Overview

Dataset statistics

Number of variables6
Number of observations48
Missing cells14
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory51.8 B

Variable types

Numeric1
Text5

Dataset

Description2023년 화물운송사업자 현황으로 운송사업자명, 대표자명, 주소, 전화번호 등 일반현황을 소개하는 데이터 입니다.
URLhttps://www.data.go.kr/data/15115341/fileData.do

Alerts

전화번호 has 2 (4.2%) missing valuesMissing
FAX has 12 (25.0%) missing valuesMissing
연번 has unique valuesUnique
업 체 명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:39:37.145277
Analysis finished2023-12-12 13:39:38.018445
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T22:39:38.107039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q112.75
median24.5
Q336.25
95-th percentile45.65
Maximum48
Range47
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation14
Coefficient of variation (CV)0.57142857
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)12
Skewness0
Sum1176
Variance196
MonotonicityStrictly increasing
2023-12-12T22:39:38.284955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
35 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
48 1
2.1%
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%

업 체 명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-12T22:39:38.600067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.3958333
Min length3

Characters and Unicode

Total characters307
Distinct characters100
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

Unique48 ?
Unique (%)100.0%

Sample

1st row금사특수레카
2nd row대양티앤티에스
3rd row㈜미성콘테이너
4th row혁성운수㈜
5th row부산시연료운수㈜
ValueCountFrequency (%)
금사특수레카 1
 
2.0%
대륙견인운수 1
 
2.0%
하남운수㈜ 1
 
2.0%
유)대양특수 1
 
2.0%
범창화물㈜ 1
 
2.0%
세아로직스㈜ 1
 
2.0%
주)세중종합물류 1
 
2.0%
거양특수레카 1
 
2.0%
유)카라바로지스틱스 1
 
2.0%
상호물류㈜ 1
 
2.0%
Other values (39) 39
79.6%
2023-12-12T22:39:39.065589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 38
 
12.4%
스 20
 
6.5%
운 15
 
4.9%
로 13
 
4.2%
수 11
 
3.6%
물 11
 
3.6%
류 9
 
2.9%
지 8
 
2.6%
대 7
 
2.3%
특 6
 
2.0%
Other values (90) 169
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
83.1%
Other Symbol 38
 
12.4%
Open Punctuation 6
 
2.0%
Close Punctuation 6
 
2.0%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 20
 
7.8%
운 15
 
5.9%
로 13
 
5.1%
수 11
 
4.3%
물 11
 
4.3%
류 9
 
3.5%
지 8
 
3.1%
대 7
 
2.7%
특 6
 
2.4%
직 6
 
2.4%
Other values (86) 149
58.4%
Other Symbol
ValueCountFrequency (%)
㈜ 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
95.4%
Common 14
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 38
 
13.0%
스 20
 
6.8%
운 15
 
5.1%
로 13
 
4.4%
수 11
 
3.8%
물 11
 
3.8%
류 9
 
3.1%
지 8
 
2.7%
대 7
 
2.4%
특 6
 
2.0%
Other values (87) 155
52.9%
Common
ValueCountFrequency (%)
( 6
42.9%
) 6
42.9%
2
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
83.1%
None 38
 
12.4%
ASCII 14
 
4.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 38
100.0%
Hangul
ValueCountFrequency (%)
스 20
 
7.8%
운 15
 
5.9%
로 13
 
5.1%
수 11
 
4.3%
물 11
 
4.3%
류 9
 
3.5%
지 8
 
3.1%
대 7
 
2.7%
특 6
 
2.4%
직 6
 
2.4%
Other values (86) 149
58.4%
ASCII
ValueCountFrequency (%)
( 6
42.9%
) 6
42.9%
2
 
14.3%

대표자
Text

Distinct35
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-12T22:39:39.293569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters144
Distinct characters44
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)58.3%

Sample

1st row서*순
2nd row송*훈
3rd row김*원
4th row강*혁
5th row강*우
ValueCountFrequency (%)
강*혁 5
 
10.4%
강*우 5
 
10.4%
황*영 2
 
4.2%
김*주 2
 
4.2%
김*규 2
 
4.2%
장*현 2
 
4.2%
김*용 2
 
4.2%
정*진 1
 
2.1%
박*배 1
 
2.1%
고*나 1
 
2.1%
Other values (25) 25
52.1%
2023-12-12T22:39:39.610162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 48
33.3%
김 15
 
10.4%
강 13
 
9.0%
우 6
 
4.2%
혁 5
 
3.5%
이 4
 
2.8%
박 3
 
2.1%
규 3
 
2.1%
정 3
 
2.1%
영 2
 
1.4%
Other values (34) 42
29.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 96
66.7%
Other Punctuation 48
33.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 15
 
15.6%
강 13
 
13.5%
우 6
 
6.2%
혁 5
 
5.2%
이 4
 
4.2%
박 3
 
3.1%
규 3
 
3.1%
정 3
 
3.1%
영 2
 
2.1%
장 2
 
2.1%
Other values (33) 40
41.7%
Other Punctuation
ValueCountFrequency (%)
* 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 96
66.7%
Common 48
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 15
 
15.6%
강 13
 
13.5%
우 6
 
6.2%
혁 5
 
5.2%
이 4
 
4.2%
박 3
 
3.1%
규 3
 
3.1%
정 3
 
3.1%
영 2
 
2.1%
장 2
 
2.1%
Other values (33) 40
41.7%
Common
ValueCountFrequency (%)
* 48
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 96
66.7%
ASCII 48
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 48
100.0%
Hangul
ValueCountFrequency (%)
김 15
 
15.6%
강 13
 
13.5%
우 6
 
6.2%
혁 5
 
5.2%
이 4
 
4.2%
박 3
 
3.1%
규 3
 
3.1%
정 3
 
3.1%
영 2
 
2.1%
장 2
 
2.1%
Other values (33) 40
41.7%

주 사 무 소
Text

Distinct38
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-12T22:39:39.857642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length30
Mean length24.5625
Min length14

Characters and Unicode

Total characters1179
Distinct characters103
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

Unique35 ?
Unique (%)72.9%

Sample

1st row해운대구 선수촌로 125(반여동)
2nd row해운대구 센텀중앙로 48,1507호(우동,에이스하이테크21)
3rd row해운대구 마린시티3로 1, 527호(우동,선프라자)
4th row해운대구 재반로 57-14(재송동)
5th row해운대구 재반로 57-14(재송동)
ValueCountFrequency (%)
해운대구 27
 
15.4%
재반로 14
 
8.0%
57-14(재송동 11
 
6.3%
센텀중앙로 5
 
2.9%
해운대로 5
 
2.9%
마린시티3로 5
 
2.9%
26 5
 
2.9%
한화꿈에그린센텀 3
 
1.7%
1 3
 
1.7%
센텀동로 3
 
1.7%
Other values (80) 94
53.7%
2023-12-12T22:39:40.233538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
10.8%
동 58
 
4.9%
, 54
 
4.6%
) 50
 
4.2%
로 48
 
4.1%
( 47
 
4.0%
1 45
 
3.8%
2 42
 
3.6%
대 41
 
3.5%
운 40
 
3.4%
Other values (93) 627
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 634
53.8%
Decimal Number 246
 
20.9%
Space Separator 127
 
10.8%
Other Punctuation 56
 
4.7%
Close Punctuation 50
 
4.2%
Open Punctuation 47
 
4.0%
Dash Punctuation 13
 
1.1%
Uppercase Letter 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 58
 
9.1%
로 48
 
7.6%
대 41
 
6.5%
운 40
 
6.3%
해 38
 
6.0%
재 33
 
5.2%
구 29
 
4.6%
송 23
 
3.6%
텀 22
 
3.5%
센 22
 
3.5%
Other values (73) 280
44.2%
Decimal Number
ValueCountFrequency (%)
1 45
18.3%
2 42
17.1%
4 33
13.4%
3 25
10.2%
0 24
9.8%
5 23
9.3%
7 22
8.9%
9 15
 
6.1%
6 12
 
4.9%
8 5
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
C 1
 
16.7%
E 1
 
16.7%
P 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
, 54
96.4%
@ 2
 
3.6%
Space Separator
ValueCountFrequency (%)
127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 634
53.8%
Common 539
45.7%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 58
 
9.1%
로 48
 
7.6%
대 41
 
6.5%
운 40
 
6.3%
해 38
 
6.0%
재 33
 
5.2%
구 29
 
4.6%
송 23
 
3.6%
텀 22
 
3.5%
센 22
 
3.5%
Other values (73) 280
44.2%
Common
ValueCountFrequency (%)
127
23.6%
, 54
10.0%
) 50
 
9.3%
( 47
 
8.7%
1 45
 
8.3%
2 42
 
7.8%
4 33
 
6.1%
3 25
 
4.6%
0 24
 
4.5%
5 23
 
4.3%
Other values (6) 69
12.8%
Latin
ValueCountFrequency (%)
A 3
50.0%
C 1
 
16.7%
E 1
 
16.7%
P 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 634
53.8%
ASCII 545
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
23.3%
, 54
9.9%
) 50
 
9.2%
( 47
 
8.6%
1 45
 
8.3%
2 42
 
7.7%
4 33
 
6.1%
3 25
 
4.6%
0 24
 
4.4%
5 23
 
4.2%
Other values (10) 75
13.8%
Hangul
ValueCountFrequency (%)
동 58
 
9.1%
로 48
 
7.6%
대 41
 
6.5%
운 40
 
6.3%
해 38
 
6.0%
재 33
 
5.2%
구 29
 
4.6%
송 23
 
3.6%
텀 22
 
3.5%
센 22
 
3.5%
Other values (73) 280
44.2%

전화번호
Text

MISSING 

Distinct38
Distinct (%)82.6%
Missing2
Missing (%)4.2%
Memory size516.0 B
2023-12-12T22:39:40.468367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.130435
Min length11

Characters and Unicode

Total characters558
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)69.6%

Sample

1st row051-525-0071
2nd row051-742-5711
3rd row051-742-6446
4th row051-784-6747
5th row051-783-2700
ValueCountFrequency (%)
051-784-3300 3
 
6.5%
051-898-0656 3
 
6.5%
051-784-6747 2
 
4.3%
051-704-7022 2
 
4.3%
051-503-5079 2
 
4.3%
051-781-6800 2
 
4.3%
051-975-1134 1
 
2.2%
051-668-6921 1
 
2.2%
051-622-4758 1
 
2.2%
051-714-1945 1
 
2.2%
Other values (28) 28
60.9%
2023-12-12T22:39:40.809261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 92
16.5%
0 87
15.6%
1 84
15.1%
5 71
12.7%
7 45
8.1%
4 40
7.2%
8 32
 
5.7%
6 31
 
5.6%
2 28
 
5.0%
9 24
 
4.3%
Other values (3) 24
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 462
82.8%
Dash Punctuation 92
 
16.5%
Math Symbol 3
 
0.5%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87
18.8%
1 84
18.2%
5 71
15.4%
7 45
9.7%
4 40
8.7%
8 32
 
6.9%
6 31
 
6.7%
2 28
 
6.1%
9 24
 
5.2%
3 20
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 558
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 92
16.5%
0 87
15.6%
1 84
15.1%
5 71
12.7%
7 45
8.1%
4 40
7.2%
8 32
 
5.7%
6 31
 
5.6%
2 28
 
5.0%
9 24
 
4.3%
Other values (3) 24
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 558
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 92
16.5%
0 87
15.6%
1 84
15.1%
5 71
12.7%
7 45
8.1%
4 40
7.2%
8 32
 
5.7%
6 31
 
5.6%
2 28
 
5.0%
9 24
 
4.3%
Other values (3) 24
 
4.3%

FAX
Text

MISSING 

Distinct22
Distinct (%)61.1%
Missing12
Missing (%)25.0%
Memory size516.0 B
2023-12-12T22:39:41.004097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters432
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

Unique17 ?
Unique (%)47.2%

Sample

1st row051-525-0013
2nd row051-742-5714
3rd row051-746-3311
4th row051-784-7100
5th row051-784-7100
ValueCountFrequency (%)
051-784-7100 10
27.8%
051-898-0658 3
 
8.3%
051-784-0746 2
 
5.6%
051-918-4119 2
 
5.6%
051-501-2001 2
 
5.6%
051-747-8771 1
 
2.8%
051-525-0013 1
 
2.8%
051-745-9501 1
 
2.8%
051-701-9963 1
 
2.8%
051-703-1188 1
 
2.8%
Other values (12) 12
33.3%
2023-12-12T22:39:41.272197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 77
17.8%
- 72
16.7%
1 70
16.2%
5 52
12.0%
7 47
10.9%
8 38
8.8%
4 30
 
6.9%
6 18
 
4.2%
9 13
 
3.0%
2 8
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.3%
Dash Punctuation 72
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 77
21.4%
1 70
19.4%
5 52
14.4%
7 47
13.1%
8 38
10.6%
4 30
 
8.3%
6 18
 
5.0%
9 13
 
3.6%
2 8
 
2.2%
3 7
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 77
17.8%
- 72
16.7%
1 70
16.2%
5 52
12.0%
7 47
10.9%
8 38
8.8%
4 30
 
6.9%
6 18
 
4.2%
9 13
 
3.0%
2 8
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 77
17.8%
- 72
16.7%
1 70
16.2%
5 52
12.0%
7 47
10.9%
8 38
8.8%
4 30
 
6.9%
6 18
 
4.2%
9 13
 
3.0%
2 8
 
1.9%

Interactions

2023-12-12T22:39:37.573058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:39:41.359081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업 체 명대표자주 사 무 소전화번호FAX
연번1.0001.0000.0000.4680.0000.648
업 체 명1.0001.0001.0001.0001.0001.000
대표자0.0001.0001.0000.9940.9960.995
주 사 무 소0.4681.0000.9941.0000.9750.994
전화번호0.0001.0000.9960.9751.0000.996
FAX0.6481.0000.9950.9940.9961.000

Missing values

2023-12-12T22:39:37.712931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:39:37.860550image/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.
2023-12-12T22:39:37.963651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업 체 명대표자주 사 무 소전화번호FAX
01금사특수레카서*순해운대구 선수촌로 125(반여동)051-525-0071051-525-0013
12대양티앤티에스송*훈해운대구 센텀중앙로 48,1507호(우동,에이스하이테크21)051-742-5711051-742-5714
23㈜미성콘테이너김*원해운대구 마린시티3로 1, 527호(우동,선프라자)051-742-6446051-746-3311
34혁성운수㈜강*혁해운대구 재반로 57-14(재송동)051-784-6747051-784-7100
45부산시연료운수㈜강*우해운대구 재반로 57-14(재송동)051-783-2700051-784-7100
56㈜평화육운윤*남해운대구 마린시티3로 1,421호(우동, 선프라자)051-782-9784051-782-9786
67㈜세미특수김*연해운대구 재반로 7(재송동)051-781-9011~2051-784-5037
78㈜서울물류강*혁해운대구 재반로 57-14(재송동)051-784-3300051-784-7100
89광동통운㈜최*태영) 해운대구 해운대로 143번길24(재송동)051-783-2147051-784-0746
910경남통상㈜박*규영)해운대구해운대로143번길24(재송동)051-783-2144~5051-784-0746
연번업 체 명대표자주 사 무 소전화번호FAX
3839㈜대통박*배반여로155번다길 41, 201호(반여동)051-465-9351<NA>
3940㈜대일로직스정*진해운대로469번길 190, 303호(우동, 센텀현대@상가동)051-638-0466<NA>
4041㈜정광로지스틱스박*훈해운대로 1154, 2층(송정동)051-714-1945051-714-1948
4142서운종합물류(주)강*호센텀중앙로 97, 에이동 1405호(재송동, 센텀스카이비즈)051-622-4758<NA>
4243㈜짐모아로지스틱스김*규마린시티3로 37, 1016호(우동, 한일오르듀)051-583-2296<NA>
4344㈜원큐특수운송고*나센텀중앙로 90, 큐비이센텀(재송동)051-668-6921<NA>
4445㈜중앙상운원*이재반로 57-14(재송동)<NA><NA>
4546㈜진아김*용센텀동로 26, A동 2209호(우동, 한화꿈에그린센텀)051-898-0656051-898-0658
4647㈜제주항공 해운화물이*우APEC로 17, 3607호(우동, 센텀리더스마크)051-745-9111<NA>
4748세아로직스(주)황*영해운대로 1249, 4층(송정동, 삼양주유소)051-704-7022<NA>