Overview

Dataset statistics

Number of variables6
Number of observations370
Missing cells11
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.8 KiB
Average record size in memory49.4 B

Variable types

Text4
Numeric1
Categorical1

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

기준일자 has constant value ""Constant
전화번호 has 11 (3.0%) missing valuesMissing
가맹점명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:25:29.564373
Analysis finished2023-12-10 23:25:30.143281
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가맹점명
Text

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-11T08:25:30.383328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length10.762162
Min length6

Characters and Unicode

Total characters3982
Distinct characters258
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

Unique370 ?
Unique (%)100.0%

Sample

1st row이마트24 거제유스호스텔점
2nd rowGS25 거제해금강점
3rd row이마트24 바람의언덕점
4th rowCU 거제바람의언덕점
5th row엔젤 바람의언덕점
ValueCountFrequency (%)
cu 104
 
14.2%
gs25 82
 
11.2%
세븐일레븐 47
 
6.4%
k7 32
 
4.4%
ms 26
 
3.5%
이마트24 25
 
3.4%
br 7
 
1.0%
롯데리아 6
 
0.8%
거제아주점 5
 
0.7%
엔젤 5
 
0.7%
Other values (338) 394
53.8%
2023-12-11T08:25:30.866719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
363
 
9.1%
점 344
 
8.6%
거 280
 
7.0%
제 280
 
7.0%
2 141
 
3.5%
S 119
 
3.0%
C 105
 
2.6%
U 104
 
2.6%
븐 94
 
2.4%
5 92
 
2.3%
Other values (248) 2060
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2642
66.3%
Uppercase Letter 570
 
14.3%
Decimal Number 399
 
10.0%
Space Separator 363
 
9.1%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 344
 
13.0%
거 280
 
10.6%
제 280
 
10.6%
븐 94
 
3.6%
포 85
 
3.2%
아 55
 
2.1%
장 54
 
2.0%
레 53
 
2.0%
일 52
 
2.0%
세 51
 
1.9%
Other values (221) 1294
49.0%
Uppercase Letter
ValueCountFrequency (%)
S 119
20.9%
C 105
18.4%
U 104
18.2%
G 85
14.9%
K 35
 
6.1%
T 31
 
5.4%
M 26
 
4.6%
B 21
 
3.7%
P 19
 
3.3%
D 11
 
1.9%
Other values (4) 14
 
2.5%
Decimal Number
ValueCountFrequency (%)
2 141
35.3%
5 92
23.1%
4 45
 
11.3%
7 44
 
11.0%
1 24
 
6.0%
8 12
 
3.0%
3 12
 
3.0%
9 11
 
2.8%
0 10
 
2.5%
6 8
 
2.0%
Space Separator
ValueCountFrequency (%)
363
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2642
66.3%
Common 770
 
19.3%
Latin 570
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 344
 
13.0%
거 280
 
10.6%
제 280
 
10.6%
븐 94
 
3.6%
포 85
 
3.2%
아 55
 
2.1%
장 54
 
2.0%
레 53
 
2.0%
일 52
 
2.0%
세 51
 
1.9%
Other values (221) 1294
49.0%
Latin
ValueCountFrequency (%)
S 119
20.9%
C 105
18.4%
U 104
18.2%
G 85
14.9%
K 35
 
6.1%
T 31
 
5.4%
M 26
 
4.6%
B 21
 
3.7%
P 19
 
3.3%
D 11
 
1.9%
Other values (4) 14
 
2.5%
Common
ValueCountFrequency (%)
363
47.1%
2 141
 
18.3%
5 92
 
11.9%
4 45
 
5.8%
7 44
 
5.7%
1 24
 
3.1%
8 12
 
1.6%
3 12
 
1.6%
9 11
 
1.4%
0 10
 
1.3%
Other values (3) 16
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2642
66.3%
ASCII 1340
33.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
363
27.1%
2 141
 
10.5%
S 119
 
8.9%
C 105
 
7.8%
U 104
 
7.8%
5 92
 
6.9%
G 85
 
6.3%
4 45
 
3.4%
7 44
 
3.3%
K 35
 
2.6%
Other values (17) 207
15.4%
Hangul
ValueCountFrequency (%)
점 344
 
13.0%
거 280
 
10.6%
제 280
 
10.6%
븐 94
 
3.6%
포 85
 
3.2%
아 55
 
2.1%
장 54
 
2.0%
레 53
 
2.0%
일 52
 
2.0%
세 51
 
1.9%
Other values (221) 1294
49.0%

주소
Text

UNIQUE 

Distinct370
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-11T08:25:31.131422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length52.5
Mean length29.081081
Min length15

Characters and Unicode

Total characters10760
Distinct characters231
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

Unique370 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 남부면 거제대로 283 (남부면)
2nd row경상남도 거제시 남부면 해금강3길 2 (남부면)
3rd row경상남도 거제시 남부면 갈곶리 남부면 해금강로 124，주2동
4th row경상남도 거제시 남부면 도장포1길 2 (남부면)
5th row경상남도 거제시 남부면 다대리 해금강로 121
ValueCountFrequency (%)
거제시 371
 
16.4%
경상남도 370
 
16.4%
고현동 105
 
4.7%
장평동 71
 
3.1%
아주동 58
 
2.6%
옥포동 53
 
2.3%
1층 39
 
1.7%
일운면 22
 
1.0%
능포동 22
 
1.0%
옥포1동 22
 
1.0%
Other values (621) 1124
49.8%
2023-12-11T08:25:31.559566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1887
 
17.5%
동 573
 
5.3%
1 535
 
5.0%
제 470
 
4.4%
거 457
 
4.2%
상 450
 
4.2%
남 385
 
3.6%
도 374
 
3.5%
경 372
 
3.5%
시 372
 
3.5%
Other values (221) 4885
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6378
59.3%
Space Separator 1887
 
17.5%
Decimal Number 1770
 
16.4%
Close Punctuation 246
 
2.3%
Open Punctuation 245
 
2.3%
Dash Punctuation 130
 
1.2%
Other Punctuation 72
 
0.7%
Math Symbol 15
 
0.1%
Uppercase Letter 13
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 573
 
9.0%
제 470
 
7.4%
거 457
 
7.2%
상 450
 
7.1%
남 385
 
6.0%
도 374
 
5.9%
경 372
 
5.8%
시 372
 
5.8%
로 241
 
3.8%
포 208
 
3.3%
Other values (195) 2476
38.8%
Decimal Number
ValueCountFrequency (%)
1 535
30.2%
2 240
13.6%
3 181
 
10.2%
0 170
 
9.6%
4 154
 
8.7%
5 128
 
7.2%
7 100
 
5.6%
9 99
 
5.6%
6 99
 
5.6%
8 64
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
30.8%
A 2
15.4%
S 1
 
7.7%
G 1
 
7.7%
R 1
 
7.7%
P 1
 
7.7%
I 1
 
7.7%
K 1
 
7.7%
L 1
 
7.7%
Space Separator
ValueCountFrequency (%)
1887
100.0%
Close Punctuation
ValueCountFrequency (%)
) 246
100.0%
Open Punctuation
ValueCountFrequency (%)
( 245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Other Punctuation
ValueCountFrequency (%)
， 72
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6378
59.3%
Common 4365
40.6%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 573
 
9.0%
제 470
 
7.4%
거 457
 
7.2%
상 450
 
7.1%
남 385
 
6.0%
도 374
 
5.9%
경 372
 
5.8%
시 372
 
5.8%
로 241
 
3.8%
포 208
 
3.3%
Other values (195) 2476
38.8%
Common
ValueCountFrequency (%)
1887
43.2%
1 535
 
12.3%
) 246
 
5.6%
( 245
 
5.6%
2 240
 
5.5%
3 181
 
4.1%
0 170
 
3.9%
4 154
 
3.5%
- 130
 
3.0%
5 128
 
2.9%
Other values (6) 449
 
10.3%
Latin
ValueCountFrequency (%)
B 4
23.5%
e 4
23.5%
A 2
11.8%
S 1
 
5.9%
G 1
 
5.9%
R 1
 
5.9%
P 1
 
5.9%
I 1
 
5.9%
K 1
 
5.9%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6378
59.3%
ASCII 4310
40.1%
None 72
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1887
43.8%
1 535
 
12.4%
) 246
 
5.7%
( 245
 
5.7%
2 240
 
5.6%
3 181
 
4.2%
0 170
 
3.9%
4 154
 
3.6%
- 130
 
3.0%
5 128
 
3.0%
Other values (15) 394
 
9.1%
Hangul
ValueCountFrequency (%)
동 573
 
9.0%
제 470
 
7.4%
거 457
 
7.2%
상 450
 
7.1%
남 385
 
6.0%
도 374
 
5.9%
경 372
 
5.8%
시 372
 
5.8%
로 241
 
3.8%
포 208
 
3.3%
Other values (195) 2476
38.8%
None
ValueCountFrequency (%)
， 72
100.0%

위도
Real number (ℝ)

Distinct369
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.881771
Minimum34.738226
Maximum35.012848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-11T08:25:31.707078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.738226
5-th percentile34.823225
Q134.868606
median34.888457
Q334.893526
95-th percentile34.930404
Maximum35.012848
Range0.2746216
Interquartile range (IQR)0.024919955

Descriptive statistics

Standard deviation0.03490144
Coefficient of variation (CV)0.0010005639
Kurtosis5.6966535
Mean34.881771
Median Absolute Deviation (MAD)0.00926238
Skewness-0.93055505
Sum12906.255
Variance0.0012181105
MonotonicityNot monotonic
2023-12-11T08:25:31.857944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.85783569 2
 
0.5%
34.73822631 1
 
0.3%
34.89183186 1
 
0.3%
34.8922358 1
 
0.3%
34.892108 1
 
0.3%
34.89207845 1
 
0.3%
34.89207004 1
 
0.3%
34.89205309 1
 
0.3%
34.89200965 1
 
0.3%
34.89199993 1
 
0.3%
Other values (359) 359
97.0%
ValueCountFrequency (%)
34.73822631 1
0.3%
34.73824981 1
0.3%
34.74048399 1
0.3%
34.74080557 1
0.3%
34.74087944 1
0.3%
34.74331041 1
0.3%
34.77275962 1
0.3%
34.77283076 1
0.3%
34.77519149 1
0.3%
34.77592623 1
0.3%
ValueCountFrequency (%)
35.01284791 1
0.3%
35.00520281 1
0.3%
34.98744927 1
0.3%
34.98614741 1
0.3%
34.98108825 1
0.3%
34.97403577 1
0.3%
34.9733378 1
0.3%
34.97080338 1
0.3%
34.96817224 1
0.3%
34.95693723 1
0.3%

경도
Text

Distinct369
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-11T08:25:32.144877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.87027
Min length1

Characters and Unicode

Total characters4022
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique368 ?
Unique (%)99.5%

Sample

1st row128.6385152
2nd row128.6742253
3rd row128.6630279
4th row128.6619165
5th row128.6632494
ValueCountFrequency (%)
128.645127 2
 
0.5%
128.6170567 1
 
0.3%
128.6953264 1
 
0.3%
128.6033827 1
 
0.3%
128.6110848 1
 
0.3%
128.6915541 1
 
0.3%
128.6404606 1
 
0.3%
128.6926586 1
 
0.3%
128.6402852 1
 
0.3%
128.6278118 1
 
0.3%
Other values (359) 359
97.0%
2023-12-11T08:25:32.512490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 652
16.2%
1 613
15.2%
8 582
14.5%
6 490
12.2%
. 369
9.2%
9 248
 
6.2%
4 230
 
5.7%
7 224
 
5.6%
3 221
 
5.5%
5 219
 
5.4%
Other values (2) 174
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3652
90.8%
Other Punctuation 369
 
9.2%
Other Letter 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 652
17.9%
1 613
16.8%
8 582
15.9%
6 490
13.4%
9 248
 
6.8%
4 230
 
6.3%
7 224
 
6.1%
3 221
 
6.1%
5 219
 
6.0%
0 173
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 369
100.0%
Other Letter
ValueCountFrequency (%)
안 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4021
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 652
16.2%
1 613
15.2%
8 582
14.5%
6 490
12.2%
. 369
9.2%
9 248
 
6.2%
4 230
 
5.7%
7 224
 
5.6%
3 221
 
5.5%
5 219
 
5.4%
Hangul
ValueCountFrequency (%)
안 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4021
> 99.9%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 652
16.2%
1 613
15.2%
8 582
14.5%
6 490
12.2%
. 369
9.2%
9 248
 
6.2%
4 230
 
5.7%
7 224
 
5.6%
3 221
 
5.5%
5 219
 
5.4%
Hangul
ValueCountFrequency (%)
안 1
100.0%

전화번호
Text

MISSING 

Distinct103
Distinct (%)28.7%
Missing11
Missing (%)3.0%
Memory size3.0 KiB
2023-12-11T08:25:32.798444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.493036
Min length9

Characters and Unicode

Total characters4126
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

Unique88 ?
Unique (%)24.5%

Sample

1st row02-3284-8168
2nd row055-687-7900
3rd row1577-8007
4th row080-555-5525
5th row1577-8007
ValueCountFrequency (%)
02-3284-8168 69
19.2%
1577-8007 62
17.3%
080-555-2525 56
15.6%
02-6916-1500 22
 
6.1%
02-1577-9621 20
 
5.6%
080-555-5525 12
 
3.3%
080-855-5525 12
 
3.3%
02-2006-2954 3
 
0.8%
031-340-4260 3
 
0.8%
055-297-1293 2
 
0.6%
Other values (93) 98
27.3%
2023-12-11T08:25:33.195959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 748
18.1%
- 656
15.9%
0 621
15.1%
8 454
11.0%
2 437
10.6%
7 297
 
7.2%
1 270
 
6.5%
6 254
 
6.2%
3 174
 
4.2%
4 120
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3470
84.1%
Dash Punctuation 656
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 748
21.6%
0 621
17.9%
8 454
13.1%
2 437
12.6%
7 297
 
8.6%
1 270
 
7.8%
6 254
 
7.3%
3 174
 
5.0%
4 120
 
3.5%
9 95
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4126
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 748
18.1%
- 656
15.9%
0 621
15.1%
8 454
11.0%
2 437
10.6%
7 297
 
7.2%
1 270
 
6.5%
6 254
 
6.2%
3 174
 
4.2%
4 120
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 748
18.1%
- 656
15.9%
0 621
15.1%
8 454
11.0%
2 437
10.6%
7 297
 
7.2%
1 270
 
6.5%
6 254
 
6.2%
3 174
 
4.2%
4 120
 
2.9%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2021-09-30
370 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-30
2nd row2021-09-30
3rd row2021-09-30
4th row2021-09-30
5th row2021-09-30

Common Values

ValueCountFrequency (%)
2021-09-30 370
100.0%

Length

2023-12-11T08:25:33.329626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:25:33.418355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-30 370
100.0%

Interactions

2023-12-11T08:25:29.877113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-11T08:25:29.984298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:25:30.097110image/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

가맹점명주소위도경도전화번호기준일자
0이마트24 거제유스호스텔점경상남도 거제시 남부면 거제대로 283 (남부면)34.738226128.638515202-3284-81682021-09-30
1GS25 거제해금강점경상남도 거제시 남부면 해금강3길 2 (남부면)34.73825128.6742253055-687-79002021-09-30
2이마트24 바람의언덕점경상남도 거제시 남부면 갈곶리 남부면 해금강로 124，주2동34.740484128.66302791577-80072021-09-30
3CU 거제바람의언덕점경상남도 거제시 남부면 도장포1길 2 (남부면)34.740806128.6619165080-555-55252021-09-30
4엔젤 바람의언덕점경상남도 거제시 남부면 다대리 해금강로 12134.740879128.66324941577-80072021-09-30
5이마트24 거제도장포점경상남도 거제시 남부면 갈곶리 292-1634.74331128.66215502-3284-81682021-09-30
6CU 거제학동바다점경상남도 거제시 동부면 학동4길 2 (동부면)34.77276128.639011102-3284-81682021-09-30
7CU 거제학동다바다점경상남도 거제시 동부면 거제대로 924 (동부면)34.772831128.639197402-6916-15002021-09-30
8세븐일레븐 거제몽돌점경상남도 거제시 동부면 거제중앙로 6 (동부면)34.775191128.641127602-3284-81682021-09-30
9CU 거제학동몽돌점경상남도 거제시 동부면 거제대로 965 (동부면)34.775926128.641974502-3284-81682021-09-30
가맹점명주소위도경도전화번호기준일자
360세븐일레븐 거제하청LH점경상남도 거제시 하청면 하청2길 12 (하청면，국민주택)34.956937128.6578501055-681-51412021-09-30
361세븐일레븐 거제매미성점경상남도 거제시 장목면 옥포대첩로 1298 (장목면) 1층34.968172128.7023129080-555-25252021-09-30
362세븐일레븐 거제라모타점경상남도 거제시 사등면 가조로 1025 (사등면)34.970803128.5327334080-555-25252021-09-30
363CU 거가대교거제휴게소경상남도 거제시 장목면 거가대로 1068 (장목면)34.973338128.69287311577-80072021-09-30
364GS25 거제실전점경상남도 거제시 하청면 거제북로 83434.974036128.6565633055-687-83082021-09-30
365세븐일레븐 거제칠천도점경상남도 거제시 하청면 칠천출장소 칠천로 114 (하청면)34.981088128.645919102-3284-81682021-09-30
366GS25 거제장목점경상남도 거제시 장목면 거제북로 1138-2 (장목면)34.986147128.67853391577-80072021-09-30
367MS 거제장목점경상남도 거제시 장목면 거제북로 1167 (장목면) 1층34.987449128.6810749080-555-25252021-09-30
368이마트24 거제농소몽돌점경상남도 거제시 장목면 거제북로 2594 (장목면)35.005203128.700909802-3284-81682021-09-30
369GS25 한화리조트거제점경상남도 거제시 장목면 농소리 149 한화호텔앤드리조트 거제벨버디어 4층35.012848128.706968502-3284-81682021-09-30