Overview

Dataset statistics

Number of variables8
Number of observations194
Missing cells99
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.3 KiB
Average record size in memory64.7 B

Variable types

Categorical3
Text3
DateTime2

Dataset

Description강원도 평창군 담배 소매인 등록현황에 대한 데이터로 업소명, 지번주소, 도로명주소, 업소전화번호, 영업구분, 지정일자 등의 데이터를 제공합니다.
Author강원도 평창군
URLhttps://www.data.go.kr/data/15035666/fileData.do

Alerts

시군명 has constant value ""Constant
영업구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
민원구분 is highly imbalanced (62.6%)Imbalance
업소전화번호 has 99 (51.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 17:14:54.493382
Analysis finished2023-12-12 17:14:55.023640
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
평창군
194 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평창군 194
100.0%

Length

2023-12-13T02:14:55.079475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:14:55.159237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평창군 194
100.0%

업소명
Text

Distinct193
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T02:14:55.419600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length8.6494845
Min length3

Characters and Unicode

Total characters1678
Distinct characters291
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)99.0%

Sample

1st row대관령원예농협 하나로마트
2nd rowCU 대관령휴게소점
3rd rowGS25 횡계로드점
4th rowGS25횡계점
5th row원주상회
ValueCountFrequency (%)
씨유 11
 
4.1%
세븐일레븐 10
 
3.7%
gs25 8
 
3.0%
미니스톱 6
 
2.2%
하나로마트 4
 
1.5%
국군복지단 4
 
1.5%
주식회사 3
 
1.1%
지에스25 3
 
1.1%
스토리평창 2
 
0.7%
주)코리아세븐 2
 
0.7%
Other values (207) 217
80.4%
2023-12-13T02:14:55.850664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 82
 
4.9%
76
 
4.5%
평 67
 
4.0%
창 50
 
3.0%
트 39
 
2.3%
대 38
 
2.3%
마 37
 
2.2%
븐 30
 
1.8%
2 29
 
1.7%
지 26
 
1.5%
Other values (281) 1204
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1420
84.6%
Space Separator 76
 
4.5%
Decimal Number 69
 
4.1%
Uppercase Letter 63
 
3.8%
Close Punctuation 22
 
1.3%
Open Punctuation 22
 
1.3%
Other Symbol 3
 
0.2%
Lowercase Letter 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 82
 
5.8%
평 67
 
4.7%
창 50
 
3.5%
트 39
 
2.7%
대 38
 
2.7%
마 37
 
2.6%
븐 30
 
2.1%
지 26
 
1.8%
스 24
 
1.7%
유 22
 
1.5%
Other values (258) 1005
70.8%
Decimal Number
ValueCountFrequency (%)
2 29
42.0%
5 25
36.2%
1 4
 
5.8%
4 4
 
5.8%
8 2
 
2.9%
7 2
 
2.9%
0 1
 
1.4%
9 1
 
1.4%
3 1
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
G 18
28.6%
S 17
27.0%
C 13
20.6%
U 8
12.7%
I 5
 
7.9%
T 1
 
1.6%
K 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
u 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1423
84.8%
Common 190
 
11.3%
Latin 65
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 82
 
5.8%
평 67
 
4.7%
창 50
 
3.5%
트 39
 
2.7%
대 38
 
2.7%
마 37
 
2.6%
븐 30
 
2.1%
지 26
 
1.8%
스 24
 
1.7%
유 22
 
1.5%
Other values (259) 1008
70.8%
Common
ValueCountFrequency (%)
76
40.0%
2 29
 
15.3%
5 25
 
13.2%
) 22
 
11.6%
( 22
 
11.6%
1 4
 
2.1%
4 4
 
2.1%
8 2
 
1.1%
7 2
 
1.1%
- 1
 
0.5%
Other values (3) 3
 
1.6%
Latin
ValueCountFrequency (%)
G 18
27.7%
S 17
26.2%
C 13
20.0%
U 8
12.3%
I 5
 
7.7%
u 1
 
1.5%
c 1
 
1.5%
T 1
 
1.5%
K 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1420
84.6%
ASCII 255
 
15.2%
None 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 82
 
5.8%
평 67
 
4.7%
창 50
 
3.5%
트 39
 
2.7%
대 38
 
2.7%
마 37
 
2.6%
븐 30
 
2.1%
지 26
 
1.8%
스 24
 
1.7%
유 22
 
1.5%
Other values (258) 1005
70.8%
ASCII
ValueCountFrequency (%)
76
29.8%
2 29
 
11.4%
5 25
 
9.8%
) 22
 
8.6%
( 22
 
8.6%
G 18
 
7.1%
S 17
 
6.7%
C 13
 
5.1%
U 8
 
3.1%
I 5
 
2.0%
Other values (12) 20
 
7.8%
None
ValueCountFrequency (%)
㈜ 3
100.0%

업소도로명주소
Text

Distinct190
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T02:14:56.174174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length41
Mean length22.871134
Min length17

Characters and Unicode

Total characters4437
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique188 ?
Unique (%)96.9%

Sample

1st row강원도 평창군 대관령면 경강로 4980
2nd row강원도 평창군 대관령면 경강로 5721. 대관령휴게소 1층 3호
3rd row강원도 평창군 대관령면 눈마을길 39
4th row강원도 평창군 대관령면 대관령로 100
5th row강원도 평창군 대관령면 대관령로 103
ValueCountFrequency (%)
강원도 194
18.3%
평창군 194
18.3%
대관령면 50
 
4.7%
봉평면 38
 
3.6%
진부면 32
 
3.0%
평창읍 26
 
2.5%
대화면 19
 
1.8%
태기로 16
 
1.5%
용평면 11
 
1.0%
올림픽로 10
 
0.9%
Other values (307) 471
44.4%
2023-12-13T02:14:56.589480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
884
19.9%
평 295
 
6.6%
창 242
 
5.5%
강 209
 
4.7%
원 196
 
4.4%
군 195
 
4.4%
도 194
 
4.4%
1 188
 
4.2%
면 168
 
3.8%
로 118
 
2.7%
Other values (171) 1748
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2797
63.0%
Space Separator 884
 
19.9%
Decimal Number 652
 
14.7%
Dash Punctuation 38
 
0.9%
Other Punctuation 30
 
0.7%
Open Punctuation 17
 
0.4%
Close Punctuation 17
 
0.4%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 295
 
10.5%
창 242
 
8.7%
강 209
 
7.5%
원 196
 
7.0%
군 195
 
7.0%
도 194
 
6.9%
면 168
 
6.0%
로 118
 
4.2%
대 97
 
3.5%
령 63
 
2.3%
Other values (154) 1020
36.5%
Decimal Number
ValueCountFrequency (%)
1 188
28.8%
3 77
11.8%
2 72
 
11.0%
0 58
 
8.9%
5 54
 
8.3%
4 51
 
7.8%
6 43
 
6.6%
7 42
 
6.4%
9 35
 
5.4%
8 32
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
884
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Other Punctuation
ValueCountFrequency (%)
. 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2797
63.0%
Common 1638
36.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 295
 
10.5%
창 242
 
8.7%
강 209
 
7.5%
원 196
 
7.0%
군 195
 
7.0%
도 194
 
6.9%
면 168
 
6.0%
로 118
 
4.2%
대 97
 
3.5%
령 63
 
2.3%
Other values (154) 1020
36.5%
Common
ValueCountFrequency (%)
884
54.0%
1 188
 
11.5%
3 77
 
4.7%
2 72
 
4.4%
0 58
 
3.5%
5 54
 
3.3%
4 51
 
3.1%
6 43
 
2.6%
7 42
 
2.6%
- 38
 
2.3%
Other values (5) 131
 
8.0%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2797
63.0%
ASCII 1640
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
884
53.9%
1 188
 
11.5%
3 77
 
4.7%
2 72
 
4.4%
0 58
 
3.5%
5 54
 
3.3%
4 51
 
3.1%
6 43
 
2.6%
7 42
 
2.6%
- 38
 
2.3%
Other values (7) 133
 
8.1%
Hangul
ValueCountFrequency (%)
평 295
 
10.5%
창 242
 
8.7%
강 209
 
7.5%
원 196
 
7.0%
군 195
 
7.0%
도 194
 
6.9%
면 168
 
6.0%
로 118
 
4.2%
대 97
 
3.5%
령 63
 
2.3%
Other values (154) 1020
36.5%

업소전화번호
Text

MISSING 

Distinct90
Distinct (%)94.7%
Missing99
Missing (%)51.0%
Memory size1.6 KiB
2023-12-13T02:14:56.793977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.663158
Min length1

Characters and Unicode

Total characters1108
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)91.6%

Sample

1st row 033-335-5880
2nd row033-335-5397
3rd row033-336-5012
4th row033-335-5126
5th row033-335-5961
ValueCountFrequency (%)
033-254-7095 3
 
3.3%
033-333-2724 2
 
2.2%
02-535-6103 1
 
1.1%
033-333-9514 1
 
1.1%
033-332-7383 1
 
1.1%
033-333-8811 1
 
1.1%
033-332-6435 1
 
1.1%
033-335-2332 1
 
1.1%
033-336-8114 1
 
1.1%
033-332-6444 1
 
1.1%
Other values (79) 79
85.9%
2023-12-13T02:14:57.084484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 406
36.6%
- 184
16.6%
0 137
 
12.4%
2 78
 
7.0%
5 73
 
6.6%
1 49
 
4.4%
4 41
 
3.7%
6 36
 
3.2%
7 34
 
3.1%
9 34
 
3.1%
Other values (2) 36
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 918
82.9%
Dash Punctuation 184
 
16.6%
Space Separator 6
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 406
44.2%
0 137
 
14.9%
2 78
 
8.5%
5 73
 
8.0%
1 49
 
5.3%
4 41
 
4.5%
6 36
 
3.9%
7 34
 
3.7%
9 34
 
3.7%
8 30
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 406
36.6%
- 184
16.6%
0 137
 
12.4%
2 78
 
7.0%
5 73
 
6.6%
1 49
 
4.4%
4 41
 
3.7%
6 36
 
3.2%
7 34
 
3.1%
9 34
 
3.1%
Other values (2) 36
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 406
36.6%
- 184
16.6%
0 137
 
12.4%
2 78
 
7.0%
5 73
 
6.6%
1 49
 
4.4%
4 41
 
3.7%
6 36
 
3.2%
7 34
 
3.1%
9 34
 
3.1%
Other values (2) 36
 
3.2%

영업구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
정상영업
194 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 194
100.0%

Length

2023-12-13T02:14:57.192748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:14:57.278913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 194
100.0%

지정일자
Date

Distinct173
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2009-01-12 00:00:00
Maximum2021-09-03 00:00:00
2023-12-13T02:14:57.358767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:14:57.478092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

민원구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
제7조의3제2항에따른경우
180 
제7조의3제3항에따른경우
 
14

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제7조의3제2항에따른경우
2nd row제7조의3제2항에따른경우
3rd row제7조의3제2항에따른경우
4th row제7조의3제2항에따른경우
5th row제7조의3제2항에따른경우

Common Values

ValueCountFrequency (%)
제7조의3제2항에따른경우 180
92.8%
제7조의3제3항에따른경우 14
 
7.2%

Length

2023-12-13T02:14:57.598985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:14:57.898904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제7조의3제2항에따른경우 180
92.8%
제7조의3제3항에따른경우 14
 
7.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-09-23 00:00:00
Maximum2022-09-23 00:00:00
2023-12-13T02:14:57.960480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:14:58.028115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T02:14:58.083991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소전화번호민원구분
업소전화번호1.0001.000
민원구분1.0001.000

Missing values

2023-12-13T02:14:54.865858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:14:54.980218image/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

시군명업소명업소도로명주소업소전화번호영업구분지정일자민원구분데이터기준일자
0평창군대관령원예농협 하나로마트강원도 평창군 대관령면 경강로 4980033-335-5880정상영업2021-09-03제7조의3제2항에따른경우2022-09-23
1평창군CU 대관령휴게소점강원도 평창군 대관령면 경강로 5721. 대관령휴게소 1층 3호<NA>정상영업2021-08-27제7조의3제2항에따른경우2022-09-23
2평창군GS25 횡계로드점강원도 평창군 대관령면 눈마을길 39<NA>정상영업2021-08-30제7조의3제2항에따른경우2022-09-23
3평창군GS25횡계점강원도 평창군 대관령면 대관령로 100033-335-5397정상영업2021-08-30제7조의3제2항에따른경우2022-09-23
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