Overview

Dataset statistics

Number of variables6
Number of observations730
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.1 KiB
Average record size in memory49.2 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description도 내에 자리잡고 있는 모범음식점 현황으로, 시도, 시군, 주메뉴, 업소명, 주소와 같은 항목에 대한 정보들을 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079051

Alerts

시도 has constant value ""Constant
연번 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:58:07.417777
Analysis finished2023-12-10 22:58:08.255423
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct730
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean365.5
Minimum1
Maximum730
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-11T07:58:08.345037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37.45
Q1183.25
median365.5
Q3547.75
95-th percentile693.55
Maximum730
Range729
Interquartile range (IQR)364.5

Descriptive statistics

Standard deviation210.87714
Coefficient of variation (CV)0.57695523
Kurtosis-1.2
Mean365.5
Median Absolute Deviation (MAD)182.5
Skewness0
Sum266815
Variance44469.167
MonotonicityStrictly increasing
2023-12-11T07:58:08.517543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
481 1
 
0.1%
483 1
 
0.1%
484 1
 
0.1%
485 1
 
0.1%
486 1
 
0.1%
487 1
 
0.1%
488 1
 
0.1%
489 1
 
0.1%
490 1
 
0.1%
Other values (720) 720
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
730 1
0.1%
729 1
0.1%
728 1
0.1%
727 1
0.1%
726 1
0.1%
725 1
0.1%
724 1
0.1%
723 1
0.1%
722 1
0.1%
721 1
0.1%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
경상남도
730 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 730
100.0%

Length

2023-12-11T07:58:08.665356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:58:08.752608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 730
100.0%

시군
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
창원시
201 
거제시
54 
사천시
49 
통영시
44 
함안군
41 
Other values (13)
341 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
창원시 201
27.5%
거제시 54
 
7.4%
사천시 49
 
6.7%
통영시 44
 
6.0%
함안군 41
 
5.6%
남해군 40
 
5.5%
거창군 35
 
4.8%
창녕군 33
 
4.5%
밀양시 32
 
4.4%
진주시 30
 
4.1%
Other values (8) 171
23.4%

Length

2023-12-11T07:58:08.848494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
창원시 201
27.5%
거제시 54
 
7.4%
사천시 49
 
6.7%
통영시 44
 
6.0%
함안군 41
 
5.6%
남해군 40
 
5.5%
거창군 35
 
4.8%
창녕군 33
 
4.5%
밀양시 32
 
4.4%
진주시 30
 
4.1%
Other values (8) 171
23.4%
Distinct435
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T07:58:09.071511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length5.8424658
Min length1

Characters and Unicode

Total characters4265
Distinct characters261
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique350 ?
Unique (%)47.9%

Sample

1st row중화요리
2nd row민물회
3rd row석쇠구이, 국밥
4th row활어회
5th row활어회
ValueCountFrequency (%)
생선회 54
 
5.5%
매운탕 26
 
2.7%
돼지갈비 26
 
2.7%
삼겹살 25
 
2.6%
오리불고기 16
 
1.6%
소고기 16
 
1.6%
삼계탕 16
 
1.6%
갈비 14
 
1.4%
갈비탕 12
 
1.2%
추어탕 11
 
1.1%
Other values (399) 761
77.9%
2023-12-11T07:58:09.442760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 315
 
7.4%
247
 
5.8%
183
 
4.3%
134
 
3.1%
131
 
3.1%
119
 
2.8%
113
 
2.6%
112
 
2.6%
108
 
2.5%
105
 
2.5%
Other values (251) 2698
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3686
86.4%
Other Punctuation 323
 
7.6%
Space Separator 247
 
5.8%
Open Punctuation 5
 
0.1%
Close Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
183
 
5.0%
134
 
3.6%
131
 
3.6%
119
 
3.2%
113
 
3.1%
112
 
3.0%
108
 
2.9%
105
 
2.8%
91
 
2.5%
90
 
2.4%
Other values (246) 2500
67.8%
Other Punctuation
ValueCountFrequency (%)
, 315
97.5%
. 8
 
2.5%
Space Separator
ValueCountFrequency (%)
247
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3686
86.4%
Common 579
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
183
 
5.0%
134
 
3.6%
131
 
3.6%
119
 
3.2%
113
 
3.1%
112
 
3.0%
108
 
2.9%
105
 
2.8%
91
 
2.5%
90
 
2.4%
Other values (246) 2500
67.8%
Common
ValueCountFrequency (%)
, 315
54.4%
247
42.7%
. 8
 
1.4%
( 5
 
0.9%
) 4
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3686
86.4%
ASCII 579
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 315
54.4%
247
42.7%
. 8
 
1.4%
( 5
 
0.9%
) 4
 
0.7%
Hangul
ValueCountFrequency (%)
183
 
5.0%
134
 
3.6%
131
 
3.6%
119
 
3.2%
113
 
3.1%
112
 
3.0%
108
 
2.9%
105
 
2.8%
91
 
2.5%
90
 
2.4%
Other values (246) 2500
67.8%
Distinct714
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T07:58:09.714378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length5.4671233
Min length1

Characters and Unicode

Total characters3991
Distinct characters431
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique700 ?
Unique (%)95.9%

Sample

1st row국일성
2nd row해훈식당
3rd row임진각식당
4th row자갈치횟집
5th row충무활어횟집
ValueCountFrequency (%)
푸주옥 3
 
0.4%
남해 3
 
0.4%
양평해장국 3
 
0.4%
대가한우촌 2
 
0.3%
클럽하우스 2
 
0.3%
사랑채 2
 
0.3%
싱싱게장 2
 
0.3%
진고려삼계탕 2
 
0.3%
대복식당 2
 
0.3%
산마루 2
 
0.3%
Other values (762) 773
97.1%
2023-12-11T07:58:10.106423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
2.9%
95
 
2.4%
91
 
2.3%
78
 
2.0%
70
 
1.8%
70
 
1.8%
60
 
1.5%
60
 
1.5%
59
 
1.5%
58
 
1.5%
Other values (421) 3234
81.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3852
96.5%
Space Separator 70
 
1.8%
Decimal Number 17
 
0.4%
Open Punctuation 16
 
0.4%
Close Punctuation 16
 
0.4%
Other Punctuation 12
 
0.3%
Uppercase Letter 6
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
116
 
3.0%
95
 
2.5%
91
 
2.4%
78
 
2.0%
70
 
1.8%
60
 
1.6%
60
 
1.6%
59
 
1.5%
58
 
1.5%
56
 
1.5%
Other values (399) 3109
80.7%
Decimal Number
ValueCountFrequency (%)
2 5
29.4%
3 3
17.6%
0 2
 
11.8%
4 2
 
11.8%
1 2
 
11.8%
6 1
 
5.9%
9 1
 
5.9%
5 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
· 4
33.3%
& 4
33.3%
. 2
16.7%
/ 1
 
8.3%
, 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
G 1
16.7%
L 1
16.7%
O 1
16.7%
Y 1
16.7%
Space Separator
ValueCountFrequency (%)
70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3852
96.5%
Common 133
 
3.3%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
116
 
3.0%
95
 
2.5%
91
 
2.4%
78
 
2.0%
70
 
1.8%
60
 
1.6%
60
 
1.6%
59
 
1.5%
58
 
1.5%
56
 
1.5%
Other values (399) 3109
80.7%
Common
ValueCountFrequency (%)
70
52.6%
( 16
 
12.0%
) 16
 
12.0%
2 5
 
3.8%
· 4
 
3.0%
& 4
 
3.0%
3 3
 
2.3%
- 2
 
1.5%
. 2
 
1.5%
0 2
 
1.5%
Other values (7) 9
 
6.8%
Latin
ValueCountFrequency (%)
C 2
33.3%
G 1
16.7%
L 1
16.7%
O 1
16.7%
Y 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3852
96.5%
ASCII 135
 
3.4%
None 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
116
 
3.0%
95
 
2.5%
91
 
2.4%
78
 
2.0%
70
 
1.8%
60
 
1.6%
60
 
1.6%
59
 
1.5%
58
 
1.5%
56
 
1.5%
Other values (399) 3109
80.7%
ASCII
ValueCountFrequency (%)
70
51.9%
( 16
 
11.9%
) 16
 
11.9%
2 5
 
3.7%
& 4
 
3.0%
3 3
 
2.2%
- 2
 
1.5%
. 2
 
1.5%
C 2
 
1.5%
0 2
 
1.5%
Other values (11) 13
 
9.6%
None
ValueCountFrequency (%)
· 4
100.0%

주소
Text

Distinct727
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T07:58:10.368506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length49
Mean length21.469863
Min length11

Characters and Unicode

Total characters15673
Distinct characters304
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique724 ?
Unique (%)99.2%

Sample

1st row창원시 의창구 의안로31번길 26, 1,2층 (중동)
2nd row창원시 의창구 동읍 주남로 105
3rd row창원시 의창구 팔용로 515, 1, 2층 (팔용동, 외 1필지)
4th row창원시 의창구 원이대로285번길 19 (봉곡동,1층 101호)
5th row창원시 의창구 원이대로285번길 17 (봉곡동,1층 3호)
ValueCountFrequency (%)
창원시 201
 
6.0%
1층 63
 
1.9%
거제시 54
 
1.6%
사천시 49
 
1.5%
의창구 49
 
1.5%
성산구 49
 
1.5%
통영시 42
 
1.3%
함안군 41
 
1.2%
남해군 40
 
1.2%
마산합포구 40
 
1.2%
Other values (1361) 2731
81.3%
2023-12-11T07:58:10.745272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2666
 
17.0%
1 756
 
4.8%
505
 
3.2%
496
 
3.2%
2 475
 
3.0%
468
 
3.0%
( 391
 
2.5%
) 391
 
2.5%
380
 
2.4%
363
 
2.3%
Other values (294) 8782
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8666
55.3%
Decimal Number 3034
 
19.4%
Space Separator 2666
 
17.0%
Open Punctuation 391
 
2.5%
Close Punctuation 391
 
2.5%
Other Punctuation 294
 
1.9%
Dash Punctuation 217
 
1.4%
Uppercase Letter 7
 
< 0.1%
Math Symbol 5
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
505
 
5.8%
496
 
5.7%
468
 
5.4%
380
 
4.4%
363
 
4.2%
287
 
3.3%
272
 
3.1%
222
 
2.6%
219
 
2.5%
210
 
2.4%
Other values (270) 5244
60.5%
Decimal Number
ValueCountFrequency (%)
1 756
24.9%
2 475
15.7%
3 344
11.3%
5 251
 
8.3%
0 222
 
7.3%
4 220
 
7.3%
8 213
 
7.0%
7 197
 
6.5%
6 195
 
6.4%
9 161
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 278
94.6%
. 11
 
3.7%
· 4
 
1.4%
/ 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
A 3
42.9%
G 2
28.6%
H 1
 
14.3%
B 1
 
14.3%
Space Separator
ValueCountFrequency (%)
2666
100.0%
Open Punctuation
ValueCountFrequency (%)
( 391
100.0%
Close Punctuation
ValueCountFrequency (%)
) 391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 217
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8666
55.3%
Common 6998
44.7%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
505
 
5.8%
496
 
5.7%
468
 
5.4%
380
 
4.4%
363
 
4.2%
287
 
3.3%
272
 
3.1%
222
 
2.6%
219
 
2.5%
210
 
2.4%
Other values (270) 5244
60.5%
Common
ValueCountFrequency (%)
2666
38.1%
1 756
 
10.8%
2 475
 
6.8%
( 391
 
5.6%
) 391
 
5.6%
3 344
 
4.9%
, 278
 
4.0%
5 251
 
3.6%
0 222
 
3.2%
4 220
 
3.1%
Other values (9) 1004
 
14.3%
Latin
ValueCountFrequency (%)
A 3
33.3%
l 2
22.2%
G 2
22.2%
H 1
 
11.1%
B 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8666
55.3%
ASCII 7003
44.7%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2666
38.1%
1 756
 
10.8%
2 475
 
6.8%
( 391
 
5.6%
) 391
 
5.6%
3 344
 
4.9%
, 278
 
4.0%
5 251
 
3.6%
0 222
 
3.2%
4 220
 
3.1%
Other values (13) 1009
 
14.4%
Hangul
ValueCountFrequency (%)
505
 
5.8%
496
 
5.7%
468
 
5.4%
380
 
4.4%
363
 
4.2%
287
 
3.3%
272
 
3.1%
222
 
2.6%
219
 
2.5%
210
 
2.4%
Other values (270) 5244
60.5%
None
ValueCountFrequency (%)
· 4
100.0%

Interactions

2023-12-11T07:58:07.949544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:58:10.837052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군
연번1.0000.956
시군0.9561.000
2023-12-11T07:58:10.908965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군
연번1.0000.794
시군0.7941.000

Missing values

2023-12-11T07:58:08.104176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:58:08.208021image/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

연번시도시군주메뉴업소명주소
01경상남도창원시중화요리국일성창원시 의창구 의안로31번길 26, 1,2층 (중동)
12경상남도창원시민물회해훈식당창원시 의창구 동읍 주남로 105
23경상남도창원시석쇠구이, 국밥임진각식당창원시 의창구 팔용로 515, 1, 2층 (팔용동, 외 1필지)
34경상남도창원시활어회자갈치횟집창원시 의창구 원이대로285번길 19 (봉곡동,1층 101호)
45경상남도창원시활어회충무활어횟집창원시 의창구 원이대로285번길 17 (봉곡동,1층 3호)
56경상남도창원시갈비류봉강그린가든창원시 의창구 동읍 동읍로 1145
67경상남도창원시갈비살은행식당창원시 의창구 창이대로113번길 12 (명서동)
78경상남도창원시메기매운탕생초메기탕창원시 의창구 사화로10번길 4 (팔용동,1층)
89경상남도창원시갈비생포갈비창원시 의창구 원이대로279번길 18 (봉곡동)
910경상남도창원시설렁탕우리 곰내랑창원시 의창구 창이대로107번길 7 (명서동,세원빌딩 1층)
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720721경상남도합천군산채비빔밥,해물전골금호관합천군 가야면 가야산로 1183
721722경상남도합천군한식,추어탕,된장찌개청솔음식마을합천군 청덕면 동부로 2488-6
722723경상남도합천군쇠고기대식한우명가합천군 용주면 합천호수로 873
723724경상남도합천군한우요리대가식당1호점합천군 삼가면 일부3길 8
724725경상남도합천군오리요리합천민물숯불장어합천군 합천읍 남정길 49
725726경상남도합천군메기매운탕약천메기탕합천군 합천읍 강변로 35
726727경상남도합천군돼지갈비찜합천명품돼지합천군 합천읍 남정길 82
727728경상남도합천군북어요리북어마을합천군 대병면 회양관광단지길 34
728729경상남도합천군한우모듬삼가명품한우합천군 삼가면 서부로 39
729730경상남도합천군돼지국밥수미정식당합천군 가야면 가조가야로 2880