Overview

Dataset statistics

Number of variables5
Number of observations81
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory42.6 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description경상남도 내(부산진해경제자유구역청 관할 제외) 국제물류주선업 등록 업체에 관한 현황자료로 법인명, 상세주소, 최초등록일, 영업상태에 관한 정보를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15088732

Alerts

Unnamed: 4 has 1 (1.2%) missing valuesMissing
등록번호 has unique valuesUnique
업 체 명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:25:56.058225
Analysis finished2023-12-11 00:25:56.810059
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Real number (ℝ)

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-11T09:25:56.887782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q121
median41
Q361
95-th percentile77
Maximum81
Range80
Interquartile range (IQR)40

Descriptive statistics

Standard deviation23.526581
Coefficient of variation (CV)0.57381904
Kurtosis-1.2
Mean41
Median Absolute Deviation (MAD)20
Skewness0
Sum3321
Variance553.5
MonotonicityStrictly increasing
2023-12-11T09:25:57.024674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
62 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%

업 체 명
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-11T09:25:57.511053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.382716
Min length3

Characters and Unicode

Total characters517
Distinct characters130
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row(주)신한상운
2nd row(주)지아이지
3rd row(주)윈윈종합물류
4th row거성해운(주)
5th row(주)지티씨
ValueCountFrequency (%)
주)신한상운 1
 
1.2%
㈜네오맥스 1
 
1.2%
㈜진현로직스 1
 
1.2%
㈜진아 1
 
1.2%
㈜미래종합물류 1
 
1.2%
㈜부영씨엔티 1
 
1.2%
㈜창성물류 1
 
1.2%
㈜푸르미르 1
 
1.2%
하나지엘에스㈜ 1
 
1.2%
㈜미래중량 1
 
1.2%
Other values (72) 72
87.8%
2023-12-11T09:25:57.876878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 66
 
12.8%
스 40
 
7.7%
로 27
 
5.2%
지 23
 
4.4%
물 22
 
4.3%
류 21
 
4.1%
( 15
 
2.9%
) 15
 
2.9%
주 15
 
2.9%
에 10
 
1.9%
Other values (120) 263
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 420
81.2%
Other Symbol 66
 
12.8%
Open Punctuation 15
 
2.9%
Close Punctuation 15
 
2.9%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 40
 
9.5%
로 27
 
6.4%
지 23
 
5.5%
물 22
 
5.2%
류 21
 
5.0%
주 15
 
3.6%
에 10
 
2.4%
티 9
 
2.1%
틱 8
 
1.9%
이 8
 
1.9%
Other values (116) 237
56.4%
Other Symbol
ValueCountFrequency (%)
㈜ 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 486
94.0%
Common 31
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 66
 
13.6%
스 40
 
8.2%
로 27
 
5.6%
지 23
 
4.7%
물 22
 
4.5%
류 21
 
4.3%
주 15
 
3.1%
에 10
 
2.1%
티 9
 
1.9%
틱 8
 
1.6%
Other values (117) 245
50.4%
Common
ValueCountFrequency (%)
( 15
48.4%
) 15
48.4%
1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
81.2%
None 66
 
12.8%
ASCII 31
 
6.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 66
100.0%
Hangul
ValueCountFrequency (%)
스 40
 
9.5%
로 27
 
6.4%
지 23
 
5.5%
물 22
 
5.2%
류 21
 
5.0%
주 15
 
3.6%
에 10
 
2.4%
티 9
 
2.1%
틱 8
 
1.9%
이 8
 
1.9%
Other values (116) 237
56.4%
ASCII
ValueCountFrequency (%)
( 15
48.4%
) 15
48.4%
1
 
3.2%

대표자
Text

Distinct80
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-11T09:25:58.141791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0987654
Min length3

Characters and Unicode

Total characters251
Distinct characters96
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)97.5%

Sample

1st row마성훈
2nd row김기운
3rd row김정하
4th row원경희
5th row배기중
ValueCountFrequency (%)
김정하 2
 
2.4%
김현영 1
 
1.2%
최병희 1
 
1.2%
김은지 1
 
1.2%
김지용 1
 
1.2%
장수진 1
 
1.2%
신상길 1
 
1.2%
이주희 1
 
1.2%
조영민 1
 
1.2%
박상준 1
 
1.2%
Other values (71) 71
86.6%
2023-12-11T09:25:58.624472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 22
 
8.8%
이 10
 
4.0%
성 9
 
3.6%
상 9
 
3.6%
희 8
 
3.2%
재 7
 
2.8%
진 7
 
2.8%
현 6
 
2.4%
최 6
 
2.4%
박 6
 
2.4%
Other values (86) 161
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 248
98.8%
Other Punctuation 2
 
0.8%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 22
 
8.9%
이 10
 
4.0%
성 9
 
3.6%
상 9
 
3.6%
희 8
 
3.2%
재 7
 
2.8%
진 7
 
2.8%
현 6
 
2.4%
최 6
 
2.4%
박 6
 
2.4%
Other values (84) 158
63.7%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 248
98.8%
Common 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 22
 
8.9%
이 10
 
4.0%
성 9
 
3.6%
상 9
 
3.6%
희 8
 
3.2%
재 7
 
2.8%
진 7
 
2.8%
현 6
 
2.4%
최 6
 
2.4%
박 6
 
2.4%
Other values (84) 158
63.7%
Common
ValueCountFrequency (%)
, 2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 248
98.8%
ASCII 3
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 22
 
8.9%
이 10
 
4.0%
성 9
 
3.6%
상 9
 
3.6%
희 8
 
3.2%
재 7
 
2.8%
진 7
 
2.8%
현 6
 
2.4%
최 6
 
2.4%
박 6
 
2.4%
Other values (84) 158
63.7%
ASCII
ValueCountFrequency (%)
, 2
66.7%
1
33.3%

지자체
Categorical

Distinct10
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size780.0 B
창원시
33 
양산시
18 
김해시
13 
거제시
4 
고성군
 
3
Other values (5)
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st row양산시
2nd row양산시
3rd row창원시
4th row거제시
5th row양산시

Common Values

ValueCountFrequency (%)
창원시 33
40.7%
양산시 18
22.2%
김해시 13
 
16.0%
거제시 4
 
4.9%
고성군 3
 
3.7%
통영시 3
 
3.7%
진주시 3
 
3.7%
함안군 2
 
2.5%
사천시 1
 
1.2%
밀양시 1
 
1.2%

Length

2023-12-11T09:25:58.760555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:25:58.909991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창원시 33
40.7%
양산시 18
22.2%
김해시 13
 
16.0%
거제시 4
 
4.9%
고성군 3
 
3.7%
통영시 3
 
3.7%
진주시 3
 
3.7%
함안군 2
 
2.5%
사천시 1
 
1.2%
밀양시 1
 
1.2%

Unnamed: 4
Text

MISSING 

Distinct79
Distinct (%)98.8%
Missing1
Missing (%)1.2%
Memory size780.0 B
2023-12-11T09:25:59.203808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length21.4375
Min length8

Characters and Unicode

Total characters1715
Distinct characters192
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

Unique78 ?
Unique (%)97.5%

Sample

1st row산막공단북8길 9(호계동 857)
2nd row상북면 수서로 223-40
3rd row의창구 차상로150번길 102, 216호(팔용동)
4th row마전9길 6(장승포동)
5th row물금읍 제방로 225
ValueCountFrequency (%)
진해구 11
 
3.7%
의창구 10
 
3.3%
성산구 5
 
1.7%
물금읍 4
 
1.3%
동면 4
 
1.3%
마산회원구 4
 
1.3%
2층 3
 
1.0%
225 3
 
1.0%
북면 3
 
1.0%
마산합포구 3
 
1.0%
Other values (227) 251
83.4%
2023-12-11T09:25:59.694644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
 
13.0%
1 97
 
5.7%
2 76
 
4.4%
로 61
 
3.6%
동 61
 
3.6%
, 57
 
3.3%
0 52
 
3.0%
( 46
 
2.7%
) 46
 
2.7%
4 44
 
2.6%
Other values (182) 952
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 889
51.8%
Decimal Number 432
25.2%
Space Separator 223
 
13.0%
Other Punctuation 57
 
3.3%
Open Punctuation 46
 
2.7%
Close Punctuation 46
 
2.7%
Dash Punctuation 19
 
1.1%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 61
 
6.9%
동 61
 
6.9%
길 37
 
4.2%
구 34
 
3.8%
호 34
 
3.8%
산 26
 
2.9%
면 26
 
2.9%
번 20
 
2.2%
해 17
 
1.9%
용 17
 
1.9%
Other values (164) 556
62.5%
Decimal Number
ValueCountFrequency (%)
1 97
22.5%
2 76
17.6%
0 52
12.0%
4 44
10.2%
3 43
10.0%
5 38
 
8.8%
6 24
 
5.6%
8 22
 
5.1%
9 19
 
4.4%
7 17
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
A 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
223
100.0%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 889
51.8%
Common 823
48.0%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 61
 
6.9%
동 61
 
6.9%
길 37
 
4.2%
구 34
 
3.8%
호 34
 
3.8%
산 26
 
2.9%
면 26
 
2.9%
번 20
 
2.2%
해 17
 
1.9%
용 17
 
1.9%
Other values (164) 556
62.5%
Common
ValueCountFrequency (%)
223
27.1%
1 97
11.8%
2 76
 
9.2%
, 57
 
6.9%
0 52
 
6.3%
( 46
 
5.6%
) 46
 
5.6%
4 44
 
5.3%
3 43
 
5.2%
5 38
 
4.6%
Other values (5) 101
12.3%
Latin
ValueCountFrequency (%)
S 1
33.3%
A 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 889
51.8%
ASCII 826
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
27.0%
1 97
11.7%
2 76
 
9.2%
, 57
 
6.9%
0 52
 
6.3%
( 46
 
5.6%
) 46
 
5.6%
4 44
 
5.3%
3 43
 
5.2%
5 38
 
4.6%
Other values (8) 104
12.6%
Hangul
ValueCountFrequency (%)
로 61
 
6.9%
동 61
 
6.9%
길 37
 
4.2%
구 34
 
3.8%
호 34
 
3.8%
산 26
 
2.9%
면 26
 
2.9%
번 20
 
2.2%
해 17
 
1.9%
용 17
 
1.9%
Other values (164) 556
62.5%

Interactions

2023-12-11T09:25:56.597759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:25:59.826586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호업 체 명대표자지자체Unnamed: 4
등록번호1.0001.0000.9520.0001.000
업 체 명1.0001.0001.0001.0001.000
대표자0.9521.0001.0001.0000.999
지자체0.0001.0001.0001.0001.000
Unnamed: 41.0001.0000.9991.0001.000
2023-12-11T09:25:59.930832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호지자체
등록번호1.0000.000
지자체0.0001.000

Missing values

2023-12-11T09:25:56.691079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:25:56.780970image/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

등록번호업 체 명대표자지자체Unnamed: 4
01(주)신한상운마성훈양산시산막공단북8길 9(호계동 857)
12(주)지아이지김기운양산시상북면 수서로 223-40
23(주)윈윈종합물류김정하창원시의창구 차상로150번길 102, 216호(팔용동)
34거성해운(주)원경희거제시마전9길 6(장승포동)
45(주)지티씨배기중양산시물금읍 제방로 225
56(주)천경서성훈양산시물금읍 제방로 225
67(주)엘에스엘조정근창원시마산회원구 무역로32(양덕동)
78㈜신현강태목거제시거제시 용소1길105, 비동 4층(아주동, 칸빌딩)
89삼화로지스틱(주)서경규창원시마산합포구 드림베이대로 201, 301호(가포동)
910위더스글로벌로지스(주)김광현창원시마산합포구 월영동서로7, 3층(해운동, 새마을회관빌딩)
등록번호업 체 명대표자지자체Unnamed: 4
7172㈜늘푸른물류김헌석양산시상북면 양산대로1354,2층(소토리)
7273㈜엠제이물류김순아김해시생림면 안양로 72-28
7374㈜디씨티로직스문상헌창원시진해구 용원중로25번길 6-22, 102호
7475㈜신항특수로직스심청화창원시진해구 신항2로 114, 5층 533(용원동)
7576㈜케이원 로지스최선동김해시식만로 358(불암동)
7677(유)신진로지스이진우,이선영창원시진해구 신항10로 16, 디더블유국제물류센터내 1층(남문동)
7778㈜비티에프로지스틱스한명수창원시진해구 신항8로 104(남문동)
7879㈜명진물류넷김미숙창원시진해구 용재로3번길 23, 201호(용원동, 다복빌딩)
7980㈜다보물류백유성창원시진해구 신항2로 106, 11층 1140호(용원동, 다인로얄팰리스부산신항1차)
8081큰고을물류㈜이병옥진주시대곡면 단목길7번길37-21