Overview

Dataset statistics

Number of variables5
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory44.2 B

Variable types

Text2
Categorical2
Numeric1

Dataset

Description경상남도 함안군의 화물자동차 운송사업 등록된 사업자 현황입니다. 사업자의 명칭, 사업의 종류, 운영차량대수, 사업장의 주소 등을 포함하는 정보입니다.
Author공공데이터포털
URLhttps://www.data.go.kr/data/15115274/fileData.do

Alerts

사업의종류 has constant value ""Constant
영업상태 has constant value ""Constant
상호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 12:11:47.747771
Analysis finished2024-04-21 12:11:48.796423
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-04-21T21:11:49.409486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.025
Min length4

Characters and Unicode

Total characters281
Distinct characters90
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row(주)아이지건업
2nd row(주)아시아환경
3rd row(주)마창스카이
4th row마창스카이
5th row문성물류
ValueCountFrequency (%)
주식회사 2
 
4.7%
주)아이지건업 1
 
2.3%
삼호운수(주 1
 
2.3%
함안지점 1
 
2.3%
신창가스(주 1
 
2.3%
주)대명통운 1
 
2.3%
함안서비스기아오토큐(주 1
 
2.3%
가야렉카 1
 
2.3%
엘림인더스트리 1
 
2.3%
함안중앙레카 1
 
2.3%
Other values (32) 32
74.4%
2024-04-21T21:11:50.297596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 29
 
10.3%
( 26
 
9.3%
) 26
 
9.3%
운 10
 
3.6%
물 9
 
3.2%
류 9
 
3.2%
스 8
 
2.8%
수 7
 
2.5%
이 6
 
2.1%
카 6
 
2.1%
Other values (80) 145
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 226
80.4%
Open Punctuation 26
 
9.3%
Close Punctuation 26
 
9.3%
Space Separator 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
12.8%
운 10
 
4.4%
물 9
 
4.0%
류 9
 
4.0%
스 8
 
3.5%
수 7
 
3.1%
이 6
 
2.7%
카 6
 
2.7%
통 5
 
2.2%
안 5
 
2.2%
Other values (77) 132
58.4%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 226
80.4%
Common 55
 
19.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 29
 
12.8%
운 10
 
4.4%
물 9
 
4.0%
류 9
 
4.0%
스 8
 
3.5%
수 7
 
3.1%
이 6
 
2.7%
카 6
 
2.7%
통 5
 
2.2%
안 5
 
2.2%
Other values (77) 132
58.4%
Common
ValueCountFrequency (%)
( 26
47.3%
) 26
47.3%
3
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 226
80.4%
ASCII 55
 
19.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 29
 
12.8%
운 10
 
4.4%
물 9
 
4.0%
류 9
 
4.0%
스 8
 
3.5%
수 7
 
3.1%
이 6
 
2.7%
카 6
 
2.7%
통 5
 
2.2%
안 5
 
2.2%
Other values (77) 132
58.4%
ASCII
ValueCountFrequency (%)
( 26
47.3%
) 26
47.3%
3
 
5.5%

사업의종류
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
일반화물
40 

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 40
100.0%

Length

2024-04-21T21:11:50.516545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:11:50.679233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화물 40
100.0%

차량 대수
Real number (ℝ)

Distinct18
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.45
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-04-21T21:11:50.840291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.75
median5
Q39
95-th percentile57.1
Maximum95
Range94
Interquartile range (IQR)7.25

Descriptive statistics

Standard deviation20.181167
Coefficient of variation (CV)1.7625473
Kurtosis9.8438992
Mean11.45
Median Absolute Deviation (MAD)4
Skewness3.1423631
Sum458
Variance407.27949
MonotonicityNot monotonic
2024-04-21T21:11:51.026463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 10
25.0%
4 4
 
10.0%
9 4
 
10.0%
2 3
 
7.5%
6 2
 
5.0%
8 2
 
5.0%
7 2
 
5.0%
3 2
 
5.0%
5 2
 
5.0%
56 1
 
2.5%
Other values (8) 8
20.0%
ValueCountFrequency (%)
1 10
25.0%
2 3
 
7.5%
3 2
 
5.0%
4 4
 
10.0%
5 2
 
5.0%
6 2
 
5.0%
7 2
 
5.0%
8 2
 
5.0%
9 4
 
10.0%
10 1
 
2.5%
ValueCountFrequency (%)
95 1
 
2.5%
78 1
 
2.5%
56 1
 
2.5%
29 1
 
2.5%
26 1
 
2.5%
15 1
 
2.5%
12 1
 
2.5%
11 1
 
2.5%
10 1
 
2.5%
9 4
10.0%

주사무소도로명주소
Text

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-04-21T21:11:51.857934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length24.725
Min length19

Characters and Unicode

Total characters989
Distinct characters104
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

Unique32 ?
Unique (%)80.0%

Sample

1st row경상남도 함안군 칠원읍 운무로 88
2nd row경상남도 함안군 군북면 현포로 152
3rd row경상남도 함안군 산인면 송산로 139
4th row경상남도 함안군 산인면 송산로 139
5th row경상남도 함안군 칠원읍 호곡3길 32
ValueCountFrequency (%)
경상남도 40
17.8%
함안군 40
17.8%
법수면 9
 
4.0%
칠서면 9
 
4.0%
군북면 6
 
2.7%
가야읍 6
 
2.7%
산인면 5
 
2.2%
17 4
 
1.8%
칠원읍 4
 
1.8%
송산로 3
 
1.3%
Other values (85) 99
44.0%
2024-04-21T21:11:52.943801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
18.8%
군 46
 
4.7%
함 43
 
4.3%
안 43
 
4.3%
도 42
 
4.2%
상 42
 
4.2%
경 41
 
4.1%
남 41
 
4.1%
1 30
 
3.0%
면 30
 
3.0%
Other values (94) 445
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 612
61.9%
Space Separator 186
 
18.8%
Decimal Number 155
 
15.7%
Other Punctuation 11
 
1.1%
Open Punctuation 9
 
0.9%
Close Punctuation 9
 
0.9%
Dash Punctuation 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 46
 
7.5%
함 43
 
7.0%
안 43
 
7.0%
도 42
 
6.9%
상 42
 
6.9%
경 41
 
6.7%
남 41
 
6.7%
면 30
 
4.9%
로 24
 
3.9%
칠 18
 
2.9%
Other values (79) 242
39.5%
Decimal Number
ValueCountFrequency (%)
1 30
19.4%
2 27
17.4%
3 18
11.6%
0 17
11.0%
4 15
9.7%
9 13
8.4%
5 10
 
6.5%
6 9
 
5.8%
7 9
 
5.8%
8 7
 
4.5%
Space Separator
ValueCountFrequency (%)
186
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 612
61.9%
Common 377
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 46
 
7.5%
함 43
 
7.0%
안 43
 
7.0%
도 42
 
6.9%
상 42
 
6.9%
경 41
 
6.7%
남 41
 
6.7%
면 30
 
4.9%
로 24
 
3.9%
칠 18
 
2.9%
Other values (79) 242
39.5%
Common
ValueCountFrequency (%)
186
49.3%
1 30
 
8.0%
2 27
 
7.2%
3 18
 
4.8%
0 17
 
4.5%
4 15
 
4.0%
9 13
 
3.4%
, 11
 
2.9%
5 10
 
2.7%
( 9
 
2.4%
Other values (5) 41
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 612
61.9%
ASCII 377
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
186
49.3%
1 30
 
8.0%
2 27
 
7.2%
3 18
 
4.8%
0 17
 
4.5%
4 15
 
4.0%
9 13
 
3.4%
, 11
 
2.9%
5 10
 
2.7%
( 9
 
2.4%
Other values (5) 41
 
10.9%
Hangul
ValueCountFrequency (%)
군 46
 
7.5%
함 43
 
7.0%
안 43
 
7.0%
도 42
 
6.9%
상 42
 
6.9%
경 41
 
6.7%
남 41
 
6.7%
면 30
 
4.9%
로 24
 
3.9%
칠 18
 
2.9%
Other values (79) 242
39.5%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
신규
40 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신규 40
100.0%

Length

2024-04-21T21:11:53.163577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T21:11:53.328870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 40
100.0%

Interactions

2024-04-21T21:11:48.062847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T21:11:53.430075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호차량 대수주사무소도로명주소
상호1.0001.0001.000
차량 대수1.0001.0000.000
주사무소도로명주소1.0000.0001.000

Missing values

2024-04-21T21:11:48.366672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T21:11:48.675040image/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

상호사업의종류차량 대수주사무소도로명주소영업상태
0(주)아이지건업일반화물1경상남도 함안군 칠원읍 운무로 88신규
1(주)아시아환경일반화물9경상남도 함안군 군북면 현포로 152신규
2(주)마창스카이일반화물1경상남도 함안군 산인면 송산로 139신규
3마창스카이일반화물10경상남도 함안군 산인면 송산로 139신규
4문성물류일반화물1경상남도 함안군 칠원읍 호곡3길 32신규
5우진운수일반화물2경상남도 함안군 칠원읍 원서로 89-21, 102동 404호 (칠원동성아파트)신규
6주식회사 창원특수운송일반화물9경상남도 함안군 칠원읍 광려천북로 230-1신규
7(주)남일특수운수일반화물5경상남도 함안군 군북면 삼봉로 144신규
8한국스카이일반화물1경상남도 함안군 산인면 부봉2길 126신규
9성원물류일반화물2경상남도 함안군 칠서면 칠평로 62, 204동 905호 (에이스아파트)신규
상호사업의종류차량 대수주사무소도로명주소영업상태
30삼호운수(주)일반화물29경상남도 함안군 가야읍 함안대로 779신규
31함안견인일반화물6경상남도 함안군 가야읍 도항2길 23신규
32(주)창특일반화물26경상남도 함안군 군북면 장백로 39신규
33함안레카일반화물7경상남도 함안군 가야읍 도항2길 23신규
34(주)합동통운일반화물12경상남도 함안군 가야읍 함안대로 779신규
35경남통상(주)일반화물78경상남도 함안군 법수면 대송3길 17, 경남통상(주)신규
36광동통운(주)일반화물95경상남도 함안군 법수면 대송3길 17신규
37디에이치케미칼스(주)일반화물1경상남도 함안군 칠서면 공단동4길 95, 공장신규
38티엘에스(주)일반화물8경상남도 함안군 군북면 함마대로 290-14, 현대자동차(주) 출고센터신규
39강산통운(주)일반화물11경상남도 함안군 법수면 두배길 16신규