Overview

Dataset statistics

Number of variables6
Number of observations105
Missing cells42
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory50.3 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description데이터정비(2023년 안심식당 신규지정으로 안심식당 신규자료 재정비로 업데이트를 위한 변경) - 연번, 업체명, 대표자명, 업소 소재지, 소재지전화번호 등
URLhttps://www.data.go.kr/data/15086189/fileData.do

Alerts

전화번호 has 42 (40.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:03:05.853974
Analysis finished2023-12-12 00:03:06.445372
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct105
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53
Minimum1
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T09:03:06.543967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.2
Q127
median53
Q379
95-th percentile99.8
Maximum105
Range104
Interquartile range (IQR)52

Descriptive statistics

Standard deviation30.454885
Coefficient of variation (CV)0.57462047
Kurtosis-1.2
Mean53
Median Absolute Deviation (MAD)26
Skewness0
Sum5565
Variance927.5
MonotonicityStrictly increasing
2023-12-12T09:03:06.738404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
80 1
 
1.0%
78 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
Other values (95) 95
90.5%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
105 1
1.0%
104 1
1.0%
103 1
1.0%
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%

업체명
Text

Distinct103
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size972.0 B
2023-12-12T09:03:07.008228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.4
Min length2

Characters and Unicode

Total characters567
Distinct characters196
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

Unique101 ?
Unique (%)96.2%

Sample

1st row섬진강식당
2nd row원조재첩국나루터식당
3rd row원조강변할매재첩국식당
4th row하동솔잎한우프라자
5th row큰바다횟집
ValueCountFrequency (%)
홍이네갱조개 2
 
1.7%
날 2
 
1.7%
새부산횟집 2
 
1.7%
김밥 1
 
0.9%
옥화주막 1
 
0.9%
북천식육식당 1
 
0.9%
목화관광식당 1
 
0.9%
섬진강식당 1
 
0.9%
향미가든 1
 
0.9%
장씨네식당 1
 
0.9%
Other values (102) 102
88.7%
2023-12-12T09:03:07.524092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 26
 
4.6%
당 25
 
4.4%
집 23
 
4.1%
횟 17
 
3.0%
하 15
 
2.6%
동 13
 
2.3%
가 10
 
1.8%
성 10
 
1.8%
10
 
1.8%
갈 8
 
1.4%
Other values (186) 410
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 537
94.7%
Space Separator 10
 
1.8%
Lowercase Letter 9
 
1.6%
Decimal Number 4
 
0.7%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%
Other Punctuation 2
 
0.4%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 26
 
4.8%
당 25
 
4.7%
집 23
 
4.3%
횟 17
 
3.2%
하 15
 
2.8%
동 13
 
2.4%
가 10
 
1.9%
성 10
 
1.9%
갈 8
 
1.5%
이 8
 
1.5%
Other values (171) 382
71.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
r 2
22.2%
s 2
22.2%
y 1
11.1%
o 1
11.1%
t 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 1
25.0%
9 1
25.0%
Other Punctuation
ValueCountFrequency (%)
' 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 537
94.7%
Common 20
 
3.5%
Latin 10
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 26
 
4.8%
당 25
 
4.7%
집 23
 
4.3%
횟 17
 
3.2%
하 15
 
2.8%
동 13
 
2.4%
가 10
 
1.9%
성 10
 
1.9%
갈 8
 
1.5%
이 8
 
1.5%
Other values (171) 382
71.1%
Common
ValueCountFrequency (%)
10
50.0%
1 2
 
10.0%
) 2
 
10.0%
( 2
 
10.0%
' 1
 
5.0%
2 1
 
5.0%
9 1
 
5.0%
, 1
 
5.0%
Latin
ValueCountFrequency (%)
e 2
20.0%
r 2
20.0%
s 2
20.0%
L 1
10.0%
y 1
10.0%
o 1
10.0%
t 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 537
94.7%
ASCII 30
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 26
 
4.8%
당 25
 
4.7%
집 23
 
4.3%
횟 17
 
3.2%
하 15
 
2.8%
동 13
 
2.4%
가 10
 
1.9%
성 10
 
1.9%
갈 8
 
1.5%
이 8
 
1.5%
Other values (171) 382
71.1%
ASCII
ValueCountFrequency (%)
10
33.3%
e 2
 
6.7%
r 2
 
6.7%
s 2
 
6.7%
1 2
 
6.7%
) 2
 
6.7%
( 2
 
6.7%
' 1
 
3.3%
2 1
 
3.3%
9 1
 
3.3%
Other values (5) 5
16.7%

대표자명
Text

Distinct101
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size972.0 B
2023-12-12T09:03:07.903970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters315
Distinct characters95
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)92.4%

Sample

1st row김영미
2nd row이상태
3rd row이순자
4th row이병호
5th row신호숙
ValueCountFrequency (%)
이영자 2
 
1.9%
박은주 2
 
1.9%
김종화 2
 
1.9%
이선희 2
 
1.9%
김봉학 1
 
1.0%
장계덕 1
 
1.0%
강은희 1
 
1.0%
이경애 1
 
1.0%
김태임 1
 
1.0%
이경희 1
 
1.0%
Other values (91) 91
86.7%
2023-12-12T09:03:08.484803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 29
 
9.2%
이 17
 
5.4%
정 14
 
4.4%
영 12
 
3.8%
숙 12
 
3.8%
순 10
 
3.2%
자 9
 
2.9%
희 9
 
2.9%
경 8
 
2.5%
미 8
 
2.5%
Other values (85) 187
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 315
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 29
 
9.2%
이 17
 
5.4%
정 14
 
4.4%
영 12
 
3.8%
숙 12
 
3.8%
순 10
 
3.2%
자 9
 
2.9%
희 9
 
2.9%
경 8
 
2.5%
미 8
 
2.5%
Other values (85) 187
59.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 315
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 29
 
9.2%
이 17
 
5.4%
정 14
 
4.4%
영 12
 
3.8%
숙 12
 
3.8%
순 10
 
3.2%
자 9
 
2.9%
희 9
 
2.9%
경 8
 
2.5%
미 8
 
2.5%
Other values (85) 187
59.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 315
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 29
 
9.2%
이 17
 
5.4%
정 14
 
4.4%
영 12
 
3.8%
숙 12
 
3.8%
순 10
 
3.2%
자 9
 
2.9%
희 9
 
2.9%
경 8
 
2.5%
미 8
 
2.5%
Other values (85) 187
59.4%

읍면
Categorical

Distinct12
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size972.0 B
하동읍
40 
화개면
20 
금남면
17 
고전면
5 
옥종면
5 
Other values (7)
18 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row고전면
2nd row고전면
3rd row고전면
4th row고전면
5th row금남면

Common Values

ValueCountFrequency (%)
하동읍 40
38.1%
화개면 20
19.0%
금남면 17
16.2%
고전면 5
 
4.8%
옥종면 5
 
4.8%
진교면 4
 
3.8%
청암면 3
 
2.9%
횡천면 3
 
2.9%
적량면 3
 
2.9%
악양면 2
 
1.9%
Other values (2) 3
 
2.9%

Length

2023-12-12T09:03:08.671747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
하동읍 40
38.1%
화개면 20
19.0%
금남면 17
16.2%
고전면 5
 
4.8%
옥종면 5
 
4.8%
진교면 4
 
3.8%
청암면 3
 
2.9%
횡천면 3
 
2.9%
적량면 3
 
2.9%
악양면 2
 
1.9%
Other values (2) 3
 
2.9%

소재지
Text

Distinct103
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size972.0 B
2023-12-12T09:03:08.951200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length15
Mean length10.980952
Min length7

Characters and Unicode

Total characters1153
Distinct characters100
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

Unique101 ?
Unique (%)96.2%

Sample

1st row고전면재첩길237
2nd row고전면재첩길286
3rd row고전면재첩길286-1
4th row고전면하동읍성로9
5th row금남면노량해안길155
ValueCountFrequency (%)
하동읍 11
 
6.4%
금남면 7
 
4.1%
섬진강대로 7
 
4.1%
경서대로 5
 
2.9%
화개면 4
 
2.3%
1층 3
 
1.8%
노량해안길 3
 
1.8%
옥종면 3
 
1.8%
화개면쌍계로17 2
 
1.2%
21-9 2
 
1.2%
Other values (118) 124
72.5%
2023-12-12T09:03:09.382409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 76
 
6.6%
면 66
 
5.7%
66
 
5.7%
로 57
 
4.9%
동 48
 
4.2%
2 47
 
4.1%
길 45
 
3.9%
하 43
 
3.7%
읍 43
 
3.7%
5 30
 
2.6%
Other values (90) 632
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 742
64.4%
Decimal Number 313
27.1%
Space Separator 66
 
5.7%
Dash Punctuation 25
 
2.2%
Other Punctuation 4
 
0.3%
Uppercase Letter 1
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 66
 
8.9%
로 57
 
7.7%
동 48
 
6.5%
길 45
 
6.1%
하 43
 
5.8%
읍 43
 
5.8%
화 28
 
3.8%
대 27
 
3.6%
개 26
 
3.5%
금 20
 
2.7%
Other values (74) 339
45.7%
Decimal Number
ValueCountFrequency (%)
1 76
24.3%
2 47
15.0%
5 30
 
9.6%
6 27
 
8.6%
4 27
 
8.6%
8 24
 
7.7%
3 23
 
7.3%
7 22
 
7.0%
9 20
 
6.4%
0 17
 
5.4%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 742
64.4%
Common 410
35.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 66
 
8.9%
로 57
 
7.7%
동 48
 
6.5%
길 45
 
6.1%
하 43
 
5.8%
읍 43
 
5.8%
화 28
 
3.8%
대 27
 
3.6%
개 26
 
3.5%
금 20
 
2.7%
Other values (74) 339
45.7%
Common
ValueCountFrequency (%)
1 76
18.5%
66
16.1%
2 47
11.5%
5 30
 
7.3%
6 27
 
6.6%
4 27
 
6.6%
- 25
 
6.1%
8 24
 
5.9%
3 23
 
5.6%
7 22
 
5.4%
Other values (5) 43
10.5%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 742
64.4%
ASCII 411
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 76
18.5%
66
16.1%
2 47
11.4%
5 30
 
7.3%
6 27
 
6.6%
4 27
 
6.6%
- 25
 
6.1%
8 24
 
5.8%
3 23
 
5.6%
7 22
 
5.4%
Other values (6) 44
10.7%
Hangul
ValueCountFrequency (%)
면 66
 
8.9%
로 57
 
7.7%
동 48
 
6.5%
길 45
 
6.1%
하 43
 
5.8%
읍 43
 
5.8%
화 28
 
3.8%
대 27
 
3.6%
개 26
 
3.5%
금 20
 
2.7%
Other values (74) 339
45.7%

전화번호
Text

MISSING 

Distinct62
Distinct (%)98.4%
Missing42
Missing (%)40.0%
Memory size972.0 B
2023-12-12T09:03:09.665980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters756
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

Unique61 ?
Unique (%)96.8%

Sample

1st row055-883-0247
2nd row055-882-1369
3rd row055-884-1515
4th row055-884-2869
5th row055-884-4691
ValueCountFrequency (%)
055-882-4210 2
 
3.2%
055-882-0055 1
 
1.6%
055-882-3457 1
 
1.6%
055-883-9959 1
 
1.6%
055-883-4544 1
 
1.6%
055-883-9944 1
 
1.6%
055-883-8200 1
 
1.6%
055-883-3316 1
 
1.6%
055-883-1672 1
 
1.6%
055-883-8060 1
 
1.6%
Other values (52) 52
82.5%
2023-12-12T09:03:10.119149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 157
20.8%
8 151
20.0%
- 126
16.7%
0 95
12.6%
3 54
 
7.1%
2 48
 
6.3%
4 41
 
5.4%
1 27
 
3.6%
9 25
 
3.3%
6 18
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 630
83.3%
Dash Punctuation 126
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 157
24.9%
8 151
24.0%
0 95
15.1%
3 54
 
8.6%
2 48
 
7.6%
4 41
 
6.5%
1 27
 
4.3%
9 25
 
4.0%
6 18
 
2.9%
7 14
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 157
20.8%
8 151
20.0%
- 126
16.7%
0 95
12.6%
3 54
 
7.1%
2 48
 
6.3%
4 41
 
5.4%
1 27
 
3.6%
9 25
 
3.3%
6 18
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 157
20.8%
8 151
20.0%
- 126
16.7%
0 95
12.6%
3 54
 
7.1%
2 48
 
6.3%
4 41
 
5.4%
1 27
 
3.6%
9 25
 
3.3%
6 18
 
2.4%

Interactions

2023-12-12T09:03:06.153612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:03:10.247314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면전화번호
연번1.0000.7081.000
읍면0.7081.0000.337
전화번호1.0000.3371.000
2023-12-12T09:03:10.347566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면
연번1.0000.388
읍면0.3881.000

Missing values

2023-12-12T09:03:06.262496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:03:06.399353image/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

연번업체명대표자명읍면소재지전화번호
01섬진강식당김영미고전면고전면재첩길237055-883-0247
12원조재첩국나루터식당이상태고전면고전면재첩길286<NA>
23원조강변할매재첩국식당이순자고전면고전면재첩길286-1055-882-1369
34하동솔잎한우프라자이병호고전면고전면하동읍성로9055-884-1515
45큰바다횟집신호숙금남면금남면노량해안길155<NA>
56제일회센타천정숙금남면금남면노량해안길217<NA>
67덕원회센타임성미금남면금남면노량해안길37<NA>
78회성회센타도향순금남면금남면노량해안길145<NA>
89금성숯불갈비이연숙금성면금성면신도길124<NA>
910하동갈매기 회초밥김영희진교면진교면경충로1051<NA>
연번업체명대표자명읍면소재지전화번호
9596미미식당장계숙하동읍하동읍 중앙로 69<NA>
9697미청식당김돌순하동읍하동읍 시장1길 26-35055-884-0303
9798부흥재첩식당김연자하동읍하동읍 경서대로 98055-884-3903
9899하동정 재첩, 참게탕황순옥하동읍하동읍 섬진강대로 2564055-882-8998
99100하옹촌재첩식당황춘성하동읍하동읍 섬진강대로 1877, 하동재첩 특화마을B동 주1동055-883-8261
100101해성식당정현숙하동읍하동읍 섬진강대로 1877055-883-6635
101102홍이네갱조개김종화하동읍하동읍 섬진강대로 1880<NA>
102103하옹김진현하동읍하동읍 섬진강대로 2587055-882-3457
103104욱's 김밥박영화하동읍하동읍 경서대로 130, 1층055-883-8822
104105샤브향(하동점)문초롱하동읍하동읍 경서대로 231, 1층055-882-4949