Overview

Dataset statistics

Number of variables17
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory154.3 B

Variable types

Text1
Categorical9
Numeric7

Dataset

Description도축장별 축종별 도축현황입니다.
Author전라북도
URLhttps://www.data.go.kr/data/15010844/fileData.do

Alerts

수입소 has constant value ""Constant
겸용종(닭) has constant value ""Constant
말 is highly overall correlated with 한우 and 2 other fieldsHigh correlation
젖소 is highly overall correlated with 한우 and 2 other fieldsHigh correlation
산란노계 is highly overall correlated with 산란종계 and 1 other fieldsHigh correlation
육용종계 is highly overall correlated with 산란노계 and 1 other fieldsHigh correlation
산란종계 is highly overall correlated with 산란노계 and 1 other fieldsHigh correlation
한우 is highly overall correlated with 육우 and 3 other fieldsHigh correlation
육우 is highly overall correlated with 한우 and 2 other fieldsHigh correlation
돼지 is highly overall correlated with 육계 and 1 other fieldsHigh correlation
육계 is highly overall correlated with 돼지 and 2 other fieldsHigh correlation
삼계 is highly overall correlated with 육계 and 1 other fieldsHigh correlation
토종닭 is highly overall correlated with 돼지 and 2 other fieldsHigh correlation
양 is highly overall correlated with 한우High correlation
젖소 is highly imbalanced (60.1%)Imbalance
말 is highly imbalanced (83.1%)Imbalance
양 is highly imbalanced (83.1%)Imbalance
산란노계 is highly imbalanced (78.8%)Imbalance
산란종계 is highly imbalanced (71.4%)Imbalance
육용종계 is highly imbalanced (78.8%)Imbalance
한우 has 28 (70.0%) zerosZeros
육우 has 30 (75.0%) zerosZeros
돼지 has 24 (60.0%) zerosZeros
육계 has 28 (70.0%) zerosZeros
삼계 has 32 (80.0%) zerosZeros
토종닭 has 28 (70.0%) zerosZeros
오리 has 34 (85.0%) zerosZeros

Reproduction

Analysis started2024-04-17 14:21:56.869972
Analysis finished2024-04-17 14:22:02.242185
Duration5.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도축장명
Text

Distinct20
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-04-17T23:22:02.375133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12.5
Mean length8.95
Min length4

Characters and Unicode

Total characters358
Distinct characters74
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

Unique0 ?
Unique (%)0.0%

Sample

1st row(유)금돈
2nd row(유)금돈
3rd row(주)농협목우촌 김제육가공공장
4th row(주)농협목우촌 김제육가공공장
5th row(주)동우팜투테이블
ValueCountFrequency (%)
주)하림 4
 
7.7%
주식회사 4
 
7.7%
농업회사법인(주)사조원 4
 
7.7%
정읍공장 2
 
3.8%
정다운 2
 
3.8%
싱그린에프에스 2
 
3.8%
도드람김제에프엠씨 2
 
3.8%
농업회사법인산수들주식회사 2
 
3.8%
순동공장 2
 
3.8%
금호실업 2
 
3.8%
Other values (13) 26
50.0%
2024-04-17T23:22:02.940104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 32
 
8.9%
( 28
 
7.8%
) 28
 
7.8%
사 16
 
4.5%
회 12
 
3.4%
12
 
3.4%
업 10
 
2.8%
공 10
 
2.8%
농 8
 
2.2%
산 8
 
2.2%
Other values (64) 194
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 290
81.0%
Open Punctuation 28
 
7.8%
Close Punctuation 28
 
7.8%
Space Separator 12
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 32
 
11.0%
사 16
 
5.5%
회 12
 
4.1%
업 10
 
3.4%
공 10
 
3.4%
농 8
 
2.8%
산 8
 
2.8%
장 8
 
2.8%
식 6
 
2.1%
에 6
 
2.1%
Other values (61) 174
60.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 290
81.0%
Common 68
 
19.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 32
 
11.0%
사 16
 
5.5%
회 12
 
4.1%
업 10
 
3.4%
공 10
 
3.4%
농 8
 
2.8%
산 8
 
2.8%
장 8
 
2.8%
식 6
 
2.1%
에 6
 
2.1%
Other values (61) 174
60.0%
Common
ValueCountFrequency (%)
( 28
41.2%
) 28
41.2%
12
17.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 290
81.0%
ASCII 68
 
19.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 32
 
11.0%
사 16
 
5.5%
회 12
 
4.1%
업 10
 
3.4%
공 10
 
3.4%
농 8
 
2.8%
산 8
 
2.8%
장 8
 
2.8%
식 6
 
2.1%
에 6
 
2.1%
Other values (61) 174
60.0%
ASCII
ValueCountFrequency (%)
( 28
41.2%
) 28
41.2%
12
17.6%

축종
Categorical

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
당월
20 
분기
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row당월
2nd row분기
3rd row당월
4th row분기
5th row당월

Common Values

ValueCountFrequency (%)
당월 20
50.0%
분기 20
50.0%

Length

2024-04-17T23:22:03.065383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:03.166322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당월 20
50.0%
분기 20
50.0%

한우
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.5
Minimum0
Maximum3076
Zeros28
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:03.248009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q321.75
95-th percentile932.35
Maximum3076
Range3076
Interquartile range (IQR)21.75

Descriptive statistics

Standard deviation549.14614
Coefficient of variation (CV)2.8527072
Kurtosis20.189564
Mean192.5
Median Absolute Deviation (MAD)0
Skewness4.210613
Sum7700
Variance301561.49
MonotonicityNot monotonic
2024-04-17T23:22:03.341286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 28
70.0%
39 1
 
2.5%
64 1
 
2.5%
248 1
 
2.5%
522 1
 
2.5%
1338 1
 
2.5%
3076 1
 
2.5%
4 1
 
2.5%
16 1
 
2.5%
300 1
 
2.5%
Other values (3) 3
 
7.5%
ValueCountFrequency (%)
0 28
70.0%
4 1
 
2.5%
16 1
 
2.5%
39 1
 
2.5%
64 1
 
2.5%
248 1
 
2.5%
300 1
 
2.5%
463 1
 
2.5%
522 1
 
2.5%
719 1
 
2.5%
ValueCountFrequency (%)
3076 1
2.5%
1338 1
2.5%
911 1
2.5%
719 1
2.5%
522 1
2.5%
463 1
2.5%
300 1
2.5%
248 1
2.5%
64 1
2.5%
39 1
2.5%

젖소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
34 
1
4 
11
 
1
19
 
1

Length

Max length2
Median length1
Mean length1.05
Min length1

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 34
85.0%
1 4
 
10.0%
11 1
 
2.5%
19 1
 
2.5%

Length

2024-04-17T23:22:03.446171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:03.537531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 34
85.0%
1 4
 
10.0%
11 1
 
2.5%
19 1
 
2.5%

육우
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.975
Minimum0
Maximum15
Zeros30
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:03.614477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile3.25
Maximum15
Range15
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation2.7126248
Coefficient of variation (CV)2.7821793
Kurtosis19.507982
Mean0.975
Median Absolute Deviation (MAD)0
Skewness4.1898399
Sum39
Variance7.3583333
MonotonicityNot monotonic
2024-04-17T23:22:03.705787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 30
75.0%
2 4
 
10.0%
3 2
 
5.0%
1 2
 
5.0%
8 1
 
2.5%
15 1
 
2.5%
ValueCountFrequency (%)
0 30
75.0%
1 2
 
5.0%
2 4
 
10.0%
3 2
 
5.0%
8 1
 
2.5%
15 1
 
2.5%
ValueCountFrequency (%)
15 1
 
2.5%
8 1
 
2.5%
3 2
 
5.0%
2 4
 
10.0%
1 2
 
5.0%
0 30
75.0%

수입소
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 40
100.0%

Length

2024-04-17T23:22:03.808559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:03.890891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
100.0%

돼지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)42.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18141.125
Minimum0
Maximum183402
Zeros24
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:03.964944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q318248.5
95-th percentile72922.5
Maximum183402
Range183402
Interquartile range (IQR)18248.5

Descriptive statistics

Standard deviation37398.142
Coefficient of variation (CV)2.0615117
Kurtosis9.9366567
Mean18141.125
Median Absolute Deviation (MAD)0
Skewness2.9395423
Sum725645
Variance1.398621 × 109
MonotonicityNot monotonic
2024-04-17T23:22:04.055759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 24
60.0%
18916 1
 
2.5%
40 1
 
2.5%
183402 1
 
2.5%
63234 1
 
2.5%
14501 1
 
2.5%
4919 1
 
2.5%
48150 1
 
2.5%
18026 1
 
2.5%
10 1
 
2.5%
Other values (7) 7
 
17.5%
ValueCountFrequency (%)
0 24
60.0%
10 1
 
2.5%
40 1
 
2.5%
4919 1
 
2.5%
14501 1
 
2.5%
16221 1
 
2.5%
18026 1
 
2.5%
18916 1
 
2.5%
25003 1
 
2.5%
40578 1
 
2.5%
ValueCountFrequency (%)
183402 1
2.5%
117544 1
2.5%
70574 1
2.5%
63234 1
2.5%
56990 1
2.5%
48150 1
2.5%
47537 1
2.5%
40578 1
2.5%
25003 1
2.5%
18916 1
2.5%

말
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
39 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 39
97.5%
2 1
 
2.5%

Length

2024-04-17T23:22:04.147436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:04.221896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39
97.5%
2 1
 
2.5%

양
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
39 
17
 
1

Length

Max length2
Median length1
Mean length1.025
Min length1

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 39
97.5%
17 1
 
2.5%

Length

2024-04-17T23:22:04.308796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:04.386920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39
97.5%
17 1
 
2.5%

육계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3071291.6
Minimum0
Maximum26960781
Zeros28
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:04.478074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31386974.8
95-th percentile17536770
Maximum26960781
Range26960781
Interquartile range (IQR)1386974.8

Descriptive statistics

Standard deviation6481327.1
Coefficient of variation (CV)2.1102936
Kurtosis4.8983392
Mean3071291.6
Median Absolute Deviation (MAD)0
Skewness2.320796
Sum1.2285167 × 108
Variance4.2007601 × 1013
MonotonicityNot monotonic
2024-04-17T23:22:04.569033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 28
70.0%
5865968 1
 
2.5%
17423543 1
 
2.5%
6229610 1
 
2.5%
19688081 1
 
2.5%
97871 1
 
2.5%
406654 1
 
2.5%
8466738 1
 
2.5%
26960781 1
 
2.5%
4327937 1
 
2.5%
Other values (3) 3
 
7.5%
ValueCountFrequency (%)
0 28
70.0%
97871 1
 
2.5%
406654 1
 
2.5%
4327937 1
 
2.5%
4702848 1
 
2.5%
5865968 1
 
2.5%
6229610 1
 
2.5%
8466738 1
 
2.5%
13965639 1
 
2.5%
14715996 1
 
2.5%
ValueCountFrequency (%)
26960781 1
2.5%
19688081 1
2.5%
17423543 1
2.5%
14715996 1
2.5%
13965639 1
2.5%
8466738 1
2.5%
6229610 1
2.5%
5865968 1
2.5%
4702848 1
2.5%
4327937 1
2.5%

삼계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean664762.88
Minimum0
Maximum8727032
Zeros32
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:04.655895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4105730.4
Maximum8727032
Range8727032
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1844060.6
Coefficient of variation (CV)2.7740126
Kurtosis11.278705
Mean664762.88
Median Absolute Deviation (MAD)0
Skewness3.3316807
Sum26590515
Variance3.4005595 × 1012
MonotonicityNot monotonic
2024-04-17T23:22:04.740992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 32
80.0%
1507134 1
 
2.5%
6584897 1
 
2.5%
632528 1
 
2.5%
3975248 1
 
2.5%
1584941 1
 
2.5%
8727032 1
 
2.5%
488137 1
 
2.5%
3090598 1
 
2.5%
ValueCountFrequency (%)
0 32
80.0%
488137 1
 
2.5%
632528 1
 
2.5%
1507134 1
 
2.5%
1584941 1
 
2.5%
3090598 1
 
2.5%
3975248 1
 
2.5%
6584897 1
 
2.5%
8727032 1
 
2.5%
ValueCountFrequency (%)
8727032 1
 
2.5%
6584897 1
 
2.5%
3975248 1
 
2.5%
3090598 1
 
2.5%
1584941 1
 
2.5%
1507134 1
 
2.5%
632528 1
 
2.5%
488137 1
 
2.5%
0 32
80.0%

산란노계
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
38 
1065137
 
1
3658892
 
1

Length

Max length7
Median length1
Mean length1.3
Min length1

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
95.0%
1065137 1
 
2.5%
3658892 1
 
2.5%

Length

2024-04-17T23:22:04.844779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:04.936586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
95.0%
1065137 1
 
2.5%
3658892 1
 
2.5%

산란종계
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
38 
21364
 
2

Length

Max length5
Median length1
Mean length1.2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
95.0%
21364 2
 
5.0%

Length

2024-04-17T23:22:05.046066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:05.161656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
95.0%
21364 2
 
5.0%

육용종계
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
38 
118498
 
1
449905
 
1

Length

Max length6
Median length1
Mean length1.25
Min length1

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 38
95.0%
118498 1
 
2.5%
449905 1
 
2.5%

Length

2024-04-17T23:22:05.255724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:05.344754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 38
95.0%
118498 1
 
2.5%
449905 1
 
2.5%

겸용종(닭)
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
0
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 40
100.0%

Length

2024-04-17T23:22:05.426256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:22:05.501990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 40
100.0%

토종닭
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168506.85
Minimum0
Maximum1997286
Zeros28
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:05.576482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q316951
95-th percentile1090903.4
Maximum1997286
Range1997286
Interquartile range (IQR)16951

Descriptive statistics

Standard deviation449081.67
Coefficient of variation (CV)2.6650648
Kurtosis9.7098717
Mean168506.85
Median Absolute Deviation (MAD)0
Skewness3.1578637
Sum6740274
Variance2.0167435 × 1011
MonotonicityNot monotonic
2024-04-17T23:22:05.677254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 28
70.0%
196743 1
 
2.5%
1058446 1
 
2.5%
330103 1
 
2.5%
1707595 1
 
2.5%
385588 1
 
2.5%
1997286 1
 
2.5%
150337 1
 
2.5%
807688 1
 
2.5%
5824 1
 
2.5%
Other values (3) 3
 
7.5%
ValueCountFrequency (%)
0 28
70.0%
5824 1
 
2.5%
12072 1
 
2.5%
31588 1
 
2.5%
57004 1
 
2.5%
150337 1
 
2.5%
196743 1
 
2.5%
330103 1
 
2.5%
385588 1
 
2.5%
807688 1
 
2.5%
ValueCountFrequency (%)
1997286 1
2.5%
1707595 1
2.5%
1058446 1
2.5%
807688 1
2.5%
385588 1
2.5%
330103 1
2.5%
196743 1
2.5%
150337 1
2.5%
57004 1
2.5%
31588 1
2.5%

오리
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91934.05
Minimum0
Maximum1257079
Zeros34
Zeros (%)85.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-17T23:22:05.773000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile701809.6
Maximum1257079
Range1257079
Interquartile range (IQR)0

Descriptive statistics

Standard deviation265206.82
Coefficient of variation (CV)2.8847508
Kurtosis10.976913
Mean91934.05
Median Absolute Deviation (MAD)0
Skewness3.2954153
Sum3677362
Variance7.033466 × 1010
MonotonicityNot monotonic
2024-04-17T23:22:05.864134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 34
85.0%
205872 1
 
2.5%
692927 1
 
2.5%
391032 1
 
2.5%
1257079 1
 
2.5%
259873 1
 
2.5%
870579 1
 
2.5%
ValueCountFrequency (%)
0 34
85.0%
205872 1
 
2.5%
259873 1
 
2.5%
391032 1
 
2.5%
692927 1
 
2.5%
870579 1
 
2.5%
1257079 1
 
2.5%
ValueCountFrequency (%)
1257079 1
 
2.5%
870579 1
 
2.5%
692927 1
 
2.5%
391032 1
 
2.5%
259873 1
 
2.5%
205872 1
 
2.5%
0 34
85.0%

Interactions

2024-04-17T23:22:01.377540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:57.637078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.327202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.926565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.577171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.180571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.711617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.447264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:57.728535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.429687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.004589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.665794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.251631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.788661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.523719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:57.839598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.521795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.082326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.761214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.331548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.877894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.595968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:57.939286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.604493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.165834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.857539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.405876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.991227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.660611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.032263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.673475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.259492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.930455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.477577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.124464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.723044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.112839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.751425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.349373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.999261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.543508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.209683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.798604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.218906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:58.853173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:21:59.454311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.099089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:00.638083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:22:01.299970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T23:22:05.943924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도축장명축종한우젖소육우돼지말양육계삼계산란노계산란종계육용종계토종닭오리
도축장명1.0000.0000.4000.8750.9500.3800.1930.1930.4890.3870.3811.0000.3810.3870.460
축종0.0001.0000.0470.0000.0000.0000.0000.0000.4010.2480.0000.0000.0000.2480.000
한우0.4000.0471.0000.9120.9700.0001.0000.5420.0000.0000.0000.0000.0000.0000.000
젖소0.8750.0000.9121.0000.9300.0001.0000.5950.0000.0000.0000.0000.0000.0000.000
육우0.9500.0000.9700.9301.0000.0001.0000.3120.0000.0000.0000.0000.0000.0000.000
돼지0.3800.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
말0.1930.0001.0001.0001.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.000
양0.1930.0000.5420.5950.3120.0000.0001.0000.0000.0000.0000.0000.0000.0000.000
육계0.4890.4010.0000.0000.0000.0000.0000.0001.0000.9610.0000.0000.0000.8660.515
삼계0.3870.2480.0000.0000.0000.0000.0000.0000.9611.0000.0000.0000.0000.9770.402
산란노계0.3810.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0001.0000.0000.000
산란종계1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0001.0000.0000.000
육용종계0.3810.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0001.0000.0000.000
토종닭0.3870.2480.0000.0000.0000.0000.0000.0000.8660.9770.0000.0000.0001.0000.402
오리0.4600.0000.0000.0000.0000.0000.0000.0000.5150.4020.0000.0000.0000.4021.000
2024-04-17T23:22:06.077563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
말젖소산란노계육용종계축종양산란종계
말1.0000.9730.0000.0000.0000.0000.000
젖소0.9731.0000.0000.0000.0000.3970.000
산란노계0.0000.0001.0001.0000.0000.0000.987
육용종계0.0000.0001.0001.0000.0000.0000.987
축종0.0000.0000.0000.0001.0000.0000.000
양0.0000.3970.0000.0000.0001.0000.000
산란종계0.0000.0000.9870.9870.0000.0001.000
2024-04-17T23:22:06.176088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한우육우돼지육계삼계토종닭오리축종젖소말양산란노계산란종계육용종계
한우1.0000.9240.385-0.411-0.318-0.411-0.2680.0200.9080.9600.6280.0000.0000.000
육우0.9241.0000.349-0.366-0.283-0.366-0.2380.0000.9300.9730.2650.0000.0000.000
돼지0.3850.3491.000-0.502-0.388-0.502-0.3270.0000.0000.0000.0000.0000.0000.000
육계-0.411-0.366-0.5021.0000.8320.7720.0790.2690.0000.0000.0000.0000.0000.000
삼계-0.318-0.283-0.3880.8321.0000.5540.1490.1590.0000.0000.0000.0000.0000.000
토종닭-0.411-0.366-0.5020.7720.5541.0000.0700.1590.0000.0000.0000.0000.0000.000
오리-0.268-0.238-0.3270.0790.1490.0701.0000.0000.0000.0000.0000.0000.0000.000
축종0.0200.0000.0000.2690.1590.1590.0001.0000.0000.0000.0000.0000.0000.000
젖소0.9080.9300.0000.0000.0000.0000.0000.0001.0000.9730.3970.0000.0000.000
말0.9600.9730.0000.0000.0000.0000.0000.0000.9731.0000.0000.0000.0000.000
양0.6280.2650.0000.0000.0000.0000.0000.0000.3970.0001.0000.0000.0000.000
산란노계0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.9871.000
산란종계0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.9871.0000.987
육용종계0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.9871.000

Missing values

2024-04-17T23:22:01.931512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T23:22:02.162099image/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

도축장명축종한우젖소육우수입소돼지말양육계삼계산란노계산란종계육용종계겸용종(닭)토종닭오리
0(유)금돈당월39020189160000000000
1(유)금돈분기64020475370000000000
2(주)농협목우촌 김제육가공공장당월0000405780000000000
3(주)농협목우촌 김제육가공공장분기00001175440000000000
4(주)동우팜투테이블당월000000058659681507134000000
5(주)동우팜투테이블분기0000000174235436584897000000
6(주)복수당월248130162210000000000
7(주)복수분기522130569900000000000
8(주)부광산업당월1338118000000000000
9(주)부광산업분기30761915002000000000
도축장명축종한우젖소육우수입소돼지말양육계삼계산란노계산란종계육용종계겸용종(닭)토종닭오리
30농업회사법인(주)사조원 순동공장당월000000000000000
31농업회사법인(주)사조원 순동공장분기000000000000000
32농업회사법인산수들주식회사당월46312049190000000000
33농업회사법인산수들주식회사분기9111201450101700000000
34도드람김제에프엠씨당월0000632340000000000
35도드람김제에프엠씨분기00001834020000000000
36주식회사 싱그린에프에스당월0000000001065137213641184980120720
37주식회사 싱그린에프에스분기0000000003658892213644499050570040
38주식회사 정다운 익산공장당월00000000000000259873
39주식회사 정다운 익산공장분기00000000000000870579