Overview

Dataset statistics

Number of variables16
Number of observations287
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.6 KiB
Average record size in memory130.5 B

Variable types

Numeric1
Categorical8
Text7

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 건축주구분High correlation
건축주구분 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
건축물용도 is highly overall correlated with 건축주구분High correlation
분류 is highly imbalanced (72.8%)Imbalance
건축물용도 is highly imbalanced (54.4%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:28:52.306234
Analysis finished2024-03-14 02:28:53.576987
Duration1.27 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct287
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.32404
Minimum1
Maximum303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-14T11:28:53.639201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.3
Q184.5
median158
Q3230.5
95-th percentile288.7
Maximum303
Range302
Interquartile range (IQR)146

Descriptive statistics

Standard deviation86.409354
Coefficient of variation (CV)0.55275793
Kurtosis-1.1865089
Mean156.32404
Median Absolute Deviation (MAD)73
Skewness-0.054537484
Sum44865
Variance7466.5764
MonotonicityStrictly increasing
2024-03-14T11:28:53.760753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
2 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
210 1
 
0.3%
209 1
 
0.3%
208 1
 
0.3%
207 1
 
0.3%
206 1
 
0.3%
205 1
 
0.3%
Other values (277) 277
96.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
6 1
0.3%
7 1
0.3%
9 1
0.3%
10 1
0.3%
14 1
0.3%
15 1
0.3%
16 1
0.3%
ValueCountFrequency (%)
303 1
0.3%
302 1
0.3%
301 1
0.3%
300 1
0.3%
299 1
0.3%
298 1
0.3%
297 1
0.3%
296 1
0.3%
295 1
0.3%
294 1
0.3%

분류
Categorical

IMBALANCE 

Distinct8
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
조각
245 
회화
31 
공예
 
3
상징탑
 
3
기타
 
2
Other values (3)
 
3

Length

Max length3
Median length2
Mean length2.010453
Min length2

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
조각 245
85.4%
회화 31
 
10.8%
공예 3
 
1.0%
상징탑 3
 
1.0%
기타 2
 
0.7%
사진 1
 
0.3%
서예 1
 
0.3%
벽화 1
 
0.3%

Length

2024-03-14T11:28:53.887074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:54.009332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조각 245
85.4%
회화 31
 
10.8%
공예 3
 
1.0%
상징탑 3
 
1.0%
기타 2
 
0.7%
사진 1
 
0.3%
서예 1
 
0.3%
벽화 1
 
0.3%

작품명
Text

Distinct254
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:54.313606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length5.5505226
Min length1

Characters and Unicode

Total characters1593
Distinct characters332
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)82.9%

Sample

1st row비상
2nd row향기터
3rd row무형유산의시원
4th row평화의소리
5th row공간저너머
ValueCountFrequency (%)
이야기 9
 
2.1%
비상 8
 
1.9%
가족 7
 
1.7%
꿈 6
 
1.4%
풍요 5
 
1.2%
풍경 5
 
1.2%
자연 5
 
1.2%
평화 4
 
0.9%
향연 3
 
0.7%
꿈꾸는 3
 
0.7%
Other values (328) 369
87.0%
2024-03-14T11:28:54.760235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
 
8.6%
의 55
 
3.5%
- 44
 
2.8%
기 30
 
1.9%
가 27
 
1.7%
이 24
 
1.5%
) 23
 
1.4%
( 23
 
1.4%
생 21
 
1.3%
는 20
 
1.3%
Other values (322) 1189
74.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1131
71.0%
Space Separator 137
 
8.6%
Lowercase Letter 124
 
7.8%
Decimal Number 51
 
3.2%
Dash Punctuation 44
 
2.8%
Uppercase Letter 28
 
1.8%
Close Punctuation 23
 
1.4%
Open Punctuation 23
 
1.4%
Other Punctuation 16
 
1.0%
Letter Number 12
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 55
 
4.9%
기 30
 
2.7%
가 27
 
2.4%
이 24
 
2.1%
생 21
 
1.9%
는 20
 
1.8%
화 19
 
1.7%
풍 19
 
1.7%
연 17
 
1.5%
상 17
 
1.5%
Other values (272) 882
78.0%
Lowercase Letter
ValueCountFrequency (%)
e 19
15.3%
r 14
11.3%
a 12
 
9.7%
n 10
 
8.1%
o 8
 
6.5%
t 6
 
4.8%
m 6
 
4.8%
i 5
 
4.0%
p 5
 
4.0%
l 5
 
4.0%
Other values (10) 34
27.4%
Uppercase Letter
ValueCountFrequency (%)
S 4
14.3%
H 4
14.3%
N 3
10.7%
T 3
10.7%
E 3
10.7%
I 2
7.1%
R 2
7.1%
G 1
 
3.6%
P 1
 
3.6%
O 1
 
3.6%
Other values (4) 4
14.3%
Decimal Number
ValueCountFrequency (%)
0 17
33.3%
2 15
29.4%
1 13
25.5%
7 3
 
5.9%
8 2
 
3.9%
6 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 11
68.8%
. 4
 
25.0%
& 1
 
6.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
58.3%
Ⅰ 5
41.7%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1107
69.5%
Common 298
 
18.7%
Latin 164
 
10.3%
Han 24
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 55
 
5.0%
기 30
 
2.7%
가 27
 
2.4%
이 24
 
2.2%
생 21
 
1.9%
는 20
 
1.8%
화 19
 
1.7%
풍 19
 
1.7%
연 17
 
1.5%
상 17
 
1.5%
Other values (249) 858
77.5%
Latin
ValueCountFrequency (%)
e 19
 
11.6%
r 14
 
8.5%
a 12
 
7.3%
n 10
 
6.1%
o 8
 
4.9%
Ⅱ 7
 
4.3%
t 6
 
3.7%
m 6
 
3.7%
i 5
 
3.0%
p 5
 
3.0%
Other values (26) 72
43.9%
Han
ValueCountFrequency (%)
合 2
 
8.3%
飛 1
 
4.2%
生 1
 
4.2%
傳 1
 
4.2%
說 1
 
4.2%
家 1
 
4.2%
族 1
 
4.2%
內 1
 
4.2%
面 1
 
4.2%
氣 1
 
4.2%
Other values (13) 13
54.2%
Common
ValueCountFrequency (%)
137
46.0%
- 44
 
14.8%
) 23
 
7.7%
( 23
 
7.7%
0 17
 
5.7%
2 15
 
5.0%
1 13
 
4.4%
, 11
 
3.7%
. 4
 
1.3%
+ 4
 
1.3%
Other values (4) 7
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1107
69.5%
ASCII 450
28.2%
CJK 24
 
1.5%
Number Forms 12
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
30.4%
- 44
 
9.8%
) 23
 
5.1%
( 23
 
5.1%
e 19
 
4.2%
0 17
 
3.8%
2 15
 
3.3%
r 14
 
3.1%
1 13
 
2.9%
a 12
 
2.7%
Other values (38) 133
29.6%
Hangul
ValueCountFrequency (%)
의 55
 
5.0%
기 30
 
2.7%
가 27
 
2.4%
이 24
 
2.2%
생 21
 
1.9%
는 20
 
1.8%
화 19
 
1.7%
풍 19
 
1.7%
연 17
 
1.5%
상 17
 
1.5%
Other values (249) 858
77.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
58.3%
Ⅰ 5
41.7%
CJK
ValueCountFrequency (%)
合 2
 
8.3%
飛 1
 
4.2%
生 1
 
4.2%
傳 1
 
4.2%
說 1
 
4.2%
家 1
 
4.2%
族 1
 
4.2%
內 1
 
4.2%
面 1
 
4.2%
氣 1
 
4.2%
Other values (13) 13
54.2%

시군명
Categorical

Distinct13
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
전주시
151 
군산시
45 
익산시
45 
완주군
 
15
정읍시
 
8
Other values (8)
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)1.0%

Sample

1st row전주시
2nd row정읍시
3rd row전주시
4th row전주시
5th row전주시

Common Values

ValueCountFrequency (%)
전주시 151
52.6%
군산시 45
 
15.7%
익산시 45
 
15.7%
완주군 15
 
5.2%
정읍시 8
 
2.8%
고창군 7
 
2.4%
김제시 7
 
2.4%
순창군 2
 
0.7%
무주군 2
 
0.7%
남원시 2
 
0.7%
Other values (3) 3
 
1.0%

Length

2024-03-14T11:28:54.868747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 151
52.6%
군산시 45
 
15.7%
익산시 45
 
15.7%
완주군 15
 
5.2%
정읍시 8
 
2.8%
고창군 7
 
2.4%
김제시 7
 
2.4%
순창군 2
 
0.7%
무주군 2
 
0.7%
남원시 2
 
0.7%
Other values (3) 3
 
1.0%

작가명
Text

Distinct134
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:55.139906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.9860627
Min length2

Characters and Unicode

Total characters857
Distinct characters117
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)32.4%

Sample

1st row권치규
2nd row원유진
3rd row이용백
4th row국경오
5th row국경오
ValueCountFrequency (%)
김동헌 27
 
9.4%
국경오 18
 
6.3%
엄혁용 14
 
4.9%
강용면 12
 
4.2%
이한우 11
 
3.8%
선기현 10
 
3.5%
이효문 6
 
2.1%
유휴열 6
 
2.1%
김귀복 6
 
2.1%
김상호 5
 
1.7%
Other values (124) 172
59.9%
2024-03-14T11:28:55.527756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 65
 
7.6%
이 41
 
4.8%
동 33
 
3.9%
용 33
 
3.9%
경 29
 
3.4%
헌 27
 
3.2%
현 27
 
3.2%
오 24
 
2.8%
정 22
 
2.6%
강 22
 
2.6%
Other values (107) 534
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 857
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 65
 
7.6%
이 41
 
4.8%
동 33
 
3.9%
용 33
 
3.9%
경 29
 
3.4%
헌 27
 
3.2%
현 27
 
3.2%
오 24
 
2.8%
정 22
 
2.6%
강 22
 
2.6%
Other values (107) 534
62.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 857
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 65
 
7.6%
이 41
 
4.8%
동 33
 
3.9%
용 33
 
3.9%
경 29
 
3.4%
헌 27
 
3.2%
현 27
 
3.2%
오 24
 
2.8%
정 22
 
2.6%
강 22
 
2.6%
Other values (107) 534
62.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 857
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 65
 
7.6%
이 41
 
4.8%
동 33
 
3.9%
용 33
 
3.9%
경 29
 
3.4%
헌 27
 
3.2%
현 27
 
3.2%
오 24
 
2.8%
정 22
 
2.6%
강 22
 
2.6%
Other values (107) 534
62.3%

건축물명
Text

Distinct207
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:55.756089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length9.4006969
Min length1

Characters and Unicode

Total characters2698
Distinct characters278
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)55.7%

Sample

1st row농촌진흥청
2nd row대광 로제비앙아파트
3rd row국립무형유산원
4th row호반베르디움 아파트
5th row전주효자복합시설
ValueCountFrequency (%)
아파트 46
 
9.2%
전북대학교 13
 
2.6%
어린이병원 13
 
2.6%
익산 9
 
1.8%
전주점 8
 
1.6%
휴먼시아 7
 
1.4%
현대 7
 
1.4%
주공아파트 6
 
1.2%
롯데마트 6
 
1.2%
롯데백화점 5
 
1.0%
Other values (258) 380
76.0%
2024-03-14T11:28:56.084317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 231
 
8.6%
트 227
 
8.4%
파 218
 
8.1%
213
 
7.9%
주 54
 
2.0%
대 47
 
1.7%
전 46
 
1.7%
지 46
 
1.7%
동 39
 
1.4%
스 37
 
1.4%
Other values (268) 1540
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2361
87.5%
Space Separator 213
 
7.9%
Decimal Number 43
 
1.6%
Uppercase Letter 32
 
1.2%
Lowercase Letter 20
 
0.7%
Dash Punctuation 19
 
0.7%
Close Punctuation 4
 
0.1%
Other Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 231
 
9.8%
트 227
 
9.6%
파 218
 
9.2%
주 54
 
2.3%
대 47
 
2.0%
전 46
 
1.9%
지 46
 
1.9%
동 39
 
1.7%
스 37
 
1.6%
이 35
 
1.5%
Other values (239) 1381
58.5%
Uppercase Letter
ValueCountFrequency (%)
P 7
21.9%
K 6
18.8%
I 4
12.5%
A 3
9.4%
S 3
9.4%
R 3
9.4%
W 2
 
6.2%
J 2
 
6.2%
G 1
 
3.1%
B 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
2 18
41.9%
1 10
23.3%
3 5
 
11.6%
5 4
 
9.3%
8 2
 
4.7%
9 1
 
2.3%
7 1
 
2.3%
4 1
 
2.3%
6 1
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
e 7
35.0%
k 4
20.0%
r 4
20.0%
a 4
20.0%
ｉ 1
 
5.0%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2361
87.5%
Common 285
 
10.6%
Latin 52
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 231
 
9.8%
트 227
 
9.6%
파 218
 
9.2%
주 54
 
2.3%
대 47
 
2.0%
전 46
 
1.9%
지 46
 
1.9%
동 39
 
1.7%
스 37
 
1.6%
이 35
 
1.5%
Other values (239) 1381
58.5%
Latin
ValueCountFrequency (%)
e 7
13.5%
P 7
13.5%
K 6
11.5%
k 4
7.7%
r 4
7.7%
a 4
7.7%
I 4
7.7%
A 3
5.8%
S 3
5.8%
R 3
5.8%
Other values (5) 7
13.5%
Common
ValueCountFrequency (%)
213
74.7%
- 19
 
6.7%
2 18
 
6.3%
1 10
 
3.5%
3 5
 
1.8%
5 4
 
1.4%
) 4
 
1.4%
, 3
 
1.1%
( 3
 
1.1%
8 2
 
0.7%
Other values (4) 4
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2361
87.5%
ASCII 336
 
12.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 231
 
9.8%
트 227
 
9.6%
파 218
 
9.2%
주 54
 
2.3%
대 47
 
2.0%
전 46
 
1.9%
지 46
 
1.9%
동 39
 
1.7%
스 37
 
1.6%
이 35
 
1.5%
Other values (239) 1381
58.5%
ASCII
ValueCountFrequency (%)
213
63.4%
- 19
 
5.7%
2 18
 
5.4%
1 10
 
3.0%
e 7
 
2.1%
P 7
 
2.1%
K 6
 
1.8%
3 5
 
1.5%
5 4
 
1.2%
k 4
 
1.2%
Other values (18) 43
 
12.8%
None
ValueCountFrequency (%)
ｉ 1
100.0%

도로명주소
Text

Distinct207
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:56.377664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length13.745645
Min length9

Characters and Unicode

Total characters3945
Distinct characters174
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)55.1%

Sample

1st row전주시 완산구 농생명로 300
2nd row정읍시 학산로 89-9
3rd row전주시 완산구 서학로 95
4th row전주시 완산구 유연로 217
5th row전주시 완산구 용머리로 45
ValueCountFrequency (%)
전주시 152
 
14.6%
완산구 87
 
8.3%
덕진구 65
 
6.2%
군산시 45
 
4.3%
익산시 45
 
4.3%
건지로 15
 
1.4%
20 15
 
1.4%
완주군 14
 
1.3%
봉동읍 9
 
0.9%
12 8
 
0.8%
Other values (320) 587
56.3%
2024-03-14T11:28:56.741634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
755
19.1%
시 260
 
6.6%
로 226
 
5.7%
산 215
 
5.4%
1 187
 
4.7%
주 169
 
4.3%
전 157
 
4.0%
구 155
 
3.9%
2 122
 
3.1%
완 101
 
2.6%
Other values (164) 1598
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2386
60.5%
Decimal Number 782
 
19.8%
Space Separator 755
 
19.1%
Dash Punctuation 21
 
0.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 260
 
10.9%
로 226
 
9.5%
산 215
 
9.0%
주 169
 
7.1%
전 157
 
6.6%
구 155
 
6.5%
완 101
 
4.2%
길 81
 
3.4%
군 73
 
3.1%
덕 69
 
2.9%
Other values (151) 880
36.9%
Decimal Number
ValueCountFrequency (%)
1 187
23.9%
2 122
15.6%
3 99
12.7%
0 81
10.4%
5 64
 
8.2%
4 58
 
7.4%
7 52
 
6.6%
6 45
 
5.8%
9 43
 
5.5%
8 31
 
4.0%
Space Separator
ValueCountFrequency (%)
755
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2386
60.5%
Common 1559
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 260
 
10.9%
로 226
 
9.5%
산 215
 
9.0%
주 169
 
7.1%
전 157
 
6.6%
구 155
 
6.5%
완 101
 
4.2%
길 81
 
3.4%
군 73
 
3.1%
덕 69
 
2.9%
Other values (151) 880
36.9%
Common
ValueCountFrequency (%)
755
48.4%
1 187
 
12.0%
2 122
 
7.8%
3 99
 
6.4%
0 81
 
5.2%
5 64
 
4.1%
4 58
 
3.7%
7 52
 
3.3%
6 45
 
2.9%
9 43
 
2.8%
Other values (3) 53
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2386
60.5%
ASCII 1559
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
755
48.4%
1 187
 
12.0%
2 122
 
7.8%
3 99
 
6.4%
0 81
 
5.2%
5 64
 
4.1%
4 58
 
3.7%
7 52
 
3.3%
6 45
 
2.9%
9 43
 
2.8%
Other values (3) 53
 
3.4%
Hangul
ValueCountFrequency (%)
시 260
 
10.9%
로 226
 
9.5%
산 215
 
9.0%
주 169
 
7.1%
전 157
 
6.6%
구 155
 
6.5%
완 101
 
4.2%
길 81
 
3.4%
군 73
 
3.1%
덕 69
 
2.9%
Other values (151) 880
36.9%

건축주구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
-
203 
공공
63 
민간
 
20
기타(공공+
 
1

Length

Max length6
Median length1
Mean length1.3066202
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row기타(공공+
2nd row민간
3rd row공공
4th row공공
5th row공공

Common Values

ValueCountFrequency (%)
- 203
70.7%
공공 63
 
22.0%
민간 20
 
7.0%
기타(공공+ 1
 
0.3%

Length

2024-03-14T11:28:56.850581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:56.941046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
203
70.7%
공공 63
 
22.0%
민간 20
 
7.0%
기타(공공 1
 
0.3%

연면적
Text

Distinct148
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:57.154136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.9407666
Min length1

Characters and Unicode

Total characters1705
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)42.2%

Sample

1st row47196.67
2nd row49864.1809
3rd row-
4th row86549.4898
5th row25908.59
ValueCountFrequency (%)
98
34.1%
30788.0 13
 
4.5%
104431.27 3
 
1.0%
182718.73 3
 
1.0%
134812.825 3
 
1.0%
209648.88 3
 
1.0%
12695.3 3
 
1.0%
11523.2997 3
 
1.0%
75519.35 3
 
1.0%
192280.0 2
 
0.7%
Other values (137) 153
53.3%
2024-03-14T11:28:57.546865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 189
11.1%
1 169
9.9%
8 161
9.4%
0 151
8.9%
9 147
8.6%
2 141
8.3%
7 139
8.2%
5 135
7.9%
4 131
7.7%
3 127
7.4%
Other values (2) 215
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1416
83.0%
Other Punctuation 189
 
11.1%
Dash Punctuation 100
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 169
11.9%
8 161
11.4%
0 151
10.7%
9 147
10.4%
2 141
10.0%
7 139
9.8%
5 135
9.5%
4 131
9.3%
3 127
9.0%
6 115
8.1%
Other Punctuation
ValueCountFrequency (%)
. 189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1705
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 189
11.1%
1 169
9.9%
8 161
9.4%
0 151
8.9%
9 147
8.6%
2 141
8.3%
7 139
8.2%
5 135
7.9%
4 131
7.7%
3 127
7.4%
Other values (2) 215
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 189
11.1%
1 169
9.9%
8 161
9.4%
0 151
8.9%
9 147
8.6%
2 141
8.3%
7 139
8.2%
5 135
7.9%
4 131
7.7%
3 127
7.4%
Other values (2) 215
12.6%

건축물용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
근린생활시설
194 
공동주택
62 
의료시설
 
15
업무시설
 
5
공연장, 집회장 및 관람장
 
4
Other values (4)
 
7

Length

Max length14
Median length6
Mean length5.5017422
Min length2

Unique

Unique2 ?
Unique (%)0.7%

Sample

1st row업무시설
2nd row공동주택
3rd row공연장, 집회장 및 관람장
4th row공동주택
5th row근린생활시설

Common Values

ValueCountFrequency (%)
근린생활시설 194
67.6%
공동주택 62
 
21.6%
의료시설 15
 
5.2%
업무시설 5
 
1.7%
공연장, 집회장 및 관람장 4
 
1.4%
숙박시설 3
 
1.0%
판매시설 2
 
0.7%
기타 1
 
0.3%
방송 · 통신시설 1
 
0.3%

Length

2024-03-14T11:28:57.722382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:57.875682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근린생활시설 194
64.5%
공동주택 62
 
20.6%
의료시설 15
 
5.0%
업무시설 5
 
1.7%
공연장 4
 
1.3%
집회장 4
 
1.3%
및 4
 
1.3%
관람장 4
 
1.3%
숙박시설 3
 
1.0%
판매시설 2
 
0.7%
Other values (4) 4
 
1.3%

작품심의일
Text

Distinct91
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:58.138775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length6.5818815
Min length1

Characters and Unicode

Total characters1889
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)19.5%

Sample

1st row2013-04-05
2nd row2013-06-19
3rd row2013-06-19
4th row2014-03-20
5th row2014-05-28
ValueCountFrequency (%)
103
35.9%
2011-11-29 11
 
3.8%
2001 8
 
2.8%
2013-03-06 8
 
2.8%
2013-06-19 8
 
2.8%
2007-02-06 6
 
2.1%
2012-05-31 6
 
2.1%
2012-08-24 6
 
2.1%
2012-01-05 5
 
1.7%
2007-10-26 5
 
1.7%
Other values (81) 121
42.2%
2024-03-14T11:28:58.618429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 504
26.7%
- 453
24.0%
2 321
17.0%
1 236
12.5%
6 79
 
4.2%
3 68
 
3.6%
7 62
 
3.3%
9 49
 
2.6%
4 42
 
2.2%
8 38
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1436
76.0%
Dash Punctuation 453
 
24.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 504
35.1%
2 321
22.4%
1 236
16.4%
6 79
 
5.5%
3 68
 
4.7%
7 62
 
4.3%
9 49
 
3.4%
4 42
 
2.9%
8 38
 
2.6%
5 37
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 453
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1889
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 504
26.7%
- 453
24.0%
2 321
17.0%
1 236
12.5%
6 79
 
4.2%
3 68
 
3.6%
7 62
 
3.3%
9 49
 
2.6%
4 42
 
2.2%
8 38
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 504
26.7%
- 453
24.0%
2 321
17.0%
1 236
12.5%
6 79
 
4.2%
3 68
 
3.6%
7 62
 
3.3%
9 49
 
2.6%
4 42
 
2.2%
8 38
 
2.0%

작품설치일
Text

Distinct199
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-14T11:28:58.873720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.3101045
Min length1

Characters and Unicode

Total characters2672
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)51.6%

Sample

1st row2014-08-13
2nd row2014-08-13
3rd row2014-07-28
4th row2014-07-21
5th row2014-07-21
ValueCountFrequency (%)
2012-12-14 13
 
4.5%
6
 
2.1%
2001 6
 
2.1%
2014-04-10 4
 
1.4%
2006-06 4
 
1.4%
2003-11-14 4
 
1.4%
2007-11-06 3
 
1.0%
2007-11-15 3
 
1.0%
2003-12 3
 
1.0%
2009-04-06 3
 
1.0%
Other values (189) 238
82.9%
2024-03-14T11:28:59.210051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 778
29.1%
- 520
19.5%
2 455
17.0%
1 391
14.6%
3 106
 
4.0%
4 96
 
3.6%
6 79
 
3.0%
8 73
 
2.7%
7 62
 
2.3%
5 60
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2152
80.5%
Dash Punctuation 520
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 778
36.2%
2 455
21.1%
1 391
18.2%
3 106
 
4.9%
4 96
 
4.5%
6 79
 
3.7%
8 73
 
3.4%
7 62
 
2.9%
5 60
 
2.8%
9 52
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 520
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2672
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 778
29.1%
- 520
19.5%
2 455
17.0%
1 391
14.6%
3 106
 
4.0%
4 96
 
3.6%
6 79
 
3.0%
8 73
 
2.7%
7 62
 
2.3%
5 60
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 778
29.1%
- 520
19.5%
2 455
17.0%
1 391
14.6%
3 106
 
4.0%
4 96
 
3.6%
6 79
 
3.0%
8 73
 
2.7%
7 62
 
2.3%
5 60
 
2.2%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
문화예술과
287 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화예술과 287
100.0%

Length

2024-03-14T11:28:59.338070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:59.418658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화예술과 287
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
공개
287 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 287
100.0%

Length

2024-03-14T11:28:59.492316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:59.564892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 287
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2015.1
287 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 287
100.0%

Length

2024-03-14T11:28:59.658702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:59.731257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 287
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
1년
287 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 287
100.0%

Length

2024-03-14T11:28:59.808174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:28:59.922616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 287
100.0%

Interactions

2024-03-14T11:28:53.166267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:28:59.984629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번분류시군명건축주구분건축물용도작품심의일
순번1.0000.3180.2590.7200.6370.924
분류0.3181.0000.2920.2330.3570.000
시군명0.2590.2921.0000.2500.4030.962
건축주구분0.7200.2330.2501.0000.7170.897
건축물용도0.6370.3570.4030.7171.0000.964
작품심의일0.9240.0000.9620.8970.9641.000
2024-03-14T11:29:00.090060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류건축물용도시군명건축주구분
분류1.0000.1830.1340.105
건축물용도0.1831.0000.1840.549
시군명0.1340.1841.0000.145
건축주구분0.1050.5490.1451.000
2024-03-14T11:29:00.168340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번분류시군명건축주구분건축물용도
순번1.0000.1570.1080.5190.354
분류0.1571.0000.1340.1050.183
시군명0.1080.1341.0000.1450.184
건축주구분0.5190.1050.1451.0000.549
건축물용도0.3540.1830.1840.5491.000

Missing values

2024-03-14T11:28:53.330442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:28:53.514090image/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.

Sample

순번분류작품명시군명작가명건축물명도로명주소건축주구분연면적건축물용도작품심의일작품설치일자료출처공개여부작성일갱신주기
01조각비상전주시권치규농촌진흥청전주시 완산구 농생명로 300기타(공공+47196.67업무시설2013-04-052014-08-13문화예술과공개2015.11년
12조각향기터정읍시원유진대광 로제비앙아파트정읍시 학산로 89-9민간49864.1809공동주택2013-06-192014-08-13문화예술과공개2015.11년
23조각무형유산의시원전주시이용백국립무형유산원전주시 완산구 서학로 95공공-공연장, 집회장 및 관람장2013-06-192014-07-28문화예술과공개2015.11년
36조각평화의소리전주시국경오호반베르디움 아파트전주시 완산구 유연로 217공공86549.4898공동주택2014-03-202014-07-21문화예술과공개2015.11년
47조각공간저너머전주시국경오전주효자복합시설전주시 완산구 용머리로 45공공25908.59근린생활시설2014-05-282014-07-21문화예술과공개2015.11년
59조각늘봄군산시김오성지곡동 쌍용예가아파트군산시 계산로 71공공129875.6236공동주택2013-04-052014-07-11문화예술과공개2015.11년
610조각한옥의꿈익산시이한우오투그란테아파트익산시 선화로73길 38민간111916.1603공동주택2013-03-062014-07-04문화예술과공개2015.11년
714회화컬러환타지완주군하태임한국전기안전공사완주군 이서면 오공로 12공공-업무시설2013-06-192014-04-10문화예술과공개2015.11년
815조각이야기완주군김동헌이노팰리스아파트전주시 덕진구 틀못4길 33공공-공동주택2012-05-312014-04-10문화예술과공개2015.11년
916조각빛과 어둠완주군배동호한국전기안전공사완주군 이서면 오공로 12공공-업무시설2013-06-192014-04-10문화예술과공개2015.11년
순번분류작품명시군명작가명건축물명도로명주소건축주구분연면적건축물용도작품심의일작품설치일자료출처공개여부작성일갱신주기
277294회화자연1익산시선기현금강동 쉐르빌아파트익산시 약촌로 31---근린생활시설20012001문화예술과공개2015.11년
278295조각가족김제시김동헌-김제시 성산길 138--근린생활시설-2000-11-25문화예술과공개2015.11년
279296조각이야기김제시김동헌-김제시 도작로 33--근린생활시설-2000-07-06문화예술과공개2015.11년
280297조각家族(가족)익산시이한우영등동 제일아파트익산시 무왕로9길 60--근린생활시설-2000문화예술과공개2015.11년
281298조각평화전주시국경오알리앙스 웨딩홀전주시 완산구 용머리로 3-17711.51근린생활시설--문화예술과공개2015.11년
282299조각21c 탄생축제전주시김영숙롯데백화점 전주점전주시 완산구 온고을로 2-75519.35근린생활시설--문화예술과공개2015.11년
283300조각젊음의 광장전주시황순례롯데백화점 전주점전주시 완산구 온고을로 2-75519.35근린생활시설--문화예술과공개2015.11년
284301회화조바심전주시김두해롯데백화점 전주점전주시 완산구 온고을로 2--근린생활시설--문화예술과공개2015.11년
285302회화신포항전주시신세자알리앙스 웨딩홀전주시 완산구 용머리로 3--근린생활시설--문화예술과공개2015.11년
286303회화서해전주시김두해알리앙스 웨딩홀전주시 완산구 용머리로 3--근린생활시설--문화예술과공개2015.11년