Overview

Dataset statistics

Number of variables5
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory46.1 B

Variable types

Text2
Categorical2
Numeric1

Dataset

Description일반화물업체(일반화물 자동차 운송사업자 업체) 현황입니다. 업체명, 면허종류, 차량대수, 주소, 운영여부에 대한 자료를 제공합니다.
URLhttps://www.data.go.kr/data/15114751/fileData.do

Alerts

면허종류 has constant value ""Constant
현재운영여부 has constant value ""Constant
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:35:25.702215
Analysis finished2023-12-12 22:35:26.101002
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T07:35:26.245743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length5.6153846
Min length3

Characters and Unicode

Total characters146
Distinct characters69
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

Unique26 ?
Unique (%)100.0%

Sample

1st row서대구 대형 렉카 크레인
2nd row대구특수렉카캐리어
3rd row진종합정비
4th row㈜대한운수
5th row㈜한성
ValueCountFrequency (%)
서대구 1
 
3.4%
㈜로드로지스 1
 
3.4%
㈜대성글로벌 1
 
3.4%
월드모터스 1
 
3.4%
㈜우산통운 1
 
3.4%
㈜정도기업 1
 
3.4%
㈜세종 1
 
3.4%
가나익스프레스 1
 
3.4%
㈜영주추레라 1
 
3.4%
㈜신흥운수 1
 
3.4%
Other values (19) 19
65.5%
2023-12-13T07:35:26.571595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 18
 
12.3%
성 5
 
3.4%
스 5
 
3.4%
대 5
 
3.4%
류 5
 
3.4%
물 5
 
3.4%
운 5
 
3.4%
수 5
 
3.4%
구 4
 
2.7%
합 3
 
2.1%
Other values (59) 86
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
84.2%
Other Symbol 18
 
12.3%
Space Separator 3
 
2.1%
Close Punctuation 1
 
0.7%
Open Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 5
 
4.1%
스 5
 
4.1%
대 5
 
4.1%
류 5
 
4.1%
물 5
 
4.1%
운 5
 
4.1%
수 5
 
4.1%
구 4
 
3.3%
합 3
 
2.4%
드 3
 
2.4%
Other values (55) 78
63.4%
Other Symbol
ValueCountFrequency (%)
㈜ 18
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 141
96.6%
Common 5
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 18
 
12.8%
성 5
 
3.5%
스 5
 
3.5%
대 5
 
3.5%
류 5
 
3.5%
물 5
 
3.5%
운 5
 
3.5%
수 5
 
3.5%
구 4
 
2.8%
합 3
 
2.1%
Other values (56) 81
57.4%
Common
ValueCountFrequency (%)
3
60.0%
) 1
 
20.0%
( 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
84.2%
None 18
 
12.3%
ASCII 5
 
3.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 18
100.0%
Hangul
ValueCountFrequency (%)
성 5
 
4.1%
스 5
 
4.1%
대 5
 
4.1%
류 5
 
4.1%
물 5
 
4.1%
운 5
 
4.1%
수 5
 
4.1%
구 4
 
3.3%
합 3
 
2.4%
드 3
 
2.4%
Other values (55) 78
63.4%
ASCII
ValueCountFrequency (%)
3
60.0%
) 1
 
20.0%
( 1
 
20.0%

면허종류
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
일반화물
26 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반화물 26
100.0%

Length

2023-12-13T07:35:26.690209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:35:26.777894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화물 26
100.0%

차량대수
Real number (ℝ)

Distinct15
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.846154
Minimum1
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T07:35:26.866234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.25
Q13
median5
Q312.75
95-th percentile83
Maximum105
Range104
Interquartile range (IQR)9.75

Descriptive statistics

Standard deviation28.656158
Coefficient of variation (CV)1.605733
Kurtosis3.5385917
Mean17.846154
Median Absolute Deviation (MAD)3
Skewness2.1283686
Sum464
Variance821.17538
MonotonicityNot monotonic
2023-12-13T07:35:26.973005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2 4
15.4%
3 3
11.5%
4 3
11.5%
5 2
 
7.7%
1 2
 
7.7%
6 2
 
7.7%
12 2
 
7.7%
19 1
 
3.8%
71 1
 
3.8%
7 1
 
3.8%
Other values (5) 5
19.2%
ValueCountFrequency (%)
1 2
7.7%
2 4
15.4%
3 3
11.5%
4 3
11.5%
5 2
7.7%
6 2
7.7%
7 1
 
3.8%
12 2
7.7%
13 1
 
3.8%
19 1
 
3.8%
ValueCountFrequency (%)
105 1
3.8%
87 1
3.8%
71 1
3.8%
58 1
3.8%
27 1
3.8%
19 1
3.8%
13 1
3.8%
12 2
7.7%
7 1
3.8%
6 2
7.7%

주소
Text

Distinct20
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T07:35:27.193131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length23.192308
Min length20

Characters and Unicode

Total characters603
Distinct characters60
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)65.4%

Sample

1st row경상북도 영주시 중앙로126번길 14, 2층 (하망동)
2nd row경상북도 영주시 중앙로126번길 14, 202호 (하망동)
3rd row경상북도 영주시 원당로 71 (영주동)
4th row경상북도 영주시 적서로 239 (적서동)
5th row경상북도 영주시 안정면 장안로 709-6
ValueCountFrequency (%)
경상북도 26
19.7%
영주시 26
19.7%
적서로 6
 
4.5%
적서동 6
 
4.5%
201 5
 
3.8%
휴천동 4
 
3.0%
영주동 4
 
3.0%
가흥동 3
 
2.3%
하망동 3
 
2.3%
선비로 3
 
2.3%
Other values (38) 46
34.8%
2023-12-13T07:35:27.626408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
17.6%
영 32
 
5.3%
주 32
 
5.3%
상 27
 
4.5%
경 26
 
4.3%
북 26
 
4.3%
도 26
 
4.3%
시 26
 
4.3%
로 26
 
4.3%
2 23
 
3.8%
Other values (50) 253
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 356
59.0%
Space Separator 106
 
17.6%
Decimal Number 96
 
15.9%
Open Punctuation 21
 
3.5%
Close Punctuation 21
 
3.5%
Other Punctuation 2
 
0.3%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 32
 
9.0%
주 32
 
9.0%
상 27
 
7.6%
경 26
 
7.3%
북 26
 
7.3%
도 26
 
7.3%
시 26
 
7.3%
로 26
 
7.3%
동 21
 
5.9%
서 13
 
3.7%
Other values (35) 101
28.4%
Decimal Number
ValueCountFrequency (%)
2 23
24.0%
1 21
21.9%
0 13
13.5%
4 8
 
8.3%
6 6
 
6.2%
8 6
 
6.2%
9 6
 
6.2%
3 6
 
6.2%
7 5
 
5.2%
5 2
 
2.1%
Space Separator
ValueCountFrequency (%)
106
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 356
59.0%
Common 247
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 32
 
9.0%
주 32
 
9.0%
상 27
 
7.6%
경 26
 
7.3%
북 26
 
7.3%
도 26
 
7.3%
시 26
 
7.3%
로 26
 
7.3%
동 21
 
5.9%
서 13
 
3.7%
Other values (35) 101
28.4%
Common
ValueCountFrequency (%)
106
42.9%
2 23
 
9.3%
( 21
 
8.5%
) 21
 
8.5%
1 21
 
8.5%
0 13
 
5.3%
4 8
 
3.2%
6 6
 
2.4%
8 6
 
2.4%
9 6
 
2.4%
Other values (5) 16
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 356
59.0%
ASCII 247
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
42.9%
2 23
 
9.3%
( 21
 
8.5%
) 21
 
8.5%
1 21
 
8.5%
0 13
 
5.3%
4 8
 
3.2%
6 6
 
2.4%
8 6
 
2.4%
9 6
 
2.4%
Other values (5) 16
 
6.5%
Hangul
ValueCountFrequency (%)
영 32
 
9.0%
주 32
 
9.0%
상 27
 
7.6%
경 26
 
7.3%
북 26
 
7.3%
도 26
 
7.3%
시 26
 
7.3%
로 26
 
7.3%
동 21
 
5.9%
서 13
 
3.7%
Other values (35) 101
28.4%

현재운영여부
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
여
26 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여 26
100.0%

Length

2023-12-13T07:35:27.798143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:35:27.893405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 26
100.0%

Interactions

2023-12-13T07:35:25.862383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:35:27.951348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명차량대수주소
업체명1.0001.0001.000
차량대수1.0001.0000.000
주소1.0000.0001.000

Missing values

2023-12-13T07:35:25.971470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:35:26.060701image/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

업체명면허종류차량대수주소현재운영여부
0서대구 대형 렉카 크레인일반화물5경상북도 영주시 중앙로126번길 14, 2층 (하망동)여
1대구특수렉카캐리어일반화물3경상북도 영주시 중앙로126번길 14, 202호 (하망동)여
2진종합정비일반화물2경상북도 영주시 원당로 71 (영주동)여
3㈜대한운수일반화물5경상북도 영주시 적서로 239 (적서동)여
4㈜한성일반화물1경상북도 영주시 안정면 장안로 709-6여
5성진물류일반화물4경상북도 영주시 반지미로 222 (가흥동)여
6㈜한류일반화물3경상북도 영주시 안정면 장안로 700여
7㈜전국물류일반화물6경상북도 영주시 선비로 193 (영주동)여
8㈜보성물류일반화물1경상북도 영주시 영주로 25 (가흥동)여
9㈜참좋은친구일반화물19경상북도 영주시 적서로 201 (적서동)여
업체명면허종류차량대수주소현재운영여부
16(합)친구유통일반화물12경상북도 영주시 적서로 201 (적서동)여
17㈜신흥운수일반화물12경상북도 영주시 반지미로 222 (가흥동)여
18㈜영주추레라일반화물7경상북도 영주시 구성로88번길 204 (휴천동)여
19가나익스프레스일반화물3경상북도 영주시 원당로 385 (상망동)여
20㈜세종일반화물105경상북도 영주시 서원로 111 (휴천동)여
21㈜정도기업일반화물87경상북도 영주시 선비로 193 (영주동)여
22㈜우산통운일반화물27경상북도 영주시 구성로148번길 18 (휴천동)여
23월드모터스일반화물4경상북도 영주시 지천로 101 (휴천동)여
24㈜대성글로벌일반화물13경상북도 영주시 장수면 장수로220번길 34여
25삼양운수㈜일반화물58경상북도 영주시 이산면 간운로 467여