Overview

Dataset statistics

Number of variables6
Number of observations62
Missing cells10
Missing cells (%)2.7%
Duplicate rows1
Duplicate rows (%)1.6%
Total size in memory3.1 KiB
Average record size in memory51.1 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description전라남도 시군에 위치한 남도미향 참여업체 현황 (업체명, 소재지, 인증품목 등)에 관한 데이터를 조회하실 수 있습니다.
Author전라남도
URLhttps://www.data.go.kr/data/3036127/fileData.do

Alerts

Dataset has 1 (1.6%) duplicate rowsDuplicates
연번 is highly overall correlated with 시군High correlation
시군 is highly overall correlated with 연번High correlation
연번 has 2 (3.2%) missing valuesMissing
업체명 has 2 (3.2%) missing valuesMissing
대표자 has 2 (3.2%) missing valuesMissing
소재지 has 2 (3.2%) missing valuesMissing
인증품목 has 2 (3.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 03:23:02.801541
Analysis finished2023-12-12 03:23:04.321074
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct60
Distinct (%)100.0%
Missing2
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size690.0 B
2023-12-12T12:23:04.428320image/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
2023-12-12T12:23:04.622491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32 1
 
1.6%
34 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (50) 50
80.6%
(Missing) 2
 
3.2%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%
52 1
1.6%
51 1
1.6%

시군
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size628.0 B
해남
8 
순천
6 
함평
5 
고흥
4 
장성
4 
Other values (15)
35 

Length

Max length4
Median length2
Mean length2.0645161
Min length2

Unique

Unique3 ?
Unique (%)4.8%

Sample

1st row목포
2nd row여수
3rd row여수
4th row순천
5th row순천

Common Values

ValueCountFrequency (%)
해남 8
12.9%
순천 6
 
9.7%
함평 5
 
8.1%
고흥 4
 
6.5%
장성 4
 
6.5%
영광 4
 
6.5%
구례 3
 
4.8%
무안 3
 
4.8%
보성 3
 
4.8%
곡성 3
 
4.8%
Other values (10) 19
30.6%

Length

2023-12-12T12:23:04.799054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
해남 8
12.9%
순천 6
 
9.7%
함평 5
 
8.1%
고흥 4
 
6.5%
장성 4
 
6.5%
영광 4
 
6.5%
곡성 3
 
4.8%
장흥 3
 
4.8%
나주 3
 
4.8%
보성 3
 
4.8%
Other values (10) 19
30.6%

업체명
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing2
Missing (%)3.2%
Memory size628.0 B
2023-12-12T12:23:05.136596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13.5
Mean length9.9666667
Min length4

Characters and Unicode

Total characters598
Distinct characters160
Distinct categories5 ?
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 row제이농수산
2nd row강순의명가
3rd row돌산갓영농조합법인
4th row동부생약영농조합법인
5th row순천고들빼기영농조합법인
ValueCountFrequency (%)
농업회사법인 9
 
11.4%
유한회사 2
 
2.5%
어업회사법인 2
 
2.5%
해밀영농조합법인 1
 
1.3%
힐링영농조합법인 1
 
1.3%
맛나푸드㈜ 1
 
1.3%
하늘과땅㈜ 1
 
1.3%
영흥농산영농조합법인 1
 
1.3%
팜스뱅크 1
 
1.3%
명랑주식회사 1
 
1.3%
Other values (59) 59
74.7%
2023-12-12T12:23:05.637368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 44
 
7.4%
인 39
 
6.5%
법 39
 
6.5%
사 30
 
5.0%
회 27
 
4.5%
21
 
3.5%
업 21
 
3.5%
영 20
 
3.3%
조 19
 
3.2%
합 19
 
3.2%
Other values (150) 319
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 553
92.5%
Space Separator 21
 
3.5%
Other Symbol 14
 
2.3%
Close Punctuation 5
 
0.8%
Open Punctuation 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 44
 
8.0%
인 39
 
7.1%
법 39
 
7.1%
사 30
 
5.4%
회 27
 
4.9%
업 21
 
3.8%
영 20
 
3.6%
조 19
 
3.4%
합 19
 
3.4%
식 13
 
2.4%
Other values (146) 282
51.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 567
94.8%
Common 31
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 44
 
7.8%
인 39
 
6.9%
법 39
 
6.9%
사 30
 
5.3%
회 27
 
4.8%
업 21
 
3.7%
영 20
 
3.5%
조 19
 
3.4%
합 19
 
3.4%
㈜ 14
 
2.5%
Other values (147) 295
52.0%
Common
ValueCountFrequency (%)
21
67.7%
) 5
 
16.1%
( 5
 
16.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 553
92.5%
ASCII 31
 
5.2%
None 14
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 44
 
8.0%
인 39
 
7.1%
법 39
 
7.1%
사 30
 
5.4%
회 27
 
4.9%
업 21
 
3.8%
영 20
 
3.6%
조 19
 
3.4%
합 19
 
3.4%
식 13
 
2.4%
Other values (146) 282
51.0%
ASCII
ValueCountFrequency (%)
21
67.7%
) 5
 
16.1%
( 5
 
16.1%
None
ValueCountFrequency (%)
㈜ 14
100.0%

대표자
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing2
Missing (%)3.2%
Memory size628.0 B
2023-12-12T12:23:06.017210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.1
Min length2

Characters and Unicode

Total characters186
Distinct characters84
Distinct categories4 ?
Distinct scripts2 ?
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 row송준호 외1
2nd row이점희
3rd row조양효
4th row홍재희
5th row유성진
ValueCountFrequency (%)
이점희 1
 
1.6%
윤승남 1
 
1.6%
이웅 1
 
1.6%
박준환 1
 
1.6%
김원청 1
 
1.6%
박기홍 1
 
1.6%
김도연 1
 
1.6%
박성관 1
 
1.6%
이세운 1
 
1.6%
김성규 1
 
1.6%
Other values (51) 51
83.6%
2023-12-12T12:23:06.527389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 12
 
6.5%
이 9
 
4.8%
희 8
 
4.3%
정 6
 
3.2%
경 5
 
2.7%
임 5
 
2.7%
홍 4
 
2.2%
박 4
 
2.2%
현 4
 
2.2%
최 4
 
2.2%
Other values (74) 125
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 183
98.4%
Other Punctuation 1
 
0.5%
Space Separator 1
 
0.5%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 12
 
6.6%
이 9
 
4.9%
희 8
 
4.4%
정 6
 
3.3%
경 5
 
2.7%
임 5
 
2.7%
홍 4
 
2.2%
박 4
 
2.2%
현 4
 
2.2%
최 4
 
2.2%
Other values (71) 122
66.7%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 183
98.4%
Common 3
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 12
 
6.6%
이 9
 
4.9%
희 8
 
4.4%
정 6
 
3.3%
경 5
 
2.7%
임 5
 
2.7%
홍 4
 
2.2%
박 4
 
2.2%
현 4
 
2.2%
최 4
 
2.2%
Other values (71) 122
66.7%
Common
ValueCountFrequency (%)
, 1
33.3%
1
33.3%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 183
98.4%
ASCII 3
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 12
 
6.6%
이 9
 
4.9%
희 8
 
4.4%
정 6
 
3.3%
경 5
 
2.7%
임 5
 
2.7%
홍 4
 
2.2%
박 4
 
2.2%
현 4
 
2.2%
최 4
 
2.2%
Other values (71) 122
66.7%
ASCII
ValueCountFrequency (%)
, 1
33.3%
1
33.3%
1 1
33.3%

소재지
Text

MISSING 

Distinct60
Distinct (%)100.0%
Missing2
Missing (%)3.2%
Memory size628.0 B
2023-12-12T12:23:06.962997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19.5
Mean length16.333333
Min length10

Characters and Unicode

Total characters980
Distinct characters142
Distinct categories6 ?
Distinct scripts2 ?
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 row목포시영산로849-6
2nd row여수시 화양로 1615-5
3rd row여수시 돌산읍 두문포길 6
4th row순천시 해룡면 여순로 1679
5th row순천시 별량면 개령1길 23
ValueCountFrequency (%)
해남군 8
 
3.4%
순천시 6
 
2.5%
함평군 5
 
2.1%
영광군 4
 
1.7%
장성군 4
 
1.7%
고흥군 4
 
1.7%
보성군 3
 
1.3%
곡성군 3
 
1.3%
구례군 3
 
1.3%
나주시 3
 
1.3%
Other values (171) 195
81.9%
2023-12-12T12:23:07.491179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
18.2%
1 51
 
5.2%
군 51
 
5.2%
면 42
 
4.3%
길 41
 
4.2%
- 25
 
2.6%
4 22
 
2.2%
2 22
 
2.2%
로 21
 
2.1%
0 18
 
1.8%
Other values (132) 509
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 578
59.0%
Decimal Number 197
 
20.1%
Space Separator 178
 
18.2%
Dash Punctuation 25
 
2.6%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 51
 
8.8%
면 42
 
7.3%
길 41
 
7.1%
로 21
 
3.6%
성 18
 
3.1%
산 17
 
2.9%
읍 15
 
2.6%
장 15
 
2.6%
흥 13
 
2.2%
동 13
 
2.2%
Other values (118) 332
57.4%
Decimal Number
ValueCountFrequency (%)
1 51
25.9%
4 22
11.2%
2 22
11.2%
0 18
 
9.1%
6 17
 
8.6%
5 16
 
8.1%
7 15
 
7.6%
3 14
 
7.1%
8 11
 
5.6%
9 11
 
5.6%
Space Separator
ValueCountFrequency (%)
178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 578
59.0%
Common 402
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 51
 
8.8%
면 42
 
7.3%
길 41
 
7.1%
로 21
 
3.6%
성 18
 
3.1%
산 17
 
2.9%
읍 15
 
2.6%
장 15
 
2.6%
흥 13
 
2.2%
동 13
 
2.2%
Other values (118) 332
57.4%
Common
ValueCountFrequency (%)
178
44.3%
1 51
 
12.7%
- 25
 
6.2%
4 22
 
5.5%
2 22
 
5.5%
0 18
 
4.5%
6 17
 
4.2%
5 16
 
4.0%
7 15
 
3.7%
3 14
 
3.5%
Other values (4) 24
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 578
59.0%
ASCII 402
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
44.3%
1 51
 
12.7%
- 25
 
6.2%
4 22
 
5.5%
2 22
 
5.5%
0 18
 
4.5%
6 17
 
4.2%
5 16
 
4.0%
7 15
 
3.7%
3 14
 
3.5%
Other values (4) 24
 
6.0%
Hangul
ValueCountFrequency (%)
군 51
 
8.8%
면 42
 
7.3%
길 41
 
7.1%
로 21
 
3.6%
성 18
 
3.1%
산 17
 
2.9%
읍 15
 
2.6%
장 15
 
2.6%
흥 13
 
2.2%
동 13
 
2.2%
Other values (118) 332
57.4%

인증품목
Text

MISSING 

Distinct33
Distinct (%)55.0%
Missing2
Missing (%)3.2%
Memory size628.0 B
2023-12-12T12:23:07.720767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length2
Mean length2.85
Min length1

Characters and Unicode

Total characters171
Distinct characters72
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

Unique22 ?
Unique (%)36.7%

Sample

1st row고춧가루
2nd row김치
3rd row김치
4th row건강식품
5th row김치
ValueCountFrequency (%)
김치 11
17.7%
건강식품 7
 
11.3%
부각 3
 
4.8%
식품 3
 
4.8%
고구마 2
 
3.2%
쌀과자 2
 
3.2%
배즙 2
 
3.2%
배추 2
 
3.2%
굴비 2
 
3.2%
전복 2
 
3.2%
Other values (24) 26
41.9%
2023-12-12T12:23:08.149036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 13
 
7.6%
김 11
 
6.4%
치 11
 
6.4%
품 10
 
5.8%
건 8
 
4.7%
강 8
 
4.7%
배 6
 
3.5%
고 5
 
2.9%
차 4
 
2.3%
추 4
 
2.3%
Other values (62) 91
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
96.5%
Other Punctuation 3
 
1.8%
Space Separator 3
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 13
 
7.9%
김 11
 
6.7%
치 11
 
6.7%
품 10
 
6.1%
건 8
 
4.8%
강 8
 
4.8%
배 6
 
3.6%
고 5
 
3.0%
차 4
 
2.4%
추 4
 
2.4%
Other values (60) 85
51.5%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
96.5%
Common 6
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 13
 
7.9%
김 11
 
6.7%
치 11
 
6.7%
품 10
 
6.1%
건 8
 
4.8%
강 8
 
4.8%
배 6
 
3.6%
고 5
 
3.0%
차 4
 
2.4%
추 4
 
2.4%
Other values (60) 85
51.5%
Common
ValueCountFrequency (%)
, 3
50.0%
3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
96.5%
ASCII 6
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 13
 
7.9%
김 11
 
6.7%
치 11
 
6.7%
품 10
 
6.1%
건 8
 
4.8%
강 8
 
4.8%
배 6
 
3.6%
고 5
 
3.0%
차 4
 
2.4%
추 4
 
2.4%
Other values (60) 85
51.5%
ASCII
ValueCountFrequency (%)
, 3
50.0%
3
50.0%

Interactions

2023-12-12T12:23:03.392741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:23:08.280646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군업체명대표자소재지인증품목
연번1.0000.9611.0001.0001.0000.674
시군0.9611.0001.0001.0001.0000.813
업체명1.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
인증품목0.6740.8131.0001.0001.0001.000
2023-12-12T12:23:08.391415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군
연번1.0000.726
시군0.7261.000

Missing values

2023-12-12T12:23:03.552372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:23:03.711270image/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.
2023-12-12T12:23:04.205802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번시군업체명대표자소재지인증품목
01목포제이농수산송준호 외1목포시영산로849-6고춧가루
12여수강순의명가이점희여수시 화양로 1615-5김치
23여수돌산갓영농조합법인조양효여수시 돌산읍 두문포길 6김치
34순천동부생약영농조합법인홍재희순천시 해룡면 여순로 1679건강식품
45순천순천고들빼기영농조합법인유성진순천시 별량면 개령1길 23김치
56순천순천만더드림영농조합법인이철희순천시 별량면 우산외동길 58-5김치
67순천순천만모링가협동조합신춘호순천시 낙안면 덕천길 15건강식품
78순천쌍지뜰전통식품㈜김해옥순천시 평촌길 28쌀과자
89순천순천농협 남도식품장용식순천시 녹색로 1404-6 (대룡동)김치
910나주농업회사법인㈜개미와배짱이김경식나주시 노안면 금산로 33초당옥수수
연번시군업체명대표자소재지인증품목
5253장성농업회사법인 ㈜옐로우푸드전건수장성군 황룡면 신호신촌길 2-13김치
5354장성어업회사법인㈜아주식품최정림장성군 북하면 담장로 1110건강식품
5455장성이일사농장임봉수장성군 북하면 단풍로 1812곶감
5556완도어업회사법인 경영수산(유)최경영완도군 완도읍 농공단지1길 40-18전복
5657완도㈜흥일식품김도환완도군 완도읍 농공단지5길 4김치
5758진도어업회사법인 유한회사 기적수산용치평진도군 고군면 회동길 14-1전복
5859진도소랑다래랑오승희진도군 군내면 연산길 117보리쌀
5960곡성대신영농조합법인유도열곡성군 곡성읍 대평1길 15-19멜론
60<NA><NA><NA><NA><NA><NA>
61<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연번시군업체명대표자소재지인증품목# duplicates
0<NA><NA><NA><NA><NA><NA>2