Overview

Dataset statistics

Number of variables4
Number of observations88
Missing cells7
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory34.5 B

Variable types

Numeric1
Text3

Dataset

Description진주시 소재 화물운송주선업체(이사업체) 현황(업체명, 주소, 연락처)에 대한 데이터 88건을 csv 형태로 제공합니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15005184

Alerts

전화번호 has 7 (8.0%) missing valuesMissing
연번 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:17:16.664267
Analysis finished2023-12-11 00:17:17.155566
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.5
Minimum1
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size924.0 B
2023-12-11T09:17:17.226326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.35
Q122.75
median44.5
Q366.25
95-th percentile83.65
Maximum88
Range87
Interquartile range (IQR)43.5

Descriptive statistics

Standard deviation25.547342
Coefficient of variation (CV)0.57409757
Kurtosis-1.2
Mean44.5
Median Absolute Deviation (MAD)22
Skewness0
Sum3916
Variance652.66667
MonotonicityStrictly increasing
2023-12-11T09:17:17.348173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
46 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
Other values (78) 78
88.6%
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 (%)
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%
79 1
1.1%

업체명
Text

UNIQUE 

Distinct88
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-11T09:17:17.640262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.8295455
Min length2

Characters and Unicode

Total characters601
Distinct characters145
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

Unique88 ?
Unique (%)100.0%

Sample

1st row(주)거산종합물류
2nd row(주)계원물류
3rd row(주)남영운수
4th row(주)로지스퀘어 진주지점
5th row(주)미광산업
ValueCountFrequency (%)
익스프레스 2
 
2.2%
주)거산종합물류 1
 
1.1%
신행운익스프레스 1
 
1.1%
일신로지스(주 1
 
1.1%
원포장이사 1
 
1.1%
원강 1
 
1.1%
우창상사 1
 
1.1%
용현화물 1
 
1.1%
완벽익스프레스 1
 
1.1%
아줌마화물 1
 
1.1%
Other values (82) 82
88.2%
2023-12-11T09:17:17.979585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 63
 
10.5%
주 39
 
6.5%
물 32
 
5.3%
익 27
 
4.5%
프 27
 
4.5%
( 26
 
4.3%
) 26
 
4.3%
레 26
 
4.3%
류 20
 
3.3%
진 16
 
2.7%
Other values (135) 299
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 536
89.2%
Open Punctuation 26
 
4.3%
Close Punctuation 26
 
4.3%
Space Separator 5
 
0.8%
Uppercase Letter 5
 
0.8%
Decimal Number 2
 
0.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 63
 
11.8%
주 39
 
7.3%
물 32
 
6.0%
익 27
 
5.0%
프 27
 
5.0%
레 26
 
4.9%
류 20
 
3.7%
진 16
 
3.0%
화 13
 
2.4%
이 12
 
2.2%
Other values (124) 261
48.7%
Uppercase Letter
ValueCountFrequency (%)
G 1
20.0%
K 1
20.0%
H 1
20.0%
D 1
20.0%
B 1
20.0%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 536
89.2%
Common 60
 
10.0%
Latin 5
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 63
 
11.8%
주 39
 
7.3%
물 32
 
6.0%
익 27
 
5.0%
프 27
 
5.0%
레 26
 
4.9%
류 20
 
3.7%
진 16
 
3.0%
화 13
 
2.4%
이 12
 
2.2%
Other values (124) 261
48.7%
Common
ValueCountFrequency (%)
( 26
43.3%
) 26
43.3%
5
 
8.3%
4 1
 
1.7%
2 1
 
1.7%
- 1
 
1.7%
Latin
ValueCountFrequency (%)
G 1
20.0%
K 1
20.0%
H 1
20.0%
D 1
20.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 536
89.2%
ASCII 65
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 63
 
11.8%
주 39
 
7.3%
물 32
 
6.0%
익 27
 
5.0%
프 27
 
5.0%
레 26
 
4.9%
류 20
 
3.7%
진 16
 
3.0%
화 13
 
2.4%
이 12
 
2.2%
Other values (124) 261
48.7%
ASCII
ValueCountFrequency (%)
( 26
40.0%
) 26
40.0%
5
 
7.7%
G 1
 
1.5%
K 1
 
1.5%
H 1
 
1.5%
D 1
 
1.5%
4 1
 
1.5%
2 1
 
1.5%
B 1
 
1.5%

소재지
Text

Distinct78
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size836.0 B
2023-12-11T09:17:18.267171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length26.147727
Min length20

Characters and Unicode

Total characters2301
Distinct characters122
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)83.0%

Sample

1st row경상남도 진주시 문산읍 동부로 802
2nd row경상남도 진주시 금산면 월아산로 1911
3rd row경상남도 진주시 미천면 향양로 416
4th row경상남도 진주시 신평공원길47번길 10-5 (평거동)
5th row경상남도 진주시 집현면 남강로 1819-6
ValueCountFrequency (%)
경상남도 88
 
18.6%
진주시 88
 
18.6%
상대동 13
 
2.7%
상봉동 13
 
2.7%
도동로 11
 
2.3%
131 11
 
2.3%
문산읍 8
 
1.7%
이현동 6
 
1.3%
1층 5
 
1.1%
충무공동 5
 
1.1%
Other values (162) 225
47.6%
2023-12-11T09:17:18.689423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
385
 
16.7%
상 124
 
5.4%
1 111
 
4.8%
진 104
 
4.5%
주 101
 
4.4%
도 100
 
4.3%
동 96
 
4.2%
남 91
 
4.0%
경 90
 
3.9%
시 88
 
3.8%
Other values (112) 1011
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1351
58.7%
Space Separator 385
 
16.7%
Decimal Number 382
 
16.6%
Open Punctuation 68
 
3.0%
Close Punctuation 68
 
3.0%
Other Punctuation 22
 
1.0%
Dash Punctuation 20
 
0.9%
Uppercase Letter 4
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 124
 
9.2%
진 104
 
7.7%
주 101
 
7.5%
도 100
 
7.4%
동 96
 
7.1%
남 91
 
6.7%
경 90
 
6.7%
시 88
 
6.5%
로 83
 
6.1%
길 46
 
3.4%
Other values (94) 428
31.7%
Decimal Number
ValueCountFrequency (%)
1 111
29.1%
2 51
13.4%
3 47
12.3%
0 33
 
8.6%
6 28
 
7.3%
5 27
 
7.1%
9 25
 
6.5%
4 21
 
5.5%
7 20
 
5.2%
8 19
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
A 2
50.0%
Space Separator
ValueCountFrequency (%)
385
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1351
58.7%
Common 945
41.1%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 124
 
9.2%
진 104
 
7.7%
주 101
 
7.5%
도 100
 
7.4%
동 96
 
7.1%
남 91
 
6.7%
경 90
 
6.7%
시 88
 
6.5%
로 83
 
6.1%
길 46
 
3.4%
Other values (94) 428
31.7%
Common
ValueCountFrequency (%)
385
40.7%
1 111
 
11.7%
( 68
 
7.2%
) 68
 
7.2%
2 51
 
5.4%
3 47
 
5.0%
0 33
 
3.5%
6 28
 
3.0%
5 27
 
2.9%
9 25
 
2.6%
Other values (5) 102
 
10.8%
Latin
ValueCountFrequency (%)
B 2
40.0%
A 2
40.0%
g 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1351
58.7%
ASCII 950
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
385
40.5%
1 111
 
11.7%
( 68
 
7.2%
) 68
 
7.2%
2 51
 
5.4%
3 47
 
4.9%
0 33
 
3.5%
6 28
 
2.9%
5 27
 
2.8%
9 25
 
2.6%
Other values (8) 107
 
11.3%
Hangul
ValueCountFrequency (%)
상 124
 
9.2%
진 104
 
7.7%
주 101
 
7.5%
도 100
 
7.4%
동 96
 
7.1%
남 91
 
6.7%
경 90
 
6.7%
시 88
 
6.5%
로 83
 
6.1%
길 46
 
3.4%
Other values (94) 428
31.7%

전화번호
Text

MISSING 

Distinct80
Distinct (%)98.8%
Missing7
Missing (%)8.0%
Memory size836.0 B
2023-12-11T09:17:18.930617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.987654
Min length9

Characters and Unicode

Total characters971
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

Unique79 ?
Unique (%)97.5%

Sample

1st row055-763-7711
2nd row055-752-4433
3rd row055-752-5325
4th row055-756-5533
5th row055-761-0305
ValueCountFrequency (%)
055-921-3182 2
 
2.5%
055-761-2482 1
 
1.2%
055-763-7711 1
 
1.2%
055-759-2300 1
 
1.2%
055-761-9871 1
 
1.2%
055-755-4708 1
 
1.2%
055-743-3600 1
 
1.2%
055-972-7024 1
 
1.2%
055-757-6062 1
 
1.2%
055-753-2424 1
 
1.2%
Other values (70) 70
86.4%
2023-12-11T09:17:19.284734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 222
22.9%
- 161
16.6%
0 144
14.8%
7 117
12.0%
4 72
 
7.4%
2 71
 
7.3%
1 47
 
4.8%
3 44
 
4.5%
8 37
 
3.8%
6 35
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 810
83.4%
Dash Punctuation 161
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 222
27.4%
0 144
17.8%
7 117
14.4%
4 72
 
8.9%
2 71
 
8.8%
1 47
 
5.8%
3 44
 
5.4%
8 37
 
4.6%
6 35
 
4.3%
9 21
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 971
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 222
22.9%
- 161
16.6%
0 144
14.8%
7 117
12.0%
4 72
 
7.4%
2 71
 
7.3%
1 47
 
4.8%
3 44
 
4.5%
8 37
 
3.8%
6 35
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 971
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 222
22.9%
- 161
16.6%
0 144
14.8%
7 117
12.0%
4 72
 
7.4%
2 71
 
7.3%
1 47
 
4.8%
3 44
 
4.5%
8 37
 
3.8%
6 35
 
3.6%

Interactions

2023-12-11T09:17:16.959937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:17:19.386631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명소재지전화번호
연번1.0001.0000.7711.000
업체명1.0001.0001.0001.000
소재지0.7711.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2023-12-11T09:17:17.052155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:17:17.125399image/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

연번업체명소재지전화번호
01(주)거산종합물류경상남도 진주시 문산읍 동부로 802055-763-7711
12(주)계원물류경상남도 진주시 금산면 월아산로 1911055-752-4433
23(주)남영운수경상남도 진주시 미천면 향양로 416055-752-5325
34(주)로지스퀘어 진주지점경상남도 진주시 신평공원길47번길 10-5 (평거동)055-756-5533
45(주)미광산업경상남도 진주시 집현면 남강로 1819-6055-761-0305
56(주)부민화물경상남도 진주시 범골로54번길 30-9, B동 1102호 (충무공동)055-757-7557
67(주)승진 진주영업소경상남도 진주시 동부로169번길 12, A1805호 (충무공동)061-652-6671
78(주)신용종합물류경상남도 진주시 문산읍 동부로326번길 11055-758-6161
89(주)신화종합물류경상남도 진주시 도동로 131 (상대동)055-762-2600
910(주)에스에이물류경상남도 진주시 초전북로61번길 25-6, 102호 (초전동)031-901-2007
연번업체명소재지전화번호
7879하나화물경상남도 진주시 진양호로626번길 17 (옥봉동)<NA>
7980하모포장이사경상남도 진주시 창렬로161번길 5, 1층 (상봉동)055-748-2411
8081하이익스프레스경상남도 진주시 진주성로 127 (상봉동)055-743-1234
8182한국물류경상남도 진주시 범골로54번길 30-9, B동 904호 (충무공동)<NA>
8283한국익스프레스경상남도 진주시 신안로100번길 12 (신안동)055-748-2900
8384행복익스프레스경상남도 진주시 진주대로404번길 17-3 (가좌동)<NA>
8485행운익스프레스경상남도 진주시 모덕로294번길 3 (하대동)055-757-9000
8586현대익스프레스경상남도 진주시 의병로80번길 3 (상봉동)055-742-8700
8687황소트랜스경상남도 진주시 평거로39번길 17, 들말한보아파트 상가동 114호055-747-3737
8788흥진종합물류(주)경상남도 진주시 도동로 131, 1층 (상대동, 진주화물터미널)055-761-3103