IQR of 4.75 and right skew of 0.98. This looks like an ordinal category (e.g., a primary-rating or grade code) masquerading as a number rather than a continuous measurement. Treatment: Treat as an ordinal categorical and one-hot or ordinal-encode before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

6

min

1

max

7

mean

2.45

median

1

std

2.219

q1

1

q3

5.75

iqr

4.75

skew

0.9751

kurtosis

-0.9467

n_outliers

0

outlier_rate

0

zero_rate

0

This column lists capital cities, with 233 unique values across 238 rows and a null rate of 1.68%. Cardinality is essentially one-per-row (entropy ratio 0.9997), and the only repeat is Kingston appearing twice — likely Jamaica and Norfolk Island sharing the name. Effectively a near-unique label tied to the country/territory record. Treatment: Treat as a near-unique label; drop or use as a join key rather than a model feature. high · anthropic:claude-opus-4-7

n

238

nulls

4 (1.7%)

unique

233

top_value

Kingston

top_rate

0.008547

cardinality

233

entropy

7.862

entropy_ratio

0.9997

This is a country/region population count, with 238 rows and 230 unique values, no nulls. The distribution is extremely right-skewed (skew 9.10, kurtosis 89.06): the median is 5,606,500 but the max reaches 1,463,866,000, dwarfing the Q3 of 23,200,000. About 10.9% of values (26 rows) flag as outliers, consistent with a handful of population giants like China/India-scale entities. Treatment: log-transform before any modelling or aggregation. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

230

min

50

max

1.464e+09

mean

3.459e+07

median

5.606e+06

std

1.378e+08

q1

399,250

q3

2.32e+07

iqr

2.28e+07

skew

9.099

kurtosis

89.06

n_outliers

26

outlier_rate

0.1092

zero_rate

0

CntPeoplesLR is a numeric count of people (likely a left/right group size or attendance metric) with 57 distinct values across 238 rows and a 15.13% null rate. The distribution is severely right-skewed (skew 10.79, kurtosis 129.0): the median is 6.5 and Q3 is 24.75, yet the max reaches 2032 and the mean is 35.27 with std 157.42. 17 outliers (8.42%) pull the tail dramatically, and no zeros are recorded. Treatment: log-transform (or winsorize the upper tail) and impute the ~15% nulls before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

36 (15.1%)

unique

57

min

1

max

2,032

mean

35.27

median

6.5

std

157.4

q1

2

q3

24.75

iqr

22.75

skew

10.79

kurtosis

129

n_outliers

17

outlier_rate

0.08416

zero_rate

0

A numeric count column (likely 'count of people FPG') with only 44 unique values across 238 rows and 28.57% nulls. The distribution is extremely right-skewed (skew 10.07, kurtosis 109.5): median is 4 and Q3 is 12.75, yet the max reaches 1700, producing 18 outliers (10.6% rate) and inflating the mean to 28.04 against a std of 143.69. Treatment: Impute the 28.57% nulls and apply a log1p transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

68 (28.6%)

unique

44

min

1

max

1,700

mean

28.04

median

4

std

143.7

q1

1

q3

12.75

iqr

11.75

skew

10.07

kurtosis

109.5

n_outliers

18

outlier_rate

0.1059

zero_rate

0

Country-level share of population identifying as Hindu, expressed as a percentage. The distribution is dominated by zeros (zero_rate 0.559, median 0) with a long right tail to 82.4, producing extreme skew (6.90) and kurtosis (53.0); 43 of 238 rows (18.1%) flag as outliers, presumably the few Hindu-majority countries. Treatment: Apply a log1p or zero-inflated transform before modelling, since most values are 0 with a heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

106

min

0

max

82.4

mean

2.01

median

0

std

8.927

q1

0

q3

0.2745

iqr

0.2745

skew

6.898

kurtosis

53.02

n_outliers

43

outlier_rate

0.1807

zero_rate

0.5588

A numeric share/percentage feature called PercentOtherSmall, with 238 rows and 199 unique values, no nulls, but 16.4% zeros and a long right tail (median 0.29, max 12.84). Skew of 5.05 and kurtosis 39.4 with 15 outliers (6.3%) signal an extremely heavy-tailed distribution. Despite the name, values exceed 1, so this is not bounded as a 0–1 proportion. Treatment: Apply a log1p transform and consider a zero-inflation indicator before modelling. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

199

min

0

max

12.84

mean

0.6962

median

0.2884

std

1.242

q1

0.01289

q3

0.9557

iqr

0.9428

skew

5.052

kurtosis

39.39

n_outliers

15

outlier_rate

0.06303

zero_rate

0.1639

This column appears to be the percentage of Buddhists per country (or similar geographic unit), with 238 rows and 125 unique values. The distribution is extremely right-skewed (skew 4.59, kurtosis 20.4): nearly half the rows are zero (zero_rate 0.48), the median is 0.004%, yet the max reaches 88.74%. Saturn flagged 38 outliers (16% of rows), reflecting the handful of Buddhist-majority countries dominating the tail. Treatment: Apply a log1p or similar transform before modelling to tame the heavy right tail. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

125

min

0

max

88.74

mean

3.701

median

0.004281

std

14.74

q1

0

q3

0.2949

iqr

0.2949

skew

4.592

kurtosis

20.42

n_outliers

38

outlier_rate

0.1597

zero_rate

0.479

JPScaleCtry holds an integer 1–5 rating with only 5 unique values across 238 rows and no nulls, consistent with a Likert-style country-level scale. The distribution leans high (mean 3.62, median 4, Q1=3, Q3=5) with a left skew of -0.78, indicating most respondents cluster at the upper end. No outliers are flagged. Treatment: Treat as an ordinal Likert feature; consider ordered encoding rather than raw numeric use. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

5

min

1

max

5

mean

3.622

median

4

std

1.473

q1

3

q3

5

iqr

2

skew

-0.7839

kurtosis

-0.8065

n_outliers

0

outlier_rate

0

zero_rate

0

This column reports the percentage of Christians per row (likely country or region), spanning the full 0.02% to 100% range across 238 nearly unique values. The distribution is strongly bimodal-feeling: the median (75.3%) sits far above the mean (58.2%), with a wide IQR from 11.7% to 90.9% and negative skew (-0.54), suggesting many heavily Christian populations alongside a substantial cluster of very low-share rows. No nulls, no zeros, and no statistical outliers despite the extreme spread. Treatment: Use as-is or rescale to 0-1; consider pairing with other religion-share columns since values are bounded percentages. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

237

min

0.0165

max

100

mean

58.17

median

75.3

std

37.03

q1

11.72

q3

90.92

iqr

79.2

skew

-0.5364

kurtosis

-1.392

n_outliers

0

outlier_rate

0

zero_rate

0

ISO3 is the standard three-letter country code, with all 238 values unique (AFG, ALB, DZA, ASM, ...) and zero nulls. Maximum entropy ratio (≈1.0) and a top_rate of 0.0042 confirm one row per country, making this a clean primary key for the table. Treatment: use as the join key to merge country-level data; do not feed into models as a feature. high · anthropic:claude-opus-4-7

n

238

nulls

0 (0.0%)

unique

238

top_value

AFG

top_rate

0.004202

cardinality

238

entropy

7.895

entropy_ratio

1