Overview

Dataset statistics

Number of variables4
Number of observations300
Missing cells12
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory32.4 B

Variable types

Text3
Categorical1

Dataset

Description해당 데이터는 인천광역시 남동구의 부동산중개업 현황에 관련된 자료로서, 인천광역시 남동구 부동산중개업 현황의 사무소명, 업소명, 사무소전화번호, 사무소주소의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15104343/fileData.do

Alerts

업소명 has constant value ""Constant
사무소전화번호 has 12 (4.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 07:24:18.193848
Analysis finished2023-12-12 07:24:18.646501
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사무소명
Text

Distinct279
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T16:24:18.840120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length10.746667
Min length4

Characters and Unicode

Total characters3224
Distinct characters253
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

Unique263 ?
Unique (%)87.7%

Sample

1st row이일 공인중개사사무소
2nd row새힘공인중개사사무소
3rd row신한뷰공인중개사
4th row장승백이공인중개사사무소
5th row미소공인중개사사무소
ValueCountFrequency (%)
공인중개사사무소 41
 
11.7%
행운공인중개사사무소 5
 
1.4%
은혜공인중개사사무소 3
 
0.9%
황금공인중개사사무소 3
 
0.9%
삼성공인중개사사무소 2
 
0.6%
행복한공인중개사사무소 2
 
0.6%
공인중개사 2
 
0.6%
스타공인중개사사무소 2
 
0.6%
사무소 2
 
0.6%
은성공인중개사사무소 2
 
0.6%
Other values (277) 287
81.8%
2023-12-12T16:24:19.252670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 511
15.8%
중 272
 
8.4%
인 271
 
8.4%
개 270
 
8.4%
공 267
 
8.3%
소 256
 
7.9%
무 252
 
7.8%
동 70
 
2.2%
부 68
 
2.1%
산 68
 
2.1%
Other values (243) 919
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3119
96.7%
Space Separator 51
 
1.6%
Decimal Number 30
 
0.9%
Uppercase Letter 22
 
0.7%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 511
16.4%
중 272
 
8.7%
인 271
 
8.7%
개 270
 
8.7%
공 267
 
8.6%
소 256
 
8.2%
무 252
 
8.1%
동 70
 
2.2%
부 68
 
2.2%
산 68
 
2.2%
Other values (223) 814
26.1%
Uppercase Letter
ValueCountFrequency (%)
S 3
13.6%
H 3
13.6%
L 3
13.6%
K 3
13.6%
O 2
9.1%
I 2
9.1%
G 1
 
4.5%
R 1
 
4.5%
A 1
 
4.5%
B 1
 
4.5%
Other values (2) 2
9.1%
Decimal Number
ValueCountFrequency (%)
1 17
56.7%
4 8
26.7%
2 3
 
10.0%
5 1
 
3.3%
9 1
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3119
96.7%
Common 81
 
2.5%
Latin 24
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 511
16.4%
중 272
 
8.7%
인 271
 
8.7%
개 270
 
8.7%
공 267
 
8.6%
소 256
 
8.2%
무 252
 
8.1%
동 70
 
2.2%
부 68
 
2.2%
산 68
 
2.2%
Other values (223) 814
26.1%
Latin
ValueCountFrequency (%)
S 3
12.5%
H 3
12.5%
L 3
12.5%
K 3
12.5%
O 2
8.3%
I 2
8.3%
G 1
 
4.2%
R 1
 
4.2%
A 1
 
4.2%
B 1
 
4.2%
Other values (4) 4
16.7%
Common
ValueCountFrequency (%)
51
63.0%
1 17
 
21.0%
4 8
 
9.9%
2 3
 
3.7%
5 1
 
1.2%
9 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3119
96.7%
ASCII 105
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 511
16.4%
중 272
 
8.7%
인 271
 
8.7%
개 270
 
8.7%
공 267
 
8.6%
소 256
 
8.2%
무 252
 
8.1%
동 70
 
2.2%
부 68
 
2.2%
산 68
 
2.2%
Other values (223) 814
26.1%
ASCII
ValueCountFrequency (%)
51
48.6%
1 17
 
16.2%
4 8
 
7.6%
S 3
 
2.9%
H 3
 
2.9%
2 3
 
2.9%
L 3
 
2.9%
K 3
 
2.9%
O 2
 
1.9%
I 2
 
1.9%
Other values (10) 10
 
9.5%

업소명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
중개업
300 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중개업 300
100.0%

Length

2023-12-12T16:24:19.386327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:24:19.476724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중개업 300
100.0%

사무소전화번호
Text

MISSING 

Distinct286
Distinct (%)99.3%
Missing12
Missing (%)4.0%
Memory size2.5 KiB
2023-12-12T16:24:19.657072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.430556
Min length12

Characters and Unicode

Total characters3580
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

Unique284 ?
Unique (%)98.6%

Sample

1st row032-469-2221
2nd row032-437-4584
3rd row032-421-7989
4th row0507-1478-5014
5th row0507-1343-6330
ValueCountFrequency (%)
032-446-8249 2
 
0.7%
032-435-0000 2
 
0.7%
032-461-1313 1
 
0.3%
0507-1410-0025 1
 
0.3%
032-466-0144 1
 
0.3%
032-421-7191 1
 
0.3%
0507-1411-3377 1
 
0.3%
0507-1343-9497 1
 
0.3%
0507-1333-8888 1
 
0.3%
032-424-6800 1
 
0.3%
Other values (276) 276
95.8%
2023-12-12T16:24:19.995298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 621
17.3%
- 576
16.1%
3 427
11.9%
4 413
11.5%
2 401
11.2%
1 245
 
6.8%
7 211
 
5.9%
5 197
 
5.5%
8 189
 
5.3%
6 168
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3004
83.9%
Dash Punctuation 576
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 621
20.7%
3 427
14.2%
4 413
13.7%
2 401
13.3%
1 245
 
8.2%
7 211
 
7.0%
5 197
 
6.6%
8 189
 
6.3%
6 168
 
5.6%
9 132
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 576
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3580
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 621
17.3%
- 576
16.1%
3 427
11.9%
4 413
11.5%
2 401
11.2%
1 245
 
6.8%
7 211
 
5.9%
5 197
 
5.5%
8 189
 
5.3%
6 168
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3580
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 621
17.3%
- 576
16.1%
3 427
11.9%
4 413
11.5%
2 401
11.2%
1 245
 
6.8%
7 211
 
5.9%
5 197
 
5.5%
8 189
 
5.3%
6 168
 
4.7%

사무소주소
Text

Distinct293
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T16:24:20.229279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length35
Mean length21.356667
Min length12

Characters and Unicode

Total characters6407
Distinct characters235
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique287 ?
Unique (%)95.7%

Sample

1st row인천 남동구 용천로 97
2nd row인천 남동구 백범로 457 성우네오빌
3rd row인천 남동구 미래로 21 SR노빌리안2
4th row인천 남동구 서창남로 45 로데오프라자 103호
5th row인천 남동구 경인로644번길 55
ValueCountFrequency (%)
인천 300
 
20.3%
남동구 300
 
20.3%
1층 29
 
2.0%
101호 16
 
1.1%
호구포로 14
 
0.9%
서창남순환로 13
 
0.9%
상가 13
 
0.9%
102호 12
 
0.8%
미래로 11
 
0.7%
103호 10
 
0.7%
Other values (473) 762
51.5%
2023-12-12T16:24:20.639501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1180
18.4%
남 369
 
5.8%
동 357
 
5.6%
구 353
 
5.5%
인 329
 
5.1%
1 323
 
5.0%
천 312
 
4.9%
로 305
 
4.8%
2 171
 
2.7%
0 159
 
2.5%
Other values (225) 2549
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3742
58.4%
Decimal Number 1408
 
22.0%
Space Separator 1180
 
18.4%
Dash Punctuation 41
 
0.6%
Uppercase Letter 25
 
0.4%
Other Punctuation 4
 
0.1%
Lowercase Letter 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 369
 
9.9%
동 357
 
9.5%
구 353
 
9.4%
인 329
 
8.8%
천 312
 
8.3%
로 305
 
8.2%
번 125
 
3.3%
길 125
 
3.3%
호 116
 
3.1%
서 50
 
1.3%
Other values (195) 1301
34.8%
Uppercase Letter
ValueCountFrequency (%)
A 6
24.0%
B 5
20.0%
D 3
12.0%
C 2
 
8.0%
P 2
 
8.0%
I 1
 
4.0%
N 1
 
4.0%
T 1
 
4.0%
R 1
 
4.0%
S 1
 
4.0%
Other values (2) 2
 
8.0%
Decimal Number
ValueCountFrequency (%)
1 323
22.9%
2 171
12.1%
0 159
11.3%
3 142
10.1%
4 123
 
8.7%
5 121
 
8.6%
6 104
 
7.4%
9 98
 
7.0%
7 89
 
6.3%
8 78
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
66.7%
a 1
33.3%
Space Separator
ValueCountFrequency (%)
1180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3740
58.4%
Common 2637
41.2%
Latin 28
 
0.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 369
 
9.9%
동 357
 
9.5%
구 353
 
9.4%
인 329
 
8.8%
천 312
 
8.3%
로 305
 
8.2%
번 125
 
3.3%
길 125
 
3.3%
호 116
 
3.1%
서 50
 
1.3%
Other values (193) 1299
34.7%
Common
ValueCountFrequency (%)
1180
44.7%
1 323
 
12.2%
2 171
 
6.5%
0 159
 
6.0%
3 142
 
5.4%
4 123
 
4.7%
5 121
 
4.6%
6 104
 
3.9%
9 98
 
3.7%
7 89
 
3.4%
Other values (6) 127
 
4.8%
Latin
ValueCountFrequency (%)
A 6
21.4%
B 5
17.9%
D 3
10.7%
b 2
 
7.1%
C 2
 
7.1%
P 2
 
7.1%
a 1
 
3.6%
I 1
 
3.6%
N 1
 
3.6%
T 1
 
3.6%
Other values (4) 4
14.3%
Han
ValueCountFrequency (%)
品 1
50.0%
名 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3740
58.4%
ASCII 2665
41.6%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1180
44.3%
1 323
 
12.1%
2 171
 
6.4%
0 159
 
6.0%
3 142
 
5.3%
4 123
 
4.6%
5 121
 
4.5%
6 104
 
3.9%
9 98
 
3.7%
7 89
 
3.3%
Other values (20) 155
 
5.8%
Hangul
ValueCountFrequency (%)
남 369
 
9.9%
동 357
 
9.5%
구 353
 
9.4%
인 329
 
8.8%
천 312
 
8.3%
로 305
 
8.2%
번 125
 
3.3%
길 125
 
3.3%
호 116
 
3.1%
서 50
 
1.3%
Other values (193) 1299
34.7%
CJK
ValueCountFrequency (%)
品 1
50.0%
名 1
50.0%

Missing values

2023-12-12T16:24:18.507643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:24:18.610806image/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

사무소명업소명사무소전화번호사무소주소
0이일 공인중개사사무소중개업032-469-2221인천 남동구 용천로 97
1새힘공인중개사사무소중개업032-437-4584인천 남동구 백범로 457 성우네오빌
2신한뷰공인중개사중개업032-421-7989인천 남동구 미래로 21 SR노빌리안2
3장승백이공인중개사사무소중개업0507-1478-5014인천 남동구 서창남로 45 로데오프라자 103호
4미소공인중개사사무소중개업0507-1343-6330인천 남동구 경인로644번길 55
5가옥부동산공인중개사사무소중개업0507-1392-8943인천 남동구 앵고개로 928 DA PLAZA 1층 116-1호
6선수촌골드공인중개사사무소중개업032-446-7100인천 남동구 인하로 565 103호
7푸른부동산중개업032-226-2580인천 남동구 구월남로342번길 3
8파라디아공인중개사사무소중개업032-425-2525인천 남동구 남동대로765번길 26
9서창대박 공인중개사사무소중개업032-429-7100인천 남동구 서창남순환로 201
사무소명업소명사무소전화번호사무소주소
290웰빙공인중개사사무소중개업032-463-4545인천 남동구 인주대로751번길 62 106호
291벽산공인중개사사무소중개업032-468-8822인천 남동구 호구포로 920 주상가동 105호
292신논현II공인중개사사무소중개업032-442-3600인천 남동구 논고개로 87 논현메디스타워 104호
293에코스타부동산중개업<NA>인천 남동구 소래역남로 22
294경성부공산중개인사무소중개업032-465-5554인천 남동구 장아산로 184 103호
295힘찬공인중개사사무소중개업<NA>인천 남동구 호구포로 189 남동테크노타워 지식산업센터
296금화공인중개사중개업032-822-8945인천 남동구 청능대로289번길 76
297행운공인중개사사무소중개업032-446-8249인천 남동구 성말로 38
298미소공인중개사사무소중개업032-446-8249인천 남동구 구월로 65
299하나공인중개사사무소중개업032-465-5858인천 남동구 서창남순환로 190-100