Overview

Dataset statistics

Number of variables5
Number of observations70
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory41.9 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description충청남도 부여군에 등록된 의약품 판매업소 현황에 대한 정보입니다. (업소이름, 분야, 위치, 전화번호, 데이터기준일자)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=444&beforeMenuCd=DOM_000000201001001000&publicdatapk=3046035

Alerts

데이터기준일자 has constant value ""Constant
판매업소명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:11:41.024987
Analysis finished2024-01-09 22:11:41.374859
Duration0.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
약국
35 
안전상비의약품판매업소
17 
한약업사
11 
의약품도매상
 
3
약업사
 
3

Length

Max length11
Median length8.5
Mean length4.7285714
Min length2

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
약국 35
50.0%
안전상비의약품판매업소 17
24.3%
한약업사 11
 
15.7%
의약품도매상 3
 
4.3%
약업사 3
 
4.3%
한약국 1
 
1.4%

Length

2024-01-10T07:11:41.422596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:11:41.527174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
약국 35
50.0%
안전상비의약품판매업소 17
24.3%
한약업사 11
 
15.7%
의약품도매상 3
 
4.3%
약업사 3
 
4.3%
한약국 1
 
1.4%

판매업소명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-01-10T07:11:41.757326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.7571429
Min length3

Characters and Unicode

Total characters403
Distinct characters115
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

Unique70 ?
Unique (%)100.0%

Sample

1st row행복약국
2nd row홍산예약국
3rd row은혜약국
4th row홍산종로약국
5th row솔약국
ValueCountFrequency (%)
행복약국 1
 
1.4%
우리들약국 1
 
1.4%
광제한약방 1
 
1.4%
세창한약방 1
 
1.4%
대성당한약방 1
 
1.4%
동광한약방 1
 
1.4%
대생당한약방 1
 
1.4%
동산한약방 1
 
1.4%
장춘당한약방 1
 
1.4%
씨유부여로터리점 1
 
1.4%
Other values (62) 62
86.1%
2024-01-10T07:11:42.070531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
12.9%
36
 
8.9%
23
 
5.7%
20
 
5.0%
14
 
3.5%
14
 
3.5%
13
 
3.2%
9
 
2.2%
8
 
2.0%
7
 
1.7%
Other values (105) 207
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 381
94.5%
Decimal Number 6
 
1.5%
Uppercase Letter 6
 
1.5%
Close Punctuation 4
 
1.0%
Open Punctuation 4
 
1.0%
Space Separator 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
52
 
13.6%
36
 
9.4%
23
 
6.0%
20
 
5.2%
14
 
3.7%
14
 
3.7%
13
 
3.4%
9
 
2.4%
8
 
2.1%
7
 
1.8%
Other values (98) 185
48.6%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
5 3
50.0%
Uppercase Letter
ValueCountFrequency (%)
G 3
50.0%
S 3
50.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 381
94.5%
Common 16
 
4.0%
Latin 6
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
52
 
13.6%
36
 
9.4%
23
 
6.0%
20
 
5.2%
14
 
3.7%
14
 
3.7%
13
 
3.4%
9
 
2.4%
8
 
2.1%
7
 
1.8%
Other values (98) 185
48.6%
Common
ValueCountFrequency (%)
) 4
25.0%
( 4
25.0%
2 3
18.8%
5 3
18.8%
2
12.5%
Latin
ValueCountFrequency (%)
G 3
50.0%
S 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 381
94.5%
ASCII 22
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
52
 
13.6%
36
 
9.4%
23
 
6.0%
20
 
5.2%
14
 
3.7%
14
 
3.7%
13
 
3.4%
9
 
2.4%
8
 
2.1%
7
 
1.8%
Other values (98) 185
48.6%
ASCII
ValueCountFrequency (%)
) 4
18.2%
( 4
18.2%
2 3
13.6%
G 3
13.6%
S 3
13.6%
5 3
13.6%
2
9.1%

도로명주소
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-01-10T07:11:42.295295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27
Mean length21.628571
Min length19

Characters and Unicode

Total characters1514
Distinct characters79
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st row충청남도 부여군 임천면 성흥로 91-1
2nd row충청남도 부여군 홍산면 홍산로 49
3rd row충청남도 부여군 부여읍 사비로 61
4th row충청남도 부여군 홍산면 홍산로 52-1
5th row충청남도 부여군 부여읍 사비로99번길 8-2
ValueCountFrequency (%)
충청남도 70
19.9%
부여군 70
19.9%
부여읍 43
 
12.3%
성왕로 8
 
2.3%
부여로 7
 
2.0%
홍산면 6
 
1.7%
사비로 6
 
1.7%
중앙로 5
 
1.4%
홍산로 4
 
1.1%
은산면 4
 
1.1%
Other values (99) 128
36.5%
2024-01-10T07:11:42.624047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
346
22.9%
122
 
8.1%
120
 
7.9%
75
 
5.0%
74
 
4.9%
74
 
4.9%
70
 
4.6%
70
 
4.6%
68
 
4.5%
43
 
2.8%
Other values (69) 452
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 953
62.9%
Space Separator 346
 
22.9%
Decimal Number 194
 
12.8%
Dash Punctuation 18
 
1.2%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
122
12.8%
120
12.6%
75
 
7.9%
74
 
7.8%
74
 
7.8%
70
 
7.3%
70
 
7.3%
68
 
7.1%
43
 
4.5%
27
 
2.8%
Other values (54) 210
22.0%
Decimal Number
ValueCountFrequency (%)
1 39
20.1%
6 24
12.4%
2 23
11.9%
8 18
9.3%
3 17
8.8%
7 16
8.2%
9 16
8.2%
0 15
 
7.7%
5 14
 
7.2%
4 12
 
6.2%
Space Separator
ValueCountFrequency (%)
346
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 953
62.9%
Common 561
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
122
12.8%
120
12.6%
75
 
7.9%
74
 
7.8%
74
 
7.8%
70
 
7.3%
70
 
7.3%
68
 
7.1%
43
 
4.5%
27
 
2.8%
Other values (54) 210
22.0%
Common
ValueCountFrequency (%)
346
61.7%
1 39
 
7.0%
6 24
 
4.3%
2 23
 
4.1%
- 18
 
3.2%
8 18
 
3.2%
3 17
 
3.0%
7 16
 
2.9%
9 16
 
2.9%
0 15
 
2.7%
Other values (5) 29
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 953
62.9%
ASCII 561
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
346
61.7%
1 39
 
7.0%
6 24
 
4.3%
2 23
 
4.1%
- 18
 
3.2%
8 18
 
3.2%
3 17
 
3.0%
7 16
 
2.9%
9 16
 
2.9%
0 15
 
2.7%
Other values (5) 29
 
5.2%
Hangul
ValueCountFrequency (%)
122
12.8%
120
12.6%
75
 
7.9%
74
 
7.8%
74
 
7.8%
70
 
7.3%
70
 
7.3%
68
 
7.1%
43
 
4.5%
27
 
2.8%
Other values (54) 210
22.0%

전화번호
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-01-10T07:11:42.835307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters840
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

Unique70 ?
Unique (%)100.0%

Sample

1st row041-832-1363
2nd row041-836-4520
3rd row041-835-1130
4th row041-835-9139
5th row041-835-1600
ValueCountFrequency (%)
041-832-1363 1
 
1.4%
041-836-3777 1
 
1.4%
041-833-0135 1
 
1.4%
041-835-4728 1
 
1.4%
041-832-6101 1
 
1.4%
041-832-3636 1
 
1.4%
041-833-2694 1
 
1.4%
041-834-5842 1
 
1.4%
041-832-3010 1
 
1.4%
041-835-5116 1
 
1.4%
Other values (60) 60
85.7%
2024-01-10T07:11:43.137726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/