Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory43.2 B

Variable types

Numeric1
Text4

Dataset

Description2022년도 충청남도 서산시 모범음식점 및 위생등급제 지정현황
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=450&beforeMenuCd=DOM_000000201001001000&publicdatapk=3068030

Alerts

연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명) has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:35:07.857515
Analysis finished2024-01-09 22:35:08.384529
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-01-10T07:35:08.446622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2024-01-10T07:35:08.567212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

업소명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-10T07:35:08.790403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.4333333
Min length1

Characters and Unicode

Total characters326
Distinct characters156
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row가마솥밥상
2nd row가보
3rd row가야면옥
4th row갈비본가 두툼한숯불갈비
5th row강미루
ValueCountFrequency (%)
가마솥밥상 1
 
1.6%
가보 1
 
1.6%
서산촌닭 1
 
1.6%
서산할매아구찜 1
 
1.6%
웰빙갈비랑메밀막국수 1
 
1.6%
서원생고기 1
 
1.6%
서해안해물맛집 1
 
1.6%
소문난대구왕뽈찜 1
 
1.6%
소청 1
 
1.6%
수복집 1
 
1.6%
Other values (54) 54
84.4%
2024-01-10T07:35:09.159809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 14
 
4.3%
서 12
 
3.7%
대 8
 
2.5%
가 7
 
2.1%
구 7
 
2.1%
비 7
 
2.1%
소 6
 
1.8%
갈 6
 
1.8%
집 5
 
1.5%
식 4
 
1.2%
Other values (146) 250
76.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
95.4%
Open Punctuation 4
 
1.2%
Close Punctuation 4
 
1.2%
Space Separator 4
 
1.2%
Other Symbol 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 14
 
4.5%
서 12
 
3.9%
대 8
 
2.6%
가 7
 
2.3%
구 7
 
2.3%
비 7
 
2.3%
소 6
 
1.9%
갈 6
 
1.9%
집 5
 
1.6%
식 4
 
1.3%
Other values (141) 235
75.6%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
96.0%
Common 13
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 14
 
4.5%
서 12
 
3.8%
대 8
 
2.6%
가 7
 
2.2%
구 7
 
2.2%
비 7
 
2.2%
소 6
 
1.9%
갈 6
 
1.9%
집 5
 
1.6%
식 4
 
1.3%
Other values (142) 237
75.7%
Common
ValueCountFrequency (%)
( 4
30.8%
) 4
30.8%
4
30.8%
. 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
95.4%
ASCII 13
 
4.0%
None 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 14
 
4.5%
서 12
 
3.9%
대 8
 
2.6%
가 7
 
2.3%
구 7
 
2.3%
비 7
 
2.3%
소 6
 
1.9%
갈 6
 
1.9%
집 5
 
1.6%
식 4
 
1.3%
Other values (141) 235
75.6%
ASCII
ValueCountFrequency (%)
( 4
30.8%
) 4
30.8%
4
30.8%
. 1
 
7.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

영업자성명
Text

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-10T07:35:09.388294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length3
Mean length3.4833333
Min length2

Characters and Unicode

Total characters209
Distinct characters92
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)96.7%

Sample

1st row이서영
2nd row방운자
3rd row이영철
4th row안진구
5th row이강민
ValueCountFrequency (%)
문희철 2
 
3.1%
이재혁 1
 
1.6%
조수현 1
 
1.6%
김수영 1
 
1.6%
박종옥 1
 
1.6%
최장현 1
 
1.6%
최영현 1
 
1.6%
김명호 1
 
1.6%
김승환 1
 
1.6%
이용례 1
 
1.6%
Other values (53) 53
82.8%
2024-01-10T07:35:09.755319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 11
 
5.3%
김 11
 
5.3%
영 9
 
4.3%
희 7
 
3.3%
숙 7
 
3.3%
자 7
 
3.3%
H 6
 
2.9%
철 5
 
2.4%
용 5
 
2.4%
신 4
 
1.9%
Other values (82) 137
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 176
84.2%
Uppercase Letter 27
 
12.9%
Space Separator 4
 
1.9%
Close Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 11
 
6.2%
김 11
 
6.2%
영 9
 
5.1%
희 7
 
4.0%
숙 7
 
4.0%
자 7
 
4.0%
철 5
 
2.8%
용 5
 
2.8%
신 4
 
2.3%
현 4
 
2.3%
Other values (68) 106
60.2%
Uppercase Letter
ValueCountFrequency (%)
H 6
22.2%
N 4
14.8%
I 3
11.1%
G 3
11.1%
C 3
11.1%
U 2
 
7.4%
S 2
 
7.4%
J 1
 
3.7%
Z 1
 
3.7%
E 1
 
3.7%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 176
84.2%
Latin 27
 
12.9%
Common 6
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 11
 
6.2%
김 11
 
6.2%
영 9
 
5.1%
희 7
 
4.0%
숙 7
 
4.0%
자 7
 
4.0%
철 5
 
2.8%
용 5
 
2.8%
신 4
 
2.3%
현 4
 
2.3%
Other values (68) 106
60.2%
Latin
ValueCountFrequency (%)
H 6
22.2%
N 4
14.8%
I 3
11.1%
G 3
11.1%
C 3
11.1%
U 2
 
7.4%
S 2
 
7.4%
J 1
 
3.7%
Z 1
 
3.7%
E 1
 
3.7%
Common
ValueCountFrequency (%)
4
66.7%
) 1
 
16.7%
( 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 176
84.2%
ASCII 33
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 11
 
6.2%
김 11
 
6.2%
영 9
 
5.1%
희 7
 
4.0%
숙 7
 
4.0%
자 7
 
4.0%
철 5
 
2.8%
용 5
 
2.8%
신 4
 
2.3%
현 4
 
2.3%
Other values (68) 106
60.2%
ASCII
ValueCountFrequency (%)
H 6
18.2%
4
12.1%
N 4
12.1%
I 3
9.1%
G 3
9.1%
C 3
9.1%
U 2
 
6.1%
S 2
 
6.1%
) 1
 
3.0%
J 1
 
3.0%
Other values (4) 4
12.1%

소재지(도로명)
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-10T07:35:10.022018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length18
Mean length14.833333
Min length10

Characters and Unicode

Total characters890
Distinct characters88
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

Unique60 ?
Unique (%)100.0%

Sample

1st row부춘3로 27, 1층
2nd row호수공원9로 47, 1층 (예천동)
3rd row명륜1로 80 (읍내동,(2,3층))
4th row율지19길 74 (동문동)
5th row양유정1로 3 (읍내동)
ValueCountFrequency (%)
동문동 17
 
8.8%
1층 13
 
6.7%
읍내동 9
 
4.6%
해미면 5
 
2.6%
대산읍 4
 
2.1%
율지6로 4
 
2.1%
부석면 4
 
2.1%
부춘3로 3
 
1.5%
6 3
 
1.5%
3 3
 
1.5%
Other values (111) 129
66.5%
2024-01-10T07:35:10.390593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134
 
15.1%
1 67
 
7.5%
동 66
 
7.4%
로 53
 
6.0%
) 47
 
5.3%
( 47
 
5.3%
문 26
 
2.9%
, 25
 
2.8%
층 24
 
2.7%
4 23
 
2.6%
Other values (78) 378
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 415
46.6%
Decimal Number 215
24.2%
Space Separator 134
 
15.1%
Close Punctuation 47
 
5.3%
Open Punctuation 47
 
5.3%
Other Punctuation 25
 
2.8%
Dash Punctuation 6
 
0.7%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
15.9%
로 53
 
12.8%
문 26
 
6.3%
층 24
 
5.8%
지 20
 
4.8%
읍 18
 
4.3%
율 17
 
4.1%
내 15
 
3.6%
면 14
 
3.4%
부 11
 
2.7%
Other values (62) 151
36.4%
Decimal Number
ValueCountFrequency (%)
1 67
31.2%
4 23
 
10.7%
2 22
 
10.2%
6 22
 
10.2%
3 19
 
8.8%
7 17
 
7.9%
5 14
 
6.5%
9 12
 
5.6%
8 12
 
5.6%
0 7
 
3.3%
Space Separator
ValueCountFrequency (%)
134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 474
53.3%
Hangul 415
46.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
15.9%
로 53
 
12.8%
문 26
 
6.3%
층 24
 
5.8%
지 20
 
4.8%
읍 18
 
4.3%
율 17
 
4.1%
내 15
 
3.6%
면 14
 
3.4%
부 11
 
2.7%
Other values (62) 151
36.4%
Common
ValueCountFrequency (%)
134
28.3%
1 67
14.1%
) 47
 
9.9%
( 47
 
9.9%
, 25
 
5.3%
4 23
 
4.9%
2 22
 
4.6%
6 22
 
4.6%
3 19
 
4.0%
7 17
 
3.6%
Other values (5) 51
 
10.8%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 475
53.4%
Hangul 415
46.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
134
28.2%
1 67
14.1%
) 47
 
9.9%
( 47
 
9.9%
, 25
 
5.3%
4 23
 
4.8%
2 22
 
4.6%
6 22
 
4.6%
3 19
 
4.0%
7 17
 
3.6%
Other values (6) 52
 
10.9%
Hangul
ValueCountFrequency (%)
동 66
15.9%
로 53
 
12.8%
문 26
 
6.3%
층 24
 
5.8%
지 20
 
4.8%
읍 18
 
4.3%
율 17
 
4.1%
내 15
 
3.6%
면 14
 
3.4%
부 11
 
2.7%
Other values (62) 151
36.4%

전화번호
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-01-10T07:35:10.618956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.033333
Min length12

Characters and Unicode

Total characters722
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

Unique60 ?
Unique (%)100.0%

Sample

1st row041-666-1573
2nd row041-666-7700
3rd row041-668-8123
4th row041-669-4420
5th row041-669-4938
ValueCountFrequency (%)
041-666-1573 1
 
1.7%
041-666-7700 1
 
1.7%
041-665-8787 1
 
1.7%
041-664-1480 1
 
1.7%
041-665-5466 1
 
1.7%
041-668-8006 1
 
1.7%
041-666-5588 1
 
1.7%
041-662-4128 1
 
1.7%
041-662-8699 1
 
1.7%
041-666-9200 1
 
1.7%
Other values (50) 50
83.3%
2024-01-10T07:35:10.971975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 141
19.5%
- 120
16.6%
0 99
13.7%
4 83
11.5%
1 80
11.1%
8 52
 
7.2%
5 35
 
4.8%
9 34
 
4.7%
2 29
 
4.0%
7 25
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 602
83.4%
Dash Punctuation 120
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 141
23.4%
0 99
16.4%
4 83
13.8%
1 80
13.3%
8 52
 
8.6%
5 35
 
5.8%
9 34
 
5.6%
2 29
 
4.8%
7 25
 
4.2%
3 24
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 722
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 141
19.5%
- 120
16.6%
0 99
13.7%
4 83
11.5%
1 80
11.1%
8 52
 
7.2%
5 35
 
4.8%
9 34
 
4.7%
2 29
 
4.0%
7 25
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 722
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 141
19.5%
- 120
16.6%
0 99
13.7%
4 83
11.5%
1 80
11.1%
8 52
 
7.2%
5 35
 
4.8%
9 34
 
4.7%
2 29
 
4.0%
7 25
 
3.5%

Interactions

2024-01-10T07:35:08.157670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:35:11.063519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명영업자성명소재지(도로명)전화번호
연번1.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.000
영업자성명1.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000

Missing values

2024-01-10T07:35:08.266908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:35:08.352313image/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

연번업소명영업자성명소재지(도로명)전화번호
01가마솥밥상이서영부춘3로 27, 1층041-666-1573
12가보방운자호수공원9로 47, 1층 (예천동)041-666-7700
23가야면옥이영철명륜1로 80 (읍내동,(2,3층))041-668-8123
34갈비본가 두툼한숯불갈비안진구율지19길 74 (동문동)041-669-4420
45강미루이강민양유정1로 3 (읍내동)041-669-4938
56거북이 횟집유병일율지6로 45 (동문동,1층)041-668-6116
67고삐김영철쌍연남2로 14 (동문동)041-664-9253
78구도횟집서경자팔봉면 팔봉1로 748041-662-6117
89군산오징어구기호호수공원3로 50, 1층(예천동)041-665-5399
910궁김연수대지제5길 7 (석남동)041-668-0205
연번업소명영업자성명소재지(도로명)전화번호
5051자금성박순옥서령로 82, 1층 (동문동)041-681-9639
5152재래식가든이선자부춘4로 6 (읍내동)041-667-8860
5253창포가든김명화팔봉면 어송4길 4, 1층041-669-8899
5354천수만회타운구본대부석면 천수만로 602041-664-4800
5455큰마을영양굴밥김병식부석면 간월도1길 65041-662-2706
5556태능갈비권용균대산읍 가로림로 56-1041-681-5252
5657현대한우촌오만용율지17로 21 (동문동)041-665-3271
5758황우숯불갈비신영숙해미면 남문5로 16041-688-0599
5859㈜백광소재서산(상)휴게소문희철해미면 서해안고속도로 242041-688-7714
5960㈜백광소재서산(하)휴게소문희철해미면 서해안고속도로 241041-688-8814