Overview

Dataset statistics

Number of variables6
Number of observations192
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory50.7 B

Variable types

Numeric2
Categorical2
Text2

Dataset

Description서울특별시 성북구 공공건축물 현황에 대한 자료로 구분, 시설명, 행정동, 도로명주소, 연면적 정보를 제공합니다.
Author서울특별시 성북구
URLhttps://www.data.go.kr/data/15112869/fileData.do

Alerts

연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique
연면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:02:37.505573
Analysis finished2023-12-12 14:02:38.540586
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct192
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.5
Minimum1
Maximum192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T23:02:38.633275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.55
Q148.75
median96.5
Q3144.25
95-th percentile182.45
Maximum192
Range191
Interquartile range (IQR)95.5

Descriptive statistics

Standard deviation55.569776
Coefficient of variation (CV)0.5758526
Kurtosis-1.2
Mean96.5
Median Absolute Deviation (MAD)48
Skewness0
Sum18528
Variance3088
MonotonicityStrictly increasing
2023-12-12T23:02:39.147477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
98 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
Other values (182) 182
94.8%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%
183 1
0.5%

구분
Categorical

Distinct37
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
구립경로당
35 
구립어린이집
23 
행정
20 
공영주차장
13 
구립도서관
12 
Other values (32)
89 

Length

Max length7
Median length6
Mean length4.4739583
Min length2

Unique

Unique12 ?
Unique (%)6.2%

Sample

1st row구립경로당
2nd row경로당
3rd row구립경로당
4th row구립어린이집
5th row공영주차장

Common Values

ValueCountFrequency (%)
구립경로당 35
18.2%
구립어린이집 23
 
12.0%
행정 20
 
10.4%
공영주차장 13
 
6.8%
구립도서관 12
 
6.2%
아동청소년지원 6
 
3.1%
문화 6
 
3.1%
키움센터 6
 
3.1%
실내체육 6
 
3.1%
실버복지센터 5
 
2.6%
Other values (27) 60
31.2%

Length

2023-12-12T23:02:39.321423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구립경로당 35
18.2%
구립어린이집 23
 
12.0%
행정 20
 
10.4%
공영주차장 13
 
6.8%
구립도서관 12
 
6.2%
키움센터 6
 
3.1%
실내체육 6
 
3.1%
문화 6
 
3.1%
아동청소년지원 6
 
3.1%
실버복지센터 5
 
2.6%
Other values (27) 60
31.2%

시설명
Text

UNIQUE 

Distinct192
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T23:02:39.584753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length9.1302083
Min length3

Characters and Unicode

Total characters1753
Distinct characters242
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

Unique192 ?
Unique (%)100.0%

Sample

1st row동소문동경로당
2nd row북정경로당
3rd row성북동경로당
4th row한빛어린이집
5th row성북동길 공영주차장
ValueCountFrequency (%)
주민센터 18
 
6.3%
성북구립 10
 
3.5%
공영주차장 10
 
3.5%
우리동네키움센터 6
 
2.1%
집 5
 
1.7%
노인의 4
 
1.4%
성북구보건소 3
 
1.0%
고객편의센터 3
 
1.0%
성북구 3
 
1.0%
종암동 2
 
0.7%
Other values (216) 223
77.7%
2023-12-12T23:02:39.969058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
 
5.5%
동 77
 
4.4%
터 65
 
3.7%
센 63
 
3.6%
북 62
 
3.5%
성 61
 
3.5%
장 50
 
2.9%
경 42
 
2.4%
로 41
 
2.3%
당 39
 
2.2%
Other values (232) 1157
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1587
90.5%
Space Separator 96
 
5.5%
Decimal Number 54
 
3.1%
Close Punctuation 5
 
0.3%
Open Punctuation 5
 
0.3%
Lowercase Letter 3
 
0.2%
Other Punctuation 2
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 77
 
4.9%
터 65
 
4.1%
센 63
 
4.0%
북 62
 
3.9%
성 61
 
3.8%
장 50
 
3.2%
경 42
 
2.6%
로 41
 
2.6%
당 39
 
2.5%
주 32
 
2.0%
Other values (216) 1055
66.5%
Decimal Number
ValueCountFrequency (%)
2 18
33.3%
1 18
33.3%
3 6
 
11.1%
5 4
 
7.4%
4 4
 
7.4%
0 3
 
5.6%
8 1
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
r 1
33.3%
b 1
33.3%
s 1
33.3%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1587
90.5%
Common 163
 
9.3%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 77
 
4.9%
터 65
 
4.1%
센 63
 
4.0%
북 62
 
3.9%
성 61
 
3.8%
장 50
 
3.2%
경 42
 
2.6%
로 41
 
2.6%
당 39
 
2.5%
주 32
 
2.0%
Other values (216) 1055
66.5%
Common
ValueCountFrequency (%)
96
58.9%
2 18
 
11.0%
1 18
 
11.0%
3 6
 
3.7%
) 5
 
3.1%
( 5
 
3.1%
5 4
 
2.5%
4 4
 
2.5%
0 3
 
1.8%
: 1
 
0.6%
Other values (3) 3
 
1.8%
Latin
ValueCountFrequency (%)
r 1
33.3%
b 1
33.3%
s 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1587
90.5%
ASCII 165
 
9.4%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
58.2%
2 18
 
10.9%
1 18
 
10.9%
3 6
 
3.6%
) 5
 
3.0%
( 5
 
3.0%
5 4
 
2.4%
4 4
 
2.4%
0 3
 
1.8%
r 1
 
0.6%
Other values (5) 5
 
3.0%
Hangul
ValueCountFrequency (%)
동 77
 
4.9%
터 65
 
4.1%
센 63
 
4.0%
북 62
 
3.9%
성 61
 
3.8%
장 50
 
3.2%
경 42
 
2.6%
로 41
 
2.6%
당 39
 
2.5%
주 32
 
2.0%
Other values (216) 1055
66.5%
None
ValueCountFrequency (%)
· 1
100.0%

행정동
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
삼선동
18 
종암동
17 
정릉2동
16 
장위1동
16 
성북동
15 
Other values (15)
110 

Length

Max length4
Median length4
Mean length3.5729167
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
삼선동 18
 
9.4%
종암동 17
 
8.9%
정릉2동 16
 
8.3%
장위1동 16
 
8.3%
성북동 15
 
7.8%
월곡2동 13
 
6.8%
정릉3동 11
 
5.7%
석관동 11
 
5.7%
돈암2동 9
 
4.7%
월곡1동 8
 
4.2%
Other values (10) 58
30.2%

Length

2023-12-12T23:02:40.096359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
삼선동 18
 
9.4%
종암동 17
 
8.9%
정릉2동 16
 
8.3%
장위1동 16
 
8.3%
성북동 15
 
7.8%
월곡2동 13
 
6.8%
정릉3동 11
 
5.7%
석관동 11
 
5.7%
돈암2동 9
 
4.7%
길음1동 8
 
4.2%
Other values (10) 58
30.2%

도로명주소
Text

Distinct182
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T23:02:40.375266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37
Mean length23.182292
Min length16

Characters and Unicode

Total characters4451
Distinct characters147
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

Unique173 ?
Unique (%)90.1%

Sample

1st row서울특별시 성북구 동소문로13길 39-20, 203동
2nd row서울특별시 성북구 성북로23길 129-5
3rd row서울특별시 성북구 성북로 41-12
4th row서울특별시 성북구 성북동1가 성북로 37, 성북동 주민센터 1층
5th row서울특별시 성북구 성북동 237-3
ValueCountFrequency (%)
성북구 196
22.2%
서울특별시 195
22.1%
1층 12
 
1.4%
화랑로 8
 
0.9%
성북로 7
 
0.8%
168 6
 
0.7%
보문로 6
 
0.7%
삼선교로4길 5
 
0.6%
정릉로 5
 
0.6%
종암로 5
 
0.6%
Other values (322) 436
49.5%
2023-12-12T23:02:40.763750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
692
 
15.5%
북 231
 
5.2%
성 226
 
5.1%
구 203
 
4.6%
서 201
 
4.5%
울 197
 
4.4%
특 195
 
4.4%
별 195
 
4.4%
시 195
 
4.4%
로 181
 
4.1%
Other values (137) 1935
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2776
62.4%
Decimal Number 801
 
18.0%
Space Separator 692
 
15.5%
Dash Punctuation 50
 
1.1%
Close Punctuation 42
 
0.9%
Open Punctuation 42
 
0.9%
Other Punctuation 38
 
0.9%
Math Symbol 7
 
0.2%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 231
 
8.3%
성 226
 
8.1%
구 203
 
7.3%
서 201
 
7.2%
울 197
 
7.1%
특 195
 
7.0%
별 195
 
7.0%
시 195
 
7.0%
로 181
 
6.5%
길 139
 
5.0%
Other values (119) 813
29.3%
Decimal Number
ValueCountFrequency (%)
1 169
21.1%
2 127
15.9%
3 101
12.6%
4 70
8.7%
8 62
 
7.7%
0 61
 
7.6%
6 59
 
7.4%
5 55
 
6.9%
7 49
 
6.1%
9 48
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
692
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2776
62.4%
Common 1672
37.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 231
 
8.3%
성 226
 
8.1%
구 203
 
7.3%
서 201
 
7.2%
울 197
 
7.1%
특 195
 
7.0%
별 195
 
7.0%
시 195
 
7.0%
로 181
 
6.5%
길 139
 
5.0%
Other values (119) 813
29.3%
Common
ValueCountFrequency (%)
692
41.4%
1 169
 
10.1%
2 127
 
7.6%
3 101
 
6.0%
4 70
 
4.2%
8 62
 
3.7%
0 61
 
3.6%
6 59
 
3.5%
5 55
 
3.3%
- 50
 
3.0%
Other values (6) 226
 
13.5%
Latin
ValueCountFrequency (%)
B 2
66.7%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2776
62.4%
ASCII 1675
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
692
41.3%
1 169
 
10.1%
2 127
 
7.6%
3 101
 
6.0%
4 70
 
4.2%
8 62
 
3.7%
0 61
 
3.6%
6 59
 
3.5%
5 55
 
3.3%
- 50
 
3.0%
Other values (8) 229
 
13.7%
Hangul
ValueCountFrequency (%)
북 231
 
8.3%
성 226
 
8.1%
구 203
 
7.3%
서 201
 
7.2%
울 197
 
7.1%
특 195
 
7.0%
별 195
 
7.0%
시 195
 
7.0%
로 181
 
6.5%
길 139
 
5.0%
Other values (119) 813
29.3%

연면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct192
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean890.73576
Minimum13
Maximum27489.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T23:02:40.885242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile50.935
Q1145.0225
median338.56
Q3816.55
95-th percentile3063.45
Maximum27489.39
Range27476.39
Interquartile range (IQR)671.5275

Descriptive statistics

Standard deviation2328.3462
Coefficient of variation (CV)2.6139584
Kurtosis91.033818
Mean890.73576
Median Absolute Deviation (MAD)239.5
Skewness8.5475963
Sum171021.27
Variance5421196.2
MonotonicityNot monotonic
2023-12-12T23:02:40.992168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120.0 1
 
0.5%
147.07 1
 
0.5%
105.0 1
 
0.5%
827.0 1
 
0.5%
168.7 1
 
0.5%
1170.0 1
 
0.5%
2096.0 1
 
0.5%
2036.0 1
 
0.5%
43.0 1
 
0.5%
579.0 1
 
0.5%
Other values (182) 182
94.8%
ValueCountFrequency (%)
13.0 1
0.5%
20.43 1
0.5%
26.45 1
0.5%
28.0 1
0.5%
29.75 1
0.5%
39.27 1
0.5%
39.6 1
0.5%
43.0 1
0.5%
49.15 1
0.5%
50.0 1
0.5%
ValueCountFrequency (%)
27489.39 1
0.5%
8953.41 1
0.5%
8659.77 1
0.5%
7426.0 1
0.5%
6667.0 1
0.5%
4316.0 1
0.5%
3788.82 1
0.5%
3608.0 1
0.5%
3557.0 1
0.5%
3273.0 1
0.5%

Interactions

2023-12-12T23:02:38.134886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:02:37.913287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:02:38.232025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:02:38.037279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:02:41.067158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분행정동연면적(제곱미터)
연번1.0000.0000.9970.057
구분0.0001.0000.0000.767
행정동0.9970.0001.0000.000
연면적(제곱미터)0.0570.7670.0001.000
2023-12-12T23:02:41.144150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분행정동
구분1.0000.000
행정동0.0001.000
2023-12-12T23:02:41.211314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(제곱미터)구분행정동
연번1.0000.1370.0000.871
연면적(제곱미터)0.1371.0000.4440.000
구분0.0000.4441.0000.000
행정동0.8710.0000.0001.000

Missing values

2023-12-12T23:02:38.365542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:02:38.485263image/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

연번구분시설명행정동도로명주소연면적(제곱미터)
01구립경로당동소문동경로당성북동서울특별시 성북구 동소문로13길 39-20, 203동120.0
12경로당북정경로당성북동서울특별시 성북구 성북로23길 129-539.6
23구립경로당성북동경로당성북동서울특별시 성북구 성북로 41-12176.0
34구립어린이집한빛어린이집성북동서울특별시 성북구 성북동1가 성북로 37, 성북동 주민센터 1층438.0
45공영주차장성북동길 공영주차장성북동서울특별시 성북구 성북동 237-3928.0
56공영주차장과학고길 공영주차장성북동서울특별시 성북구 혜화로 80~84 일대151.8
67공영주차장성북동길 임시 공영주차장성북동서울특별시 성북구 성북동 256-11360.0
78행정성북동 주민센터성북동서울특별시 성북구 성북로 37(성북동)2892.0
89문화성북예술창작터성북동서울특별시 성북구 성북로 23204.76
910미술관성북구립미술관성북동서울특별시 성북구 성북로134400.0
연번구분시설명행정동도로명주소연면적(제곱미터)
182183실버복지센터성북구립 석관실버복지센터석관동서울특별시 성북구 화랑로 32길 88(석관동)821.2
183184구립어린이집하늘채어린이집석관동서울특별시 성북구 한천로 509 104-10186.0
184185지역아동센터구립석관동꿈나무키우미돌봄센터석관동서울특별시 성북구 한천로79길 14-14132.0
185186키움센터우리동네키움센터 성북2호점석관동서울특별시 성북구 화랑로 214 래미안석관아파트 단지 내, 201호269.0
186187청소환경석관동 재활용선별장r석관동서울특별시 성북구 한천로58길 2933608.0
187188경제지원돌곶이시장 고객편의센터석관동서울특별시 성북구 한천로73길 22193.88
188189구립도서관석관동미리내도서관석관동서울특별시 성북구 한천로66길 203, 석관빗물펌프장 4~5층629.52
189190문화돌곶이 생활예술문화센터석관동서울특별시 성북구 화랑로32길 100-1372.0
190191실내체육성북종합레포츠타운석관동서울특별시 성북구 한천로 58길 3078659.77
191192보건행정성북구보건소 장위석관보건지소석관동서울특별시 성북구 한천로 568828.78