Overview

Dataset statistics

Number of variables5
Number of observations353
Missing cells301
Missing cells (%)17.1%
Duplicate rows1
Duplicate rows (%)0.3%
Total size in memory13.9 KiB
Average record size in memory40.4 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description경상남도 거제시 교통카드판매(충전)소 현황(가맹점명, 주소, 위도, 경도, 전화번호, 기준일자)등에 대한 정보를 제공합니다.
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3080039

Alerts

기준일 has constant value ""Constant
Dataset has 1 (0.3%) duplicate rowsDuplicates
전화번호 has 301 (85.3%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:25:39.689573
Analysis finished2023-12-10 23:25:40.109146
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역명
Categorical

Distinct19
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
고현동
63 
옥포동
54 
장평동
43 
아주동
40 
연초면
20 
Other values (14)
133 

Length

Max length4
Median length3
Mean length3.0538244
Min length3

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
고현동 63
17.8%
옥포동 54
15.3%
장평동 43
12.2%
아주동 40
11.3%
연초면 20
 
5.7%
장승포동 19
 
5.4%
능포동 16
 
4.5%
사등면 16
 
4.5%
상문동 15
 
4.2%
일운면 15
 
4.2%
Other values (9) 52
14.7%

Length

2023-12-11T08:25:40.171182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고현동 63
17.8%
옥포동 54
15.3%
장평동 43
12.2%
아주동 40
11.3%
연초면 20
 
5.7%
장승포동 19
 
5.4%
능포동 16
 
4.5%
사등면 16
 
4.5%
일운면 15
 
4.2%
상문동 15
 
4.2%
Other values (9) 52
14.7%

충전소명
Text

Distinct348
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-11T08:25:40.463534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.6062323
Min length2

Characters and Unicode

Total characters3391
Distinct characters244
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique343 ?
Unique (%)97.2%

Sample

1st row거제농협 하나로마트
2nd row탑할인마트
3rd row기가마트
4th row스카이마트 거제면점
5th rowCU 거제면동상점
ValueCountFrequency (%)
cu 77
 
11.6%
gs25 75
 
11.3%
k7 59
 
8.9%
ms 25
 
3.8%
위드미 25
 
3.8%
세븐일레븐 20
 
3.0%
신현농협 4
 
0.6%
거제옥포점 3
 
0.5%
미니스톱 3
 
0.5%
거제계룡점 3
 
0.5%
Other values (325) 372
55.9%
2023-12-11T08:25:40.893179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
 
9.4%
점 314
 
9.3%
제 232
 
6.8%
거 231
 
6.8%
S 112
 
3.3%
C 91
 
2.7%
U 90
 
2.7%
2 85
 
2.5%
G 85
 
2.5%
5 82
 
2.4%
Other values (234) 1749
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2374
70.0%
Uppercase Letter 469
 
13.8%
Space Separator 320
 
9.4%
Decimal Number 228
 
6.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 314
 
13.2%
제 232
 
9.8%
거 231
 
9.7%
포 74
 
3.1%
장 50
 
2.1%
옥 44
 
1.9%
현 43
 
1.8%
아 42
 
1.8%
븐 40
 
1.7%
고 39
 
1.6%
Other values (218) 1265
53.3%
Uppercase Letter
ValueCountFrequency (%)
S 112
23.9%
C 91
19.4%
U 90
19.2%
G 85
18.1%
K 61
13.0%
M 25
 
5.3%
B 2
 
0.4%
W 1
 
0.2%
L 1
 
0.2%
H 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 85
37.3%
5 82
36.0%
7 59
25.9%
1 1
 
0.4%
4 1
 
0.4%
Space Separator
ValueCountFrequency (%)
320
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2374
70.0%
Common 548
 
16.2%
Latin 469
 
13.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 314
 
13.2%
제 232
 
9.8%
거 231
 
9.7%
포 74
 
3.1%
장 50
 
2.1%
옥 44
 
1.9%
현 43
 
1.8%
아 42
 
1.8%
븐 40
 
1.7%
고 39
 
1.6%
Other values (218) 1265
53.3%
Latin
ValueCountFrequency (%)
S 112
23.9%
C 91
19.4%
U 90
19.2%
G 85
18.1%
K 61
13.0%
M 25
 
5.3%
B 2
 
0.4%
W 1
 
0.2%
L 1
 
0.2%
H 1
 
0.2%
Common
ValueCountFrequency (%)
320
58.4%
2 85
 
15.5%
5 82
 
15.0%
7 59
 
10.8%
1 1
 
0.2%
4 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2374
70.0%
ASCII 1017
30.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
31.5%
S 112
 
11.0%
C 91
 
8.9%
U 90
 
8.8%
2 85
 
8.4%
G 85
 
8.4%
5 82
 
8.1%
K 61
 
6.0%
7 59
 
5.8%
M 25
 
2.5%
Other values (6) 7
 
0.7%
Hangul
ValueCountFrequency (%)
점 314
 
13.2%
제 232
 
9.8%
거 231
 
9.7%
포 74
 
3.1%
장 50
 
2.1%
옥 44
 
1.9%
현 43
 
1.8%
아 42
 
1.8%
븐 40
 
1.7%
고 39
 
1.6%
Other values (218) 1265
53.3%

전화번호
Text

MISSING 

Distinct51
Distinct (%)98.1%
Missing301
Missing (%)85.3%
Memory size2.9 KiB
2023-12-11T08:25:41.107214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.019231
Min length12

Characters and Unicode

Total characters625
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

Unique50 ?
Unique (%)96.2%

Sample

1st row055-633-4125
2nd row055-633-1881
3rd row055-634-5551
4th row055-632-4300
5th row055-635-5102
ValueCountFrequency (%)
055-688-3485 2
 
3.8%
055-681-0075 1
 
1.9%
055-633-4125 1
 
1.9%
055-681-9855 1
 
1.9%
055-636-4270 1
 
1.9%
055-638-5980 1
 
1.9%
055-636-9803 1
 
1.9%
055-688-1470 1
 
1.9%
055-688-4774 1
 
1.9%
055-688-4883 1
 
1.9%
Other values (41) 41
78.8%
2023-12-11T08:25:41.410412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 138
22.1%
- 104
16.6%
0 89
14.2%
6 75
12.0%
3 57
9.1%
8 50
 
8.0%
4 29
 
4.6%
1 29
 
4.6%
2 22
 
3.5%
7 18
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 521
83.4%
Dash Punctuation 104
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 138
26.5%
0 89
17.1%
6 75
14.4%
3 57
10.9%
8 50
 
9.6%
4 29
 
5.6%
1 29
 
5.6%
2 22
 
4.2%
7 18
 
3.5%
9 14
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 625
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 138
22.1%
- 104
16.6%
0 89
14.2%
6 75
12.0%
3 57
9.1%
8 50
 
8.0%
4 29
 
4.6%
1 29
 
4.6%
2 22
 
3.5%
7 18
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 138
22.1%
- 104
16.6%
0 89
14.2%
6 75
12.0%
3 57
9.1%
8 50
 
8.0%
4 29
 
4.6%
1 29
 
4.6%
2 22
 
3.5%
7 18
 
2.9%

도로명주소(지번주소)
Text

Distinct346
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-11T08:25:41.742443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length51
Mean length26.546742
Min length18

Characters and Unicode

Total characters9371
Distinct characters208
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

Unique339 ?
Unique (%)96.0%

Sample

1st row경상남도 거제시 거제면 읍내로2길 32
2nd row경상남도 거제시 거제면 기성로 15
3rd row경상남도 거제시 거제면 읍내로 23
4th row경상남도 거제시 거제면 거제남서로 3446
5th row경상남도 거제시 거제면 읍내로2길 35-1
ValueCountFrequency (%)
경상남도 353
 
19.2%
거제시 351
 
19.1%
고현동 39
 
2.1%
옥포동 31
 
1.7%
1층 28
 
1.5%
장평동 28
 
1.5%
거제대로 26
 
1.4%
연초면 20
 
1.1%
아주동 19
 
1.0%
사등면 17
 
0.9%
Other values (565) 925
50.4%
2023-12-11T08:25:42.245312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1509
 
16.1%
제 446
 
4.8%
거 437
 
4.7%
1 425
 
4.5%
상 404
 
4.3%
남 369
 
3.9%
도 362
 
3.9%
시 355
 
3.8%
경 353
 
3.8%
동 332
 
3.5%
Other values (198) 4379
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5451
58.2%
Decimal Number 1553
 
16.6%
Space Separator 1509
 
16.1%
Open Punctuation 281
 
3.0%
Close Punctuation 280
 
3.0%
Dash Punctuation 212
 
2.3%
Other Punctuation 77
 
0.8%
Uppercase Letter 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 446
 
8.2%
거 437
 
8.0%
상 404
 
7.4%
남 369
 
6.8%
도 362
 
6.6%
시 355
 
6.5%
경 353
 
6.5%
동 332
 
6.1%
로 294
 
5.4%
길 168
 
3.1%
Other values (175) 1931
35.4%
Decimal Number
ValueCountFrequency (%)
1 425
27.4%
0 272
17.5%
2 200
12.9%
3 156
 
10.0%
4 120
 
7.7%
5 103
 
6.6%
7 93
 
6.0%
6 71
 
4.6%
9 61
 
3.9%
8 52
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
C 1
25.0%
J 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 277
98.6%
[ 4
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 276
98.6%
] 4
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 75
97.4%
. 2
 
2.6%
Space Separator
ValueCountFrequency (%)
1509
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 212
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5451
58.2%
Common 3912
41.7%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 446
 
8.2%
거 437
 
8.0%
상 404
 
7.4%
남 369
 
6.8%
도 362
 
6.6%
시 355
 
6.5%
경 353
 
6.5%
동 332
 
6.1%
로 294
 
5.4%
길 168
 
3.1%
Other values (175) 1931
35.4%
Common
ValueCountFrequency (%)
1509
38.6%
1 425
 
10.9%
( 277
 
7.1%
) 276
 
7.1%
0 272
 
7.0%
- 212
 
5.4%
2 200
 
5.1%
3 156
 
4.0%
4 120
 
3.1%
5 103
 
2.6%
Other values (8) 362
 
9.3%
Latin
ValueCountFrequency (%)
e 3
37.5%
B 2
25.0%
C 1
 
12.5%
J 1
 
12.5%
Ⅱ 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5451
58.2%
ASCII 3919
41.8%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1509
38.5%
1 425
 
10.8%
( 277
 
7.1%
) 276
 
7.0%
0 272
 
6.9%
- 212
 
5.4%
2 200
 
5.1%
3 156
 
4.0%
4 120
 
3.1%
5 103
 
2.6%
Other values (12) 369
 
9.4%
Hangul
ValueCountFrequency (%)
제 446
 
8.2%
거 437
 
8.0%
상 404
 
7.4%
남 369
 
6.8%
도 362
 
6.6%
시 355
 
6.5%
경 353
 
6.5%
동 332
 
6.1%
로 294
 
5.4%
길 168
 
3.1%
Other values (175) 1931
35.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2017-11-29 00:00:00
Maximum2017-11-29 00:00:00
2023-12-11T08:25:42.360377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:25:42.451095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T08:25:42.516492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명전화번호
지역명1.0001.000
전화번호1.0001.000

Missing values

2023-12-11T08:25:39.985898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:25:40.067072image/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.

Sample

지역명충전소명전화번호도로명주소(지번주소)기준일
0거제면거제농협 하나로마트055-633-4125경상남도 거제시 거제면 읍내로2길 322017-11-29
1거제면탑할인마트055-633-1881경상남도 거제시 거제면 기성로 152017-11-29
2거제면기가마트055-634-5551경상남도 거제시 거제면 읍내로 232017-11-29
3거제면스카이마트 거제면점055-632-4300경상남도 거제시 거제면 거제남서로 34462017-11-29
4거제면CU 거제면동상점<NA>경상남도 거제시 거제면 읍내로2길 35-12017-11-29
5거제면GS25 거제아델하임점<NA>경상남도 거제시 거제면 거제남서로 3466, 상가 1층 104호2017-11-29
6거제면GS25 고현해안로점<NA>경상남도 거제시 거제면 고당리 991-10 1층2017-11-29
7거제면GS25 고현햇님점<NA>경상남도 거제시 거제면 고당리 796-12017-11-29
8거제면GS25거제서정점<NA>경상남도 거제시 거제면 읍내로 67-12017-11-29
9거제면K7 거제남동로드점<NA>경상남도 거제시 거제면 남동리 1층 101호2017-11-29
지역명충전소명전화번호도로명주소(지번주소)기준일
343장평동세븐일레븐 거제장평금강점<NA>경상남도 거제시 장평1로 166-0, 월드프리미엄 101호(장평동)2017-11-29
344장평동세븐일레븐 거제장평수창점<NA>경상남도 거제시 거제대로 4951-0 (장평동, 거제수창프라임시티아파트) 상가 109동 101호-102호2017-11-29
345장평동세븐일레븐 거제장평주공점<NA>경상남도 거제시 장평2로 36-0 (장평동)2017-11-29
346장평동위드미 거제성원아파트점<NA>경상남도 거제시 장평로6길 22(장평동)2017-11-29
347장평동위드미 거제장평아내점<NA>경상남도 거제시 장평4로2길 2-0 (장평동) 1층2017-11-29
348장평동위드미 거제장평원룸점<NA>경상남도 거제시 장평3로2길 45-0 (장평동)2017-11-29
349장평동위드미 거제장평점<NA>경상남도 거제시 장평3로4길 12-0 (장평동)2017-11-29
350하청면삼거리상회055-636-3708경상남도 거제시 하청면 연하해안로 17212017-11-29
351하청면GS25 거제실전점<NA>경상남도 거제시 하청면 거제북로 8342017-11-29
352하청면K7 거제하청LH점<NA>경상남도 거제시 하청면 하청2길 12-0 (하청면)2017-11-29

Duplicate rows

Most frequently occurring

지역명충전소명전화번호도로명주소(지번주소)기준일# duplicates
0일운면일운농협하나로마트 본점055-688-3485경상남도 거제시 일운면 지세포로 1312017-11-292