Overview

Dataset statistics

Number of variables4
Number of observations2846
Missing cells0
Missing cells (%)0.0%
Duplicate rows13
Duplicate rows (%)0.5%
Total size in memory89.1 KiB
Average record size in memory32.0 B

Variable types

Text3
DateTime1

Dataset

Description경상남도 밀양시 밀양사랑상품권 가맹점 현황에 대한 자료로, 가맹점 명, 업종, 주소, 데이터 기준일자에 대한 정보를 제공합니다.
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15103724

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 13 (0.5%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 00:39:18.656902
Analysis finished2023-12-11 00:39:19.398816
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가맹점명
Text

Distinct2774
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
2023-12-11T09:39:19.582306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length6.035137
Min length1

Characters and Unicode

Total characters17176
Distinct characters795
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2712 ?
Unique (%)95.3%

Sample

1st row드림마트
2nd row아디다스밀양대리점
3rd row투피스
4th row경남밀양지역자활센터카페아리랑
5th row경남밀양지역자활센터(cafe밀양)
ValueCountFrequency (%)
밀양점 25
 
0.8%
주식회사 14
 
0.4%
밀양삼문점 10
 
0.3%
세븐일레븐 9
 
0.3%
아모레카운셀러 7
 
0.2%
이마트24 5
 
0.2%
밀양 5
 
0.2%
씨유 5
 
0.2%
필프라이스 5
 
0.2%
드림마트 4
 
0.1%
Other values (2929) 3045
97.2%
2023-12-11T09:39:20.012474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 477
 
2.8%
밀 458
 
2.7%
점 419
 
2.4%
이 305
 
1.8%
리 297
 
1.7%
297
 
1.7%
원 259
 
1.5%
스 258
 
1.5%
식 234
 
1.4%
사 190
 
1.1%
Other values (785) 13982
81.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16270
94.7%
Space Separator 297
 
1.7%
Uppercase Letter 255
 
1.5%
Decimal Number 146
 
0.9%
Other Punctuation 68
 
0.4%
Lowercase Letter 58
 
0.3%
Open Punctuation 35
 
0.2%
Close Punctuation 35
 
0.2%
Other Symbol 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 477
 
2.9%
밀 458
 
2.8%
점 419
 
2.6%
이 305
 
1.9%
리 297
 
1.8%
원 259
 
1.6%
스 258
 
1.6%
식 234
 
1.4%
사 190
 
1.2%
마 174
 
1.1%
Other values (722) 13199
81.1%
Uppercase Letter
ValueCountFrequency (%)
C 45
17.6%
G 32
12.5%
U 28
11.0%
S 28
11.0%
P 13
 
5.1%
B 11
 
4.3%
K 11
 
4.3%
L 10
 
3.9%
A 10
 
3.9%
O 9
 
3.5%
Other values (14) 58
22.7%
Lowercase Letter
ValueCountFrequency (%)
e 12
20.7%
a 6
10.3%
h 5
8.6%
c 5
8.6%
f 5
8.6%
i 4
 
6.9%
t 3
 
5.2%
u 3
 
5.2%
b 2
 
3.4%
y 2
 
3.4%
Other values (8) 11
19.0%
Decimal Number
ValueCountFrequency (%)
2 47
32.2%
5 26
17.8%
1 14
 
9.6%
4 13
 
8.9%
8 12
 
8.2%
3 12
 
8.2%
9 10
 
6.8%
0 5
 
3.4%
6 4
 
2.7%
7 3
 
2.1%
Other Punctuation
ValueCountFrequency (%)
& 31
45.6%
. 16
23.5%
, 13
19.1%
# 5
 
7.4%
… 1
 
1.5%
· 1
 
1.5%
! 1
 
1.5%
Space Separator
ValueCountFrequency (%)
297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16280
94.8%
Common 581
 
3.4%
Latin 313
 
1.8%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 477
 
2.9%
밀 458
 
2.8%
점 419
 
2.6%
이 305
 
1.9%
리 297
 
1.8%
원 259
 
1.6%
스 258
 
1.6%
식 234
 
1.4%
사 190
 
1.2%
마 174
 
1.1%
Other values (722) 13209
81.1%
Latin
ValueCountFrequency (%)
C 45
 
14.4%
G 32
 
10.2%
U 28
 
8.9%
S 28
 
8.9%
P 13
 
4.2%
e 12
 
3.8%
B 11
 
3.5%
K 11
 
3.5%
L 10
 
3.2%
A 10
 
3.2%
Other values (32) 113
36.1%
Common
ValueCountFrequency (%)
297
51.1%
2 47
 
8.1%
( 35
 
6.0%
) 35
 
6.0%
& 31
 
5.3%
5 26
 
4.5%
. 16
 
2.8%
1 14
 
2.4%
4 13
 
2.2%
, 13
 
2.2%
Other values (10) 54
 
9.3%
Han
ValueCountFrequency (%)
金 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16268
94.7%
ASCII 892
 
5.2%
None 13
 
0.1%
CJK 2
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 477
 
2.9%
밀 458
 
2.8%
점 419
 
2.6%
이 305
 
1.9%
리 297
 
1.8%
원 259
 
1.6%
스 258
 
1.6%
식 234
 
1.4%
사 190
 
1.2%
마 174
 
1.1%
Other values (721) 13197
81.1%
ASCII
ValueCountFrequency (%)
297
33.3%
2 47
 
5.3%
C 45
 
5.0%
( 35
 
3.9%
) 35
 
3.9%
G 32
 
3.6%
& 31
 
3.5%
U 28
 
3.1%
S 28
 
3.1%
5 26
 
2.9%
Other values (50) 288
32.3%
None
ValueCountFrequency (%)
㈜ 12
92.3%
· 1
 
7.7%
CJK
ValueCountFrequency (%)
金 2
100.0%
Punctuation
ValueCountFrequency (%)
… 1
100.0%

업종
Text

Distinct592
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
2023-12-11T09:39:20.325303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length2
Mean length3.1099789
Min length1

Characters and Unicode

Total characters8851
Distinct characters329
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

Unique416 ?
Unique (%)14.6%

Sample

1st row마트
2nd row의류
3rd row음료
4th row음료
5th row음료
ValueCountFrequency (%)
음식 501
 
16.4%
한식 231
 
7.6%
기타 170
 
5.6%
식품 135
 
4.4%
미용 119
 
3.9%
의류 117
 
3.8%
편의점 85
 
2.8%
음식점업 67
 
2.2%
음료 64
 
2.1%
잡화 58
 
1.9%
Other values (567) 1506
49.3%
2023-12-11T09:39:20.825472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 1145
 
12.9%
음 721
 
8.1%
업 310
 
3.5%
한 284
 
3.2%
점 267
 
3.0%
의 264
 
3.0%
기 246
 
2.8%
품 234
 
2.6%
용 225
 
2.5%
215
 
2.4%
Other values (319) 4940
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8404
94.9%
Space Separator 215
 
2.4%
Other Punctuation 153
 
1.7%
Uppercase Letter 55
 
0.6%
Close Punctuation 12
 
0.1%
Open Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 1145
 
13.6%
음 721
 
8.6%
업 310
 
3.7%
한 284
 
3.4%
점 267
 
3.2%
의 264
 
3.1%
기 246
 
2.9%
품 234
 
2.8%
용 225
 
2.7%
타 192
 
2.3%
Other values (307) 4516
53.7%
Uppercase Letter
ValueCountFrequency (%)
P 18
32.7%
L 17
30.9%
G 16
29.1%
C 2
 
3.6%
D 1
 
1.8%
E 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 147
96.1%
/ 4
 
2.6%
. 2
 
1.3%
Space Separator
ValueCountFrequency (%)
215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8404
94.9%
Common 392
 
4.4%
Latin 55
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 1145
 
13.6%
음 721
 
8.6%
업 310
 
3.7%
한 284
 
3.4%
점 267
 
3.2%
의 264
 
3.1%
기 246
 
2.9%
품 234
 
2.8%
용 225
 
2.7%
타 192
 
2.3%
Other values (307) 4516
53.7%
Common
ValueCountFrequency (%)
215
54.8%
, 147
37.5%
) 12
 
3.1%
( 12
 
3.1%
/ 4
 
1.0%
. 2
 
0.5%
Latin
ValueCountFrequency (%)
P 18
32.7%
L 17
30.9%
G 16
29.1%
C 2
 
3.6%
D 1
 
1.8%
E 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8404
94.9%
ASCII 447
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 1145
 
13.6%
음 721
 
8.6%
업 310
 
3.7%
한 284
 
3.4%
점 267
 
3.2%
의 264
 
3.1%
기 246
 
2.9%
품 234
 
2.8%
용 225
 
2.7%
타 192
 
2.3%
Other values (307) 4516
53.7%
ASCII
ValueCountFrequency (%)
215
48.1%
, 147
32.9%
P 18
 
4.0%
L 17
 
3.8%
G 16
 
3.6%
) 12
 
2.7%
( 12
 
2.7%
/ 4
 
0.9%
. 2
 
0.4%
C 2
 
0.4%
Other values (2) 2
 
0.4%

주소
Text

Distinct2453
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
2023-12-11T09:39:21.120559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length14.469431
Min length1

Characters and Unicode

Total characters41180
Distinct characters227
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2170 ?
Unique (%)76.2%

Sample

1st row밀양시 산외면 표충로 14
2nd row밀양시 석정로 30-1
3rd row밀양시 중앙로 300-34, 3,4층
4th row밀양시 밀양대로 2047
5th row밀양시 중앙로 118, 라동 1층
ValueCountFrequency (%)
밀양시 2784
27.7%
1층 333
 
3.3%
중앙로 290
 
2.9%
하남읍 157
 
1.6%
밀양대로 136
 
1.4%
석정로 133
 
1.3%
상남면 110
 
1.1%
2층 107
 
1.1%
미리벌중앙로 101
 
1.0%
북성로 96
 
1.0%
Other values (1663) 5813
57.8%
2023-12-11T09:39:21.618116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7230
17.6%
시 3019
 
7.3%
밀 2977
 
7.2%
양 2966
 
7.2%
1 2649
 
6.4%
로 1912
 
4.6%
2 1432
 
3.5%
3 1202
 
2.9%
길 1041
 
2.5%
- 988
 
2.4%
Other values (217) 15764
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22704
55.1%
Decimal Number 9612
23.3%
Space Separator 7230
 
17.6%
Dash Punctuation 988
 
2.4%
Other Punctuation 602
 
1.5%
Open Punctuation 19
 
< 0.1%
Close Punctuation 19
 
< 0.1%
Math Symbol 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3019
 
13.3%
밀 2977
 
13.1%
양 2966
 
13.1%
로 1912
 
8.4%
길 1041
 
4.6%
중 675
 
3.0%
앙 670
 
3.0%
면 536
 
2.4%
층 483
 
2.1%
리 452
 
2.0%
Other values (198) 7973
35.1%
Decimal Number
ValueCountFrequency (%)
1 2649
27.6%
2 1432
14.9%
3 1202
12.5%
4 867
 
9.0%
5 693
 
7.2%
7 604
 
6.3%
6 598
 
6.2%
8 553
 
5.8%
0 513
 
5.3%
9 501
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 600
99.7%
. 2
 
0.3%
Space Separator
ValueCountFrequency (%)
7230
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 988
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22704
55.1%
Common 18473
44.9%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3019
 
13.3%
밀 2977
 
13.1%
양 2966
 
13.1%
로 1912
 
8.4%
길 1041
 
4.6%
중 675
 
3.0%
앙 670
 
3.0%
면 536
 
2.4%
층 483
 
2.1%
리 452
 
2.0%
Other values (198) 7973
35.1%
Common
ValueCountFrequency (%)
7230
39.1%
1 2649
 
14.3%
2 1432
 
7.8%
3 1202
 
6.5%
- 988
 
5.3%
4 867
 
4.7%
5 693
 
3.8%
7 604
 
3.3%
, 600
 
3.2%
6 598
 
3.2%
Other values (7) 1610
 
8.7%
Latin
ValueCountFrequency (%)
c 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22704
55.1%
ASCII 18476
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7230
39.1%
1 2649
 
14.3%
2 1432
 
7.8%
3 1202
 
6.5%
- 988
 
5.3%
4 867
 
4.7%
5 693
 
3.8%
7 604
 
3.3%
, 600
 
3.2%
6 598
 
3.2%
Other values (9) 1613
 
8.7%
Hangul
ValueCountFrequency (%)
시 3019
 
13.3%
밀 2977
 
13.1%
양 2966
 
13.1%
로 1912
 
8.4%
길 1041
 
4.6%
중 675
 
3.0%
앙 670
 
3.0%
면 536
 
2.4%
층 483
 
2.1%
리 452
 
2.0%
Other values (198) 7973
35.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.4 KiB
Minimum2022-08-01 00:00:00
Maximum2022-08-01 00:00:00
2023-12-11T09:39:21.724307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:39:21.810994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-11T09:39:19.277954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:39:19.361587image/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

가맹점명업종주소데이터기준일자
0드림마트마트밀양시 산외면 표충로 142022-08-01
1아디다스밀양대리점의류밀양시 석정로 30-12022-08-01
2투피스음료밀양시 중앙로 300-34, 3,4층2022-08-01
3경남밀양지역자활센터카페아리랑음료밀양시 밀양대로 20472022-08-01
4경남밀양지역자활센터(cafe밀양)음료밀양시 중앙로 118, 라동 1층2022-08-01
5미리벌밀면음식밀양시 삼문중앙로6길 252022-08-01
6휠라밀양대리점의류밀양시 석정로 15-22022-08-01
7서울마님죽음식밀양시 중앙로 359, 1층2022-08-01
8삼수장군음식밀양시 터미널2길 112022-08-01
9손형주피부사랑미용밀양시 노상하1길 42022-08-01
가맹점명업종주소데이터기준일자
2836봄이오면….화초 및 식물 소매업밀양시 중앙로 234-3, 2동 131호(삼문동, 유성청구상가타운)2022-08-01
2837청구건강원건강원밀양시 중앙로 234-3, 1층(삼문동, 유성청구상가타운)2022-08-01
2838세븐일레븐사포공단점편의점밀양시 부북면 사포산단2길 31-132022-08-01
2839의료법인 은성의료재단 좋은연인요양병원보건업밀양시 삼랑진읍 천태로 355-99(,산59-2)2022-08-01
2840오가네돼지국밥음식점업밀양시 청도면 창밀로 2279, 나동2022-08-01
2841장미미용실미용실밀양시 북성로 162022-08-01
2842이정훈내과의원병원밀양시 내일동 389 2 층2022-08-01
2843황금꽃화원꽃집밀양시 내일동 211-22022-08-01
2844은하유통도매및소매업밀양시 상남면 양림동촌2길 692022-08-01
2845용전주유소주유소밀양시 산내면 밀양대로 3666-402022-08-01

Duplicate rows

Most frequently occurring

가맹점명업종주소데이터기준일자# duplicates
2밀양LPG충전소LPG가스밀양시 상남면 밀양대로 13672022-08-013
6아모레카운셀러화장품밀양시 내이동 721-42022-08-013
0구이구이한식밀양시 북성로 23-12022-08-012
1마왕족발음식밀양시 미리벌중앙로1길 282022-08-012
3본죽&비빔밥카페음식밀양시 석정로 372022-08-012
4산내의원일반의원밀양시 산내면 송백1길 202022-08-012
5삼문동면돈한식밀양시 미리벌중앙로1길 282022-08-012
7일월상사의류밀양시 상설시장1길 13-12022-08-012
8장성통닭음식밀양시 가곡8길 32022-08-012
9장어본가한식밀양시 단장면 표충로 2192022-08-012