Overview

Dataset statistics

Number of variables5
Number of observations33
Missing cells5
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory45.0 B

Variable types

Numeric1
Text4

Dataset

Description인천광역시 미추홀구 내의 건축사사무소 현황입니다. 사무소명, 도로명주소, 전화번호 등의 정보를 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15086987/fileData.do

Alerts

도로명주소 has 1 (3.0%) missing valuesMissing
전화번호 has 4 (12.1%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:55:12.715328
Analysis finished2023-12-12 05:55:13.359191
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T14:55:13.428857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q19
median17
Q325
95-th percentile31.4
Maximum33
Range32
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.6695398
Coefficient of variation (CV)0.56879646
Kurtosis-1.2
Mean17
Median Absolute Deviation (MAD)8
Skewness0
Sum561
Variance93.5
MonotonicityStrictly increasing
2023-12-12T14:55:13.597511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 1
 
3.0%
26 1
 
3.0%
20 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
24 1
 
3.0%
25 1
 
3.0%
27 1
 
3.0%
2 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
1 1
3.0%
2 1
3.0%
3 1
3.0%
4 1
3.0%
5 1
3.0%
6 1
3.0%
7 1
3.0%
8 1
3.0%
9 1
3.0%
10 1
3.0%
ValueCountFrequency (%)
33 1
3.0%
32 1
3.0%
31 1
3.0%
30 1
3.0%
29 1
3.0%
28 1
3.0%
27 1
3.0%
26 1
3.0%
25 1
3.0%
24 1
3.0%

상호명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T14:55:13.906208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.8484848
Min length8

Characters and Unicode

Total characters292
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row제이에스건축사사무소
2nd row도담건축사사무소
3rd row고우건축사사무소
4th row광도건축사사무소
5th row백림종합건축사사무소
ValueCountFrequency (%)
제이에스건축사사무소 1
 
3.0%
나래건축사사무소 1
 
3.0%
효림건축사사무소 1
 
3.0%
경인건축사사무소 1
 
3.0%
도화동건축사사무소 1
 
3.0%
주안동건축사사무소 1
 
3.0%
예찬건축사사무소 1
 
3.0%
숭의동건축사사무소 1
 
3.0%
예인환경건축사사무소 1
 
3.0%
초원건축사사무소 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T14:55:14.420583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 66
22.6%
건 34
11.6%
축 33
11.3%
무 33
11.3%
소 33
11.3%
동 6
 
2.1%
이 4
 
1.4%
도 3
 
1.0%
예 3
 
1.0%
종 3
 
1.0%
Other values (60) 74
25.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 292
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 66
22.6%
건 34
11.6%
축 33
11.3%
무 33
11.3%
소 33
11.3%
동 6
 
2.1%
이 4
 
1.4%
도 3
 
1.0%
예 3
 
1.0%
종 3
 
1.0%
Other values (60) 74
25.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 292
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 66
22.6%
건 34
11.6%
축 33
11.3%
무 33
11.3%
소 33
11.3%
동 6
 
2.1%
이 4
 
1.4%
도 3
 
1.0%
예 3
 
1.0%
종 3
 
1.0%
Other values (60) 74
25.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 292
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 66
22.6%
건 34
11.6%
축 33
11.3%
무 33
11.3%
소 33
11.3%
동 6
 
2.1%
이 4
 
1.4%
도 3
 
1.0%
예 3
 
1.0%
종 3
 
1.0%
Other values (60) 74
25.3%

지번주소
Text

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-12T14:55:14.691254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length21.393939
Min length18

Characters and Unicode

Total characters706
Distinct characters47
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row인천광역시 미추홀구 숭의동 173-39
2nd row인천광역시 미추홀구 용현동 627-47
3rd row인천광역시 미추홀구 용현동 659
4th row인천광역시 미추홀구 주안동 216-12
5th row인천광역시 미추홀구 주안동 231-11 우신주안빌딩 10층 1001호
ValueCountFrequency (%)
인천광역시 33
23.6%
미추홀구 33
23.6%
주안동 11
 
7.9%
문학동 7
 
5.0%
용현동 5
 
3.6%
381-4 4
 
2.9%
숭의동 4
 
2.9%
학익동 3
 
2.1%
241-9 2
 
1.4%
989-1 2
 
1.4%
Other values (35) 36
25.7%
2023-12-12T14:55:15.164856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
 
15.2%
동 34
 
4.8%
인 33
 
4.7%
광 33
 
4.7%
역 33
 
4.7%
시 33
 
4.7%
미 33
 
4.7%
추 33
 
4.7%
홀 33
 
4.7%
구 33
 
4.7%
Other values (37) 301
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 415
58.8%
Decimal Number 151
 
21.4%
Space Separator 107
 
15.2%
Dash Punctuation 32
 
4.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 34
8.2%
인 33
 
8.0%
광 33
 
8.0%
역 33
 
8.0%
시 33
 
8.0%
미 33
 
8.0%
추 33
 
8.0%
홀 33
 
8.0%
구 33
 
8.0%
천 33
 
8.0%
Other values (24) 84
20.2%
Decimal Number
ValueCountFrequency (%)
1 31
20.5%
2 22
14.6%
3 19
12.6%
9 17
11.3%
4 16
10.6%
6 12
 
7.9%
8 11
 
7.3%
7 10
 
6.6%
0 7
 
4.6%
5 6
 
4.0%
Space Separator
ValueCountFrequency (%)
107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 415
58.8%
Common 291
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 34
8.2%
인 33
 
8.0%
광 33
 
8.0%
역 33
 
8.0%
시 33
 
8.0%
미 33
 
8.0%
추 33
 
8.0%
홀 33
 
8.0%
구 33
 
8.0%
천 33
 
8.0%
Other values (24) 84
20.2%
Common
ValueCountFrequency (%)
107
36.8%
- 32
 
11.0%
1 31
 
10.7%
2 22
 
7.6%
3 19
 
6.5%
9 17
 
5.8%
4 16
 
5.5%
6 12
 
4.1%
8 11
 
3.8%
7 10
 
3.4%
Other values (3) 14
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 415
58.8%
ASCII 291
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
36.8%
- 32
 
11.0%
1 31
 
10.7%
2 22
 
7.6%
3 19
 
6.5%
9 17
 
5.8%
4 16
 
5.5%
6 12
 
4.1%
8 11
 
3.8%
7 10
 
3.4%
Other values (3) 14
 
4.8%
Hangul
ValueCountFrequency (%)
동 34
8.2%
인 33
 
8.0%
광 33
 
8.0%
역 33
 
8.0%
시 33
 
8.0%
미 33
 
8.0%
추 33
 
8.0%
홀 33
 
8.0%
구 33
 
8.0%
천 33
 
8.0%
Other values (24) 84
20.2%

도로명주소
Text

MISSING 

Distinct27
Distinct (%)84.4%
Missing1
Missing (%)3.0%
Memory size396.0 B
2023-12-12T14:55:15.467094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length22.15625
Min length17

Characters and Unicode

Total characters709
Distinct characters68
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)75.0%

Sample

1st row인천광역시 미추홀구 독정이로 96
2nd row인천광역시 미추홀구 매소홀로 121
3rd row인천광역시 미추홀구 아암대로29번길 16
4th row인천광역시 미추홀구 주안서로 26
5th row인천광역시 미추홀구 주안로 86 우신주안빌딩 10층 1001호
ValueCountFrequency (%)
인천광역시 32
23.0%
미추홀구 32
23.0%
매소홀로592번길 4
 
2.9%
5-17 4
 
2.9%
주안로 3
 
2.2%
16 2
 
1.4%
5층 2
 
1.4%
독정이로 2
 
1.4%
주안서로 2
 
1.4%
4 2
 
1.4%
Other values (49) 54
38.8%
2023-12-12T14:55:15.921477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
 
15.1%
홀 40
 
5.6%
인 35
 
4.9%
미 33
 
4.7%
추 33
 
4.7%
광 32
 
4.5%
역 32
 
4.5%
시 32
 
4.5%
구 32
 
4.5%
천 32
 
4.5%
Other values (58) 301
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 458
64.6%
Decimal Number 133
 
18.8%
Space Separator 107
 
15.1%
Dash Punctuation 10
 
1.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홀 40
 
8.7%
인 35
 
7.6%
미 33
 
7.2%
추 33
 
7.2%
광 32
 
7.0%
역 32
 
7.0%
시 32
 
7.0%
구 32
 
7.0%
천 32
 
7.0%
로 30
 
6.6%
Other values (45) 127
27.7%
Decimal Number
ValueCountFrequency (%)
5 23
17.3%
1 22
16.5%
2 16
12.0%
9 15
11.3%
6 14
10.5%
4 10
7.5%
8 9
 
6.8%
7 8
 
6.0%
3 8
 
6.0%
0 8
 
6.0%
Space Separator
ValueCountFrequency (%)
107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 458
64.6%
Common 251
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홀 40
 
8.7%
인 35
 
7.6%
미 33
 
7.2%
추 33
 
7.2%
광 32
 
7.0%
역 32
 
7.0%
시 32
 
7.0%
구 32
 
7.0%
천 32
 
7.0%
로 30
 
6.6%
Other values (45) 127
27.7%
Common
ValueCountFrequency (%)
107
42.6%
5 23
 
9.2%
1 22
 
8.8%
2 16
 
6.4%
9 15
 
6.0%
6 14
 
5.6%
4 10
 
4.0%
- 10
 
4.0%
8 9
 
3.6%
7 8
 
3.2%
Other values (3) 17
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 458
64.6%
ASCII 251
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
42.6%
5 23
 
9.2%
1 22
 
8.8%
2 16
 
6.4%
9 15
 
6.0%
6 14
 
5.6%
4 10
 
4.0%
- 10
 
4.0%
8 9
 
3.6%
7 8
 
3.2%
Other values (3) 17
 
6.8%
Hangul
ValueCountFrequency (%)
홀 40
 
8.7%
인 35
 
7.6%
미 33
 
7.2%
추 33
 
7.2%
광 32
 
7.0%
역 32
 
7.0%
시 32
 
7.0%
구 32
 
7.0%
천 32
 
7.0%
로 30
 
6.6%
Other values (45) 127
27.7%

전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing4
Missing (%)12.1%
Memory size396.0 B
2023-12-12T14:55:16.172315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.172414
Min length12

Characters and Unicode

Total characters353
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row032-887-8272
2nd row032-887-2924
3rd row032-888-9080
4th row032-864-3351
5th row032-710-8978
ValueCountFrequency (%)
032-887-8272 1
 
3.4%
032-719-3206 1
 
3.4%
032-435-1488 1
 
3.4%
032-868-9981 1
 
3.4%
032-719-3339 1
 
3.4%
032-721-3927 1
 
3.4%
032-427-1902 1
 
3.4%
032-713-8770 1
 
3.4%
070-7005-8683 1
 
3.4%
032-441-9442 1
 
3.4%
Other values (19) 19
65.5%
2023-12-12T14:55:16.603044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
16.4%
0 49
13.9%
3 49
13.9%
2 45
12.7%
8 38
10.8%
7 29
8.2%
4 24
6.8%
1 22
 
6.2%
9 16
 
4.5%
6 13
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 295
83.6%
Dash Punctuation 58
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
16.6%
3 49
16.6%
2 45
15.3%
8 38
12.9%
7 29
9.8%
4 24
8.1%
1 22
7.5%
9 16
 
5.4%
6 13
 
4.4%
5 10
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 353
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
16.4%
0 49
13.9%
3 49
13.9%
2 45
12.7%
8 38
10.8%
7 29
8.2%
4 24
6.8%
1 22
 
6.2%
9 16
 
4.5%
6 13
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 353
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
16.4%
0 49
13.9%
3 49
13.9%
2 45
12.7%
8 38
10.8%
7 29
8.2%
4 24
6.8%
1 22
 
6.2%
9 16
 
4.5%
6 13
 
3.7%

Interactions

2023-12-12T14:55:12.958383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:55:16.734780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명지번주소도로명주소전화번호
연번1.0001.0000.8040.8011.000
상호명1.0001.0001.0001.0001.000
지번주소0.8041.0001.0001.0001.000
도로명주소0.8011.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2023-12-12T14:55:13.100113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:55:13.211460image/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.
2023-12-12T14:55:13.311875image/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

연번상호명지번주소도로명주소전화번호
01제이에스건축사사무소인천광역시 미추홀구 숭의동 173-39인천광역시 미추홀구 독정이로 96032-887-8272
12도담건축사사무소인천광역시 미추홀구 용현동 627-47인천광역시 미추홀구 매소홀로 121032-887-2924
23고우건축사사무소인천광역시 미추홀구 용현동 659인천광역시 미추홀구 아암대로29번길 16032-888-9080
34광도건축사사무소인천광역시 미추홀구 주안동 216-12인천광역시 미추홀구 주안서로 26032-864-3351
45백림종합건축사사무소인천광역시 미추홀구 주안동 231-11 우신주안빌딩 10층 1001호인천광역시 미추홀구 주안로 86 우신주안빌딩 10층 1001호032-710-8978
56이드건축사사무소인천광역시 미추홀구 용현동 199-9인천광역시 미추홀구 인하로 53 5층032-876-7066
67플랜지건축사사무소인천광역시 미추홀구 학익동 244-40인천광역시 미추홀구 소성로185번길 16-20032-872-3083
78남구건축사사무소인천광역시 미추홀구 숭의동 173-38인천광역시 미추홀구 독정이로 94032-884-1733
89하랑건축사사무소인천광역시 미추홀구 주안동 169-1인천광역시 미추홀구 주안중로 19032-435-7942
910동명건축사사무소인천광역시 미추홀구 학익동 244-33인천광역시 미추홀구 소성로185번길 5032-434-7920
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2324동인종합건축사사무소인천광역시 미추홀구 숭의동 78-9 숭의동아르떼노블 203호인천광역시 미추홀구 경인로 99 숭의동아르떼노블 203호032-866-8855
2425초원건축사사무소인천광역시 미추홀구 주안동 206-16인천광역시 미추홀구 석바위로 56032-441-9442
2526예인환경건축사사무소인천광역시 미추홀구 문학동 381-4인천광역시 미추홀구 매소홀로592번길 5-17070-7005-8683
2627숭의동건축사사무소인천광역시 미추홀구 숭의동 29-3인천광역시 미추홀구 수봉로27번길 4032-713-8770
2728예찬건축사사무소인천광역시 미추홀구 주안동 290-22인천광역시 미추홀구 동주길120번길 55-6032-427-1902
2829주안동건축사사무소인천광역시 미추홀구 주안동 215-8인천광역시 미추홀구 주안서로 28-2032-721-3927
2930도화동건축사사무소인천광역시 미추홀구 도화동 765-1인천광역시 미추홀구 방축로 198032-719-3339
3031경인건축사사무소인천광역시 미추홀구 주안동 241-9인천광역시 미추홀구 주안로 73032-868-9981
3132효림건축사사무소인천광역시 미추홀구 문학동 381-4인천광역시 미추홀구 매소홀로592번길 5-17032-438-8741
3233새울건축사사무소인천광역시 미추홀구 주안동 989-1인천광역시 미추홀구 경원대로 869<NA>