Overview

Dataset statistics

Number of variables10
Number of observations31
Missing cells3
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory88.3 B

Variable types

Categorical3
Text4
Numeric3

Alerts

집계년도 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
도축집유구분명 is highly overall correlated with 도축종류명High correlation
도축종류명 is highly overall correlated with 도축집유구분명High correlation
소재지도로명주소 has 3 (9.7%) missing valuesMissing
사업장명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
소재지우편번호 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:34:33.247938
Analysis finished2023-12-10 21:34:34.902909
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 31
100.0%

Length

2023-12-11T06:34:34.979412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:34:35.079137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 31
100.0%

시군명
Text

Distinct18
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T06:34:35.260628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1290323
Min length3

Characters and Unicode

Total characters97
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)32.3%

Sample

1st row광주시
2nd row광주시
3rd row김포시
4th row김포시
5th row남양주시
ValueCountFrequency (%)
화성시 3
 
9.7%
포천시 3
 
9.7%
평택시 3
 
9.7%
안성시 3
 
9.7%
남양주시 3
 
9.7%
김포시 2
 
6.5%
광주시 2
 
6.5%
양주시 2
 
6.5%
연천군 1
 
3.2%
안산시 1
 
3.2%
Other values (8) 8
25.8%
2023-12-11T06:34:35.613729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
29.9%
주 8
 
8.2%
양 7
 
7.2%
천 7
 
7.2%
성 7
 
7.2%
포 5
 
5.2%
안 5
 
5.2%
남 4
 
4.1%
평 4
 
4.1%
화 3
 
3.1%
Other values (13) 18
18.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 97
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
29.9%
주 8
 
8.2%
양 7
 
7.2%
천 7
 
7.2%
성 7
 
7.2%
포 5
 
5.2%
안 5
 
5.2%
남 4
 
4.1%
평 4
 
4.1%
화 3
 
3.1%
Other values (13) 18
18.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 97
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
29.9%
주 8
 
8.2%
양 7
 
7.2%
천 7
 
7.2%
성 7
 
7.2%
포 5
 
5.2%
안 5
 
5.2%
남 4
 
4.1%
평 4
 
4.1%
화 3
 
3.1%
Other values (13) 18
18.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 97
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
29.9%
주 8
 
8.2%
양 7
 
7.2%
천 7
 
7.2%
성 7
 
7.2%
포 5
 
5.2%
안 5
 
5.2%
남 4
 
4.1%
평 4
 
4.1%
화 3
 
3.1%
Other values (13) 18
18.6%

도축집유구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
도축
21 
집유
10 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도축
2nd row집유
3rd row도축
4th row도축
5th row집유

Common Values

ValueCountFrequency (%)
도축 21
67.7%
집유 10
32.3%

Length

2023-12-11T06:34:35.752563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:34:35.869243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도축 21
67.7%
집유 10
32.3%

사업장명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T06:34:36.071110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length10.193548
Min length3

Characters and Unicode

Total characters316
Distinct characters94
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

Unique31 ?
Unique (%)100.0%

Sample

1st row우진산업,
2nd row㈜빙그레,광주집유장
3rd row영농조합법인,김포축산
4th row㈜우석식품
5th row(주)빙그레,도농집유장
ValueCountFrequency (%)
우진산업 1
 
3.2%
서울우유협동조합,양주공장,집유장 1
 
3.2%
㈜한강식품 1
 
3.2%
에비앙푸드㈜ 1
 
3.2%
농업회사법인,정우식품㈜ 1
 
3.2%
서울우유협동조합,포천집유장 1
 
3.2%
포천농축산(주 1
 
3.2%
매일유업(주),평택공장 1
 
3.2%
㈜평농 1
 
3.2%
평택축산업협동조합,평택집유장 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T06:34:36.439419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 24
 
7.6%
유 15
 
4.7%
㈜ 14
 
4.4%
장 13
 
4.1%
우 11
 
3.5%
조 10
 
3.2%
협 10
 
3.2%
주 9
 
2.8%
집 9
 
2.8%
산 9
 
2.8%
Other values (84) 192
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
85.4%
Other Punctuation 24
 
7.6%
Other Symbol 14
 
4.4%
Open Punctuation 4
 
1.3%
Close Punctuation 4
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 15
 
5.6%
장 13
 
4.8%
우 11
 
4.1%
조 10
 
3.7%
협 10
 
3.7%
주 9
 
3.3%
집 9
 
3.3%
산 9
 
3.3%
동 9
 
3.3%
합 9
 
3.3%
Other values (80) 166
61.5%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
89.9%
Common 32
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 15
 
5.3%
㈜ 14
 
4.9%
장 13
 
4.6%
우 11
 
3.9%
조 10
 
3.5%
협 10
 
3.5%
주 9
 
3.2%
집 9
 
3.2%
산 9
 
3.2%
동 9
 
3.2%
Other values (81) 175
61.6%
Common
ValueCountFrequency (%)
, 24
75.0%
( 4
 
12.5%
) 4
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
85.4%
ASCII 32
 
10.1%
None 14
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 24
75.0%
( 4
 
12.5%
) 4
 
12.5%
Hangul
ValueCountFrequency (%)
유 15
 
5.6%
장 13
 
4.8%
우 11
 
4.1%
조 10
 
3.7%
협 10
 
3.7%
주 9
 
3.3%
집 9
 
3.3%
산 9
 
3.3%
동 9
 
3.3%
합 9
 
3.3%
Other values (80) 166
61.5%
None
ValueCountFrequency (%)
㈜ 14
100.0%

도축종류명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
집유
10 
닭
8 
소,돼지
7 
메추리
 
1
돼지
 
1
Other values (4)
4 

Length

Max length10
Median length6
Mean length2.6774194
Min length1

Unique

Unique6 ?
Unique (%)19.4%

Sample

1st row소,돼지
2nd row집유
3rd row메추리
4th row돼지
5th row집유

Common Values

ValueCountFrequency (%)
집유 10
32.3%
닭 8
25.8%
소,돼지 7
22.6%
메추리 1
 
3.2%
돼지 1
 
3.2%
염소,닭 1
 
3.2%
오리 1
 
3.2%
소,돼지,말,당나귀 1
 
3.2%
소,돼지,말 1
 
3.2%

Length

2023-12-11T06:34:36.579058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:34:36.712619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집유 10
32.3%
닭 8
25.8%
소,돼지 7
22.6%
메추리 1
 
3.2%
돼지 1
 
3.2%
염소,닭 1
 
3.2%
오리 1
 
3.2%
소,돼지,말,당나귀 1
 
3.2%
소,돼지,말 1
 
3.2%

소재지지번주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T06:34:36.920524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length22.548387
Min length18

Characters and Unicode

Total characters699
Distinct characters104
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

Unique31 ?
Unique (%)100.0%

Sample

1st row경기도 광주시 곤지암읍 열미리 502-7번지
2nd row경기도 광주시 곤지암읍 삼리 580-1번지
3rd row경기도 김포시 대곶면 석정리 1030번지
4th row경기도 김포시 풍무동 661-8번지
5th row경기도 남양주시 다산동 4344-3번지
ValueCountFrequency (%)
경기도 31
 
20.9%
화성시 3
 
2.0%
안성시 3
 
2.0%
포천시 3
 
2.0%
남양주시 3
 
2.0%
평택시 3
 
2.0%
양주시 2
 
1.4%
곤지암읍 2
 
1.4%
광주시 2
 
1.4%
신북면 2
 
1.4%
Other values (93) 94
63.5%
2023-12-11T06:34:37.289638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
16.7%
지 32
 
4.6%
경 31
 
4.4%
도 31
 
4.4%
기 31
 
4.4%
번 30
 
4.3%
시 29
 
4.1%
1 28
 
4.0%
- 23
 
3.3%
동 17
 
2.4%
Other values (94) 330
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 420
60.1%
Decimal Number 133
 
19.0%
Space Separator 117
 
16.7%
Dash Punctuation 23
 
3.3%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 32
 
7.6%
경 31
 
7.4%
도 31
 
7.4%
기 31
 
7.4%
번 30
 
7.1%
시 29
 
6.9%
동 17
 
4.0%
리 17
 
4.0%
성 11
 
2.6%
면 10
 
2.4%
Other values (80) 181
43.1%
Decimal Number
ValueCountFrequency (%)
1 28
21.1%
3 17
12.8%
2 17
12.8%
4 15
11.3%
6 14
10.5%
0 10
 
7.5%
9 9
 
6.8%
5 9
 
6.8%
7 7
 
5.3%
8 7
 
5.3%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 420
60.1%
Common 279
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 32
 
7.6%
경 31
 
7.4%
도 31
 
7.4%
기 31
 
7.4%
번 30
 
7.1%
시 29
 
6.9%
동 17
 
4.0%
리 17
 
4.0%
성 11
 
2.6%
면 10
 
2.4%
Other values (80) 181
43.1%
Common
ValueCountFrequency (%)
117
41.9%
1 28
 
10.0%
- 23
 
8.2%
3 17
 
6.1%
2 17
 
6.1%
4 15
 
5.4%
6 14
 
5.0%
0 10
 
3.6%
9 9
 
3.2%
5 9
 
3.2%
Other values (4) 20
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
60.1%
ASCII 279
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
41.9%
1 28
 
10.0%
- 23
 
8.2%
3 17
 
6.1%
2 17
 
6.1%
4 15
 
5.4%
6 14
 
5.0%
0 10
 
3.6%
9 9
 
3.2%
5 9
 
3.2%
Other values (4) 20
 
7.2%
Hangul
ValueCountFrequency (%)
지 32
 
7.6%
경 31
 
7.4%
도 31
 
7.4%
기 31
 
7.4%
번 30
 
7.1%
시 29
 
6.9%
동 17
 
4.0%
리 17
 
4.0%
성 11
 
2.6%
면 10
 
2.4%
Other values (80) 181
43.1%

소재지도로명주소
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing3
Missing (%)9.7%
Memory size380.0 B
2023-12-11T06:34:37.580088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.214286
Min length14

Characters and Unicode

Total characters566
Distinct characters107
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

Unique28 ?
Unique (%)100.0%

Sample

1st row경기도 광주시 곤지암읍 광여로 200-18
2nd row경기도 광주시 곤지암읍 독고개길86번길 23
3rd row경기도 김포시 대곶면 대곶로 429-19
4th row경기도 김포시 승가로 71
5th row경기도 남양주시 다산순환로 45
ValueCountFrequency (%)
경기도 28
 
21.1%
포천시 3
 
2.3%
화성시 3
 
2.3%
남양주시 3
 
2.3%
71 2
 
1.5%
곤지암읍 2
 
1.5%
광주시 2
 
1.5%
안성시 2
 
1.5%
평택시 2
 
1.5%
63 2
 
1.5%
Other values (82) 84
63.2%
2023-12-11T06:34:38.055435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
18.6%
경 29
 
5.1%
기 28
 
4.9%
도 28
 
4.9%
시 26
 
4.6%
로 25
 
4.4%
1 19
 
3.4%
2 16
 
2.8%
6 13
 
2.3%
0 11
 
1.9%
Other values (97) 266
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 347
61.3%
Space Separator 105
 
18.6%
Decimal Number 104
 
18.4%
Dash Punctuation 10
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 29
 
8.4%
기 28
 
8.1%
도 28
 
8.1%
시 26
 
7.5%
로 25
 
7.2%
면 10
 
2.9%
길 9
 
2.6%
양 8
 
2.3%
성 8
 
2.3%
천 8
 
2.3%
Other values (85) 168
48.4%
Decimal Number
ValueCountFrequency (%)
1 19
18.3%
2 16
15.4%
6 13
12.5%
0 11
10.6%
3 10
9.6%
8 8
7.7%
5 8
7.7%
9 7
 
6.7%
7 6
 
5.8%
4 6
 
5.8%
Space Separator
ValueCountFrequency (%)
105
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 347
61.3%
Common 219
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 29
 
8.4%
기 28
 
8.1%
도 28
 
8.1%
시 26
 
7.5%
로 25
 
7.2%
면 10
 
2.9%
길 9
 
2.6%
양 8
 
2.3%
성 8
 
2.3%
천 8
 
2.3%
Other values (85) 168
48.4%
Common
ValueCountFrequency (%)
105
47.9%
1 19
 
8.7%
2 16
 
7.3%
6 13
 
5.9%
0 11
 
5.0%
- 10
 
4.6%
3 10
 
4.6%
8 8
 
3.7%
5 8
 
3.7%
9 7
 
3.2%
Other values (2) 12
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 347
61.3%
ASCII 219
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
105
47.9%
1 19
 
8.7%
2 16
 
7.3%
6 13
 
5.9%
0 11
 
5.0%
- 10
 
4.6%
3 10
 
4.6%
8 8
 
3.7%
5 8
 
3.7%
9 7
 
3.2%
Other values (2) 12
 
5.5%
Hangul
ValueCountFrequency (%)
경 29
 
8.4%
기 28
 
8.1%
도 28
 
8.1%
시 26
 
7.5%
로 25
 
7.2%
면 10
 
2.9%
길 9
 
2.6%
양 8
 
2.3%
성 8
 
2.3%
천 8
 
2.3%
Other values (85) 168
48.4%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14105.097
Minimum10026
Maximum18523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T06:34:38.207579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10026
5-th percentile10470.5
Q111368.5
median12806
Q317524.5
95-th percentile18331
Maximum18523
Range8497
Interquartile range (IQR)6156

Descriptive statistics

Standard deviation3011.4625
Coefficient of variation (CV)0.21350172
Kurtosis-1.6492225
Mean14105.097
Median Absolute Deviation (MAD)1798
Skewness0.2762483
Sum437258
Variance9068906.2
MonotonicityNot monotonic
2023-12-11T06:34:38.338253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
12717 1
 
3.2%
12806 1
 
3.2%
18523 1
 
3.2%
18365 1
 
3.2%
18297 1
 
3.2%
11140 1
 
3.2%
11127 1
 
3.2%
11138 1
 
3.2%
17714 1
 
3.2%
17748 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
10026 1
3.2%
10116 1
3.2%
10825 1
3.2%
11008 1
3.2%
11127 1
3.2%
11138 1
3.2%
11140 1
3.2%
11300 1
3.2%
11437 1
3.2%
11460 1
3.2%
ValueCountFrequency (%)
18523 1
3.2%
18365 1
3.2%
18297 1
3.2%
17934 1
3.2%
17748 1
3.2%
17714 1
3.2%
17539 1
3.2%
17533 1
3.2%
17516 1
3.2%
17412 1
3.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.473977
Minimum36.996014
Maximum38.031452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T06:34:38.505535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.996014
5-th percentile37.0321
Q137.168241
median37.429335
Q337.751323
95-th percentile37.997123
Maximum38.031452
Range1.0354386
Interquartile range (IQR)0.58308277

Descriptive statistics

Standard deviation0.33479046
Coefficient of variation (CV)0.0089339452
Kurtosis-1.2780213
Mean37.473977
Median Absolute Deviation (MAD)0.28986854
Skewness0.20026103
Sum1161.6933
Variance0.11208465
MonotonicityNot monotonic
2023-12-11T06:34:38.632431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
37.35034674 1
 
3.2%
37.35364048 1
 
3.2%
37.12599256 1
 
3.2%
37.1970148 1
 
3.2%
37.24142631 1
 
3.2%
37.91793432 1
 
3.2%
38.03145214 1
 
3.2%
37.92795045 1
 
3.2%
37.10872118 1
 
3.2%
37.02615661 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
36.99601352 1
3.2%
37.02615661 1
3.2%
37.0380434 1
3.2%
37.05234283 1
3.2%
37.07363513 1
3.2%
37.10872118 1
3.2%
37.12599256 1
3.2%
37.13946629 1
3.2%
37.1970148 1
3.2%
37.24142631 1
3.2%
ValueCountFrequency (%)
38.03145214 1
3.2%
38.0240704 1
3.2%
37.97017636 1
3.2%
37.92795045 1
3.2%
37.91793432 1
3.2%
37.86480217 1
3.2%
37.8334523 1
3.2%
37.82084084 1
3.2%
37.6818058 1
3.2%
37.64320754 1
3.2%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.1004
Minimum126.55244
Maximum127.50556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T06:34:38.766947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55244
5-th percentile126.73599
Q1126.97692
median127.07278
Q3127.23965
95-th percentile127.49219
Maximum127.50556
Range0.9531179
Interquartile range (IQR)0.26272965

Descriptive statistics

Standard deviation0.23261146
Coefficient of variation (CV)0.0018301395
Kurtosis-0.072794587
Mean127.1004
Median Absolute Deviation (MAD)0.1449789
Skewness-0.25252264
Sum3940.1123
Variance0.054108091
MonotonicityNot monotonic
2023-12-11T06:34:38.918692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
127.3662244 1
 
3.2%
127.3096821 1
 
3.2%
126.9983753 1
 
3.2%
127.0027059 1
 
3.2%
126.9554669 1
 
3.2%
127.2149900499 1
 
3.2%
127.2594345 1
 
3.2%
127.219867 1
 
3.2%
127.0693952 1
 
3.2%
127.0727835 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
126.5524444 1
3.2%
126.716038 1
3.2%
126.7559404 1
3.2%
126.7646451 1
3.2%
126.8463527 1
3.2%
126.8873644 1
3.2%
126.9412634 1
3.2%
126.9554669 1
3.2%
126.9983753 1
3.2%
127.0027059 1
3.2%
ValueCountFrequency (%)
127.5055623 1
3.2%
127.4953763 1
3.2%
127.489003 1
3.2%
127.3662244 1
3.2%
127.3607998 1
3.2%
127.3096821 1
3.2%
127.2607369 1
3.2%
127.2594345 1
3.2%
127.219867 1
3.2%
127.2177624 1
3.2%

Interactions

2023-12-11T06:34:34.297158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:33.735629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:34.000107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:34.387722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:33.809195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:34.106131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:34.513379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:33.891158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:34:34.201324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:34:39.028653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명도축집유구분명사업장명도축종류명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
시군명1.0000.0001.0000.6291.0001.0001.0000.8800.878
도축집유구분명0.0001.0001.0001.0001.0001.0000.0000.0000.000
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.000
도축종류명0.6291.0001.0001.0001.0001.0000.0000.5250.695
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0000.0001.0000.0001.0001.0001.0000.7060.910
WGS84위도0.8800.0001.0000.5251.0001.0000.7061.0000.000
WGS84경도0.8780.0001.0000.6951.0001.0000.9100.0001.000
2023-12-11T06:34:39.168785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도축종류명도축집유구분명
도축종류명1.0000.871
도축집유구분명0.8711.000
2023-12-11T06:34:39.266348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도도축집유구분명도축종류명
소재지우편번호1.000-0.8970.1130.0000.000
WGS84위도-0.8971.000-0.1480.0000.240
WGS84경도0.113-0.1481.0000.0000.384
도축집유구분명0.0000.0000.0001.0000.871
도축종류명0.0000.2400.3840.8711.000

Missing values

2023-12-11T06:34:34.661310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:34:34.846286image/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

집계년도시군명도축집유구분명사업장명도축종류명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
02023광주시도축우진산업,소,돼지경기도 광주시 곤지암읍 열미리 502-7번지경기도 광주시 곤지암읍 광여로 200-181271737.350347127.366224
12023광주시집유㈜빙그레,광주집유장집유경기도 광주시 곤지암읍 삼리 580-1번지경기도 광주시 곤지암읍 독고개길86번길 231280637.35364127.309682
22023김포시도축영농조합법인,김포축산메추리경기도 김포시 대곶면 석정리 1030번지경기도 김포시 대곶면 대곶로 429-191002637.681806126.552444
32023김포시도축㈜우석식품돼지경기도 김포시 풍무동 661-8번지경기도 김포시 승가로 711011637.604862126.716038
42023남양주시집유(주)빙그레,도농집유장집유경기도 남양주시 다산동 4344-3번지경기도 남양주시 다산순환로 451225337.6142127.149007
52023남양주시집유서울우우협동조합,남양주집유장집유경기도 남양주시 일패동 466-6번지경기도 남양주시 양정로 631224237.617632127.18669
62023남양주시도축㈜친환경명품축산소,돼지경기도 남양주시 진건읍 진관리 931-3번지경기도 남양주시 진건읍 금강로361번길 501213937.643208127.152872
72023동두천시도축㈜마니커,동두천지점닭경기도 동두천시 하봉암동 127번지경기도 동두천시 승전로 61130037.970176127.065619
82023부천시도축농협경제지주주식회사,부천축산물공판장소,돼지경기도 부천시 삼정동 12-4번지경기도 부천시 송내대로518번길 711444537.530607126.764645
92023성남시도축한국축산혁신협동조합염소,닭경기도 성남시 중원구 성남동 4931번지경기도 성남시 중원구 둔촌대로 681338337.429335127.126656
집계년도시군명도축집유구분명사업장명도축종류명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
212023파주시도축㈜정다운,자연일가닭경기도 파주시 법원읍 동문리 619-23번지경기도 파주시 법원읍 자운서원로 410-61082537.864802126.846353
222023평택시집유평택축산업협동조합,평택집유장,집유경기도 평택시 안중읍 안중리 194-14번지경기도 평택시 안중읍 서해로 1146-201793436.996014126.941263
232023평택시도축㈜평농소,돼지경기도 평택시 지제동 233-1(칠괴길 25)<NA>1774837.026157127.072783
242023평택시집유매일유업(주),평택공장집유경기도 평택시 진위면 가곡리 480번지경기도 평택시 진위면 진위서로 631771437.108721127.069395
252023포천시도축포천농축산(주),소,돼지,말,당나귀경기도 포천시 신북면 신평리 647-8번지경기도 포천시 신북면 중앙로461번길 251113837.92795127.219867
262023포천시집유서울우유협동조합,포천집유장집유경기도 포천시 영중면 성동리 411-5번지경기도 포천시 영중면 호국로 3295-231112738.031452127.259434
272023포천시도축농업회사법인,정우식품㈜닭경기도 포천시 신북면 가채리 274-2번지경기도 포천시 신북면 중앙로 3781114037.917934127.21499
282023화성시도축에비앙푸드㈜닭경기도 화성시 봉담읍 수영리 386-1번지경기도 화성시 봉담읍 효행로20번길 16-321829737.241426126.955467
292023화성시도축㈜한강식품닭경기도 화성시 안녕동 146-123번지경기도 화성시 만년로969번길 171836537.197015127.002706
302023화성시도축㈜우경축산소,돼지,말경기도 화성시 정남면 귀래리 209-26번지경기도 화성시 정남면 내향로 3601852337.125993126.998375