Overview

Dataset statistics

Number of variables12
Number of observations303
Missing cells258
Missing cells (%)7.1%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory28.8 KiB
Average record size in memory97.4 B

Variable types

Categorical4
Text5
Numeric1
DateTime2

Dataset

Description전북특별자치도 건축물.미술작품 현황(지역, 작품명, 작가명, 건축물명, 건축물주소, 건축주명, 건축주성격, 크기, 설치 일자 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055837/fileData.do

Alerts

Dataset has 1 (0.3%) duplicate rowsDuplicates
분류 is highly imbalanced (71.5%)Imbalance
건축물용도 is highly imbalanced (51.2%)Imbalance
건축주명 has 44 (14.5%) missing valuesMissing
연면적 has 104 (34.3%) missing valuesMissing
작품심의일자 has 104 (34.3%) missing valuesMissing
작품설치일자 has 6 (2.0%) missing valuesMissing

Reproduction

Analysis started2024-03-14 16:38:24.897593
Analysis finished2024-03-14 16:38:27.262123
Duration2.36 seconds
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

2024-03-15T01:38:27.379870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:38:27.725510image/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

2024-03-15T01:38:28.127086image/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
2024-03-15T01:38:29.855354image/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%
2024-03-15T01:38:31.989099image/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
2024-03-15T01:38:33.405530image/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%
2024-03-15T01:38:35.318581image/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
2024-03-15T01:38:36.312985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length9.009901
Min length3

Characters and Unicode

Total characters2730
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 42
 
8.0%
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
77.1%
2024-03-15T01:38:38.034175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
 
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
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2355
86.3%
Space Separator 221
 
8.1%
Uppercase Letter 57
 
2.1%
Decimal Number 45
 
1.6%
Lowercase Letter 21
 
0.8%
Dash Punctuation 15
 
0.5%
Other Punctuation 7
 
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 (244) 1514
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
57.1%
, 3
42.9%
Space Separator
ValueCountFrequency (%)
221
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 2356
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 (245) 1515
64.3%
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%
Common
ValueCountFrequency (%)
221
74.7%
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 (5) 7
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2355
86.3%
ASCII 373
 
13.7%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
59.2%
2 18
 
4.8%
- 15
 
4.0%
K 12
 
3.2%
1 11
 
2.9%
S 9
 
2.4%
P 9
 
2.4%
e 8
 
2.1%
B 8
 
2.1%
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 (244) 1514
64.3%
None
ValueCountFrequency (%)
㈜ 1
50.0%
ｉ 1
50.0%

건축물주소
Text

Distinct225
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T01:38:39.348067image/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%
2024-03-15T01:38:41.102093image/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%

건축주명
Text

MISSING 

Distinct156
Distinct (%)60.2%
Missing44
Missing (%)14.5%
Memory size2.5 KiB
2024-03-15T01:38:42.002830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length8.1814672
Min length1

Characters and Unicode

Total characters2119
Distinct characters236
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)39.4%

Sample

1st row농촌진흥청
2nd row(주)한국토지신탁
3rd row문화재청
4th row신동아파트주택재건축정비사업조합
5th row신동아파트주택재건축정비사업조합
ValueCountFrequency (%)
대한주택공사 18
 
4.7%
전북대학교 13
 
3.4%
총장 13
 
3.4%
대표이사 8
 
2.1%
사장 8
 
2.1%
롯데쇼핑㈜ 8
 
2.1%
한국방송공사 7
 
1.8%
김인규 7
 
1.8%
주)제일건설 7
 
1.8%
전북개발공사 6
 
1.6%
Other values (187) 290
75.3%
2024-03-15T01:38:43.371380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
5.9%
주 110
 
5.2%
) 74
 
3.5%
사 72
 
3.4%
건 66
 
3.1%
( 62
 
2.9%
대 59
 
2.8%
한 56
 
2.6%
설 54
 
2.5%
택 54
 
2.5%
Other values (226) 1386
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1782
84.1%
Space Separator 126
 
5.9%
Close Punctuation 74
 
3.5%
Open Punctuation 62
 
2.9%
Other Symbol 49
 
2.3%
Uppercase Letter 13
 
0.6%
Decimal Number 8
 
0.4%
Other Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 110
 
6.2%
사 72
 
4.0%
건 66
 
3.7%
대 59
 
3.3%
한 56
 
3.1%
설 54
 
3.0%
택 54
 
3.0%
공 52
 
2.9%
이 35
 
2.0%
전 34
 
1.9%
Other values (211) 1190
66.8%
Uppercase Letter
ValueCountFrequency (%)
S 4
30.8%
T 3
23.1%
K 2
15.4%
G 2
15.4%
E 1
 
7.7%
B 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 5
62.5%
0 2
 
25.0%
2 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
& 1
 
20.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1831
86.4%
Common 275
 
13.0%
Latin 13
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 110
 
6.0%
사 72
 
3.9%
건 66
 
3.6%
대 59
 
3.2%
한 56
 
3.1%
설 54
 
2.9%
택 54
 
2.9%
공 52
 
2.8%
㈜ 49
 
2.7%
이 35
 
1.9%
Other values (212) 1224
66.8%
Common
ValueCountFrequency (%)
126
45.8%
) 74
26.9%
( 62
22.5%
1 5
 
1.8%
, 4
 
1.5%
0 2
 
0.7%
2 1
 
0.4%
& 1
 
0.4%
Latin
ValueCountFrequency (%)
S 4
30.8%
T 3
23.1%
K 2
15.4%
G 2
15.4%
E 1
 
7.7%
B 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1782
84.1%
ASCII 288
 
13.6%
None 49
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
43.8%
) 74
25.7%
( 62
21.5%
1 5
 
1.7%
S 4
 
1.4%
, 4
 
1.4%
T 3
 
1.0%
K 2
 
0.7%
G 2
 
0.7%
0 2
 
0.7%
Other values (4) 4
 
1.4%
Hangul
ValueCountFrequency (%)
주 110
 
6.2%
사 72
 
4.0%
건 66
 
3.7%
대 59
 
3.3%
한 56
 
3.1%
설 54
 
3.0%
택 54
 
3.0%
공 52
 
2.9%
이 35
 
2.0%
전 34
 
1.9%
Other values (211) 1190
66.8%
None
ValueCountFrequency (%)
㈜ 49
100.0%

건축주성격
Categorical

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

Length

Max length11
Median length4
Mean length3.3960396
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

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

Length

2024-03-15T01:38:43.592291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:38:43.847503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 207
68.3%
공공 75
 
24.8%
민간 20
 
6.6%
기타(공공+민간합작 1
 
0.3%

연면적
Real number (ℝ)

MISSING 

Distinct149
Distinct (%)74.9%
Missing104
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean61287.761
Minimum1841.88
Maximum567229.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T01:38:44.205539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1841.88
5-th percentile10674.595
Q123081.005
median47196.67
Q375991
95-th percentile172867.79
Maximum567229.74
Range565387.86
Interquartile range (IQR)52909.995

Descriptive statistics

Standard deviation59129.396
Coefficient of variation (CV)0.96478311
Kurtosis26.489638
Mean61287.761
Median Absolute Deviation (MAD)25655.69
Skewness3.7616518
Sum12196264
Variance3.4962855 × 109
MonotonicityNot monotonic
2024-03-15T01:38:44.736646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30788.0 13
 
4.3%
14168.0 7
 
2.3%
134812.825 3
 
1.0%
11523.2997 3
 
1.0%
75519.35 3
 
1.0%
12695.3 3
 
1.0%
182718.73 3
 
1.0%
209648.88 3
 
1.0%
104431.27 3
 
1.0%
143878.8088 2
 
0.7%
Other values (139) 156
51.5%
(Missing) 104
34.3%
ValueCountFrequency (%)
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%
10365.5415 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

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

2024-03-15T01:38:45.054261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:38:45.333765image/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
Date

MISSING 

Distinct92
Distinct (%)46.2%
Missing104
Missing (%)34.3%
Memory size2.5 KiB
Minimum2001-01-01 00:00:00
Maximum2014-05-28 00:00:00
2024-03-15T01:38:45.581760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:38:45.860610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

작품설치일자
Date

MISSING 

Distinct198
Distinct (%)66.7%
Missing6
Missing (%)2.0%
Memory size2.5 KiB
Minimum2000-01-01 00:00:00
Maximum2014-08-13 00:00:00
2024-03-15T01:38:46.094572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:38:46.454665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-15T01:38:26.216930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:38:46.630488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류지역건축주성격연면적건축물용도작품심의일자
분류1.0000.2130.0000.0000.3650.000
지역0.2131.0000.0000.0000.4240.979
건축주성격0.0000.0001.0000.0000.6770.606
연면적0.0000.0000.0001.0000.2650.589
건축물용도0.3650.4240.6770.2651.0000.941
작품심의일자0.0000.9790.6060.5890.9411.000
2024-03-15T01:38:46.857912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물용도지역분류건축주성격
건축물용도1.0000.1950.1880.374
지역0.1951.0000.0960.000
분류0.1880.0961.0000.000
건축주성격0.3740.0000.0001.000
2024-03-15T01:38:47.020083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적분류지역건축주성격건축물용도
연면적1.0000.0000.0000.0000.164
분류0.0001.0000.0960.0000.188
지역0.0000.0961.0000.0000.195
건축주성격0.0000.0000.0001.0000.374
건축물용도0.1640.1880.1950.3741.000

Missing values

2024-03-15T01:38:26.590685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:38:26.918897image/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.
2024-03-15T01:38:27.138536image/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

분류지역작품명작가명건축물명건축물주소건축주명건축주성격연면적건축물용도작품심의일자작품설치일자
0조각전북/전주시비상권치규농촌진흥청전북 전주시 완산구 중동 혁신도시개발지구 농생16블럭 1노트농촌진흥청기타(공공+민간합작)47196.67업무시설2013-04-052014-08-13
1조각전북/정읍시향기터원유진대광 로제비앙전북 정읍시 상동 89-4번지(주)한국토지신탁민간49864.1809공동주택2013-06-192014-08-13
2조각전북/전주시무형유산의시원이용백국립무형유산원전북 전주시 완산구 동서학동 896-1문화재청공공<NA>공연장, 집회장 및 관람장2013-06-192014-07-28
3공예전북/익산시천년의사랑엄혁용익산금호어울림전북 익산시 신동 816-1번지외 5필지신동아파트주택재건축정비사업조합공공112135.11공동주택2013-11-262014-07-28
4조각전북/익산시생성공간-흔적신치현익산금호어울림전북 익산시 신동 816-1번지외 5필지신동아파트주택재건축정비사업조합공공112135.11공동주택2013-11-262014-07-28
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6조각전북/전주시공간저너머국경오전주효자복합시설전북 전주시 완산구 효자동1가 434번지 외에스티에스개발주식회사공공25908.59근린생활시설2014-05-282014-07-21
7조각전북/김제시내면속의풍경이상현김제 아이지파크전북 김제시 신풍동 300번지외 2필지김제아이지파크공공22308.156공동주택2014-03-202014-07-11
8조각전북/군산시늘봄김오성지곡동 쌍용예가전북 군산시 지곡동 31-7번지외하나자산신탁공공129875.6236공동주택2013-04-052014-07-11
9조각전북/익산시한옥의꿈이한우오투그란테아파트전북 익산시 모현동1가 배산택지지구 4블럭제일건설민간111916.1603공동주택2013-03-062014-07-04
분류지역작품명작가명건축물명건축물주소건축주명건축주성격연면적건축물용도작품심의일자작품설치일자
293회화전북/익산시자연1선기현금강동 쉐르빌전북 익산 금강동<NA><NA><NA>근린생활시설2001-01-012001-01-01
294조각전북/김제시가족김동헌건축물기록없음전북 김제시 요촌동 423-2 김제쇼핑 센터<NA><NA><NA>근린생활시설<NA>2000-11-25
295조각전북/김제시이야기김동헌건축물기록없음전북 김제시 신풍동 63 부영3차아파트<NA><NA><NA>근린생활시설<NA>2000-07-06
296조각전북/익산시家族(가족)이한우영등동 제일아파트전북 익산 영등동<NA><NA><NA>근린생활시설<NA>2000-01-01
297조각전북/전주시평화국경오알리앙스 웨딩홀전북 전주시 완산구 효자동1가 410-1박재근<NA>17711.51근린생활시설<NA><NA>
298조각전북/전주시21c 탄생축제김영숙롯데백화점 전주점전북 전주시 완산구 서신동 971번지이인원<NA>75519.35근린생활시설<NA><NA>
299조각전북/전주시젊음의 광장황순례롯데백화점 전주점전북 전주시 완산구 서신동 971번지이인원<NA>75519.35근린생활시설<NA><NA>
300회화전북/전주시조바심김두해롯데백화점 전주점전북 전주 완산구 서신동 971번지<NA><NA><NA>근린생활시설<NA><NA>
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Duplicate rows

Most frequently occurring

분류지역작품명작가명건축물명건축물주소건축주명건축주성격연면적건축물용도작품심의일자작품설치일자# duplicates
0조각전북/전주시The flower(꽃의 향연)류경미휴먼시아 국민임대아파트전북 전주 완산구 효자동 택지개발지구 A-3블럭대한주택공사<NA><NA>근린생활시설2007-08-072007-11-062