Overview

Dataset statistics

Number of variables8
Number of observations93
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory68.4 B

Variable types

Numeric3
Text2
Categorical2
DateTime1

Dataset

Description경상남도 내(부산진해경제자유구역청 관할 제외) 국제물류주선업 등록 업체에 관한 현황자료로 법인명, 상세주소, 최초등록일, 영업상태에 관한 정보를 제공합니다.
Author경상남도
URLhttps://www.data.go.kr/data/15088732/fileData.do

Alerts

연번 is highly overall correlated with 등록번호High correlation
등록번호 is highly overall correlated with 연번High correlation
우편번호 is highly overall correlated with 지자체High correlation
지자체 is highly overall correlated with 우편번호High correlation
구분 is highly imbalanced (91.4%)Imbalance
연번 has unique valuesUnique
등록번호 has unique valuesUnique
법인명 has unique valuesUnique
상세주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:37:40.339806
Analysis finished2024-03-14 10:37:43.407111
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size965.0 B
2024-03-14T19:37:43.553568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.6
Q124
median47
Q370
95-th percentile88.4
Maximum93
Range92
Interquartile range (IQR)46

Descriptive statistics

Standard deviation26.990739
Coefficient of variation (CV)0.57427105
Kurtosis-1.2
Mean47
Median Absolute Deviation (MAD)23
Skewness0
Sum4371
Variance728.5
MonotonicityStrictly increasing
2024-03-14T19:37:43.815201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%

등록번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.03226
Minimum4
Maximum174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size965.0 B
2024-03-14T19:37:44.056316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile16.2
Q171
median119
Q3150
95-th percentile169.4
Maximum174
Range170
Interquartile range (IQR)79

Descriptive statistics

Standard deviation49.635728
Coefficient of variation (CV)0.4637455
Kurtosis-0.85547475
Mean107.03226
Median Absolute Deviation (MAD)36
Skewness-0.54702347
Sum9954
Variance2463.7055
MonotonicityStrictly increasing
2024-03-14T19:37:44.434140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 1
 
1.1%
136 1
 
1.1%
149 1
 
1.1%
148 1
 
1.1%
147 1
 
1.1%
146 1
 
1.1%
145 1
 
1.1%
144 1
 
1.1%
140 1
 
1.1%
138 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
4 1
1.1%
5 1
1.1%
6 1
1.1%
9 1
1.1%
12 1
1.1%
19 1
1.1%
24 1
1.1%
25 1
1.1%
28 1
1.1%
29 1
1.1%
ValueCountFrequency (%)
174 1
1.1%
173 1
1.1%
172 1
1.1%
171 1
1.1%
170 1
1.1%
169 1
1.1%
168 1
1.1%
166 1
1.1%
165 1
1.1%
164 1
1.1%

법인명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
2024-03-14T19:37:45.333609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length8.7204301
Min length3

Characters and Unicode

Total characters811
Distinct characters152
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st row주식회사 신한상운
2nd row주식회사 지아이지
3rd row주식회사 윈윈종합물류
4th row거성해운앤엔지니어링 주식회사
5th row주식회사 천경
ValueCountFrequency (%)
주식회사 56
35.9%
엘 2
 
1.3%
㈜엠제이물류 1
 
0.6%
㈜신태양로직스 1
 
0.6%
이맥스㈜ 1
 
0.6%
㈜기현로지텍 1
 
0.6%
티엠로지스틱㈜ 1
 
0.6%
신화해운항공 1
 
0.6%
큰고을물류㈜ 1
 
0.6%
㈜다보물류 1
 
0.6%
Other values (90) 90
57.7%
2024-03-14T19:37:46.674414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
7.8%
사 59
 
7.3%
주 58
 
7.2%
회 57
 
7.0%
식 56
 
6.9%
스 43
 
5.3%
㈜ 33
 
4.1%
로 29
 
3.6%
물 24
 
3.0%
지 24
 
3.0%
Other values (142) 365
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 702
86.6%
Space Separator 63
 
7.8%
Other Symbol 33
 
4.1%
Uppercase Letter 6
 
0.7%
Close Punctuation 4
 
0.5%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 59
 
8.4%
주 58
 
8.3%
회 57
 
8.1%
식 56
 
8.0%
스 43
 
6.1%
로 29
 
4.1%
물 24
 
3.4%
지 24
 
3.4%
류 24
 
3.4%
에 13
 
1.9%
Other values (133) 315
44.9%
Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
J 1
16.7%
T 1
16.7%
S 1
16.7%
G 1
16.7%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 735
90.6%
Common 70
 
8.6%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 59
 
8.0%
주 58
 
7.9%
회 57
 
7.8%
식 56
 
7.6%
스 43
 
5.9%
㈜ 33
 
4.5%
로 29
 
3.9%
물 24
 
3.3%
지 24
 
3.3%
류 24
 
3.3%
Other values (134) 328
44.6%
Latin
ValueCountFrequency (%)
K 2
33.3%
J 1
16.7%
T 1
16.7%
S 1
16.7%
G 1
16.7%
Common
ValueCountFrequency (%)
63
90.0%
) 4
 
5.7%
( 3
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 702
86.6%
ASCII 76
 
9.4%
None 33
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
82.9%
) 4
 
5.3%
( 3
 
3.9%
K 2
 
2.6%
J 1
 
1.3%
T 1
 
1.3%
S 1
 
1.3%
G 1
 
1.3%
Hangul
ValueCountFrequency (%)
사 59
 
8.4%
주 58
 
8.3%
회 57
 
8.1%
식 56
 
8.0%
스 43
 
6.1%
로 29
 
4.1%
물 24
 
3.4%
지 24
 
3.4%
류 24
 
3.4%
에 13
 
1.9%
Other values (133) 315
44.9%
None
ValueCountFrequency (%)
㈜ 33
100.0%

지자체
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size872.0 B
창원시
37 
김해시
22 
양산시
16 
진주시
6 
거제시
 
3
Other values (5)
9 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 37
39.8%
김해시 22
23.7%
양산시 16
17.2%
진주시 6
 
6.5%
거제시 3
 
3.2%
사천시 2
 
2.2%
고성군 2
 
2.2%
함안군 2
 
2.2%
밀양시 2
 
2.2%
통영시 1
 
1.1%

Length

2024-03-14T19:37:46.896161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:37:47.089310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
창원시 37
39.8%
김해시 22
23.7%
양산시 16
17.2%
진주시 6
 
6.5%
거제시 3
 
3.2%
사천시 2
 
2.2%
고성군 2
 
2.2%
함안군 2
 
2.2%
밀양시 2
 
2.2%
통영시 1
 
1.1%

상세주소
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
2024-03-14T19:37:48.275325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length30
Mean length21.55914
Min length7

Characters and Unicode

Total characters2005
Distinct characters194
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

Unique93 ?
Unique (%)100.0%

Sample

1st row산막공단북8길 9(호계동 857)
2nd row상북면 수서로 223-40
3rd row의창구 차상로150번길 102, 216호(팔용동)
4th row마전9길 6(장승포동)
5th row물금읍 제방로 285
ValueCountFrequency (%)
의창구 10
 
2.9%
성산구 10
 
2.9%
진해구 8
 
2.3%
2층 5
 
1.4%
마산합포구 5
 
1.4%
물금읍 4
 
1.2%
마산회원구 4
 
1.2%
제방로 3
 
0.9%
주촌면 3
 
0.9%
북면 3
 
0.9%
Other values (268) 292
84.1%
2024-03-14T19:37:49.739527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
260
 
13.0%
1 105
 
5.2%
2 89
 
4.4%
로 77
 
3.8%
, 69
 
3.4%
동 65
 
3.2%
0 63
 
3.1%
) 56
 
2.8%
( 56
 
2.8%
3 48
 
2.4%
Other values (184) 1117
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1024
51.1%
Decimal Number 508
25.3%
Space Separator 260
 
13.0%
Other Punctuation 70
 
3.5%
Close Punctuation 56
 
2.8%
Open Punctuation 56
 
2.8%
Dash Punctuation 24
 
1.2%
Uppercase Letter 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 77
 
7.5%
동 65
 
6.3%
호 46
 
4.5%
산 42
 
4.1%
길 42
 
4.1%
구 40
 
3.9%
면 28
 
2.7%
번 27
 
2.6%
대 18
 
1.8%
성 18
 
1.8%
Other values (162) 621
60.6%
Decimal Number
ValueCountFrequency (%)
1 105
20.7%
2 89
17.5%
0 63
12.4%
3 48
9.4%
5 47
9.3%
4 44
8.7%
6 36
 
7.1%
9 29
 
5.7%
8 25
 
4.9%
7 22
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
T 1
14.3%
I 1
14.3%
D 1
14.3%
K 1
14.3%
S 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 69
98.6%
. 1
 
1.4%
Space Separator
ValueCountFrequency (%)
260
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1024
51.1%
Common 974
48.6%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 77
 
7.5%
동 65
 
6.3%
호 46
 
4.5%
산 42
 
4.1%
길 42
 
4.1%
구 40
 
3.9%
면 28
 
2.7%
번 27
 
2.6%
대 18
 
1.8%
성 18
 
1.8%
Other values (162) 621
60.6%
Common
ValueCountFrequency (%)
260
26.7%
1 105
10.8%
2 89
 
9.1%
, 69
 
7.1%
0 63
 
6.5%
) 56
 
5.7%
( 56
 
5.7%
3 48
 
4.9%
5 47
 
4.8%
4 44
 
4.5%
Other values (6) 137
14.1%
Latin
ValueCountFrequency (%)
A 2
28.6%
T 1
14.3%
I 1
14.3%
D 1
14.3%
K 1
14.3%
S 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1024
51.1%
ASCII 981
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
260
26.5%
1 105
10.7%
2 89
 
9.1%
, 69
 
7.0%
0 63
 
6.4%
) 56
 
5.7%
( 56
 
5.7%
3 48
 
4.9%
5 47
 
4.8%
4 44
 
4.5%
Other values (12) 144
14.7%
Hangul
ValueCountFrequency (%)
로 77
 
7.5%
동 65
 
6.3%
호 46
 
4.5%
산 42
 
4.1%
길 42
 
4.1%
구 40
 
3.9%
면 28
 
2.7%
번 27
 
2.6%
대 18
 
1.8%
성 18
 
1.8%
Other values (162) 621
60.6%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct83
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51368.656
Minimum50417
Maximum53323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size965.0 B
2024-03-14T19:37:50.097599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50417
5-th percentile50565.4
Q150853
median51321
Q351611
95-th percentile52871
Maximum53323
Range2906
Interquartile range (IQR)758

Descriptive statistics

Standard deviation721.58944
Coefficient of variation (CV)0.014047271
Kurtosis0.50986855
Mean51368.656
Median Absolute Deviation (MAD)399
Skewness1.0470904
Sum4777285
Variance520691.32
MonotonicityNot monotonic
2024-03-14T19:37:50.514805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50615 4
 
4.3%
51604 3
 
3.2%
50567 2
 
2.2%
51611 2
 
2.2%
51505 2
 
2.2%
51103 2
 
2.2%
51401 2
 
2.2%
50840 1
 
1.1%
51654 1
 
1.1%
51564 1
 
1.1%
Other values (73) 73
78.5%
ValueCountFrequency (%)
50417 1
1.1%
50467 1
1.1%
50503 1
1.1%
50541 1
1.1%
50563 1
1.1%
50567 2
2.2%
50568 1
1.1%
50573 1
1.1%
50583 1
1.1%
50591 1
1.1%
ValueCountFrequency (%)
53323 1
1.1%
53305 1
1.1%
53265 1
1.1%
52961 1
1.1%
52949 1
1.1%
52819 1
1.1%
52733 1
1.1%
52620 1
1.1%
52615 1
1.1%
52609 1
1.1%

최초등록일
Date

Distinct90
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size872.0 B
Minimum1987-11-04 00:00:00
Maximum2023-12-18 00:00:00
2024-03-14T19:37:51.116611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:51.547082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size872.0 B
정상
92 
휴업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
정상 92
98.9%
휴업 1
 
1.1%

Length

2024-03-14T19:37:51.943703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:37:52.239924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 92
98.9%
휴업 1
 
1.1%

Interactions

2024-03-14T19:37:42.247220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:40.995418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:41.705489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:42.383109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:41.221987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:41.941691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:42.537242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:41.468803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:37:42.100011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:37:52.428785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등록번호법인명지자체상세주소우편번호최초등록일구분
연번1.0000.9741.0000.0001.0000.0000.9880.094
등록번호0.9741.0001.0000.0001.0000.0000.9940.000
법인명1.0001.0001.0001.0001.0001.0001.0001.000
지자체0.0000.0001.0001.0001.0000.9420.0000.000
상세주소1.0001.0001.0001.0001.0001.0001.0001.000
우편번호0.0000.0001.0000.9421.0001.0000.0000.000
최초등록일0.9880.9941.0000.0001.0000.0001.0001.000
구분0.0940.0001.0000.0001.0000.0001.0001.000
2024-03-14T19:37:52.718241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지자체
구분1.0000.000
지자체0.0001.000
2024-03-14T19:37:52.956211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등록번호우편번호지자체구분
연번1.0001.0000.0500.0000.061
등록번호1.0001.0000.0500.0000.000
우편번호0.0500.0501.0000.7980.000
지자체0.0000.0000.7981.0000.000
구분0.0610.0000.0000.0001.000

Missing values

2024-03-14T19:37:42.801896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:37:43.233829image/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

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349거성해운앤엔지니어링 주식회사거제시마전9길 6(장승포동)533232002-02-20정상
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8384164아라로지스 주식회사김해시월산로 82-58, 2층 203호(부곡동, 대동아파트상가)509812022-11-14정상
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