Overview

Dataset statistics

Number of variables11
Number of observations1475
Missing cells1486
Missing cells (%)9.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.2 KiB
Average record size in memory91.1 B

Variable types

Text4
Numeric3
Categorical2
DateTime2

Dataset

Description키값,문화재 일련번호,문화재명칭,수량ㆍ규모,행정시,행정구,행정동,X좌표,Y좌표,지정일,해제일
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-13050/S/1/datasetView.do

Alerts

행정시 has constant value ""Constant
X좌표 is highly overall correlated with 행정구High correlation
Y좌표 is highly overall correlated with 행정구High correlation
행정구 is highly overall correlated with X좌표 and 1 other fieldsHigh correlation
수량ㆍ규모 has 45 (3.1%) missing valuesMissing
해제일 has 1441 (97.7%) missing valuesMissing
키값 has unique valuesUnique
문화재 일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 08:35:01.855766
Analysis finished2023-12-11 08:35:04.084685
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

키값
Text

UNIQUE 

Distinct1475
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-11T17:35:04.292065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters20650
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1475 ?
Unique (%)100.0%

Sample

1st rowBE_LiST24-1038
2nd rowBE_LiST24-0256
3rd rowBE_LiST24-0764
4th rowBE_LiST24-0444
5th rowBE_LiST24-0445
ValueCountFrequency (%)
be_list24-1038 1
 
0.1%
be_list24-0088 1
 
0.1%
be_list24-0142 1
 
0.1%
be_list24-0144 1
 
0.1%
be_list24-0976 1
 
0.1%
be_list24-0666 1
 
0.1%
be_list24-0667 1
 
0.1%
be_list24-1158 1
 
0.1%
be_list24-1157 1
 
0.1%
be_list24-1156 1
 
0.1%
Other values (1465) 1465
99.3%
2023-12-11T17:35:04.735765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1973
9.6%
4 1949
 
9.4%
0 1494
 
7.2%
B 1475
 
7.1%
T 1475
 
7.1%
E 1475
 
7.1%
- 1475
 
7.1%
S 1475
 
7.1%
i 1475
 
7.1%
L 1475
 
7.1%
Other values (8) 4909
23.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8850
42.9%
Uppercase Letter 7375
35.7%
Dash Punctuation 1475
 
7.1%
Lowercase Letter 1475
 
7.1%
Connector Punctuation 1475
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1973
22.3%
4 1949
22.0%
0 1494
16.9%
1 974
11.0%
3 498
 
5.6%
5 398
 
4.5%
6 397
 
4.5%
7 393
 
4.4%
8 387
 
4.4%
9 387
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 1475
20.0%
T 1475
20.0%
E 1475
20.0%
S 1475
20.0%
L 1475
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 1475
100.0%
Lowercase Letter
ValueCountFrequency (%)
i 1475
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1475
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11800
57.1%
Latin 8850
42.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1973
16.7%
4 1949
16.5%
0 1494
12.7%
- 1475
12.5%
_ 1475
12.5%
1 974
8.3%
3 498
 
4.2%
5 398
 
3.4%
6 397
 
3.4%
7 393
 
3.3%
Other values (2) 774
 
6.6%
Latin
ValueCountFrequency (%)
B 1475
16.7%
T 1475
16.7%
E 1475
16.7%
S 1475
16.7%
i 1475
16.7%
L 1475
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1973
9.6%
4 1949
 
9.4%
0 1494
 
7.2%
B 1475
 
7.1%
T 1475
 
7.1%
E 1475
 
7.1%
- 1475
 
7.1%
S 1475
 
7.1%
i 1475
 
7.1%
L 1475
 
7.1%
Other values (8) 4909
23.8%

문화재 일련번호
Real number (ℝ)

UNIQUE 

Distinct1475
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17028.272
Minimum11001
Maximum30710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T17:35:04.911983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11001
5-th percentile11088.7
Q111461.5
median11881
Q330111.5
95-th percentile30579.3
Maximum30710
Range19709
Interquartile range (IQR)18650

Descriptive statistics

Standard deviation8488.7584
Coefficient of variation (CV)0.49850968
Kurtosis-1.1243741
Mean17028.272
Median Absolute Deviation (MAD)481
Skewness0.93283691
Sum25116701
Variance72059019
MonotonicityNot monotonic
2023-12-11T17:35:05.071565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30270 1
 
0.1%
11206 1
 
0.1%
30186 1
 
0.1%
11855 1
 
0.1%
11856 1
 
0.1%
11854 1
 
0.1%
11858 1
 
0.1%
11857 1
 
0.1%
11204 1
 
0.1%
11203 1
 
0.1%
Other values (1465) 1465
99.3%
ValueCountFrequency (%)
11001 1
0.1%
11002 1
0.1%
11003 1
0.1%
11005 1
0.1%
11006 1
0.1%
11007 1
0.1%
11010 1
0.1%
11011 1
0.1%
11012 1
0.1%
11013 1
0.1%
ValueCountFrequency (%)
30710 1
0.1%
30709 1
0.1%
30708 1
0.1%
30707 1
0.1%
30706 1
0.1%
30705 1
0.1%
30704 1
0.1%
30701 1
0.1%
30696 1
0.1%
30694 1
0.1%

문화재명칭
Text

Distinct1271
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-11T17:35:05.452001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length166
Median length98
Mean length50.988475
Min length3

Characters and Unicode

Total characters75208
Distinct characters78
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1192 ?
Unique (%)80.8%

Sample

1st rowBaekundong Valley of Inwangsan Mountain
2nd rowUnderground Waterway of Namdaemun-ro
3rd rowUnderground Waterway of Seoulgwangjang Square
4th rowPainting of Nectar Ritual of Mitasa Temple
5th rowPainting of Hermit Sage of Mitasa Temple
ValueCountFrequency (%)
of 931
 
8.6%
the 417
 
3.8%
sutra 244
 
2.2%
temple 201
 
1.8%
and 197
 
1.8%
in 186
 
1.7%
with 164
 
1.5%
from 136
 
1.3%
volume 119
 
1.1%
painting 116
 
1.1%
Other values (2208) 8156
75.1%
2023-12-11T17:35:06.016939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9489
 
12.6%
e 6033
 
8.0%
a 5900
 
7.8%
o 5608
 
7.5%
n 5473
 
7.3%
i 3871
 
5.1%
t 3278
 
4.4%
r 3219
 
4.3%
g 2535
 
3.4%
s 2360
 
3.1%
Other values (68) 27442
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 55508
73.8%
Space Separator 9489
 
12.6%
Uppercase Letter 8097
 
10.8%
Open Punctuation 505
 
0.7%
Close Punctuation 491
 
0.7%
Dash Punctuation 476
 
0.6%
Decimal Number 470
 
0.6%
Other Punctuation 158
 
0.2%
Other Letter 9
 
< 0.1%
Final Punctuation 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6033
10.9%
a 5900
 
10.6%
o 5608
 
10.1%
n 5473
 
9.9%
i 3871
 
7.0%
t 3278
 
5.9%
r 3219
 
5.8%
g 2535
 
4.6%
s 2360
 
4.3%
l 2357
 
4.2%
Other values (16) 14874
26.8%
Uppercase Letter
ValueCountFrequency (%)
S 1185
14.6%
B 653
 
8.1%
T 651
 
8.0%
P 651
 
8.0%
C 578
 
7.1%
G 465
 
5.7%
H 384
 
4.7%
D 348
 
4.3%
M 297
 
3.7%
V 296
 
3.7%
Other values (15) 2589
32.0%
Decimal Number
ValueCountFrequency (%)
1 115
24.5%
2 73
15.5%
3 58
12.3%
4 42
 
8.9%
7 42
 
8.9%
6 39
 
8.3%
5 37
 
7.9%
0 33
 
7.0%
8 17
 
3.6%
9 14
 
3.0%
Other Letter
ValueCountFrequency (%)
서 4
44.4%
다 1
 
11.1%
天 1
 
11.1%
地 1
 
11.1%
玄 1
 
11.1%
黃 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
' 128
81.0%
? 27
 
17.1%
. 2
 
1.3%
! 1
 
0.6%
Space Separator
ValueCountFrequency (%)
9489
100.0%
Open Punctuation
ValueCountFrequency (%)
( 505
100.0%
Close Punctuation
ValueCountFrequency (%)
) 491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 476
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63605
84.6%
Common 11594
 
15.4%
Hangul 5
 
< 0.1%
Han 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6033
 
9.5%
a 5900
 
9.3%
o 5608
 
8.8%
n 5473
 
8.6%
i 3871
 
6.1%
t 3278
 
5.2%
r 3219
 
5.1%
g 2535
 
4.0%
s 2360
 
3.7%
l 2357
 
3.7%
Other values (41) 22971
36.1%
Common
ValueCountFrequency (%)
9489
81.8%
( 505
 
4.4%
) 491
 
4.2%
- 476
 
4.1%
' 128
 
1.1%
1 115
 
1.0%
2 73
 
0.6%
3 58
 
0.5%
4 42
 
0.4%
7 42
 
0.4%
Other values (11) 175
 
1.5%
Han
ValueCountFrequency (%)
天 1
25.0%
地 1
25.0%
玄 1
25.0%
黃 1
25.0%
Hangul
ValueCountFrequency (%)
서 4
80.0%
다 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75195
> 99.9%
Hangul 5
 
< 0.1%
Punctuation 4
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9489
 
12.6%
e 6033
 
8.0%
a 5900
 
7.8%
o 5608
 
7.5%
n 5473
 
7.3%
i 3871
 
5.1%
t 3278
 
4.4%
r 3219
 
4.3%
g 2535
 
3.4%
s 2360
 
3.1%
Other values (60) 27429
36.5%
Hangul
ValueCountFrequency (%)
서 4
80.0%
다 1
 
20.0%
Punctuation
ValueCountFrequency (%)
’ 3
75.0%
‘ 1
 
25.0%
CJK
ValueCountFrequency (%)
天 1
25.0%
地 1
25.0%
玄 1
25.0%
黃 1
25.0%

수량ㆍ규모
Text

MISSING 

Distinct346
Distinct (%)24.2%
Missing45
Missing (%)3.1%
Memory size11.7 KiB
2023-12-11T17:35:06.412064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length6
Mean length8.4090909
Min length3

Characters and Unicode

Total characters12025
Distinct characters194
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)21.2%

Sample

1st row1piece
2nd row1piece
3rd row3piece
4th row1Book
5th row1piece
ValueCountFrequency (%)
1piece 612
32.5%
1picture 141
 
7.5%
토지 92
 
4.9%
1book 58
 
3.1%
건물 57
 
3.0%
1chapter 55
 
2.9%
2piece 35
 
1.9%
1棟 33
 
1.8%
1chapter1book 31
 
1.6%
3chapter1book 25
 
1.3%
Other values (465) 742
39.4%
2023-12-11T17:35:07.396879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1749
14.5%
1 1392
 
11.6%
p 1068
 
8.9%
i 847
 
7.0%
c 844
 
7.0%
626
 
5.2%
o 466
 
3.9%
r 378
 
3.1%
t 369
 
3.1%
2 323
 
2.7%
Other values (184) 3963
33.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6665
55.4%
Decimal Number 2696
22.4%
Other Letter 1039
 
8.6%
Space Separator 626
 
5.2%
Uppercase Letter 462
 
3.8%
Other Symbol 214
 
1.8%
Other Punctuation 151
 
1.3%
Open Punctuation 82
 
0.7%
Close Punctuation 81
 
0.7%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 103
 
9.9%
토 97
 
9.3%
물 83
 
8.0%
棟 77
 
7.4%
건 74
 
7.1%
基 55
 
5.3%
면 32
 
3.1%
적 30
 
2.9%
총 27
 
2.6%
석 26
 
2.5%
Other values (135) 435
41.9%
Lowercase Letter
ValueCountFrequency (%)
e 1749
26.2%
p 1068
16.0%
i 847
12.7%
c 844
12.7%
o 466
 
7.0%
r 378
 
5.7%
t 369
 
5.5%
a 248
 
3.7%
k 232
 
3.5%
h 221
 
3.3%
Other values (8) 243
 
3.6%
Decimal Number
ValueCountFrequency (%)
1 1392
51.6%
2 323
 
12.0%
3 213
 
7.9%
4 149
 
5.5%
5 118
 
4.4%
7 112
 
4.2%
0 107
 
4.0%
6 106
 
3.9%
9 90
 
3.3%
8 86
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 232
50.2%
C 221
47.8%
N 2
 
0.4%
L 1
 
0.2%
W 1
 
0.2%
H 1
 
0.2%
O 1
 
0.2%
D 1
 
0.2%
R 1
 
0.2%
P 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 144
95.4%
: 6
 
4.0%
/ 1
 
0.7%
Other Symbol
ValueCountFrequency (%)
㎡ 213
99.5%
㎝ 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
× 2
50.0%
~ 2
50.0%
Space Separator
ValueCountFrequency (%)
626
100.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7127
59.3%
Common 3859
32.1%
Hangul 868
 
7.2%
Han 171
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 103
 
11.9%
토 97
 
11.2%
물 83
 
9.6%
건 74
 
8.5%
면 32
 
3.7%
적 30
 
3.5%
총 27
 
3.1%
석 26
 
3.0%
묘 23
 
2.6%
분 21
 
2.4%
Other values (119) 352
40.6%
Latin
ValueCountFrequency (%)
e 1749
24.5%
p 1068
15.0%
i 847
11.9%
c 844
11.8%
o 466
 
6.5%
r 378
 
5.3%
t 369
 
5.2%
a 248
 
3.5%
k 232
 
3.3%
B 232
 
3.3%
Other values (18) 694
 
9.7%
Common
ValueCountFrequency (%)
1 1392
36.1%
626
16.2%
2 323
 
8.4%
3 213
 
5.5%
㎡ 213
 
5.5%
4 149
 
3.9%
. 144
 
3.7%
5 118
 
3.1%
7 112
 
2.9%
0 107
 
2.8%
Other values (11) 462
 
12.0%
Han
ValueCountFrequency (%)
棟 77
45.0%
基 55
32.2%
帖 7
 
4.1%
点 4
 
2.3%
軀 4
 
2.3%
幅 4
 
2.3%
一 3
 
1.8%
括 3
 
1.8%
面 3
 
1.8%
個 3
 
1.8%
Other values (6) 8
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10770
89.6%
Hangul 868
 
7.2%
CJK Compat 214
 
1.8%
CJK 171
 
1.4%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1749
16.2%
1 1392
12.9%
p 1068
 
9.9%
i 847
 
7.9%
c 844
 
7.8%
626
 
5.8%
o 466
 
4.3%
r 378
 
3.5%
t 369
 
3.4%
2 323
 
3.0%
Other values (36) 2708
25.1%
CJK Compat
ValueCountFrequency (%)
㎡ 213
99.5%
㎝ 1
 
0.5%
Hangul
ValueCountFrequency (%)
지 103
 
11.9%
토 97
 
11.2%
물 83
 
9.6%
건 74
 
8.5%
면 32
 
3.7%
적 30
 
3.5%
총 27
 
3.1%
석 26
 
3.0%
묘 23
 
2.6%
분 21
 
2.4%
Other values (119) 352
40.6%
CJK
ValueCountFrequency (%)
棟 77
45.0%
基 55
32.2%
帖 7
 
4.1%
点 4
 
2.3%
軀 4
 
2.3%
幅 4
 
2.3%
一 3
 
1.8%
括 3
 
1.8%
面 3
 
1.8%
個 3
 
1.8%
Other values (6) 8
 
4.7%
None
ValueCountFrequency (%)
× 2
100.0%

행정시
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
Seoul
1475 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSeoul
2nd rowSeoul
3rd rowSeoul
4th rowSeoul
5th rowSeoul

Common Values

ValueCountFrequency (%)
Seoul 1475
100.0%

Length

2023-12-11T17:35:07.586802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:35:07.721677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
seoul 1475
100.0%

행정구
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
Yongsan-gu
384 
Jongno-gu
382 
Seongbuk-gu
110 
Gwanak-gu
108 
Jung-gu
103 
Other values (20)
388 

Length

Max length15
Median length13
Mean length9.6413559
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJongno-gu
2nd rowJung-gu
3rd rowJung-gu
4th rowSeongbuk-gu
5th rowSeongbuk-gu

Common Values

ValueCountFrequency (%)
Yongsan-gu 384
26.0%
Jongno-gu 382
25.9%
Seongbuk-gu 110
 
7.5%
Gwanak-gu 108
 
7.3%
Jung-gu 103
 
7.0%
Seodaemun-gu 74
 
5.0%
Seocho-gu 52
 
3.5%
Dongjak-gu 39
 
2.6%
Gangnam-gu 38
 
2.6%
Gangseo-gu 31
 
2.1%
Other values (15) 154
10.4%

Length

2023-12-11T17:35:07.911834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
yongsan-gu 384
26.0%
jongno-gu 382
25.9%
seongbuk-gu 110
 
7.5%
gwanak-gu 108
 
7.3%
jung-gu 103
 
7.0%
seodaemun-gu 74
 
5.0%
seocho-gu 52
 
3.5%
dongjak-gu 39
 
2.6%
gangnam-gu 38
 
2.6%
gangseo-gu 31
 
2.1%
Other values (15) 154
10.4%

행정동
Text

Distinct152
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-11T17:35:08.293441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length13.165424
Min length7

Characters and Unicode

Total characters19419
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)4.5%

Sample

1st rowCheongunhyoja-dong
2nd rowSogong-dong
3rd rowSogong-dong
4th rowBomun-dong
5th rowBomun-dong
ValueCountFrequency (%)
hangangno-dong 208
 
14.1%
hannam-dong 125
 
8.5%
jongno1.2.3.4ga-dong 101
 
6.8%
sajik-dong 86
 
5.8%
cheongunhyoja-dong 76
 
5.2%
miseong-dong 57
 
3.9%
nakseongdae-dong 46
 
3.1%
anam-dong 44
 
3.0%
chunghyeon-dong 41
 
2.8%
myeong-dong 38
 
2.6%
Other values (142) 653
44.3%
2023-12-11T17:35:08.800539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 3683
19.0%
g 2900
14.9%
o 2710
14.0%
d 1552
8.0%
a 1520
 
7.8%
- 1475
 
7.6%
e 640
 
3.3%
h 446
 
2.3%
H 380
 
2.0%
. 307
 
1.6%
Other values (36) 3806
19.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15470
79.7%
Dash Punctuation 1475
 
7.6%
Uppercase Letter 1475
 
7.6%
Decimal Number 692
 
3.6%
Other Punctuation 307
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 3683
23.8%
g 2900
18.7%
o 2710
17.5%
d 1552
10.0%
a 1520
9.8%
e 640
 
4.1%
h 446
 
2.9%
i 300
 
1.9%
u 274
 
1.8%
y 256
 
1.7%
Other values (10) 1189
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
H 380
25.8%
S 289
19.6%
C 188
12.7%
J 153
10.4%
M 114
 
7.7%
N 72
 
4.9%
A 51
 
3.5%
G 50
 
3.4%
P 47
 
3.2%
B 42
 
2.8%
Other values (7) 89
 
6.0%
Decimal Number
ValueCountFrequency (%)
1 218
31.5%
2 191
27.6%
4 131
18.9%
3 125
18.1%
8 21
 
3.0%
5 4
 
0.6%
6 2
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 1475
100.0%
Other Punctuation
ValueCountFrequency (%)
. 307
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16945
87.3%
Common 2474
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 3683
21.7%
g 2900
17.1%
o 2710
16.0%
d 1552
9.2%
a 1520
9.0%
e 640
 
3.8%
h 446
 
2.6%
H 380
 
2.2%
i 300
 
1.8%
S 289
 
1.7%
Other values (27) 2525
14.9%
Common
ValueCountFrequency (%)
- 1475
59.6%
. 307
 
12.4%
1 218
 
8.8%
2 191
 
7.7%
4 131
 
5.3%
3 125
 
5.1%
8 21
 
0.8%
5 4
 
0.2%
6 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 3683
19.0%
g 2900
14.9%
o 2710
14.0%
d 1552
8.0%
a 1520
 
7.8%
- 1475
 
7.6%
e 640
 
3.3%
h 446
 
2.3%
H 380
 
2.0%
. 307
 
1.6%
Other values (36) 3806
19.6%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct378
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98306
Minimum126.8033
Maximum127.17088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T17:35:09.042813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.8033
5-th percentile126.91878
Q1126.96878
median126.97795
Q3126.99848
95-th percentile127.05808
Maximum127.17088
Range0.3675826
Interquartile range (IQR)0.029708232

Descriptive statistics

Standard deviation0.043060833
Coefficient of variation (CV)0.0003391069
Kurtosis2.932788
Mean126.98306
Median Absolute Deviation (MAD)0.019414547
Skewness-0.069421645
Sum187300.02
Variance0.0018542353
MonotonicityNot monotonic
2023-12-11T17:35:09.277749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9779494323 207
 
14.0%
126.9984838194 117
 
7.9%
126.9707639611 75
 
5.1%
126.9187772571 57
 
3.9%
126.9824538449 45
 
3.1%
126.9579934852 44
 
3.0%
126.9743475252 41
 
2.8%
126.9690236271 30
 
2.0%
126.9973639789 27
 
1.8%
126.964880108 27
 
1.8%
Other values (368) 805
54.6%
ValueCountFrequency (%)
126.8032977558 1
 
0.1%
126.805917366 2
 
0.1%
126.8140518727 1
 
0.1%
126.828839459 1
 
0.1%
126.8395193617 1
 
0.1%
126.8398905235 2
 
0.1%
126.8406079631 1
 
0.1%
126.8480762789 1
 
0.1%
126.8481351331 20
1.4%
126.8508812082 1
 
0.1%
ValueCountFrequency (%)
127.1708803571 1
0.1%
127.1451045948 1
0.1%
127.1323154885 1
0.1%
127.1305992737 1
0.1%
127.1215696435 2
0.1%
127.1206173957 1
0.1%
127.1109136415 1
0.1%
127.1070644329 1
0.1%
127.1059034908 1
0.1%
127.1058634152 1
0.1%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct378
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.551923
Minimum37.444011
Maximum37.697105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.1 KiB
2023-12-11T17:35:09.513734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.444011
5-th percentile37.473716
Q137.52427
median37.559899
Q337.57764
95-th percentile37.616452
Maximum37.697105
Range0.25309402
Interquartile range (IQR)0.053369749

Descriptive statistics

Standard deviation0.041382883
Coefficient of variation (CV)0.0011020177
Kurtosis0.30802474
Mean37.551923
Median Absolute Deviation (MAD)0.024604783
Skewness-0.0095050325
Sum55389.086
Variance0.001712543
MonotonicityNot monotonic
2023-12-11T17:35:09.765310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.524269884 207
 
14.0%
37.5385437936 117
 
7.9%
37.5698408482 75
 
5.1%
37.4807614879 57
 
3.9%
37.5737174434 45
 
3.1%
37.468593076 44
 
3.0%
37.5770063925 41
 
2.8%
37.5519718363 30
 
2.0%
37.5936234625 27
 
1.8%
37.5649558474 27
 
1.8%
Other values (368) 805
54.6%
ValueCountFrequency (%)
37.4440114146 1
0.1%
37.4510956978 1
0.1%
37.4525029034 1
0.1%
37.4584935909 1
0.1%
37.4612704888 1
0.1%
37.4626384395 1
0.1%
37.4629383312 1
0.1%
37.4643191489 1
0.1%
37.466110681 1
0.1%
37.4679026584 1
0.1%
ValueCountFrequency (%)
37.6971054391 1
0.1%
37.6942688733 2
0.1%
37.6940888554 1
0.1%
37.687104418 1
0.1%
37.6855272592 1
0.1%
37.6842513786 1
0.1%
37.6818369679 1
0.1%
37.6795105517 1
0.1%
37.6788782066 1
0.1%
37.6747555224 1
0.1%

지정일
Date

Distinct316
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
Minimum1901-11-30 00:00:00
Maximum2014-10-30 00:00:00
2023-12-11T17:35:09.965372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:10.199604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

해제일
Date

MISSING 

Distinct18
Distinct (%)52.9%
Missing1441
Missing (%)97.7%
Memory size11.7 KiB
Minimum1978-12-18 00:00:00
Maximum2014-12-31 00:00:00
2023-12-11T17:35:10.374576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:10.540673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

Interactions

2023-12-11T17:35:03.299929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:02.448564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:02.838289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:03.415028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:02.566185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:02.982472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:03.574623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:02.689137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:35:03.141487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:35:10.670544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문화재 일련번호행정구X좌표Y좌표해제일
문화재 일련번호1.0000.3080.2630.2610.923
행정구0.3081.0000.9410.9380.917
X좌표0.2630.9411.0000.6800.954
Y좌표0.2610.9380.6801.0000.853
해제일0.9230.9170.9540.8531.000
2023-12-11T17:35:10.816267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
문화재 일련번호X좌표Y좌표행정구
문화재 일련번호1.000-0.094-0.1440.265
X좌표-0.0941.0000.1890.699
Y좌표-0.1440.1891.0000.687
행정구0.2650.6990.6871.000

Missing values

2023-12-11T17:35:03.737007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:35:03.906367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T17:35:04.024567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

키값문화재 일련번호문화재명칭수량ㆍ규모행정시행정구행정동X좌표Y좌표지정일해제일
0BE_LiST24-103830270Baekundong Valley of Inwangsan Mountain<NA>SeoulJongno-guCheongunhyoja-dong126.96682537.5896982014-10-30<NA>
1BE_LiST24-025630269Underground Waterway of Namdaemun-ro<NA>SeoulJung-guSogong-dong126.98142437.5624662014-07-03<NA>
2BE_LiST24-076430268Underground Waterway of Seoulgwangjang Square<NA>SeoulJung-guSogong-dong126.9764837.5648762014-07-03<NA>
3BE_LiST24-044430278Painting of Nectar Ritual of Mitasa Temple<NA>SeoulSeongbuk-guBomun-dong127.01631737.5849732014-07-03<NA>
4BE_LiST24-044530280Painting of Hermit Sage of Mitasa Temple<NA>SeoulSeongbuk-guBomun-dong127.01631737.5849732014-07-03<NA>
5BE_LiST24-044630279Painting of Mountain Spirit of Mitasa Temple<NA>SeoulSeongbuk-guBomun-dong127.01631737.5849732014-07-03<NA>
6BE_LiST24-098430277Wolamdong (Letters carved on the side of Rock)<NA>SeoulJongno-guGyonam-dong126.96556637.5705532014-06-26<NA>
7BE_LiST24-067930275Samcheongdongmun (Letters carved on Rock)<NA>SeoulJongno-guSamcheong-dong126.98222537.5837542014-06-26<NA>
8BE_LiST24-052430276Baekhojeong Archery Field<NA>SeoulJongno-guCheongunhyoja-dong126.96551737.5790222014-06-26<NA>
9BE_LiST24-074030561Rock-carved Seated Bodhisattva at Okcheonam Hermitage Seoul1pieceSeoulSeodaemun-guHongeun1-dong126.95390437.5970562014-03-11<NA>
키값문화재 일련번호문화재명칭수량ㆍ규모행정시행정구행정동X좌표Y좌표지정일해제일
1465BE_LiST24-129411589Celadon Incense Burner with Girin-shaped Lid1pieceSeoulSeongbuk-guSeongbuk-dong126.99736437.5936231962-12-20<NA>
1466BE_LiST24-066211127Three-story Stone Pagoda in Beomhak-ri Sancheong1pieceSeoulYongsan-guHangangno-dong126.97794937.524271962-12-20<NA>
1467BE_LiST24-003511603Ten-story Stone Pagoda from Gyeongcheonsa Temple Site Gaeseong1pieceSeoulYongsan-guHangangno-dong126.97794937.524271962-12-20<NA>
1468BE_LiST24-138411125Stupa of State Preceptor Hongbeop from Jeongtosa Temple Site Chungju1pieceSeoulYongsan-guHangangno-dong126.97794937.524271962-12-20<NA>
1469BE_LiST24-134311612Celadon Prunus Vase with Incised Lotus and Scroll Design1pieceSeoulYongsan-guHangangno-dong126.97794937.524271962-12-20<NA>
1470BE_LiST24-102711615Portrait of Yi Je-hyeon1pieceSeoulYongsan-guHangangno-dong126.97794937.524271962-12-20<NA>
1471BE_LiST24-075211343Lacebark Pine of Jogyesa Temple Seoul1pieceSeoulJongno-guJongno1.2.3.4ga-dong126.98245437.5737171962-12-03<NA>
1472BE_LiST24-075011342Lacebark Pine of Jae-dong Seoul1pieceSeoulJongno-guGahoe-dong126.98536437.5782051962-12-03<NA>
1473BE_LiST24-087311215Yun Po-sun's House in Anguk-dong4664㎡SeoulJongno-guSamcheong-dong126.98331337.5786731902-01-29<NA>
1474BE_LiST24-106712238Artifacts Used by Jang Yeong-jik一括(6種41点)SeoulJongno-guCheongunhyoja-dong126.97677637.5866011901-11-30<NA>