saturn

This is a 50-row, 107-column sample from the Joshua Project API describing Arab and related Muslim people groups across 41 countries. The dataset is dominated by one affinity bloc ('Arab World', 100%) and one religion ('Islam', 98%), so the interesting variation lies in geography, population size, and reachedness rather than in identity fields. Look first at Population and PopulationPGAC, which are heavily right-skewed (max 2.22M and 7.56M respectively, with multiple outliers) and at PCIslam, which is high but varies from 25% to 100%. JPScaleText shows that 76% of groups are classified 'Unreached', making that the most actionable signal alongside Continent/RegionName for where these groups sit. Note also the high null rates on language, Bible-translation, and nomadic descriptors (86–98% missing), which limits any analysis of those attributes.

ROL3 holds 3-letter codes (likely ISO 639-3 language tags such as 'eng', 'arz', 'ary', 'apc', 'afb') across 50 complete rows with 10 distinct values. Distribution is skewed toward Levantine/Gulf Arabic variants: 'apc' covers 36% and 'afb' another 13/50, while six codes appear only once or twice. Entropy ratio of 0.75 indicates moderate concentration rather than uniform spread.

Attribution string for the image accompanying each row, naming photographer and source platform. Just 5 distinct credits cover all 50 rows, with 'Hashim Abdullah - Pixabay' alone accounting for 56% and the top three Pixabay/Flickr contributors covering 48 of 50 entries. Two credits ('Link Up Africa', 'Claudiovidri - Shutterstock') appear only once, suggesting a long tail of incidental sources.

Categorical column capturing the dominant religion of each record, with only two observed values across 50 rows. The distribution is severely imbalanced: Islam accounts for 49 of 50 entries (top_rate 0.98) and Christianity for just 1, yielding an entropy ratio of 0.14. With effectively no variance, this column carries almost no discriminative signal.

Country field with 41 distinct values across 50 rows and no nulls. The distribution is essentially flat — entropy ratio is 0.986 and the most common value, United Arab Emirates, appears just twice (4%). Nine countries tie at 2 occurrences each, the rest are singletons, hence the long_tail alert.

RegionName is a categorical geographic grouping with 11 distinct regions across 50 rows and no nulls. The distribution is uneven: 'Africa, North and Middle East' alone accounts for 32% (16/50), and the three African regions together dominate the column. Entropy ratio of 0.86 indicates spread is fairly even given the cardinality, but several regions ('Australia and Pacific', 'America, Latin') appear only once.

BibleYear appears to be a metadata field capturing the publication year or year-range of a Bible edition, with values like "1890-2024", "1382-2020", and "2021". The column is almost entirely empty: 92% null with only 4 of 50 rows populated and 3 distinct values. Format is inconsistent, mixing single years with hyphenated ranges, which blocks numeric parsing.

RLG3PC is a numeric column that is entirely constant: all 50 rows hold the value 6.0, with zero variance and only 1 unique value. There is no information for a model to learn from, and no nulls or outliers to caveat.

Population counts across 50 rows, ranging from 200 to 2,221,000 with a median of just 46,500 versus a mean of 264,074. The distribution is severely right-skewed (skew 2.52, kurtosis 5.78) and 12% of rows (6 values) flag as outliers, indicating a few very large populations dominate an otherwise small-town dataset. No nulls or zeros, and 49 of 50 values are unique.

The column is named "Resources" and contains 50 non-null entries, but saturn skipped profiling it so its kind is unknown and no descriptive stats (uniqueness, distribution, type) are available. Without further signals, its content and structure cannot be characterized from this evidence.

Binary Y/N flag indicating whether some 'least reached PGAC' condition was met, with no nulls across 50 rows. The split is nearly balanced (28 N, 22 Y; top_rate 0.56) and entropy_ratio of 0.99 confirms maximal informativeness for a binary feature.

Counts the number of languages spoken, but with only 2 unique values across 50 rows it is effectively a binary indicator of monolingual vs bilingual. The mean of 1.04 and median of 1.0 show 48 of 50 records sit at 1, with just 2 outliers at 2.0 driving the extreme skew (4.69) and kurtosis (20.04).

GSEC is a binary categorical field with exactly two values, "1" and an empty string, split perfectly 25/25 across the 50 rows. The maximum entropy (1.0) confirms a balanced flag, but the empty string rather than "0" or null suggests the absent state is encoded as a blank string rather than a true missing value.

AudioRecordings is a categorical flag that takes the single value 'Y' across all 50 rows, with zero nulls and entropy of 0. Because cardinality is 1 and top_rate is 1.0, the column carries no information and cannot discriminate between records.

PercentAdherents holds numeric percentages stored as strings, with 29 distinct values across 50 rows and no nulls. The mode is "0.000" at 12% of rows, and entropy ratio 0.942 indicates a very flat distribution with a long tail of small-frequency values. The mix of fractional (0.200, 0.500) and whole-number (5.000, 6.000) entries suggests the values are raw percentages rather than proportions.

ROP1 is a categorical column holding a single constant value 'A001' across all 50 rows, with zero nulls and entropy of 0.0. It carries no information for modelling or segmentation since cardinality is 1 and top_rate is 1.0.

A binary categorical field with only the values "1" and "2", split 28/22 across 50 rows. The near-maximal entropy ratio (0.99) indicates an almost balanced two-class distribution with no nulls. The column name suggests a Japanese PGA scale code, likely an ordinal seismic-intensity or rating bucket.

Numeric column holding geographic latitude in degrees, with all 50 values unique and no nulls. The range spans -33.87 to 59.11, consistent with worldwide coordinates, and the distribution is mildly left-skewed (-0.46) with a mean of 22.28 sitting below the median of 24.12. Only one outlier (2%) is flagged, suggesting one row sits far from the otherwise broad spread (IQR 26.18).

Categorical label naming the people group in-country, with only 7 distinct values across 50 rows and no nulls. The distribution is heavily concentrated on Arab variants: 'Arab' alone covers 54% of rows, and the top three Arab-prefixed labels account for 46 of 50 entries, leaving a long tail of singletons like 'Tuareg, Air' and 'Amri'. Entropy ratio of 0.65 confirms the imbalance flagged by the long_tail alert.

Window1040 is a binary Y/N flag, almost perfectly balanced with 26 'Y' and 24 'N' across 50 rows. Entropy ratio of 0.999 confirms a near-maximum-uncertainty split, and there are no nulls. The name suggests a windowed indicator (possibly a 1040-period rolling event flag), but the evidence does not confirm its semantics.

URL pointing to a people-group map image hosted on joshuaproject.net, one per row. 48% of the 50 rows are empty strings, so the field is missing more often than populated, and a single map (m00007.png) accounts for 9 of the 26 non-blank entries. With 17 unique values across 50 rows and a long_tail alert, most distinct URLs appear only once.

URLs to country pages on joshuaproject.net, with the two-letter country code as the path suffix. With 41 unique values across 50 rows and entropy ratio 0.986, the column is near-unique; the most frequent URL (UAE) appears just twice (top_rate 0.04). The base domain is constant, so the country code is the only informative part.

Numeric-looking field stored as a categorical with only 3 distinct values across 50 rows, and 96% of rows share the single value '0.197'. The other two values ('0.103' and '0.265') each appear exactly once, giving an extreme imbalance and an entropy ratio of just 0.178. This looks like a principal-component or aggregate score that has been collapsed/repeated for nearly every record, leaving almost no signal.

CountOfProvinces was skipped by the profiler, so no type, uniqueness, or distribution stats are available beyond a row count of 50 with no nulls. The name suggests an integer tally of provinces per record, but this cannot be confirmed from the evidence. No further signal is present to flag skew, duplicates, or range.

Likely a percentage of evangelical adherents (PGAC denomination grouping) stored as strings rather than floats, with only 5 distinct values across 50 rows. The distribution is severely lumpy: '1.892' covers 56% of rows and the top three values ('1.892', '0.233', '0.023') account for 48 of 50 observations, suggesting these are imputed or default category codes rather than true continuous measurements.

This appears to be a descriptive label for a nomadic lifestyle classification, but it carries almost no information in this sample. 90% of rows are null, and the 5 non-null rows all hold the single value 'Agro-Pastoralists' (top_rate 1.0, cardinality 1, entropy 0.0). As-is, the column cannot discriminate between records.

MapCredits holds attribution strings for the map associated with each row, citing sources like Joshua Project, GMI, ESRI, and Bethany World Prayer Center. Nearly half the rows (24 of 50) carry an empty string rather than a null, and a single credit to 'Bethany World Prayer Center' covers another 14 rows, leaving only 7 distinct values across the column. The dominance of blanks alongside non-null status is the main surprise — missingness is encoded as empty text, not NULL.

Binary Y/N flag indicating whether each record has an associated 'Jesus Film' resource. The column is complete (null_rate 0.0) with only 2 unique values, heavily skewed toward 'Y' at 82% (41 of 50), leaving just 9 'N' cases.

HowReach holds free-text outreach suggestions, likely missionary engagement strategies for various people groups. The column is dominated by empty strings (62% top_rate, 31 of 50 rows blank), and every non-blank value is unique, yielding 20 distinct values across 50 rows with no nulls flagged. Entropy ratio of 0.60 plus the long_tail alert confirm this is essentially sparse prose, not a categorical variable.

PCIslam appears to be a percentage measure of Islamic affiliation per record, ranging 25.0 to 100.0 with a median of 95.99 and mean 91.12. The distribution is heavily left-skewed (skew -2.65, kurtosis 7.39) with a tight IQR of 6.55 between Q1 92.93 and Q3 99.48, yet 8 outliers (16%) sit far below that cluster. Most observations are near-saturation while a small tail of low-share records pulls the mean down.

NTYear appears to be a free-form annotation about a 'NT' year status, mixing a yes/no flag with single years (e.g. 2005, 1932, 2012) and year ranges (e.g. 1879-1989, 1990-2003). The format is inconsistent: 'Yes' dominates at 62% of non-null entries, while 42% of all rows are null and the remaining cells split across 7 heterogeneous values. This is effectively two or three different fields collapsed into one string column.

RLG4 is a numeric column that is effectively unusable: 86% of its 50 rows are null, and every one of the remaining values equals 20.0 (min, median, max, std all confirm this). With a single distinct value and no variance, it carries no information for modelling.

AffinityBloc is a categorical grouping label, but every one of the 50 rows holds the same value, "Arab World". With cardinality 1 and entropy 0, this column carries no information for distinguishing records in this slice.

NaturalName is a low-cardinality categorical label, likely an ethnic or linguistic group identifier, with 7 distinct values across 50 rows and no nulls. The distribution is heavily concentrated: 'Arab' alone covers 54% of rows, and together with 'Gulf-spoken Arab' (11) and 'Omani Arab' (8) accounts for 46 of 50 records, leaving four singleton categories in a long tail. Entropy ratio of 0.65 confirms the imbalance.

This column appears to be a percentage-based metric (likely 'Percent Christian' from a PGAC indicator) stored as strings, with only 5 distinct values across 50 rows. The distribution is heavily concentrated: '14.741' accounts for 56% of records, followed by '0.935' (12 rows) and '0.066' (8 rows), suggesting these are repeated category-level constants rather than per-row measurements. The presence of just 5 unique values for what looks like a continuous percentage is suspicious and points to either aggregated/joined reference data or a coarse bucketing.

This is a categorical column naming a primary language, dominated by Arabic dialects across 10 distinct values in 50 rows. Levantine Arabic leads at 18/50 (36%), followed by Gulf (13) and Omani (8); non-Arabic entries are rare (Swahili 2, plus singletons for Tamajeq, English, etc.). Entropy ratio of 0.75 indicates moderate concentration without a single overwhelming class, and there are no nulls.

Numeric count of countries with only 4 unique values across 50 rows, ranging 1 to 28 with median 28 and mean 19.88. The distribution is heavily concentrated at the maximum (median equals max, Q3 equals max), indicating most rows hit the ceiling of 28 while a minority sit much lower. Negative kurtosis (-1.52) and mild left skew (-0.43) confirm a bimodal-like spread rather than a smooth distribution.

PeopleID2 is stored as numeric but behaves like a categorical key, with only 3 unique values across 50 rows and an IQR of 0 because Q1, median, and Q3 all equal 111. The mean (115.04) is pulled above the median by 2 outliers reaching up to 307, producing extreme skew (6.85) and kurtosis (44.93). No nulls or zeros are present.

Free-text ethnographic summaries describing people groups, with 21 unique values across 50 rows and a 60% top rate driven entirely by empty strings (30 of 50). The non-empty entries are long, prose paragraphs about Tuareg, Arab, and other groups, so this is descriptive content rather than a category. Entropy ratio of 0.61 and the long_tail alert confirm most non-empty values appear only once.

Free-text commentary describing barriers to gospel outreach for various people groups, one paragraph per row. 30 of 50 rows (top_rate 0.6) are empty strings, and the remaining 20 entries are essentially unique, yielding 21 distinct values and entropy_ratio 0.61. Despite the categorical kind, the content is prose passages about Islam, identity, and mission access, not a bounded label set.

ROP2 is a categorical column with only 3 distinct codes (C0013, C0219, C0019) across 50 rows and no nulls. The distribution is extremely lopsided: C0013 covers 96% of rows while the other two codes appear once each, yielding an entropy ratio of just 0.178. As a near-constant feature it carries almost no signal.

RLG3 is a near-constant numeric feature: 49 of 50 rows take the value 6.0 (median, Q1, and Q3 all equal 6.0), with a single outlier at 1.0 producing extreme negative skew (-6.86) and kurtosis (45.02). With only 2 unique values and an IQR of 0, this behaves more like a degenerate flag than a continuous measurement.

PercentEvangelical appears to be a numeric share of evangelicals stored as strings, with 18 distinct values across 50 rows and no nulls. The distribution is heavily concentrated on small values: '0.000' and '0.500' tie for the mode at 8 occurrences each (16% top_rate), while values up to '2.500' form a long tail. High entropy_ratio (0.88) indicates the mass is spread fairly evenly across the small set of bins despite the long_tail alert.

Binary Y/N flag, likely indicating whether some 'least reached' status applies to each record. The class is imbalanced toward Y at 76% (38 of 50), with N covering the remaining 12. No nulls, and entropy ratio of 0.80 reflects the moderate skew.

Categorical continent label with 6 distinct values across 50 rows and no nulls. Asia dominates at 38% (19 rows), followed by Africa (14) and Europe (10), while Australia and South America appear only once each. The skewed distribution and high entropy ratio (0.80) suggest reasonable spread but with a clear Asia/Africa concentration.

JPScalePC is a categorical column that holds the single value "1" across all 50 rows, giving it cardinality 1 and zero entropy. With a top_rate of 1.0 and no nulls, it carries no information and likely represents a constant flag or scale parameter that was never varied in this slice.

Categorical label describing a Joshua Project reach scale, with 4 distinct levels across 50 rows and no nulls. The distribution is heavily skewed: 'Unreached' covers 76% of rows, while 'Superficially Reached' appears just once, giving an entropy ratio of 0.54. Class imbalance will dominate any model trained on this field.

SecurityLevel takes only 3 distinct integer values across 50 rows (min 0, max 2, median 2), so it reads as an ordinal category encoded as a number rather than a continuous measure. The distribution is bimodal-leaning: 42% of rows are zero while the median sits at 2, and the strongly negative kurtosis (-1.90) confirms a flat, multi-peaked shape with no outliers.

This is a categorical flag (likely 'is in LR Top 100') that takes the single value 'N' across all 50 rows. With cardinality 1 and entropy 0.0, it carries no information for any downstream model. The 'imbalance' alert here reflects total constancy rather than skew.

This column records the primary religion classification (PGAC), but every one of the 50 rows holds the single value "Islam". With cardinality of 1 and entropy of 0.0, it carries no information for modelling or segmentation.

Likely a percentage of non-religious population per row, with 50 records and only 6 distinct values. The distribution is dominated by zeros (zero_rate 0.755) with median and IQR both 0, yet a long right tail pushes the max to 10.0 and flags 12 outliers (24.5%). Skew of 1.89 and one missing value (null_rate 0.02) confirm a sparse, heavily right-skewed feature.

This column holds photo credit URLs (Pixabay and Flickr links), but with only 3 unique values across 50 rows it functions as a coarse source tag rather than a per-record citation. The top URL covers 58.3% of non-null rows (28 of 50), suggesting the same stock photo is reused widely. Null rate is 4%.

Binary Y/N flag indicating whether a photo carries a Creative Commons license, with no nulls across 50 rows. The distribution is heavily skewed toward 'N' at 84% (42 of 50), leaving only 8 records flagged 'Y'.

Free-text prayer prompts for unreached people groups, with 60% of the 50 rows being empty strings and the remaining 20 entries each unique multi-sentence paragraphs. The dominance of the blank value (top_rate 0.60) coexists with very high textual diversity among non-blank rows, hence the long_tail alert and entropy_ratio of 0.61. No nulls are recorded, but the empty string is functioning as a missing-value sentinel.

This column holds URLs to people-group profile photos hosted on joshuaproject.net, one per row with no nulls. Despite 50 rows, only 5 distinct images appear, and a single photo (p10375.jpg) covers 56% of records while the top three URLs account for 48 of 50 — suggesting many rows share the same people-group identity rather than being unique entities.

ROG2 looks like a regional grouping code with 6 categories (ASI, AFR, EUR, NAR, AUS, LAM), fully populated across all 50 rows. Distribution is moderately concentrated — ASI leads at 38% (19/50) and AFR follows at 14, while AUS and LAM appear only once each. Entropy ratio of 0.80 indicates fairly even spread among the top regions but with thin tails.

This is a categorical license-text field for photo Creative Commons versioning, with only 2 distinct values across 50 rows. 84% of entries are empty strings (42/50), and the remaining 8 carry 'CC BY-NC-SA 2.0' — there are no nulls, just blanks standing in for missing licenses. Entropy ratio of 0.63 reflects this binary, heavily imbalanced split.

Geographic longitude coordinates spanning -118.3 to 151.2, covering most of the globe's east-west range with all 50 values unique. The distribution is left-skewed (skew -0.77) with a median of 39.4 sitting well above the mean of 27.5, and 7 outliers (14%) flag locations far from the central cluster around Europe/Asia.

This column holds URLs to Joshua Project gauge images (gauge-1 through gauge-4), almost certainly a visual encoding of an ordinal progress/status scale. Distribution is heavily skewed: 76% point to gauge-1.png, while gauge-3.png appears only once across 50 rows. With just 4 unique values and no nulls, it's a low-cardinality categorical masquerading as a URL.

This is a categorical column naming an official language, with 21 distinct values across 50 rows and no nulls. The distribution is heavily skewed: 'Arabic, Standard' alone covers 36% of rows, followed by English (8) and French (5), while a long tail of languages like Swahili, Ukrainian, Sinhala and Bulgarian appear only once. Entropy ratio of 0.77 confirms concentration at the top despite the wide vocabulary.

Binary Y/N flag indicating whether photo permission has been granted, with no missing values across 50 rows. The distribution is severely imbalanced: 'N' covers 49 of 50 rows (top_rate 0.98) with only a single 'Y', yielding entropy_ratio of 0.14. With one positive case, this column carries almost no discriminative signal in the current sample.

PCHinduism appears to be a per-row count or percentage related to Hinduism, with 95.9% of values being zero and only 3 distinct values across 50 rows. The distribution is extremely sparse and right-skewed (skew 5.96, kurtosis 35.36), with a max of 6.0 standing out as an outlier against a median and IQR of 0. Effectively a near-constant feature with rare nonzero spikes.

PeopleID3 is a numeric identifier-like field with only 5 unique values across 50 rows, clustered tightly around 10375-10376 (IQR of 1.0). The distribution is severely left-skewed (skew -5.59, kurtosis 31.2) because at least one value drops to 10208 while the bulk sits near the max of 10378, producing a 20% outlier rate. Despite being typed as numeric, the near-constant range and low cardinality suggest this behaves as a categorical key rather than a measurement.

PeopleID1 is flagged as constant: every one of the 50 rows holds the value 10, with zero variance and a single unique value. Despite the 'ID' name, it carries no identifying information and cannot distinguish records. There is no null or outlier activity to interpret.

Saturn skipped this column, so no profiling stats were computed beyond row count (50) and a null rate of 0.0. The name 'SpeakNationalLang' suggests a binary or categorical indicator of whether a respondent speaks the national language, but kind is 'unknown' and n_unique is missing, so the actual value distribution cannot be confirmed from this evidence.

PortionsYear is a low-cardinality categorical with 9 unique values across 50 rows and a 16% null rate. Most entries are year ranges (e.g., "1939-2021" at 42.9% and "2009-2024"), but 4 rows contain the string "Yes", indicating a mixed/dirty schema where a boolean answer was recorded in a date-range field. Entropy ratio of 0.70 and a long-tail alert reflect many singleton ranges alongside two dominant values.

This column records the primary religion of a people-cluster (PC), but every one of the 50 rows holds the value "Islam". With cardinality 1 and entropy 0, it carries no information for distinguishing records in this slice.

PCUnknown is a numeric column that is effectively constant: every one of the 49 non-null observations is exactly 0, and 2% of rows are null. There is no variance, no spread, and no outliers, so the column carries no information as currently populated.

Binary Y/N flag indicating whether a profile text exists, with no nulls across 50 rows. The distribution is heavily imbalanced: 'Y' covers 45 of 50 (top_rate 0.9) versus only 5 'N', giving an entropy ratio of 0.47.

PCOtherSmall is a numeric count-like feature that is essentially zero for nearly everyone — 93.9% of the 49 non-null rows are 0 and only 3 distinct values appear. The distribution is extremely right-skewed (skew 6.41, kurtosis 40.46) with a max of 7 driving 3 outliers (6.1% outlier rate), so almost all signal lives in a tiny tail.

BibleStatus is a small-range integer code with only 4 distinct values spanning 2 to 5, mean 3.5 and median 4. The tight IQR (3 to 4) and absence of zeros or nulls suggest it's an ordinal status flag rather than a true numeric measurement. Mild left skew (-0.38) indicates most records sit at the higher end of the scale.

Frontier is a binary Y/N flag with no nulls across 50 rows. The distribution is heavily skewed toward 'N' at 84% (42 of 50), leaving only 8 'Y' cases, which limits its discriminative power.

MapAddress holds filenames of map images (e.g. 'm00007.png', 'm10375_ke.png'), with country/region suffixes appearing on some variants. Nearly half the rows (24/50) are empty strings and a single file 'm00007.png' covers 9 more, leaving a long tail of 15 other filenames at 1-2 occurrences each. Cardinality is 17 unique values with entropy ratio 0.68, so the column is dominated by the blank and one hero image.

PeopleID3ROG3 looks like a per-row identifier: every one of the 50 rows holds a distinct alphanumeric code (5 digits followed by 2 letters, e.g. '10208NG'), giving cardinality 50 and entropy_ratio 1.0. Top_rate is 0.02 because no value repeats, and there are no nulls. The long_tail alert simply reflects that uniqueness rather than any skew.

ROP3 is a near-constant numeric reading clustered tightly around 100425 (median) with an IQR of just 2, yet 20% of values are flagged as outliers and the minimum drops to 100161 versus a max of 100431. The extreme negative skew (-5.53) and kurtosis above 30 indicate a heavy left tail dragging the mean (100418.74) below the median. With only 5 unique values across 50 rows, this looks like a sensor or pressure-style measurement that is mostly stuck at one level with occasional sharp dips.

PrimaryLanguageDialect is a categorical field that is effectively empty: 98% of the 50 rows are null, and the single non-null value is the string "Air" — which doesn't read like a language or dialect at all. With only 1 unique value, entropy is 0, so the column carries no signal in this sample and the lone value looks suspect.

JPScale is a small-integer ordinal feature with only 4 distinct values ranging from 1 to 4, where the bulk of records sit at 1 (median, Q1 and Q3 all equal 1.0, IQR 0.0). The distribution is heavily right-skewed (skew 2.29, kurtosis 4.44) and 24% of rows (12 of 50) flag as outliers simply because anything above 1 deviates from the dominant value. Mean 1.38 against std 0.81 confirms most mass is at the floor with a long thin tail toward 4.

This column is a flag indicating whether audio recordings exist, but every one of the 50 rows holds the value "Y". Cardinality is 1 and entropy is 0, so it carries no information for any downstream task.

PCBuddhism appears to be a numeric feature (likely a per-capita or principal-component-style indicator for Buddhism) that carries no information in this sample: every one of the 49 non-null values is exactly 0.0, with a 2% null rate. The constant alert and zero_rate of 1.0 confirm there is no variance to model.

This column appears to label ethnic or people-group identities across countries, with only 5 unique values across 50 rows and no nulls. The distribution is heavily skewed toward 'Arab' (28 of 50, top_rate 0.56), with 'Arab, Arabic Gulf Spoken' and 'Arab, Omani' as the next most common, while 'Tuareg, Air' and 'Amri' appear just once each. Entropy ratio of 0.69 confirms moderate concentration rather than uniform spread.

This column appears to hold a Creative Commons license URL associated with a photo, but it is overwhelmingly empty: 42 of 50 rows are blank strings and only 8 carry the single license value 'https://creativecommons.org/licenses/by-nc-sa/2.0/'. With just 2 unique values and a top_rate of 0.84, it functions more as a binary licensed/unlicensed flag than a true URL field. Note that nulls are reported as 0.0 because the missing entries are empty strings rather than true nulls.

MapCCVersionText is a categorical column that contains a single value — the empty string — across all 50 rows. Cardinality is 1, entropy is 0, and null_rate is 0.0, so the field is technically populated but carries no information.

This appears to be a per-capita or principal-component-style 'PercentChristian' score, stored as strings with only 3 distinct values across 50 rows. It is overwhelmingly degenerate: the value '0.997' covers 48/50 rows (top_rate 0.96), with '0.116' and '1.344' each appearing once, yielding an entropy ratio of just 0.178. The two outlier values look anomalous relative to the dominant 0.997 and may be data-entry artefacts or genuine extremes worth investigating.

Binary Y/N flag indicating whether a record is nomadic, with no nulls across 50 rows. The distribution is heavily imbalanced: 'N' covers 45 of 50 (top_rate 0.9) while 'Y' appears only 5 times, yielding low entropy_ratio of 0.47.

Free-text prayer prompts about Christian outreach to Arab/Muslim people groups, stored as a categorical but functionally a short-document field. 42 of 50 rows (top_rate 0.84) are empty strings and the remaining 8 are all unique long sentences, giving 9 distinct values and an entropy ratio of 0.35. The long_tail alert reflects this empty-vs-unique split rather than meaningful category structure.

RLG3PGAC is a numeric column that holds the constant value 6.0 across all 50 rows, with zero variance and no nulls. Since min, max, mean, and both quartiles are all 6.0, the column carries no information for modelling or analysis.

ISO3 holds three-letter country codes (ARE, CAN, EGY, KEN...), making it a country identifier. With 41 unique values across 50 rows and entropy ratio 0.986, it is near-uniform with only nine countries appearing twice; no nulls. The long_tail alert reflects that most countries appear exactly once.

Phonetic pronunciation guides for what appear to be Arabic-related labels, with most variants ending in 'AE-rub' (likely 'Arab'). The top value 'AE-rub' covers 55% of rows (27/50), and the top three values account for 46 of 50 entries, leaving three singleton long-tail spellings like 'AH-eer TWA-reg' and 'KEN-yun AE-rub'. Cardinality is just 6 with a 2% null rate, suggesting a controlled vocabulary rather than free text.

PhotoAddress holds JPG filenames (e.g., p10375.jpg), so it points to image assets associated with each row. With only 5 unique values across 50 rows and the top file p10375.jpg covering 56% of records, the same images are reused heavily rather than being row-specific. Entropy ratio of 0.69 confirms a skewed distribution dominated by three filenames, while two others appear just once each.

RegionCode is stored as an integer but only takes 11 distinct values across 50 rows (min 1, max 12), so it is almost certainly a categorical region identifier rather than a true numeric quantity. The distribution is roughly centered (mean 7.28, median 7) with low skew (-0.09) and one flagged outlier, but those moments are not meaningful for a code. No nulls or zeros are present.

Free-text geographic descriptions of where a group is located within a country, ranging from single words like "Scattered" to multi-clause sentences naming provinces and landmarks. The column is 72% null and only 14 of 50 rows carry values, yet entropy_ratio is 0.99 with 13 unique strings across 14 non-nulls — essentially every response is bespoke. The top value "Widespread." appears just twice, so there is no usable category structure.

JF is a binary Y/N flag with no missing values across 50 rows. The distribution is imbalanced: 'Y' accounts for 41 of 50 records (top_rate 0.82) versus 9 'N's, yielding entropy of 0.68.

PopulationPGAC appears to be a population count tied to some PGAC grouping, with values ranging from 101,000 to 7,562,600 across 50 rows. Only 5 unique values populate the column, so the 'numeric' framing is misleading — it behaves more like a coarse categorical bucket. The right-skew (1.03) and 26% outlier rate stem from a small number of rows carrying the largest population value far above the Q3 of 3,096,000.

This column holds URLs to expanded people-group map PDFs hosted on joshuaproject.net, one per row. It is mostly empty: 38 of 50 rows (top_rate 0.76) are blank strings, leaving only 11 distinct values across the 50 records with a long tail of near-unique links. Despite null_rate being 0, the dominant value is an empty string, so true coverage is roughly a quarter of rows.

The column 'TranslationNeedQuestionable' was skipped by the profiler, so no type, uniqueness, or value statistics are available beyond a row count of 50 with no nulls. The name suggests a boolean or flag indicating whether a translation need is in doubt, but this cannot be confirmed from the evidence. No distributional signals are present to flag.

A low-cardinality categorical with 3 distinct values ('1','2','3') across 50 rows and no nulls, likely a class label or category code. The distribution is imbalanced: '1' dominates at 68% (34/50) while '2' and '3' account for just 7 and 9 rows respectively, giving an entropy ratio of 0.77.

PhotoCopyright is a binary Y/N flag, almost certainly indicating whether a photo carries a copyright restriction. The distribution is severely imbalanced: 49 of 50 rows are 'N' and only 1 is 'Y', giving an entropy ratio of just 0.14. With effectively no variance, this column carries little signal on its own.

NTOnline is a categorical flag that takes only the value 'Y' across all 41 non-null rows, with 18% of records null. Effectively a constant indicator with no discriminative information, plus a non-trivial missingness rate that may itself be the only signal.

This is a categorical flag that takes the value "Y" for all 50 rows, giving cardinality 1 and entropy 0.0. With a single constant value it carries no information and cannot discriminate between records. The name suggests it once tracked a 'least reached PC' status, but here it is degenerate.

ROG3 holds two-letter country codes (AE, CA, EG, KE, SO, etc.), making it a geographic categorical feature. With 41 unique values across 50 rows and a top rate of just 0.04, the column is almost a unique-per-row identifier — entropy ratio 0.9862 confirms an extremely flat, long-tail distribution. No nulls, but the sample is too thin for any country to dominate.

This column records a religious subdivision, but it is overwhelmingly empty: 86% of the 50 rows are null, and every one of the 7 populated rows is 'Sunni'. With cardinality of 1 and entropy of 0, the field carries no discriminative signal in this sample.

Numeric count-like column where 93.9% of the 49 non-null values are zero and only 3 distinct values appear. The distribution is highly right-skewed (skew 4.45, kurtosis 19.79) with a max of 10 against a median of 0, producing 3 outliers (6.1%). One null is present.

Categorical grouping of people clusters, with only 3 distinct values across 50 rows and no nulls. The distribution is extremely imbalanced: 'Arab, Arabian' covers 96% of rows, leaving 'Tuareg' and 'Arab, Sudan' with a single record each, yielding a very low entropy ratio of 0.178.

Binary Y/N flag indicating Indigenous status, with 'N' dominating at 86% (43 of 50) versus 7 'Y' records. The column is fully populated with no nulls and only 2 distinct values, yielding a low entropy ratio of 0.58. The class imbalance is notable for any modelling use.

MapCreditURL appears to be a metadata field intended to hold a URL crediting a map's source, but every one of the 50 rows is an empty string. Cardinality is 1, entropy is 0, and the top value (empty) accounts for 100% of records, so the column carries no information.

MapCopyright is a categorical column that holds the single value "N" across all 50 rows, giving it zero entropy and a top_rate of 1.0. With cardinality of 1 and no nulls, it carries no information for any downstream model or comparison.

This column appears to be a metadata field intended to hold a Creative Commons version URL for a map, but every one of the 50 rows contains an empty string. Cardinality is 1 with entropy of 0.0, so it carries no information whatsoever.

This column holds Joshua Project people-group URLs, with each row pointing to a /people_groups/{id}/{country} path. All 50 rows are unique (cardinality 50, entropy_ratio 1.0, top_rate 0.02) and there are no nulls, so it functions as a per-row identifier rather than a categorical feature. The URL stems repeat (e.g. 10375 appears across TZ, UP, AG, AS, AU, BA), suggesting the same people group is tracked across multiple country codes.