Overview

Dataset statistics

Number of variables4
Number of observations63
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory35.1 B

Variable types

Numeric1
Text3

Dataset

Description이 데이터는 서울특별시 동작구 관내에 있는 건축사 사무소 현황에 관한 것입니다. 이 데이터에는 사무소명, 도로명주소, 대표자 성명(마스킹 처리)이 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15034782/fileData.do

Alerts

도로명주소 has 1 (1.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:57:29.718844
Analysis finished2023-12-12 11:57:30.297283
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32
Minimum1
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T20:57:30.368459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.1
Q116.5
median32
Q347.5
95-th percentile59.9
Maximum63
Range62
Interquartile range (IQR)31

Descriptive statistics

Standard deviation18.330303
Coefficient of variation (CV)0.57282196
Kurtosis-1.2
Mean32
Median Absolute Deviation (MAD)16
Skewness0
Sum2016
Variance336
MonotonicityStrictly increasing
2023-12-12T20:57:30.518548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
2 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
63 1
1.6%
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%

사무소명
Text

Distinct59
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T20:57:30.795199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length11.809524
Min length8

Characters and Unicode

Total characters744
Distinct characters120
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)87.3%

Sample

1st row남서건축사사무소
2nd row비욘드스페이스 종합건축사사무소
3rd row(주)지우종합건축사사무소
4th row종합건축사사무소 대현
5th row도형건축사사무소
ValueCountFrequency (%)
건축사사무소 17
 
18.7%
종합건축사사무소 3
 
3.3%
주식회사 3
 
3.3%
주)건축사사무소감 2
 
2.2%
주)모인건축사사무소 2
 
2.2%
에이앤디 2
 
2.2%
주)모드건축사사무소 2
 
2.2%
주)에이플랜건축사사무소 1
 
1.1%
파사드건축사사무소 1
 
1.1%
가자건축사사무소 1
 
1.1%
Other values (57) 57
62.6%
2023-12-12T20:57:31.287084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 132
17.7%
건 69
 
9.3%
축 65
 
8.7%
소 63
 
8.5%
무 63
 
8.5%
주 32
 
4.3%
30
 
4.0%
( 26
 
3.5%
) 26
 
3.5%
이 13
 
1.7%
Other values (110) 225
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 659
88.6%
Space Separator 30
 
4.0%
Open Punctuation 26
 
3.5%
Close Punctuation 26
 
3.5%
Uppercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 132
20.0%
건 69
 
10.5%
축 65
 
9.9%
소 63
 
9.6%
무 63
 
9.6%
주 32
 
4.9%
이 13
 
2.0%
합 12
 
1.8%
종 12
 
1.8%
인 7
 
1.1%
Other values (104) 191
29.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
33.3%
I 1
33.3%
M 1
33.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 659
88.6%
Common 82
 
11.0%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 132
20.0%
건 69
 
10.5%
축 65
 
9.9%
소 63
 
9.6%
무 63
 
9.6%
주 32
 
4.9%
이 13
 
2.0%
합 12
 
1.8%
종 12
 
1.8%
인 7
 
1.1%
Other values (104) 191
29.0%
Common
ValueCountFrequency (%)
30
36.6%
( 26
31.7%
) 26
31.7%
Latin
ValueCountFrequency (%)
N 1
33.3%
I 1
33.3%
M 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 659
88.6%
ASCII 85
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 132
20.0%
건 69
 
10.5%
축 65
 
9.9%
소 63
 
9.6%
무 63
 
9.6%
주 32
 
4.9%
이 13
 
2.0%
합 12
 
1.8%
종 12
 
1.8%
인 7
 
1.1%
Other values (104) 191
29.0%
ASCII
ValueCountFrequency (%)
30
35.3%
( 26
30.6%
) 26
30.6%
N 1
 
1.2%
I 1
 
1.2%
M 1
 
1.2%

도로명주소
Text

MISSING 

Distinct56
Distinct (%)90.3%
Missing1
Missing (%)1.6%
Memory size636.0 B
2023-12-12T20:57:31.651364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length32.322581
Min length1

Characters and Unicode

Total characters2004
Distinct characters101
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)82.3%

Sample

1st row서울특별시 동작구 양녕로26길 28 (상도동)
2nd row서울특별시 동작구 동작대로5길 9 (사당동)
3rd row서울특별시 동작구 상도로12길 1 3층 (상도동) (상도동)
4th row서울특별시 동작구 장승배기로27길 7-1 (노량진동)
5th row서울특별시 동작구 장승배기로27길 13 (노량진동)
ValueCountFrequency (%)
서울특별시 60
 
15.8%
동작구 60
 
15.8%
사당동 36
 
9.5%
상도동 17
 
4.5%
사당로 10
 
2.6%
2층 10
 
2.6%
노량진동 6
 
1.6%
162 5
 
1.3%
302호 5
 
1.3%
202호 5
 
1.3%
Other values (114) 166
43.7%
2023-12-12T20:57:32.176442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
382
19.1%
동 151
 
7.5%
작 75
 
3.7%
2 72
 
3.6%
( 71
 
3.5%
) 71
 
3.5%
1 68
 
3.4%
서 62
 
3.1%
구 61
 
3.0%
사 61
 
3.0%
Other values (91) 930
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1125
56.1%
Space Separator 382
 
19.1%
Decimal Number 332
 
16.6%
Open Punctuation 71
 
3.5%
Close Punctuation 71
 
3.5%
Dash Punctuation 10
 
0.5%
Other Punctuation 9
 
0.4%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 151
 
13.4%
작 75
 
6.7%
서 62
 
5.5%
구 61
 
5.4%
사 61
 
5.4%
시 61
 
5.4%
별 60
 
5.3%
울 60
 
5.3%
특 60
 
5.3%
로 59
 
5.2%
Other values (75) 415
36.9%
Decimal Number
ValueCountFrequency (%)
2 72
21.7%
1 68
20.5%
3 49
14.8%
0 40
12.0%
5 22
 
6.6%
4 19
 
5.7%
8 17
 
5.1%
7 17
 
5.1%
6 16
 
4.8%
9 12
 
3.6%
Space Separator
ValueCountFrequency (%)
382
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1125
56.1%
Common 875
43.7%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 151
 
13.4%
작 75
 
6.7%
서 62
 
5.5%
구 61
 
5.4%
사 61
 
5.4%
시 61
 
5.4%
별 60
 
5.3%
울 60
 
5.3%
특 60
 
5.3%
로 59
 
5.2%
Other values (75) 415
36.9%
Common
ValueCountFrequency (%)
382
43.7%
2 72
 
8.2%
( 71
 
8.1%
) 71
 
8.1%
1 68
 
7.8%
3 49
 
5.6%
0 40
 
4.6%
5 22
 
2.5%
4 19
 
2.2%
8 17
 
1.9%
Other values (5) 64
 
7.3%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1125
56.1%
ASCII 879
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
382
43.5%
2 72
 
8.2%
( 71
 
8.1%
) 71
 
8.1%
1 68
 
7.7%
3 49
 
5.6%
0 40
 
4.6%
5 22
 
2.5%
4 19
 
2.2%
8 17
 
1.9%
Other values (6) 68
 
7.7%
Hangul
ValueCountFrequency (%)
동 151
 
13.4%
작 75
 
6.7%
서 62
 
5.5%
구 61
 
5.4%
사 61
 
5.4%
시 61
 
5.4%
별 60
 
5.3%
울 60
 
5.3%
특 60
 
5.3%
로 59
 
5.2%
Other values (75) 415
36.9%

대표자
Text

Distinct60
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T20:57:32.442128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.984127
Min length2

Characters and Unicode

Total characters188
Distinct characters67
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)90.5%

Sample

1st row조*천
2nd row송*문
3rd row김*수
4th row박*영
5th row천*상
ValueCountFrequency (%)
박*욱 2
 
3.2%
김*철 2
 
3.2%
김*욱 2
 
3.2%
강*지 1
 
1.6%
김*식 1
 
1.6%
김*로 1
 
1.6%
차*란 1
 
1.6%
조*천 1
 
1.6%
김*면 1
 
1.6%
최*식 1
 
1.6%
Other values (50) 50
79.4%
2023-12-12T20:57:32.951905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 63
33.5%
김 15
 
8.0%
박 7
 
3.7%
철 5
 
2.7%
영 5
 
2.7%
욱 4
 
2.1%
신 3
 
1.6%
최 3
 
1.6%
송 3
 
1.6%
이 3
 
1.6%
Other values (57) 77
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
66.5%
Other Punctuation 63
33.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 15
 
12.0%
박 7
 
5.6%
철 5
 
4.0%
영 5
 
4.0%
욱 4
 
3.2%
신 3
 
2.4%
최 3
 
2.4%
송 3
 
2.4%
이 3
 
2.4%
진 3
 
2.4%
Other values (56) 74
59.2%
Other Punctuation
ValueCountFrequency (%)
* 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
66.5%
Common 63
33.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 15
 
12.0%
박 7
 
5.6%
철 5
 
4.0%
영 5
 
4.0%
욱 4
 
3.2%
신 3
 
2.4%
최 3
 
2.4%
송 3
 
2.4%
이 3
 
2.4%
진 3
 
2.4%
Other values (56) 74
59.2%
Common
ValueCountFrequency (%)
* 63
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
66.5%
ASCII 63
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 63
100.0%
Hangul
ValueCountFrequency (%)
김 15
 
12.0%
박 7
 
5.6%
철 5
 
4.0%
영 5
 
4.0%
욱 4
 
3.2%
신 3
 
2.4%
최 3
 
2.4%
송 3
 
2.4%
이 3
 
2.4%
진 3
 
2.4%
Other values (56) 74
59.2%

Interactions

2023-12-12T20:57:30.066749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:57:33.082486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사무소명도로명주소대표자
연번1.0000.9870.9520.945
사무소명0.9871.0001.0000.974
도로명주소0.9521.0001.0000.967
대표자0.9450.9740.9671.000

Missing values

2023-12-12T20:57:30.182033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:57:30.264436image/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

연번사무소명도로명주소대표자
01남서건축사사무소서울특별시 동작구 양녕로26길 28 (상도동)조*천
12비욘드스페이스 종합건축사사무소서울특별시 동작구 동작대로5길 9 (사당동)송*문
23(주)지우종합건축사사무소서울특별시 동작구 상도로12길 1 3층 (상도동) (상도동)김*수
34종합건축사사무소 대현서울특별시 동작구 장승배기로27길 7-1 (노량진동)박*영
45도형건축사사무소서울특별시 동작구 장승배기로27길 13 (노량진동)천*상
56(주)태건건축사사무소서울특별시 동작구 성대로1길 22 2층 (상도동) (상도동)이*희
67동양건축 건축사사무소서울특별시 동작구 장승배기로 95 (노량진동)이*순
78수도디자인건축사사무소 주식회사서울특별시 동작구 상도로30길 26-8 B01호 (상도동)김*아
89둥지아트건축사사무소서울특별시 동작구 상도로43길 4 1층 (상도1동)문*도
910건축사사무소 환서울특별시 동작구 동작대로43길 1 (동작동)송*섭
연번사무소명도로명주소대표자
5354모프 건축사사무소서울특별시 동작구 여의대방로22길 94 그린시티 B01호 (신대방동)박*민
5455디자인그룹MIN 건축사사무소(주)서울특별시 동작구 노량진로23가길 23 상가동 303호 (본동)김*철
5556건축사사무소 피에이그룹서울특별시 동작구 사당로 253-3 남성빌딩 202호 (사당동)오*섭
5657필드온 건축사사무소서울특별시 동작구 동작대로43길 1 101호 (동작동)최*명
5758주식회사트라움벡건축사사무소서울특별시 동작구 사당로 162 302호 (사당동)김*진
5859(주)비엠도시건축사사무소서울특별시 동작구 상도로68길 1-16 2층 (상도동)김*식
5960오름건축사사무소서울특별시 동작구 사당로30길 80 2층 오름건축사사무소 (사당동)강*지
6061치읓건축사사무소서울특별시 동작구 남부순환로271길 55 202호 (사당동)차*란
6162아이디엠개발건축사사무소주식회사서울특별시 동작구 동작대로1길 50 중동빌딩 2층 202호 (사당동)신*철
6263제이유건축사사무소서울특별시 동작구 사당로 215 서림빌딩 505호 (사당동)박*욱