Overview

Dataset statistics

Number of variables13
Number of observations4798
Missing cells0
Missing cells (%)0.0%
Duplicate rows167
Duplicate rows (%)3.5%
Total size in memory520.2 KiB
Average record size in memory111.0 B

Variable types

Categorical5
Text1
DateTime1
Numeric6

Dataset

Description국립종자원 정부보급종 정밀정선 현황에 대한 데이터로 정선일자, 소집단량, 투입량, 작업량, 소독할량, 미소독할량 용도 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15066327/fileData.do

Alerts

Dataset has 167 (3.5%) duplicate rowsDuplicates
지원명 is highly overall correlated with 부서명High correlation
부서명 is highly overall correlated with 지원명High correlation
투입량 is highly overall correlated with 1교대작업량 and 1 other fieldsHigh correlation
1교대작업량 is highly overall correlated with 투입량 and 1 other fieldsHigh correlation
소독할량 is highly overall correlated with 미소독할량High correlation
미소독할량 is highly overall correlated with 투입량 and 2 other fieldsHigh correlation
작물명 is highly overall correlated with 용도High correlation
용도 is highly overall correlated with 작물명High correlation
작물명 is highly imbalanced (57.0%)Imbalance
용도 is highly imbalanced (99.7%)Imbalance
2교대작업량 is highly skewed (γ1 = 23.28792603)Skewed
소집단량 has 57 (1.2%) zerosZeros
1교대작업량 has 57 (1.2%) zerosZeros
2교대작업량 has 4780 (99.6%) zerosZeros
소독할량 has 3910 (81.5%) zerosZeros
미소독할량 has 789 (16.4%) zerosZeros

Reproduction

Analysis started2023-12-12 08:38:26.453033
Analysis finished2023-12-12 08:38:32.601288
Duration6.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년산
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2022
1677 
2021
1609 
2020
1512 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2022 1677
35.0%
2021 1609
33.5%
2020 1512
31.5%

Length

2023-12-12T17:38:32.693123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:38:32.806619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 1677
35.0%
2021 1609
33.5%
2020 1512
31.5%

지원명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
전북지원
1049 
전남지원
1037 
경북지원
585 
충남지원
555 
경남지원
460 
Other values (3)
1112 

Length

Max length7
Median length4
Mean length4.2819925
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북지원 1049
21.9%
전남지원 1037
21.6%
경북지원 585
12.2%
충남지원 555
11.6%
경남지원 460
9.6%
경기종자관리소 451
9.4%
강원지원 399
 
8.3%
충북지원 262
 
5.5%

Length

2023-12-12T17:38:32.950337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:38:33.121123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북지원 1049
21.9%
전남지원 1037
21.6%
경북지원 585
12.2%
충남지원 555
11.6%
경남지원 460
9.6%
경기종자관리소 451
9.4%
강원지원 399
 
8.3%
충북지원 262
 
5.5%

부서명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
<NA>
2714 
함평
599 
정읍
532 
익산
515 
영암
438 

Length

Max length4
Median length4
Mean length3.1313047
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 2714
56.6%
함평 599
 
12.5%
정읍 532
 
11.1%
익산 515
 
10.7%
영암 438
 
9.1%

Length

2023-12-12T17:38:33.356402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:38:33.533715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2714
56.6%
함평 599
 
12.5%
정읍 532
 
11.1%
익산 515
 
10.7%
영암 438
 
9.1%

작물명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
벼
3552 
콩
595 
보리
 
307
밀
 
277
호밀
 
36
Other values (3)
 
31

Length

Max length6
Median length1
Mean length1.074406
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
벼 3552
74.0%
콩 595
 
12.4%
보리 307
 
6.4%
밀 277
 
5.8%
호밀 36
 
0.8%
팥 28
 
0.6%
보리(춘파) 2
 
< 0.1%
밀(비축) 1
 
< 0.1%

Length

2023-12-12T17:38:33.702071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:38:33.824990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
벼 3552
74.0%
콩 595
 
12.4%
보리 307
 
6.4%
밀 277
 
5.8%
호밀 36
 
0.8%
팥 28
 
0.6%
보리(춘파 2
 
< 0.1%
밀(비축 1
 
< 0.1%

품종명
Text

Distinct59
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
2023-12-12T17:38:34.078108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4581075
Min length2

Characters and Unicode

Total characters16592
Distinct characters78
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 row고시히카리
2nd row고시히카리
3rd row고시히카리
4th row고시히카리
5th row고시히카리
ValueCountFrequency (%)
신동진벼 602
 
12.5%
삼광벼 492
 
10.3%
새청무 381
 
7.9%
대원콩 345
 
7.2%
일품벼 313
 
6.5%
추청벼 254
 
5.3%
오대벼 192
 
4.0%
동진찰벼 181
 
3.8%
영호진미 176
 
3.7%
새일미벼 172
 
3.6%
Other values (49) 1690
35.2%
2023-12-12T17:38:34.606267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
벼 2671
 
16.1%
진 989
 
6.0%
동 783
 
4.7%
새 724
 
4.4%
청 643
 
3.9%
대 608
 
3.7%
신 602
 
3.6%
콩 595
 
3.6%
광 546
 
3.3%
일 510
 
3.1%
Other values (68) 7921
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16521
99.6%
Decimal Number 67
 
0.4%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
벼 2671
 
16.2%
진 989
 
6.0%
동 783
 
4.7%
새 724
 
4.4%
청 643
 
3.9%
대 608
 
3.7%
신 602
 
3.6%
콩 595
 
3.6%
광 546
 
3.3%
일 510
 
3.1%
Other values (65) 7850
47.5%
Decimal Number
ValueCountFrequency (%)
1 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16521
99.6%
Common 71
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
벼 2671
 
16.2%
진 989
 
6.0%
동 783
 
4.7%
새 724
 
4.4%
청 643
 
3.9%
대 608
 
3.7%
신 602
 
3.6%
콩 595
 
3.6%
광 546
 
3.3%
일 510
 
3.1%
Other values (65) 7850
47.5%
Common
ValueCountFrequency (%)
1 67
94.4%
( 2
 
2.8%
) 2
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16521
99.6%
ASCII 71
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
벼 2671
 
16.2%
진 989
 
6.0%
동 783
 
4.7%
새 724
 
4.4%
청 643
 
3.9%
대 608
 
3.7%
신 602
 
3.6%
콩 595
 
3.6%
광 546
 
3.3%
일 510
 
3.1%
Other values (65) 7850
47.5%
ASCII
ValueCountFrequency (%)
1 67
94.4%
( 2
 
2.8%
) 2
 
2.8%

정선일자2
Date

Distinct407
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
Minimum2020-08-14 00:00:00
Maximum2023-04-21 00:00:00
2023-12-12T17:38:34.808128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:34.981454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소집단량
Real number (ℝ)

ZEROS 

Distinct989
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14903.505
Minimum0
Maximum30380
Zeros57
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size42.3 KiB
2023-12-12T17:38:35.529337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1500
Q16655
median13930
Q323775
95-th percentile30000
Maximum30380
Range30380
Interquartile range (IQR)17120

Descriptive statistics

Standard deviation9516.8755
Coefficient of variation (CV)0.63856628
Kurtosis-1.2658608
Mean14903.505
Median Absolute Deviation (MAD)8070
Skewness0.20441714
Sum71507015
Variance90570919
MonotonicityNot monotonic
2023-12-12T17:38:35.695019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 564
 
11.8%
24000 166
 
3.5%
10000 139
 
2.9%
8000 126
 
2.6%
20000 116
 
2.4%
5000 99
 
2.1%
15000 94
 
2.0%
2000 93
 
1.9%
3000 93
 
1.9%
7000 79
 
1.6%
Other values (979) 3229
67.3%
ValueCountFrequency (%)
0 57
1.2%
15 1
 
< 0.1%
20 1
 
< 0.1%
60 1
 
< 0.1%
80 3
 
0.1%
100 4
 
0.1%
115 1
 
< 0.1%
120 1
 
< 0.1%
140 1
 
< 0.1%
160 4
 
0.1%
ValueCountFrequency (%)
30380 1
 
< 0.1%
30000 564
11.8%
29980 1
 
< 0.1%
29940 1
 
< 0.1%
29920 2
 
< 0.1%
29900 1
 
< 0.1%
29860 1
 
< 0.1%
29840 2
 
< 0.1%
29800 2
 
< 0.1%
29780 1
 
< 0.1%

투입량
Real number (ℝ)

HIGH CORRELATION 

Distinct2205
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37954.821
Minimum0
Maximum94734
Zeros15
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size42.3 KiB
2023-12-12T17:38:35.875148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7040
Q125831.25
median36685
Q346580
95-th percentile79105.3
Maximum94734
Range94734
Interquartile range (IQR)20748.75

Descriptive statistics

Standard deviation20576.393
Coefficient of variation (CV)0.54212858
Kurtosis0.0089374673
Mean37954.821
Median Absolute Deviation (MAD)10476
Skewness0.50105106
Sum1.8210723 × 108
Variance4.2338795 × 108
MonotonicityNot monotonic
2023-12-12T17:38:36.043099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
0.3%
9000 10
 
0.2%
12000 9
 
0.2%
15000 9
 
0.2%
7040 9
 
0.2%
37770 8
 
0.2%
41870 8
 
0.2%
10040 8
 
0.2%
34310 8
 
0.2%
9040 8
 
0.2%
Other values (2195) 4706
98.1%
ValueCountFrequency (%)
0 15
0.3%
31 1
 
< 0.1%
44 1
 
< 0.1%
49 1
 
< 0.1%
75 1
 
< 0.1%
89 1
 
< 0.1%
169 1
 
< 0.1%
174 1
 
< 0.1%
203 1
 
< 0.1%
222 1
 
< 0.1%
ValueCountFrequency (%)
94734 4
0.1%
94388 3
0.1%
94090 4
0.1%
93762 3
0.1%
93329 4
0.1%
91746 4
0.1%
91668 4
0.1%
91217 4
0.1%
90840 4
0.1%
90480 3
0.1%

1교대작업량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct903
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35206.658
Minimum0
Maximum91000
Zeros57
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size42.3 KiB
2023-12-12T17:38:36.172389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6400
Q123800
median33740
Q343540
95-th percentile75000
Maximum91000
Range91000
Interquartile range (IQR)19740

Descriptive statistics

Standard deviation19473.709
Coefficient of variation (CV)0.55312574
Kurtosis0.10445413
Mean35206.658
Median Absolute Deviation (MAD)9900
Skewness0.56722177
Sum1.6892154 × 108
Variance3.7922533 × 108
MonotonicityNot monotonic
2023-12-12T17:38:36.305911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40000 134
 
2.8%
30000 134
 
2.8%
60000 95
 
2.0%
32000 87
 
1.8%
35000 79
 
1.6%
28000 67
 
1.4%
50000 65
 
1.4%
70000 65
 
1.4%
9000 59
 
1.2%
36000 58
 
1.2%
Other values (893) 3955
82.4%
ValueCountFrequency (%)
0 57
1.2%
410 2
 
< 0.1%
750 1
 
< 0.1%
755 2
 
< 0.1%
865 1
 
< 0.1%
980 1
 
< 0.1%
1000 2
 
< 0.1%
1095 1
 
< 0.1%
1160 1
 
< 0.1%
1195 2
 
< 0.1%
ValueCountFrequency (%)
91000 4
 
0.1%
90000 10
0.2%
89000 4
 
0.1%
87000 8
0.2%
86000 3
 
0.1%
85200 4
 
0.1%
85000 19
0.4%
83400 4
 
0.1%
83200 8
0.2%
83000 8
0.2%

2교대작업량
Real number (ℝ)

SKEWED  ZEROS 

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.668195
Minimum0
Maximum14000
Zeros4780
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size42.3 KiB
2023-12-12T17:38:36.394408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum14000
Range14000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation440.23321
Coefficient of variation (CV)18.600202
Kurtosis621.47858
Mean23.668195
Median Absolute Deviation (MAD)0
Skewness23.287926
Sum113560
Variance193805.28
MonotonicityNot monotonic
2023-12-12T17:38:36.486205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 4780
99.6%
11000 2
 
< 0.1%
14000 2
 
< 0.1%
4300 2
 
< 0.1%
5320 2
 
< 0.1%
5000 2
 
< 0.1%
4345 2
 
< 0.1%
3200 2
 
< 0.1%
5820 2
 
< 0.1%
3795 2
 
< 0.1%
ValueCountFrequency (%)
0 4780
99.6%
3200 2
 
< 0.1%
3795 2
 
< 0.1%
4300 2
 
< 0.1%
4345 2
 
< 0.1%
5000 2
 
< 0.1%
5320 2
 
< 0.1%
5820 2
 
< 0.1%
11000 2
 
< 0.1%
14000 2
 
< 0.1%
ValueCountFrequency (%)
14000 2
 
< 0.1%
11000 2
 
< 0.1%
5820 2
 
< 0.1%
5320 2
 
< 0.1%
5000 2
 
< 0.1%
4345 2
 
< 0.1%
4300 2
 
< 0.1%
3795 2
 
< 0.1%
3200 2
 
< 0.1%
0 4780
99.6%

소독할량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct290
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4543.5348
Minimum0
Maximum91000
Zeros3910
Zeros (%)81.5%
Negative0
Negative (%)0.0%
Memory size42.3 KiB
2023-12-12T17:38:36.625133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile34289
Maximum91000
Range91000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13416.334
Coefficient of variation (CV)2.9528406
Kurtosis16.038307
Mean4543.5348
Median Absolute Deviation (MAD)0
Skewness3.8475527
Sum21799880
Variance1.7999801 × 108
MonotonicityNot monotonic
2023-12-12T17:38:36.759867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3910
81.5%
10000 36
 
0.8%
9000 36
 
0.8%
60000 33
 
0.7%
8000 30
 
0.6%
32000 20
 
0.4%
12000 17
 
0.4%
15000 16
 
0.3%
38000 15
 
0.3%
40000 15
 
0.3%
Other values (280) 670
 
14.0%
ValueCountFrequency (%)
0 3910
81.5%
410 2
 
< 0.1%
750 1
 
< 0.1%
755 2
 
< 0.1%
940 2
 
< 0.1%
980 1
 
< 0.1%
1195 2
 
< 0.1%
1205 1
 
< 0.1%
1230 1
 
< 0.1%
1300 2
 
< 0.1%
ValueCountFrequency (%)
91000 4
0.1%
90000 7
0.1%
89000 4
0.1%
87000 4
0.1%
85000 7
0.1%
83000 4
0.1%
82000 3
0.1%
80000 3
0.1%
77000 3
0.1%
75620 3
0.1%

미소독할량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct775
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30686.791
Minimum0
Maximum90000
Zeros789
Zeros (%)16.4%
Negative0
Negative (%)0.0%
Memory size42.3 KiB
2023-12-12T17:38:36.892838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112175
median32100
Q341200
95-th percentile73000
Maximum90000
Range90000
Interquartile range (IQR)29025

Descriptive statistics

Standard deviation21555.572
Coefficient of variation (CV)0.70243813
Kurtosis-0.28616883
Mean30686.791
Median Absolute Deviation (MAD)12000
Skewness0.3413613
Sum1.4723522 × 108
Variance4.646427 × 108
MonotonicityNot monotonic
2023-12-12T17:38:37.040498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 789
 
16.4%
30000 129
 
2.7%
40000 119
 
2.5%
35000 80
 
1.7%
32000 64
 
1.3%
60000 58
 
1.2%
28000 57
 
1.2%
50000 55
 
1.1%
70000 53
 
1.1%
36000 48
 
1.0%
Other values (765) 3346
69.7%
ValueCountFrequency (%)
0 789
16.4%
115 3
 
0.1%
530 2
 
< 0.1%
700 2
 
< 0.1%
780 2
 
< 0.1%
855 2
 
< 0.1%
865 1
 
< 0.1%
1000 2
 
< 0.1%
1095 1
 
< 0.1%
1160 1
 
< 0.1%
ValueCountFrequency (%)
90000 3
 
0.1%
87000 4
 
0.1%
86000 3
 
0.1%
85200 4
 
0.1%
85000 12
0.3%
83400 4
 
0.1%
83200 8
0.2%
83000 4
 
0.1%
82000 7
0.1%
81600 7
0.1%

용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
일반
4797 
비축
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반 4797
> 99.9%
비축 1
 
< 0.1%

Length

2023-12-12T17:38:37.149904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:38:37.251294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 4797
> 99.9%
비축 1
 
< 0.1%

Interactions

2023-12-12T17:38:31.471645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:27.871226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.575204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.289074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.901457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.690809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.591075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:27.999480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.712202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.416236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.013587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.814619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.704562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.114452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.836879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.506342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.135026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.947007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.815615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.224826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.932347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.594860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.274510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.097845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.953738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.345240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.073251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.706471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.413888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.246160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:32.070865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:28.446461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.181567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:29.803498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:30.539578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:38:31.368488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:38:37.333882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명부서명작물명품종명소집단량투입량1교대작업량2교대작업량소독할량미소독할량용도
년산1.0000.1030.0310.1420.4050.0700.2600.2960.1240.3080.2980.004
지원명0.1031.0001.0000.4010.9470.3420.6360.6320.0380.3580.6020.000
부서명0.0311.0001.0000.3690.8670.1370.3690.4140.0640.1430.4080.029
작물명0.1420.4010.3691.0000.9920.3260.5730.5650.1210.4140.5030.883
품종명0.4050.9470.8670.9921.0000.5080.8100.8100.4610.6590.7840.814
소집단량0.0700.3420.1370.3260.5081.0000.5930.5980.0490.3010.5190.030
투입량0.2600.6360.3690.5730.8100.5931.0000.9940.0970.7950.9780.015
1교대작업량0.2960.6320.4140.5650.8100.5980.9941.0000.1080.8230.9920.000
2교대작업량0.1240.0380.0640.1210.4610.0490.0970.1081.0000.1370.0890.000
소독할량0.3080.3580.1430.4140.6590.3010.7950.8230.1371.0000.5920.000
미소독할량0.2980.6020.4080.5030.7840.5190.9780.9920.0890.5921.0000.009
용도0.0040.0000.0290.8830.8140.0300.0150.0000.0000.0000.0091.000
2023-12-12T17:38:37.535869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년산지원명작물명부서명용도
년산1.0000.0650.0900.0300.006
지원명0.0651.0000.1441.0000.000
작물명0.0900.1441.0000.2620.706
부서명0.0301.0000.2621.0000.019
용도0.0060.0000.7060.0191.000
2023-12-12T17:38:37.724487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소집단량투입량1교대작업량2교대작업량소독할량미소독할량년산지원명부서명작물명용도
소집단량1.0000.4680.471-0.049-0.1400.3860.0410.1710.0820.1620.023
투입량0.4681.0000.995-0.066-0.2050.8100.1600.3690.2610.3180.011
1교대작업량0.4710.9951.000-0.085-0.1880.8050.1850.3660.2780.3120.000
2교대작업량-0.049-0.066-0.0851.0000.098-0.0560.0510.0210.0520.0670.000
소독할량-0.140-0.205-0.1880.0981.000-0.6360.1930.1790.1170.2120.000
미소독할량0.3860.8100.805-0.056-0.6361.0000.1870.3410.2740.2680.007
년산0.0410.1600.1850.0510.1930.1871.0000.0650.0300.0900.006
지원명0.1710.3690.3660.0210.1790.3410.0651.0001.0000.1440.000
부서명0.0820.2610.2780.0520.1170.2740.0301.0001.0000.2620.019
작물명0.1620.3180.3120.0670.2120.2680.0900.1440.2621.0000.706
용도0.0230.0110.0000.0000.0000.0070.0060.0000.0190.7061.000

Missing values

2023-12-12T17:38:32.274258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:38:32.516640image/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

년산지원명부서명작물명품종명정선일자2소집단량투입량1교대작업량2교대작업량소독할량미소독할량용도
02020경기종자관리소<NA>벼고시히카리2021-01-222400050993480000048000일반
12020경기종자관리소<NA>벼고시히카리2021-01-222400050993480000048000일반
22020경기종자관리소<NA>벼고시히카리2021-01-252400064862600000060000일반
32020경기종자관리소<NA>벼고시히카리2021-01-252400064862600000060000일반
42020경기종자관리소<NA>벼고시히카리2021-01-251200064862600000060000일반
52020경기종자관리소<NA>벼고시히카리2021-01-261200065318600000060000일반
62020경기종자관리소<NA>벼고시히카리2021-01-262400065318600000060000일반
72020경기종자관리소<NA>벼고시히카리2021-01-262400065318600000060000일반
82020경기종자관리소<NA>벼고시히카리2021-01-272400065650600000060000일반
92020경기종자관리소<NA>벼고시히카리2021-01-272400065650600000060000일반
년산지원명부서명작물명품종명정선일자2소집단량투입량1교대작업량2교대작업량소독할량미소독할량용도
47882022강원지원<NA>콩청아콩2023-03-27284030652840002840일반
47892022강원지원<NA>콩청아콩2023-03-23700070407000007000일반
47902022강원지원<NA>콩청아콩2023-03-24300070407000007000일반
47912022강원지원<NA>팥아라리팥2023-03-16850085808500008500일반
47922022강원지원<NA>팥아라리팥2023-03-17150097609700009700일반
47932022강원지원<NA>팥아라리팥2023-03-17820097609700009700일반
47942022강원지원<NA>팥아라리팥2023-03-20180088608800008800일반
47952022강원지원<NA>팥아라리팥2023-03-20700088608800008800일반
47962022강원지원<NA>팥아라리팥2023-03-21300052805195005195일반
47972022강원지원<NA>팥아라리팥2023-03-21219552805195005195일반

Duplicate rows

Most frequently occurring

년산지원명부서명작물명품종명정선일자2소집단량투입량1교대작업량2교대작업량소독할량미소독할량용도# duplicates
372020충남지원<NA>벼삼광벼2020-12-293000093762900000090000일반3
412020충남지원<NA>벼삼광벼2021-01-063000094388900000900000일반3
02020강원지원<NA>벼오대벼2020-12-241400029985280000028000일반2
12020경기종자관리소<NA>벼고시히카리2021-01-222400050993480000048000일반2
22020경기종자관리소<NA>벼고시히카리2021-01-252400064862600000060000일반2
32020경기종자관리소<NA>벼고시히카리2021-01-262400065318600000060000일반2
42020경기종자관리소<NA>벼고시히카리2021-01-272400065650600000060000일반2
52020경기종자관리소<NA>벼대안벼2021-02-192400062817600000600000일반2
62020경기종자관리소<NA>벼대안벼2021-02-222400063161600000600000일반2
72020경기종자관리소<NA>벼대안벼2021-02-232400062746600000600000일반2