Overview

Dataset statistics

Number of variables5
Number of observations314
Missing cells240
Missing cells (%)15.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.4 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
전화번호 has 240 (76.4%) missing valuesMissing

Reproduction

Analysis started2023-12-10 23:25:35.419878
Analysis finished2023-12-10 23:25:35.928551
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역명
Categorical

Distinct17
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
고현동
55 
옥포동
52 
장평동
39 
아주동
36 
연초면
19 
Other values (12)
113 

Length

Max length4
Median length3
Mean length3.0541401
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
고현동 55
17.5%
옥포동 52
16.6%
장평동 39
12.4%
아주동 36
11.5%
연초면 19
 
6.1%
장승포동 17
 
5.4%
수양동 16
 
5.1%
사등면 13
 
4.1%
일운면 12
 
3.8%
상문동 12
 
3.8%
Other values (7) 43
13.7%

Length

2023-12-11T08:25:36.269467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고현동 55
17.5%
옥포동 52
16.6%
장평동 39
12.4%
아주동 36
11.5%
연초면 19
 
6.1%
장승포동 17
 
5.4%
수양동 16
 
5.1%
사등면 13
 
4.1%
상문동 12
 
3.8%
일운면 12
 
3.8%
Other values (7) 43
13.7%

충전소명
Text

Distinct313
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T08:25:36.540262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length10.041401
Min length3

Characters and Unicode

Total characters3153
Distinct characters225
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

Unique312 ?
Unique (%)99.4%

Sample

1st rowGS25 지세포점
2nd row세븐일레븐 거제망치몽돌점
3rd row탑훼미리마트 일운점
4th rowCU 거제 지세포점
5th row썬마트 일운점
ValueCountFrequency (%)
cu 92
 
15.1%
gs25 66
 
10.8%
세븐일레븐 60
 
9.8%
미니스톱 23
 
3.8%
위드미 20
 
3.3%
하나로마트 6
 
1.0%
신현농협 6
 
1.0%
거제 5
 
0.8%
거제옥포점 4
 
0.7%
거제고현점 3
 
0.5%
Other values (298) 326
53.4%
2023-12-11T08:25:36.945747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
319
 
10.1%
점 276
 
8.8%
제 190
 
6.0%
거 189
 
6.0%
븐 120
 
3.8%
C 93
 
2.9%
U 92
 
2.9%
S 76
 
2.4%
G 74
 
2.3%
2 73
 
2.3%
Other values (215) 1651
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2346
74.4%
Uppercase Letter 343
 
10.9%
Space Separator 319
 
10.1%
Decimal Number 145
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 276
 
11.8%
제 190
 
8.1%
거 189
 
8.1%
븐 120
 
5.1%
일 70
 
3.0%
포 64
 
2.7%
세 64
 
2.7%
레 60
 
2.6%
미 49
 
2.1%
옥 41
 
1.7%
Other values (202) 1223
52.1%
Uppercase Letter
ValueCountFrequency (%)
C 93
27.1%
U 92
26.8%
S 76
22.2%
G 74
21.6%
K 2
 
0.6%
B 2
 
0.6%
W 1
 
0.3%
A 1
 
0.3%
H 1
 
0.3%
L 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 73
50.3%
5 72
49.7%
Space Separator
ValueCountFrequency (%)
319
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2346
74.4%
Common 464
 
14.7%
Latin 343
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 276
 
11.8%
제 190
 
8.1%
거 189
 
8.1%
븐 120
 
5.1%
일 70
 
3.0%
포 64
 
2.7%
세 64
 
2.7%
레 60
 
2.6%
미 49
 
2.1%
옥 41
 
1.7%
Other values (202) 1223
52.1%
Latin
ValueCountFrequency (%)
C 93
27.1%
U 92
26.8%
S 76
22.2%
G 74
21.6%
K 2
 
0.6%
B 2
 
0.6%
W 1
 
0.3%
A 1
 
0.3%
H 1
 
0.3%
L 1
 
0.3%
Common
ValueCountFrequency (%)
319
68.8%
2 73
 
15.7%
5 72
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2346
74.4%
ASCII 807
 
25.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319
39.5%
C 93
 
11.5%
U 92
 
11.4%
S 76
 
9.4%
G 74
 
9.2%
2 73
 
9.0%
5 72
 
8.9%
K 2
 
0.2%
B 2
 
0.2%
W 1
 
0.1%
Other values (3) 3
 
0.4%
Hangul
ValueCountFrequency (%)
점 276
 
11.8%
제 190
 
8.1%
거 189
 
8.1%
븐 120
 
5.1%
일 70
 
3.0%
포 64
 
2.7%
세 64
 
2.7%
레 60
 
2.6%
미 49
 
2.1%
옥 41
 
1.7%
Other values (202) 1223
52.1%

전화번호
Text

MISSING 

Distinct73
Distinct (%)98.6%
Missing240
Missing (%)76.4%
Memory size2.6 KiB
2023-12-11T08:25:37.163973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters888
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

Unique72 ?
Unique (%)97.3%

Sample

1st row055-681-6660
2nd row055-681-8338
3rd row055-681-0075
4th row055-681-3970
5th row055-681-6601
ValueCountFrequency (%)
055-687-5777 2
 
2.7%
055-687-4240 1
 
1.4%
055-632-8307 1
 
1.4%
055-634-0636 1
 
1.4%
055-636-5005 1
 
1.4%
055-638-0227 1
 
1.4%
055-637-4067 1
 
1.4%
055-637-5242 1
 
1.4%
055-637-7580 1
 
1.4%
055-637-0688 1
 
1.4%
Other values (63) 63
85.1%
2023-12-11T08:25:37.492483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 189
21.3%
- 148
16.7%
0 122
13.7%
6 111
12.5%
3 75
 
8.4%
8 66
 
7.4%
7 42
 
4.7%
1 42
 
4.7%
2 39
 
4.4%
4 36
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 740
83.3%
Dash Punctuation 148
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 189
25.5%
0 122
16.5%
6 111
15.0%
3 75
 
10.1%
8 66
 
8.9%
7 42
 
5.7%
1 42
 
5.7%
2 39
 
5.3%
4 36
 
4.9%
9 18
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 888
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 189
21.3%
- 148
16.7%
0 122
13.7%
6 111
12.5%
3 75
 
8.4%
8 66
 
7.4%
7 42
 
4.7%
1 42
 
4.7%
2 39
 
4.4%
4 36
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 189
21.3%
- 148
16.7%
0 122
13.7%
6 111
12.5%
3 75
 
8.4%
8 66
 
7.4%
7 42
 
4.7%
1 42
 
4.7%
2 39
 
4.4%
4 36
 
4.1%

도로명주소(지번주소)
Text

Distinct312
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-11T08:25:37.807509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length25.853503
Min length15

Characters and Unicode

Total characters8118
Distinct characters210
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique310 ?
Unique (%)98.7%

Sample

1st row경상남도 거제시 일운면 거제대로 2563
2nd row경상남도 거제시 일운면 거제대로 1794
3rd row경상남도 거제시 일운면 거제대로 2470
4th row경상남도 거제시 일운면 거제대로 2480
5th row경상남도 거제시 일운면 거제대로 2591(일운주공APT) 상가 103호
ValueCountFrequency (%)
거제시 315
 
20.0%
경상남도 314
 
19.9%
거제대로 25
 
1.6%
고현동 23
 
1.5%
연초면 19
 
1.2%
사등면 15
 
1.0%
일운면 13
 
0.8%
1층 12
 
0.8%
옥포로 11
 
0.7%
거제중앙로 11
 
0.7%
Other values (548) 818
51.9%
2023-12-11T08:25:38.242433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1342
 
16.5%
거 396
 
4.9%
제 396
 
4.9%
상 350
 
4.3%
남 329
 
4.1%
도 321
 
4.0%
시 320
 
3.9%
경 314
 
3.9%
1 293
 
3.6%
동 285
 
3.5%
Other values (200) 3772
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4969
61.2%
Space Separator 1342
 
16.5%
Decimal Number 1122
 
13.8%
Close Punctuation 281
 
3.5%
Open Punctuation 281
 
3.5%
Dash Punctuation 52
 
0.6%
Other Punctuation 40
 
0.5%
Uppercase Letter 29
 
0.4%
Other Symbol 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 396
 
8.0%
제 396
 
8.0%
상 350
 
7.0%
남 329
 
6.6%
도 321
 
6.5%
시 320
 
6.4%
경 314
 
6.3%
동 285
 
5.7%
로 271
 
5.5%
길 146
 
2.9%
Other values (176) 1841
37.0%
Decimal Number
ValueCountFrequency (%)
1 293
26.1%
2 175
15.6%
3 136
12.1%
4 106
 
9.4%
0 84
 
7.5%
5 80
 
7.1%
7 79
 
7.0%
6 69
 
6.1%
8 55
 
4.9%
9 45
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 9
31.0%
T 9
31.0%
P 9
31.0%
J 1
 
3.4%
C 1
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 243
86.5%
] 38
 
13.5%
Open Punctuation
ValueCountFrequency (%)
( 242
86.1%
[ 39
 
13.9%
Space Separator
ValueCountFrequency (%)
1342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Other Punctuation
ValueCountFrequency (%)
, 40
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4970
61.2%
Common 3118
38.4%
Latin 30
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 396
 
8.0%
제 396
 
8.0%
상 350
 
7.0%
남 329
 
6.6%
도 321
 
6.5%
시 320
 
6.4%
경 314
 
6.3%
동 285
 
5.7%
로 271
 
5.5%
길 146
 
2.9%
Other values (177) 1842
37.1%
Common
ValueCountFrequency (%)
1342
43.0%
1 293
 
9.4%
) 243
 
7.8%
( 242
 
7.8%
2 175
 
5.6%
3 136
 
4.4%
4 106
 
3.4%
0 84
 
2.7%
5 80
 
2.6%
7 79
 
2.5%
Other values (7) 338
 
10.8%
Latin
ValueCountFrequency (%)
A 9
30.0%
T 9
30.0%
P 9
30.0%
Ⅱ 1
 
3.3%
J 1
 
3.3%
C 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4969
61.2%
ASCII 3147
38.8%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1342
42.6%
1 293
 
9.3%
) 243
 
7.7%
( 242
 
7.7%
2 175
 
5.6%
3 136
 
4.3%
4 106
 
3.4%
0 84
 
2.7%
5 80
 
2.5%
7 79
 
2.5%
Other values (12) 367
 
11.7%
Hangul
ValueCountFrequency (%)
거 396
 
8.0%
제 396
 
8.0%
상 350
 
7.0%
남 329
 
6.6%
도 321
 
6.5%
시 320
 
6.4%
경 314
 
6.3%
동 285
 
5.7%
로 271
 
5.5%
길 146
 
2.9%
Other values (176) 1841
37.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2017-05-23 00:00:00
Maximum2017-05-23 00:00:00
2023-12-11T08:25:38.345770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:25:38.429469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T08:25:38.496903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역명전화번호
지역명1.0000.995
전화번호0.9951.000

Missing values

2023-12-11T08:25:35.787233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:25:35.891601image/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
0일운면GS25 지세포점<NA>경상남도 거제시 일운면 거제대로 25632017-05-23
1일운면세븐일레븐 거제망치몽돌점<NA>경상남도 거제시 일운면 거제대로 17942017-05-23
2일운면탑훼미리마트 일운점055-681-6660경상남도 거제시 일운면 거제대로 24702017-05-23
3일운면CU 거제 지세포점055-681-8338경상남도 거제시 일운면 거제대로 24802017-05-23
4일운면썬마트 일운점055-681-0075경상남도 거제시 일운면 거제대로 2591(일운주공APT) 상가 103호2017-05-23
5일운면미니스톱 거제구조라점<NA>경상남도 거제시 일운면 구조라로 34-12017-05-23
6일운면삼양상회055-681-3970경상남도 거제시 일운면 구조라로3길 362017-05-23
7일운면GS25 거제일운<NA>경상남도 거제시 일운면 반송재로 481-92017-05-23
8일운면세븐일레븐 소동점<NA>경상남도 거제시 일운면 소동6길 17-32017-05-23
9일운면CU 거제리우점<NA>경상남도 거제시 일운면 옥림3길 302017-05-23
지역명충전소명전화번호도로명주소(지번주소)기준일
304수양동CU 내담점055-638-5359경상남도 거제시 수양로 503(양정동) [보건소 앞]2017-05-23
305수양동GS25 거제쉐르빌점<NA>경상남도 거제시 제산로 2-5 (양정동, 삼성쉐르빌상가)2017-05-23
306수양동CU 힐스점055-632-0190경상남도 거제시 제산로 54(양정동) [힐스테이트아파트 부근]2017-05-23
307수양동CU 양정점055-637-5214경상남도 거제시 제산로3길 6(양정동) [힐스테이트 후문]2017-05-23
308수양동위드미 거제양정점<NA>경상남도 거제시 제산로3안길 18-2(양정동)2017-05-23
309수양동CU 거제수양센텀점<NA>경상남도 거제시 제산윗길 2 (양정동)2017-05-23
310수양동CU 거제수월자이점<NA>경상남도 거제시 해명로 22 (수월동)2017-05-23
311수양동GS25 거제자이점<NA>경상남도 거제시 해명로 49 (수월동)2017-05-23
312수양동CU 거제수월자이2호점<NA>경상남도 거제시 해명로 57(수월동)2017-05-23
313수양동세븐일레븐 거제유리안점<NA>경상남도 거제시 해명로4길 8 (수월동) 상가동 106호 엘리유리안2차2017-05-23