Overview

Dataset statistics

Number of variables6
Number of observations961
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.9 KiB
Average record size in memory52.1 B

Variable types

Numeric4
Categorical2

Dataset

Description축종별(소, 돼지, 말, 양, 닭, 오리) 평균 생체중량 현황
Author농림축산검역본부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220214000000001878

Alerts

LVSTCKSPC_CODE is highly overall correlated with PYEONGARMY and 3 other fieldsHigh correlation
LVSTCKSPC_NM is highly overall correlated with PYEONGARMY and 3 other fieldsHigh correlation
PYEONGARMY is highly overall correlated with CANCER and 3 other fieldsHigh correlation
CANCER is highly overall correlated with PYEONGARMY and 3 other fieldsHigh correlation
CO is highly overall correlated with PYEONGARMY and 3 other fieldsHigh correlation
PYEONGARMY has 60 (6.2%) zerosZeros
CANCER has 105 (10.9%) zerosZeros
CO has 184 (19.1%) zerosZeros

Reproduction

Analysis started2023-12-11 03:43:39.348274
Analysis finished2023-12-11 03:43:42.112838
Duration2.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

YM
Real number (ℝ)

Distinct121
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201253.27
Minimum200711
Maximum201712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2023-12-11T12:43:42.221053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200711
5-th percentile200806
Q1201004
median201301
Q3201508
95-th percentile201707
Maximum201712
Range1001
Interquartile range (IQR)504

Descriptive statistics

Standard deviation295.38491
Coefficient of variation (CV)0.0014677273
Kurtosis-1.3093668
Mean201253.27
Median Absolute Deviation (MAD)292
Skewness0.0074967338
Sum1.9340439 × 108
Variance87252.244
MonotonicityNot monotonic
2023-12-11T12:43:42.415316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200912 12
 
1.2%
201011 12
 
1.2%
200911 11
 
1.1%
201007 10
 
1.0%
201612 10
 
1.0%
200807 10
 
1.0%
201010 10
 
1.0%
201503 10
 
1.0%
201410 9
 
0.9%
201603 9
 
0.9%
Other values (111) 858
89.3%
ValueCountFrequency (%)
200711 1
 
0.1%
200801 8
0.8%
200802 9
0.9%
200803 8
0.8%
200804 8
0.8%
200805 8
0.8%
200806 8
0.8%
200807 10
1.0%
200808 9
0.9%
200809 7
0.7%
ValueCountFrequency (%)
201712 8
0.8%
201711 9
0.9%
201710 8
0.8%
201709 9
0.9%
201708 7
0.7%
201707 8
0.8%
201706 9
0.9%
201705 9
0.9%
201704 8
0.8%
201703 8
0.8%

LVSTCKSPC_NM
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
소
121 
산양
120 
말
120 
돼지
120 
사슴
104 
Other values (10)
376 

Length

Max length4
Median length2
Mean length1.8751301
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row산양
2nd row소
3rd row면양
4th row면양
5th row소

Common Values

ValueCountFrequency (%)
소 121
12.6%
산양 120
12.5%
말 120
12.5%
돼지 120
12.5%
사슴 104
10.8%
당나귀 82
8.5%
면양 65
6.8%
메추리 45
 
4.7%
오리 44
 
4.6%
타조 43
 
4.5%
Other values (5) 97
10.1%

Length

2023-12-11T12:43:42.576040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소 121
12.6%
산양 120
12.5%
말 120
12.5%
돼지 120
12.5%
사슴 104
10.8%
당나귀 82
8.5%
면양 65
6.8%
메추리 45
 
4.7%
오리 44
 
4.6%
타조 43
 
4.5%
Other values (5) 97
10.1%

LVSTCKSPC_CODE
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
LBI1000080
121 
LBI1000087
120 
LBI1000007
120 
LBI1000006
120 
LBI1000017
104 
Other values (10)
376 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowLBI1000087
2nd rowLBI1000080
3rd rowLBI1000086
4th rowLBI1000086
5th rowLBI1000080

Common Values

ValueCountFrequency (%)
LBI1000080 121
12.6%
LBI1000087 120
12.5%
LBI1000007 120
12.5%
LBI1000006 120
12.5%
LBI1000017 104
10.8%
LBI1000023 82
8.5%
LBI1000086 65
6.8%
LBI1000021 45
 
4.7%
LBI1000016 44
 
4.6%
LBI1000024 43
 
4.5%
Other values (5) 97
10.1%

Length

2023-12-11T12:43:42.718596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
lbi1000080 121
12.6%
lbi1000087 120
12.5%
lbi1000007 120
12.5%
lbi1000006 120
12.5%
lbi1000017 104
10.8%
lbi1000023 82
8.5%
lbi1000086 65
6.8%
lbi1000021 45
 
4.7%
lbi1000016 44
 
4.6%
lbi1000024 43
 
4.5%
Other values (5) 97
10.1%

PYEONGARMY
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct320
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207.57232
Minimum0
Maximum837
Zeros60
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2023-12-11T12:43:42.901463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q138
median121
Q3338
95-th percentile651
Maximum837
Range837
Interquartile range (IQR)300

Descriptive statistics

Standard deviation210.22397
Coefficient of variation (CV)1.0127746
Kurtosis-0.13799177
Mean207.57232
Median Absolute Deviation (MAD)119
Skewness1.0047108
Sum199477
Variance44194.118
MonotonicityNot monotonic
2023-12-11T12:43:43.092662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60
 
6.2%
2 57
 
5.9%
100 35
 
3.6%
3 26
 
2.7%
123 23
 
2.4%
1 20
 
2.1%
80 17
 
1.8%
39 16
 
1.7%
40 16
 
1.7%
120 14
 
1.5%
Other values (310) 677
70.4%
ValueCountFrequency (%)
0 60
6.2%
1 20
 
2.1%
2 57
5.9%
3 26
2.7%
10 1
 
0.1%
12 3
 
0.3%
15 2
 
0.2%
16 1
 
0.1%
20 1
 
0.1%
21 1
 
0.1%
ValueCountFrequency (%)
837 1
 
0.1%
694 1
 
0.1%
692 3
0.3%
690 1
 
0.1%
686 3
0.3%
684 1
 
0.1%
683 1
 
0.1%
680 1
 
0.1%
677 2
0.2%
676 2
0.2%

CANCER
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct302
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190.85328
Minimum0
Maximum623
Zeros105
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2023-12-11T12:43:43.283693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q127
median122
Q3324
95-th percentile583
Maximum623
Range623
Interquartile range (IQR)297

Descriptive statistics

Standard deviation196.42832
Coefficient of variation (CV)1.0292111
Kurtosis-0.52362529
Mean190.85328
Median Absolute Deviation (MAD)120
Skewness0.87471354
Sum183410
Variance38584.084
MonotonicityNot monotonic
2023-12-11T12:43:43.784382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 105
 
10.9%
2 56
 
5.8%
1 33
 
3.4%
100 30
 
3.1%
3 27
 
2.8%
80 20
 
2.1%
118 15
 
1.6%
42 15
 
1.6%
129 14
 
1.5%
200 11
 
1.1%
Other values (292) 635
66.1%
ValueCountFrequency (%)
0 105
10.9%
1 33
 
3.4%
2 56
5.8%
3 27
 
2.8%
9 1
 
0.1%
12 1
 
0.1%
15 2
 
0.2%
16 1
 
0.1%
17 2
 
0.2%
20 1
 
0.1%
ValueCountFrequency (%)
623 1
 
0.1%
622 2
0.2%
621 2
0.2%
620 1
 
0.1%
619 2
0.2%
616 1
 
0.1%
613 1
 
0.1%
612 1
 
0.1%
610 1
 
0.1%
609 3
0.3%

CO
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct262
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.79396
Minimum0
Maximum2001
Zeros184
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size8.6 KiB
2023-12-11T12:43:43.985478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median100
Q3340
95-th percentile665
Maximum2001
Range2001
Interquartile range (IQR)338

Descriptive statistics

Standard deviation230.316
Coefficient of variation (CV)1.2199331
Kurtosis3.5741568
Mean188.79396
Median Absolute Deviation (MAD)100
Skewness1.494666
Sum181431
Variance53045.46
MonotonicityNot monotonic
2023-12-11T12:43:44.183205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 184
 
19.1%
2 55
 
5.7%
100 32
 
3.3%
3 27
 
2.8%
117 27
 
2.8%
116 22
 
2.3%
36 19
 
2.0%
37 17
 
1.8%
35 15
 
1.6%
115 15
 
1.6%
Other values (252) 548
57.0%
ValueCountFrequency (%)
0 184
19.1%
1 14
 
1.5%
2 55
 
5.7%
3 27
 
2.8%
7 1
 
0.1%
11 1
 
0.1%
12 3
 
0.3%
13 1
 
0.1%
15 2
 
0.2%
19 2
 
0.2%
ValueCountFrequency (%)
2001 1
0.1%
738 1
0.1%
737 1
0.1%
730 1
0.1%
726 1
0.1%
723 1
0.1%
720 1
0.1%
719 1
0.1%
718 1
0.1%
713 1
0.1%

Interactions

2023-12-11T12:43:41.350411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:39.725848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.243314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.790232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:41.479382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:39.844222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.354764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.934493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:41.612510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:39.944112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.487585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:41.064842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:41.746186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.093406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:40.623489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:43:41.199637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:43:44.298634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
YMLVSTCKSPC_NMLVSTCKSPC_CODEPYEONGARMYCANCERCO
YM1.0000.4370.4370.3920.4720.212
LVSTCKSPC_NM0.4371.0001.0000.9030.9030.928
LVSTCKSPC_CODE0.4371.0001.0000.9030.9030.928
PYEONGARMY0.3920.9030.9031.0000.9600.996
CANCER0.4720.9030.9030.9601.0000.947
CO0.2120.9280.9280.9960.9471.000
2023-12-11T12:43:44.436116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
LVSTCKSPC_CODELVSTCKSPC_NM
LVSTCKSPC_CODE1.0001.000
LVSTCKSPC_NM1.0001.000
2023-12-11T12:43:44.556797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
YMPYEONGARMYCANCERCOLVSTCKSPC_NMLVSTCKSPC_CODE
YM1.0000.0760.0900.0680.1780.178
PYEONGARMY0.0761.0000.9310.7900.6190.619
CANCER0.0900.9311.0000.7160.6170.617
CO0.0680.7900.7161.0000.6600.660
LVSTCKSPC_NM0.1780.6190.6170.6601.0001.000
LVSTCKSPC_CODE0.1780.6190.6170.6601.0001.000

Missing values

2023-12-11T12:43:41.942839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:43:42.064564image/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

YMLVSTCKSPC_NMLVSTCKSPC_CODEPYEONGARMYCANCERCO
0201302산양LBI1000087454240
1201302소LBI1000080628572650
2201302면양LBI100008690900
3201303면양LBI1000086909090
4201303소LBI1000080636574662
5201303말LBI1000007391393378
6201303사슴LBI10000172052050
7201303산양LBI1000087433942
8201303돼지LBI1000006121126117
9201303당나귀LBI1000023229248200
YMLVSTCKSPC_NMLVSTCKSPC_CODEPYEONGARMYCANCERCO
951201110말LBI1000007373367373
952201110돼지LBI1000006119121118
953201110면양LBI1000086707070
954201110소LBI1000080654576664
955201712토끼LBI1000018222
956201712소LBI1000080692622737
957201712돼지LBI1000006123130115
958201712면양LBI10000861000100
959201712말LBI1000007450440441
960201712메추리LBI1000021000