Overview

Dataset statistics

Number of variables5
Number of observations92
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory42.4 B

Variable types

Text2
Categorical1
Numeric1
Boolean1

Dataset

Description전북특별자치도 익산시 일반화물자동차 운송사업자의 목록으로 파일 내에 사업자명, 차량대수, 사업장의 도로명주소, 운영여부가 포함되어있습니다.
Author전북특별자치도 익산시
URLhttps://www.data.go.kr/data/15115104/fileData.do

Alerts

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

Reproduction

Analysis started2024-03-14 19:04:09.761951
Analysis finished2024-03-14 19:04:10.895331
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size864.0 B
2024-03-15T04:04:11.851454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.8586957
Min length3

Characters and Unicode

Total characters631
Distinct characters127
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

Unique92 ?
Unique (%)100.0%

Sample

1st row보배물류(주)
2nd row(유)해성운수
3rd row(유)육육운수
4th row(유)석천운수
5th row㈜서일특수
ValueCountFrequency (%)
보배물류(주 1
 
1.1%
초원환경 1
 
1.1%
유)페트로물류 1
 
1.1%
㈜한로지스 1
 
1.1%
㈜한선기업 1
 
1.1%
유)고속로지스 1
 
1.1%
㈜프랜드로직스 1
 
1.1%
영등렉커 1
 
1.1%
유)창대환경 1
 
1.1%
유)마한운수 1
 
1.1%
Other values (83) 83
89.2%
2024-03-15T04:04:13.377792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 54
 
8.6%
) 54
 
8.6%
유 52
 
8.2%
운 29
 
4.6%
스 26
 
4.1%
㈜ 26
 
4.1%
수 25
 
4.0%
로 21
 
3.3%
이 18
 
2.9%
물 18
 
2.9%
Other values (117) 308
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 496
78.6%
Open Punctuation 54
 
8.6%
Close Punctuation 54
 
8.6%
Other Symbol 26
 
4.1%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 52
 
10.5%
운 29
 
5.8%
스 26
 
5.2%
수 25
 
5.0%
로 21
 
4.2%
이 18
 
3.6%
물 18
 
3.6%
지 17
 
3.4%
류 13
 
2.6%
대 9
 
1.8%
Other values (113) 268
54.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 26
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 522
82.7%
Common 109
 
17.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 52
 
10.0%
운 29
 
5.6%
스 26
 
5.0%
㈜ 26
 
5.0%
수 25
 
4.8%
로 21
 
4.0%
이 18
 
3.4%
물 18
 
3.4%
지 17
 
3.3%
류 13
 
2.5%
Other values (114) 277
53.1%
Common
ValueCountFrequency (%)
( 54
49.5%
) 54
49.5%
1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 496
78.6%
ASCII 109
 
17.3%
None 26
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 54
49.5%
) 54
49.5%
1
 
0.9%
Hangul
ValueCountFrequency (%)
유 52
 
10.5%
운 29
 
5.8%
스 26
 
5.2%
수 25
 
5.0%
로 21
 
4.2%
이 18
 
3.6%
물 18
 
3.6%
지 17
 
3.4%
류 13
 
2.6%
대 9
 
1.8%
Other values (113) 268
54.0%
None
ValueCountFrequency (%)
㈜ 26
100.0%

면허종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size864.0 B
일반화물
92 

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 92
100.0%

Length

2024-03-15T04:04:13.778603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:04:14.083805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화물 92
100.0%

차량대수
Real number (ℝ)

Distinct33
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.630435
Minimum1
Maximum211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-03-15T04:04:14.322554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q320
95-th percentile92.45
Maximum211
Range210
Interquartile range (IQR)17

Descriptive statistics

Standard deviation41.435696
Coefficient of variation (CV)1.9156201
Kurtosis11.688847
Mean21.630435
Median Absolute Deviation (MAD)3
Skewness3.4170027
Sum1990
Variance1716.9169
MonotonicityNot monotonic
2024-03-15T04:04:14.716911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2 17
18.5%
3 11
 
12.0%
5 10
 
10.9%
14 5
 
5.4%
4 5
 
5.4%
1 4
 
4.3%
51 3
 
3.3%
6 3
 
3.3%
15 3
 
3.3%
20 2
 
2.2%
Other values (23) 29
31.5%
ValueCountFrequency (%)
1 4
 
4.3%
2 17
18.5%
3 11
12.0%
4 5
 
5.4%
5 10
10.9%
6 3
 
3.3%
8 2
 
2.2%
10 2
 
2.2%
11 1
 
1.1%
13 2
 
2.2%
ValueCountFrequency (%)
211 1
 
1.1%
194 1
 
1.1%
188 1
 
1.1%
181 1
 
1.1%
126 1
 
1.1%
65 1
 
1.1%
58 1
 
1.1%
57 1
 
1.1%
51 3
3.3%
45 1
 
1.1%

도로명주소
Text

Distinct72
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size864.0 B
2024-03-15T04:04:15.951297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length21.945652
Min length18

Characters and Unicode

Total characters2019
Distinct characters90
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)65.2%

Sample

1st row전북특별자치도 익산시 석암로3길 67
2nd row전북특별자치도 익산시 춘포면 궁성로 107
3rd row전북특별자치도 익산시 무왕로 1706
4th row전북특별자치도 익산시 낭산면 함낭로 1275
5th row전북특별자치도 익산시 춘포면 궁성로 107
ValueCountFrequency (%)
전북특별자치도 92
22.3%
익산시 92
22.3%
무왕로 12
 
2.9%
함열읍 8
 
1.9%
약촌로 7
 
1.7%
궁성로 7
 
1.7%
금마면 6
 
1.5%
미륵사지로 6
 
1.5%
춘포면 6
 
1.5%
107 5
 
1.2%
Other values (119) 171
41.5%
2024-03-15T04:04:17.374363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
324
 
16.0%
산 105
 
5.2%
익 97
 
4.8%
도 92
 
4.6%
북 92
 
4.6%
시 92
 
4.6%
전 92
 
4.6%
치 92
 
4.6%
자 92
 
4.6%
별 92
 
4.6%
Other values (80) 849
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1371
67.9%
Space Separator 324
 
16.0%
Decimal Number 310
 
15.4%
Dash Punctuation 13
 
0.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 105
 
7.7%
익 97
 
7.1%
도 92
 
6.7%
북 92
 
6.7%
시 92
 
6.7%
전 92
 
6.7%
치 92
 
6.7%
자 92
 
6.7%
별 92
 
6.7%
특 92
 
6.7%
Other values (67) 433
31.6%
Decimal Number
ValueCountFrequency (%)
1 68
21.9%
2 44
14.2%
7 36
11.6%
4 32
10.3%
6 29
9.4%
3 27
 
8.7%
5 26
 
8.4%
0 25
 
8.1%
9 13
 
4.2%
8 10
 
3.2%
Space Separator
ValueCountFrequency (%)
324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1371
67.9%
Common 648
32.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 105
 
7.7%
익 97
 
7.1%
도 92
 
6.7%
북 92
 
6.7%
시 92
 
6.7%
전 92
 
6.7%
치 92
 
6.7%
자 92
 
6.7%
별 92
 
6.7%
특 92
 
6.7%
Other values (67) 433
31.6%
Common
ValueCountFrequency (%)
324
50.0%
1 68
 
10.5%
2 44
 
6.8%
7 36
 
5.6%
4 32
 
4.9%
6 29
 
4.5%
3 27
 
4.2%
5 26
 
4.0%
0 25
 
3.9%
- 13
 
2.0%
Other values (3) 24
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1371
67.9%
ASCII 648
32.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
324
50.0%
1 68
 
10.5%
2 44
 
6.8%
7 36
 
5.6%
4 32
 
4.9%
6 29
 
4.5%
3 27
 
4.2%
5 26
 
4.0%
0 25
 
3.9%
- 13
 
2.0%
Other values (3) 24
 
3.7%
Hangul
ValueCountFrequency (%)
산 105
 
7.7%
익 97
 
7.1%
도 92
 
6.7%
북 92
 
6.7%
시 92
 
6.7%
전 92
 
6.7%
치 92
 
6.7%
자 92
 
6.7%
별 92
 
6.7%
특 92
 
6.7%
Other values (67) 433
31.6%

운영여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size220.0 B
True
92 
ValueCountFrequency (%)
True 92
100.0%
2024-03-15T04:04:17.563987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2024-03-15T04:04:10.122053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:04:17.743336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명차량대수도로명주소
업체명1.0001.0001.000
차량대수1.0001.0000.000
도로명주소1.0000.0001.000

Missing values

2024-03-15T04:04:10.453538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:04:10.769144image/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

업체명면허종류차량대수도로명주소운영여부
0보배물류(주)일반화물51전북특별자치도 익산시 석암로3길 67Y
1(유)해성운수일반화물188전북특별자치도 익산시 춘포면 궁성로 107Y
2(유)육육운수일반화물51전북특별자치도 익산시 무왕로 1706Y
3(유)석천운수일반화물57전북특별자치도 익산시 낭산면 함낭로 1275Y
4㈜서일특수일반화물211전북특별자치도 익산시 춘포면 궁성로 107Y
5㈜세신특수운수일반화물15전북특별자치도 익산시 성당면 성당로 595Y
6(유)태림종합물류일반화물194전북특별자치도 익산시 함열읍 익산대로 1418Y
7(유)세림특수일반화물126전북특별자치도 익산시 함열읍 익산대로 1418Y
8백제종합운수일반화물1전북특별자치도 익산시 금마면 미륵사지로 96Y
9(유)서광운수일반화물5전북특별자치도 익산시 무왕로 1529Y
업체명면허종류차량대수도로명주소운영여부
82이리모범용달일반화물3전북특별자치도 익산시 약촌로 174Y
83예스로지텍㈜일반화물23전북특별자치도 익산시 약촌로 174Y
84진경로지스일반화물4전북특별자치도 익산시 함열읍 함열3길 67-12Y
85(유)팔팔용달사일반화물3전북특별자치도 익산시 목천로 263Y
86(유)이리용달일반화물3전북특별자치도 익산시 금마면 미륵사지로 96Y
87(유)야후화물자동차일반화물2전북특별자치도 익산시 왕궁면 평장2길 2Y
88(유)디와이종합물류일반화물3전북특별자치도 익산시 함열읍 익산대로 1366-5Y
89(유)동원화물일반화물1전북특별자치도 익산시 여산면 가람로 56Y
90(주)케이특수안전일반화물45전북특별자치도 익산시 고현로 35-12Y
91㈜제이에스에이일반화물2전북특별자치도 익산시 무왕로1242Y