Overview

Dataset statistics

Number of variables5
Number of observations778
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.3 KiB
Average record size in memory41.2 B

Variable types

Text3
Numeric1
Categorical1

Dataset

Description기계설비법 적용 대상 건축물 목록 데이터로 건물명, 우편번호, 주소, 연면적 및 세대수, 주 용도 등의 항목을 제공합니다.*건축물 대장상 용도별 건축물에 따라 연면적과 세대수로 나누어 지며, 적용 시기도 다르나, 2024년에는 일괄 적용
Author경기도 고양시
URLhttps://www.data.go.kr/data/15112017/fileData.do

Reproduction

Analysis started2024-04-06 08:38:32.681966
Analysis finished2024-04-06 08:38:34.657380
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct776
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-06T17:38:35.082062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length8.6105398
Min length3

Characters and Unicode

Total characters6699
Distinct characters423
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique774 ?
Unique (%)99.5%

Sample

1st row한국철도공사 고양고속철도차량기지
2nd row중부대학교 고양캠퍼스
3rd row고양 원마운트
4th row고양 일산 호수공원 가로수길
5th row고양농수산물종합유통센터
ValueCountFrequency (%)
일산 17
 
1.6%
고양 10
 
1.0%
아파트 9
 
0.9%
호반베르디움 7
 
0.7%
오피스텔 6
 
0.6%
킨텍스 6
 
0.6%
일산점 5
 
0.5%
e편한세상 5
 
0.5%
백석역 5
 
0.5%
하이파크시티 5
 
0.5%
Other values (883) 969
92.8%
2024-04-06T17:38:36.177610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
296
 
4.4%
270
 
4.0%
266
 
4.0%
251
 
3.7%
235
 
3.5%
167
 
2.5%
127
 
1.9%
1 111
 
1.7%
109
 
1.6%
100
 
1.5%
Other values (413) 4767
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5675
84.7%
Decimal Number 399
 
6.0%
Space Separator 270
 
4.0%
Uppercase Letter 208
 
3.1%
Lowercase Letter 45
 
0.7%
Open Punctuation 34
 
0.5%
Close Punctuation 34
 
0.5%
Dash Punctuation 14
 
0.2%
Other Punctuation 10
 
0.1%
Letter Number 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
296
 
5.2%
266
 
4.7%
251
 
4.4%
235
 
4.1%
167
 
2.9%
127
 
2.2%
109
 
1.9%
100
 
1.8%
96
 
1.7%
86
 
1.5%
Other values (356) 3942
69.5%
Uppercase Letter
ValueCountFrequency (%)
C 28
13.5%
M 23
11.1%
D 20
9.6%
B 15
 
7.2%
E 15
 
7.2%
I 15
 
7.2%
A 14
 
6.7%
K 11
 
5.3%
S 11
 
5.3%
T 9
 
4.3%
Other values (13) 47
22.6%
Lowercase Letter
ValueCountFrequency (%)
l 10
22.2%
s 8
17.8%
e 7
15.6%
k 4
 
8.9%
t 3
 
6.7%
b 2
 
4.4%
a 2
 
4.4%
c 2
 
4.4%
i 1
 
2.2%
v 1
 
2.2%
Other values (5) 5
11.1%
Decimal Number
ValueCountFrequency (%)
1 111
27.8%
2 70
17.5%
3 56
14.0%
5 31
 
7.8%
4 27
 
6.8%
6 25
 
6.3%
7 23
 
5.8%
8 21
 
5.3%
9 20
 
5.0%
0 15
 
3.8%
Letter Number
ValueCountFrequency (%)
4
40.0%
3
30.0%
3
30.0%
Other Punctuation
ValueCountFrequency (%)
, 8
80.0%
. 2
 
20.0%
Space Separator
ValueCountFrequency (%)
270
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5675
84.7%
Common 761
 
11.4%
Latin 263
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
296
 
5.2%
266
 
4.7%
251
 
4.4%
235
 
4.1%
167
 
2.9%
127
 
2.2%
109
 
1.9%
100
 
1.8%
96
 
1.7%
86
 
1.5%
Other values (356) 3942
69.5%
Latin
ValueCountFrequency (%)
C 28
 
10.6%
M 23
 
8.7%
D 20
 
7.6%
B 15
 
5.7%
E 15
 
5.7%
I 15
 
5.7%
A 14
 
5.3%
K 11
 
4.2%
S 11
 
4.2%
l 10
 
3.8%
Other values (31) 101
38.4%
Common
ValueCountFrequency (%)
270
35.5%
1 111
14.6%
2 70
 
9.2%
3 56
 
7.4%
( 34
 
4.5%
) 34
 
4.5%
5 31
 
4.1%
4 27
 
3.5%
6 25
 
3.3%
7 23
 
3.0%
Other values (6) 80
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5674
84.7%
ASCII 1014
 
15.1%
Number Forms 10
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
296
 
5.2%
266
 
4.7%
251
 
4.4%
235
 
4.1%
167
 
2.9%
127
 
2.2%
109
 
1.9%
100
 
1.8%
96
 
1.7%
86
 
1.5%
Other values (355) 3941
69.5%
ASCII
ValueCountFrequency (%)
270
26.6%
1 111
 
10.9%
2 70
 
6.9%
3 56
 
5.5%
( 34
 
3.4%
) 34
 
3.4%
5 31
 
3.1%
C 28
 
2.8%
4 27
 
2.7%
6 25
 
2.5%
Other values (44) 328
32.3%
Number Forms
ValueCountFrequency (%)
4
40.0%
3
30.0%
3
30.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

우편번호
Real number (ℝ)

Distinct224
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13522.373
Minimum10209
Maximum412817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.0 KiB
2024-04-06T17:38:36.666549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10209
5-th percentile10240
Q110364
median10409.5
Q310518
95-th percentile10585
Maximum412817
Range402608
Interquartile range (IQR)154

Descriptive statistics

Standard deviation35152.459
Coefficient of variation (CV)2.5995778
Kurtosis125.48657
Mean13522.373
Median Absolute Deviation (MAD)76
Skewness11.276636
Sum10520406
Variance1.2356954 × 109
MonotonicityNot monotonic
2024-04-06T17:38:37.067783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10401 27
 
3.5%
10449 22
 
2.8%
10551 20
 
2.6%
10364 17
 
2.2%
10546 17
 
2.2%
10402 16
 
2.1%
10403 15
 
1.9%
10585 13
 
1.7%
10414 12
 
1.5%
10450 11
 
1.4%
Other values (214) 608
78.1%
ValueCountFrequency (%)
10209 1
 
0.1%
10210 4
0.5%
10211 2
0.3%
10212 1
 
0.1%
10214 1
 
0.1%
10218 4
0.5%
10219 3
0.4%
10221 1
 
0.1%
10222 2
0.3%
10223 3
0.4%
ValueCountFrequency (%)
412817 1
 
0.1%
412170 3
 
0.4%
412120 1
 
0.1%
410570 1
 
0.1%
10654 1
 
0.1%
10599 1
 
0.1%
10598 2
 
0.3%
10597 3
 
0.4%
10595 9
1.2%
10594 2
 
0.3%

주소
Text

Distinct775
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-06T17:38:37.873411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length36.245501
Min length16

Characters and Unicode

Total characters28199
Distinct characters437
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique772 ?
Unique (%)99.2%

Sample

1st row경기도 고양시 덕양구 행주로 108-1(강매동, 한국철도공사 고양고속철도차량기지)
2nd row경기도 고양시 덕양구 동헌로 305(대자동, 중부대학교 고양캠퍼스)
3rd row경기도 고양시 일산서구 한류월드로 300(대화동, 고양 원마운트 관리사무소)
4th row경기도 고양시 일산서구 주엽로 80(대화동, 일산호수공원 가로수길 관리사무소)
5th row경기도 고양시 일산서구 대화로 362 (대화동, 고양농수산물종합유통센터)
ValueCountFrequency (%)
고양시 778
 
14.1%
경기도 667
 
12.1%
관리사무소 517
 
9.4%
덕양구 299
 
5.4%
일산동구 276
 
5.0%
아파트 231
 
4.2%
일산서구 198
 
3.6%
중앙로 80
 
1.4%
고양대로 25
 
0.5%
호수로 24
 
0.4%
Other values (1582) 2426
43.9%
2024-04-06T17:38:39.471845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4760
 
16.9%
1191
 
4.2%
902
 
3.2%
848
 
3.0%
791
 
2.8%
784
 
2.8%
706
 
2.5%
702
 
2.5%
685
 
2.4%
683
 
2.4%
Other values (427) 16147
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19524
69.2%
Space Separator 4760
 
16.9%
Decimal Number 2808
 
10.0%
Other Punctuation 278
 
1.0%
Open Punctuation 274
 
1.0%
Close Punctuation 273
 
1.0%
Uppercase Letter 172
 
0.6%
Dash Punctuation 82
 
0.3%
Lowercase Letter 23
 
0.1%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1191
 
6.1%
902
 
4.6%
848
 
4.3%
791
 
4.1%
784
 
4.0%
706
 
3.6%
702
 
3.6%
685
 
3.5%
683
 
3.5%
651
 
3.3%
Other values (376) 11581
59.3%
Uppercase Letter
ValueCountFrequency (%)
I 24
14.0%
C 21
12.2%
M 18
10.5%
D 17
9.9%
B 13
7.6%
S 12
 
7.0%
K 10
 
5.8%
A 9
 
5.2%
L 9
 
5.2%
T 9
 
5.2%
Other values (11) 30
17.4%
Lowercase Letter
ValueCountFrequency (%)
l 7
30.4%
e 5
21.7%
c 2
 
8.7%
a 2
 
8.7%
p 1
 
4.3%
b 1
 
4.3%
r 1
 
4.3%
u 1
 
4.3%
n 1
 
4.3%
t 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 672
23.9%
2 379
13.5%
3 323
11.5%
6 253
 
9.0%
0 244
 
8.7%
5 233
 
8.3%
4 207
 
7.4%
7 198
 
7.1%
8 157
 
5.6%
9 142
 
5.1%
Letter Number
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 268
96.4%
? 10
 
3.6%
Space Separator
ValueCountFrequency (%)
4760
100.0%
Open Punctuation
ValueCountFrequency (%)
( 274
100.0%
Close Punctuation
ValueCountFrequency (%)
) 273
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19524
69.2%
Common 8475
30.1%
Latin 200
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1191
 
6.1%
902
 
4.6%
848
 
4.3%
791
 
4.1%
784
 
4.0%
706
 
3.6%
702
 
3.6%
685
 
3.5%
683
 
3.5%
651
 
3.3%
Other values (376) 11581
59.3%
Latin
ValueCountFrequency (%)
I 24
12.0%
C 21
 
10.5%
M 18
 
9.0%
D 17
 
8.5%
B 13
 
6.5%
S 12
 
6.0%
K 10
 
5.0%
A 9
 
4.5%
L 9
 
4.5%
T 9
 
4.5%
Other values (25) 58
29.0%
Common
ValueCountFrequency (%)
4760
56.2%
1 672
 
7.9%
2 379
 
4.5%
3 323
 
3.8%
( 274
 
3.2%
) 273
 
3.2%
, 268
 
3.2%
6 253
 
3.0%
0 244
 
2.9%
5 233
 
2.7%
Other values (6) 796
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19523
69.2%
ASCII 8670
30.7%
Number Forms 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4760
54.9%
1 672
 
7.8%
2 379
 
4.4%
3 323
 
3.7%
( 274
 
3.2%
) 273
 
3.1%
, 268
 
3.1%
6 253
 
2.9%
0 244
 
2.8%
5 233
 
2.7%
Other values (38) 991
 
11.4%
Hangul
ValueCountFrequency (%)
1191
 
6.1%
902
 
4.6%
848
 
4.3%
791
 
4.1%
784
 
4.0%
706
 
3.6%
702
 
3.6%
685
 
3.5%
683
 
3.5%
651
 
3.3%
Other values (375) 11580
59.3%
Number Forms
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct712
Distinct (%)91.6%
Missing1
Missing (%)0.1%
Memory size6.2 KiB
2024-04-06T17:38:40.412359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.7644788
Min length3

Characters and Unicode

Total characters4479
Distinct characters14
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

Unique661 ?
Unique (%)85.1%

Sample

1st row153929
2nd row64737
3rd row165386.923
4th row35424.73
5th row59,612
ValueCountFrequency (%)
390 4
 
0.5%
720 4
 
0.5%
608 3
 
0.4%
540 3
 
0.4%
496 3
 
0.4%
782 3
 
0.4%
624 3
 
0.4%
480 3
 
0.4%
604 3
 
0.4%
504 3
 
0.4%
Other values (702) 745
95.9%
2024-04-06T17:38:42.148575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 695
15.5%
2 426
9.5%
4 416
9.3%
3 411
9.2%
6 377
8.4%
0 371
8.3%
5 356
7.9%
9 344
7.7%
8 330
7.4%
. 322
7.2%
Other values (4) 431
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4022
89.8%
Other Punctuation 343
 
7.7%
Other Letter 114
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 695
17.3%
2 426
10.6%
4 416
10.3%
3 411
10.2%
6 377
9.4%
0 371
9.2%
5 356
8.9%
9 344
8.6%
8 330
8.2%
7 296
7.4%
Other Punctuation
ValueCountFrequency (%)
. 322
93.9%
, 21
 
6.1%
Other Letter
ValueCountFrequency (%)
57
50.0%
57
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4365
97.5%
Hangul 114
 
2.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 695
15.9%
2 426
9.8%
4 416
9.5%
3 411
9.4%
6 377
8.6%
0 371
8.5%
5 356
8.2%
9 344
7.9%
8 330
7.6%
. 322
7.4%
Other values (2) 317
7.3%
Hangul
ValueCountFrequency (%)
57
50.0%
57
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4365
97.5%
Hangul 114
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 695
15.9%
2 426
9.8%
4 416
9.5%
3 411
9.4%
6 377
8.6%
0 371
8.5%
5 356
8.2%
9 344
7.9%
8 330
7.6%
. 322
7.4%
Other values (2) 317
7.3%
Hangul
ValueCountFrequency (%)
57
50.0%
57
50.0%

주 용도
Categorical

Distinct34
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
공동주택
322 
업무시설
147 
교육연구시설
78 
제1종근린생활시설
45 
제2종근린생활시설
39 
Other values (29)
147 

Length

Max length11
Median length4
Mean length4.9151671
Min length2

Unique

Unique10 ?
Unique (%)1.3%

Sample

1st row판매및영업시설
2nd row교육연구시설
3rd row운동시설
4th row판매시설
5th row판매시설

Common Values

ValueCountFrequency (%)
공동주택 322
41.4%
업무시설 147
18.9%
교육연구시설 78
 
10.0%
제1종근린생활시설 45
 
5.8%
제2종근린생활시설 39
 
5.0%
판매시설 32
 
4.1%
공장 17
 
2.2%
자동차관련시설 15
 
1.9%
의료시설 11
 
1.4%
문화및집회시설 9
 
1.2%
Other values (24) 63
 
8.1%

Length

2024-04-06T17:38:42.559904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 323
41.4%
업무시설 148
19.0%
교육연구시설 78
 
10.0%
제1종근린생활시설 45
 
5.8%
제2종근린생활시설 39
 
5.0%
판매시설 32
 
4.1%
공장 17
 
2.2%
자동차관련시설 15
 
1.9%
의료시설 11
 
1.4%
문화및집회시설 9
 
1.2%
Other values (25) 64
 
8.2%

Interactions

2024-04-06T17:38:33.674431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:38:42.795883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호주 용도
우편번호1.0000.546
주 용도0.5461.000
2024-04-06T17:38:43.077443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호주 용도
우편번호1.0000.457
주 용도0.4571.000

Missing values

2024-04-06T17:38:34.152106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:38:34.526196image/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

건물명우편번호주소연면적 및 세대수주 용도
0한국철도공사 고양고속철도차량기지10439경기도 고양시 덕양구 행주로 108-1(강매동, 한국철도공사 고양고속철도차량기지)153929판매및영업시설
1중부대학교 고양캠퍼스10279경기도 고양시 덕양구 동헌로 305(대자동, 중부대학교 고양캠퍼스)64737교육연구시설
2고양 원마운트10392경기도 고양시 일산서구 한류월드로 300(대화동, 고양 원마운트 관리사무소)165386.923운동시설
3고양 일산 호수공원 가로수길10392경기도 고양시 일산서구 주엽로 80(대화동, 일산호수공원 가로수길 관리사무소)35424.73판매시설
4고양농수산물종합유통센터10226경기도 고양시 일산서구 대화로 362 (대화동, 고양농수산물종합유통센터)59,612판매시설
5고양시종합운동장10223경기도 고양시 일산서구 중앙로 1601(대화동, 고양종합운동장)64207문화및집회시설
6현대백화점10391경기도 고양시 일산서구 호수로 817(대화동, 현대백화점)95160판매시설
7홈플러스 킨텍스점10391경기도 고양시 일산서구 호수로 817(대화동, 홈플러스 킨텍스점)42,954판매시설
8신동아노블타워10380경기도 고양시 일산서구 중앙로 1542(대화동, 신동아노블타워 관리사무소)33,279업무시설
9일산 더샵 그라비스타10390경기도 고양시 일산서구 킨텍스로 217-23(대화동, 일산 더샵 그라비스타 관리사무소)171107.5349업무시설
건물명우편번호주소연면적 및 세대수주 용도
768신원고등학교10567고양시 덕양구 통일로 391(신원동, 신원고등학교)14309교육연구시설
769향동고등학교10546고양시 덕양구 향기3로 6(향동동, 향동고등학교)12622교육연구시설
770덕은한강초등학교10543고양시 덕양구 대덕산로 55(덕은동, 덕은한강초등학교)14799교육연구시설
771디안빌딩10474고양시 덕양구 충장로 285(화정동, 디안빌딩)13215자동차관련시설
772삼송2차 원흥역 동원로얄듀크비스타 판매시설10558고양시 덕양구 권율대로 690(원흥동, 삼송2차동원로얄듀크비스타)10195판매시설
773DMC한강삼정그린코아더베스트412170고양시 덕양구 덕은동 455-14(덕은동, DMC한강삼정그린코아더베스트)366공동주택
774라코드412120고양시 덕양구 지축동 1072(지축동, 라코드 오피스텔)14377업무시설
775지축 수피움10584고양시 덕양구 오부자로 120(지축동, 지축역수피움)583공동주택
776채움지축역10585고양시 덕양구 지축로 50(지축동, 채움지축역)10647근린생활시설
777큰마을주상가10239고양시 일산서구 일현로 140(탄현동, 큰마을주상가)11740근린생활시설