saturn

/home/coolhand/html/datavis/data_trove/data/quirky/lighthouses.json 14,585 rows sample n=14,585 seed 42 2026-06-22T00:32:58+00:00

Overview

Source/home/coolhand/html/datavis/data_trove/data/quirky/lighthouses.json
Total rows14,585
Profiled sample14,585
Columns13
Generated2026-06-22T00:32:58+00:00
Show data table
Per-column null rate across the corpus.
columnkindnull %
nametext0.0%
latnumeric0.0%
lonnumeric0.0%
countrycategorical99.6%
heightcategorical90.2%
year_builtcategorical93.2%
operatorcategorical92.7%
seamark_typecategorical48.0%
light_charactercategorical71.3%
heritagecategorical96.9%
wikipediatext86.2%
osm_idnumeric0.0%
osm_typecategorical0.0%

Insights opt-in

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

Dataset medium anthropic:default

This dataset contains 14,585 lighthouse and seamark records sourced from OpenStreetMap, covering navigational lights and related structures worldwide. The most immediately striking feature is that many descriptive columns — country, operator, year_built, height, and heritage — have null rates of 90% or higher, meaning the richest analysis must focus on the minority of well-filled records. Two columns worth close inspection are seamark_type, which cleanly splits records into light_minor (3,496), light_major (3,051), and landmark (716) with no nulls beyond the 48% gap, and light_character, where 'Fl' (flashing) dominates at 74.7% of non-null values across 19 pattern types. Geographically, all 14,585 records carry latitude and longitude, revealing a notable left skew in latitude (mean 34.5°, median 40.8°) with 1,295 outliers, suggesting a clustering of records in the Northern Hemisphere with some Southern outliers worth mapping.

wikipedia high anthropic:default

This column contains Wikipedia article titles or slugs for lighthouse-related entries, as evidenced by top words including 'lighthouse', 'light', 'fr:phare', 'es:faro', 'de:leuchtturm', and 'pt:farol' — indicating multilingual cross-references. The column is extremely sparse, with an 86.23% null rate across 14,585 rows, meaning only ~2,027 rows carry a value. Despite being flagged near-unique, there are 43 duplicate values across 1,965 unique entries, which is low but worth noting if this is intended as a one-to-one reference.

height medium anthropic:default

This column represents a numeric height measurement stored as a categorical/string type, with values that appear to be small integers (range visible: 6–20, likely in inches or some domain-specific unit). The most alarming signal is a null rate of 90.18%, meaning only ~1,433 of 14,585 rows carry any value at all — this is a severely sparse field. Among non-null values, 316 unique levels exist with modest concentration (top value '15' appears in only 4.12% of rows) and a high entropy ratio of 0.823, indicating the non-null values are broadly spread rather than clustered.

operator high anthropic:default

This column records the operating authority or agency responsible for a navigational aid or maritime infrastructure asset — dominated by coast guard entities (U.S., Philippine, and Chinese 海上保安厅) alongside European bodies like Plovput and INEA. The 92.7% null rate is the critical anomaly: only 1,074 of 14,585 rows carry a value, meaning operator attribution is nearly absent across the dataset. Among populated rows, entropy ratio of 0.861 across 283 unique values signals a long tail of rarely-seen operators beyond the top few, and the top value 'U.S. Coast Guard' covers only 7.7% of non-null rows. The presence of CJK characters (海上保安庁) confirms a multilingual mix requiring normalisation before any grouping or analysis.

year_built high anthropic:default

This column represents the year a structure was built, but it has been parsed as categorical rather than numeric, likely because it contains century-level codes such as 'C19' and 'C20' mixed with specific years like '1875' and '1906'. The null rate is extremely high at 93.2%, meaning only about 990 of 14,585 rows carry any value at all. Among populated values, 429 distinct entries exist with the top value 'C19' appearing only 31 times (3.1% of non-null rows), indicating a very long tail. The mixed format — century codes alongside specific years — signals data quality issues that require harmonisation before any temporal analysis.

lat high anthropic:default

This column represents geographic latitude, with values ranging from -63.4° (near Antarctica) to 81.8° (high Arctic), consistent with global location data across 14,585 records. The distribution is notably left-skewed (skew = -1.46) with a mean of 34.5° but a median of 40.8°, suggesting a concentration of records in mid-to-high Northern Hemisphere latitudes pulled down by a Southern Hemisphere tail. Nearly 9% of values (1,295) are flagged as outliers, likely corresponding to records in the Southern Hemisphere or extreme polar regions which are genuinely sparse in most datasets. Uniqueness is near-perfect (14,572 of 14,585 values distinct), implying precise coordinate capture with minimal rounding.

seamark_type high anthropic:default

This column captures the classification of maritime seamarks (navigational aids such as lights, beacons, and landmarks), drawn from what appears to be nautical/GIS data. Nearly half the rows (48.01%) are null, which is flagged as an alert and likely reflects features in the dataset that are not seamarks at all. Among the 7,588 populated rows, the distribution is heavily skewed toward light types: 'light_minor' alone accounts for 46.1% of non-null values, and combined with 'light_major' these two dominate, while the remaining 23 categories (beacons, landmarks, buildings, etc.) cover a long tail. Entropy ratio of 0.357 confirms moderate but uneven spread across the 25 categories.

light_character high anthropic:default

This column encodes the light character (flashing pattern) of maritime navigational aids — values like 'Fl' (flashing), 'Iso' (isophase), 'Oc' (occulting), and 'LFl' (long flashing) are standard IALA light notation. The dominant concern is a 71.31% null rate, meaning nearly three-quarters of records carry no light character, likely because many features in the dataset are unlighted aids or non-light structures. Among populated rows, 'Fl' accounts for 74.7% of non-null values, making the distribution heavily skewed across 19 categories.

name high anthropic:default

This column contains the proper names of lighthouses, drawn from a multilingual global dataset — 'lighthouse', 'faro' (Spanish/Italian), 'fyr' (Scandinavian), 'phare' (French), 'farol' (Portuguese), and 'маяк' (Russian/Cyrillic) all appear in the top words, confirming broad geographic coverage. With 14,239 unique values across 14,585 rows, the near-unique alert is expected for a name field; the 346 duplicates (2.37%) likely reflect shared names for distinct structures (e.g., 'North Light'). Average name length is ~19 characters with a median of 2 words, consistent with short proper-noun phrases. The multilingual vocabulary mix is the key surprise and warrants attention if name-matching or NLP is planned.

lon high anthropic:default

This column contains geographic longitude values, spanning the full valid range from -179.2 to 179.3 degrees with a mean near 23° and median near 15°, suggesting a slight concentration of observations in Europe/Africa relative to the Americas and East Asia. The distribution is nearly symmetric (skew ≈ 0.05) and platykurtic (kurtosis ≈ -0.95), consistent with a broad, flat spread of coordinates across the globe rather than clustering around a single region. Near-uniqueness (14,565 distinct values out of 14,585 rows) and zero nulls confirm these are precise geospatial measurements, not coarse bins. The IQR of ~153 degrees reinforces global coverage.

osm_id high anthropic:default

This column contains OpenStreetMap object identifiers, a well-known external reference system where numeric IDs are assigned sequentially as features are added to the OSM database. Nearly all 14,585 rows have a unique ID (only 1 duplicate exists across 14,584 unique values), and the null rate is zero, indicating high integrity. The wide IQR of ~5.4 billion and right skew (1.07) reflect OSM's historical ID growth — older features have lower IDs while newer additions push into the 10+ billion range, which is consistent with OSM's current ID space.

osm_type high anthropic:default

This column captures the OpenStreetMap geometry type, distinguishing between point features ('node') and linear/polygon features ('way'). With only 2 distinct values across 14,585 rows and zero nulls, it is a clean binary indicator. The distribution is notably skewed: 'node' dominates at 77.9% (11,358 records) versus 'way' at 22.1% (3,227 records), reflecting the typical OSM pattern where point features outnumber area/line features. Entropy ratio of 0.76 confirms moderate imbalance but not extreme dominance.

Numeric correlation

Show data table
Pearson correlation across 3 numeric columns (values clipped to 2 decimals).
latlonosm_id
lat+1.00-0.12-0.04
lon-0.12+1.00+0.18
osm_id-0.04+0.18+1.00

name text

97.6% of rows are unique strings
rows14,585
null0 (0.0%)
unique14,239
len_min2
len_max91
len_mean18.948
len_median21.000
len_p9527.000
word_mean2.327
word_median2.000
n_empty0
n_duplicates346
duplicate_rate0.024
vocab_size14,670
readability_flesch_mean75.784
emoji_rate0.000
url_rate0.000
one_word_rate0.107
allcaps_rate0.058
boilerplate_rate0.000
Show data table
Character-length distribution for name (mean: 18.947685978745287).
charscount
2 – 4301
4 – 6525
6 – 9304
9 – 11528
11 – 13827
13 – 15705
15 – 18859
18 – 20906
20 – 227858
22 – 24560
24 – 26414
26 – 29287
29 – 31151
31 – 33155
33 – 3552
35 – 3842
38 – 4042
40 – 4237
42 – 445
44 – 468
46 – 494
49 – 513
51 – 532
53 – 552
55 – 582
58 – 601
60 – 621
62 – 641
64 – 670
67 – 690
69 – 710
71 – 732
73 – 750
75 – 780
78 – 800
80 – 820
82 – 840
84 – 870
87 – 890
89 – 911
Sample values (first 10)
  1. Far de Capdepera
  2. Lighthouse 12736917711
  3. 出雲日御碕灯台
  4. Pilsumer Leuchtturm
  5. Lighthouse 3592895556
  6. Hải đăng Vạn Ca
  7. Lighthouse 3954003290
  8. Lighthouse 666429022
  9. Farol do Bugio
  10. Vejsnæs Nakke

lat numeric

8.9% rows beyond 1.5 IQR
rows14,585
null0 (0.0%)
unique14,572
min-63.396
max81.800
mean34.520
median40.812
std24.643
q128.111
q348.983
iqr20.871
skew-1.458
kurtosis2.028
n_outliers1,295
outlier_rate0.089
zero_rate0.000
Show data table
Histogram bins for lat (median: 40.8121914).
bincount
-63.4 – -59.773
-59.77 – -56.142
-56.14 – -52.5138
-52.51 – -48.8844
-48.88 – -45.2529
-45.25 – -41.6292
-41.62 – -37.99108
-37.99 – -34.36112
-34.36 – -30.73147
-30.73 – -27.1101
-27.1 – -23.4793
-23.47 – -19.84113
-19.84 – -16.2158
-16.21 – -12.5892
-12.58 – -8.94758
-8.947 – -5.317130
-5.317 – -1.687129
-1.687 – 1.942168
1.942 – 5.572121
5.572 – 9.202239
9.202 – 12.83549
12.83 – 16.46274
16.46 – 20.09241
20.09 – 23.72383
23.72 – 27.35273
27.35 – 30.98226
30.98 – 34.611062
34.61 – 38.241554
38.24 – 41.871300
41.87 – 45.51976
45.5 – 49.131257
49.13 – 52.76625
52.76 – 56.39900
56.39 – 60.021039
60.02 – 63.65410
63.65 – 67.28357
67.28 – 70.91179
70.91 – 74.5473
74.54 – 78.1722
78.17 – 81.88

lon numeric

rows14,585
null0 (0.0%)
unique14,565
min-179.197
max179.340
mean23.039
median14.975
std79.396
q1-40.500
q3112.445
iqr152.945
skew0.053
kurtosis-0.954
n_outliers0
outlier_rate0.000
zero_rate0.000
Show data table
Histogram bins for lon (median: 14.9745494).
bincount
-179.2 – -170.239
-170.2 – -161.33
-161.3 – -152.320
-152.3 – -143.36
-143.3 – -134.48
-134.4 – -125.4179
-125.4 – -116.5235
-116.5 – -107.578
-107.5 – -98.5338
-98.53 – -89.56132
-89.56 – -80.6544
-80.6 – -71.64805
-71.64 – -62.67835
-62.67 – -53.71379
-53.71 – -44.75272
-44.75 – -35.78178
-35.78 – -26.8273
-26.82 – -17.86128
-17.86 – -8.892277
-8.892 – 0.071371272
0.07137 – 9.035770
9.035 – 181383
18 – 26.961441
26.96 – 35.93659
35.93 – 44.89258
44.89 – 53.85141
53.85 – 62.8277
62.82 – 71.7838
71.78 – 80.74131
80.74 – 89.7173
89.71 – 98.6757
98.67 – 107.6245
107.6 – 116.6388
116.6 – 125.6955
125.6 – 134.51230
134.5 – 143.5818
143.5 – 152.4199
152.4 – 161.466
161.4 – 170.449
170.4 – 179.3106

country categorical

11 singleton categories 99.6% null
rows14,585
null14,524 (99.6%)
unique19
top_valueLV
top_rate0.295
cardinality19
entropy3.442
entropy_ratio0.810
Show data table
Top values for country (19 unique shown, of 19 total).
valuecountshare
LV180.1%
DE80.1%
EE70.0%
HT60.0%
US50.0%
GB20.0%
PT20.0%
IM20.0%
JP10.0%
KY10.0%
PH10.0%
IN10.0%
FI10.0%
PL10.0%
IT10.0%
RU10.0%
UZ10.0%
MX10.0%
TW10.0%
Top values (rank 1–20)
  1. LV — 18
  2. DE — 8
  3. EE — 7
  4. HT — 6
  5. US — 5
  6. GB — 2
  7. PT — 2
  8. IM — 2
  9. JP — 1
  10. KY — 1
  11. PH — 1
  12. IN — 1
  13. FI — 1
  14. PL — 1
  15. IT — 1
  16. RU — 1
  17. UZ — 1
  18. MX — 1
  19. TW — 1

height categorical

197 singleton categories 90.2% null
rows14,585
null13,153 (90.2%)
unique316
top_value15
top_rate0.041
cardinality316
entropy6.837
entropy_ratio0.823
Show data table
Top values for height (20 unique shown, of 316 total).
valuecountshare
15590.4%
12550.4%
14540.4%
10510.3%
8450.3%
18440.3%
20430.3%
13380.3%
6370.3%
17330.2%
25310.2%
11280.2%
30280.2%
16270.2%
23260.2%
21210.1%
19200.1%
28190.1%
9190.1%
26180.1%
Top values (rank 1–20)
  1. 15 — 59
  2. 12 — 55
  3. 14 — 54
  4. 10 — 51
  5. 8 — 45
  6. 18 — 44
  7. 20 — 43
  8. 13 — 38
  9. 6 — 37
  10. 17 — 33
  11. 25 — 31
  12. 11 — 28
  13. 30 — 28
  14. 16 — 27
  15. 23 — 26
  16. 21 — 21
  17. 19 — 20
  18. 28 — 19
  19. 9 — 19
  20. 26 — 18

year_built categorical

271 singleton categories 93.2% null
rows14,585
null13,593 (93.2%)
unique429
top_valueC19
top_rate0.031
cardinality429
entropy8.142
entropy_ratio0.931
Show data table
Top values for year_built (20 unique shown, of 429 total).
valuecountshare
C19310.2%
1875160.1%
1872150.1%
1881120.1%
C20120.1%
1906110.1%
1871110.1%
1877110.1%
1882110.1%
1874110.1%
1873110.1%
1939100.1%
1898100.1%
189790.1%
187090.1%
190980.1%
188480.1%
189080.1%
191170.0%
195070.0%
Top values (rank 1–20)
  1. C19 — 31
  2. 1875 — 16
  3. 1872 — 15
  4. 1881 — 12
  5. C20 — 12
  6. 1906 — 11
  7. 1871 — 11
  8. 1877 — 11
  9. 1882 — 11
  10. 1874 — 11
  11. 1873 — 11
  12. 1939 — 10
  13. 1898 — 10
  14. 1897 — 9
  15. 1870 — 9
  16. 1909 — 8
  17. 1884 — 8
  18. 1890 — 8
  19. 1911 — 7
  20. 1950 — 7

operator categorical

167 singleton categories 92.7% null
rows14,585
null13,520 (92.7%)
unique283
top_valueU.S. Coast Guard
top_rate0.077
cardinality283
entropy7.013
entropy_ratio0.861
Show data table
Top values for operator (20 unique shown, of 283 total).
valuecountshare
U.S. Coast Guard820.6%
Plovput490.3%
INEA420.3%
Tagbilaran Station, Philippine Coast Guard270.2%
Cebu Station, Philippine Coast Guard260.2%
Catbalogan Station, Philippine Coast Guard180.1%
Surigao Station, Philippine Coast Guard180.1%
Masbate Station, Philippine Coast Guard170.1%
Maasin Station, Philippine Coast Guard170.1%
海上保安庁160.1%
Directorate General of Lighthouses and Lightships150.1%
Romblon Station, Philippine Coast Guard150.1%
Iloilo Station, Philippine Coast Guard140.1%
Puerto Princesa Station, Philippine Coast Guard140.1%
Bacolod Station, Philippine Coast Guard130.1%
Sorsogon Station, Philippine Coast Guard130.1%
Cagayan de Oro Station, Philippine Coast Guard130.1%
Marine Department of Sabah130.1%
Dumaguete Station, Philippine Coast Guard120.1%
Appari Station, Philippine Coast Guard120.1%
Top values (rank 1–20)
  1. U.S. Coast Guard — 82
  2. Plovput — 49
  3. INEA — 42
  4. Tagbilaran Station, Philippine Coast Guard — 27
  5. Cebu Station, Philippine Coast Guard — 26
  6. Catbalogan Station, Philippine Coast Guard — 18
  7. Surigao Station, Philippine Coast Guard — 18
  8. Masbate Station, Philippine Coast Guard — 17
  9. Maasin Station, Philippine Coast Guard — 17
  10. 海上保安庁 — 16
  11. Directorate General of Lighthouses and Lightships — 15
  12. Romblon Station, Philippine Coast Guard — 15
  13. Iloilo Station, Philippine Coast Guard — 14
  14. Puerto Princesa Station, Philippine Coast Guard — 14
  15. Bacolod Station, Philippine Coast Guard — 13
  16. Sorsogon Station, Philippine Coast Guard — 13
  17. Cagayan de Oro Station, Philippine Coast Guard — 13
  18. Marine Department of Sabah — 13
  19. Dumaguete Station, Philippine Coast Guard — 12
  20. Appari Station, Philippine Coast Guard — 12

seamark_type categorical

48.0% null
rows14,585
null7,002 (48.0%)
unique25
top_valuelight_minor
top_rate0.461
cardinality25
entropy1.657
entropy_ratio0.357
Show data table
Top values for seamark_type (20 unique shown, of 25 total).
valuecountshare
light_minor349624.0%
light_major305120.9%
landmark7164.9%
beacon_special_purpose1461.0%
beacon_lateral1020.7%
beacon_cardinal190.1%
light90.1%
beacon50.0%
beacon_isolated_danger50.0%
building40.0%
daymark40.0%
radio_station30.0%
pile30.0%
signal_station_traffic30.0%
signal_station_warning30.0%
buoy_lateral30.0%
navigation_line20.0%
fishing_facility20.0%
light_vessel10.0%
cone10.0%
Top values (rank 1–20)
  1. light_minor — 3,496
  2. light_major — 3,051
  3. landmark — 716
  4. beacon_special_purpose — 146
  5. beacon_lateral — 102
  6. beacon_cardinal — 19
  7. light — 9
  8. beacon — 5
  9. beacon_isolated_danger — 5
  10. building — 4
  11. daymark — 4
  12. radio_station — 3
  13. pile — 3
  14. signal_station_traffic — 3
  15. signal_station_warning — 3
  16. buoy_lateral — 3
  17. navigation_line — 2
  18. fishing_facility — 2
  19. light_vessel — 1
  20. cone — 1

light_character categorical

71.3% null
rows14,585
null10,401 (71.3%)
unique19
top_valueFl
top_rate0.747
cardinality19
entropy1.503
entropy_ratio0.354
Show data table
Top values for light_character (19 unique shown, of 19 total).
valuecountshare
Fl312621.4%
Iso2491.7%
F2451.7%
Q1821.2%
Oc1511.0%
LFl1481.0%
VQ240.2%
Al.Fl240.2%
Mo140.1%
FFl40.0%
Al40.0%
IQ30.0%
Al.LFl20.0%
Al.Oc20.0%
Q+LFl20.0%
IVQ10.0%
Fl(2)10.0%
LFl W 10s10.0%
Al.Iso10.0%
Top values (rank 1–20)
  1. Fl — 3,126
  2. Iso — 249
  3. F — 245
  4. Q — 182
  5. Oc — 151
  6. LFl — 148
  7. VQ — 24
  8. Al.Fl — 24
  9. Mo — 14
  10. FFl — 4
  11. Al — 4
  12. IQ — 3
  13. Al.LFl — 2
  14. Al.Oc — 2
  15. Q+LFl — 2
  16. IVQ — 1
  17. Fl(2) — 1
  18. LFl W 10s — 1
  19. Al.Iso — 1

heritage categorical

96.9% null
rows14,585
null14,132 (96.9%)
unique7
top_value2
top_rate0.757
cardinality7
entropy1.244
entropy_ratio0.443
Show data table
Top values for heritage (7 unique shown, of 7 total).
valuecountshare
23432.4%
3520.4%
4260.2%
yes250.2%
140.0%
regional20.0%
no10.0%
Top values (rank 1–20)
  1. 2 — 343
  2. 3 — 52
  3. 4 — 26
  4. yes — 25
  5. 1 — 4
  6. regional — 2
  7. no — 1

wikipedia text

97.9% of rows are unique strings 86.2% null
rows14,585
null12,577 (86.2%)
unique1,965
len_min6
len_max55
len_mean22.296
len_median22.000
len_p9533.000
word_mean2.996
word_median3.000
n_empty0
n_duplicates43
duplicate_rate0.021
vocab_size2,370
readability_flesch_mean48.916
emoji_rate0.000
url_rate0.000
one_word_rate0.076
allcaps_rate0.000
boilerplate_rate0.000
Show data table
Character-length distribution for wikipedia (mean: 22.296314741035857).
charscount
6 – 729
7 – 874
8 – 1020
10 – 119
11 – 1217
12 – 1322
13 – 1524
15 – 1645
16 – 17107
17 – 1893
18 – 19132
19 – 21139
21 – 22178
22 – 23307
23 – 24147
24 – 26129
26 – 27103
27 – 28168
28 – 2956
29 – 3038
30 – 3238
32 – 3322
33 – 3438
34 – 3511
35 – 3713
37 – 385
38 – 3920
39 – 405
40 – 422
42 – 432
43 – 442
44 – 459
45 – 460
46 – 480
48 – 490
49 – 500
50 – 511
51 – 530
53 – 541
54 – 552
Sample values (first 10)
  1. de:Neuer Leuchtturm Borkum
  2. hr:Svjetionik Hrid Blitvenica
  3. en:Gay Head Light
  4. ja:葛登支岬灯台
  5. en:Sentinel Island Light
  6. it:Faro di Scilla
  7. es:Faro Punta Bajos
  8. en:Grassy Island Range Lights
  9. fr:Phare de Kéréon
  10. fr:Phare de Tuskar Rock

osm_id numeric

rows14,585
null0 (0.0%)
unique14,584
min13,391,742
max13,525,496,137
mean3,722,756,855
median1,574,285,300
std3,828,250,124
q11,000,644,758
q36,401,686,693
iqr5,401,041,935
skew1.073
kurtosis-0.199
n_outliers0
outlier_rate0.000
zero_rate0.000
Show data table
Histogram bins for osm_id (median: 1574285300.0).
bincount
1.339e+07 – 3.512e+081272
3.512e+08 – 6.89e+081457
6.89e+08 – 1.027e+09998
1.027e+09 – 1.365e+092358
1.365e+09 – 1.702e+091852
1.702e+09 – 2.04e+09348
2.04e+09 – 2.378e+09245
2.378e+09 – 2.716e+09266
2.716e+09 – 3.054e+09212
3.054e+09 – 3.391e+09223
3.391e+09 – 3.729e+09234
3.729e+09 – 4.067e+09178
4.067e+09 – 4.405e+09187
4.405e+09 – 4.743e+09216
4.743e+09 – 5.08e+09220
5.08e+09 – 5.418e+09241
5.418e+09 – 5.756e+09180
5.756e+09 – 6.094e+09113
6.094e+09 – 6.432e+09143
6.432e+09 – 6.769e+09248
6.769e+09 – 7.107e+09351
7.107e+09 – 7.445e+0994
7.445e+09 – 7.783e+09185
7.783e+09 – 8.121e+09147
8.121e+09 – 8.458e+09150
8.458e+09 – 8.796e+09131
8.796e+09 – 9.134e+09163
9.134e+09 – 9.472e+09210
9.472e+09 – 9.81e+09199
9.81e+09 – 1.015e+10422
1.015e+10 – 1.049e+10102
1.049e+10 – 1.082e+1091
1.082e+10 – 1.116e+10107
1.116e+10 – 1.15e+1097
1.15e+10 – 1.184e+10198
1.184e+10 – 1.217e+10162
1.217e+10 – 1.251e+10158
1.251e+10 – 1.285e+10161
1.285e+10 – 1.319e+10132
1.319e+10 – 1.353e+10134

osm_type categorical

rows14,585
null0 (0.0%)
unique2
top_valuenode
top_rate0.779
cardinality2
entropy0.762
entropy_ratio0.762
Show data table
Top values for osm_type (2 unique shown, of 2 total).
valuecountshare
node1135877.9%
way322722.1%
Top values (rank 1–20)
  1. node — 11,358
  2. way — 3,227