Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows235
Duplicate rows (%)2.4%
Total size in memory1.5 MiB
Average record size in memory160.0 B

Variable types

Text1
Numeric16

Dataset

Description충청남도 내 소 사육농가 현황 정보(소재지, 주사육업종 등)충남도 내 한우, 육우, 젖소 사육농가 수 및 한우, 젖소, 육우 사육두수농가 호수 등
Author충청남도
URLhttps://www.data.go.kr/data/15040671/fileData.do

Alerts

Dataset has 235 (2.4%) duplicate rowsDuplicates
계(전체) is highly overall correlated with 암(전체) and 5 other fieldsHigh correlation
암(전체) is highly overall correlated with 계(전체) and 4 other fieldsHigh correlation
수(전체) is highly overall correlated with 계(전체) and 4 other fieldsHigh correlation
거세(전체) is highly overall correlated with 계(전체) and 1 other fieldsHigh correlation
기타(전체) is highly overall correlated with 기타(한우) and 1 other fieldsHigh correlation
계(한우) is highly overall correlated with 계(전체) and 5 other fieldsHigh correlation
암(한우) is highly overall correlated with 계(전체) and 4 other fieldsHigh correlation
수(한우) is highly overall correlated with 계(전체) and 4 other fieldsHigh correlation
거세(한우) is highly overall correlated with 거세(전체) and 1 other fieldsHigh correlation
기타(한우) is highly overall correlated with 기타(전체)High correlation
(젖소) is highly overall correlated with 계(육우) and 1 other fieldsHigh correlation
계(육우) is highly overall correlated with (젖소) and 3 other fieldsHigh correlation
수(육우) is highly overall correlated with (젖소) and 2 other fieldsHigh correlation
거세(육우) is highly overall correlated with 계(육우)High correlation
기타(육우) is highly overall correlated with 기타(전체) and 2 other fieldsHigh correlation
수(전체) is highly skewed (γ1 = 39.35064648)Skewed
수(한우) is highly skewed (γ1 = 44.63690485)Skewed
거세(한우) is highly skewed (γ1 = 20.20253422)Skewed
암(육우) is highly skewed (γ1 = 26.58589722)Skewed
거세(육우) is highly skewed (γ1 = 20.02164001)Skewed
기타(육우) is highly skewed (γ1 = 20.66210182)Skewed
암(전체) has 523 (5.2%) zerosZeros
수(전체) has 2546 (25.5%) zerosZeros
거세(전체) has 6720 (67.2%) zerosZeros
기타(전체) has 9048 (90.5%) zerosZeros
계(한우) has 583 (5.8%) zerosZeros
암(한우) has 1114 (11.1%) zerosZeros
수(한우) has 3063 (30.6%) zerosZeros
거세(한우) has 6951 (69.5%) zerosZeros
기타(한우) has 9312 (93.1%) zerosZeros
(젖소) has 9123 (91.2%) zerosZeros
계(육우) has 9079 (90.8%) zerosZeros
암(육우) has 9759 (97.6%) zerosZeros
수(육우) has 9253 (92.5%) zerosZeros
거세(육우) has 9642 (96.4%) zerosZeros
기타(육우) has 9716 (97.2%) zerosZeros

Reproduction

Analysis started2024-03-14 12:46:52.430035
Analysis finished2024-03-14 12:47:56.561901
Duration1 minute and 4.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct3078
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-14T21:47:57.725728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length16.9982
Min length15

Characters and Unicode

Total characters169982
Distinct characters433
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1566 ?
Unique (%)15.7%

Sample

1st row(지번) 충청남도 공주시 이인면
2nd row충청남도 예산군 신양면 예당남로
3rd row충청남도 천안시 동남구 풍세면
4th row(지번) 충청남도 아산시 둔포면
5th row충청남도 예산군 삽교읍 두리별리
ValueCountFrequency (%)
충청남도 10000
24.9%
지번 3195
 
8.0%
홍성군 1394
 
3.5%
공주시 1367
 
3.4%
예산군 1096
 
2.7%
부여군 864
 
2.2%
청양군 752
 
1.9%
서산시 729
 
1.8%
당진시 692
 
1.7%
논산시 652
 
1.6%
Other values (2891) 19363
48.3%
2024-03-14T21:47:59.286717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32759
19.3%
11082
 
6.5%
11034
 
6.5%
10302
 
6.1%
10233
 
6.0%
8430
 
5.0%
5215
 
3.1%
5051
 
3.0%
4896
 
2.9%
3490
 
2.1%
Other values (423) 67490
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128722
75.7%
Space Separator 32759
 
19.3%
Open Punctuation 3203
 
1.9%
Close Punctuation 3195
 
1.9%
Decimal Number 2045
 
1.2%
Dash Punctuation 56
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11082
 
8.6%
11034
 
8.6%
10302
 
8.0%
10233
 
7.9%
8430
 
6.5%
5215
 
4.1%
5051
 
3.9%
4896
 
3.8%
3490
 
2.7%
3200
 
2.5%
Other values (408) 55789
43.3%
Decimal Number
ValueCountFrequency (%)
1 670
32.8%
2 448
21.9%
3 233
 
11.4%
4 197
 
9.6%
5 136
 
6.7%
6 96
 
4.7%
8 89
 
4.4%
7 78
 
3.8%
9 70
 
3.4%
0 28
 
1.4%
Space Separator
ValueCountFrequency (%)
32759
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3203
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128722
75.7%
Common 41260
 
24.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11082
 
8.6%
11034
 
8.6%
10302
 
8.0%
10233
 
7.9%
8430
 
6.5%
5215
 
4.1%
5051
 
3.9%
4896
 
3.8%
3490
 
2.7%
3200
 
2.5%
Other values (408) 55789
43.3%
Common
ValueCountFrequency (%)
32759
79.4%
( 3203
 
7.8%
) 3195
 
7.7%
1 670
 
1.6%
2 448
 
1.1%
3 233
 
0.6%
4 197
 
0.5%
5 136
 
0.3%
6 96
 
0.2%
8 89
 
0.2%
Other values (5) 234
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128722
75.7%
ASCII 41260
 
24.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32759
79.4%
( 3203
 
7.8%
) 3195
 
7.7%
1 670
 
1.6%
2 448
 
1.1%
3 233
 
0.6%
4 197
 
0.5%
5 136
 
0.3%
6 96
 
0.2%
8 89
 
0.2%
Other values (5) 234
 
0.6%
Hangul
ValueCountFrequency (%)
11082
 
8.6%
11034
 
8.6%
10302
 
8.0%
10233
 
7.9%
8430
 
6.5%
5215
 
4.1%
5051
 
3.9%
4896
 
3.8%
3490
 
2.7%
3200
 
2.5%
Other values (408) 55789
43.3%

계(전체)
Real number (ℝ)

HIGH CORRELATION 

Distinct359
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.555
Minimum1
Maximum2873
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:47:59.540553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median20
Q350
95-th percentile154
Maximum2873
Range2872
Interquartile range (IQR)43

Descriptive statistics

Standard deviation75.849241
Coefficient of variation (CV)1.7823814
Kurtosis347.24225
Mean42.555
Median Absolute Deviation (MAD)16
Skewness12.517272
Sum425550
Variance5753.1073
MonotonicityNot monotonic
2024-03-14T21:47:59.792639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 478
 
4.8%
3 449
 
4.5%
4 391
 
3.9%
5 372
 
3.7%
6 359
 
3.6%
7 317
 
3.2%
1 299
 
3.0%
8 281
 
2.8%
10 256
 
2.6%
9 255
 
2.5%
Other values (349) 6543
65.4%
ValueCountFrequency (%)
1 299
3.0%
2 478
4.8%
3 449
4.5%
4 391
3.9%
5 372
3.7%
6 359
3.6%
7 317
3.2%
8 281
2.8%
9 255
2.5%
10 256
2.6%
ValueCountFrequency (%)
2873 1
< 0.1%
2525 1
< 0.1%
1441 1
< 0.1%
1229 1
< 0.1%
1189 1
< 0.1%
1113 1
< 0.1%
1102 1
< 0.1%
875 1
< 0.1%
754 1
< 0.1%
696 1
< 0.1%

암(전체)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct258
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.5468
Minimum0
Maximum1521
Zeros523
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:00.065723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median13
Q335
95-th percentile105
Maximum1521
Range1521
Interquartile range (IQR)30

Descriptive statistics

Standard deviation49.042876
Coefficient of variation (CV)1.7179816
Kurtosis211.68439
Mean28.5468
Median Absolute Deviation (MAD)11
Skewness10.114111
Sum285468
Variance2405.2037
MonotonicityNot monotonic
2024-03-14T21:48:00.508001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 571
 
5.7%
0 523
 
5.2%
3 486
 
4.9%
4 456
 
4.6%
1 424
 
4.2%
5 421
 
4.2%
6 385
 
3.9%
7 310
 
3.1%
8 301
 
3.0%
9 292
 
2.9%
Other values (248) 5831
58.3%
ValueCountFrequency (%)
0 523
5.2%
1 424
4.2%
2 571
5.7%
3 486
4.9%
4 456
4.6%
5 421
4.2%
6 385
3.9%
7 310
3.1%
8 301
3.0%
9 292
2.9%
ValueCountFrequency (%)
1521 1
< 0.1%
1300 1
< 0.1%
1108 1
< 0.1%
1030 1
< 0.1%
990 1
< 0.1%
953 1
< 0.1%
665 1
< 0.1%
596 1
< 0.1%
586 1
< 0.1%
553 1
< 0.1%

수(전체)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct115
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8835
Minimum0
Maximum1292
Zeros2546
Zeros (%)25.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:00.936453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q36
95-th percentile22
Maximum1292
Range1292
Interquartile range (IQR)6

Descriptive statistics

Standard deviation17.987298
Coefficient of variation (CV)3.0572445
Kurtosis2638.4459
Mean5.8835
Median Absolute Deviation (MAD)2
Skewness39.350646
Sum58835
Variance323.54288
MonotonicityNot monotonic
2024-03-14T21:48:01.574726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2546
25.5%
1 1628
16.3%
2 1143
11.4%
3 818
 
8.2%
4 591
 
5.9%
5 490
 
4.9%
6 390
 
3.9%
7 336
 
3.4%
8 255
 
2.5%
10 185
 
1.8%
Other values (105) 1618
16.2%
ValueCountFrequency (%)
0 2546
25.5%
1 1628
16.3%
2 1143
11.4%
3 818
 
8.2%
4 591
 
5.9%
5 490
 
4.9%
6 390
 
3.9%
7 336
 
3.4%
8 255
 
2.5%
9 181
 
1.8%
ValueCountFrequency (%)
1292 1
< 0.1%
303 1
< 0.1%
228 1
< 0.1%
207 1
< 0.1%
192 1
< 0.1%
191 1
< 0.1%
181 1
< 0.1%
179 1
< 0.1%
175 1
< 0.1%
169 1
< 0.1%

거세(전체)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9634
Minimum0
Maximum1438
Zeros6720
Zeros (%)67.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:01.982818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile39
Maximum1438
Range1438
Interquartile range (IQR)3

Descriptive statistics

Standard deviation33.980988
Coefficient of variation (CV)4.2671457
Kurtosis438.49643
Mean7.9634
Median Absolute Deviation (MAD)0
Skewness15.379203
Sum79634
Variance1154.7075
MonotonicityNot monotonic
2024-03-14T21:48:02.418446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6720
67.2%
1 406
 
4.1%
2 312
 
3.1%
3 220
 
2.2%
4 198
 
2.0%
5 173
 
1.7%
6 125
 
1.2%
7 107
 
1.1%
8 96
 
1.0%
10 93
 
0.9%
Other values (198) 1550
 
15.5%
ValueCountFrequency (%)
0 6720
67.2%
1 406
 
4.1%
2 312
 
3.1%
3 220
 
2.2%
4 198
 
2.0%
5 173
 
1.7%
6 125
 
1.2%
7 107
 
1.1%
8 96
 
1.0%
9 92
 
0.9%
ValueCountFrequency (%)
1438 1
< 0.1%
988 1
< 0.1%
647 1
< 0.1%
503 1
< 0.1%
475 1
< 0.1%
449 1
< 0.1%
446 1
< 0.1%
418 1
< 0.1%
405 1
< 0.1%
400 1
< 0.1%

기타(전체)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1613
Minimum0
Maximum28
Zeros9048
Zeros (%)90.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:02.786407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum28
Range28
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.78685718
Coefficient of variation (CV)4.8782218
Kurtosis300.651
Mean0.1613
Median Absolute Deviation (MAD)0
Skewness13.617443
Sum1613
Variance0.61914422
MonotonicityNot monotonic
2024-03-14T21:48:03.133120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 9048
90.5%
1 678
 
6.8%
2 156
 
1.6%
3 53
 
0.5%
4 24
 
0.2%
5 14
 
0.1%
7 6
 
0.1%
14 5
 
0.1%
9 4
 
< 0.1%
6 3
 
< 0.1%
Other values (7) 9
 
0.1%
ValueCountFrequency (%)
0 9048
90.5%
1 678
 
6.8%
2 156
 
1.6%
3 53
 
0.5%
4 24
 
0.2%
5 14
 
0.1%
6 3
 
< 0.1%
7 6
 
0.1%
8 1
 
< 0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
28 1
 
< 0.1%
19 1
 
< 0.1%
16 2
 
< 0.1%
14 5
0.1%
13 1
 
< 0.1%
11 2
 
< 0.1%
10 1
 
< 0.1%
9 4
< 0.1%
8 1
 
< 0.1%
7 6
0.1%

계(한우)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct322
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5053
Minimum0
Maximum2873
Zeros583
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:03.512071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median15
Q340
95-th percentile127
Maximum2873
Range2873
Interquartile range (IQR)35

Descriptive statistics

Standard deviation69.747263
Coefficient of variation (CV)2.0213493
Kurtosis484.70962
Mean34.5053
Median Absolute Deviation (MAD)12
Skewness15.404016
Sum345053
Variance4864.6806
MonotonicityNot monotonic
2024-03-14T21:48:03.940324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 583
 
5.8%
2 506
 
5.1%
3 467
 
4.7%
4 401
 
4.0%
5 372
 
3.7%
6 368
 
3.7%
1 339
 
3.4%
7 318
 
3.2%
8 290
 
2.9%
10 257
 
2.6%
Other values (312) 6099
61.0%
ValueCountFrequency (%)
0 583
5.8%
1 339
3.4%
2 506
5.1%
3 467
4.7%
4 401
4.0%
5 372
3.7%
6 368
3.7%
7 318
3.2%
8 290
2.9%
9 252
2.5%
ValueCountFrequency (%)
2873 1
< 0.1%
2525 1
< 0.1%
1441 1
< 0.1%
1229 1
< 0.1%
1188 1
< 0.1%
1102 1
< 0.1%
863 1
< 0.1%
754 1
< 0.1%
695 1
< 0.1%
674 1
< 0.1%

암(한우)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct231
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.7719
Minimum0
Maximum1521
Zeros1114
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:04.208156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median10
Q327
95-th percentile84
Maximum1521
Range1521
Interquartile range (IQR)24

Descriptive statistics

Standard deviation43.50522
Coefficient of variation (CV)1.9104783
Kurtosis308.41853
Mean22.7719
Median Absolute Deviation (MAD)9
Skewness12.556916
Sum227719
Variance1892.7041
MonotonicityNot monotonic
2024-03-14T21:48:04.456388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1114
 
11.1%
2 590
 
5.9%
3 497
 
5.0%
1 454
 
4.5%
4 451
 
4.5%
5 422
 
4.2%
6 383
 
3.8%
7 310
 
3.1%
8 299
 
3.0%
9 292
 
2.9%
Other values (221) 5188
51.9%
ValueCountFrequency (%)
0 1114
11.1%
1 454
4.5%
2 590
5.9%
3 497
5.0%
4 451
4.5%
5 422
 
4.2%
6 383
 
3.8%
7 310
 
3.1%
8 299
 
3.0%
9 292
 
2.9%
ValueCountFrequency (%)
1521 1
< 0.1%
1300 1
< 0.1%
1030 1
< 0.1%
989 1
< 0.1%
953 1
< 0.1%
655 1
< 0.1%
596 1
< 0.1%
586 1
< 0.1%
553 1
< 0.1%
519 1
< 0.1%

수(한우)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct109
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0518
Minimum0
Maximum1292
Zeros3063
Zeros (%)30.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:04.710411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q35
95-th percentile19
Maximum1292
Range1292
Interquartile range (IQR)5

Descriptive statistics

Standard deviation17.179745
Coefficient of variation (CV)3.4007175
Kurtosis3173.8315
Mean5.0518
Median Absolute Deviation (MAD)2
Skewness44.636905
Sum50518
Variance295.14363
MonotonicityNot monotonic
2024-03-14T21:48:05.155322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3063
30.6%
1 1625
16.2%
2 1128
 
11.3%
3 771
 
7.7%
4 567
 
5.7%
5 448
 
4.5%
6 354
 
3.5%
7 304
 
3.0%
8 240
 
2.4%
9 162
 
1.6%
Other values (99) 1338
13.4%
ValueCountFrequency (%)
0 3063
30.6%
1 1625
16.2%
2 1128
 
11.3%
3 771
 
7.7%
4 567
 
5.7%
5 448
 
4.5%
6 354
 
3.5%
7 304
 
3.0%
8 240
 
2.4%
9 162
 
1.6%
ValueCountFrequency (%)
1292 1
< 0.1%
303 1
< 0.1%
228 1
< 0.1%
192 1
< 0.1%
179 1
< 0.1%
175 1
< 0.1%
169 1
< 0.1%
167 1
< 0.1%
166 1
< 0.1%
160 1
< 0.1%

거세(한우)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct181
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5875
Minimum0
Maximum1438
Zeros6951
Zeros (%)69.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:05.561773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile34
Maximum1438
Range1438
Interquartile range (IQR)2

Descriptive statistics

Standard deviation29.19082
Coefficient of variation (CV)4.431244
Kurtosis751.09128
Mean6.5875
Median Absolute Deviation (MAD)0
Skewness20.202534
Sum65875
Variance852.10395
MonotonicityNot monotonic
2024-03-14T21:48:05.997977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6951
69.5%
1 363
 
3.6%
2 296
 
3.0%
3 214
 
2.1%
4 188
 
1.9%
5 167
 
1.7%
6 111
 
1.1%
7 98
 
1.0%
8 94
 
0.9%
10 87
 
0.9%
Other values (171) 1431
 
14.3%
ValueCountFrequency (%)
0 6951
69.5%
1 363
 
3.6%
2 296
 
3.0%
3 214
 
2.1%
4 188
 
1.9%
5 167
 
1.7%
6 111
 
1.1%
7 98
 
1.0%
8 94
 
0.9%
9 86
 
0.9%
ValueCountFrequency (%)
1438 1
< 0.1%
988 1
< 0.1%
475 1
< 0.1%
446 1
< 0.1%
405 1
< 0.1%
400 1
< 0.1%
396 1
< 0.1%
393 1
< 0.1%
363 1
< 0.1%
343 1
< 0.1%

기타(한우)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0941
Minimum0
Maximum16
Zeros9312
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:06.359235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.46504496
Coefficient of variation (CV)4.9420294
Kurtosis335.33822
Mean0.0941
Median Absolute Deviation (MAD)0
Skewness13.508771
Sum941
Variance0.21626682
MonotonicityNot monotonic
2024-03-14T21:48:06.721567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 9312
93.1%
1 548
 
5.5%
2 96
 
1.0%
3 23
 
0.2%
4 10
 
0.1%
5 5
 
0.1%
14 2
 
< 0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
0 9312
93.1%
1 548
 
5.5%
2 96
 
1.0%
3 23
 
0.2%
4 10
 
0.1%
5 5
 
0.1%
7 2
 
< 0.1%
9 1
 
< 0.1%
14 2
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
14 2
 
< 0.1%
9 1
 
< 0.1%
7 2
 
< 0.1%
5 5
 
0.1%
4 10
 
0.1%
3 23
 
0.2%
2 96
 
1.0%
1 548
 
5.5%
0 9312
93.1%

(젖소)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct187
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.6921
Minimum0
Maximum1096
Zeros9123
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:07.001524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile45
Maximum1096
Range1096
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26.963987
Coefficient of variation (CV)4.7370895
Kurtosis297.66989
Mean5.6921
Median Absolute Deviation (MAD)0
Skewness11.133391
Sum56921
Variance727.0566
MonotonicityNot monotonic
2024-03-14T21:48:07.371449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9123
91.2%
1 54
 
0.5%
2 32
 
0.3%
3 25
 
0.2%
10 17
 
0.2%
4 15
 
0.1%
5 14
 
0.1%
49 13
 
0.1%
6 12
 
0.1%
71 11
 
0.1%
Other values (177) 684
 
6.8%
ValueCountFrequency (%)
0 9123
91.2%
1 54
 
0.5%
2 32
 
0.3%
3 25
 
0.2%
4 15
 
0.1%
5 14
 
0.1%
6 12
 
0.1%
7 9
 
0.1%
8 7
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
1096 1
< 0.1%
398 1
< 0.1%
353 1
< 0.1%
301 1
< 0.1%
299 1
< 0.1%
287 1
< 0.1%
279 1
< 0.1%
272 1
< 0.1%
270 1
< 0.1%
263 1
< 0.1%

계(육우)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct124
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3576
Minimum0
Maximum667
Zeros9079
Zeros (%)90.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:07.778747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum667
Range667
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20.057656
Coefficient of variation (CV)8.5076585
Kurtosis347.56419
Mean2.3576
Median Absolute Deviation (MAD)0
Skewness16.679943
Sum23576
Variance402.30955
MonotonicityNot monotonic
2024-03-14T21:48:08.222087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9079
90.8%
1 110
 
1.1%
3 74
 
0.7%
2 71
 
0.7%
4 62
 
0.6%
5 55
 
0.5%
6 46
 
0.5%
7 42
 
0.4%
8 31
 
0.3%
12 26
 
0.3%
Other values (114) 404
 
4.0%
ValueCountFrequency (%)
0 9079
90.8%
1 110
 
1.1%
2 71
 
0.7%
3 74
 
0.7%
4 62
 
0.6%
5 55
 
0.5%
6 46
 
0.5%
7 42
 
0.4%
8 31
 
0.3%
9 26
 
0.3%
ValueCountFrequency (%)
667 1
< 0.1%
505 1
< 0.1%
470 1
< 0.1%
449 1
< 0.1%
392 1
< 0.1%
380 1
< 0.1%
372 1
< 0.1%
366 1
< 0.1%
350 1
< 0.1%
347 1
< 0.1%

암(육우)
Real number (ℝ)

SKEWED  ZEROS 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.083
Minimum0
Maximum44
Zeros9759
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:08.622348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum44
Range44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.98944879
Coefficient of variation (CV)11.92107
Kurtosis952.87545
Mean0.083
Median Absolute Deviation (MAD)0
Skewness26.585897
Sum830
Variance0.9790089
MonotonicityNot monotonic
2024-03-14T21:48:08.991301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 9759
97.6%
1 117
 
1.2%
2 37
 
0.4%
3 29
 
0.3%
4 14
 
0.1%
6 9
 
0.1%
5 7
 
0.1%
7 6
 
0.1%
9 3
 
< 0.1%
13 3
 
< 0.1%
Other values (13) 16
 
0.2%
ValueCountFrequency (%)
0 9759
97.6%
1 117
 
1.2%
2 37
 
0.4%
3 29
 
0.3%
4 14
 
0.1%
5 7
 
0.1%
6 9
 
0.1%
7 6
 
0.1%
8 2
 
< 0.1%
9 3
 
< 0.1%
ValueCountFrequency (%)
44 1
 
< 0.1%
43 1
 
< 0.1%
33 1
 
< 0.1%
22 1
 
< 0.1%
18 2
< 0.1%
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 1
 
< 0.1%
13 3
< 0.1%

수(육우)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct63
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8317
Minimum0
Maximum203
Zeros9253
Zeros (%)92.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:09.388162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum203
Range203
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.7978735
Coefficient of variation (CV)6.9711115
Kurtosis480.72353
Mean0.8317
Median Absolute Deviation (MAD)0
Skewness18.257006
Sum8317
Variance33.615337
MonotonicityNot monotonic
2024-03-14T21:48:09.962595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9253
92.5%
1 110
 
1.1%
3 72
 
0.7%
2 70
 
0.7%
5 59
 
0.6%
6 44
 
0.4%
4 43
 
0.4%
7 35
 
0.4%
8 31
 
0.3%
10 23
 
0.2%
Other values (53) 260
 
2.6%
ValueCountFrequency (%)
0 9253
92.5%
1 110
 
1.1%
2 70
 
0.7%
3 72
 
0.7%
4 43
 
0.4%
5 59
 
0.6%
6 44
 
0.4%
7 35
 
0.4%
8 31
 
0.3%
9 20
 
0.2%
ValueCountFrequency (%)
203 1
< 0.1%
191 1
< 0.1%
176 1
< 0.1%
160 1
< 0.1%
120 1
< 0.1%
115 1
< 0.1%
110 1
< 0.1%
106 1
< 0.1%
82 1
< 0.1%
80 1
< 0.1%

거세(육우)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct94
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3759
Minimum0
Maximum647
Zeros9642
Zeros (%)96.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:10.367746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum647
Range647
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17.447689
Coefficient of variation (CV)12.680928
Kurtosis488.34487
Mean1.3759
Median Absolute Deviation (MAD)0
Skewness20.02164
Sum13759
Variance304.42184
MonotonicityNot monotonic
2024-03-14T21:48:10.625000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9642
96.4%
1 85
 
0.9%
2 35
 
0.4%
3 24
 
0.2%
4 18
 
0.2%
5 17
 
0.2%
6 16
 
0.2%
10 6
 
0.1%
8 6
 
0.1%
9 6
 
0.1%
Other values (84) 145
 
1.5%
ValueCountFrequency (%)
0 9642
96.4%
1 85
 
0.9%
2 35
 
0.4%
3 24
 
0.2%
4 18
 
0.2%
5 17
 
0.2%
6 16
 
0.2%
7 5
 
0.1%
8 6
 
0.1%
9 6
 
0.1%
ValueCountFrequency (%)
647 1
< 0.1%
503 1
< 0.1%
449 1
< 0.1%
418 1
< 0.1%
392 1
< 0.1%
369 1
< 0.1%
366 1
< 0.1%
333 2
< 0.1%
300 1
< 0.1%
290 1
< 0.1%

기타(육우)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.067
Minimum0
Maximum28
Zeros9716
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-14T21:48:10.991318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum28
Range28
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.62269557
Coefficient of variation (CV)9.2939638
Kurtosis629.13016
Mean0.067
Median Absolute Deviation (MAD)0
Skewness20.662102
Sum670
Variance0.38774977
MonotonicityNot monotonic
2024-03-14T21:48:11.338234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 9716
97.2%
1 147
 
1.5%
2 71
 
0.7%
3 27
 
0.3%
4 11
 
0.1%
5 9
 
0.1%
6 3
 
< 0.1%
12 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
Other values (7) 10
 
0.1%
ValueCountFrequency (%)
0 9716
97.2%
1 147
 
1.5%
2 71
 
0.7%
3 27
 
0.3%
4 11
 
0.1%
5 9
 
0.1%
6 3
 
< 0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
28 1
< 0.1%
17 1
< 0.1%
16 1
< 0.1%
14 2
< 0.1%
12 2
< 0.1%
11 2
< 0.1%
10 1
< 0.1%
9 2
< 0.1%
8 2
< 0.1%
7 2
< 0.1%

Interactions

2024-03-14T21:47:51.852276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:54.727941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:58.698192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:03.064654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:06.794703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:09.752381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:12.645255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:15.875621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:19.351140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:23.825748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:27.396592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:31.349538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:35.442400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:39.619496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:43.817493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:47.707063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:52.117441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:54.994712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:58.970252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:03.522259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:06.971782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:09.985118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:13.082119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:16.045558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:19.619796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:24.106265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:27.644469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:31.614557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:35.614571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:39.876945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:44.095211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:48.062900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:52.386654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:55.272145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:59.247624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:03.799481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:07.144836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:10.152335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:13.254832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:16.222091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:19.890558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:24.324256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:27.928826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:31.883581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:35.923237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:40.142272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:44.374611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:48.236172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:52.648854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:55.542876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:59.518490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:04.099576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:07.315102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:10.330311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:13.510477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:16.389761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:20.155432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:24.492982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:28.200377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:32.147054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:36.224448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:40.401977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:44.649067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:48.401377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:52.919251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:55.843776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:59.793071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:04.378491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:07.577712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:10.498524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:13.684698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:16.569337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:20.425872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:24.666253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:28.480479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:32.419615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:36.499940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:40.669695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:44.927898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:48.635640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:53.173353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:56.087013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:00.061903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:04.642272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:07.756615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:10.654678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:13.846382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:16.733064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:20.690376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:24.835825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:28.748743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:32.679304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:36.767126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:40.920680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:45.199809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:48.895243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:53.440232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:56.302164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:00.333633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:04.916244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:07.925958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:10.816993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:14.012274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:16.932842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:20.955378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:25.106795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:29.030113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:32.944048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:37.039676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:41.178361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:45.372385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:49.162513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:53.708847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:56.477470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:00.612289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:05.189429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:08.102195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:11.053658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:14.184042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:17.163694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:21.224441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:25.386445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:29.213073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:33.215452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:37.317983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:41.448873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:45.552671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:49.433830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:53.971959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:56.643719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:00.880950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:05.353562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:08.270359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:11.233601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:14.351029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:17.337507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:21.488960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:25.656415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:29.384809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:33.480716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:37.586020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:41.709154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:45.723885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:49.702357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:54.239545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:56.819169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:01.157477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:05.526705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:08.446747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:11.406259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:14.555346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:17.515935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:21.761423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:25.930023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:29.565322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:33.748977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:37.815993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:41.976321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:45.903786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:49.976235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:54.519018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:57.093302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:01.442135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:05.706756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:08.715629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:11.581014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:14.793371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:17.725958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:22.042176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:26.213868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:29.747848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:34.023514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:38.006718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:42.249934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:46.088198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:50.257893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:54.772600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:57.355016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:01.706541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:05.865742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:08.879611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:11.738576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:14.951780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:17.991020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:22.298708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:26.482728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:29.984874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:34.276079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:38.268296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:42.507258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:46.336724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:50.517307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:55.043279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:57.627729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:01.984648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:06.036888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:09.055676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:11.907805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:15.126453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:18.276939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:22.572268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:26.711247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:30.263587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:34.551873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:38.543575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:42.787657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:46.615439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:50.789506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:55.291439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:57.884906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:02.241560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:06.233228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:09.216882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:12.059538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:15.280225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:18.535126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:22.833150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:26.870301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:30.523522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:34.751673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:38.800284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:43.034557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:46.876801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:51.045789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:55.570143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:58.169563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:02.525604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:06.459322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:09.399657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:12.323607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:15.460913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:18.816666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:23.116559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:27.057516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:30.807537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:34.928250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:39.083238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:43.306015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:47.157842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:51.326206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:55.783485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:46:58.437748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:02.799856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:06.626600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:09.571684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:12.490028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:15.626663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:19.087135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:23.381629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:27.229870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:31.083151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:35.088887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:39.354561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:43.566173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:47.434600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:47:51.591826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:48:11.604017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계(전체)암(전체)수(전체)거세(전체)기타(전체)계(한우)암(한우)수(한우)거세(한우)기타(한우)(젖소)계(육우)암(육우)수(육우)거세(육우)기타(육우)
계(전체)1.0000.9210.9280.8250.5430.9980.9740.9340.8310.8570.4770.3940.4210.2220.3660.270
암(전체)0.9211.0000.7910.6400.4260.9190.9830.8060.7090.7700.7700.1230.3480.2480.1200.139
수(전체)0.9280.7911.0000.1800.3790.9310.9270.9990.1910.5050.0000.1800.1790.3880.1070.289
거세(전체)0.8250.6400.1801.0000.2880.8010.6360.2050.9350.6360.0000.7710.0310.1840.7780.084
기타(전체)0.5430.4260.3790.2881.0000.5050.5610.2340.2930.8020.1470.4590.7990.6870.3490.989
계(한우)0.9980.9190.9310.8010.5051.0000.9820.9410.8380.8690.0000.0000.2340.0000.0000.000
암(한우)0.9740.9830.9270.6360.5610.9821.0000.9360.6630.8980.0000.0000.3330.0000.0000.000
수(한우)0.9340.8060.9990.2050.2340.9410.9361.0000.2190.5340.0000.0000.0810.0000.0000.000
거세(한우)0.8310.7090.1910.9350.2930.8380.6630.2191.0000.6630.0000.0000.0000.0000.0000.000
기타(한우)0.8570.7700.5050.6360.8020.8690.8980.5340.6631.0000.0000.0000.2490.0000.0000.098
(젖소)0.4770.7700.0000.0000.1470.0000.0000.0000.0000.0001.0000.1480.2620.4200.0000.185
계(육우)0.3940.1230.1800.7710.4590.0000.0000.0000.0000.0000.1481.0000.3110.7690.9750.510
암(육우)0.4210.3480.1790.0310.7990.2340.3330.0810.0000.2490.2620.3111.0000.2770.2330.832
수(육우)0.2220.2480.3880.1840.6870.0000.0000.0000.0000.0000.4200.7690.2771.0000.6070.709
거세(육우)0.3660.1200.1070.7780.3490.0000.0000.0000.0000.0000.0000.9750.2330.6071.0000.381
기타(육우)0.2700.1390.2890.0840.9890.0000.0000.0000.0000.0980.1850.5100.8320.7090.3811.000
2024-03-14T21:48:11.996695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계(전체)암(전체)수(전체)거세(전체)기타(전체)계(한우)암(한우)수(한우)거세(한우)기타(한우)(젖소)계(육우)암(육우)수(육우)거세(육우)기타(육우)
계(전체)1.0000.8590.7440.5100.3250.7370.6220.5930.4690.2530.2830.3030.1630.2900.1950.203
암(전체)0.8591.0000.6980.2260.2900.6320.7490.5650.2220.2410.3000.2420.1450.2700.0750.161
수(전체)0.7440.6981.0000.2590.2630.6000.5610.8710.2390.2140.1690.2040.1030.2480.1050.151
거세(전체)0.5100.2260.2591.0000.2070.4770.2360.2450.9520.194-0.0060.0940.0990.0220.2770.087
기타(전체)0.3250.2900.2630.2071.0000.1450.1330.1350.1510.8320.2300.2820.2000.2500.2230.540
계(한우)0.7370.6320.6000.4770.1451.0000.8820.7690.5470.284-0.347-0.306-0.092-0.321-0.131-0.158
암(한우)0.6220.7490.5610.2360.1330.8821.0000.7270.3000.270-0.338-0.310-0.097-0.317-0.148-0.161
수(한우)0.5930.5650.8710.2450.1350.7690.7271.0000.2900.235-0.222-0.201-0.053-0.204-0.092-0.106
거세(한우)0.4690.2220.2390.9520.1510.5470.3000.2901.0000.204-0.113-0.0700.012-0.1010.018-0.029
기타(한우)0.2530.2410.2140.1940.8320.2840.2700.2350.2041.000-0.027-0.0190.034-0.0340.0100.002
(젖소)0.2830.3000.169-0.0060.230-0.347-0.338-0.222-0.113-0.0271.0000.8190.3990.8440.3880.473
계(육우)0.3030.2420.2040.0940.282-0.306-0.310-0.201-0.070-0.0190.8191.0000.4990.8950.6240.553
암(육우)0.1630.1450.1030.0990.200-0.092-0.097-0.0530.0120.0340.3990.4991.0000.3860.3670.338
수(육우)0.2900.2700.2480.0220.250-0.321-0.317-0.204-0.101-0.0340.8440.8950.3861.0000.4320.514
거세(육우)0.1950.0750.1050.2770.223-0.131-0.148-0.0920.0180.0100.3880.6240.3670.4321.0000.412
기타(육우)0.2030.1610.1510.0870.540-0.158-0.161-0.106-0.0290.0020.4730.5530.3380.5140.4121.000

Missing values

2024-03-14T21:47:56.023693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:47:56.402444image/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

소재지계(전체)암(전체)수(전체)거세(전체)기타(전체)계(한우)암(한우)수(한우)거세(한우)기타(한우)(젖소)계(육우)암(육우)수(육우)거세(육우)기타(육우)
1086(지번) 충청남도 공주시 이인면18201601820160000000
8195충청남도 예산군 신양면 예당남로4220042200000000
8814충청남도 천안시 동남구 풍세면4330211043302110000000
6733(지번) 충청남도 아산시 둔포면65569006556900000000
7994충청남도 예산군 삽교읍 두리별리1621575000000015750500
10219충청남도 태안군 태안읍 지막골길3300033000000000
10921충청남도 홍성군 금마면 봉수산로44306804430680000000
2584충청남도 논산시 연산면 관창로14267165901426716590000000
1971충청남도 논산시 가야곡면 원앙종4400044000000000
11147(지번) 충청남도 홍성군 은하면8800088000000000
소재지계(전체)암(전체)수(전체)거세(전체)기타(전체)계(한우)암(한우)수(한우)거세(한우)기타(한우)(젖소)계(육우)암(육우)수(육우)거세(육우)기타(육우)
3737(지번) 충청남도 보령시 웅천읍40334214033421000000
10665충청남도 홍성군 구항면 내포로66757100067571000000000
4799(지번) 충청남도 부여군 은산면24186002418600000000
1979충청남도 논산시 광석면 갈산길150015000150015000000000
7965(지번) 충청남도 예산군 삽교읍17125001712500000000
6222(지번) 충청남도 서천군 마산면58535005853500000000
4892(지번) 충청남도 부여군 은산면22193002219300000000
8415(지번) 충청남도 예산군 오가면4523220045232200000000
9796충청남도 청양군 청남면 명덕로1100011000000000
8383(지번) 충청남도 예산군 오가면16142001614200000000

Duplicate rows

Most frequently occurring

소재지계(전체)암(전체)수(전체)거세(전체)기타(전체)계(한우)암(한우)수(한우)거세(한우)기타(한우)(젖소)계(육우)암(육우)수(육우)거세(육우)기타(육우)# duplicates
114(지번) 충청남도 청양군 장평면22000220000000005
25(지번) 충청남도 공주시 이인면55000550000000004
60(지번) 충청남도 부여군 은산면33000330000000004
100(지번) 충청남도 예산군 오가면22000220000000004
103(지번) 충청남도 청양군 남양면22000220000000004
224충청남도 홍성군 은하면 홍남로744000440000000004
7(지번) 충청남도 공주시 우성면21100211000000003
16(지번) 충청남도 공주시 유구읍22000220000000003
18(지번) 충청남도 공주시 유구읍44000440000000003
19(지번) 충청남도 공주시 유구읍55000550000000003