Overview

Dataset statistics

Number of variables6
Number of observations659
Missing cells68
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.3 KiB
Average record size in memory50.2 B

Variable types

Categorical2
Text2
Numeric2

Dataset

Description남해군 내 축산업 정보에 대한 데이터로 가축 종, 소재지지번주소, 소재지도로명주소, 사육 두수, 가축 면적 등 축산 현행 정보를 제공합니다.
Author경상남도 남해군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15109568

Alerts

데이터기준일자 has constant value ""Constant
사육두수 is highly overall correlated with 축산면적 and 1 other fieldsHigh correlation
축산면적 is highly overall correlated with 사육두수High correlation
가축종 is highly overall correlated with 사육두수High correlation
가축종 is highly imbalanced (79.9%)Imbalance
도로명주소 has 68 (10.3%) missing valuesMissing
사육두수 is highly skewed (γ1 = 22.06507888)Skewed
사육두수 has 8 (1.2%) zerosZeros

Reproduction

Analysis started2023-12-10 23:23:28.581667
Analysis finished2023-12-10 23:23:29.235494
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가축종
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct16
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
한우
593 
산양
 
18
염소
 
10
젖소
 
6
돼지
 
6
Other values (11)
 
26

Length

Max length7
Median length2
Mean length2.1001517
Min length2

Unique

Unique5 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
한우 593
90.0%
산양 18
 
2.7%
염소 10
 
1.5%
젖소 6
 
0.9%
돼지 6
 
0.9%
<NA> 6
 
0.9%
한우, 산양 4
 
0.6%
면양 4
 
0.6%
산란육성계 3
 
0.5%
한우, 육우 2
 
0.3%
Other values (6) 7
 
1.1%

Length

2023-12-11T08:23:29.294072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한우 602
89.9%
산양 23
 
3.4%
염소 13
 
1.9%
젖소 6
 
0.9%
돼지 6
 
0.9%
na 6
 
0.9%
면양 4
 
0.6%
산란육성계 3
 
0.4%
육우 3
 
0.4%
육계 2
 
0.3%
Other values (2) 2
 
0.3%
Distinct655
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2023-12-11T08:23:29.497734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length25.479514
Min length22

Characters and Unicode

Total characters16791
Distinct characters114
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique651 ?
Unique (%)98.8%

Sample

1st row경상남도 남해군 남면 상가리 1070번지
2nd row경상남도 남해군 서면 정포리 1015번지 2호
3rd row경상남도 남해군 서면 서호리 232번지 2호
4th row경상남도 남해군 이동면 다정리 549번지 3호
5th row경상남도 남해군 삼동면 봉화리 729번지
ValueCountFrequency (%)
경상남도 659
18.0%
남해군 659
18.0%
1호 130
 
3.6%
남면 124
 
3.4%
서면 110
 
3.0%
고현면 91
 
2.5%
설천면 84
 
2.3%
이동면 76
 
2.1%
2호 63
 
1.7%
남해읍 61
 
1.7%
Other values (663) 1598
43.7%
2023-12-11T08:23:29.885559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4283
25.5%
1565
 
9.3%
764
 
4.6%
720
 
4.3%
702
 
4.2%
668
 
4.0%
660
 
3.9%
659
 
3.9%
659
 
3.9%
659
 
3.9%
Other values (104) 5452
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10032
59.7%
Space Separator 4283
25.5%
Decimal Number 2469
 
14.7%
Dash Punctuation 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1565
15.6%
764
 
7.6%
720
 
7.2%
702
 
7.0%
668
 
6.7%
660
 
6.6%
659
 
6.6%
659
 
6.6%
659
 
6.6%
601
 
6.0%
Other values (89) 2375
23.7%
Decimal Number
ValueCountFrequency (%)
1 522
21.1%
2 292
11.8%
3 245
9.9%
8 209
8.5%
4 208
 
8.4%
6 205
 
8.3%
5 201
 
8.1%
0 201
 
8.1%
7 196
 
7.9%
9 190
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
4283
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10032
59.7%
Common 6757
40.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1565
15.6%
764
 
7.6%
720
 
7.2%
702
 
7.0%
668
 
6.7%
660
 
6.6%
659
 
6.6%
659
 
6.6%
659
 
6.6%
601
 
6.0%
Other values (89) 2375
23.7%
Common
ValueCountFrequency (%)
4283
63.4%
1 522
 
7.7%
2 292
 
4.3%
3 245
 
3.6%
8 209
 
3.1%
4 208
 
3.1%
6 205
 
3.0%
5 201
 
3.0%
0 201
 
3.0%
7 196
 
2.9%
Other values (3) 195
 
2.9%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10032
59.7%
ASCII 6759
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4283
63.4%
1 522
 
7.7%
2 292
 
4.3%
3 245
 
3.6%
8 209
 
3.1%
4 208
 
3.1%
6 205
 
3.0%
5 201
 
3.0%
0 201
 
3.0%
7 196
 
2.9%
Other values (5) 197
 
2.9%
Hangul
ValueCountFrequency (%)
1565
15.6%
764
 
7.6%
720
 
7.2%
702
 
7.0%
668
 
6.7%
660
 
6.6%
659
 
6.6%
659
 
6.6%
659
 
6.6%
601
 
6.0%
Other values (89) 2375
23.7%

도로명주소
Text

MISSING 

Distinct584
Distinct (%)98.8%
Missing68
Missing (%)10.3%
Memory size5.3 KiB
2023-12-11T08:23:30.092629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length35
Mean length24.746193
Min length18

Characters and Unicode

Total characters14625
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

Unique577 ?
Unique (%)97.6%

Sample

1st row경상남도 남해군 남면 고실로 193-68
2nd row경상남도 남해군 서면 남서대로 2838-26
3rd row경상남도 남해군 이동면 남해대로2385번길 22-180
4th row경상남도 남해군 삼동면 봉화로 201-19
5th row경상남도 남해군 삼동면 난음로 313
ValueCountFrequency (%)
경상남도 591
19.7%
남해군 591
19.7%
남면 114
 
3.8%
서면 97
 
3.2%
고현면 82
 
2.7%
설천면 80
 
2.7%
이동면 69
 
2.3%
남해읍 55
 
1.8%
남서대로 49
 
1.6%
삼동면 43
 
1.4%
Other values (718) 1224
40.9%
2023-12-11T08:23:30.424732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2404
16.4%
1588
 
10.9%
706
 
4.8%
601
 
4.1%
1 592
 
4.0%
591
 
4.0%
591
 
4.0%
591
 
4.0%
587
 
4.0%
565
 
3.9%
Other values (90) 5809
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8514
58.2%
Decimal Number 3262
 
22.3%
Space Separator 2404
 
16.4%
Dash Punctuation 401
 
2.7%
Open Punctuation 20
 
0.1%
Close Punctuation 20
 
0.1%
Other Punctuation 2
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1588
18.7%
706
 
8.3%
601
 
7.1%
591
 
6.9%
591
 
6.9%
591
 
6.9%
587
 
6.9%
565
 
6.6%
374
 
4.4%
370
 
4.3%
Other values (73) 1950
22.9%
Decimal Number
ValueCountFrequency (%)
1 592
18.1%
2 545
16.7%
3 343
10.5%
7 303
9.3%
4 292
9.0%
5 291
8.9%
8 237
7.3%
6 233
 
7.1%
9 223
 
6.8%
0 203
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
2404
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 401
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8514
58.2%
Common 6109
41.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1588
18.7%
706
 
8.3%
601
 
7.1%
591
 
6.9%
591
 
6.9%
591
 
6.9%
587
 
6.9%
565
 
6.6%
374
 
4.4%
370
 
4.3%
Other values (73) 1950
22.9%
Common
ValueCountFrequency (%)
2404
39.4%
1 592
 
9.7%
2 545
 
8.9%
- 401
 
6.6%
3 343
 
5.6%
7 303
 
5.0%
4 292
 
4.8%
5 291
 
4.8%
8 237
 
3.9%
6 233
 
3.8%
Other values (5) 468
 
7.7%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8514
58.2%
ASCII 6111
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2404
39.3%
1 592
 
9.7%
2 545
 
8.9%
- 401
 
6.6%
3 343
 
5.6%
7 303
 
5.0%
4 292
 
4.8%
5 291
 
4.8%
8 237
 
3.9%
6 233
 
3.8%
Other values (7) 470
 
7.7%
Hangul
ValueCountFrequency (%)
1588
18.7%
706
 
8.3%
601
 
7.1%
591
 
6.9%
591
 
6.9%
591
 
6.9%
587
 
6.9%
565
 
6.6%
374
 
4.4%
370
 
4.3%
Other values (73) 1950
22.9%

사육두수
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct102
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.45068
Minimum0
Maximum50000
Zeros8
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2023-12-11T08:23:30.567069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median10
Q326.5
95-th percentile110.8
Maximum50000
Range50000
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation2079.6922
Coefficient of variation (CV)15.130461
Kurtosis513.11611
Mean137.45068
Median Absolute Deviation (MAD)8
Skewness22.065079
Sum90580
Variance4325119.6
MonotonicityNot monotonic
2023-12-11T08:23:30.739186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 76
 
11.5%
1 45
 
6.8%
5 39
 
5.9%
4 33
 
5.0%
3 30
 
4.6%
8 27
 
4.1%
6 27
 
4.1%
7 22
 
3.3%
9 20
 
3.0%
10 19
 
2.9%
Other values (92) 321
48.7%
ValueCountFrequency (%)
0 8
 
1.2%
1 45
6.8%
2 76
11.5%
3 30
 
4.6%
4 33
5.0%
5 39
5.9%
6 27
 
4.1%
7 22
 
3.3%
8 27
 
4.1%
9 20
 
3.0%
ValueCountFrequency (%)
50000 1
0.2%
18500 1
0.2%
3400 1
0.2%
1310 1
0.2%
910 1
0.2%
510 1
0.2%
500 1
0.2%
400 1
0.2%
350 1
0.2%
339 1
0.2%

축산면적
Real number (ℝ)

HIGH CORRELATION 

Distinct341
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean367.23672
Minimum9
Maximum7438
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2023-12-11T08:23:30.877986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile12
Q144.5
median160
Q3389
95-th percentile1398.8
Maximum7438
Range7429
Interquartile range (IQR)344.5

Descriptive statistics

Standard deviation638.82672
Coefficient of variation (CV)1.7395502
Kurtosis40.602675
Mean367.23672
Median Absolute Deviation (MAD)139
Skewness5.1246529
Sum242009
Variance408099.58
MonotonicityNot monotonic
2023-12-11T08:23:31.092840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 17
 
2.6%
64 15
 
2.3%
12 12
 
1.8%
98 11
 
1.7%
20 11
 
1.7%
50 10
 
1.5%
40 10
 
1.5%
160 10
 
1.5%
18 9
 
1.4%
13 9
 
1.4%
Other values (331) 545
82.7%
ValueCountFrequency (%)
9 1
 
0.2%
10 17
2.6%
11 5
 
0.8%
12 12
1.8%
13 9
1.4%
14 4
 
0.6%
15 6
 
0.9%
16 8
1.2%
17 6
 
0.9%
18 9
1.4%
ValueCountFrequency (%)
7438 1
0.2%
6622 1
0.2%
3769 1
0.2%
3628 1
0.2%
3458 1
0.2%
3314 1
0.2%
2927 1
0.2%
2768 1
0.2%
2650 1
0.2%
2642 1
0.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2022-11-07
659 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-11-07
2nd row2022-11-07
3rd row2022-11-07
4th row2022-11-07
5th row2022-11-07

Common Values

ValueCountFrequency (%)
2022-11-07 659
100.0%

Length

2023-12-11T08:23:31.278143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:31.374839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-11-07 659
100.0%

Interactions

2023-12-11T08:23:28.921383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:23:28.773042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:23:28.998173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:23:28.844851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:23:31.442561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가축종사육두수축산면적
가축종1.0001.0000.576
사육두수1.0001.0000.497
축산면적0.5760.4971.000
2023-12-11T08:23:31.539514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사육두수축산면적가축종
사육두수1.0000.7790.991
축산면적0.7791.0000.289
가축종0.9910.2891.000

Missing values

2023-12-11T08:23:29.106679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:23:29.193839image/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

가축종지번주소도로명주소사육두수축산면적데이터기준일자
0한우경상남도 남해군 남면 상가리 1070번지경상남도 남해군 남면 고실로 193-6810017702022-11-07
1한우경상남도 남해군 서면 정포리 1015번지 2호경상남도 남해군 서면 남서대로 2838-268629272022-11-07
2한우경상남도 남해군 서면 서호리 232번지 2호<NA>1259422022-11-07
3한우경상남도 남해군 이동면 다정리 549번지 3호경상남도 남해군 이동면 남해대로2385번길 22-180404992022-11-07
4한우경상남도 남해군 삼동면 봉화리 729번지경상남도 남해군 삼동면 봉화로 201-1910611172022-11-07
5한우경상남도 남해군 삼동면 영지리 1026번지 12호경상남도 남해군 삼동면 난음로 313604362022-11-07
6한우경상남도 남해군 남해읍 평리 617번지경상남도 남해군 남해읍 당넘로247번길 78-26258682022-11-07
7한우경상남도 남해군 서면 남상리 1009번지경상남도 남해군 서면 남서대로2197번길 26-4505762022-11-07
8한우경상남도 남해군 이동면 다정리 1742번지경상남도 남해군 이동면 남해대로2513번길 48164362022-11-07
9한우경상남도 남해군 고현면 대곡리 1043번지 1호경상남도 남해군 고현면 화방로211번길 47-11606552022-11-07
가축종지번주소도로명주소사육두수축산면적데이터기준일자
649한우경상남도 남해군 남해읍 입현리 939번지 3호경상남도 남해군 남해읍 남해대로 2555-82452022-11-07
650한우경상남도 남해군 설천면 금음리 567번지경상남도 남해군 설천면 강진로 391-63802022-11-07
651한우경상남도 남해군 이동면 다정리 533번지경상남도 남해군 이동면 남해대로2385번길 22-143115022022-11-07
652한우경상남도 남해군 삼동면 봉화리 72번지경상남도 남해군 삼동면 봉화로56번길 32-48862022-11-07
653한우경상남도 남해군 설천면 문항리 628번지경상남도 남해군 설천면 강진로80번길 718982022-11-07
654한우경상남도 남해군 고현면 남치리 157번지 1호경상남도 남해군 고현면 남치로159번길 48-291502022-11-07
655한우경상남도 남해군 이동면 석평리 605번지경상남도 남해군 이동면 석평로58번길 28-202242022-11-07
656한우경상남도 남해군 서면 연죽리 760번지 1호경상남도 남해군 서면 연죽로 7-222202022-11-07
657한우경상남도 남해군 남면 상가리 248번지경상남도 남해군 남면 고실로42번길 106982022-11-07
658한우경상남도 남해군 서면 서상리 824번지 2호경상남도 남해군 서면 남서대로1517번길 831122022-11-07