Overview

Dataset statistics

Number of variables5
Number of observations98
Missing cells7
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory42.3 B

Variable types

Numeric1
Text4

Dataset

Description경상남도 밀양시의 식품제조가공업 현황에 대해 개방합니다.
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15022022

Alerts

전화번호 has 7 (7.1%) missing valuesMissing
연번 has unique valuesUnique
업체명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:35:25.703289
Analysis finished2023-12-11 00:35:26.773834
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.5
Minimum1
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1014.0 B
2023-12-11T09:35:26.850844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.85
Q125.25
median49.5
Q373.75
95-th percentile93.15
Maximum98
Range97
Interquartile range (IQR)48.5

Descriptive statistics

Standard deviation28.434134
Coefficient of variation (CV)0.57442696
Kurtosis-1.2
Mean49.5
Median Absolute Deviation (MAD)24.5
Skewness0
Sum4851
Variance808.5
MonotonicityStrictly increasing
2023-12-11T09:35:26.996638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
75 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
Other values (88) 88
89.8%
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 (%)
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%

업체명
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-11T09:35:27.299566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length7.0816327
Min length2

Characters and Unicode

Total characters694
Distinct characters195
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st row대동
2nd row수산국수
3rd row황금제과
4th row은혜식품(주)
5th row한동식품
ValueCountFrequency (%)
농업회사법인 8
 
6.8%
주식회사 2
 
1.7%
영농조합법인 2
 
1.7%
삼미르 1
 
0.8%
천연식초 1
 
0.8%
감익는마을 1
 
0.8%
가야술빵 1
 
0.8%
예촌식품 1
 
0.8%
혜민농산(주 1
 
0.8%
밀양꾸지뽕 1
 
0.8%
Other values (99) 99
83.9%
2023-12-11T09:35:27.688926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 33
 
4.8%
식 27
 
3.9%
주 27
 
3.9%
) 26
 
3.7%
( 26
 
3.7%
품 22
 
3.2%
20
 
2.9%
사 19
 
2.7%
인 19
 
2.7%
법 17
 
2.4%
Other values (185) 458
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 611
88.0%
Close Punctuation 26
 
3.7%
Open Punctuation 26
 
3.7%
Space Separator 20
 
2.9%
Lowercase Letter 6
 
0.9%
Uppercase Letter 4
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 33
 
5.4%
식 27
 
4.4%
주 27
 
4.4%
품 22
 
3.6%
사 19
 
3.1%
인 19
 
3.1%
법 17
 
2.8%
회 16
 
2.6%
업 14
 
2.3%
양 13
 
2.1%
Other values (172) 404
66.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
33.3%
g 1
16.7%
i 1
16.7%
n 1
16.7%
d 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
25.0%
M 1
25.0%
F 1
25.0%
S 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 611
88.0%
Common 73
 
10.5%
Latin 10
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 33
 
5.4%
식 27
 
4.4%
주 27
 
4.4%
품 22
 
3.6%
사 19
 
3.1%
인 19
 
3.1%
법 17
 
2.8%
회 16
 
2.6%
업 14
 
2.3%
양 13
 
2.1%
Other values (172) 404
66.1%
Latin
ValueCountFrequency (%)
o 2
20.0%
g 1
10.0%
K 1
10.0%
i 1
10.0%
n 1
10.0%
M 1
10.0%
d 1
10.0%
F 1
10.0%
S 1
10.0%
Common
ValueCountFrequency (%)
) 26
35.6%
( 26
35.6%
20
27.4%
& 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 611
88.0%
ASCII 83
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 33
 
5.4%
식 27
 
4.4%
주 27
 
4.4%
품 22
 
3.6%
사 19
 
3.1%
인 19
 
3.1%
법 17
 
2.8%
회 16
 
2.6%
업 14
 
2.3%
양 13
 
2.1%
Other values (172) 404
66.1%
ASCII
ValueCountFrequency (%)
) 26
31.3%
( 26
31.3%
20
24.1%
o 2
 
2.4%
g 1
 
1.2%
K 1
 
1.2%
i 1
 
1.2%
n 1
 
1.2%
M 1
 
1.2%
d 1
 
1.2%
Other values (3) 3
 
3.6%

대표자
Text

UNIQUE 

Distinct98
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-11T09:35:27.998310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0816327
Min length3

Characters and Unicode

Total characters302
Distinct characters105
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st row석경숙
2nd row최종문
3rd row정정두
4th row조혜경
5th row정성화
ValueCountFrequency (%)
석경숙 1
 
1.0%
손재환 1
 
1.0%
조숙재 1
 
1.0%
박재연 1
 
1.0%
조용균 1
 
1.0%
김종명 1
 
1.0%
김병순 1
 
1.0%
김정수 1
 
1.0%
김보영 1
 
1.0%
장준기 1
 
1.0%
Other values (90) 90
90.0%
2023-12-11T09:35:28.527396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 17
 
5.6%
정 14
 
4.6%
이 14
 
4.6%
수 12
 
4.0%
최 8
 
2.6%
박 7
 
2.3%
용 7
 
2.3%
선 7
 
2.3%
성 6
 
2.0%
영 6
 
2.0%
Other values (95) 204
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 298
98.7%
Space Separator 2
 
0.7%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 17
 
5.7%
정 14
 
4.7%
이 14
 
4.7%
수 12
 
4.0%
최 8
 
2.7%
박 7
 
2.3%
용 7
 
2.3%
선 7
 
2.3%
성 6
 
2.0%
영 6
 
2.0%
Other values (92) 200
67.1%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 298
98.7%
Common 4
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 17
 
5.7%
정 14
 
4.7%
이 14
 
4.7%
수 12
 
4.0%
최 8
 
2.7%
박 7
 
2.3%
용 7
 
2.3%
선 7
 
2.3%
성 6
 
2.0%
영 6
 
2.0%
Other values (92) 200
67.1%
Common
ValueCountFrequency (%)
2
50.0%
2 1
25.0%
1 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 298
98.7%
ASCII 4
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 17
 
5.7%
정 14
 
4.7%
이 14
 
4.7%
수 12
 
4.0%
최 8
 
2.7%
박 7
 
2.3%
용 7
 
2.3%
선 7
 
2.3%
성 6
 
2.0%
영 6
 
2.0%
Other values (92) 200
67.1%
ASCII
ValueCountFrequency (%)
2
50.0%
2 1
25.0%
1 1
25.0%

소재지(도로명)
Text

Distinct95
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size916.0 B
2023-12-11T09:35:28.870523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length21.755102
Min length18

Characters and Unicode

Total characters2132
Distinct characters128
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

Unique92 ?
Unique (%)93.9%

Sample

1st row경상남도 밀양시 삼문2길 21-4 (삼문동)
2nd row경상남도 밀양시 하남읍 수산중앙로 19-1
3rd row경상남도 밀양시 산외면 남기동길 181
4th row경상남도 밀양시 상남면 예평로 15
5th row경상남도 밀양시 상남면 상남로 1088-10
ValueCountFrequency (%)
경상남도 98
19.8%
밀양시 98
19.8%
상남면 16
 
3.2%
하남읍 12
 
2.4%
초동면 10
 
2.0%
단장면 9
 
1.8%
산내면 9
 
1.8%
산외면 8
 
1.6%
부북면 7
 
1.4%
삼랑진읍 6
 
1.2%
Other values (182) 221
44.7%
2023-12-11T09:35:29.376247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
396
18.6%
남 133
 
6.2%
상 123
 
5.8%
양 104
 
4.9%
도 102
 
4.8%
밀 102
 
4.8%
시 99
 
4.6%
경 98
 
4.6%
1 88
 
4.1%
면 69
 
3.2%
Other values (118) 818
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1335
62.6%
Space Separator 396
 
18.6%
Decimal Number 331
 
15.5%
Dash Punctuation 41
 
1.9%
Close Punctuation 13
 
0.6%
Open Punctuation 13
 
0.6%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 133
 
10.0%
상 123
 
9.2%
양 104
 
7.8%
도 102
 
7.6%
밀 102
 
7.6%
시 99
 
7.4%
경 98
 
7.3%
면 69
 
5.2%
길 52
 
3.9%
로 47
 
3.5%
Other values (103) 406
30.4%
Decimal Number
ValueCountFrequency (%)
1 88
26.6%
2 47
14.2%
3 39
11.8%
5 35
 
10.6%
7 25
 
7.6%
9 25
 
7.6%
8 22
 
6.6%
4 20
 
6.0%
0 16
 
4.8%
6 14
 
4.2%
Space Separator
ValueCountFrequency (%)
396
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1335
62.6%
Common 797
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 133
 
10.0%
상 123
 
9.2%
양 104
 
7.8%
도 102
 
7.6%
밀 102
 
7.6%
시 99
 
7.4%
경 98
 
7.3%
면 69
 
5.2%
길 52
 
3.9%
로 47
 
3.5%
Other values (103) 406
30.4%
Common
ValueCountFrequency (%)
396
49.7%
1 88
 
11.0%
2 47
 
5.9%
- 41
 
5.1%
3 39
 
4.9%
5 35
 
4.4%
7 25
 
3.1%
9 25
 
3.1%
8 22
 
2.8%
4 20
 
2.5%
Other values (5) 59
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1335
62.6%
ASCII 797
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
396
49.7%
1 88
 
11.0%
2 47
 
5.9%
- 41
 
5.1%
3 39
 
4.9%
5 35
 
4.4%
7 25
 
3.1%
9 25
 
3.1%
8 22
 
2.8%
4 20
 
2.5%
Other values (5) 59
 
7.4%
Hangul
ValueCountFrequency (%)
남 133
 
10.0%
상 123
 
9.2%
양 104
 
7.8%
도 102
 
7.6%
밀 102
 
7.6%
시 99
 
7.4%
경 98
 
7.3%
면 69
 
5.2%
길 52
 
3.9%
로 47
 
3.5%
Other values (103) 406
30.4%

전화번호
Text

MISSING 

Distinct89
Distinct (%)97.8%
Missing7
Missing (%)7.1%
Memory size916.0 B
2023-12-11T09:35:29.656353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010989
Min length12

Characters and Unicode

Total characters1093
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

Unique87 ?
Unique (%)95.6%

Sample

1st row055-354-2526
2nd row055-391-3400
3rd row055-355-2054
4th row055-354-3118
5th row055-354-2803
ValueCountFrequency (%)
055-391-6054 2
 
2.2%
055-354-2526 2
 
2.2%
055-351-4558 1
 
1.1%
055-391-5601 1
 
1.1%
055-352-6799 1
 
1.1%
055-355-6233 1
 
1.1%
055-352-1599 1
 
1.1%
055-355-8806 1
 
1.1%
055-355-4811 1
 
1.1%
055-356-2646 1
 
1.1%
Other values (79) 79
86.8%
2023-12-11T09:35:30.063516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 295
27.0%
- 182
16.7%
0 134
12.3%
3 127
11.6%
1 85
 
7.8%
2 63
 
5.8%
4 54
 
4.9%
6 53
 
4.8%
9 50
 
4.6%
7 25
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 911
83.3%
Dash Punctuation 182
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 295
32.4%
0 134
14.7%
3 127
13.9%
1 85
 
9.3%
2 63
 
6.9%
4 54
 
5.9%
6 53
 
5.8%
9 50
 
5.5%
7 25
 
2.7%
8 25
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1093
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 295
27.0%
- 182
16.7%
0 134
12.3%
3 127
11.6%
1 85
 
7.8%
2 63
 
5.8%
4 54
 
4.9%
6 53
 
4.8%
9 50
 
4.6%
7 25
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1093
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 295
27.0%
- 182
16.7%
0 134
12.3%
3 127
11.6%
1 85
 
7.8%
2 63
 
5.8%
4 54
 
4.9%
6 53
 
4.8%
9 50
 
4.6%
7 25
 
2.3%

Interactions

2023-12-11T09:35:26.518014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:35:30.166593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명대표자소재지(도로명)전화번호
연번1.0001.0001.0000.9430.862
업체명1.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.000
소재지(도로명)0.9431.0001.0001.0001.000
전화번호0.8621.0001.0001.0001.000

Missing values

2023-12-11T09:35:26.626223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:35:26.734875image/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

연번업체명대표자소재지(도로명)전화번호
01대동석경숙경상남도 밀양시 삼문2길 21-4 (삼문동)055-354-2526
12수산국수최종문경상남도 밀양시 하남읍 수산중앙로 19-1055-391-3400
23황금제과정정두경상남도 밀양시 산외면 남기동길 181055-355-2054
34은혜식품(주)조혜경경상남도 밀양시 상남면 예평로 15055-354-3118
45한동식품정성화경상남도 밀양시 상남면 상남로 1088-10055-354-2803
56삼락식품박희숙경상남도 밀양시 초동면 검암1길 15-1055-391-6666
67향진식품서상윤경상남도 밀양시 하남읍 대평2안길 23055-391-5800
78삼랑진농협농산물가공공장정대환경상남도 밀양시 삼랑진읍 천태로 373-21055-353-3994
89산동농협대추가공공장도성태경상남도 밀양시 단장면 표충로 89-62055-353-5367
910새한매실농원김정태경상남도 밀양시 상동면 상동로 254-13055-352-2738
연번업체명대표자소재지(도로명)전화번호
8889King콩푸드조병기경상남도 밀양시 상남면 고노실중앙길 37<NA>
8990새미음식문화예술촌김미라경상남도 밀양시 상동면 상동로 576055-353-3599
9091얼음골농산최석환경상남도 밀양시 상남면 조음로 251-78055-391-6054
9192햇빛식품박근아경상남도 밀양시 산내면 인곡안길 11-18055-352-3905
9293찌아찌아하우스권영찬경상남도 밀양시 단장면 단장로 536055-356-1171
9394미락에프엔에스이명자경상남도 밀양시 삼랑진읍 사기점길 11-2055-351-4585
9495토마토닥터박선화경상남도 밀양시 초동면 초동로 159055-391-4306
9596(주)송림에프앤비장해영경상남도 밀양시 무안면 판정로 134055-351-1548
9697농업회사법인 레드애플팜(주)조용윤경상남도 밀양시 산내면 하양지길 25-40055-351-4558
9798핼시아로니아최의영경상남도 밀양시 수월3길 18 (삼문동)055-355-4952