Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory43.2 B

Variable types

Categorical2
Text2
Numeric1

Dataset

Description경상남도 밀양시 일반운수업체 현황에 대한 자료로, 업체명, 차고지 주소, 차량허가 대수에 대한 정보를 제공합니다.
Author경상남도 밀양시
URLhttps://www.data.go.kr/data/15106627/fileData.do

Alerts

운수업분류 has constant value ""Constant
데이터기준일자 has constant value ""Constant
업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:22:31.615544
Analysis finished2023-12-12 05:22:32.091718
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

운수업분류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
일반운수업
60 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반운수업 60
100.0%

Length

2023-12-12T14:22:32.156993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:22:32.258498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반운수업 60
100.0%

업체명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T14:22:32.537207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length5.2833333
Min length3

Characters and Unicode

Total characters317
Distinct characters92
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row㈜금마로지스
2nd row호운통운㈜
3rd row밀양츄레라
4th row㈜창대운수
5th row지성운수㈜
ValueCountFrequency (%)
㈜금마로지스 1
 
1.7%
호운통운㈜ 1
 
1.7%
㈜대영로지스 1
 
1.7%
㈜대진유조 1
 
1.7%
유)동해화물 1
 
1.7%
㈜동구운수 1
 
1.7%
㈜길창운수 1
 
1.7%
경성상운㈜ 1
 
1.7%
현대렉카 1
 
1.7%
청룡특수렉커 1
 
1.7%
Other values (50) 50
83.3%
2023-12-12T14:22:32.958461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 48
 
15.1%
운 22
 
6.9%
수 19
 
6.0%
물 13
 
4.1%
대 9
 
2.8%
특 8
 
2.5%
류 8
 
2.5%
렉 7
 
2.2%
로 7
 
2.2%
성 7
 
2.2%
Other values (82) 169
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 262
82.6%
Other Symbol 48
 
15.1%
Uppercase Letter 3
 
0.9%
Close Punctuation 2
 
0.6%
Open Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
운 22
 
8.4%
수 19
 
7.3%
물 13
 
5.0%
대 9
 
3.4%
특 8
 
3.1%
류 8
 
3.1%
렉 7
 
2.7%
로 7
 
2.7%
성 7
 
2.7%
유 6
 
2.3%
Other values (76) 156
59.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
O 1
33.3%
H 1
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 310
97.8%
Common 4
 
1.3%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 48
 
15.5%
운 22
 
7.1%
수 19
 
6.1%
물 13
 
4.2%
대 9
 
2.9%
특 8
 
2.6%
류 8
 
2.6%
렉 7
 
2.3%
로 7
 
2.3%
성 7
 
2.3%
Other values (77) 162
52.3%
Latin
ValueCountFrequency (%)
L 1
33.3%
O 1
33.3%
H 1
33.3%
Common
ValueCountFrequency (%)
) 2
50.0%
( 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
82.6%
None 48
 
15.1%
ASCII 7
 
2.2%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 48
100.0%
Hangul
ValueCountFrequency (%)
운 22
 
8.4%
수 19
 
7.3%
물 13
 
5.0%
대 9
 
3.4%
특 8
 
3.1%
류 8
 
3.1%
렉 7
 
2.7%
로 7
 
2.7%
성 7
 
2.7%
유 6
 
2.3%
Other values (76) 156
59.5%
ASCII
ValueCountFrequency (%)
) 2
28.6%
( 2
28.6%
L 1
14.3%
O 1
14.3%
H 1
14.3%

차고지주소
Text

Distinct51
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T14:22:33.285827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length36
Mean length19.233333
Min length10

Characters and Unicode

Total characters1154
Distinct characters107
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

Unique44 ?
Unique (%)73.3%

Sample

1st row경상남도 김해시 서상동 278
2nd row함안군 법수면 대송리 1200-1, 양산시 원동면 용당리 16-3
3rd row밀양시 부북면 전사포리 131-3
4th row합천군 용주면 가호리 1120, 양산시 물금읍 증산리 1416
5th row울산광역시 울주군 청량읍 덕하리 1078
ValueCountFrequency (%)
밀양시 33
 
12.1%
양산시 10
 
3.7%
증산리 7
 
2.6%
1416 7
 
2.6%
물금읍 6
 
2.2%
함안군 5
 
1.8%
무안면 5
 
1.8%
창녕군 4
 
1.5%
전사포리 4
 
1.5%
부북면 4
 
1.5%
Other values (120) 187
68.8%
2023-12-12T14:22:33.784998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
212
18.4%
1 70
 
6.1%
리 62
 
5.4%
면 50
 
4.3%
시 50
 
4.3%
양 47
 
4.1%
- 45
 
3.9%
2 35
 
3.0%
밀 33
 
2.9%
3 31
 
2.7%
Other values (97) 519
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 608
52.7%
Decimal Number 278
24.1%
Space Separator 212
 
18.4%
Dash Punctuation 45
 
3.9%
Other Punctuation 11
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 62
 
10.2%
면 50
 
8.2%
시 50
 
8.2%
양 47
 
7.7%
밀 33
 
5.4%
산 31
 
5.1%
군 19
 
3.1%
동 15
 
2.5%
읍 13
 
2.1%
안 12
 
2.0%
Other values (84) 276
45.4%
Decimal Number
ValueCountFrequency (%)
1 70
25.2%
2 35
12.6%
3 31
11.2%
6 23
 
8.3%
9 22
 
7.9%
8 21
 
7.6%
4 21
 
7.6%
0 20
 
7.2%
5 20
 
7.2%
7 15
 
5.4%
Space Separator
ValueCountFrequency (%)
212
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 608
52.7%
Common 546
47.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 62
 
10.2%
면 50
 
8.2%
시 50
 
8.2%
양 47
 
7.7%
밀 33
 
5.4%
산 31
 
5.1%
군 19
 
3.1%
동 15
 
2.5%
읍 13
 
2.1%
안 12
 
2.0%
Other values (84) 276
45.4%
Common
ValueCountFrequency (%)
212
38.8%
1 70
 
12.8%
- 45
 
8.2%
2 35
 
6.4%
3 31
 
5.7%
6 23
 
4.2%
9 22
 
4.0%
8 21
 
3.8%
4 21
 
3.8%
0 20
 
3.7%
Other values (3) 46
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 608
52.7%
ASCII 546
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
212
38.8%
1 70
 
12.8%
- 45
 
8.2%
2 35
 
6.4%
3 31
 
5.7%
6 23
 
4.2%
9 22
 
4.0%
8 21
 
3.8%
4 21
 
3.8%
0 20
 
3.7%
Other values (3) 46
 
8.4%
Hangul
ValueCountFrequency (%)
리 62
 
10.2%
면 50
 
8.2%
시 50
 
8.2%
양 47
 
7.7%
밀 33
 
5.4%
산 31
 
5.1%
군 19
 
3.1%
동 15
 
2.5%
읍 13
 
2.1%
안 12
 
2.0%
Other values (84) 276
45.4%

차량허가 대수
Real number (ℝ)

Distinct39
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.166667
Minimum2
Maximum116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T14:22:33.947192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q15.75
median27.5
Q371.75
95-th percentile103.3
Maximum116
Range114
Interquartile range (IQR)66

Descriptive statistics

Standard deviation36.034901
Coefficient of variation (CV)0.94414589
Kurtosis-0.93070258
Mean38.166667
Median Absolute Deviation (MAD)25.5
Skewness0.64968917
Sum2290
Variance1298.5141
MonotonicityNot monotonic
2023-12-12T14:22:34.158460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
2 11
 
18.3%
75 4
 
6.7%
6 3
 
5.0%
8 2
 
3.3%
14 2
 
3.3%
4 2
 
3.3%
15 2
 
3.3%
45 2
 
3.3%
41 2
 
3.3%
103 1
 
1.7%
Other values (29) 29
48.3%
ValueCountFrequency (%)
2 11
18.3%
3 1
 
1.7%
4 2
 
3.3%
5 1
 
1.7%
6 3
 
5.0%
7 1
 
1.7%
8 2
 
3.3%
11 1
 
1.7%
12 1
 
1.7%
14 2
 
3.3%
ValueCountFrequency (%)
116 1
1.7%
112 1
1.7%
109 1
1.7%
103 1
1.7%
100 1
1.7%
93 1
1.7%
91 1
1.7%
90 1
1.7%
87 1
1.7%
78 1
1.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2022-09-15
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-15
2nd row2022-09-15
3rd row2022-09-15
4th row2022-09-15
5th row2022-09-15

Common Values

ValueCountFrequency (%)
2022-09-15 60
100.0%

Length

2023-12-12T14:22:34.371344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:22:34.472327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-15 60
100.0%

Interactions

2023-12-12T14:22:31.815776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:22:34.547318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명차고지주소차량허가 대수
업체명1.0001.0001.000
차고지주소1.0001.0000.815
차량허가 대수1.0000.8151.000

Missing values

2023-12-12T14:22:31.928041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:22:32.047585image/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

운수업분류업체명차고지주소차량허가 대수데이터기준일자
0일반운수업㈜금마로지스경상남도 김해시 서상동 27822022-09-15
1일반운수업호운통운㈜함안군 법수면 대송리 1200-1, 양산시 원동면 용당리 16-3142022-09-15
2일반운수업밀양츄레라밀양시 부북면 전사포리 131-332022-09-15
3일반운수업㈜창대운수합천군 용주면 가호리 1120, 양산시 물금읍 증산리 141682022-09-15
4일반운수업지성운수㈜울산광역시 울주군 청량읍 덕하리 107852022-09-15
5일반운수업㈜일신로지스합천군 용주면 가호리 1120, 양산시 물금읍 증산리 1416142022-09-15
6일반운수업㈜미래화물창녕군 대지면 구미리 495-3, 영천시 북안면 관리 19522022-09-15
7일반운수업㈜유니온물류밀양시 단장면 사연리 1027-3332022-09-15
8일반운수업LOH로직스틱스양산시 물금읍 증산리 141622022-09-15
9일반운수업㈜화물뱅크김천시 농소면 신촌리 359-3112022-09-15
운수업분류업체명차고지주소차량허가 대수데이터기준일자
50일반운수업미래물류㈜창녕군 대지면 구미리 495-3412022-09-15
51일반운수업삼문렉카밀양시 삼문동 360-322022-09-15
52일반운수업세원특수밀양시 상남면 예림리 922-642022-09-15
53일반운수업한신상운㈜하동군 진교면 백련리 355-1872022-09-15
54일반운수업쌍마공업사밀양시 삼문동 529-222022-09-15
55일반운수업(유)신흥특수화물함안군 법수면 황사리 318-2932022-09-15
56일반운수업㈜강호밀양시 단장면 사연리 1008-4752022-09-15
57일반운수업덕창종합물류㈜양산시 물금읍 증산리 14161122022-09-15
58일반운수업㈜태경물류김천시 농소면 신촌리 437-8452022-09-15
59일반운수업㈜초동물류밀양시 초동면 신월리 37942022-09-15