Overview

Dataset statistics

Number of variables4
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory36.8 B

Variable types

Numeric2
Text2

Dataset

Description인천광역시 부평구_일반화물자동차운송사업자 현황 데이터는 운송사업자 업체 명과 차량대수 주소 정보를 제공하고 있습니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15115183&srcSe=7661IVAWM27C61E190

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:18:41.500434
Analysis finished2024-01-28 08:18:42.533510
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
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
2024-01-28T17:18:42.591345image/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
2024-01-28T17:18:42.699977image/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%

업체명
Text

Distinct46
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-01-28T17:18:42.906374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length13
Mean length7.2291667
Min length3

Characters and Unicode

Total characters347
Distinct characters107
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)91.7%

Sample

1st row아시아케미칼㈜
2nd row㈜백진종합물류
3rd row㈜대지물류
4th row㈜통진
5th row화이트물류㈜
ValueCountFrequency (%)
㈜유진종합물류 2
 
3.7%
인천지점 2
 
3.7%
㈜월드종합운수 2
 
3.7%
경동물류㈜ 1
 
1.9%
태흥로지스㈜ 1
 
1.9%
㈜인천스카이 1
 
1.9%
㈜희림물류 1
 
1.9%
태건물류㈜ 1
 
1.9%
㈜행운로지스 1
 
1.9%
주)서울에너지 1
 
1.9%
Other values (41) 41
75.9%
2024-01-28T17:18:43.245572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 42
 
12.1%
스 17
 
4.9%
지 15
 
4.3%
물 13
 
3.7%
류 12
 
3.5%
운 9
 
2.6%
로 9
 
2.6%
이 9
 
2.6%
에 9
 
2.6%
( 8
 
2.3%
Other values (97) 204
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 277
79.8%
Other Symbol 42
 
12.1%
Open Punctuation 8
 
2.3%
Close Punctuation 8
 
2.3%
Space Separator 6
 
1.7%
Uppercase Letter 3
 
0.9%
Math Symbol 2
 
0.6%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 17
 
6.1%
지 15
 
5.4%
물 13
 
4.7%
류 12
 
4.3%
운 9
 
3.2%
로 9
 
3.2%
이 9
 
3.2%
에 9
 
3.2%
종 6
 
2.2%
천 6
 
2.2%
Other values (87) 172
62.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
L 1
33.3%
C 1
33.3%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 319
91.9%
Common 25
 
7.2%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 42
 
13.2%
스 17
 
5.3%
지 15
 
4.7%
물 13
 
4.1%
류 12
 
3.8%
운 9
 
2.8%
로 9
 
2.8%
이 9
 
2.8%
에 9
 
2.8%
종 6
 
1.9%
Other values (88) 178
55.8%
Common
ValueCountFrequency (%)
( 8
32.0%
) 8
32.0%
6
24.0%
4 1
 
4.0%
< 1
 
4.0%
> 1
 
4.0%
Latin
ValueCountFrequency (%)
S 1
33.3%
L 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 277
79.8%
None 42
 
12.1%
ASCII 28
 
8.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 42
100.0%
Hangul
ValueCountFrequency (%)
스 17
 
6.1%
지 15
 
5.4%
물 13
 
4.7%
류 12
 
4.3%
운 9
 
3.2%
로 9
 
3.2%
이 9
 
3.2%
에 9
 
3.2%
종 6
 
2.2%
천 6
 
2.2%
Other values (87) 172
62.1%
ASCII
ValueCountFrequency (%)
( 8
28.6%
) 8
28.6%
6
21.4%
4 1
 
3.6%
< 1
 
3.6%
> 1
 
3.6%
S 1
 
3.6%
L 1
 
3.6%
C 1
 
3.6%

차량대수
Real number (ℝ)

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.479167
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-01-28T17:18:43.362355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median6.5
Q317.25
95-th percentile36.65
Maximum48
Range47
Interquartile range (IQR)15.25

Descriptive statistics

Standard deviation11.877011
Coefficient of variation (CV)1.0346579
Kurtosis1.1290487
Mean11.479167
Median Absolute Deviation (MAD)5.5
Skewness1.3190133
Sum551
Variance141.06339
MonotonicityNot monotonic
2024-01-28T17:18:43.466227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 9
18.8%
4 7
14.6%
2 4
 
8.3%
13 2
 
4.2%
8 2
 
4.2%
11 2
 
4.2%
17 2
 
4.2%
3 2
 
4.2%
23 2
 
4.2%
7 1
 
2.1%
Other values (15) 15
31.2%
ValueCountFrequency (%)
1 9
18.8%
2 4
8.3%
3 2
 
4.2%
4 7
14.6%
5 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
8 2
 
4.2%
10 1
 
2.1%
11 2
 
4.2%
ValueCountFrequency (%)
48 1
2.1%
39 1
2.1%
37 1
2.1%
36 1
2.1%
29 1
2.1%
28 1
2.1%
25 1
2.1%
23 2
4.2%
20 1
2.1%
19 1
2.1%

주소
Text

Distinct41
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-01-28T17:18:43.741038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length41
Mean length34.8125
Min length21

Characters and Unicode

Total characters1671
Distinct characters106
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

Unique37 ?
Unique (%)77.1%

Sample

1st row인천광역시 부평구 안남로 391(청천동)
2nd row인천광역시 부평구 부흥로294번길 4, 603호(부평동, 추인타워빌딩)
3rd row인천광역시 부평구 부평북로 273(갈산동)
4th row인천광역시 부평구 영성중로 50, 305호(삼산동, 미래타워)
5th row인천광역시 부평구 부평대로 130, 청봉빌딩 3층(부평동)
ValueCountFrequency (%)
인천광역시 48
 
17.2%
부평구 48
 
17.2%
부평대로 11
 
3.9%
장제로 5
 
1.8%
145 5
 
1.8%
마장로 5
 
1.8%
1407호(부평동 4
 
1.4%
스카이 4
 
1.4%
24 3
 
1.1%
청천동 3
 
1.1%
Other values (111) 143
51.3%
2024-01-28T17:18:44.148021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
233
 
13.9%
부 87
 
5.2%
평 82
 
4.9%
천 69
 
4.1%
, 66
 
3.9%
인 56
 
3.4%
1 55
 
3.3%
동 54
 
3.2%
시 51
 
3.1%
2 49
 
2.9%
Other values (96) 869
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 970
58.0%
Decimal Number 296
 
17.7%
Space Separator 233
 
13.9%
Other Punctuation 66
 
3.9%
Open Punctuation 49
 
2.9%
Close Punctuation 49
 
2.9%
Dash Punctuation 5
 
0.3%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 87
 
9.0%
평 82
 
8.5%
천 69
 
7.1%
인 56
 
5.8%
동 54
 
5.6%
시 51
 
5.3%
로 48
 
4.9%
구 48
 
4.9%
광 48
 
4.9%
역 48
 
4.9%
Other values (78) 379
39.1%
Decimal Number
ValueCountFrequency (%)
1 55
18.6%
2 49
16.6%
3 42
14.2%
4 39
13.2%
0 36
12.2%
9 19
 
6.4%
5 18
 
6.1%
6 15
 
5.1%
7 15
 
5.1%
8 8
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
L 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
233
100.0%
Other Punctuation
ValueCountFrequency (%)
, 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 970
58.0%
Common 698
41.8%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 87
 
9.0%
평 82
 
8.5%
천 69
 
7.1%
인 56
 
5.8%
동 54
 
5.6%
시 51
 
5.3%
로 48
 
4.9%
구 48
 
4.9%
광 48
 
4.9%
역 48
 
4.9%
Other values (78) 379
39.1%
Common
ValueCountFrequency (%)
233
33.4%
, 66
 
9.5%
1 55
 
7.9%
2 49
 
7.0%
( 49
 
7.0%
) 49
 
7.0%
3 42
 
6.0%
4 39
 
5.6%
0 36
 
5.2%
9 19
 
2.7%
Other values (5) 61
 
8.7%
Latin
ValueCountFrequency (%)
C 1
33.3%
L 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 970
58.0%
ASCII 701
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
233
33.2%
, 66
 
9.4%
1 55
 
7.8%
2 49
 
7.0%
( 49
 
7.0%
) 49
 
7.0%
3 42
 
6.0%
4 39
 
5.6%
0 36
 
5.1%
9 19
 
2.7%
Other values (8) 64
 
9.1%
Hangul
ValueCountFrequency (%)
부 87
 
9.0%
평 82
 
8.5%
천 69
 
7.1%
인 56
 
5.8%
동 54
 
5.6%
시 51
 
5.3%
로 48
 
4.9%
구 48
 
4.9%
광 48
 
4.9%
역 48
 
4.9%
Other values (78) 379
39.1%

Interactions

2024-01-28T17:18:41.879714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:18:41.738936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:18:41.961843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:18:41.809624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:18:44.223160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업체명차량대수주소
순번1.0000.8190.0000.814
업체명0.8191.0000.9080.993
차량대수0.0000.9081.0000.477
주소0.8140.9930.4771.000
2024-01-28T17:18:44.298086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번차량대수
순번1.000-0.465
차량대수-0.4651.000

Missing values

2024-01-28T17:18:42.425129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:18:42.503261image/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

순번업체명차량대수주소
01아시아케미칼㈜7인천광역시 부평구 안남로 391(청천동)
12㈜백진종합물류23인천광역시 부평구 부흥로294번길 4, 603호(부평동, 추인타워빌딩)
23㈜대지물류8인천광역시 부평구 부평북로 273(갈산동)
34㈜통진15인천광역시 부평구 영성중로 50, 305호(삼산동, 미래타워)
45화이트물류㈜1인천광역시 부평구 부평대로 130, 청봉빌딩 3층(부평동)
56나눔통운㈜19인천광역시 부평구 경인로 731, 2층(십정동)
67도로청소㈜36인천광역시 부평구 송내대로373번길 15(삼산동)
78㈜동서엘지에스25인천광역시 부평구 부평대로 293, 1201호(청천동, 부평테크시티)
89동부산업㈜11인천광역시 부평구 안남로434번길 23, 202(청천동)
910삼원티엘에스㈜4인천광역시 부평구 충선로203번길 24, 421호(삼산동, 삼산프라자)
순번업체명차량대수주소
3839㈜에이앤로지스13인천광역시 부평구 부평대로 337, 1246호 (청천동, 부평 제이타워3차 지식산업센터)
3940㈜에이앤컴퍼니1인천광역시 부평구 부평대로 337, 1246호 (청천동, 부평 제이타워3차 지식산업센터)
4041(유) 엔와이글로벌18인천광역시 부평구 평천로255번길 13, 901호(청천동, 부평테크노파크엠2지식산업센터)
4142주식회사 유창(인천점)4인천광역시 부평구 장제로 145, 1407호(부평동, 스카이)
4243㈜거산로지스2인천광역시 부평구 평천로 290, 401호(갈산동, 원츠프라자)
4344쿠팡로지스틱스서비스(유)<CLS> 인천4 직영영업점1인천광역시 부평구 안남로369번길 18, CLS 인천4 직영영업점 (청천동)
4445정우물류㈜ 인천지점1인천광역시 부평구 부일로 44(부개동)
4546경동물류㈜1인천광역시 부평구 부평대로 296번길 5(갈산동)
4647㈜한울티엘에스(부평지점)4인천광역시 부평구 부영로 18(부평동)
4748충현운수㈜ 인천지점14인천광역시 부평구 장제로 145, 1407호(부평동, 스카이)