Overview

Dataset statistics

Number of variables11
Number of observations303
Missing cells150
Missing cells (%)4.5%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory27.1 KiB
Average record size in memory91.4 B

Variable types

Categorical4
Text4
Numeric3

Alerts

Dataset has 1 (0.3%) duplicate rowsDuplicates
작품심의일자 is highly overall correlated with 작품설치일자High correlation
작품설치일자 is highly overall correlated with 작품심의일자High correlation
건축주성격 is highly overall correlated with 건축물용도High correlation
건축물용도 is highly overall correlated with 건축주성격High correlation
분류 is highly imbalanced (71.5%)Imbalance
건축물용도 is highly imbalanced (51.2%)Imbalance
연면적(㎡) has 46 (15.2%) missing valuesMissing
작품심의일자 has 104 (34.3%) missing valuesMissing
연면적(㎡) has 58 (19.1%) zerosZeros
작품설치일자 has 6 (2.0%) zerosZeros

Reproduction

Analysis started2024-03-14 00:12:08.998967
Analysis finished2024-03-14 00:12:10.631800
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류
Categorical

IMBALANCE 

Distinct8
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
조각
256 
회화
34 
공예
 
4
상징탑
 
3
기타
 
3
Other values (3)
 
3

Length

Max length3
Median length2
Mean length2.009901
Min length2

Unique

Unique3 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
조각 256
84.5%
회화 34
 
11.2%
공예 4
 
1.3%
상징탑 3
 
1.0%
기타 3
 
1.0%
사진 1
 
0.3%
서예 1
 
0.3%
벽화 1
 
0.3%

Length

2024-03-14T09:12:10.686423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:12:10.776021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조각 256
84.5%
회화 34
 
11.2%
공예 4
 
1.3%
상징탑 3
 
1.0%
기타 3
 
1.0%
사진 1
 
0.3%
서예 1
 
0.3%
벽화 1
 
0.3%

지역
Categorical

Distinct13
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
전북/전주시
159 
전북/익산시
49 
전북/군산시
45 
전북/완주군
18 
전북/정읍시
 
8
Other values (8)
24 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique3 ?
Unique (%)1.0%

Sample

1st row전북/전주시
2nd row전북/정읍시
3rd row전북/전주시
4th row전북/익산시
5th row전북/익산시

Common Values

ValueCountFrequency (%)
전북/전주시 159
52.5%
전북/익산시 49
 
16.2%
전북/군산시 45
 
14.9%
전북/완주군 18
 
5.9%
전북/정읍시 8
 
2.6%
전북/김제시 8
 
2.6%
전북/고창군 7
 
2.3%
전북/순창군 2
 
0.7%
전북/무주군 2
 
0.7%
전북/남원시 2
 
0.7%
Other values (3) 3
 
1.0%

Length

2024-03-14T09:12:10.871205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전북/전주시 159
52.5%
전북/익산시 49
 
16.2%
전북/군산시 45
 
14.9%
전북/완주군 18
 
5.9%
전북/정읍시 8
 
2.6%
전북/김제시 8
 
2.6%
전북/고창군 7
 
2.3%
전북/순창군 2
 
0.7%
전북/무주군 2
 
0.7%
전북/남원시 2
 
0.7%
Other values (3) 3
 
1.0%

작품명
Text

Distinct269
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:12:11.145510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length5.5907591
Min length1

Characters and Unicode

Total characters1694
Distinct characters340
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

Unique253 ?
Unique (%)83.5%

Sample

1st row비상
2nd row향기터
3rd row무형유산의시원
4th row천년의사랑
5th row생성공간-흔적
ValueCountFrequency (%)
이야기 10
 
2.2%
비상 8
 
1.8%
꿈 7
 
1.5%
가족 7
 
1.5%
7
 
1.5%
풍요 6
 
1.3%
풍경 5
 
1.1%
자연 5
 
1.1%
천년의 4
 
0.9%
평화 4
 
0.9%
Other values (347) 391
86.1%
2024-03-14T09:12:11.581226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
151
 
8.9%
의 60
 
3.5%
- 46
 
2.7%
기 33
 
1.9%
가 27
 
1.6%
이 26
 
1.5%
) 23
 
1.4%
( 23
 
1.4%
생 22
 
1.3%
풍 21
 
1.2%
Other values (330) 1262
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1202
71.0%
Space Separator 151
 
8.9%
Lowercase Letter 134
 
7.9%
Decimal Number 51
 
3.0%
Dash Punctuation 46
 
2.7%
Uppercase Letter 30
 
1.8%
Close Punctuation 23
 
1.4%
Open Punctuation 23
 
1.4%
Other Punctuation 18
 
1.1%
Letter Number 12
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 60
 
5.0%
기 33
 
2.7%
가 27
 
2.2%
이 26
 
2.2%
생 22
 
1.8%
풍 21
 
1.7%
는 20
 
1.7%
화 20
 
1.7%
상 19
 
1.6%
연 17
 
1.4%
Other values (279) 937
78.0%
Lowercase Letter
ValueCountFrequency (%)
e 20
14.9%
r 15
11.2%
a 13
 
9.7%
n 11
 
8.2%
o 10
 
7.5%
m 6
 
4.5%
y 6
 
4.5%
t 6
 
4.5%
i 6
 
4.5%
p 5
 
3.7%
Other values (10) 36
26.9%
Uppercase Letter
ValueCountFrequency (%)
H 5
16.7%
S 4
13.3%
N 3
10.0%
T 3
10.0%
E 3
10.0%
I 2
 
6.7%
F 2
 
6.7%
R 2
 
6.7%
G 1
 
3.3%
W 1
 
3.3%
Other values (4) 4
13.3%
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
61.1%
. 4
 
22.2%
" 2
 
11.1%
& 1
 
5.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 7
58.3%
Ⅰ 5
41.7%
Space Separator
ValueCountFrequency (%)
151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
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 1178
69.5%
Common 316
 
18.7%
Latin 176
 
10.4%
Han 24
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 60
 
5.1%
기 33
 
2.8%
가 27
 
2.3%
이 26
 
2.2%
생 22
 
1.9%
풍 21
 
1.8%
는 20
 
1.7%
화 20
 
1.7%
상 19
 
1.6%
연 17
 
1.4%
Other values (256) 913
77.5%
Latin
ValueCountFrequency (%)
e 20
 
11.4%
r 15
 
8.5%
a 13
 
7.4%
n 11
 
6.2%
o 10
 
5.7%
Ⅱ 7
 
4.0%
m 6
 
3.4%
y 6
 
3.4%
t 6
 
3.4%
i 6
 
3.4%
Other values (26) 76
43.2%
Han
ValueCountFrequency (%)
合 2
 
8.3%
生 1
 
4.2%
天 1
 
4.2%
氣 1
 
4.2%
母 1
 
4.2%
思 1
 
4.2%
地 1
 
4.2%
家 1
 
4.2%
人 1
 
4.2%
飛 1
 
4.2%
Other values (13) 13
54.2%
Common
ValueCountFrequency (%)
151
47.8%
- 46
 
14.6%
) 23
 
7.3%
( 23
 
7.3%
0 17
 
5.4%
2 15
 
4.7%
1 13
 
4.1%
, 11
 
3.5%
. 4
 
1.3%
+ 4
 
1.3%
Other values (5) 9
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1178
69.5%
ASCII 480
28.3%
CJK 24
 
1.4%
Number Forms 12
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
31.5%
- 46
 
9.6%
) 23
 
4.8%
( 23
 
4.8%
e 20
 
4.2%
0 17
 
3.5%
2 15
 
3.1%
r 15
 
3.1%
1 13
 
2.7%
a 13
 
2.7%
Other values (39) 144
30.0%
Hangul
ValueCountFrequency (%)
의 60
 
5.1%
기 33
 
2.8%
가 27
 
2.3%
이 26
 
2.2%
생 22
 
1.9%
풍 21
 
1.8%
는 20
 
1.7%
화 20
 
1.7%
상 19
 
1.6%
연 17
 
1.4%
Other values (256) 913
77.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 7
58.3%
Ⅰ 5
41.7%
CJK
ValueCountFrequency (%)
合 2
 
8.3%
生 1
 
4.2%
天 1
 
4.2%
氣 1
 
4.2%
母 1
 
4.2%
思 1
 
4.2%
地 1
 
4.2%
家 1
 
4.2%
人 1
 
4.2%
飛 1
 
4.2%
Other values (13) 13
54.2%

작가명
Text

Distinct146
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:12:11.853704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.019802
Min length2

Characters and Unicode

Total characters915
Distinct characters124
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)34.7%

Sample

1st row권치규
2nd row원유진
3rd row이용백
4th row엄혁용
5th row신치현
ValueCountFrequency (%)
김동헌 28
 
9.2%
국경오 18
 
5.9%
엄혁용 16
 
5.2%
이한우 12
 
3.9%
강용면 12
 
3.9%
선기현 10
 
3.3%
김귀복 6
 
2.0%
이효문 6
 
2.0%
유휴열 6
 
2.0%
김상호 5
 
1.6%
Other values (136) 186
61.0%
2024-03-14T09:12:12.541416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 68
 
7.4%
이 47
 
5.1%
용 35
 
3.8%
동 34
 
3.7%
경 30
 
3.3%
현 29
 
3.2%
헌 28
 
3.1%
오 24
 
2.6%
정 24
 
2.6%
강 23
 
2.5%
Other values (114) 573
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 912
99.7%
Space Separator 2
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 68
 
7.5%
이 47
 
5.2%
용 35
 
3.8%
동 34
 
3.7%
경 30
 
3.3%
현 29
 
3.2%
헌 28
 
3.1%
오 24
 
2.6%
정 24
 
2.6%
강 23
 
2.5%
Other values (112) 570
62.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 912
99.7%
Common 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 68
 
7.5%
이 47
 
5.2%
용 35
 
3.8%
동 34
 
3.7%
경 30
 
3.3%
현 29
 
3.2%
헌 28
 
3.1%
오 24
 
2.6%
정 24
 
2.6%
강 23
 
2.5%
Other values (112) 570
62.5%
Common
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 912
99.7%
ASCII 3
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 68
 
7.5%
이 47
 
5.2%
용 35
 
3.8%
동 34
 
3.7%
경 30
 
3.3%
현 29
 
3.2%
헌 28
 
3.1%
오 24
 
2.6%
정 24
 
2.6%
강 23
 
2.5%
Other values (112) 570
62.5%
ASCII
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

건축물명
Text

Distinct214
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:12:12.782798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length9.0066007
Min length3

Characters and Unicode

Total characters2729
Distinct characters286
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)54.1%

Sample

1st row농촌진흥청
2nd row대광 로제비앙
3rd row국립무형유산원
4th row익산금호어울림
5th row익산금호어울림
ValueCountFrequency (%)
아파트 41
 
7.8%
전북대학교 13
 
2.5%
어린이병원 13
 
2.5%
익산 9
 
1.7%
전주점 8
 
1.5%
롯데마트 8
 
1.5%
휴먼시아 7
 
1.3%
kbs전주방송총국 7
 
1.3%
현대 7
 
1.3%
주공아파트 6
 
1.1%
Other values (270) 404
77.2%
2024-03-14T09:12:13.132967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
220
 
8.1%
아 177
 
6.5%
트 174
 
6.4%
파 165
 
6.0%
주 65
 
2.4%
전 57
 
2.1%
대 48
 
1.8%
지 47
 
1.7%
동 40
 
1.5%
이 34
 
1.2%
Other values (276) 1702
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2354
86.3%
Space Separator 220
 
8.1%
Uppercase Letter 57
 
2.1%
Decimal Number 45
 
1.6%
Lowercase Letter 21
 
0.8%
Dash Punctuation 15
 
0.5%
Other Punctuation 8
 
0.3%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 177
 
7.5%
트 174
 
7.4%
파 165
 
7.0%
주 65
 
2.8%
전 57
 
2.4%
대 48
 
2.0%
지 47
 
2.0%
동 40
 
1.7%
이 34
 
1.4%
스 34
 
1.4%
Other values (243) 1513
64.3%
Uppercase Letter
ValueCountFrequency (%)
K 12
21.1%
S 9
15.8%
P 9
15.8%
B 8
14.0%
A 5
8.8%
I 4
 
7.0%
R 3
 
5.3%
W 2
 
3.5%
J 2
 
3.5%
T 2
 
3.5%
Decimal Number
ValueCountFrequency (%)
2 18
40.0%
1 11
24.4%
3 5
 
11.1%
5 4
 
8.9%
8 2
 
4.4%
4 2
 
4.4%
9 1
 
2.2%
7 1
 
2.2%
6 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
e 8
38.1%
r 4
19.0%
a 4
19.0%
k 4
19.0%
ｉ 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
' 4
50.0%
, 3
37.5%
？ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2355
86.3%
Common 296
 
10.8%
Latin 78
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 177
 
7.5%
트 174
 
7.4%
파 165
 
7.0%
주 65
 
2.8%
전 57
 
2.4%
대 48
 
2.0%
지 47
 
2.0%
동 40
 
1.7%
이 34
 
1.4%
스 34
 
1.4%
Other values (244) 1514
64.3%
Common
ValueCountFrequency (%)
220
74.3%
2 18
 
6.1%
- 15
 
5.1%
1 11
 
3.7%
3 5
 
1.7%
( 4
 
1.4%
) 4
 
1.4%
5 4
 
1.4%
' 4
 
1.4%
, 3
 
1.0%
Other values (6) 8
 
2.7%
Latin
ValueCountFrequency (%)
K 12
15.4%
S 9
11.5%
P 9
11.5%
e 8
10.3%
B 8
10.3%
A 5
6.4%
r 4
 
5.1%
I 4
 
5.1%
a 4
 
5.1%
k 4
 
5.1%
Other values (6) 11
14.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2354
86.3%
ASCII 372
 
13.6%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
220
59.1%
2 18
 
4.8%
- 15
 
4.0%
K 12
 
3.2%
1 11
 
3.0%
S 9
 
2.4%
P 9
 
2.4%
e 8
 
2.2%
B 8
 
2.2%
A 5
 
1.3%
Other values (20) 57
 
15.3%
Hangul
ValueCountFrequency (%)
아 177
 
7.5%
트 174
 
7.4%
파 165
 
7.0%
주 65
 
2.8%
전 57
 
2.4%
대 48
 
2.0%
지 47
 
2.0%
동 40
 
1.7%
이 34
 
1.4%
스 34
 
1.4%
Other values (243) 1513
64.3%
None
ValueCountFrequency (%)
？ 1
33.3%
㈜ 1
33.3%
ｉ 1
33.3%

건축물주소
Text

Distinct225
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:12:13.385463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length21.567657
Min length9

Characters and Unicode

Total characters6535
Distinct characters177
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)57.8%

Sample

1st row전북 전주시 완산구 중동 혁신도시개발지구 농생16블럭 1노트
2nd row전북 정읍시 상동 89-4번지
3rd row전북 전주시 완산구 동서학동 896-1
4th row전북 익산시 신동 816-1번지외 5필지
5th row전북 익산시 신동 816-1번지외 5필지
ValueCountFrequency (%)
전북 203
 
13.4%
전주시 120
 
7.9%
전라북도 100
 
6.6%
완산구 90
 
5.9%
덕진구 69
 
4.5%
익산시 43
 
2.8%
전주 40
 
2.6%
군산시 24
 
1.6%
군산 22
 
1.4%
완주군 18
 
1.2%
Other values (376) 789
52.0%
2024-03-14T09:12:13.800606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1215
18.6%
전 470
 
7.2%
북 307
 
4.7%
1 293
 
4.5%
동 282
 
4.3%
산 222
 
3.4%
시 216
 
3.3%
주 186
 
2.8%
지 179
 
2.7%
구 175
 
2.7%
Other values (167) 2990
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3912
59.9%
Space Separator 1215
 
18.6%
Decimal Number 1207
 
18.5%
Dash Punctuation 174
 
2.7%
Uppercase Letter 12
 
0.2%
Other Punctuation 9
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 470
 
12.0%
북 307
 
7.8%
동 282
 
7.2%
산 222
 
5.7%
시 216
 
5.5%
주 186
 
4.8%
지 179
 
4.6%
구 175
 
4.5%
가 123
 
3.1%
완 109
 
2.8%
Other values (145) 1643
42.0%
Decimal Number
ValueCountFrequency (%)
1 293
24.3%
2 157
13.0%
3 130
10.8%
5 114
 
9.4%
4 109
 
9.0%
6 106
 
8.8%
8 89
 
7.4%
9 85
 
7.0%
7 68
 
5.6%
0 56
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A 5
41.7%
B 4
33.3%
L 3
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 5
55.6%
, 3
33.3%
@ 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
1215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3912
59.9%
Common 2609
39.9%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 470
 
12.0%
북 307
 
7.8%
동 282
 
7.2%
산 222
 
5.7%
시 216
 
5.5%
주 186
 
4.8%
지 179
 
4.6%
구 175
 
4.5%
가 123
 
3.1%
완 109
 
2.8%
Other values (145) 1643
42.0%
Common
ValueCountFrequency (%)
1215
46.6%
1 293
 
11.2%
- 174
 
6.7%
2 157
 
6.0%
3 130
 
5.0%
5 114
 
4.4%
4 109
 
4.2%
6 106
 
4.1%
8 89
 
3.4%
9 85
 
3.3%
Other values (7) 137
 
5.3%
Latin
ValueCountFrequency (%)
A 5
35.7%
B 4
28.6%
L 3
21.4%
b 1
 
7.1%
c 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3912
59.9%
ASCII 2623
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1215
46.3%
1 293
 
11.2%
- 174
 
6.6%
2 157
 
6.0%
3 130
 
5.0%
5 114
 
4.3%
4 109
 
4.2%
6 106
 
4.0%
8 89
 
3.4%
9 85
 
3.2%
Other values (12) 151
 
5.8%
Hangul
ValueCountFrequency (%)
전 470
 
12.0%
북 307
 
7.8%
동 282
 
7.2%
산 222
 
5.7%
시 216
 
5.5%
주 186
 
4.8%
지 179
 
4.6%
구 175
 
4.5%
가 123
 
3.1%
완 109
 
2.8%
Other values (145) 1643
42.0%

건축주성격
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
-
207 
공공
75 
민간
 
20
기타(공공+민간합작)
 
1

Length

Max length11
Median length1
Mean length1.3465347
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
- 207
68.3%
공공 75
 
24.8%
민간 20
 
6.6%
기타(공공+민간합작) 1
 
0.3%

Length

2024-03-14T09:12:13.905476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:12:14.005088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
207
68.3%
공공 75
 
24.8%
민간 20
 
6.6%
기타(공공+민간합작 1
 
0.3%

연면적(㎡)
Real number (ℝ)

MISSING  ZEROS 

Distinct150
Distinct (%)58.4%
Missing46
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean47456.282
Minimum0
Maximum567229.74
Zeros58
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:12:14.107474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14114.5836
median30788
Q368539.49
95-th percentile149108.42
Maximum567229.74
Range567229.74
Interquartile range (IQR)64424.906

Descriptive statistics

Standard deviation57992.352
Coefficient of variation (CV)1.2220164
Kurtosis24.853667
Mean47456.282
Median Absolute Deviation (MAD)30788
Skewness3.5421977
Sum12196264
Variance3.3631129 × 109
MonotonicityNot monotonic
2024-03-14T09:12:14.229953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 58
 
19.1%
30788.0 13
 
4.3%
14168.0 7
 
2.3%
12695.3 3
 
1.0%
75519.35 3
 
1.0%
104431.27 3
 
1.0%
11523.2997 3
 
1.0%
209648.88 3
 
1.0%
134812.825 3
 
1.0%
182718.73 3
 
1.0%
Other values (140) 158
52.1%
(Missing) 46
 
15.2%
ValueCountFrequency (%)
0.0 58
19.1%
1841.88 1
 
0.3%
3241.368 1
 
0.3%
3267.0 1
 
0.3%
3277.7135 1
 
0.3%
3992.74 1
 
0.3%
4072.6452 1
 
0.3%
4114.5836 1
 
0.3%
4954.95 1
 
0.3%
8568.6419 1
 
0.3%
ValueCountFrequency (%)
567229.7352 1
 
0.3%
209648.88 3
1.0%
192280.0 2
0.7%
182718.73 3
1.0%
172867.7907 2
0.7%
150176.39 1
 
0.3%
149108.42 2
0.7%
143878.8088 2
0.7%
134812.825 3
1.0%
132052.745 1
 
0.3%

건축물용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
근린생활시설
198 
공동주택
68 
의료시설
 
15
방송 · 통신시설
 
7
업무시설
 
5
Other values (4)
 
10

Length

Max length14
Median length6
Mean length5.5478548
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
근린생활시설 198
65.3%
공동주택 68
 
22.4%
의료시설 15
 
5.0%
방송 · 통신시설 7
 
2.3%
업무시설 5
 
1.7%
공연장, 집회장 및 관람장 4
 
1.3%
숙박시설 3
 
1.0%
판매시설 2
 
0.7%
기타 1
 
0.3%

Length

2024-03-14T09:12:14.358910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:12:14.459394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근린생활시설 198
60.2%
공동주택 68
 
20.7%
의료시설 15
 
4.6%
방송 7
 
2.1%
· 7
 
2.1%
통신시설 7
 
2.1%
업무시설 5
 
1.5%
공연장 4
 
1.2%
집회장 4
 
1.2%
및 4
 
1.2%
Other values (4) 10
 
3.0%

작품심의일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct92
Distinct (%)46.2%
Missing104
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean20086691
Minimum20010000
Maximum20140528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:12:14.569028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010000
5-th percentile20021092
Q120060628
median20090429
Q320120308
95-th percentile20130619
Maximum20140528
Range130528
Interquartile range (IQR)59680

Descriptive statistics

Standard deviation35444.71
Coefficient of variation (CV)0.0017645868
Kurtosis-0.79119368
Mean20086691
Median Absolute Deviation (MAD)29803
Skewness-0.42405256
Sum3.9972515 × 109
Variance1.2563274 × 109
MonotonicityNot monotonic
2024-03-14T09:12:14.715871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111129 11
 
3.6%
20130619 10
 
3.3%
20010000 8
 
2.6%
20130306 8
 
2.6%
20120824 7
 
2.3%
20120531 6
 
2.0%
20070206 6
 
2.0%
20120105 5
 
1.7%
20071026 5
 
1.7%
20110718 5
 
1.7%
Other values (82) 128
42.2%
(Missing) 104
34.3%
ValueCountFrequency (%)
20010000 8
2.6%
20020101 1
 
0.3%
20021022 1
 
0.3%
20021100 1
 
0.3%
20021204 2
 
0.7%
20021207 2
 
0.7%
20030903 2
 
0.7%
20031014 1
 
0.3%
20031024 1
 
0.3%
20031226 1
 
0.3%
ValueCountFrequency (%)
20140528 1
 
0.3%
20140320 2
 
0.7%
20131126 4
 
1.3%
20131024 2
 
0.7%
20130619 10
3.3%
20130405 3
 
1.0%
20130306 8
2.6%
20130124 1
 
0.3%
20121227 2
 
0.7%
20121127 1
 
0.3%

작품설치일자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct202
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19678070
Minimum0
Maximum20140813
Zeros6
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:12:14.872834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20010243
Q120041000
median20071017
Q320110776
95-th percentile20140410
Maximum20140813
Range20140813
Interquartile range (IQR)69775

Descriptive statistics

Standard deviation2801809.9
Coefficient of variation (CV)0.14238235
Kurtosis46.281887
Mean19678070
Median Absolute Deviation (MAD)30399
Skewness-6.9257945
Sum5.9624553 × 109
Variance7.8501388 × 1012
MonotonicityDecreasing
2024-03-14T09:12:14.985013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121214 13
 
4.3%
0 6
 
2.0%
20010000 6
 
2.0%
20110725 5
 
1.7%
20060600 4
 
1.3%
20140410 4
 
1.3%
20031114 4
 
1.3%
20090406 3
 
1.0%
20031200 3
 
1.0%
20061000 3
 
1.0%
Other values (192) 252
83.2%
ValueCountFrequency (%)
0 6
2.0%
20000000 1
 
0.3%
20000706 1
 
0.3%
20001125 1
 
0.3%
20010000 6
2.0%
20010214 1
 
0.3%
20010500 1
 
0.3%
20010601 1
 
0.3%
20010721 1
 
0.3%
20010801 1
 
0.3%
ValueCountFrequency (%)
20140813 2
0.7%
20140728 3
1.0%
20140721 2
0.7%
20140711 2
0.7%
20140704 1
 
0.3%
20140425 3
1.0%
20140410 4
1.3%
20140117 1
 
0.3%
20131223 2
0.7%
20131220 2
0.7%

Interactions

2024-03-14T09:12:10.090778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:09.601635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:09.807137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:10.158671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:09.661924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:09.910481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:10.230793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:09.729955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:12:10.016049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:12:15.072358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류지역건축주성격연면적(㎡)건축물용도작품심의일자작품설치일자
분류1.0000.2130.2660.0000.3650.3520.118
지역0.2131.0000.2780.0000.4240.4070.000
건축주성격0.2660.2781.0000.0000.7240.6960.000
연면적(㎡)0.0000.0000.0001.0000.2350.3030.000
건축물용도0.3650.4240.7240.2351.0000.6640.000
작품심의일자0.3520.4070.6960.3030.6641.000NaN
작품설치일자0.1180.0000.0000.0000.000NaN1.000
2024-03-14T09:12:15.192376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류건축주성격건축물용도지역
분류1.0000.1210.1880.096
건축주성격0.1211.0000.5570.162
건축물용도0.1880.5571.0000.195
지역0.0960.1620.1951.000
2024-03-14T09:12:15.269892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적(㎡)작품심의일자작품설치일자분류지역건축주성격건축물용도
연면적(㎡)1.0000.091-0.1140.0000.0000.0000.136
작품심의일자0.0911.0000.9620.1780.2180.4940.381
작품설치일자-0.1140.9621.0000.0870.0000.0000.000
분류0.0000.1780.0871.0000.0960.1210.188
지역0.0000.2180.0000.0961.0000.1620.195
건축주성격0.0000.4940.0000.1210.1621.0000.557
건축물용도0.1360.3810.0000.1880.1950.5571.000

Missing values

2024-03-14T09:12:10.342128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:12:10.474326image/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.
2024-03-14T09:12:10.566186image/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

분류지역작품명작가명건축물명건축물주소건축주성격연면적(㎡)건축물용도작품심의일자작품설치일자
0조각전북/전주시비상권치규농촌진흥청전북 전주시 완산구 중동 혁신도시개발지구 농생16블럭 1노트기타(공공+민간합작)47196.67업무시설2013040520140813
1조각전북/정읍시향기터원유진대광 로제비앙전북 정읍시 상동 89-4번지민간49864.1809공동주택2013061920140813
2조각전북/전주시무형유산의시원이용백국립무형유산원전북 전주시 완산구 동서학동 896-1공공0.0공연장, 집회장 및 관람장2013061920140728
3공예전북/익산시천년의사랑엄혁용익산금호어울림전북 익산시 신동 816-1번지외 5필지공공112135.11공동주택2013112620140728
4조각전북/익산시생성공간-흔적신치현익산금호어울림전북 익산시 신동 816-1번지외 5필지공공112135.11공동주택2013112620140728
5조각전북/전주시평화의소리국경오호반베르디움전북 전주시 완산구 중동 전주 완주 혁신도시 c13블럭공공86549.4898공동주택2014032020140721
6조각전북/전주시공간저너머국경오전주효자복합시설전북 전주시 완산구 효자동1가 434번지 외공공25908.59근린생활시설2014052820140721
7조각전북/김제시내면속의풍경이상현김제 아이지파크전북 김제시 신풍동 300번지외 2필지공공22308.156공동주택2014032020140711
8조각전북/군산시늘봄김오성지곡동 쌍용예가전북 군산시 지곡동 31-7번지외공공129875.6236공동주택2013040520140711
9조각전북/익산시한옥의꿈이한우오투그란테아파트전북 익산시 모현동1가 배산택지지구 4블럭민간111916.1603공동주택2013030620140704
분류지역작품명작가명건축물명건축물주소건축주성격연면적(㎡)건축물용도작품심의일자작품설치일자
293회화전북/익산시자연1선기현금강동 쉐르빌전북 익산 금강동-<NA>근린생활시설2001000020010000
294조각전북/김제시가족김동헌건축물기록없음전북 김제시 요촌동 423-2 김제쇼핑 센터-<NA>근린생활시설<NA>20001125
295조각전북/김제시이야기김동헌건축물기록없음전북 김제시 신풍동 63 부영3차아파트-<NA>근린생활시설<NA>20000706
296조각전북/익산시家族(가족)이한우영등동 제일아파트전북 익산 영등동-<NA>근린생활시설<NA>20000000
297조각전북/전주시평화국경오알리앙스 웨딩홀전북 전주시 완산구 효자동1가 410-1-17711.51근린생활시설<NA>0
298조각전북/전주시21c 탄생축제김영숙롯데백화점 전주점전북 전주시 완산구 서신동 971번지-75519.35근린생활시설<NA>0
299조각전북/전주시젊음의 광장황순례롯데백화점 전주점전북 전주시 완산구 서신동 971번지-75519.35근린생활시설<NA>0
300회화전북/전주시조바심김두해롯데백화점 전주점전북 전주 완산구 서신동 971번지-<NA>근린생활시설<NA>0
301회화전북/전주시신포항신세자알리앙스 웨딩홀전북 전주 완산구 효자동1가 410-1-<NA>근린생활시설<NA>0
302회화전북/전주시서해김두해알리앙스 웨딩홀전북 전주 완산구 효자동1가 410-1-<NA>근린생활시설<NA>0

Duplicate rows

Most frequently occurring

분류지역작품명작가명건축물명건축물주소건축주성격연면적(㎡)건축물용도작품심의일자작품설치일자# duplicates
0조각전북/전주시The flower(꽃의 향연)류경미휴먼시아 국민임대아파트전북 전주 완산구 효자동 택지개발지구 A-3블럭-0.0근린생활시설20070807200711062