Overview

Dataset statistics

Number of variables7
Number of observations102
Missing cells4
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory58.3 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description서울특별시 송파구의 법인화물자동차운송사업자 업체 현황입니다. 화물자동차를 사용하여 유상으로 화물을 운송하는 업체 정보입니다.
URLhttps://www.data.go.kr/data/15115088/fileData.do

Alerts

운영여부 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
업종명 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
비고 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 업종명 and 2 other fieldsHigh correlation
업종명 is highly imbalanced (92.1%)Imbalance
운영여부 is highly imbalanced (92.1%)Imbalance
비고 is highly imbalanced (92.1%)Imbalance

Reproduction

Analysis started2023-12-12 22:34:29.583900
Analysis finished2023-12-12 22:34:30.714958
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean51
Minimum1
Maximum101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-13T07:34:30.800996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q126
median51
Q376
95-th percentile96
Maximum101
Range100
Interquartile range (IQR)50

Descriptive statistics

Standard deviation29.300171
Coefficient of variation (CV)0.57451315
Kurtosis-1.2
Mean51
Median Absolute Deviation (MAD)25
Skewness0
Sum5151
Variance858.5
MonotonicityStrictly increasing
2023-12-13T07:34:30.951608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (91) 91
89.2%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
일반화물
101 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반화물 101
99.0%
<NA> 1
 
1.0%

Length

2023-12-13T07:34:31.085338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:34:31.185907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화물 101
99.0%
na 1
 
1.0%

업체명
Text

Distinct92
Distinct (%)91.1%
Missing1
Missing (%)1.0%
Memory size948.0 B
2023-12-13T07:34:31.409287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.5643564
Min length4

Characters and Unicode

Total characters865
Distinct characters138
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

Unique83 ?
Unique (%)82.2%

Sample

1st row주식회사 유한로지스
2nd row주식회사 카고앤잡로지스
3rd row(주)이사의명가
4th row88더브레이브 주식회사
5th row디디라인 주식회사
ValueCountFrequency (%)
주식회사 9
 
8.2%
한성종합물류(주 2
 
1.8%
주)삼영이앤아이 2
 
1.8%
주)정현운수 2
 
1.8%
유)온나라물류 2
 
1.8%
주)덕영로지스 2
 
1.8%
명진지엘에스(주 2
 
1.8%
주)조은운수 2
 
1.8%
주)서현운수 2
 
1.8%
대신로지스틱스(주 2
 
1.8%
Other values (83) 83
75.5%
2023-12-13T07:34:31.835885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 97
 
11.2%
( 87
 
10.1%
) 87
 
10.1%
스 53
 
6.1%
지 39
 
4.5%
로 34
 
3.9%
이 24
 
2.8%
운 20
 
2.3%
물 18
 
2.1%
류 16
 
1.8%
Other values (128) 390
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 680
78.6%
Open Punctuation 87
 
10.1%
Close Punctuation 87
 
10.1%
Space Separator 9
 
1.0%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 97
 
14.3%
스 53
 
7.8%
지 39
 
5.7%
로 34
 
5.0%
이 24
 
3.5%
운 20
 
2.9%
물 18
 
2.6%
류 16
 
2.4%
수 15
 
2.2%
에 14
 
2.1%
Other values (124) 350
51.5%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Decimal Number
ValueCountFrequency (%)
8 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 680
78.6%
Common 185
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 97
 
14.3%
스 53
 
7.8%
지 39
 
5.7%
로 34
 
5.0%
이 24
 
3.5%
운 20
 
2.9%
물 18
 
2.6%
류 16
 
2.4%
수 15
 
2.2%
에 14
 
2.1%
Other values (124) 350
51.5%
Common
ValueCountFrequency (%)
( 87
47.0%
) 87
47.0%
9
 
4.9%
8 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 680
78.6%
ASCII 185
 
21.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 97
 
14.3%
스 53
 
7.8%
지 39
 
5.7%
로 34
 
5.0%
이 24
 
3.5%
운 20
 
2.9%
물 18
 
2.6%
류 16
 
2.4%
수 15
 
2.2%
에 14
 
2.1%
Other values (124) 350
51.5%
ASCII
ValueCountFrequency (%)
( 87
47.0%
) 87
47.0%
9
 
4.9%
8 2
 
1.1%

사용본거지 주소
Text

Distinct53
Distinct (%)52.5%
Missing1
Missing (%)1.0%
Memory size948.0 B
2023-12-13T07:34:32.143889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length17.960396
Min length13

Characters and Unicode

Total characters1814
Distinct characters69
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

Unique37 ?
Unique (%)36.6%

Sample

1st row서울특별시 송파구 위례순환로 478
2nd row서울특별시 송파구 법원로4길 10
3rd row서울특별시 송파구 송파대로37길 44
4th row서울특별시 송파구 송파대로 167
5th row서울특별시 송파구 양재대로 932
ValueCountFrequency (%)
서울특별시 100
24.9%
송파구 100
24.9%
법원로 22
 
5.5%
114 17
 
4.2%
송파대로 15
 
3.7%
201 10
 
2.5%
법원로11길 8
 
2.0%
7 5
 
1.2%
11 4
 
1.0%
충민로 4
 
1.0%
Other values (75) 116
28.9%
2023-12-13T07:34:32.627414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
300
16.5%
송 119
 
6.6%
파 119
 
6.6%
구 102
 
5.6%
서 101
 
5.6%
시 101
 
5.6%
특 100
 
5.5%
별 100
 
5.5%
울 100
 
5.5%
1 99
 
5.5%
Other values (59) 573
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1199
66.1%
Decimal Number 309
 
17.0%
Space Separator 300
 
16.5%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
송 119
9.9%
파 119
9.9%
구 102
8.5%
서 101
8.4%
시 101
8.4%
특 100
8.3%
별 100
8.3%
울 100
8.3%
로 98
8.2%
길 36
 
3.0%
Other values (47) 223
18.6%
Decimal Number
ValueCountFrequency (%)
1 99
32.0%
2 55
17.8%
4 29
 
9.4%
3 24
 
7.8%
0 23
 
7.4%
7 18
 
5.8%
6 17
 
5.5%
8 16
 
5.2%
5 16
 
5.2%
9 12
 
3.9%
Space Separator
ValueCountFrequency (%)
300
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1199
66.1%
Common 615
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
송 119
9.9%
파 119
9.9%
구 102
8.5%
서 101
8.4%
시 101
8.4%
특 100
8.3%
별 100
8.3%
울 100
8.3%
로 98
8.2%
길 36
 
3.0%
Other values (47) 223
18.6%
Common
ValueCountFrequency (%)
300
48.8%
1 99
 
16.1%
2 55
 
8.9%
4 29
 
4.7%
3 24
 
3.9%
0 23
 
3.7%
7 18
 
2.9%
6 17
 
2.8%
8 16
 
2.6%
5 16
 
2.6%
Other values (2) 18
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1199
66.1%
ASCII 615
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300
48.8%
1 99
 
16.1%
2 55
 
8.9%
4 29
 
4.7%
3 24
 
3.9%
0 23
 
3.7%
7 18
 
2.9%
6 17
 
2.8%
8 16
 
2.6%
5 16
 
2.6%
Other values (2) 18
 
2.9%
Hangul
ValueCountFrequency (%)
송 119
9.9%
파 119
9.9%
구 102
8.5%
서 101
8.4%
시 101
8.4%
특 100
8.3%
별 100
8.3%
울 100
8.3%
로 98
8.2%
길 36
 
3.0%
Other values (47) 223
18.6%

사용본거지 상세주소
Text

Distinct77
Distinct (%)76.2%
Missing1
Missing (%)1.0%
Memory size948.0 B
2023-12-13T07:34:32.928870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length17.267327
Min length5

Characters and Unicode

Total characters1744
Distinct characters128
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

Unique64 ?
Unique (%)63.4%

Sample

1st row3층 310호 (장지동)
2nd row208호 (문정동)
3rd row1층 (석촌동)
4th row에이동 223호 (문정동)
5th row농수산물도매시장내 청과물시장동 2층 30-1호 (가락동)
ValueCountFrequency (%)
문정동 51
 
16.5%
에이동 22
 
7.1%
1310호 12
 
3.9%
3층 9
 
2.9%
제비동 9
 
2.9%
방이동 8
 
2.6%
씨동 8
 
2.6%
가락동 8
 
2.6%
301호 8
 
2.6%
현대엠스테이트 7
 
2.3%
Other values (118) 167
54.0%
2023-12-13T07:34:33.419876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
11.9%
동 153
 
8.8%
) 100
 
5.7%
( 100
 
5.7%
1 91
 
5.2%
호 91
 
5.2%
0 73
 
4.2%
정 63
 
3.6%
문 62
 
3.6%
이 62
 
3.6%
Other values (118) 741
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 912
52.3%
Decimal Number 360
 
20.6%
Space Separator 208
 
11.9%
Close Punctuation 100
 
5.7%
Open Punctuation 100
 
5.7%
Other Punctuation 44
 
2.5%
Dash Punctuation 17
 
1.0%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 153
16.8%
호 91
 
10.0%
정 63
 
6.9%
문 62
 
6.8%
이 62
 
6.8%
에 29
 
3.2%
층 28
 
3.1%
스 23
 
2.5%
트 22
 
2.4%
테 19
 
2.1%
Other values (101) 360
39.5%
Decimal Number
ValueCountFrequency (%)
1 91
25.3%
0 73
20.3%
3 61
16.9%
2 51
14.2%
8 18
 
5.0%
7 17
 
4.7%
4 16
 
4.4%
6 15
 
4.2%
5 11
 
3.1%
9 7
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
208
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Other Punctuation
ValueCountFrequency (%)
, 44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 912
52.3%
Common 829
47.5%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 153
16.8%
호 91
 
10.0%
정 63
 
6.9%
문 62
 
6.8%
이 62
 
6.8%
에 29
 
3.2%
층 28
 
3.1%
스 23
 
2.5%
트 22
 
2.4%
테 19
 
2.1%
Other values (101) 360
39.5%
Common
ValueCountFrequency (%)
208
25.1%
) 100
12.1%
( 100
12.1%
1 91
11.0%
0 73
 
8.8%
3 61
 
7.4%
2 51
 
6.2%
, 44
 
5.3%
8 18
 
2.2%
7 17
 
2.1%
Other values (5) 66
 
8.0%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 912
52.3%
ASCII 832
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
25.0%
) 100
12.0%
( 100
12.0%
1 91
10.9%
0 73
 
8.8%
3 61
 
7.3%
2 51
 
6.1%
, 44
 
5.3%
8 18
 
2.2%
7 17
 
2.0%
Other values (7) 69
 
8.3%
Hangul
ValueCountFrequency (%)
동 153
16.8%
호 91
 
10.0%
정 63
 
6.9%
문 62
 
6.8%
이 62
 
6.8%
에 29
 
3.2%
층 28
 
3.1%
스 23
 
2.5%
트 22
 
2.4%
테 19
 
2.1%
Other values (101) 360
39.5%

운영여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
정상
101 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0196078
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 101
99.0%
<NA> 1
 
1.0%

Length

2023-12-13T07:34:33.595099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:34:33.703024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 101
99.0%
na 1
 
1.0%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
법인
101 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0196078
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
법인 101
99.0%
<NA> 1
 
1.0%

Length

2023-12-13T07:34:33.837788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:34:33.965487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
법인 101
99.0%
na 1
 
1.0%

Interactions

2023-12-13T07:34:30.270833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:34:34.022950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명사용본거지 주소사용본거지 상세주소
연번1.0000.8510.0430.682
업체명0.8511.0000.9990.999
사용본거지 주소0.0430.9991.0001.000
사용본거지 상세주소0.6820.9991.0001.000
2023-12-13T07:34:34.134159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영여부업종명비고
운영여부1.0001.0001.000
업종명1.0001.0001.000
비고1.0001.0001.000
2023-12-13T07:34:34.226196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종명운영여부비고
연번1.0001.0001.0001.000
업종명1.0001.0001.0001.000
운영여부1.0001.0001.0001.000
비고1.0001.0001.0001.000

Missing values

2023-12-13T07:34:30.372406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:34:30.478570image/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.
2023-12-13T07:34:30.616881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업종명업체명사용본거지 주소사용본거지 상세주소운영여부비고
01일반화물주식회사 유한로지스서울특별시 송파구 위례순환로 4783층 310호 (장지동)정상법인
12일반화물주식회사 카고앤잡로지스서울특별시 송파구 법원로4길 10208호 (문정동)정상법인
23일반화물(주)이사의명가서울특별시 송파구 송파대로37길 441층 (석촌동)정상법인
34일반화물88더브레이브 주식회사서울특별시 송파구 송파대로 167에이동 223호 (문정동)정상법인
45일반화물디디라인 주식회사서울특별시 송파구 양재대로 932농수산물도매시장내 청과물시장동 2층 30-1호 (가락동)정상법인
56일반화물(주)아주육운서울특별시 송파구 법원로 114엠스테이트오피스텔 씨동 1246호 (문정동)정상법인
67일반화물한성양행서울특별시 송파구 법원로 128비동 1405호 (문정동, 에스케이브이원지엘메트로시티)정상법인
78일반화물한일통운서울특별시 송파구 송파대로28길 6901호 (가락동, 뉴훼밀리2차오피스텔)정상법인
89일반화물삼정화물운수(주)서울특별시 송파구 위례성대로 98301호 (방이동, 삼공빌딩)정상법인
910일반화물(주)밴스특송서울특별시 송파구 위례성대로 98301호 (방이동, 삼공빌딩)정상법인
연번업종명업체명사용본거지 주소사용본거지 상세주소운영여부비고
9293일반화물(주)제이앤엘로지스틱스서울특별시 송파구 법원로 114에이동 1310호 (문정동, 현대엠스테이트)정상법인
9394일반화물(주)이든종합물류서울특별시 송파구 새말로 122301호 (문정동)정상법인
9495일반화물(주)더반야로지스서울특별시 송파구 충민로 66제8층 제티-8030호 (문정동)정상법인
9596일반화물(주)신성통운서울특별시 송파구 올림픽로30길 10428호 (방이동)정상법인
9697일반화물(주)엘제이로지스틱스서울특별시 송파구 충민로 52에이508호 (문정동, 가든파이브웍스동)정상법인
9798일반화물(주)유앤아이로지스서울특별시 송파구 송파대로 201B동 906호 (문정동,테라타워2)정상법인
9899일반화물주식회사 왕창운수서울특별시 송파구 동남로23길 20301호 (오금동)정상법인
99100일반화물한솔로지스유(주)서울특별시 송파구 중대로 803층 (문정동, 문정프라자)정상법인
100101일반화물주식회사 정운로지스서울특별시 송파구 송파대로40길 3지하1층 1호 (송파동, 삼호빌딩)정상법인
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