Overview

Dataset statistics

Number of variables6
Number of observations41
Missing cells3
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory52.2 B

Variable types

Numeric1
Text2
Categorical3

Dataset

Description서울특별시 금천구 일반화물운송사업체 현황에 관한 정보로 업체명, 면허종류, 주소, 운영여부, 데이터 기준일자 등을 제공합니다.
URLhttps://www.data.go.kr/data/15115272/fileData.do

Alerts

운영여부 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
면허종류 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
데이터 기준일자 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 면허종류 and 2 other fieldsHigh correlation
면허종류 is highly imbalanced (83.5%)Imbalance
운영여부 is highly imbalanced (83.5%)Imbalance
데이터 기준일자 is highly imbalanced (83.5%)Imbalance
연번 has 1 (2.4%) missing valuesMissing
업체명 has 1 (2.4%) missing valuesMissing
주소 has 1 (2.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 12:46:43.491752
Analysis finished2023-12-12 12:46:44.284184
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)100.0%
Missing1
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T21:46:44.366423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T21:46:44.509553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.4%
22 1
 
2.4%
24 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
Other values (30) 30
73.2%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%
32 1
2.4%
31 1
2.4%

업체명
Text

MISSING 

Distinct40
Distinct (%)100.0%
Missing1
Missing (%)2.4%
Memory size460.0 B
2023-12-12T21:46:44.769356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.875
Min length5

Characters and Unicode

Total characters355
Distinct characters95
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
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 row디엔엘그룹(주)
2nd row(주)데오로지스
3rd row(주)다학
4th row(주)브릿지월드로지스틱스
5th row한신통운(주)
ValueCountFrequency (%)
디엔엘그룹(주 1
 
2.5%
주)데오로지스 1
 
2.5%
주)대림종합운수 1
 
2.5%
주)문화로지스 1
 
2.5%
주)아이엠이로지스 1
 
2.5%
에스에이치통운(주 1
 
2.5%
주)후지로지스틱스 1
 
2.5%
주)거성물류 1
 
2.5%
주)로지스퀘어 1
 
2.5%
주)아시안타이거즈트랜스팩 1
 
2.5%
Other values (30) 30
75.0%
2023-12-12T21:46:45.144287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 38
 
10.7%
주 38
 
10.7%
) 38
 
10.7%
스 35
 
9.9%
지 22
 
6.2%
로 19
 
5.4%
이 11
 
3.1%
에 11
 
3.1%
틱 6
 
1.7%
비 4
 
1.1%
Other values (85) 133
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 277
78.0%
Open Punctuation 38
 
10.7%
Close Punctuation 38
 
10.7%
Other Symbol 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 38
 
13.7%
스 35
 
12.6%
지 22
 
7.9%
로 19
 
6.9%
이 11
 
4.0%
에 11
 
4.0%
틱 6
 
2.2%
비 4
 
1.4%
운 4
 
1.4%
신 4
 
1.4%
Other values (82) 123
44.4%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 279
78.6%
Common 76
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 38
 
13.6%
스 35
 
12.5%
지 22
 
7.9%
로 19
 
6.8%
이 11
 
3.9%
에 11
 
3.9%
틱 6
 
2.2%
비 4
 
1.4%
운 4
 
1.4%
신 4
 
1.4%
Other values (83) 125
44.8%
Common
ValueCountFrequency (%)
( 38
50.0%
) 38
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 277
78.0%
ASCII 76
 
21.4%
None 2
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 38
50.0%
) 38
50.0%
Hangul
ValueCountFrequency (%)
주 38
 
13.7%
스 35
 
12.6%
지 22
 
7.9%
로 19
 
6.9%
이 11
 
4.0%
에 11
 
4.0%
틱 6
 
2.2%
비 4
 
1.4%
운 4
 
1.4%
신 4
 
1.4%
Other values (82) 123
44.4%
None
ValueCountFrequency (%)
㈜ 2
100.0%

면허종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
일반
40 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0487805
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
일반 40
97.6%
<NA> 1
 
2.4%

Length

2023-12-12T21:46:45.277168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:46:45.383211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 40
97.6%
na 1
 
2.4%

주소
Text

MISSING 

Distinct37
Distinct (%)92.5%
Missing1
Missing (%)2.4%
Memory size460.0 B
2023-12-12T21:46:45.597967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length44.5
Mean length36.65
Min length21

Characters and Unicode

Total characters1466
Distinct characters121
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)85.0%

Sample

1st row서울특별시 금천구 가산디지털2로 101 9층 비908호 (가산동)
2nd row서울특별시 금천구 디지털로 154 3층 (가산동)
3rd row서울특별시 금천구 디지털로 154 3층 (가산동)
4th row서울특별시 금천구 가산디지털2로 46 511호 (가산동)
5th row서울특별시 금천구 시흥대로73길 67 1011호 (시흥동)
ValueCountFrequency (%)
서울특별시 39
 
15.2%
금천구 39
 
15.2%
가산동 20
 
7.8%
가산디지털1로 10
 
3.9%
시흥동 9
 
3.5%
가산디지털2로 5
 
1.9%
67 5
 
1.9%
독산동 5
 
1.9%
3층 4
 
1.6%
시흥대로73길 4
 
1.6%
Other values (102) 117
45.5%
2023-12-12T21:46:45.984962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
258
 
17.6%
1 73
 
5.0%
시 58
 
4.0%
산 53
 
3.6%
동 45
 
3.1%
가 44
 
3.0%
금 41
 
2.8%
천 40
 
2.7%
울 39
 
2.7%
서 39
 
2.7%
Other values (111) 776
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 818
55.8%
Decimal Number 286
 
19.5%
Space Separator 258
 
17.6%
Close Punctuation 38
 
2.6%
Open Punctuation 38
 
2.6%
Other Punctuation 20
 
1.4%
Dash Punctuation 7
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 58
 
7.1%
산 53
 
6.5%
동 45
 
5.5%
가 44
 
5.4%
금 41
 
5.0%
천 40
 
4.9%
울 39
 
4.8%
서 39
 
4.8%
별 39
 
4.8%
특 39
 
4.8%
Other values (95) 381
46.6%
Decimal Number
ValueCountFrequency (%)
1 73
25.5%
2 36
12.6%
0 34
11.9%
5 28
 
9.8%
3 27
 
9.4%
7 22
 
7.7%
6 21
 
7.3%
9 17
 
5.9%
4 16
 
5.6%
8 12
 
4.2%
Space Separator
ValueCountFrequency (%)
258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 818
55.8%
Common 648
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 58
 
7.1%
산 53
 
6.5%
동 45
 
5.5%
가 44
 
5.4%
금 41
 
5.0%
천 40
 
4.9%
울 39
 
4.8%
서 39
 
4.8%
별 39
 
4.8%
특 39
 
4.8%
Other values (95) 381
46.6%
Common
ValueCountFrequency (%)
258
39.8%
1 73
 
11.3%
) 38
 
5.9%
( 38
 
5.9%
2 36
 
5.6%
0 34
 
5.2%
5 28
 
4.3%
3 27
 
4.2%
7 22
 
3.4%
6 21
 
3.2%
Other values (6) 73
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 818
55.8%
ASCII 648
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
258
39.8%
1 73
 
11.3%
) 38
 
5.9%
( 38
 
5.9%
2 36
 
5.6%
0 34
 
5.2%
5 28
 
4.3%
3 27
 
4.2%
7 22
 
3.4%
6 21
 
3.2%
Other values (6) 73
 
11.3%
Hangul
ValueCountFrequency (%)
시 58
 
7.1%
산 53
 
6.5%
동 45
 
5.5%
가 44
 
5.4%
금 41
 
5.0%
천 40
 
4.9%
울 39
 
4.8%
서 39
 
4.8%
별 39
 
4.8%
특 39
 
4.8%
Other values (95) 381
46.6%

운영여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
운영중
40 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0243902
Min length3

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 40
97.6%
<NA> 1
 
2.4%

Length

2023-12-12T21:46:46.112343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:46:46.220638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 40
97.6%
na 1
 
2.4%

데이터 기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-06-16
40 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.8536585
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row2023-06-16
2nd row2023-06-16
3rd row2023-06-16
4th row2023-06-16
5th row2023-06-16

Common Values

ValueCountFrequency (%)
2023-06-16 40
97.6%
<NA> 1
 
2.4%

Length

2023-12-12T21:46:46.343700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:46:46.473799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-16 40
97.6%
na 1
 
2.4%

Interactions

2023-12-12T21:46:43.750636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:46:46.559255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명주소
연번1.0001.0000.978
업체명1.0001.0001.000
주소0.9781.0001.000
2023-12-12T21:46:46.678275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영여부면허종류데이터 기준일자
운영여부1.0001.0001.000
면허종류1.0001.0001.000
데이터 기준일자1.0001.0001.000
2023-12-12T21:46:46.791173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면허종류운영여부데이터 기준일자
연번1.0001.0001.0001.000
면허종류1.0001.0001.0001.000
운영여부1.0001.0001.0001.000
데이터 기준일자1.0001.0001.0001.000

Missing values

2023-12-12T21:46:43.942099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:46:44.067915image/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.
2023-12-12T21:46:44.206004image/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

연번업체명면허종류주소운영여부데이터 기준일자
01디엔엘그룹(주)일반서울특별시 금천구 가산디지털2로 101 9층 비908호 (가산동)운영중2023-06-16
12(주)데오로지스일반서울특별시 금천구 디지털로 154 3층 (가산동)운영중2023-06-16
23(주)다학일반서울특별시 금천구 디지털로 154 3층 (가산동)운영중2023-06-16
34(주)브릿지월드로지스틱스일반서울특별시 금천구 가산디지털2로 46 511호 (가산동)운영중2023-06-16
45한신통운(주)일반서울특별시 금천구 시흥대로73길 67 1011호 (시흥동)운영중2023-06-16
56대원냉동(주)일반서울특별시 금천구 가산디지털1로 168 비동 1411호(가산동,우림라이온스밸리)운영중2023-06-16
67신한종합물류(주)일반서울특별시 금천구 가마산로 96 1203호 (가산동, 대륭테크노타운8차)운영중2023-06-16
78동양통운(주)일반서울특별시 금천구 시흥대로73길 67 1011호 (시흥동)운영중2023-06-16
89(주)이삭로지스틱일반서울특별시 금천구 독산로22가길 3-3 101호 (시흥동)운영중2023-06-16
910(주)코리아로지스일반서울특별시 금천구 가산디지털1로 145 508호,605호~607호,802호,1504호 (가산동,에이스하이엔드타워3차)운영중2023-06-16
연번업체명면허종류주소운영여부데이터 기준일자
3132(주)투제이비씨엘일반서울특별시 금천구 벚꽃로 286 1008호 (가산동, 삼성리더스타워)운영중2023-06-16
3233(주)경일로지스틱일반서울특별시 금천구 두산로 70 219호 (독산동, 현대지식산업센터)운영중2023-06-16
3334이안로지스틱스(주)일반서울특별시 금천구 디지털로 154 (가산동)운영중2023-06-16
3435한빛물류(주)일반서울특별시 금천구 시흥대로59길 35 301호 (시흥동, 건영아파트상가)운영중2023-06-16
3536(주)에스엠로지스일반서울특별시 금천구 가산디지털1로 24 903호 (가산동, 대륭테크로타운13차)운영중2023-06-16
3637제너럴로지스(주)일반서울특별시 금천구 가산디지털2로 165 706호 (가산동, 백상스타타워2차)운영중2023-06-16
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