Overview

Dataset statistics

Number of variables10
Number of observations266
Missing cells225
Missing cells (%)8.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.9 KiB
Average record size in memory80.5 B

Variable types

Categorical3
DateTime2
Text5

Dataset

Description경기도 용인시 화물자동차운송주선사업 허가업체 현황입니다. 인허가일자, 인허가번호, 업체명, 주소 등의 데이터를 제공합니다.※ 데이터기준일자 : 2024-04-25
Author경기도 용인시
URLhttps://www.data.go.kr/data/15113539/fileData.do

Alerts

시군명 has constant value ""Constant
영업상태 has constant value ""Constant
업종구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
도로명주소 has 4 (1.5%) missing valuesMissing
지번주소 has 10 (3.8%) missing valuesMissing
연락처 has 211 (79.3%) missing valuesMissing
인허가번호 has unique valuesUnique
업체명 has unique valuesUnique

Reproduction

Analysis started2024-04-29 23:08:59.280295
Analysis finished2024-04-29 23:09:00.374895
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
용인시
266 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 266
100.0%

Length

2024-04-30T08:09:00.435349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:09:00.519420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용인시 266
100.0%

인허가일자
Date

Distinct257
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1962-06-21 00:00:00
Maximum2022-05-26 00:00:00
2024-04-30T08:09:00.606982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:09:00.734474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가번호
Text

UNIQUE 

Distinct266
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T08:09:00.923055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters5586
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

Unique266 ?
Unique (%)100.0%

Sample

1st row4050000-2024-03-00003
2nd row4050000-2024-03-00002
3rd row4050000-2024-03-00001
4th row4050000-2023-03-00007
5th row4050000-2023-03-00006
ValueCountFrequency (%)
4050000-2024-03-00003 1
 
0.4%
4050000-1998-03-00025 1
 
0.4%
4050000-1999-03-00026 1
 
0.4%
4050000-1997-03-00035 1
 
0.4%
4050000-1999-03-00013 1
 
0.4%
4050000-1999-03-00011 1
 
0.4%
4050000-1999-03-00009 1
 
0.4%
4050000-1999-03-00008 1
 
0.4%
4050000-1999-03-00004 1
 
0.4%
4050000-1999-03-00002 1
 
0.4%
Other values (256) 256
96.2%
2024-04-30T08:09:01.227409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2802
50.2%
- 798
 
14.3%
3 364
 
6.5%
4 331
 
5.9%
5 330
 
5.9%
2 302
 
5.4%
9 252
 
4.5%
1 234
 
4.2%
7 60
 
1.1%
8 59
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4788
85.7%
Dash Punctuation 798
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2802
58.5%
3 364
 
7.6%
4 331
 
6.9%
5 330
 
6.9%
2 302
 
6.3%
9 252
 
5.3%
1 234
 
4.9%
7 60
 
1.3%
8 59
 
1.2%
6 54
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 798
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5586
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2802
50.2%
- 798
 
14.3%
3 364
 
6.5%
4 331
 
5.9%
5 330
 
5.9%
2 302
 
5.4%
9 252
 
4.5%
1 234
 
4.2%
7 60
 
1.1%
8 59
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2802
50.2%
- 798
 
14.3%
3 364
 
6.5%
4 331
 
5.9%
5 330
 
5.9%
2 302
 
5.4%
9 252
 
4.5%
1 234
 
4.2%
7 60
 
1.1%
8 59
 
1.1%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
영업
266 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 266
100.0%

Length

2024-04-30T08:09:01.352327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:09:01.436206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 266
100.0%

업종구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
화물운송주선
266 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
화물운송주선 266
100.0%

Length

2024-04-30T08:09:01.522211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T08:09:01.603503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화물운송주선 266
100.0%

업체명
Text

UNIQUE 

Distinct266
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-30T08:09:01.785767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.4398496
Min length2

Characters and Unicode

Total characters1979
Distinct characters241
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

Unique266 ?
Unique (%)100.0%

Sample

1st row(주)이안로지스
2nd row(주)엘루션
3rd row위카모빌리티 주식회사
4th row대원냉동운수(주)
5th row지앤비로지스(주)
ValueCountFrequency (%)
주식회사 16
 
5.6%
주)이안로지스 1
 
0.3%
지팩스(주 1
 
0.3%
한진운수 1
 
0.3%
주)에스앤에스물류 1
 
0.3%
삼성합동화물 1
 
0.3%
로지스원 1
 
0.3%
코리아 1
 
0.3%
제이디케이 1
 
0.3%
대명화물 1
 
0.3%
Other values (261) 261
91.3%
2024-04-30T08:09:02.149103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 192
 
9.7%
( 175
 
8.8%
) 175
 
8.8%
스 115
 
5.8%
물 93
 
4.7%
로 76
 
3.8%
지 76
 
3.8%
류 55
 
2.8%
화 41
 
2.1%
이 38
 
1.9%
Other values (231) 943
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1590
80.3%
Open Punctuation 175
 
8.8%
Close Punctuation 175
 
8.8%
Space Separator 20
 
1.0%
Uppercase Letter 10
 
0.5%
Decimal Number 5
 
0.3%
Other Symbol 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 192
 
12.1%
스 115
 
7.2%
물 93
 
5.8%
로 76
 
4.8%
지 76
 
4.8%
류 55
 
3.5%
화 41
 
2.6%
이 38
 
2.4%
운 34
 
2.1%
에 32
 
2.0%
Other values (215) 838
52.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
30.0%
J 2
20.0%
K 1
 
10.0%
D 1
 
10.0%
C 1
 
10.0%
T 1
 
10.0%
G 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
5 2
40.0%
6 1
20.0%
3 1
20.0%
2 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1593
80.5%
Common 376
 
19.0%
Latin 10
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 192
 
12.1%
스 115
 
7.2%
물 93
 
5.8%
로 76
 
4.8%
지 76
 
4.8%
류 55
 
3.5%
화 41
 
2.6%
이 38
 
2.4%
운 34
 
2.1%
에 32
 
2.0%
Other values (216) 841
52.8%
Common
ValueCountFrequency (%)
( 175
46.5%
) 175
46.5%
20
 
5.3%
5 2
 
0.5%
6 1
 
0.3%
3 1
 
0.3%
2 1
 
0.3%
. 1
 
0.3%
Latin
ValueCountFrequency (%)
S 3
30.0%
J 2
20.0%
K 1
 
10.0%
D 1
 
10.0%
C 1
 
10.0%
T 1
 
10.0%
G 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1590
80.3%
ASCII 386
 
19.5%
None 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 192
 
12.1%
스 115
 
7.2%
물 93
 
5.8%
로 76
 
4.8%
지 76
 
4.8%
류 55
 
3.5%
화 41
 
2.6%
이 38
 
2.4%
운 34
 
2.1%
에 32
 
2.0%
Other values (215) 838
52.7%
ASCII
ValueCountFrequency (%)
( 175
45.3%
) 175
45.3%
20
 
5.2%
S 3
 
0.8%
5 2
 
0.5%
J 2
 
0.5%
K 1
 
0.3%
D 1
 
0.3%
6 1
 
0.3%
3 1
 
0.3%
Other values (5) 5
 
1.3%
None
ValueCountFrequency (%)
㈜ 3
100.0%

도로명주소
Text

MISSING 

Distinct249
Distinct (%)95.0%
Missing4
Missing (%)1.5%
Memory size2.2 KiB
2024-04-30T08:09:02.425966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length32.534351
Min length21

Characters and Unicode

Total characters8524
Distinct characters238
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)90.8%

Sample

1st row경기도 용인시 기흥구 금화로 103, 정진프라자 5층 (상갈동)
2nd row경기도 용인시 처인구 남사읍 경기동로 316 (주)리바트 2층
3rd row경기도 용인시 기흥구 중부대로 242, 오토허브 A동 W117호 (영덕동)
4th row경기도 용인시 처인구 이동읍 백옥대로 664-10, 202호
5th row경기도 용인시 기흥구 기흥단지로 45, 4층 (고매동)
ValueCountFrequency (%)
경기도 262
 
14.0%
용인시 262
 
14.0%
처인구 139
 
7.4%
기흥구 103
 
5.5%
양지면 32
 
1.7%
2층 23
 
1.2%
수지구 20
 
1.1%
이동읍 18
 
1.0%
중부대로 16
 
0.9%
백암면 16
 
0.9%
Other values (549) 986
52.5%
2024-04-30T08:09:02.843324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1615
 
18.9%
인 411
 
4.8%
기 387
 
4.5%
구 291
 
3.4%
1 281
 
3.3%
경 274
 
3.2%
용 274
 
3.2%
시 264
 
3.1%
로 263
 
3.1%
도 262
 
3.1%
Other values (228) 4202
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4969
58.3%
Space Separator 1615
 
18.9%
Decimal Number 1350
 
15.8%
Other Punctuation 157
 
1.8%
Close Punctuation 151
 
1.8%
Open Punctuation 151
 
1.8%
Dash Punctuation 79
 
0.9%
Uppercase Letter 51
 
0.6%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 411
 
8.3%
기 387
 
7.8%
구 291
 
5.9%
경 274
 
5.5%
용 274
 
5.5%
시 264
 
5.3%
로 263
 
5.3%
도 262
 
5.3%
동 234
 
4.7%
처 143
 
2.9%
Other values (196) 2166
43.6%
Uppercase Letter
ValueCountFrequency (%)
T 7
13.7%
A 7
13.7%
I 5
9.8%
B 5
9.8%
R 4
7.8%
O 4
7.8%
U 4
7.8%
W 4
7.8%
E 3
5.9%
L 2
 
3.9%
Other values (6) 6
11.8%
Decimal Number
ValueCountFrequency (%)
1 281
20.8%
2 222
16.4%
0 163
12.1%
3 125
9.3%
4 124
9.2%
6 98
 
7.3%
5 94
 
7.0%
9 87
 
6.4%
7 86
 
6.4%
8 70
 
5.2%
Space Separator
ValueCountFrequency (%)
1615
100.0%
Other Punctuation
ValueCountFrequency (%)
, 157
100.0%
Close Punctuation
ValueCountFrequency (%)
) 151
100.0%
Open Punctuation
ValueCountFrequency (%)
( 151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4969
58.3%
Common 3503
41.1%
Latin 52
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 411
 
8.3%
기 387
 
7.8%
구 291
 
5.9%
경 274
 
5.5%
용 274
 
5.5%
시 264
 
5.3%
로 263
 
5.3%
도 262
 
5.3%
동 234
 
4.7%
처 143
 
2.9%
Other values (196) 2166
43.6%
Latin
ValueCountFrequency (%)
T 7
13.5%
A 7
13.5%
I 5
9.6%
B 5
9.6%
R 4
7.7%
O 4
7.7%
U 4
7.7%
W 4
7.7%
E 3
5.8%
L 2
 
3.8%
Other values (7) 7
13.5%
Common
ValueCountFrequency (%)
1615
46.1%
1 281
 
8.0%
2 222
 
6.3%
0 163
 
4.7%
, 157
 
4.5%
) 151
 
4.3%
( 151
 
4.3%
3 125
 
3.6%
4 124
 
3.5%
6 98
 
2.8%
Other values (5) 416
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4969
58.3%
ASCII 3554
41.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1615
45.4%
1 281
 
7.9%
2 222
 
6.2%
0 163
 
4.6%
, 157
 
4.4%
) 151
 
4.2%
( 151
 
4.2%
3 125
 
3.5%
4 124
 
3.5%
6 98
 
2.8%
Other values (21) 467
 
13.1%
Hangul
ValueCountFrequency (%)
인 411
 
8.3%
기 387
 
7.8%
구 291
 
5.9%
경 274
 
5.5%
용 274
 
5.5%
시 264
 
5.3%
로 263
 
5.3%
도 262
 
5.3%
동 234
 
4.7%
처 143
 
2.9%
Other values (196) 2166
43.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

지번주소
Text

MISSING 

Distinct231
Distinct (%)90.2%
Missing10
Missing (%)3.8%
Memory size2.2 KiB
2024-04-30T08:09:03.124344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length26.703125
Min length19

Characters and Unicode

Total characters6836
Distinct characters236
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)82.4%

Sample

1st row경기도 용인시 기흥구 상갈동 473 정진프라자
2nd row경기도 용인시 처인구 남사읍 북리 54-10 (주)리바트
3rd row경기도 용인시 기흥구 영덕동 1266 오토허브
4th row경기도 용인시 처인구 이동읍 천리 715
5th row경기도 용인시 기흥구 고매동 411-20 SK기흥단지주유소
ValueCountFrequency (%)
경기도 256
 
16.4%
용인시 256
 
16.4%
처인구 137
 
8.8%
기흥구 99
 
6.4%
양지면 32
 
2.1%
이동읍 27
 
1.7%
수지구 20
 
1.3%
양지리 16
 
1.0%
백암면 16
 
1.0%
남사읍 15
 
1.0%
Other values (413) 683
43.9%
2024-04-30T08:09:03.564309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1535
22.5%
인 401
 
5.9%
기 360
 
5.3%
구 269
 
3.9%
용 260
 
3.8%
시 258
 
3.8%
경 256
 
3.7%
도 256
 
3.7%
1 202
 
3.0%
동 187
 
2.7%
Other values (226) 2852
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3997
58.5%
Space Separator 1535
 
22.5%
Decimal Number 1076
 
15.7%
Dash Punctuation 178
 
2.6%
Uppercase Letter 43
 
0.6%
Other Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 401
 
10.0%
기 360
 
9.0%
구 269
 
6.7%
용 260
 
6.5%
시 258
 
6.5%
경 256
 
6.4%
도 256
 
6.4%
동 187
 
4.7%
처 137
 
3.4%
리 127
 
3.2%
Other values (195) 1486
37.2%
Uppercase Letter
ValueCountFrequency (%)
B 5
11.6%
I 5
11.6%
T 5
11.6%
A 4
9.3%
O 3
7.0%
K 3
7.0%
S 3
7.0%
U 3
7.0%
R 3
7.0%
E 2
 
4.7%
Other values (5) 7
16.3%
Decimal Number
ValueCountFrequency (%)
1 202
18.8%
2 137
12.7%
3 129
12.0%
4 122
11.3%
5 106
9.9%
0 96
8.9%
9 78
 
7.2%
6 75
 
7.0%
8 69
 
6.4%
7 62
 
5.8%
Space Separator
ValueCountFrequency (%)
1535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3997
58.5%
Common 2795
40.9%
Latin 44
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 401
 
10.0%
기 360
 
9.0%
구 269
 
6.7%
용 260
 
6.5%
시 258
 
6.5%
경 256
 
6.4%
도 256
 
6.4%
동 187
 
4.7%
처 137
 
3.4%
리 127
 
3.2%
Other values (195) 1486
37.2%
Latin
ValueCountFrequency (%)
B 5
11.4%
I 5
11.4%
T 5
11.4%
A 4
9.1%
O 3
 
6.8%
K 3
 
6.8%
S 3
 
6.8%
U 3
 
6.8%
R 3
 
6.8%
E 2
 
4.5%
Other values (6) 8
18.2%
Common
ValueCountFrequency (%)
1535
54.9%
1 202
 
7.2%
- 178
 
6.4%
2 137
 
4.9%
3 129
 
4.6%
4 122
 
4.4%
5 106
 
3.8%
0 96
 
3.4%
9 78
 
2.8%
6 75
 
2.7%
Other values (5) 137
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3997
58.5%
ASCII 2838
41.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1535
54.1%
1 202
 
7.1%
- 178
 
6.3%
2 137
 
4.8%
3 129
 
4.5%
4 122
 
4.3%
5 106
 
3.7%
0 96
 
3.4%
9 78
 
2.7%
6 75
 
2.6%
Other values (20) 180
 
6.3%
Hangul
ValueCountFrequency (%)
인 401
 
10.0%
기 360
 
9.0%
구 269
 
6.7%
용 260
 
6.5%
시 258
 
6.5%
경 256
 
6.4%
도 256
 
6.4%
동 187
 
4.7%
처 137
 
3.4%
리 127
 
3.2%
Other values (195) 1486
37.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

연락처
Text

MISSING 

Distinct55
Distinct (%)100.0%
Missing211
Missing (%)79.3%
Memory size2.2 KiB
2024-04-30T08:09:03.806740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.872727
Min length9

Characters and Unicode

Total characters653
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

Unique55 ?
Unique (%)100.0%

Sample

1st row02-577-9555
2nd row031-355-4800
3rd row031-321-2844
4th row031-521-1414
5th row031-286-2479
ValueCountFrequency (%)
02-577-9555 1
 
1.8%
031-281-2131 1
 
1.8%
031-442-2676 1
 
1.8%
031-662-3600 1
 
1.8%
031-286-7744 1
 
1.8%
031-337-3224 1
 
1.8%
031-322-4775 1
 
1.8%
031-322-1588 1
 
1.8%
031-339-5858 1
 
1.8%
054-452-3003 1
 
1.8%
Other values (45) 45
81.8%
2024-04-30T08:09:04.190974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 116
17.8%
- 108
16.5%
1 81
12.4%
0 76
11.6%
2 76
11.6%
4 56
8.6%
8 42
 
6.4%
5 35
 
5.4%
7 26
 
4.0%
6 26
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 545
83.5%
Dash Punctuation 108
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 116
21.3%
1 81
14.9%
0 76
13.9%
2 76
13.9%
4 56
10.3%
8 42
 
7.7%
5 35
 
6.4%
7 26
 
4.8%
6 26
 
4.8%
9 11
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 653
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 116
17.8%
- 108
16.5%
1 81
12.4%
0 76
11.6%
2 76
11.6%
4 56
8.6%
8 42
 
6.4%
5 35
 
5.4%
7 26
 
4.0%
6 26
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 116
17.8%
- 108
16.5%
1 81
12.4%
0 76
11.6%
2 76
11.6%
4 56
8.6%
8 42
 
6.4%
5 35
 
5.4%
7 26
 
4.0%
6 26
 
4.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2024-04-25 00:00:00
Maximum2024-04-25 00:00:00
2024-04-30T08:09:04.320850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T08:09:04.429682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-04-30T08:09:00.038652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T08:09:00.193398image/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.
2024-04-30T08:09:00.313567image/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

시군명인허가일자인허가번호영업상태업종구분업체명도로명주소지번주소연락처데이터기준일자
0용인시2000-09-044050000-2024-03-00003영업화물운송주선(주)이안로지스경기도 용인시 기흥구 금화로 103, 정진프라자 5층 (상갈동)경기도 용인시 기흥구 상갈동 473 정진프라자<NA>2024-04-25
1용인시2002-03-124050000-2024-03-00002영업화물운송주선(주)엘루션경기도 용인시 처인구 남사읍 경기동로 316 (주)리바트 2층경기도 용인시 처인구 남사읍 북리 54-10 (주)리바트<NA>2024-04-25
2용인시2006-03-034050000-2024-03-00001영업화물운송주선위카모빌리티 주식회사경기도 용인시 기흥구 중부대로 242, 오토허브 A동 W117호 (영덕동)경기도 용인시 기흥구 영덕동 1266 오토허브<NA>2024-04-25
3용인시1998-02-194050000-2023-03-00007영업화물운송주선대원냉동운수(주)경기도 용인시 처인구 이동읍 백옥대로 664-10, 202호경기도 용인시 처인구 이동읍 천리 71502-577-95552024-04-25
4용인시2003-07-014050000-2023-03-00006영업화물운송주선지앤비로지스(주)경기도 용인시 기흥구 기흥단지로 45, 4층 (고매동)경기도 용인시 기흥구 고매동 411-20 SK기흥단지주유소<NA>2024-04-25
5용인시1998-07-084050000-2023-03-00005영업화물운송주선(주)그린종합물류경기도 용인시 기흥구 신구로43번길 6-14, 101호 (신갈동)경기도 용인시 기흥구 신갈동 32-16031-355-48002024-04-25
6용인시2003-08-084050000-2023-03-00004영업화물운송주선㈜비지에프로지스경기도 용인시 기흥구 기흥로 58, 기흥아이씨티밸리 에스케이 브이1 비동 1809호 (구갈동)경기도 용인시 기흥구 구갈동 681<NA>2024-04-25
7용인시2002-05-224050000-2023-03-00003영업화물운송주선에이치엠물류(주)경기도 용인시 기흥구 동백중앙로 219, 용인 동백역 현성 더 테라스 312호 (중동)경기도 용인시 기흥구 중동 846-2 용인 동백역 현성 더 테라스<NA>2024-04-25
8용인시2000-12-014050000-2023-03-00002영업화물운송주선㈜비견물류경기도 용인시 기흥구 강남로 9, 태평양프라자 703-6호 (구갈동)경기도 용인시 기흥구 구갈동 579-2 태평양프라자<NA>2024-04-25
9용인시2001-02-224050000-2023-03-00001영업화물운송주선(주)행운운수경기도 용인시 처인구 중부대로1313번길 20-25, 인상빌딩 202호-다20호 (역북동)경기도 용인시 처인구 역북동 438-9 인상빌딩031-321-28442024-04-25
시군명인허가일자인허가번호영업상태업종구분업체명도로명주소지번주소연락처데이터기준일자
256용인시2004-11-024050000-2004-03-00022영업화물운송주선아주익스프레스경기도 용인시 기흥구 지삼로 2 (지곡동)경기도 용인시 기흥구 지곡동 609-2<NA>2024-04-25
257용인시2003-12-174050000-2003-03-00043영업화물운송주선고려종합물류(주)경기도 용인시 기흥구 덕영대로 1992 (상갈동)경기도 용인시 기흥구 상갈동 246-6031-281-65112024-04-25
258용인시2002-04-244050000-2002-03-00069영업화물운송주선(주)엘에스로지스경기도 용인시 처인구 백암면 원설로 445, 1층경기도 용인시 처인구 백암면 백봉리 859<NA>2024-04-25
259용인시2002-10-224050000-2002-03-00058영업화물운송주선희망운수(주)경기도 용인시 처인구 양지면 주북로5번길 96경기도 용인시 처인구 양지면 주북리 769-2<NA>2024-04-25
260용인시1999-12-214050000-1999-03-00058영업화물운송주선양양물류(주)경기도 용인시 처인구 양지면 죽양대로 2299, 2층경기도 용인시 처인구 양지면 양지리 115-1<NA>2024-04-25
261용인시1999-08-064050000-1999-03-00021영업화물운송주선예주화물경기도 용인시 기흥구 사은로 274-20, 202호 (지곡동, 자봉마을써니밸리아파트)경기도 용인시 기흥구 지곡동 704 써니밸리아파트 상가 202호<NA>2024-04-25
262용인시1998-10-274050000-1998-03-00032영업화물운송주선주식회사 케이알로지스경기도 용인시 기흥구 구갈로60번길 11, 삼성프라자 501-2호 (구갈동)경기도 용인시 기흥구 구갈동 354-7 삼성프라자<NA>2024-04-25
263용인시1997-12-274050000-1997-03-00045영업화물운송주선동아특수운수(익성익스프레스)경기도 용인시 기흥구 지삼로201번길 28-1 (지곡동)경기도 용인시 기흥구 지곡동 250-1<NA>2024-04-25
264용인시1993-04-124050000-1993-03-00030영업화물운송주선(주)평화로지스틱스경기도 용인시 기흥구 죽전로 10, 장은메디칼프라자 601호 (보정동)경기도 용인시 기흥구 보정동 1261-4 장은메디칼프라자 601호<NA>2024-04-25
265용인시1989-07-114050000-1989-03-00005영업화물운송주선대성고속화물(주)경기도 용인시 처인구 양지면 남평로199번길 21-7경기도 용인시 처인구 양지면 제일리 375-3031-333-31412024-04-25