Overview

Dataset statistics

Number of variables7
Number of observations908
Missing cells345
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory50.7 KiB
Average record size in memory57.1 B

Variable types

Numeric1
Categorical1
Text5

Dataset

Description상기 자료는 2021년 4월 30일 기준 인천광역시 화물자동차운송주선사업 허가업체현황자료(군구명, 업체명, 주소, 대표자, 전화번호, 허가일자) 입니다.
Author인천광역시
URLhttps://www.data.go.kr/data/15081129/fileData.do

Alerts

연번 is highly overall correlated with 군구명High correlation
군구명 is highly overall correlated with 연번High correlation
전화번호 has 344 (37.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:23:14.256245
Analysis finished2023-12-12 08:23:15.866735
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct908
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean454.5
Minimum1
Maximum908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.1 KiB
2023-12-12T17:23:15.972492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile46.35
Q1227.75
median454.5
Q3681.25
95-th percentile862.65
Maximum908
Range907
Interquartile range (IQR)453.5

Descriptive statistics

Standard deviation262.26132
Coefficient of variation (CV)0.57703261
Kurtosis-1.2
Mean454.5
Median Absolute Deviation (MAD)227
Skewness0
Sum412686
Variance68781
MonotonicityStrictly increasing
2023-12-12T17:23:16.165252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
626 1
 
0.1%
600 1
 
0.1%
601 1
 
0.1%
602 1
 
0.1%
603 1
 
0.1%
604 1
 
0.1%
605 1
 
0.1%
606 1
 
0.1%
607 1
 
0.1%
Other values (898) 898
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
908 1
0.1%
907 1
0.1%
906 1
0.1%
905 1
0.1%
904 1
0.1%
903 1
0.1%
902 1
0.1%
901 1
0.1%
900 1
0.1%
899 1
0.1%

군구명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
중구
251 
남동구
119 
서구
116 
동구
102 
미추홀구
93 
Other values (4)
227 

Length

Max length4
Median length2
Mean length2.5859031
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 251
27.6%
남동구 119
13.1%
서구 116
12.8%
동구 102
11.2%
미추홀구 93
 
10.2%
부평구 82
 
9.0%
연수구 81
 
8.9%
계양구 61
 
6.7%
강화군 3
 
0.3%

Length

2023-12-12T17:23:16.361739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:23:16.516155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 251
27.6%
남동구 119
13.1%
서구 116
12.8%
동구 102
11.2%
미추홀구 93
 
10.2%
부평구 82
 
9.0%
연수구 81
 
8.9%
계양구 61
 
6.7%
강화군 3
 
0.3%

업체명
Text

Distinct892
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T17:23:16.894665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length6.6123348
Min length2

Characters and Unicode

Total characters6004
Distinct characters382
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique877 ?
Unique (%)96.6%

Sample

1st row중앙물류
2nd row박문운송알선사
3rd row㈜영진운수
4th row㈜영한
5th row동서통운㈜
ValueCountFrequency (%)
인천영업소 8
 
0.8%
인천지점 5
 
0.5%
주식회사 4
 
0.4%
삼호익스프레스 3
 
0.3%
씨제이대한통운㈜ 3
 
0.3%
인천공항지점 3
 
0.3%
이사몰 3
 
0.3%
드림익스프레스 2
 
0.2%
이사 2
 
0.2%
kgb 2
 
0.2%
Other values (908) 923
96.3%
2023-12-12T17:23:17.410422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 573
 
9.5%
㈜ 346
 
5.8%
물 321
 
5.3%
류 220
 
3.7%
이 196
 
3.3%
로 176
 
2.9%
지 169
 
2.8%
프 142
 
2.4%
레 139
 
2.3%
익 134
 
2.2%
Other values (372) 3588
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5293
88.2%
Other Symbol 346
 
5.8%
Open Punctuation 85
 
1.4%
Close Punctuation 85
 
1.4%
Space Separator 71
 
1.2%
Uppercase Letter 58
 
1.0%
Decimal Number 47
 
0.8%
Other Punctuation 11
 
0.2%
Lowercase Letter 7
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 573
 
10.8%
물 321
 
6.1%
류 220
 
4.2%
이 196
 
3.7%
로 176
 
3.3%
지 169
 
3.2%
프 142
 
2.7%
레 139
 
2.6%
익 134
 
2.5%
화 118
 
2.2%
Other values (335) 3105
58.7%
Uppercase Letter
ValueCountFrequency (%)
K 14
24.1%
B 8
13.8%
S 7
12.1%
G 6
10.3%
L 4
 
6.9%
H 3
 
5.2%
O 2
 
3.4%
C 2
 
3.4%
D 2
 
3.4%
E 2
 
3.4%
Other values (5) 8
13.8%
Decimal Number
ValueCountFrequency (%)
4 20
42.6%
2 17
36.2%
1 3
 
6.4%
7 2
 
4.3%
3 2
 
4.3%
0 2
 
4.3%
5 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
l 2
28.6%
a 1
14.3%
m 1
14.3%
g 1
14.3%
n 1
14.3%
i 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 7
63.6%
, 2
 
18.2%
/ 1
 
9.1%
? 1
 
9.1%
Other Symbol
ValueCountFrequency (%)
㈜ 346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Space Separator
ValueCountFrequency (%)
71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5638
93.9%
Common 300
 
5.0%
Latin 65
 
1.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 573
 
10.2%
㈜ 346
 
6.1%
물 321
 
5.7%
류 220
 
3.9%
이 196
 
3.5%
로 176
 
3.1%
지 169
 
3.0%
프 142
 
2.5%
레 139
 
2.5%
익 134
 
2.4%
Other values (335) 3222
57.1%
Latin
ValueCountFrequency (%)
K 14
21.5%
B 8
12.3%
S 7
10.8%
G 6
 
9.2%
L 4
 
6.2%
H 3
 
4.6%
l 2
 
3.1%
O 2
 
3.1%
C 2
 
3.1%
D 2
 
3.1%
Other values (11) 15
23.1%
Common
ValueCountFrequency (%)
( 85
28.3%
) 85
28.3%
71
23.7%
4 20
 
6.7%
2 17
 
5.7%
. 7
 
2.3%
1 3
 
1.0%
7 2
 
0.7%
3 2
 
0.7%
, 2
 
0.7%
Other values (5) 6
 
2.0%
Han
ValueCountFrequency (%)
舊 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5292
88.1%
ASCII 365
 
6.1%
None 346
 
5.8%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 573
 
10.8%
물 321
 
6.1%
류 220
 
4.2%
이 196
 
3.7%
로 176
 
3.3%
지 169
 
3.2%
프 142
 
2.7%
레 139
 
2.6%
익 134
 
2.5%
화 118
 
2.2%
Other values (334) 3104
58.7%
None
ValueCountFrequency (%)
㈜ 346
100.0%
ASCII
ValueCountFrequency (%)
( 85
23.3%
) 85
23.3%
71
19.5%
4 20
 
5.5%
2 17
 
4.7%
K 14
 
3.8%
B 8
 
2.2%
S 7
 
1.9%
. 7
 
1.9%
G 6
 
1.6%
Other values (26) 45
12.3%
CJK
ValueCountFrequency (%)
舊 1
100.0%

주소
Text

Distinct889
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T17:23:17.789779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length51
Mean length33.620044
Min length15

Characters and Unicode

Total characters30527
Distinct characters357
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique870 ?
Unique (%)95.8%

Sample

1st row인천광역시 중구 공항동로295번길 77-6, 운송대리점 B동 210-1호(운서동)
2nd row인천광역시 중구 축항대로296번길 183, 2층 19호(신흥동3가)
3rd row인천광역시 중구 축항대로290번길 164, 103호(신흥동3가)
4th row인천광역시 중구 서해대로 366, 에이동 608호(신흥동3가, 정석빌딩)
5th row인천광역시 중구 축항대로 220, 404호(항동7가, 케이티엔지인천지점)
ValueCountFrequency (%)
인천광역시 908
 
17.5%
중구 252
 
4.9%
남동구 119
 
2.3%
서구 117
 
2.3%
동구 102
 
2.0%
미추홀구 92
 
1.8%
부평구 81
 
1.6%
연수구 80
 
1.5%
계양구 61
 
1.2%
30 48
 
0.9%
Other values (1831) 3325
64.1%
2023-12-12T17:23:18.319484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4320
 
14.2%
동 1362
 
4.5%
1 1120
 
3.7%
인 1043
 
3.4%
천 1031
 
3.4%
, 968
 
3.2%
구 951
 
3.1%
광 935
 
3.1%
역 925
 
3.0%
2 924
 
3.0%
Other values (347) 16948
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17575
57.6%
Decimal Number 5751
 
18.8%
Space Separator 4320
 
14.2%
Other Punctuation 983
 
3.2%
Open Punctuation 778
 
2.5%
Close Punctuation 776
 
2.5%
Dash Punctuation 258
 
0.8%
Uppercase Letter 82
 
0.3%
Other Symbol 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1362
 
7.7%
인 1043
 
5.9%
천 1031
 
5.9%
구 951
 
5.4%
광 935
 
5.3%
역 925
 
5.3%
시 918
 
5.2%
로 855
 
4.9%
호 516
 
2.9%
길 485
 
2.8%
Other values (317) 8554
48.7%
Decimal Number
ValueCountFrequency (%)
1 1120
19.5%
2 924
16.1%
3 860
15.0%
0 634
11.0%
4 405
 
7.0%
7 402
 
7.0%
6 368
 
6.4%
9 361
 
6.3%
5 361
 
6.3%
8 316
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 26
31.7%
B 25
30.5%
C 12
14.6%
G 4
 
4.9%
D 4
 
4.9%
T 4
 
4.9%
K 3
 
3.7%
P 2
 
2.4%
E 1
 
1.2%
M 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 968
98.5%
. 13
 
1.3%
/ 1
 
0.1%
@ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4320
100.0%
Open Punctuation
ValueCountFrequency (%)
( 778
100.0%
Close Punctuation
ValueCountFrequency (%)
) 776
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 258
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17578
57.6%
Common 12866
42.1%
Latin 83
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1362
 
7.7%
인 1043
 
5.9%
천 1031
 
5.9%
구 951
 
5.4%
광 935
 
5.3%
역 925
 
5.3%
시 918
 
5.2%
로 855
 
4.9%
호 516
 
2.9%
길 485
 
2.8%
Other values (318) 8557
48.7%
Common
ValueCountFrequency (%)
4320
33.6%
1 1120
 
8.7%
, 968
 
7.5%
2 924
 
7.2%
3 860
 
6.7%
( 778
 
6.0%
) 776
 
6.0%
0 634
 
4.9%
4 405
 
3.1%
7 402
 
3.1%
Other values (8) 1679
 
13.0%
Latin
ValueCountFrequency (%)
A 26
31.3%
B 25
30.1%
C 12
14.5%
G 4
 
4.8%
D 4
 
4.8%
T 4
 
4.8%
K 3
 
3.6%
P 2
 
2.4%
E 1
 
1.2%
M 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17575
57.6%
ASCII 12949
42.4%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4320
33.4%
1 1120
 
8.6%
, 968
 
7.5%
2 924
 
7.1%
3 860
 
6.6%
( 778
 
6.0%
) 776
 
6.0%
0 634
 
4.9%
4 405
 
3.1%
7 402
 
3.1%
Other values (19) 1762
13.6%
Hangul
ValueCountFrequency (%)
동 1362
 
7.7%
인 1043
 
5.9%
천 1031
 
5.9%
구 951
 
5.4%
광 935
 
5.3%
역 925
 
5.3%
시 918
 
5.2%
로 855
 
4.9%
호 516
 
2.9%
길 485
 
2.8%
Other values (317) 8554
48.7%
None
ValueCountFrequency (%)
㈜ 3
100.0%

대표자
Text

Distinct877
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2023-12-12T17:23:18.634455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length3
Mean length3.0837004
Min length2

Characters and Unicode

Total characters2800
Distinct characters222
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique847 ?
Unique (%)93.3%

Sample

1st row김수임
2nd row한상욱
3rd row최성업
4th row명응화
5th row양재현
ValueCountFrequency (%)
강신호 3
 
0.3%
박정희 2
 
0.2%
윤옹기 2
 
0.2%
황영일 2
 
0.2%
이상근 2
 
0.2%
김민석 2
 
0.2%
김영주 2
 
0.2%
김준호 2
 
0.2%
맹선영 2
 
0.2%
김종범 2
 
0.2%
Other values (872) 892
97.7%
2023-12-12T17:23:19.058763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 189
 
6.8%
이 133
 
4.8%
영 99
 
3.5%
박 99
 
3.5%
정 89
 
3.2%
성 59
 
2.1%
희 51
 
1.8%
호 50
 
1.8%
최 48
 
1.7%
종 46
 
1.6%
Other values (212) 1937
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2770
98.9%
Uppercase Letter 15
 
0.5%
Space Separator 11
 
0.4%
Other Punctuation 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 189
 
6.8%
이 133
 
4.8%
영 99
 
3.6%
박 99
 
3.6%
정 89
 
3.2%
성 59
 
2.1%
희 51
 
1.8%
호 50
 
1.8%
최 48
 
1.7%
종 46
 
1.7%
Other values (197) 1907
68.8%
Uppercase Letter
ValueCountFrequency (%)
L 2
13.3%
K 2
13.3%
I 2
13.3%
R 2
13.3%
U 1
6.7%
A 1
6.7%
T 1
6.7%
D 1
6.7%
O 1
6.7%
V 1
6.7%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2770
98.9%
Common 15
 
0.5%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 189
 
6.8%
이 133
 
4.8%
영 99
 
3.6%
박 99
 
3.6%
정 89
 
3.2%
성 59
 
2.1%
희 51
 
1.8%
호 50
 
1.8%
최 48
 
1.7%
종 46
 
1.7%
Other values (197) 1907
68.8%
Latin
ValueCountFrequency (%)
L 2
13.3%
K 2
13.3%
I 2
13.3%
R 2
13.3%
U 1
6.7%
A 1
6.7%
T 1
6.7%
D 1
6.7%
O 1
6.7%
V 1
6.7%
Common
ValueCountFrequency (%)
11
73.3%
, 2
 
13.3%
( 1
 
6.7%
) 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2770
98.9%
ASCII 30
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 189
 
6.8%
이 133
 
4.8%
영 99
 
3.6%
박 99
 
3.6%
정 89
 
3.2%
성 59
 
2.1%
희 51
 
1.8%
호 50
 
1.8%
최 48
 
1.7%
종 46
 
1.7%
Other values (197) 1907
68.8%
ASCII
ValueCountFrequency (%)
11
36.7%
, 2
 
6.7%
L 2
 
6.7%
K 2
 
6.7%
I 2
 
6.7%
R 2
 
6.7%
U 1
 
3.3%
A 1
 
3.3%
T 1
 
3.3%
D 1
 
3.3%
Other values (5) 5
16.7%

전화번호
Text

MISSING 

Distinct556
Distinct (%)98.6%
Missing344
Missing (%)37.9%
Memory size7.2 KiB
2023-12-12T17:23:19.349026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length8
Mean length8.5868794
Min length8

Characters and Unicode

Total characters4843
Distinct characters16
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique548 ?
Unique (%)97.2%

Sample

1st row744-8080
2nd row874-2424
3rd row764-3201
4th row888-8080
5th row888-4030
ValueCountFrequency (%)
821-7766 2
 
0.4%
888-0188 2
 
0.4%
581-8170 2
 
0.4%
867-2404 2
 
0.4%
777-8401 2
 
0.4%
888-8080 2
 
0.4%
888-3451 2
 
0.4%
528-6585 2
 
0.4%
511-8866 1
 
0.2%
032)822-2482 1
 
0.2%
Other values (547) 547
96.8%
2023-12-12T17:23:19.804446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 582
12.0%
- 570
11.8%
2 516
10.7%
4 510
10.5%
0 479
9.9%
7 446
9.2%
5 437
9.0%
1 381
7.9%
3 328
6.8%
6 318
6.6%
Other values (6) 276
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4199
86.7%
Dash Punctuation 570
 
11.8%
Close Punctuation 59
 
1.2%
Open Punctuation 9
 
0.2%
Space Separator 3
 
0.1%
Math Symbol 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 582
13.9%
2 516
12.3%
4 510
12.1%
0 479
11.4%
7 446
10.6%
5 437
10.4%
1 381
9.1%
3 328
7.8%
6 318
7.6%
9 202
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 570
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4843
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 582
12.0%
- 570
11.8%
2 516
10.7%
4 510
10.5%
0 479
9.9%
7 446
9.2%
5 437
9.0%
1 381
7.9%
3 328
6.8%
6 318
6.6%
Other values (6) 276
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4843
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 582
12.0%
- 570
11.8%
2 516
10.7%
4 510
10.5%
0 479
9.9%
7 446
9.2%
5 437
9.0%
1 381
7.9%
3 328
6.8%
6 318
6.6%
Other values (6) 276
5.7%

허가일자
Text

Distinct835
Distinct (%)92.1%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2023-12-12T17:23:20.074335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length9.8919515
Min length7

Characters and Unicode

Total characters8972
Distinct characters31
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique779 ?
Unique (%)85.9%

Sample

1st row1997-07-09
2nd row1999-10-29
3rd row1993-03-30
4th row1994-04-23
5th row1994-10-26
ValueCountFrequency (%)
2004-04-21 10
 
1.1%
1999-04-23 4
 
0.4%
2002-12-30 3
 
0.3%
2001.06.13 3
 
0.3%
2004-01-20 3
 
0.3%
1996-07-29 3
 
0.3%
2002.04.18 3
 
0.3%
2004.04.21 3
 
0.3%
2004-09-08 2
 
0.2%
2000-03-20 2
 
0.2%
Other values (822) 871
96.0%
2023-12-12T17:23:20.494041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2134
23.8%
1 1241
13.8%
2 1197
13.3%
- 1012
11.3%
. 943
10.5%
9 817
 
9.1%
3 357
 
4.0%
4 303
 
3.4%
7 258
 
2.9%
8 250
 
2.8%
Other values (21) 460
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6980
77.8%
Dash Punctuation 1012
 
11.3%
Other Punctuation 943
 
10.5%
Other Letter 21
 
0.2%
Open Punctuation 7
 
0.1%
Close Punctuation 7
 
0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3
14.3%
양 2
 
9.5%
서 2
 
9.5%
수 2
 
9.5%
신 1
 
4.8%
록 1
 
4.8%
등 1
 
4.8%
남 1
 
4.8%
입 1
 
4.8%
천 1
 
4.8%
Other values (6) 6
28.6%
Decimal Number
ValueCountFrequency (%)
0 2134
30.6%
1 1241
17.8%
2 1197
17.1%
9 817
 
11.7%
3 357
 
5.1%
4 303
 
4.3%
7 258
 
3.7%
8 250
 
3.6%
5 224
 
3.2%
6 199
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 1012
100.0%
Other Punctuation
ValueCountFrequency (%)
. 943
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8951
99.8%
Hangul 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3
14.3%
양 2
 
9.5%
서 2
 
9.5%
수 2
 
9.5%
신 1
 
4.8%
록 1
 
4.8%
등 1
 
4.8%
남 1
 
4.8%
입 1
 
4.8%
천 1
 
4.8%
Other values (6) 6
28.6%
Common
ValueCountFrequency (%)
0 2134
23.8%
1 1241
13.9%
2 1197
13.4%
- 1012
11.3%
. 943
10.5%
9 817
 
9.1%
3 357
 
4.0%
4 303
 
3.4%
7 258
 
2.9%
8 250
 
2.8%
Other values (5) 439
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8951
99.8%
Hangul 21
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2134
23.8%
1 1241
13.9%
2 1197
13.4%
- 1012
11.3%
. 943
10.5%
9 817
 
9.1%
3 357
 
4.0%
4 303
 
3.4%
7 258
 
2.9%
8 250
 
2.8%
Other values (5) 439
 
4.9%
Hangul
ValueCountFrequency (%)
구 3
14.3%
양 2
 
9.5%
서 2
 
9.5%
수 2
 
9.5%
신 1
 
4.8%
록 1
 
4.8%
등 1
 
4.8%
남 1
 
4.8%
입 1
 
4.8%
천 1
 
4.8%
Other values (6) 6
28.6%

Interactions

2023-12-12T17:23:15.347668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:23:20.610328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구명
연번1.0000.948
군구명0.9481.000
2023-12-12T17:23:20.707071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번군구명
연번1.0000.820
군구명0.8201.000

Missing values

2023-12-12T17:23:15.518785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:23:15.682020image/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.
2023-12-12T17:23:15.808350image/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

연번군구명업체명주소대표자전화번호허가일자
01중구중앙물류인천광역시 중구 공항동로295번길 77-6, 운송대리점 B동 210-1호(운서동)김수임744-80801997-07-09
12중구박문운송알선사인천광역시 중구 축항대로296번길 183, 2층 19호(신흥동3가)한상욱874-24241999-10-29
23중구㈜영진운수인천광역시 중구 축항대로290번길 164, 103호(신흥동3가)최성업764-32011993-03-30
34중구㈜영한인천광역시 중구 서해대로 366, 에이동 608호(신흥동3가, 정석빌딩)명응화888-80801994-04-23
45중구동서통운㈜인천광역시 중구 축항대로 220, 404호(항동7가, 케이티엔지인천지점)양재현888-40301994-10-26
56중구동화실업㈜인천광역시 중구 내항로 465-110(북성동1가)허남민770-26211986-03-24
67중구㈜제이비엘인천광역시 중구 신포로 8, 603호(사동, 경신빌딩)이정배762-95961992-10-27
78중구인천냉동㈜인천광역시 중구 축항대로 283, 3동 2층 201호(신흥동3가)김상복885-36511999-05-31
89중구태성물류인천광역시 중구 축항대로86번길 22, 405호(항동7가, 한성빌딩)이영란885-70371997-10-29
910중구동인익스프레스(이사)인천광역시 중구 송월동1가 9-23(가설건축물)양승완766-24241997-02-10
연번군구명업체명주소대표자전화번호허가일자
898899서구대현종합화물운송인천광역시 서구 청라에메랄드로102번길 8-12, 507호(청라동, 아이케이비즈센터)김대현1661-24271996-07-29
899900서구(주)홈케어2424인천광역시 서구 경명대로 694번길1, 2층202호이소영1644-22242001-05-18
900901서구아줌마화물인천광역시 서구 신진말로 33번길 8-15김미인566-52002005-09-23
901902서구굴렁쇠로지스인천광역시 서구 청중로478번길 16, 5층(가정동)김정일1800-70781997-09-23
902903서구007트랜스인천광역시 서구 원적로47번길 6, 풍림아파트 103동 상가112호(가좌동)김종수576-00752002-10-11
903904서구연합화물익스프레스인천광역시 서구 장고개로 372, 3층(가좌동)임구택529-12342003-11-20
904905서구연희화물익스프레스인천광역시 서구 승학로 286, 2층(연희동)김종오566-24242002-02-04
905906강화군제이엘로지스인천광역시 강화군 강화읍 강화대로471번길 1노희윤933-24241997-10-08
906907강화군가람익스프레스인천광역시 강화군 강화읍 갑룡길 81-5, 2층이정주<NA>2003-08-25
907908강화군젊은익스프레스인천광역시 강화군 강화읍 갑룡길206번길 22-84최성진<NA>2005-02-28