Overview

Dataset statistics

Number of variables7
Number of observations135
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.6 KiB
Average record size in memory58.0 B

Variable types

Numeric1
Categorical3
Text2
DateTime1

Dataset

Description서울특별시 성북구 공동주택 현황에 관한 데이터로, 연번, 행정동, 구분, 공동주택명, 도로명주소, 준공일자, 데이터기준일을 포함하고 있습니다.데이터기준일 : 2023-09-13
Author서울특별시 성북구
URLhttps://www.data.go.kr/data/15122783/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:45:46.081524
Analysis finished2023-12-12 02:45:46.720687
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68
Minimum1
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T11:45:46.798622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.7
Q134.5
median68
Q3101.5
95-th percentile128.3
Maximum135
Range134
Interquartile range (IQR)67

Descriptive statistics

Standard deviation39.115214
Coefficient of variation (CV)0.57522374
Kurtosis-1.2
Mean68
Median Absolute Deviation (MAD)34
Skewness0
Sum9180
Variance1530
MonotonicityStrictly increasing
2023-12-12T11:45:46.969541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
94 1
 
0.7%
88 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
95 1
 
0.7%
2 1
 
0.7%
Other values (125) 125
92.6%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%
126 1
0.7%

행정동
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
길음1동
17 
종암동
15 
정릉1동
10 
돈암1동
9 
돈암2동
9 
Other values (15)
75 

Length

Max length5
Median length4
Mean length3.6962963
Min length3

Unique

Unique3 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
길음1동 17
12.6%
종암동 15
11.1%
정릉1동 10
 
7.4%
돈암1동 9
 
6.7%
돈암2동 9
 
6.7%
보문동 9
 
6.7%
정릉2동 9
 
6.7%
장위3동 8
 
5.9%
길음2동 8
 
5.9%
석관동 7
 
5.2%
Other values (10) 34
25.2%

Length

2023-12-12T11:45:47.129974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
길음1동 17
12.6%
종암동 15
11.1%
정릉1동 10
 
7.4%
돈암1동 9
 
6.7%
돈암2동 9
 
6.7%
보문동 9
 
6.7%
정릉2동 9
 
6.7%
장위3동 8
 
5.9%
길음2동 8
 
5.9%
정릉4동 7
 
5.2%
Other values (9) 34
25.2%

구분
Categorical

Distinct6
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
일반분양
85 
임대동
31 
혼합단지
13 
주상복합
 
4
임의(도시형)
 
1

Length

Max length8
Median length4
Mean length3.8222222
Min length3

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
일반분양 85
63.0%
임대동 31
 
23.0%
혼합단지 13
 
9.6%
주상복합 4
 
3.0%
임의(도시형) 1
 
0.7%
주상복합(혼합) 1
 
0.7%

Length

2023-12-12T11:45:47.286924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:47.428290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반분양 85
63.0%
임대동 31
 
23.0%
혼합단지 13
 
9.6%
주상복합 4
 
3.0%
임의(도시형 1
 
0.7%
주상복합(혼합 1
 
0.7%

공동주택명
Text

Distinct134
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T11:45:47.685214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length8.9259259
Min length2

Characters and Unicode

Total characters1205
Distinct characters167
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

Unique133 ?
Unique (%)98.5%

Sample

1st row 송산
2nd row삼선코오롱
3rd row삼선푸르지오
4th row삼선힐스테이트
5th row삼선SK뷰
ValueCountFrequency (%)
래미안 6
 
3.4%
sh빌 3
 
1.7%
보문리슈빌하우트 2
 
1.1%
돈암삼성 2
 
1.1%
월곡 2
 
1.1%
정릉꿈에그린 2
 
1.1%
sk아파트 2
 
1.1%
롯데캐슬클라시아 2
 
1.1%
보문e편한세상 2
 
1.1%
한신한진 2
 
1.1%
Other values (145) 149
85.6%
2023-12-12T11:45:48.151638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 54
 
4.5%
54
 
4.5%
동 40
 
3.3%
2 28
 
2.3%
암 27
 
2.2%
( 26
 
2.2%
) 26
 
2.2%
0 25
 
2.1%
길 23
 
1.9%
음 23
 
1.9%
Other values (157) 879
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 891
73.9%
Decimal Number 168
 
13.9%
Space Separator 54
 
4.5%
Open Punctuation 26
 
2.2%
Close Punctuation 26
 
2.2%
Uppercase Letter 18
 
1.5%
Other Punctuation 10
 
0.8%
Lowercase Letter 8
 
0.7%
Math Symbol 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 40
 
4.5%
암 27
 
3.0%
길 23
 
2.6%
음 23
 
2.6%
이 22
 
2.5%
대 21
 
2.4%
아 19
 
2.1%
정 19
 
2.1%
트 18
 
2.0%
릉 18
 
2.0%
Other values (136) 661
74.2%
Decimal Number
ValueCountFrequency (%)
1 54
32.1%
2 28
16.7%
0 25
14.9%
3 19
 
11.3%
7 9
 
5.4%
5 8
 
4.8%
9 8
 
4.8%
6 7
 
4.2%
8 5
 
3.0%
4 5
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
S 9
50.0%
H 6
33.3%
K 3
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
s 2
25.0%
k 2
25.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 891
73.9%
Common 288
 
23.9%
Latin 26
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 40
 
4.5%
암 27
 
3.0%
길 23
 
2.6%
음 23
 
2.6%
이 22
 
2.5%
대 21
 
2.4%
아 19
 
2.1%
정 19
 
2.1%
트 18
 
2.0%
릉 18
 
2.0%
Other values (136) 661
74.2%
Common
ValueCountFrequency (%)
1 54
18.8%
54
18.8%
2 28
9.7%
( 26
9.0%
) 26
9.0%
0 25
8.7%
3 19
 
6.6%
, 10
 
3.5%
7 9
 
3.1%
5 8
 
2.8%
Other values (5) 29
10.1%
Latin
ValueCountFrequency (%)
S 9
34.6%
H 6
23.1%
e 4
15.4%
K 3
 
11.5%
s 2
 
7.7%
k 2
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 891
73.9%
ASCII 314
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 54
17.2%
54
17.2%
2 28
8.9%
( 26
8.3%
) 26
8.3%
0 25
8.0%
3 19
 
6.1%
, 10
 
3.2%
S 9
 
2.9%
7 9
 
2.9%
Other values (11) 54
17.2%
Hangul
ValueCountFrequency (%)
동 40
 
4.5%
암 27
 
3.0%
길 23
 
2.6%
음 23
 
2.6%
이 22
 
2.5%
대 21
 
2.4%
아 19
 
2.1%
정 19
 
2.1%
트 18
 
2.0%
릉 18
 
2.0%
Other values (136) 661
74.2%

도로명주소
Text

Distinct111
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T11:45:48.461080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length40
Mean length34.703704
Min length25

Characters and Unicode

Total characters4685
Distinct characters191
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

Unique87 ?
Unique (%)64.4%

Sample

1st row서울특별시 성북구 동소문로3길 101 (동소문동4가, 송산아파트)
2nd row서울특별시 성북구 삼선교로23길 23 (삼선동4가, 코오롱 아파트)
3rd row서울특별시 성북구 보문로29다길 31 (삼선동2가, 삼선푸르지오)
4th row서울특별시 성북구 낙산길 243-15 (삼선동2가, 삼선현대힐스테이트)
5th row서울특별시 성북구 삼선교로16길 35 (삼선동3가, 삼선 SK VIEW 아파트)
ValueCountFrequency (%)
서울특별시 135
 
16.0%
성북구 135
 
16.0%
정릉동 26
 
3.1%
길음동 23
 
2.7%
돈암동 21
 
2.5%
종암동 16
 
1.9%
길음뉴타운 14
 
1.7%
하월곡동 13
 
1.5%
북악산로 10
 
1.2%
길음로 9
 
1.1%
Other values (272) 442
52.4%
2023-12-12T11:45:48.994901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
709
 
15.1%
동 165
 
3.5%
북 148
 
3.2%
길 148
 
3.2%
성 142
 
3.0%
시 141
 
3.0%
서 139
 
3.0%
구 137
 
2.9%
울 137
 
2.9%
특 135
 
2.9%
Other values (181) 2684
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3054
65.2%
Space Separator 709
 
15.1%
Decimal Number 494
 
10.5%
Close Punctuation 135
 
2.9%
Open Punctuation 135
 
2.9%
Other Punctuation 130
 
2.8%
Uppercase Letter 18
 
0.4%
Dash Punctuation 9
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 165
 
5.4%
북 148
 
4.8%
길 148
 
4.8%
성 142
 
4.6%
시 141
 
4.6%
서 139
 
4.6%
구 137
 
4.5%
울 137
 
4.5%
특 135
 
4.4%
별 135
 
4.4%
Other values (159) 1627
53.3%
Decimal Number
ValueCountFrequency (%)
1 94
19.0%
2 83
16.8%
3 64
13.0%
4 54
10.9%
5 41
8.3%
0 35
 
7.1%
9 33
 
6.7%
8 33
 
6.7%
6 30
 
6.1%
7 27
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
16.7%
W 3
16.7%
E 3
16.7%
I 3
16.7%
V 3
16.7%
K 3
16.7%
Space Separator
ValueCountFrequency (%)
709
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Other Punctuation
ValueCountFrequency (%)
, 130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3054
65.2%
Common 1612
34.4%
Latin 19
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 165
 
5.4%
북 148
 
4.8%
길 148
 
4.8%
성 142
 
4.6%
시 141
 
4.6%
서 139
 
4.6%
구 137
 
4.5%
울 137
 
4.5%
특 135
 
4.4%
별 135
 
4.4%
Other values (159) 1627
53.3%
Common
ValueCountFrequency (%)
709
44.0%
) 135
 
8.4%
( 135
 
8.4%
, 130
 
8.1%
1 94
 
5.8%
2 83
 
5.1%
3 64
 
4.0%
4 54
 
3.3%
5 41
 
2.5%
0 35
 
2.2%
Other values (5) 132
 
8.2%
Latin
ValueCountFrequency (%)
S 3
15.8%
W 3
15.8%
E 3
15.8%
I 3
15.8%
V 3
15.8%
K 3
15.8%
e 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3054
65.2%
ASCII 1631
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
709
43.5%
) 135
 
8.3%
( 135
 
8.3%
, 130
 
8.0%
1 94
 
5.8%
2 83
 
5.1%
3 64
 
3.9%
4 54
 
3.3%
5 41
 
2.5%
0 35
 
2.1%
Other values (12) 151
 
9.3%
Hangul
ValueCountFrequency (%)
동 165
 
5.4%
북 148
 
4.8%
길 148
 
4.8%
성 142
 
4.6%
시 141
 
4.6%
서 139
 
4.6%
구 137
 
4.5%
울 137
 
4.5%
특 135
 
4.4%
별 135
 
4.4%
Other values (159) 1627
53.3%

준공일자
Date

Distinct108
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1909-06-26 00:00:00
Maximum2022-07-13 00:00:00
2023-12-12T11:45:49.160618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:45:49.347872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-09-13
135 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-13
2nd row2023-09-13
3rd row2023-09-13
4th row2023-09-13
5th row2023-09-13

Common Values

ValueCountFrequency (%)
2023-09-13 135
100.0%

Length

2023-12-12T11:45:49.503305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:49.628218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-13 135
100.0%

Interactions

2023-12-12T11:45:46.414224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:45:49.698963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동구분
연번1.0000.9940.168
행정동0.9941.0000.000
구분0.1680.0001.000
2023-12-12T11:45:49.812983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분행정동
구분1.0000.000
행정동0.0001.000
2023-12-12T11:45:49.912287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동구분
연번1.0000.8190.090
행정동0.8191.0000.000
구분0.0900.0001.000

Missing values

2023-12-12T11:45:46.538307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:45:46.666259image/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

연번행정동구분공동주택명도로명주소준공일자데이터기준일
01성북동일반분양송산서울특별시 성북구 동소문로3길 101 (동소문동4가, 송산아파트)1998-06-122023-09-13
12삼선동일반분양삼선코오롱서울특별시 성북구 삼선교로23길 23 (삼선동4가, 코오롱 아파트)1999-11-022023-09-13
23삼선동일반분양삼선푸르지오서울특별시 성북구 보문로29다길 31 (삼선동2가, 삼선푸르지오)2008-01-092023-09-13
34삼선동일반분양삼선힐스테이트서울특별시 성북구 낙산길 243-15 (삼선동2가, 삼선현대힐스테이트)2008-07-282023-09-13
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