Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory947.3 KiB
Average record size in memory97.0 B

Variable types

Numeric7
Categorical2
DateTime1

Dataset

Description2021년 공공데이터 기업매칭지원사업을 통해 수집한 제주 지역 내 고품질 감귤 농가의 주별과실당도데이터입니다. 데이터 항목별 설명은 다음과 같습니다. 대상 ID, id(당도키), fm_id(농가키), fc_researched_month(측정월), fc_researched_week(측정주), fc_researched_at(측정일), fc_rfid_no(과수번호), fc_brix(평균당도), fc_size(평균크기)
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15097172/fileData.do

Alerts

구분 is highly overall correlated with 대상 아이디 and 2 other fieldsHigh correlation
대상 아이디 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
아이디 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
평균크기 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
구분 has unique valuesUnique
대상 아이디 has unique valuesUnique
아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:09:39.934173
Analysis finished2023-12-12 15:09:48.892505
Duration8.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6932.5928
Minimum1
Maximum13915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:49.320574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile658.95
Q13410.75
median6894.5
Q310453.25
95-th percentile13215.05
Maximum13915
Range13914
Interquartile range (IQR)7042.5

Descriptive statistics

Standard deviation4042.1314
Coefficient of variation (CV)0.58306199
Kurtosis-1.2098407
Mean6932.5928
Median Absolute Deviation (MAD)3519.5
Skewness0.0092427895
Sum69325928
Variance16338826
MonotonicityNot monotonic
2023-12-13T00:09:49.488220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
777 1
 
< 0.1%
10332 1
 
< 0.1%
5216 1
 
< 0.1%
3370 1
 
< 0.1%
11041 1
 
< 0.1%
9183 1
 
< 0.1%
13009 1
 
< 0.1%
6833 1
 
< 0.1%
4290 1
 
< 0.1%
3829 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
ValueCountFrequency (%)
13915 1
< 0.1%
13914 1
< 0.1%
13913 1
< 0.1%
13912 1
< 0.1%
13911 1
< 0.1%
13910 1
< 0.1%
13909 1
< 0.1%
13908 1
< 0.1%
13906 1
< 0.1%
13905 1
< 0.1%

대상 아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3404069 × 109
Minimum1.3404 × 109
Maximum1.3404139 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:49.627099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3404 × 109
5-th percentile1.3404007 × 109
Q11.3404034 × 109
median1.3404069 × 109
Q31.3404105 × 109
95-th percentile1.3404132 × 109
Maximum1.3404139 × 109
Range13914
Interquartile range (IQR)7042.5

Descriptive statistics

Standard deviation4042.1314
Coefficient of variation (CV)3.0156002 × 10-6
Kurtosis-1.2098407
Mean1.3404069 × 109
Median Absolute Deviation (MAD)3519.5
Skewness0.0092427895
Sum1.3404069 × 1013
Variance16338826
MonotonicityNot monotonic
2023-12-13T00:09:49.813815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1340400777 1
 
< 0.1%
1340410332 1
 
< 0.1%
1340405216 1
 
< 0.1%
1340403370 1
 
< 0.1%
1340411041 1
 
< 0.1%
1340409183 1
 
< 0.1%
1340413009 1
 
< 0.1%
1340406833 1
 
< 0.1%
1340404290 1
 
< 0.1%
1340403829 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1340400001 1
< 0.1%
1340400002 1
< 0.1%
1340400004 1
< 0.1%
1340400008 1
< 0.1%
1340400009 1
< 0.1%
1340400011 1
< 0.1%
1340400012 1
< 0.1%
1340400013 1
< 0.1%
1340400014 1
< 0.1%
1340400015 1
< 0.1%
ValueCountFrequency (%)
1340413915 1
< 0.1%
1340413914 1
< 0.1%
1340413913 1
< 0.1%
1340413912 1
< 0.1%
1340413911 1
< 0.1%
1340413910 1
< 0.1%
1340413909 1
< 0.1%
1340413908 1
< 0.1%
1340413906 1
< 0.1%
1340413905 1
< 0.1%

아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6932.5928
Minimum1
Maximum13915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:49.997223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile658.95
Q13410.75
median6894.5
Q310453.25
95-th percentile13215.05
Maximum13915
Range13914
Interquartile range (IQR)7042.5

Descriptive statistics

Standard deviation4042.1314
Coefficient of variation (CV)0.58306199
Kurtosis-1.2098407
Mean6932.5928
Median Absolute Deviation (MAD)3519.5
Skewness0.0092427895
Sum69325928
Variance16338826
MonotonicityNot monotonic
2023-12-13T00:09:50.206903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
777 1
 
< 0.1%
10332 1
 
< 0.1%
5216 1
 
< 0.1%
3370 1
 
< 0.1%
11041 1
 
< 0.1%
9183 1
 
< 0.1%
13009 1
 
< 0.1%
6833 1
 
< 0.1%
4290 1
 
< 0.1%
3829 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
4 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
ValueCountFrequency (%)
13915 1
< 0.1%
13914 1
< 0.1%
13913 1
< 0.1%
13912 1
< 0.1%
13911 1
< 0.1%
13910 1
< 0.1%
13909 1
< 0.1%
13908 1
< 0.1%
13906 1
< 0.1%
13905 1
< 0.1%

농가키
Real number (ℝ)

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5275
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:50.366655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median14
Q323
95-th percentile28
Maximum30
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation8.8611904
Coefficient of variation (CV)0.60995976
Kurtosis-1.2624241
Mean14.5275
Median Absolute Deviation (MAD)8
Skewness0.093438455
Sum145275
Variance78.520696
MonotonicityNot monotonic
2023-12-13T00:09:50.535712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3 518
 
5.2%
2 455
 
4.5%
1 453
 
4.5%
6 437
 
4.4%
20 436
 
4.4%
7 431
 
4.3%
25 431
 
4.3%
27 425
 
4.2%
18 423
 
4.2%
11 422
 
4.2%
Other values (18) 5569
55.7%
ValueCountFrequency (%)
1 453
4.5%
2 455
4.5%
3 518
5.2%
4 295
2.9%
5 377
3.8%
6 437
4.4%
7 431
4.3%
8 419
4.2%
9 273
2.7%
11 422
4.2%
ValueCountFrequency (%)
30 218
2.2%
29 279
2.8%
28 354
3.5%
27 425
4.2%
26 149
 
1.5%
25 431
4.3%
24 326
3.3%
23 347
3.5%
21 338
3.4%
20 436
4.4%

측정월
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
11
6272 
10
3507 
12
 
150
9
 
71

Length

Max length2
Median length2
Mean length1.9929
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row11
3rd row10
4th row11
5th row12

Common Values

ValueCountFrequency (%)
11 6272
62.7%
10 3507
35.1%
12 150
 
1.5%
9 71
 
0.7%

Length

2023-12-13T00:09:50.715605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:50.858042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 6272
62.7%
10 3507
35.1%
12 150
 
1.5%
9 71
 
0.7%

측정주
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
2718 
1
2200 
3
2032 
5
1945 
2
1105 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row2
3rd row4
4th row3
5th row1

Common Values

ValueCountFrequency (%)
4 2718
27.2%
1 2200
22.0%
3 2032
20.3%
5 1945
19.4%
2 1105
11.1%

Length

2023-12-13T00:09:51.009532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:09:51.130161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 2718
27.2%
1 2200
22.0%
3 2032
20.3%
5 1945
19.4%
2 1105
11.1%

측정일
Date

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-09-27 00:00:00
Maximum2021-12-01 00:00:00
2023-12-13T00:09:51.291660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:51.476410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

과수번호
Real number (ℝ)

Distinct100
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5565
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:51.661691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q126
median51
Q375
95-th percentile96
Maximum100
Range99
Interquartile range (IQR)49

Descriptive statistics

Standard deviation28.792692
Coefficient of variation (CV)0.56951514
Kurtosis-1.1952005
Mean50.5565
Median Absolute Deviation (MAD)25
Skewness-0.0038966127
Sum505565
Variance829.01911
MonotonicityNot monotonic
2023-12-13T00:09:51.868979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29 110
 
1.1%
37 110
 
1.1%
72 110
 
1.1%
99 109
 
1.1%
79 108
 
1.1%
54 108
 
1.1%
97 108
 
1.1%
27 108
 
1.1%
70 108
 
1.1%
87 108
 
1.1%
Other values (90) 8913
89.1%
ValueCountFrequency (%)
1 101
1.0%
2 100
1.0%
3 97
1.0%
4 102
1.0%
5 93
0.9%
6 91
0.9%
7 98
1.0%
8 104
1.0%
9 101
1.0%
10 95
0.9%
ValueCountFrequency (%)
100 89
0.9%
99 109
1.1%
98 104
1.0%
97 108
1.1%
96 107
1.1%
95 98
1.0%
94 91
0.9%
93 94
0.9%
92 94
0.9%
91 98
1.0%

평균당도
Real number (ℝ)

Distinct613
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.849476
Minimum0
Maximum15.94
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:52.094432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.98
Q19.96
median10.73
Q311.67
95-th percentile13.08
Maximum15.94
Range15.94
Interquartile range (IQR)1.71

Descriptive statistics

Standard deviation1.2523174
Coefficient of variation (CV)0.11542654
Kurtosis0.54579239
Mean10.849476
Median Absolute Deviation (MAD)0.85
Skewness0.33133522
Sum108494.76
Variance1.568299
MonotonicityNot monotonic
2023-12-13T00:09:52.246642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.57 48
 
0.5%
10.39 48
 
0.5%
10.08 48
 
0.5%
10.36 47
 
0.5%
10.4 46
 
0.5%
10.41 45
 
0.4%
10.42 45
 
0.4%
10.37 44
 
0.4%
10.38 44
 
0.4%
10.2 43
 
0.4%
Other values (603) 9542
95.4%
ValueCountFrequency (%)
0.0 1
< 0.1%
6.63 1
< 0.1%
7.08 1
< 0.1%
7.17 1
< 0.1%
7.3 1
< 0.1%
7.33 1
< 0.1%
7.44 1
< 0.1%
7.48 1
< 0.1%
7.5 1
< 0.1%
7.54 1
< 0.1%
ValueCountFrequency (%)
15.94 1
 
< 0.1%
15.82 2
< 0.1%
15.71 1
 
< 0.1%
15.66 1
 
< 0.1%
15.58 1
 
< 0.1%
15.51 3
< 0.1%
15.44 1
 
< 0.1%
15.34 1
 
< 0.1%
15.32 2
< 0.1%
15.1 1
 
< 0.1%

평균크기
Real number (ℝ)

HIGH CORRELATION 

Distinct2898
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.562496
Minimum39.59
Maximum77.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:09:52.435737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39.59
5-th percentile42.81
Q152.74
median58.66
Q363.21
95-th percentile68.6405
Maximum77.55
Range37.96
Interquartile range (IQR)10.47

Descriptive statistics

Standard deviation7.6970236
Coefficient of variation (CV)0.13371595
Kurtosis-0.51803646
Mean57.562496
Median Absolute Deviation (MAD)5.125
Skewness-0.3831116
Sum575624.96
Variance59.244173
MonotonicityNot monotonic
2023-12-13T00:09:52.628170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61.03 15
 
0.1%
60.81 14
 
0.1%
62.13 13
 
0.1%
59.45 13
 
0.1%
62.39 12
 
0.1%
58.4 12
 
0.1%
60.56 12
 
0.1%
59.21 12
 
0.1%
58.7 12
 
0.1%
63.08 12
 
0.1%
Other values (2888) 9873
98.7%
ValueCountFrequency (%)
39.59 1
< 0.1%
39.81 1
< 0.1%
39.97 1
< 0.1%
40.1 1
< 0.1%
40.19 1
< 0.1%
40.22 1
< 0.1%
40.3 1
< 0.1%
40.38 1
< 0.1%
40.55 1
< 0.1%
40.61 1
< 0.1%
ValueCountFrequency (%)
77.55 1
< 0.1%
77.5 1
< 0.1%
77.05 1
< 0.1%
76.98 1
< 0.1%
76.93 1
< 0.1%
76.91 1
< 0.1%
76.53 1
< 0.1%
76.5 1
< 0.1%
76.37 1
< 0.1%
76.08 1
< 0.1%

Interactions

2023-12-13T00:09:47.374849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:41.744220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.766163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.701919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.555373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:45.589567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.455425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:47.507169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:41.885150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.918674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.834005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.661137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:45.725841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.632534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:47.643271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.037783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.063228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.949909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.801168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:45.858932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.773186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:47.821002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.181743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.194243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.053751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.959071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.009763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.892867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:48.010606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.305332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.324712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.156384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:45.108703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.117662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:47.017368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:48.146088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.447928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.450534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.269998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:45.248322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.223600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:47.130734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:48.338566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:42.600100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:43.580040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:44.427718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:45.424332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:46.356632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:09:47.263653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:09:52.775690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대상 아이디아이디농가키측정월측정주측정일과수번호평균당도평균크기
구분1.0001.0001.0000.9110.3820.3030.8240.0000.2360.700
대상 아이디1.0001.0001.0000.9110.3820.3030.8240.0000.2360.700
아이디1.0001.0001.0000.9110.3820.3030.8240.0000.2360.700
농가키0.9110.9110.9111.0000.3790.3270.8420.0000.3110.594
측정월0.3820.3820.3820.3791.0000.4701.0000.0000.2650.242
측정주0.3030.3030.3030.3270.4701.0001.0000.0000.1340.270
측정일0.8240.8240.8240.8421.0001.0001.0000.0000.4670.607
과수번호0.0000.0000.0000.0000.0000.0000.0001.0000.0880.000
평균당도0.2360.2360.2360.3110.2650.1340.4670.0881.0000.184
평균크기0.7000.7000.7000.5940.2420.2700.6070.0000.1841.000
2023-12-13T00:09:52.926913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정월측정주
측정월1.0000.400
측정주0.4001.000
2023-12-13T00:09:53.049595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대상 아이디아이디농가키과수번호평균당도평균크기측정월측정주
구분1.0001.0001.0000.236-0.0040.082-0.6380.2370.130
대상 아이디1.0001.0001.0000.236-0.0040.082-0.6380.2370.130
아이디1.0001.0001.0000.236-0.0040.082-0.6380.2370.130
농가키0.2360.2360.2361.0000.0010.0430.0750.2350.142
과수번호-0.004-0.004-0.0040.0011.000-0.0970.0230.0000.000
평균당도0.0820.0820.0820.043-0.0971.000-0.1710.1850.086
평균크기-0.638-0.638-0.6380.0750.023-0.1711.0000.1470.115
측정월0.2370.2370.2370.2350.0000.1850.1471.0000.400
측정주0.1300.1300.1300.1420.0000.0860.1150.4001.000

Missing values

2023-12-13T00:09:48.596996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:09:48.819533image/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

구분대상 아이디아이디농가키측정월측정주측정일과수번호평균당도평균크기
776777134040077777761052021-10-257712.1357.49
3359336013404033603360271122021-11-12810.2360.12
5702570313404057035703171042021-10-21518.9362.65
7489749013404074907490211132021-11-18559.8866.76
1287412875134041287512875251212021-12-015811.9851.19
131191312013404131201312041112021-11-0139.8443.01
3106310713404031073107271042021-10-215510.0463.43
1271512716134041271612716251132021-11-169911.0752.87
5935593613404059365936171122021-11-098410.8762.29
5984598513404059855985171132021-11-173411.4962.61
구분대상 아이디아이디농가키측정월측정주측정일과수번호평균당도평균크기
6210621113404062116211191052021-10-29699.8756.18
109471094813404109481094891032021-10-155210.4964.58
9484948513404094859485111132021-11-196511.8757.11
1133211333134041133311333121042021-10-213712.1355.29
281928201340402820282071122021-11-096811.0661.46
4820482113404048214821151022021-10-07699.0462.0
161416151340401615161531132021-11-151511.3458.11
103571035813404103581035881032021-10-145411.9242.39
119761197713404119771197711112021-11-036010.1453.29
8857885813404088588858281132021-11-193812.8963.78