Overview

Dataset statistics

Number of variables6
Number of observations137
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory49.0 B

Variable types

Text4
Categorical2

Dataset

Description해당 데이터는 인천광역시 남동구의 공동주택 관리사무소 현황에 관련된 자료로서, 인천광역시 남동구 공동주택 관리사무소 현황의 기관명, 관할동, 도로명주소, 전화번호, 팩스번호의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104017&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일 has constant value ""Constant
전화번호 has unique valuesUnique
팩스번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:14:41.196873
Analysis finished2024-03-18 05:14:41.618547
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리사무소명
Text

Distinct136
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-18T14:14:41.791123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length8.3065693
Min length2

Characters and Unicode

Total characters1138
Distinct characters186
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)98.5%

Sample

1st row동아
2nd row팬더
3rd row구월아시아드선수촌1단지
4th row구월아시아드선수촌2단지
5th row구월아시아드선수촌5단지
ValueCountFrequency (%)
한화꿈에그린 8
 
4.9%
논현 3
 
1.9%
서해그랑블 2
 
1.2%
현대 2
 
1.2%
임광그대가 1
 
0.6%
논현휴먼시아13단지(푸르내마을 1
 
0.6%
도림주공그린빌2단지 1
 
0.6%
서창lh14단지 1
 
0.6%
장수주공 1
 
0.6%
풍림1차 1
 
0.6%
Other values (141) 141
87.0%
2024-03-18T14:14:42.175822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 67
 
5.9%
단 61
 
5.4%
아 36
 
3.2%
1 34
 
3.0%
현 25
 
2.2%
25
 
2.2%
시 24
 
2.1%
에 22
 
1.9%
( 21
 
1.8%
) 21
 
1.8%
Other values (176) 802
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 948
83.3%
Decimal Number 89
 
7.8%
Uppercase Letter 32
 
2.8%
Space Separator 25
 
2.2%
Open Punctuation 21
 
1.8%
Close Punctuation 21
 
1.8%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 67
 
7.1%
단 61
 
6.4%
아 36
 
3.8%
현 25
 
2.6%
시 24
 
2.5%
에 22
 
2.3%
논 21
 
2.2%
수 21
 
2.2%
서 20
 
2.1%
트 19
 
2.0%
Other values (159) 632
66.7%
Decimal Number
ValueCountFrequency (%)
1 34
38.2%
2 18
20.2%
3 8
 
9.0%
5 7
 
7.9%
4 5
 
5.6%
6 5
 
5.6%
8 4
 
4.5%
7 4
 
4.5%
9 2
 
2.2%
0 2
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
L 16
50.0%
H 14
43.8%
B 2
 
6.2%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 948
83.3%
Common 158
 
13.9%
Latin 32
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 67
 
7.1%
단 61
 
6.4%
아 36
 
3.8%
현 25
 
2.6%
시 24
 
2.5%
에 22
 
2.3%
논 21
 
2.2%
수 21
 
2.2%
서 20
 
2.1%
트 19
 
2.0%
Other values (159) 632
66.7%
Common
ValueCountFrequency (%)
1 34
21.5%
25
15.8%
( 21
13.3%
) 21
13.3%
2 18
11.4%
3 8
 
5.1%
5 7
 
4.4%
4 5
 
3.2%
6 5
 
3.2%
8 4
 
2.5%
Other values (4) 10
 
6.3%
Latin
ValueCountFrequency (%)
L 16
50.0%
H 14
43.8%
B 2
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 948
83.3%
ASCII 190
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 67
 
7.1%
단 61
 
6.4%
아 36
 
3.8%
현 25
 
2.6%
시 24
 
2.5%
에 22
 
2.3%
논 21
 
2.2%
수 21
 
2.2%
서 20
 
2.1%
트 19
 
2.0%
Other values (159) 632
66.7%
ASCII
ValueCountFrequency (%)
1 34
17.9%
25
13.2%
( 21
11.1%
) 21
11.1%
2 18
9.5%
L 16
8.4%
H 14
7.4%
3 8
 
4.2%
5 7
 
3.7%
4 5
 
2.6%
Other values (7) 21
11.1%

관할동
Categorical

Distinct8
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
논현동
39 
만수동
33 
서창동
21 
구월동
18 
간석동
18 
Other values (3)
8 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
논현동 39
28.5%
만수동 33
24.1%
서창동 21
15.3%
구월동 18
13.1%
간석동 18
13.1%
도림동 4
 
2.9%
남촌동 3
 
2.2%
장수동 1
 
0.7%

Length

2024-03-18T14:14:42.297103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:14:42.415783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
논현동 39
28.5%
만수동 33
24.1%
서창동 21
15.3%
구월동 18
13.1%
간석동 18
13.1%
도림동 4
 
2.9%
남촌동 3
 
2.2%
장수동 1
 
0.7%

도로명주소
Text

Distinct133
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-18T14:14:42.693239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.1094891
Min length5

Characters and Unicode

Total characters1248
Distinct characters85
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

Unique129 ?
Unique (%)94.2%

Sample

1st row인주대로676번길 22
2nd row인주대로662번길 32
3rd row선수촌공원로 85
4th row선수촌공원로 96
5th row선수촌로 56
ValueCountFrequency (%)
서창남순환로 10
 
3.7%
선수촌로 6
 
2.2%
논현로 5
 
1.8%
8 4
 
1.5%
장승남로 4
 
1.5%
34 4
 
1.5%
21 4
 
1.5%
17 4
 
1.5%
22 4
 
1.5%
구월로 4
 
1.5%
Other values (160) 222
81.9%
2024-03-18T14:14:43.160799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 137
 
11.0%
136
 
10.9%
1 88
 
7.1%
2 62
 
5.0%
길 52
 
4.2%
번 52
 
4.2%
0 44
 
3.5%
3 43
 
3.4%
8 42
 
3.4%
4 42
 
3.4%
Other values (75) 550
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
50.5%
Decimal Number 470
37.7%
Space Separator 136
 
10.9%
Dash Punctuation 9
 
0.7%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 137
21.7%
길 52
 
8.3%
번 52
 
8.3%
남 28
 
4.4%
서 19
 
3.0%
수 17
 
2.7%
구 17
 
2.7%
창 13
 
2.1%
촌 12
 
1.9%
장 12
 
1.9%
Other values (62) 271
43.0%
Decimal Number
ValueCountFrequency (%)
1 88
18.7%
2 62
13.2%
0 44
9.4%
3 43
9.1%
8 42
8.9%
4 42
8.9%
5 42
8.9%
6 37
7.9%
9 36
7.7%
7 34
 
7.2%
Space Separator
ValueCountFrequency (%)
136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
50.5%
Common 618
49.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 137
21.7%
길 52
 
8.3%
번 52
 
8.3%
남 28
 
4.4%
서 19
 
3.0%
수 17
 
2.7%
구 17
 
2.7%
창 13
 
2.1%
촌 12
 
1.9%
장 12
 
1.9%
Other values (62) 271
43.0%
Common
ValueCountFrequency (%)
136
22.0%
1 88
14.2%
2 62
10.0%
0 44
 
7.1%
3 43
 
7.0%
8 42
 
6.8%
4 42
 
6.8%
5 42
 
6.8%
6 37
 
6.0%
9 36
 
5.8%
Other values (3) 46
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
50.5%
ASCII 618
49.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 137
21.7%
길 52
 
8.3%
번 52
 
8.3%
남 28
 
4.4%
서 19
 
3.0%
수 17
 
2.7%
구 17
 
2.7%
창 13
 
2.1%
촌 12
 
1.9%
장 12
 
1.9%
Other values (62) 271
43.0%
ASCII
ValueCountFrequency (%)
136
22.0%
1 88
14.2%
2 62
10.0%
0 44
 
7.1%
3 43
 
7.0%
8 42
 
6.8%
4 42
 
6.8%
5 42
 
6.8%
6 37
 
6.0%
9 36
 
5.8%
Other values (3) 46
 
7.4%

전화번호
Text

UNIQUE 

Distinct137
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-18T14:14:43.411346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1644
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

Unique137 ?
Unique (%)100.0%

Sample

1st row032-462-1283
2nd row032-463-0136
3rd row032-472-2724
4th row032-472-2670
5th row032-471-9923
ValueCountFrequency (%)
032-462-1283 1
 
0.7%
032-466-4577 1
 
0.7%
032-254-7389 1
 
0.7%
032-433-7008 1
 
0.7%
032-429-3331 1
 
0.7%
032-429-7517 1
 
0.7%
032-432-2725 1
 
0.7%
032-442-0155 1
 
0.7%
032-446-9062 1
 
0.7%
032-446-1502 1
 
0.7%
Other values (127) 127
92.7%
2024-03-18T14:14:43.752488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 274
16.7%
2 257
15.6%
3 219
13.3%
0 210
12.8%
4 205
12.5%
6 112
6.8%
1 86
 
5.2%
7 84
 
5.1%
5 69
 
4.2%
8 67
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1370
83.3%
Dash Punctuation 274
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 257
18.8%
3 219
16.0%
0 210
15.3%
4 205
15.0%
6 112
8.2%
1 86
 
6.3%
7 84
 
6.1%
5 69
 
5.0%
8 67
 
4.9%
9 61
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1644
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 274
16.7%
2 257
15.6%
3 219
13.3%
0 210
12.8%
4 205
12.5%
6 112
6.8%
1 86
 
5.2%
7 84
 
5.1%
5 69
 
4.2%
8 67
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 274
16.7%
2 257
15.6%
3 219
13.3%
0 210
12.8%
4 205
12.5%
6 112
6.8%
1 86
 
5.2%
7 84
 
5.1%
5 69
 
4.2%
8 67
 
4.1%

팩스번호
Text

UNIQUE 

Distinct137
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-18T14:14:44.008302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1644
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

Unique137 ?
Unique (%)100.0%

Sample

1st row032-225-5894
2nd row032-464-2784
3rd row032-472-2723
4th row032-472-2671
5th row032-471-9924
ValueCountFrequency (%)
032-225-5894 1
 
0.7%
032-465-1226 1
 
0.7%
032-446-7389 1
 
0.7%
032-432-7009 1
 
0.7%
032-442-3331 1
 
0.7%
032-429-7518 1
 
0.7%
032-432-2703 1
 
0.7%
032-442-0156 1
 
0.7%
032-446-9065 1
 
0.7%
032-446-1503 1
 
0.7%
Other values (127) 127
92.7%
2024-03-18T14:14:44.386210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 274
16.7%
2 269
16.4%
3 220
13.4%
0 196
11.9%
4 189
11.5%
6 102
 
6.2%
1 96
 
5.8%
7 95
 
5.8%
9 77
 
4.7%
5 64
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1370
83.3%
Dash Punctuation 274
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 269
19.6%
3 220
16.1%
0 196
14.3%
4 189
13.8%
6 102
 
7.4%
1 96
 
7.0%
7 95
 
6.9%
9 77
 
5.6%
5 64
 
4.7%
8 62
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1644
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 274
16.7%
2 269
16.4%
3 220
13.4%
0 196
11.9%
4 189
11.5%
6 102
 
6.2%
1 96
 
5.8%
7 95
 
5.8%
9 77
 
4.7%
5 64
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1644
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 274
16.7%
2 269
16.4%
3 220
13.4%
0 196
11.9%
4 189
11.5%
6 102
 
6.2%
1 96
 
5.8%
7 95
 
5.8%
9 77
 
4.7%
5 64
 
3.9%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-09-04
137 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-04
2nd row2023-09-04
3rd row2023-09-04
4th row2023-09-04
5th row2023-09-04

Common Values

ValueCountFrequency (%)
2023-09-04 137
100.0%

Length

2024-03-18T14:14:44.547056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:14:44.643119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-04 137
100.0%

Missing values

2024-03-18T14:14:41.460099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:14:41.575610image/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

관리사무소명관할동도로명주소전화번호팩스번호데이터기준일
0동아구월동인주대로676번길 22032-462-1283032-225-58942023-09-04
1팬더구월동인주대로662번길 32032-463-0136032-464-27842023-09-04
2구월아시아드선수촌1단지구월동선수촌공원로 85032-472-2724032-472-27232023-09-04
3구월아시아드선수촌2단지구월동선수촌공원로 96032-472-2670032-472-26712023-09-04
4구월아시아드선수촌5단지구월동선수촌로 56032-471-9923032-471-99242023-09-04
5구월아시아드선수촌6단지구월동선수촌로 27032-471-2055032-471-20562023-09-04
6구월아시아드선수촌7단지구월동선수촌로 75032-462-5700032-462-58002023-09-04
7구월아시아드선수촌8단지구월동선수촌로 8032-471-9958032-471-99592023-09-04
8구월아시아드선수촌 센트럴자이구월동선수촌로 55032-468-0157032-468-01592023-09-04
9구월 유승한내들 퍼스티지구월동선수촌로 75032-468-0564032-468-05652023-09-04
관리사무소명관할동도로명주소전화번호팩스번호데이터기준일
127에코메트로9단지 한화꿈에그린논현동에코중앙로 96032-433-6794032-433-67702023-09-04
128소래휴먼시아3단지논현동앵고개로815번길 22032-439-7484032-439-74862023-09-04
129소래휴먼시아1단지논현동앵고개로815번길 70032-429-8817032-429-88182023-09-04
130논현유호엔시티 1단지논현동포구로 35032-423-4229032-429-84982023-09-04
131에코메트로3차 더타워논현동소래역남로 40032-423-5691032-423-56932023-09-04
132소래휴먼시아4단지(논현센트럴뷰)논현동논고개로68번길 34032-429-6833032-429-68352023-09-04
133논현유승한내들 와이드오션논현동에코중앙로66번길 6032-421-7641032-422-76412023-09-04
134논현 푸르지오논현동포구로40032-429-7066032-429-70672023-09-04
135논현 LH15단지논현동함박뫼로 456032-429-7354032-429-73562023-09-04
136논현 LH16단지(창업지원주택)논현동은봉로 297032-426-1116032-426-11182023-09-04