Overview

Dataset statistics

Number of variables6
Number of observations24
Missing cells9
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory56.5 B

Variable types

Numeric3
Categorical1
Text2

Dataset

Description인천시 관내의 곤충을 사육하고 있는 농가 현황에 대한 데이터로 상호명, 사육시설 면적, 연간사육 마릿수 등을 제공합니다.
URLhttps://www.data.go.kr/data/15059695/fileData.do

Alerts

연번 is highly overall correlated with 시군구High correlation
시군구 is highly overall correlated with 연번High correlation
곤충 사육시설(제곱미터) has 6 (25.0%) missing valuesMissing
연간 사육곤충(마리수) has 3 (12.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:15:56.914327
Analysis finished2023-12-12 14:15:58.384379
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T23:15:58.475783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2023-12-12T23:15:58.927906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

시군구
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
서구
9 
강화군
7 
옹진군
4 
남동구
2 
연수구
1 

Length

Max length3
Median length3
Mean length2.625
Min length2

Unique

Unique2 ?
Unique (%)8.3%

Sample

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

Common Values

ValueCountFrequency (%)
서구 9
37.5%
강화군 7
29.2%
옹진군 4
16.7%
남동구 2
 
8.3%
연수구 1
 
4.2%
계양구 1
 
4.2%

Length

2023-12-12T23:15:59.080177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:15:59.208406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 9
37.5%
강화군 7
29.2%
옹진군 4
16.7%
남동구 2
 
8.3%
연수구 1
 
4.2%
계양구 1
 
4.2%

나머지 주소
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T23:15:59.490611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length15.125
Min length8

Characters and Unicode

Total characters363
Distinct characters86
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

Unique22 ?
Unique (%)91.7%

Sample

1st row강화읍 고비고개로 324-1
2nd row선원면 연동로128번길 8-20
3rd row하점면 강화서로 602-15
4th row하점면 강화서로 602-15
5th row불은면 강화동로 260
ValueCountFrequency (%)
하점면 2
 
2.9%
불은면 2
 
2.9%
강화서로 2
 
2.9%
602-15 2
 
2.9%
연희동 1
 
1.5%
b01호 1
 
1.5%
252(청라동,홈플러스 1
 
1.5%
청라점 1
 
1.5%
지하 1
 
1.5%
1층 1
 
1.5%
Other values (54) 54
79.4%
2023-12-12T23:15:59.946495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
12.1%
1 27
 
7.4%
2 21
 
5.8%
로 19
 
5.2%
- 14
 
3.9%
동 13
 
3.6%
5 12
 
3.3%
4 10
 
2.8%
6 10
 
2.8%
번 9
 
2.5%
Other values (76) 184
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
46.8%
Decimal Number 112
30.9%
Space Separator 44
 
12.1%
Dash Punctuation 14
 
3.9%
Close Punctuation 7
 
1.9%
Open Punctuation 7
 
1.9%
Other Punctuation 7
 
1.9%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 19
 
11.2%
동 13
 
7.6%
번 9
 
5.3%
길 8
 
4.7%
면 7
 
4.1%
화 5
 
2.9%
불 4
 
2.4%
하 4
 
2.4%
점 4
 
2.4%
강 4
 
2.4%
Other values (60) 93
54.7%
Decimal Number
ValueCountFrequency (%)
1 27
24.1%
2 21
18.8%
5 12
10.7%
4 10
 
8.9%
6 10
 
8.9%
3 8
 
7.1%
0 7
 
6.2%
8 6
 
5.4%
9 6
 
5.4%
7 5
 
4.5%
Space Separator
ValueCountFrequency (%)
44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191
52.6%
Hangul 170
46.8%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 19
 
11.2%
동 13
 
7.6%
번 9
 
5.3%
길 8
 
4.7%
면 7
 
4.1%
화 5
 
2.9%
불 4
 
2.4%
하 4
 
2.4%
점 4
 
2.4%
강 4
 
2.4%
Other values (60) 93
54.7%
Common
ValueCountFrequency (%)
44
23.0%
1 27
14.1%
2 21
11.0%
- 14
 
7.3%
5 12
 
6.3%
4 10
 
5.2%
6 10
 
5.2%
3 8
 
4.2%
0 7
 
3.7%
) 7
 
3.7%
Other values (5) 31
16.2%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
53.2%
Hangul 170
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
22.8%
1 27
14.0%
2 21
10.9%
- 14
 
7.3%
5 12
 
6.2%
4 10
 
5.2%
6 10
 
5.2%
3 8
 
4.1%
0 7
 
3.6%
) 7
 
3.6%
Other values (6) 33
17.1%
Hangul
ValueCountFrequency (%)
로 19
 
11.2%
동 13
 
7.6%
번 9
 
5.3%
길 8
 
4.7%
면 7
 
4.1%
화 5
 
2.9%
불 4
 
2.4%
하 4
 
2.4%
점 4
 
2.4%
강 4
 
2.4%
Other values (60) 93
54.7%

상호
Text

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T23:16:00.226043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length6.0833333
Min length2

Characters and Unicode

Total characters146
Distinct characters86
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)91.7%

Sample

1st row고려산곤충나라
2nd row나비로
3rd row에어돔
4th row에어돔
5th row귀뚜라미 하우스
ValueCountFrequency (%)
에어돔 2
 
7.1%
곤충농장 2
 
7.1%
고려산곤충나라 1
 
3.6%
큰빛뮐웜 1
 
3.6%
피어나플라워 1
 
3.6%
가좌점 1
 
3.6%
홈플러스 1
 
3.6%
검단점 1
 
3.6%
롯데쇼핑㈜롯데마트 1
 
3.6%
농업회사법인㈜도시농부들 1
 
3.6%
Other values (16) 16
57.1%
2023-12-12T23:16:00.592205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 8
 
5.5%
라 6
 
4.1%
곤 4
 
2.7%
나 4
 
2.7%
굼 4
 
2.7%
4
 
2.7%
충 4
 
2.7%
원 3
 
2.1%
사 3
 
2.1%
어 3
 
2.1%
Other values (76) 103
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
95.2%
Space Separator 4
 
2.7%
Other Symbol 3
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 8
 
5.8%
라 6
 
4.3%
곤 4
 
2.9%
나 4
 
2.9%
굼 4
 
2.9%
충 4
 
2.9%
원 3
 
2.2%
사 3
 
2.2%
어 3
 
2.2%
회 3
 
2.2%
Other values (74) 97
69.8%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
97.3%
Common 4
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 8
 
5.6%
라 6
 
4.2%
곤 4
 
2.8%
나 4
 
2.8%
굼 4
 
2.8%
충 4
 
2.8%
원 3
 
2.1%
사 3
 
2.1%
어 3
 
2.1%
회 3
 
2.1%
Other values (75) 100
70.4%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
95.2%
ASCII 4
 
2.7%
None 3
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 8
 
5.8%
라 6
 
4.3%
곤 4
 
2.9%
나 4
 
2.9%
굼 4
 
2.9%
충 4
 
2.9%
원 3
 
2.2%
사 3
 
2.2%
어 3
 
2.2%
회 3
 
2.2%
Other values (74) 97
69.8%
ASCII
ValueCountFrequency (%)
4
100.0%
None
ValueCountFrequency (%)
㈜ 3
100.0%

곤충 사육시설(제곱미터)
Real number (ℝ)

MISSING 

Distinct15
Distinct (%)83.3%
Missing6
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean323.61111
Minimum10
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T23:16:00.732563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile41.45
Q1113.25
median250
Q3359.75
95-th percentile838.5
Maximum1000
Range990
Interquartile range (IQR)246.5

Descriptive statistics

Standard deviation282.92987
Coefficient of variation (CV)0.87428972
Kurtosis0.56827552
Mean323.61111
Median Absolute Deviation (MAD)132
Skewness1.1438266
Sum5825
Variance80049.31
MonotonicityNot monotonic
2023-12-12T23:16:00.826146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
330 2
 
8.3%
660 2
 
8.3%
200 2
 
8.3%
50 1
 
4.2%
300 1
 
4.2%
1000 1
 
4.2%
153 1
 
4.2%
810 1
 
4.2%
181 1
 
4.2%
364 1
 
4.2%
Other values (5) 5
20.8%
(Missing) 6
25.0%
ValueCountFrequency (%)
10 1
4.2%
47 1
4.2%
50 1
4.2%
83 1
4.2%
100 1
4.2%
153 1
4.2%
181 1
4.2%
200 2
8.3%
300 1
4.2%
330 2
8.3%
ValueCountFrequency (%)
1000 1
4.2%
810 1
4.2%
660 2
8.3%
364 1
4.2%
347 1
4.2%
330 2
8.3%
300 1
4.2%
200 2
8.3%
181 1
4.2%
153 1
4.2%

연간 사육곤충(마리수)
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)90.5%
Missing3
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean1562231.6
Minimum10
Maximum30000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T23:16:00.936336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile30
Q15000
median50200
Q3100000
95-th percentile1500000
Maximum30000000
Range29999990
Interquartile range (IQR)95000

Descriptive statistics

Standard deviation6524169.2
Coefficient of variation (CV)4.1761857
Kurtosis20.876716
Mean1562231.6
Median Absolute Deviation (MAD)49200
Skewness4.5638709
Sum32806863
Variance4.2564783 × 1013
MonotonicityNot monotonic
2023-12-12T23:16:01.032057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
100000 2
 
8.3%
60000 2
 
8.3%
468000 1
 
4.2%
10 1
 
4.2%
12500 1
 
4.2%
40000 1
 
4.2%
30 1
 
4.2%
473 1
 
4.2%
88650 1
 
4.2%
1500000 1
 
4.2%
Other values (9) 9
37.5%
(Missing) 3
 
12.5%
ValueCountFrequency (%)
10 1
4.2%
30 1
4.2%
473 1
4.2%
1000 1
4.2%
2000 1
4.2%
5000 1
4.2%
12500 1
4.2%
15000 1
4.2%
29000 1
4.2%
40000 1
4.2%
ValueCountFrequency (%)
30000000 1
4.2%
1500000 1
4.2%
468000 1
4.2%
150000 1
4.2%
125000 1
4.2%
100000 2
8.3%
88650 1
4.2%
60000 2
8.3%
50200 1
4.2%
40000 1
4.2%

Interactions

2023-12-12T23:15:57.798465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.230190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.526300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.893110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.331487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.601495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.984580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.439346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:15:57.692376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:16:01.110480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구나머지 주소상호곤충 사육시설(제곱미터)연간 사육곤충(마리수)
연번1.0000.8970.9190.9190.0000.000
시군구0.8971.0001.0001.0000.0000.000
나머지 주소0.9191.0001.0001.0001.0001.000
상호0.9191.0001.0001.0001.0001.000
곤충 사육시설(제곱미터)0.0000.0001.0001.0001.0000.000
연간 사육곤충(마리수)0.0000.0001.0001.0000.0001.000
2023-12-12T23:16:01.206114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번곤충 사육시설(제곱미터)연간 사육곤충(마리수)시군구
연번1.000-0.418-0.2200.655
곤충 사육시설(제곱미터)-0.4181.0000.0590.000
연간 사육곤충(마리수)-0.2200.0591.0000.000
시군구0.6550.0000.0001.000

Missing values

2023-12-12T23:15:58.102949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:15:58.213830image/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.
2023-12-12T23:15:58.322600image/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

연번시군구나머지 주소상호곤충 사육시설(제곱미터)연간 사육곤충(마리수)
01강화군강화읍 고비고개로 324-1고려산곤충나라5015000
12강화군선원면 연동로128번길 8-20나비로3302000
23강화군하점면 강화서로 602-15에어돔660100000
34강화군하점면 강화서로 602-15에어돔660100000
45강화군불은면 강화동로 260귀뚜라미 하우스300150000
56강화군불은면 불은북로 154-19일송10001000
67강화군화도면 해안남로 1691번길 46-24, 웨스턴비치로얄굼뱅이2005000
78옹진군내리1327-80니오타니 곤충농장15330000000
89옹진군영흥남로 23번길농업회사법인옹진라바농원주식회사810125000
910옹진군영흥로 252번길숨굼벵이18160000
연번시군구나머지 주소상호곤충 사육시설(제곱미터)연간 사육곤충(마리수)
1415계양구다남동 34-3자연나라33088650
1516서구청라커낼로 252(청라동,홈플러스 청라점 지하 1층)㈜펫뱅크<NA>473
1617서구서곶로 754(검단점, 이마트 수족관)로얄수족관<NA>30
1718서구검암동 251-17번지동대문펫샵20040000
1819서구완정로165번길 8,B동 B01호농업회사법인㈜도시농부들<NA><NA>
1920서구한들로 66-53(시천동)곤충농장4712500
2021서구원당대로 581(마전동)롯데쇼핑㈜롯데마트 검단점<NA><NA>
2122서구가정로 151번길 11홈플러스 가좌점<NA><NA>
2223서구검단로744번1길 25, 101호(불로동)피어나플라워<NA>10
2324서구연희동 127-1꿈트리농원1060000