Overview

Dataset statistics

Number of variables3
Number of observations5011
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory117.6 KiB
Average record size in memory24.0 B

Variable types

Text2
Boolean1

Dataset

Description부산도시공간정보시스템 도로상하수도기반시설에 대한 공통 부서 코드 정보입니다.(부서 코드, 부서 명, 사용 여부 등)
URLhttps://www.data.go.kr/data/15084496/fileData.do

Alerts

부서코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:47:59.807841
Analysis finished2023-12-12 17:48:00.240566
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부서코드
Text

UNIQUE 

Distinct5011
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
2023-12-13T02:48:00.471204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.9948114
Min length6

Characters and Unicode

Total characters40062
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5011 ?
Unique (%)100.0%

Sample

1st row31000000
2nd row31000001
3rd row31000100
4th row31000200
5th row31000250
ValueCountFrequency (%)
31000000 1
 
< 0.1%
31901057 1
 
< 0.1%
31901080 1
 
< 0.1%
31901074 1
 
< 0.1%
31901073 1
 
< 0.1%
31901072 1
 
< 0.1%
31901070 1
 
< 0.1%
31901060 1
 
< 0.1%
31901340 1
 
< 0.1%
31901052 1
 
< 0.1%
Other values (5001) 5001
99.8%
2023-12-13T02:48:00.922615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11863
29.6%
1 7512
18.8%
3 5768
14.4%
5 3826
 
9.6%
4 2682
 
6.7%
2 2092
 
5.2%
9 1898
 
4.7%
8 1745
 
4.4%
7 1456
 
3.6%
6 1212
 
3.0%
Other values (2) 8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40054
> 99.9%
Uppercase Letter 8
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11863
29.6%
1 7512
18.8%
3 5768
14.4%
5 3826
 
9.6%
4 2682
 
6.7%
2 2092
 
5.2%
9 1898
 
4.7%
8 1745
 
4.4%
7 1456
 
3.6%
6 1212
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
D 7
87.5%
V 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 40054
> 99.9%
Latin 8
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11863
29.6%
1 7512
18.8%
3 5768
14.4%
5 3826
 
9.6%
4 2682
 
6.7%
2 2092
 
5.2%
9 1898
 
4.7%
8 1745
 
4.4%
7 1456
 
3.6%
6 1212
 
3.0%
Latin
ValueCountFrequency (%)
D 7
87.5%
V 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11863
29.6%
1 7512
18.8%
3 5768
14.4%
5 3826
 
9.6%
4 2682
 
6.7%
2 2092
 
5.2%
9 1898
 
4.7%
8 1745
 
4.4%
7 1456
 
3.6%
6 1212
 
3.0%
Other values (2) 8
 
< 0.1%

부서명
Text

Distinct4690
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
2023-12-13T02:48:01.206445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length11.093195
Min length1

Characters and Unicode

Total characters55588
Distinct characters352
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4388 ?
Unique (%)87.6%

Sample

1st row부산광역시
2nd row변동자료갱신
3rd row시장실
4th row부시장실
5th row공보관실
ValueCountFrequency (%)
해운대구 201
 
2.0%
강서구 183
 
1.8%
부산진구 179
 
1.8%
동구 173
 
1.7%
기장군 156
 
1.6%
사하구 149
 
1.5%
남구 139
 
1.4%
중구 133
 
1.3%
금정구 129
 
1.3%
총무국 129
 
1.3%
Other values (2706) 8415
84.3%
2023-12-13T02:48:01.653462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4976
 
9.0%
구 3150
 
5.7%
과 2733
 
4.9%
국 2119
 
3.8%
지 1299
 
2.3%
정 1209
 
2.2%
도 1189
 
2.1%
관 1160
 
2.1%
사 1142
 
2.1%
동 1114
 
2.0%
Other values (342) 35497
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49516
89.1%
Space Separator 4976
 
9.0%
Decimal Number 680
 
1.2%
Close Punctuation 197
 
0.4%
Open Punctuation 197
 
0.4%
Uppercase Letter 17
 
< 0.1%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3150
 
6.4%
과 2733
 
5.5%
국 2119
 
4.3%
지 1299
 
2.6%
정 1209
 
2.4%
도 1189
 
2.4%
관 1160
 
2.3%
사 1142
 
2.3%
동 1114
 
2.2%
부 1108
 
2.2%
Other values (320) 33293
67.2%
Decimal Number
ValueCountFrequency (%)
1 302
44.4%
2 166
24.4%
9 75
 
11.0%
3 69
 
10.1%
4 29
 
4.3%
0 22
 
3.2%
5 8
 
1.2%
6 5
 
0.7%
7 2
 
0.3%
8 2
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 5
29.4%
G 4
23.5%
C 3
17.6%
I 2
 
11.8%
T 2
 
11.8%
F 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 2
40.0%
. 2
40.0%
？ 1
20.0%
Space Separator
ValueCountFrequency (%)
4976
100.0%
Close Punctuation
ValueCountFrequency (%)
) 197
100.0%
Open Punctuation
ValueCountFrequency (%)
( 197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49516
89.1%
Common 6055
 
10.9%
Latin 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3150
 
6.4%
과 2733
 
5.5%
국 2119
 
4.3%
지 1299
 
2.6%
정 1209
 
2.4%
도 1189
 
2.4%
관 1160
 
2.3%
사 1142
 
2.3%
동 1114
 
2.2%
부 1108
 
2.2%
Other values (320) 33293
67.2%
Common
ValueCountFrequency (%)
4976
82.2%
1 302
 
5.0%
) 197
 
3.3%
( 197
 
3.3%
2 166
 
2.7%
9 75
 
1.2%
3 69
 
1.1%
4 29
 
0.5%
0 22
 
0.4%
5 8
 
0.1%
Other values (6) 14
 
0.2%
Latin
ValueCountFrequency (%)
A 5
29.4%
G 4
23.5%
C 3
17.6%
I 2
 
11.8%
T 2
 
11.8%
F 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49516
89.1%
ASCII 6071
 
10.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4976
82.0%
1 302
 
5.0%
) 197
 
3.2%
( 197
 
3.2%
2 166
 
2.7%
9 75
 
1.2%
3 69
 
1.1%
4 29
 
0.5%
0 22
 
0.4%
5 8
 
0.1%
Other values (11) 30
 
0.5%
Hangul
ValueCountFrequency (%)
구 3150
 
6.4%
과 2733
 
5.5%
국 2119
 
4.3%
지 1299
 
2.6%
정 1209
 
2.4%
도 1189
 
2.4%
관 1160
 
2.3%
사 1142
 
2.3%
동 1114
 
2.2%
부 1108
 
2.2%
Other values (320) 33293
67.2%
None
ValueCountFrequency (%)
？ 1
100.0%

사용여부
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
True
2939 
False
2072 
ValueCountFrequency (%)
True 2939
58.7%
False 2072
41.3%
2023-12-13T02:48:01.774590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T02:48:00.130009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:48:00.206845image/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

부서코드부서명사용여부
031000000부산광역시Y
131000001변동자료갱신N
231000100시장실N
331000200부시장실N
431000250공보관실Y
531000255공보관실홍보담당관실N
631000260국제통상협력실N
731000270감사관Y
831000300정책기획실Y
931000305투자관리관실N
부서코드부서명사용여부
500177770014그린부산환경(주)Y
500299999999수산자원연구소 수산자원연구개발팀Y
5003D62611부산광역시(파견)N
5004D626110대기부서N
5005D626120기타 퇴직N
5006D626121기타 재활용창고N
5007D626122기타 교육청Y
5008D626126기타 시설관리공단N
5009D626129기타 부산광역시(파견)Y
5010V000092폐지부서Y