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-13052/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 08:34:16.477816
Analysis finished2023-12-11 08:34:19.583330
Duration3.11 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
2023-12-11T17:34:19.835214image/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_LiST24-0446
3rd rowBE_LiST24-0444
4th rowBE_LiST24-0764
5th rowBE_LiST24-0445
ValueCountFrequency (%)
be_list24-1038 1
 
0.1%
be_list24-0932 1
 
0.1%
be_list24-0666 1
 
0.1%
be_list24-0144 1
 
0.1%
be_list24-0976 1
 
0.1%
be_list24-0142 1
 
0.1%
be_list24-0667 1
 
0.1%
be_list24-1407 1
 
0.1%
be_list24-1156 1
 
0.1%
be_list24-1158 1
 
0.1%
Other values (1465) 1465
99.3%
2023-12-11T17:34:20.381337image/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
2023-12-11T17:34:20.616086image/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
2023-12-11T17:34:21.134748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30270 1
 
0.1%
11203 1
 
0.1%
11846 1
 
0.1%
11858 1
 
0.1%
11856 1
 
0.1%
11854 1
 
0.1%
11855 1
 
0.1%
11857 1
 
0.1%
11202 1
 
0.1%
11205 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

Distinct1403
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-11T17:34:21.475758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length28
Mean length9.9159322
Min length1

Characters and Unicode

Total characters14626
Distinct characters1374
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1357 ?
Unique (%)92.0%

Sample

1st row仁王山 白雲洞 溪谷
2nd row彌陀寺 山神圖
3rd row彌陀寺 甘露圖
4th row首?廣場 地下排水路
5th row彌陀寺 獨聖圖
ValueCountFrequency (%)
61
 
2.0%
首 51
 
1.7%
靑磁 44
 
1.4%
白磁 33
 
1.1%
三層石塔 32
 
1.0%
舍利莊嚴具 29
 
0.9%
佛國寺 28
 
0.9%
家屋 26
 
0.8%
肖像 26
 
0.8%
出土 24
 
0.8%
Other values (1759) 2734
88.5%
2023-12-11T17:34:22.028284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1671
 
11.4%
圖 216
 
1.5%
寺 204
 
1.4%
佛 196
 
1.3%
卷 186
 
1.3%
大 177
 
1.2%
文 168
 
1.1%
經 164
 
1.1%
靑 161
 
1.1%
- 133
 
0.9%
Other values (1364) 11350
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12393
84.7%
Space Separator 1671
 
11.4%
Decimal Number 151
 
1.0%
Dash Punctuation 133
 
0.9%
Other Punctuation 91
 
0.6%
Close Punctuation 46
 
0.3%
Open Punctuation 46
 
0.3%
Math Symbol 40
 
0.3%
Lowercase Letter 24
 
0.2%
Final Punctuation 14
 
0.1%
Other values (2) 17
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
圖 216
 
1.7%
寺 204
 
1.6%
佛 196
 
1.6%
卷 186
 
1.5%
大 177
 
1.4%
文 168
 
1.4%
經 164
 
1.3%
靑 161
 
1.3%
三 128
 
1.0%
像 128
 
1.0%
Other values (1322) 10665
86.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
16.7%
n 3
12.5%
o 3
12.5%
d 2
8.3%
r 2
8.3%
p 2
8.3%
l 2
8.3%
g 1
 
4.2%
w 1
 
4.2%
t 1
 
4.2%
Other values (3) 3
12.5%
Decimal Number
ValueCountFrequency (%)
1 31
20.5%
2 24
15.9%
3 20
13.2%
5 18
11.9%
7 16
10.6%
4 16
10.6%
0 10
 
6.6%
6 9
 
6.0%
8 5
 
3.3%
9 2
 
1.3%
Other Punctuation
ValueCountFrequency (%)
? 88
96.7%
' 2
 
2.2%
. 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 41
89.1%
」 4
 
8.7%
] 1
 
2.2%
Open Punctuation
ValueCountFrequency (%)
( 41
89.1%
「 4
 
8.7%
[ 1
 
2.2%
Math Symbol
ValueCountFrequency (%)
~ 36
90.0%
> 2
 
5.0%
< 2
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
U 1
33.3%
S 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
1671
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 14
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Han 12373
84.6%
Common 2206
 
15.1%
Latin 27
 
0.2%
Hangul 20
 
0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
圖 216
 
1.7%
寺 204
 
1.6%
佛 196
 
1.6%
卷 186
 
1.5%
大 177
 
1.4%
文 168
 
1.4%
經 164
 
1.3%
靑 161
 
1.3%
三 128
 
1.0%
像 128
 
1.0%
Other values (1313) 10645
86.0%
Common
ValueCountFrequency (%)
1671
75.7%
- 133
 
6.0%
? 88
 
4.0%
) 41
 
1.9%
( 41
 
1.9%
~ 36
 
1.6%
1 31
 
1.4%
2 24
 
1.1%
3 20
 
0.9%
5 18
 
0.8%
Other values (16) 103
 
4.7%
Latin
ValueCountFrequency (%)
e 4
14.8%
n 3
11.1%
o 3
11.1%
d 2
 
7.4%
r 2
 
7.4%
p 2
 
7.4%
l 2
 
7.4%
g 1
 
3.7%
U 1
 
3.7%
S 1
 
3.7%
Other values (6) 6
22.2%
Hangul
ValueCountFrequency (%)
및 6
30.0%
초 5
25.0%
과 3
15.0%
겹 1
 
5.0%
ㆍ 1
 
5.0%
의 1
 
5.0%
지 1
 
5.0%
가 1
 
5.0%
소 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 11901
81.4%
ASCII 2197
 
15.0%
CJK Compat Ideographs 472
 
3.2%
Punctuation 28
 
0.2%
Hangul 19
 
0.1%
None 8
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1671
76.1%
- 133
 
6.1%
? 88
 
4.0%
) 41
 
1.9%
( 41
 
1.9%
~ 36
 
1.6%
1 31
 
1.4%
2 24
 
1.1%
3 20
 
0.9%
5 18
 
0.8%
Other values (28) 94
 
4.3%
CJK
ValueCountFrequency (%)
圖 216
 
1.8%
寺 204
 
1.7%
佛 196
 
1.6%
卷 186
 
1.6%
大 177
 
1.5%
文 168
 
1.4%
經 164
 
1.4%
靑 161
 
1.4%
三 128
 
1.1%
像 128
 
1.1%
Other values (1251) 10173
85.5%
CJK Compat Ideographs
ValueCountFrequency (%)
金 93
19.7%
蓮 60
12.7%
李 46
 
9.7%
六 39
 
8.3%
立 36
 
7.6%
龍 23
 
4.9%
丹 16
 
3.4%
若 14
 
3.0%
了 9
 
1.9%
柳 8
 
1.7%
Other values (52) 128
27.1%
Punctuation
ValueCountFrequency (%)
’ 14
50.0%
‘ 14
50.0%
Hangul
ValueCountFrequency (%)
및 6
31.6%
초 5
26.3%
과 3
15.8%
겹 1
 
5.3%
의 1
 
5.3%
지 1
 
5.3%
가 1
 
5.3%
소 1
 
5.3%
None
ValueCountFrequency (%)
「 4
50.0%
」 4
50.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

수량ㆍ규모
Text

MISSING 

Distinct464
Distinct (%)32.4%
Missing45
Missing (%)3.1%
Memory size11.7 KiB
2023-12-11T17:34:22.514573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length2
Mean length4.693007
Min length1

Characters and Unicode

Total characters6711
Distinct characters210
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

Unique372 ?
Unique (%)26.0%

Sample

1st row불상 1점
2nd row불상 1점
3rd row불상 3점
4th row1책
5th row1기
ValueCountFrequency (%)
1点 147
 
7.6%
1幅 126
 
6.5%
토지 105
 
5.4%
1점 71
 
3.7%
1基 71
 
3.7%
1個 69
 
3.6%
1軀 59
 
3.0%
건물 58
 
3.0%
1棟 55
 
2.8%
1冊 41
 
2.1%
Other values (578) 1137
58.6%
2023-12-11T17:34:23.179882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1428
21.3%
744
 
11.1%
2 330
 
4.9%
㎡ 226
 
3.4%
3 219
 
3.3%
点 168
 
2.5%
冊 162
 
2.4%
卷 161
 
2.4%
. 153
 
2.3%
4 150
 
2.2%
Other values (200) 2970
44.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2772
41.3%
Other Letter 2572
38.3%
Space Separator 744
 
11.1%
Other Symbol 227
 
3.4%
Other Punctuation 160
 
2.4%
Open Punctuation 98
 
1.5%
Close Punctuation 97
 
1.4%
Lowercase Letter 23
 
0.3%
Uppercase Letter 9
 
0.1%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
点 168
 
6.5%
冊 162
 
6.3%
卷 161
 
6.3%
幅 138
 
5.4%
지 120
 
4.7%
점 112
 
4.4%
토 110
 
4.3%
基 109
 
4.2%
棟 100
 
3.9%
물 84
 
3.3%
Other values (167) 1308
50.9%
Decimal Number
ValueCountFrequency (%)
1 1428
51.5%
2 330
 
11.9%
3 219
 
7.9%
4 150
 
5.4%
5 121
 
4.4%
7 116
 
4.2%
0 111
 
4.0%
6 109
 
3.9%
8 95
 
3.4%
9 93
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
N 2
22.2%
H 1
11.1%
P 1
11.1%
R 1
11.1%
O 1
11.1%
L 1
11.1%
W 1
11.1%
D 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
m 12
52.2%
c 6
26.1%
x 4
 
17.4%
g 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 153
95.6%
: 6
 
3.8%
/ 1
 
0.6%
Other Symbol
ValueCountFrequency (%)
㎡ 226
99.6%
㎝ 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
× 2
50.0%
~ 2
50.0%
Space Separator
ValueCountFrequency (%)
744
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4107
61.2%
Hangul 1404
 
20.9%
Han 1168
 
17.4%
Latin 32
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 120
 
8.5%
점 112
 
8.0%
토 110
 
7.8%
물 84
 
6.0%
건 82
 
5.8%
책 70
 
5.0%
권 60
 
4.3%
석 36
 
2.6%
면 36
 
2.6%
착 35
 
2.5%
Other values (138) 659
46.9%
Han
ValueCountFrequency (%)
点 168
14.4%
冊 162
13.9%
卷 161
13.8%
幅 138
11.8%
基 109
9.3%
棟 100
8.6%
個 80
6.8%
軀 73
6.2%
軸 57
 
4.9%
帖 52
 
4.5%
Other values (19) 68
5.8%
Common
ValueCountFrequency (%)
1 1428
34.8%
744
18.1%
2 330
 
8.0%
㎡ 226
 
5.5%
3 219
 
5.3%
. 153
 
3.7%
4 150
 
3.7%
5 121
 
2.9%
7 116
 
2.8%
0 111
 
2.7%
Other values (11) 509
 
12.4%
Latin
ValueCountFrequency (%)
m 12
37.5%
c 6
18.8%
x 4
 
12.5%
N 2
 
6.2%
g 1
 
3.1%
H 1
 
3.1%
P 1
 
3.1%
R 1
 
3.1%
O 1
 
3.1%
L 1
 
3.1%
Other values (2) 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3910
58.3%
Hangul 1404
 
20.9%
CJK 1168
 
17.4%
CJK Compat 227
 
3.4%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1428
36.5%
744
19.0%
2 330
 
8.4%
3 219
 
5.6%
. 153
 
3.9%
4 150
 
3.8%
5 121
 
3.1%
7 116
 
3.0%
0 111
 
2.8%
6 109
 
2.8%
Other values (20) 429
 
11.0%
CJK Compat
ValueCountFrequency (%)
㎡ 226
99.6%
㎝ 1
 
0.4%
CJK
ValueCountFrequency (%)
点 168
14.4%
冊 162
13.9%
卷 161
13.8%
幅 138
11.8%
基 109
9.3%
棟 100
8.6%
個 80
6.8%
軀 73
6.2%
軸 57
 
4.9%
帖 52
 
4.5%
Other values (19) 68
5.8%
Hangul
ValueCountFrequency (%)
지 120
 
8.5%
점 112
 
8.0%
토 110
 
7.8%
물 84
 
6.0%
건 82
 
5.8%
책 70
 
5.0%
권 60
 
4.3%
석 36
 
2.6%
면 36
 
2.6%
착 35
 
2.5%
Other values (138) 659
46.9%
None
ValueCountFrequency (%)
× 2
100.0%

행정시
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
首?特?市
1475 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row首?特?市
2nd row首?特?市
3rd row首?特?市
4th row首?特?市
5th row首?特?市

Common Values

ValueCountFrequency (%)
首?特?市 1475
100.0%

Length

2023-12-11T17:34:23.375417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:34:23.519236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
首?特?市 1475
100.0%

행정구
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
?山?
384 
?路?
382 
城北?
110 
冠岳?
108 
中?
103 
Other values (20)
388 

Length

Max length4
Median length3
Mean length2.9938983
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row?路?
2nd row城北?
3rd row城北?
4th row中?
5th row城北?

Common Values

ValueCountFrequency (%)
?山? 384
26.0%
?路? 382
25.9%
城北? 110
 
7.5%
冠岳? 108
 
7.3%
中? 103
 
7.0%
西大?? 74
 
5.0%
瑞草? 52
 
3.5%
?雀? 39
 
2.6%
江南? 38
 
2.6%
江西? 31
 
2.1%
Other values (15) 154
10.4%

Length

2023-12-11T17:34:23.674978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
山 384
26.0%
路 382
25.9%
城北 110
 
7.5%
冠岳 108
 
7.3%
中 103
 
7.0%
西大 74
 
5.0%
瑞草 52
 
3.5%
雀 39
 
2.6%
江南 38
 
2.6%
江西 31
 
2.1%
Other values (15) 154
10.4%

행정동
Text

Distinct143
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size11.7 KiB
2023-12-11T17:34:23.931375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7
Mean length3.9620339
Min length2

Characters and Unicode

Total characters5844
Distinct characters140
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)4.1%

Sample

1st row?云孝子洞
2nd row普?洞
3rd row普?洞
4th row小公洞
5th row普?洞
ValueCountFrequency (%)
江路洞 208
 
14.1%
南洞 129
 
8.7%
路1.2.3.4街洞 101
 
6.8%
社稷洞 86
 
5.8%
云孝子洞 76
 
5.2%
米星洞 57
 
3.9%
落星垈 46
 
3.1%
安岩洞 44
 
3.0%
忠?洞 41
 
2.8%
明洞 38
 
2.6%
Other values (132) 649
44.0%
2023-12-11T17:34:24.348467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
洞 1429
24.5%
? 850
14.5%
路 321
 
5.5%
. 307
 
5.3%
1 217
 
3.7%
江 209
 
3.6%
2 193
 
3.3%
南 133
 
2.3%
4 131
 
2.2%
3 124
 
2.1%
Other values (130) 1930
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3995
68.4%
Other Punctuation 1157
 
19.8%
Decimal Number 692
 
11.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
洞 1429
35.8%
路 321
 
8.0%
江 209
 
5.2%
南 133
 
3.3%
街 103
 
2.6%
星 103
 
2.6%
社 86
 
2.2%
稷 86
 
2.2%
孝 81
 
2.0%
云 76
 
1.9%
Other values (121) 1368
34.2%
Decimal Number
ValueCountFrequency (%)
1 217
31.4%
2 193
27.9%
4 131
18.9%
3 124
17.9%
8 21
 
3.0%
5 4
 
0.6%
6 2
 
0.3%
Other Punctuation
ValueCountFrequency (%)
? 850
73.5%
. 307
 
26.5%

Most occurring scripts

ValueCountFrequency (%)
Han 3993
68.3%
Common 1849
31.6%
Hangul 2
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
洞 1429
35.8%
路 321
 
8.0%
江 209
 
5.2%
南 133
 
3.3%
街 103
 
2.6%
星 103
 
2.6%
社 86
 
2.2%
稷 86
 
2.2%
孝 81
 
2.0%
云 76
 
1.9%
Other values (120) 1366
34.2%
Common
ValueCountFrequency (%)
? 850
46.0%
. 307
 
16.6%
1 217
 
11.7%
2 193
 
10.4%
4 131
 
7.1%
3 124
 
6.7%
8 21
 
1.1%
5 4
 
0.2%
6 2
 
0.1%
Hangul
ValueCountFrequency (%)
쒧 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
CJK 3993
68.3%
ASCII 1849
31.6%
Hangul 2
 
< 0.1%

Most frequent character per block

CJK
ValueCountFrequency (%)
洞 1429
35.8%
路 321
 
8.0%
江 209
 
5.2%
南 133
 
3.3%
街 103
 
2.6%
星 103
 
2.6%
社 86
 
2.2%
稷 86
 
2.2%
孝 81
 
2.0%
云 76
 
1.9%
Other values (120) 1366
34.2%
ASCII
ValueCountFrequency (%)
? 850
46.0%
. 307
 
16.6%
1 217
 
11.7%
2 193
 
10.4%
4 131
 
7.1%
3 124
 
6.7%
8 21
 
1.1%
5 4
 
0.2%
6 2
 
0.1%
Hangul
ValueCountFrequency (%)
쒧 2
100.0%

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
2023-12-11T17:34:24.528223image/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
2023-12-11T17:34:24.760083image/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
2023-12-11T17:34:24.945462image/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
2023-12-11T17:34:25.190321image/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
2023-12-11T17:34:25.403538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:25.615433image/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
2023-12-11T17:34:25.765639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:25.923444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

Interactions

2023-12-11T17:34:18.604475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:17.714568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:18.176529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:18.749236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:17.858305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:18.358578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:18.922389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:18.031457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T17:34:18.491806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T17:34:26.034553image/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
2023-12-11T17:34:26.147895image/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

2023-12-11T17:34:19.122094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:34:19.338028image/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.
2023-12-11T17:34:19.507984image/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_LiST24-103830270仁王山 白雲洞 溪谷<NA>首?特?市?路??云孝子洞126.96682537.5896982014-10-30<NA>
1BE_LiST24-044630279彌陀寺 山神圖<NA>首?特?市城北?普?洞127.01631737.5849732014-07-03<NA>
2BE_LiST24-044430278彌陀寺 甘露圖<NA>首?特?市城北?普?洞127.01631737.5849732014-07-03<NA>
3BE_LiST24-076430268首?廣場 地下排水路<NA>首?特?市中?小公洞126.9764837.5648762014-07-03<NA>
4BE_LiST24-044530280彌陀寺 獨聖圖<NA>首?特?市城北?普?洞127.01631737.5849732014-07-03<NA>
5BE_LiST24-025630269南大門路 地下排水路<NA>首?特?市中?小公洞126.98142437.5624662014-07-03<NA>
6BE_LiST24-067930275三淸洞門<NA>首?特?市?路?三?洞126.98222537.5837542014-06-26<NA>
7BE_LiST24-052430276白虎亭<NA>首?特?市?路??云孝子洞126.96551737.5790222014-06-26<NA>
8BE_LiST24-098430277月巖洞<NA>首?特?市?路??南洞126.96556637.5705532014-06-26<NA>
9BE_LiST24-072430559首? 普陀寺 金銅菩薩坐像불상 1점首?特?市城北?安岩洞127.03044437.5901922014-03-11<NA>
키값문화재 일련번호문화재명칭수량ㆍ규모행정시행정구행정동X좌표Y좌표지정일해제일
1465BE_LiST24-007011599慶州 九黃洞 金製如來立像1軀首?特?市?山??江路洞126.97794937.524271962-12-20<NA>
1466BE_LiST24-007111598慶州 九黃洞 金製如來坐像1軀首?特?市?山??江路洞126.97794937.524271962-12-20<NA>
1467BE_LiST24-007411605慶州 夫婦塚 金製耳飾1雙首?特?市?山??江路洞126.97794937.524271962-12-20<NA>
1468BE_LiST24-129811587靑磁 獅子形蓋 香爐1点首?特?市?山??江路洞126.97794937.524271962-12-20<NA>
1469BE_LiST24-074430340首? 圓覺寺址 十層石塔<NA>首?特?市?路??路1.2.3.4街洞126.98820537.5715491962-12-20<NA>
1470BE_LiST24-016311595金銅三尊佛龕1座首?特?市城北?城北洞126.99736437.5936231962-12-20<NA>
1471BE_LiST24-075211343首? 曹溪寺 白松한그루首?特?市?路??路1.2.3.4街洞126.98245437.5737171962-12-03<NA>
1472BE_LiST24-075011342首? 齋洞 白松한그루首?特?市?路?嘉?洞126.98536437.5782051962-12-03<NA>
1473BE_LiST24-087311215安國洞 尹潽善家4664㎡首?特?市?路?三?洞126.98331337.5786731902-01-29<NA>
1474BE_LiST24-106712238張榮稷 遺品一括(6種41点)首?特?市?路??云孝子洞126.97677637.5866011901-11-30<NA>