Overview

Dataset statistics

Number of variables7
Number of observations41
Missing cells46
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory60.2 B

Variable types

Text4
Categorical2
Numeric1

Dataset

Description경기도 오산시 화물자동차 운수업체 업체 현황(상호, 업종, 보유대수, 차종, 주사무소 주소, 전화번호 등)을 제공합니다.
URLhttps://www.data.go.kr/data/15114838/fileData.do

Alerts

업종 has constant value ""Constant
기준일자 has constant value ""Constant
전화번호 has 22 (53.7%) missing valuesMissing
팩스번호 has 24 (58.5%) missing valuesMissing
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:44:16.890312
Analysis finished2023-12-12 10:44:17.774804
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T19:44:18.019690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length7.4146341
Min length4

Characters and Unicode

Total characters304
Distinct characters88
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row조일로지스(주)
2nd row㈜에스에이치오일
3rd row(주)진명로지스
4th row(주)신강물류
5th row(주)호동물류
ValueCountFrequency (%)
조일로지스(주 1
 
2.4%
대한환경(주 1
 
2.4%
봉화운수 1
 
2.4%
오산동탄호룡고소작업차&스카이차 1
 
2.4%
주)홍스카이 1
 
2.4%
경민스카이 1
 
2.4%
신우물류(주 1
 
2.4%
주)해피로지스 1
 
2.4%
주은물류(주 1
 
2.4%
주)에코로지스 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T19:44:18.558374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 33
 
10.9%
( 32
 
10.5%
) 32
 
10.5%
스 23
 
7.6%
지 14
 
4.6%
로 13
 
4.3%
이 11
 
3.6%
물 8
 
2.6%
류 8
 
2.6%
카 6
 
2.0%
Other values (78) 124
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 234
77.0%
Open Punctuation 32
 
10.5%
Close Punctuation 32
 
10.5%
Other Symbol 2
 
0.7%
Uppercase Letter 2
 
0.7%
Other Punctuation 1
 
0.3%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 33
 
14.1%
스 23
 
9.8%
지 14
 
6.0%
로 13
 
5.6%
이 11
 
4.7%
물 8
 
3.4%
류 8
 
3.4%
카 6
 
2.6%
에 6
 
2.6%
한 4
 
1.7%
Other values (71) 108
46.2%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 236
77.6%
Common 66
 
21.7%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 33
 
14.0%
스 23
 
9.7%
지 14
 
5.9%
로 13
 
5.5%
이 11
 
4.7%
물 8
 
3.4%
류 8
 
3.4%
카 6
 
2.5%
에 6
 
2.5%
한 4
 
1.7%
Other values (72) 110
46.6%
Common
ValueCountFrequency (%)
( 32
48.5%
) 32
48.5%
& 1
 
1.5%
1
 
1.5%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 234
77.0%
ASCII 68
 
22.4%
None 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 33
 
14.1%
스 23
 
9.8%
지 14
 
6.0%
로 13
 
5.6%
이 11
 
4.7%
물 8
 
3.4%
류 8
 
3.4%
카 6
 
2.6%
에 6
 
2.6%
한 4
 
1.7%
Other values (71) 108
46.2%
ASCII
ValueCountFrequency (%)
( 32
47.1%
) 32
47.1%
& 1
 
1.5%
K 1
 
1.5%
S 1
 
1.5%
1
 
1.5%
None
ValueCountFrequency (%)
㈜ 2
100.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
일반화물
41 

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 41
100.0%

Length

2023-12-12T19:44:18.757673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:18.905996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화물 41
100.0%

보유대수
Real number (ℝ)

Distinct16
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.195122
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-12T19:44:19.064434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q38
95-th percentile33
Maximum55
Range54
Interquartile range (IQR)6

Descriptive statistics

Standard deviation11.628025
Coefficient of variation (CV)1.418896
Kurtosis6.1961018
Mean8.195122
Median Absolute Deviation (MAD)2
Skewness2.4384096
Sum336
Variance135.21098
MonotonicityNot monotonic
2023-12-12T19:44:19.243928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 13
31.7%
1 5
 
12.2%
5 3
 
7.3%
4 3
 
7.3%
3 3
 
7.3%
8 3
 
7.3%
6 2
 
4.9%
27 1
 
2.4%
7 1
 
2.4%
33 1
 
2.4%
Other values (6) 6
14.6%
ValueCountFrequency (%)
1 5
 
12.2%
2 13
31.7%
3 3
 
7.3%
4 3
 
7.3%
5 3
 
7.3%
6 2
 
4.9%
7 1
 
2.4%
8 3
 
7.3%
9 1
 
2.4%
19 1
 
2.4%
ValueCountFrequency (%)
55 1
 
2.4%
34 1
 
2.4%
33 1
 
2.4%
27 1
 
2.4%
25 1
 
2.4%
24 1
 
2.4%
19 1
 
2.4%
9 1
 
2.4%
8 3
7.3%
7 1
 
2.4%

주사무소도로명주소
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-12T19:44:19.637430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length32.292683
Min length19

Characters and Unicode

Total characters1324
Distinct characters115
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

Unique39 ?
Unique (%)95.1%

Sample

1st row경기도 오산시 독산성로 425, 더퍼스트타워세교 1024, 1025호 (세교동)
2nd row경기도 오산시 대호로 83, 드라마타워 802호 (궐동)
3rd row경기도 오산시 남부대로 430-12, 106동 402호 (고현동,아이파크아파트)
4th row경기도 오산시 동부대로 429-3, 3층 (원동)
5th row경기도 오산시 경기대로 227, 2층 205-2호 (원동, 우경싸이트빌)
ValueCountFrequency (%)
경기도 41
 
15.4%
오산시 41
 
15.4%
원동 11
 
4.1%
3층 5
 
1.9%
세교동 4
 
1.5%
궐동 4
 
1.5%
독산성로 4
 
1.5%
남부대로 4
 
1.5%
대호로 3
 
1.1%
2층 3
 
1.1%
Other values (126) 147
55.1%
2023-12-12T19:44:20.211676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
 
17.1%
동 60
 
4.5%
산 58
 
4.4%
오 51
 
3.9%
경 47
 
3.5%
, 47
 
3.5%
기 46
 
3.5%
1 45
 
3.4%
2 44
 
3.3%
시 43
 
3.2%
Other values (105) 657
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 693
52.3%
Decimal Number 258
 
19.5%
Space Separator 226
 
17.1%
Other Punctuation 47
 
3.5%
Open Punctuation 42
 
3.2%
Close Punctuation 42
 
3.2%
Dash Punctuation 14
 
1.1%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 60
 
8.7%
산 58
 
8.4%
오 51
 
7.4%
경 47
 
6.8%
기 46
 
6.6%
시 43
 
6.2%
로 41
 
5.9%
도 41
 
5.9%
호 26
 
3.8%
대 18
 
2.6%
Other values (88) 262
37.8%
Decimal Number
ValueCountFrequency (%)
1 45
17.4%
2 44
17.1%
0 36
14.0%
4 35
13.6%
3 28
10.9%
8 17
 
6.6%
6 16
 
6.2%
9 15
 
5.8%
5 13
 
5.0%
7 9
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
226
100.0%
Other Punctuation
ValueCountFrequency (%)
, 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 693
52.3%
Common 629
47.5%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 60
 
8.7%
산 58
 
8.4%
오 51
 
7.4%
경 47
 
6.8%
기 46
 
6.6%
시 43
 
6.2%
로 41
 
5.9%
도 41
 
5.9%
호 26
 
3.8%
대 18
 
2.6%
Other values (88) 262
37.8%
Common
ValueCountFrequency (%)
226
35.9%
, 47
 
7.5%
1 45
 
7.2%
2 44
 
7.0%
( 42
 
6.7%
) 42
 
6.7%
0 36
 
5.7%
4 35
 
5.6%
3 28
 
4.5%
8 17
 
2.7%
Other values (5) 67
 
10.7%
Latin
ValueCountFrequency (%)
L 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 693
52.3%
ASCII 631
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
35.8%
, 47
 
7.4%
1 45
 
7.1%
2 44
 
7.0%
( 42
 
6.7%
) 42
 
6.7%
0 36
 
5.7%
4 35
 
5.5%
3 28
 
4.4%
8 17
 
2.7%
Other values (7) 69
 
10.9%
Hangul
ValueCountFrequency (%)
동 60
 
8.7%
산 58
 
8.4%
오 51
 
7.4%
경 47
 
6.8%
기 46
 
6.6%
시 43
 
6.2%
로 41
 
5.9%
도 41
 
5.9%
호 26
 
3.8%
대 18
 
2.6%
Other values (88) 262
37.8%

전화번호
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing22
Missing (%)53.7%
Memory size460.0 B
2023-12-12T19:44:20.454887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.947368
Min length11

Characters and Unicode

Total characters227
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)89.5%

Sample

1st row031-664-8667
2nd row032-675-7014
3rd row031-662-5873
4th row031-378-8225
5th row031-377-0485
ValueCountFrequency (%)
031-664-8667 2
 
10.5%
02-572-1568 1
 
5.3%
031-377-3311 1
 
5.3%
031-377-9988 1
 
5.3%
031-377-8511 1
 
5.3%
031-376-0940 1
 
5.3%
031-378-8530 1
 
5.3%
031-374-2333 1
 
5.3%
031-375-2885 1
 
5.3%
031-339-7500 1
 
5.3%
Other values (8) 8
42.1%
2023-12-12T19:44:20.837388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 43
18.9%
- 38
16.7%
0 27
11.9%
1 26
11.5%
7 25
11.0%
6 16
 
7.0%
8 16
 
7.0%
5 14
 
6.2%
2 10
 
4.4%
4 7
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 43
22.8%
0 27
14.3%
1 26
13.8%
7 25
13.2%
6 16
 
8.5%
8 16
 
8.5%
5 14
 
7.4%
2 10
 
5.3%
4 7
 
3.7%
9 5
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 43
18.9%
- 38
16.7%
0 27
11.9%
1 26
11.5%
7 25
11.0%
6 16
 
7.0%
8 16
 
7.0%
5 14
 
6.2%
2 10
 
4.4%
4 7
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 43
18.9%
- 38
16.7%
0 27
11.9%
1 26
11.5%
7 25
11.0%
6 16
 
7.0%
8 16
 
7.0%
5 14
 
6.2%
2 10
 
4.4%
4 7
 
3.1%

팩스번호
Text

MISSING 

Distinct15
Distinct (%)88.2%
Missing24
Missing (%)58.5%
Memory size460.0 B
2023-12-12T19:44:21.080264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.941176
Min length11

Characters and Unicode

Total characters203
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)76.5%

Sample

1st row031-372-4051
2nd row032-675-7017
3rd row031-662-5874
4th row031-378-8540
5th row031-458-1591
ValueCountFrequency (%)
031-372-4051 2
 
11.8%
031-378-8540 2
 
11.8%
032-675-7017 1
 
5.9%
031-662-5874 1
 
5.9%
031-458-1591 1
 
5.9%
031-378-0485 1
 
5.9%
031-378-5423 1
 
5.9%
031-376-6137 1
 
5.9%
02-577-7178 1
 
5.9%
031-372-3679 1
 
5.9%
Other values (5) 5
29.4%
2023-12-12T19:44:21.500004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 34
16.7%
- 34
16.7%
7 25
12.3%
1 24
11.8%
0 23
11.3%
8 16
7.9%
5 15
7.4%
2 11
 
5.4%
4 9
 
4.4%
6 9
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 169
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 34
20.1%
7 25
14.8%
1 24
14.2%
0 23
13.6%
8 16
9.5%
5 15
8.9%
2 11
 
6.5%
4 9
 
5.3%
6 9
 
5.3%
9 3
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 34
16.7%
- 34
16.7%
7 25
12.3%
1 24
11.8%
0 23
11.3%
8 16
7.9%
5 15
7.4%
2 11
 
5.4%
4 9
 
4.4%
6 9
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 34
16.7%
- 34
16.7%
7 25
12.3%
1 24
11.8%
0 23
11.3%
8 16
7.9%
5 15
7.4%
2 11
 
5.4%
4 9
 
4.4%
6 9
 
4.4%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-05-31
41 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-31
2nd row2023-05-31
3rd row2023-05-31
4th row2023-05-31
5th row2023-05-31

Common Values

ValueCountFrequency (%)
2023-05-31 41
100.0%

Length

2023-12-12T19:44:21.673854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:44:21.823637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-31 41
100.0%

Interactions

2023-12-12T19:44:17.255288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:44:21.902693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호보유대수주사무소도로명주소전화번호팩스번호
상호1.0001.0001.0001.0001.000
보유대수1.0001.0000.0001.0000.854
주사무소도로명주소1.0000.0001.0000.9791.000
전화번호1.0001.0000.9791.0001.000
팩스번호1.0000.8541.0001.0001.000

Missing values

2023-12-12T19:44:17.391663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:44:17.555468image/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.
2023-12-12T19:44:17.701799image/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

상호업종보유대수주사무소도로명주소전화번호팩스번호기준일자
0조일로지스(주)일반화물27경기도 오산시 독산성로 425, 더퍼스트타워세교 1024, 1025호 (세교동)031-664-8667031-372-40512023-05-31
1㈜에스에이치오일일반화물19경기도 오산시 대호로 83, 드라마타워 802호 (궐동)032-675-7014032-675-70172023-05-31
2(주)진명로지스일반화물5경기도 오산시 남부대로 430-12, 106동 402호 (고현동,아이파크아파트)031-662-5873031-662-58742023-05-31
3(주)신강물류일반화물24경기도 오산시 동부대로 429-3, 3층 (원동)031-378-8225031-378-85402023-05-31
4(주)호동물류일반화물5경기도 오산시 경기대로 227, 2층 205-2호 (원동, 우경싸이트빌)<NA>031-458-15912023-05-31
5(주)웰쉐어로지스일반화물2경기도 오산시 삼미로47번길 82, 나동 (내삼미동)<NA><NA>2023-05-31
6최영물류(주)일반화물4경기도 오산시 원동로 22, 르마레시티 1동 1103호 (원동)<NA><NA>2023-05-31
7(주)정스카이일반화물3경기도 오산시 대호로 141, 403호 (궐동, 에스에스프라자)031-377-0485031-378-04852023-05-31
8(주)영로지스일반화물8경기도 오산시 밀머리로 97 (원동)031-370-5713<NA>2023-05-31
9신영환경(주)일반화물9경기도 오산시 궐리사로 38, 3층 (궐동, 하나)031-378-5421031-378-54232023-05-31
상호업종보유대수주사무소도로명주소전화번호팩스번호기준일자
31(주)아산지엘에스일반화물33경기도 오산시 동부대로 429-3, 3층 (원동)031-378-8530031-378-85402023-05-31
32KS로지스일반화물1경기도 오산시 오산로 91-5, 108동 901호 (갈곶동,한솔솔파크아파트)<NA><NA>2023-05-31
33(주)참물류일반화물2경기도 오산시 청학로 266-22, 명성 위드스타 811호 (수청동)<NA><NA>2023-05-31
34오산운수일반화물2경기도 오산시 서동로65번길 9 (서동)<NA><NA>2023-05-31
35정이운수일반화물2경기도 오산시 운암로 64, 108동 1504호 (오산동,대동아파트)<NA><NA>2023-05-31
36(주)가온이엔티일반화물6경기도 오산시 경기동로 161-9 (부산동)031-376-0940<NA>2023-05-31
37우리로지스틱(주)일반화물7경기도 오산시 원동로 6, 406호 (원동, 오산파크스퀘어)031-377-8511031-377-85132023-05-31
38(주)승리일반화물3경기도 오산시 발안로 1353-8, 101동 308호 (누읍동, 이림아파트)<NA><NA>2023-05-31
39(주)고속로지스일반화물4경기도 오산시 경기대로658번길 17, 3층 (내삼미동)031-377-9988031-378-24562023-05-31
40(주)스카이로지스일반화물5경기도 오산시 오산로 52, 2층 (갈곶동)031-372-3896031-372-38962023-05-31