Overview

Dataset statistics

Number of variables10
Number of observations254
Missing cells537
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.2 KiB
Average record size in memory85.5 B

Variable types

Numeric5
Categorical2
DateTime1
Text2

Dataset

Description2021년 공공데이터 기업매칭지원사업을 통해 수집한 제주 지역 내 고품질 감귤 농가의 영농행위정보입니다. 데이터 항목별 설명은 다음과 같습니다. 대상 ID, id(행위키), fm_id(농가키), fa_type(실행타입), fa_acted_at(실행일), fa_act_amount(실행량), fa_unit(실행량 단위), fa_product_name(약제명), fa_memo(기타사항)
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15097170/fileData.do

Alerts

실행타입 is highly overall correlated with 실행량 and 1 other fieldsHigh correlation
실행량 단위 is highly overall correlated with 실행타입High correlation
구분 is highly overall correlated with 대상 아이디 and 1 other fieldsHigh correlation
대상 아이디 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
아이디 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
농가키 is highly overall correlated with 실행량High correlation
실행량 is highly overall correlated with 농가키 and 1 other fieldsHigh correlation
실행량 단위 is highly imbalanced (80.3%)Imbalance
실행량 has 238 (93.7%) missing valuesMissing
약제명 has 102 (40.2%) missing valuesMissing
기타사항 has 197 (77.6%) missing valuesMissing
구분 has unique valuesUnique
대상 아이디 has unique valuesUnique
아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:41:12.295869
Analysis finished2023-12-12 08:41:15.696021
Duration3.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct254
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.5
Minimum1
Maximum254
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T17:41:15.803899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.65
Q164.25
median127.5
Q3190.75
95-th percentile241.35
Maximum254
Range253
Interquartile range (IQR)126.5

Descriptive statistics

Standard deviation73.46768
Coefficient of variation (CV)0.5762171
Kurtosis-1.2
Mean127.5
Median Absolute Deviation (MAD)63.5
Skewness0
Sum32385
Variance5397.5
MonotonicityStrictly increasing
2023-12-12T17:41:15.990020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
176 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
Other values (244) 244
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%
246 1
0.4%
245 1
0.4%

대상 아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct254
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3403001 × 109
Minimum1.3403 × 109
Maximum1.3403003 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T17:41:16.168993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.3403 × 109
5-th percentile1.3403 × 109
Q11.3403001 × 109
median1.3403001 × 109
Q31.3403002 × 109
95-th percentile1.3403002 × 109
Maximum1.3403003 × 109
Range253
Interquartile range (IQR)126.5

Descriptive statistics

Standard deviation73.46768
Coefficient of variation (CV)5.481435 × 10-8
Kurtosis-1.2
Mean1.3403001 × 109
Median Absolute Deviation (MAD)63.5
Skewness0
Sum3.4043623 × 1011
Variance5397.5
MonotonicityStrictly increasing
2023-12-12T17:41:16.340485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1340300001 1
 
0.4%
1340300176 1
 
0.4%
1340300163 1
 
0.4%
1340300164 1
 
0.4%
1340300165 1
 
0.4%
1340300166 1
 
0.4%
1340300167 1
 
0.4%
1340300168 1
 
0.4%
1340300169 1
 
0.4%
1340300170 1
 
0.4%
Other values (244) 244
96.1%
ValueCountFrequency (%)
1340300001 1
0.4%
1340300002 1
0.4%
1340300003 1
0.4%
1340300004 1
0.4%
1340300005 1
0.4%
1340300006 1
0.4%
1340300007 1
0.4%
1340300008 1
0.4%
1340300009 1
0.4%
1340300010 1
0.4%
ValueCountFrequency (%)
1340300254 1
0.4%
1340300253 1
0.4%
1340300252 1
0.4%
1340300251 1
0.4%
1340300250 1
0.4%
1340300249 1
0.4%
1340300248 1
0.4%
1340300247 1
0.4%
1340300246 1
0.4%
1340300245 1
0.4%

아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct254
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.5
Minimum1
Maximum254
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T17:41:16.538127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.65
Q164.25
median127.5
Q3190.75
95-th percentile241.35
Maximum254
Range253
Interquartile range (IQR)126.5

Descriptive statistics

Standard deviation73.46768
Coefficient of variation (CV)0.5762171
Kurtosis-1.2
Mean127.5
Median Absolute Deviation (MAD)63.5
Skewness0
Sum32385
Variance5397.5
MonotonicityStrictly increasing
2023-12-12T17:41:16.765628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
176 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
Other values (244) 244
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%
249 1
0.4%
248 1
0.4%
247 1
0.4%
246 1
0.4%
245 1
0.4%

농가키
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.952756
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T17:41:16.892094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q17
median15
Q322
95-th percentile28
Maximum30
Range29
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.5232611
Coefficient of variation (CV)0.57001273
Kurtosis-1.221216
Mean14.952756
Median Absolute Deviation (MAD)8
Skewness0.1772045
Sum3798
Variance72.645981
MonotonicityNot monotonic
2023-12-12T17:41:17.046052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
6 32
 
12.6%
28 23
 
9.1%
22 20
 
7.9%
15 20
 
7.9%
7 16
 
6.3%
18 14
 
5.5%
13 12
 
4.7%
3 9
 
3.5%
19 8
 
3.1%
9 7
 
2.8%
Other values (18) 93
36.6%
ValueCountFrequency (%)
1 7
 
2.8%
2 2
 
0.8%
3 9
 
3.5%
4 5
 
2.0%
5 6
 
2.4%
6 32
12.6%
7 16
6.3%
8 6
 
2.4%
9 7
 
2.8%
10 5
 
2.0%
ValueCountFrequency (%)
30 6
 
2.4%
29 6
 
2.4%
28 23
9.1%
26 4
 
1.6%
25 4
 
1.6%
24 6
 
2.4%
23 5
 
2.0%
22 20
7.9%
21 5
 
2.0%
20 6
 
2.4%

실행타입
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
방제
84 
시비
68 
피복
30 
적과
28 
전정
27 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관수
2nd row관수
3rd row적과
4th row전정
5th row방제

Common Values

ValueCountFrequency (%)
방제 84
33.1%
시비 68
26.8%
피복 30
 
11.8%
적과 28
 
11.0%
전정 27
 
10.6%
관수 17
 
6.7%

Length

2023-12-12T17:41:17.201400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:41:17.356718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방제 84
33.1%
시비 68
26.8%
피복 30
 
11.8%
적과 28
 
11.0%
전정 27
 
10.6%
관수 17
 
6.7%

실행일
Date

Distinct138
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2021-01-04 00:00:00
Maximum2021-10-21 00:00:00
2023-12-12T17:41:17.536735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:17.721142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

실행량
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)56.2%
Missing238
Missing (%)93.7%
Infinite0
Infinite (%)0.0%
Mean8759.875
Minimum1
Maximum30000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T17:41:17.881279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.5
Q12000
median10000
Q310000
95-th percentile23250
Maximum30000
Range29999
Interquartile range (IQR)8000

Descriptive statistics

Standard deviation8222.9597
Coefficient of variation (CV)0.93870742
Kurtosis1.7614298
Mean8759.875
Median Absolute Deviation (MAD)6500
Skewness1.2007481
Sum140158
Variance67617066
MonotonicityNot monotonic
2023-12-12T17:41:18.041098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
10000 6
 
2.4%
2000 3
 
1.2%
30000 1
 
0.4%
21000 1
 
0.4%
8000 1
 
0.4%
7 1
 
0.4%
1 1
 
0.4%
150 1
 
0.4%
15000 1
 
0.4%
(Missing) 238
93.7%
ValueCountFrequency (%)
1 1
 
0.4%
7 1
 
0.4%
150 1
 
0.4%
2000 3
1.2%
8000 1
 
0.4%
10000 6
2.4%
15000 1
 
0.4%
21000 1
 
0.4%
30000 1
 
0.4%
ValueCountFrequency (%)
30000 1
 
0.4%
21000 1
 
0.4%
15000 1
 
0.4%
10000 6
2.4%
8000 1
 
0.4%
2000 3
1.2%
150 1
 
0.4%
7 1
 
0.4%
1 1
 
0.4%

실행량 단위
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
238 
리터
 
13
톤
 
2
말
 
1

Length

Max length4
Median length4
Mean length3.8622047
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 238
93.7%
리터 13
 
5.1%
톤 2
 
0.8%
말 1
 
0.4%

Length

2023-12-12T17:41:18.194381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:41:18.677483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 238
93.7%
리터 13
 
5.1%
톤 2
 
0.8%
말 1
 
0.4%

약제명
Text

MISSING 

Distinct125
Distinct (%)82.2%
Missing102
Missing (%)40.2%
Memory size2.1 KiB
2023-12-12T17:41:19.040263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length23
Mean length10.407895
Min length2

Characters and Unicode

Total characters1582
Distinct characters207
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)71.1%

Sample

1st row인트라콜,산마루,똑소리(살충제)
2nd row유기농,특호
3rd row복합비료
4th row맞춤30호
5th row보르도액
ValueCountFrequency (%)
다이센 29
 
9.2%
다이젠 13
 
4.1%
기계유제 12
 
3.8%
복합비료 9
 
2.8%
보르도액 9
 
2.8%
살충제 7
 
2.2%
진딧물 7
 
2.2%
왕중왕 6
 
1.9%
볼트액 5
 
1.6%
한아름특호 5
 
1.6%
Other values (149) 214
67.7%
2023-12-12T17:41:19.619976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 171
 
10.8%
168
 
10.6%
이 70
 
4.4%
다 60
 
3.8%
센 40
 
2.5%
비 39
 
2.5%
유 32
 
2.0%
제 32
 
2.0%
기 27
 
1.7%
르 22
 
1.4%
Other values (197) 921
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1169
73.9%
Other Punctuation 171
 
10.8%
Space Separator 168
 
10.6%
Decimal Number 37
 
2.3%
Open Punctuation 16
 
1.0%
Close Punctuation 16
 
1.0%
Lowercase Letter 4
 
0.3%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 70
 
6.0%
다 60
 
5.1%
센 40
 
3.4%
비 39
 
3.3%
유 32
 
2.7%
제 32
 
2.7%
기 27
 
2.3%
르 22
 
1.9%
스 22
 
1.9%
료 22
 
1.9%
Other values (183) 803
68.7%
Decimal Number
ValueCountFrequency (%)
0 10
27.0%
1 9
24.3%
5 7
18.9%
3 4
 
10.8%
2 4
 
10.8%
4 1
 
2.7%
8 1
 
2.7%
7 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 171
100.0%
Space Separator
ValueCountFrequency (%)
168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1169
73.9%
Common 409
 
25.9%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 70
 
6.0%
다 60
 
5.1%
센 40
 
3.4%
비 39
 
3.3%
유 32
 
2.7%
제 32
 
2.7%
기 27
 
2.3%
르 22
 
1.9%
스 22
 
1.9%
료 22
 
1.9%
Other values (183) 803
68.7%
Common
ValueCountFrequency (%)
, 171
41.8%
168
41.1%
( 16
 
3.9%
) 16
 
3.9%
0 10
 
2.4%
1 9
 
2.2%
5 7
 
1.7%
3 4
 
1.0%
2 4
 
1.0%
4 1
 
0.2%
Other values (3) 3
 
0.7%
Latin
ValueCountFrequency (%)
c 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1169
73.9%
ASCII 413
 
26.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 171
41.4%
168
40.7%
( 16
 
3.9%
) 16
 
3.9%
0 10
 
2.4%
1 9
 
2.2%
5 7
 
1.7%
3 4
 
1.0%
c 4
 
1.0%
2 4
 
1.0%
Other values (4) 4
 
1.0%
Hangul
ValueCountFrequency (%)
이 70
 
6.0%
다 60
 
5.1%
센 40
 
3.4%
비 39
 
3.3%
유 32
 
2.7%
제 32
 
2.7%
기 27
 
2.3%
르 22
 
1.9%
스 22
 
1.9%
료 22
 
1.9%
Other values (183) 803
68.7%

기타사항
Text

MISSING 

Distinct51
Distinct (%)89.5%
Missing197
Missing (%)77.6%
Memory size2.1 KiB
2023-12-12T17:41:19.922326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length18
Mean length11.982456
Min length3

Characters and Unicode

Total characters683
Distinct characters103
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)80.7%

Sample

1st row7월중순
2nd row8월28일~9월11일 사이 총 10번
3rd row9월부터 수시
4th row4월초진행
5th row3월29일 까지 수시 진행
ValueCountFrequency (%)
진행 8
 
4.6%
4월 8
 
4.6%
주기 7
 
4.0%
정확하지 6
 
3.4%
않음 6
 
3.4%
날짜 6
 
3.4%
초 6
 
3.4%
주기적으로 5
 
2.9%
15일 5
 
2.9%
3월 4
 
2.3%
Other values (91) 113
64.9%
2023-12-12T17:41:20.386216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
17.1%
월 57
 
8.3%
일 28
 
4.1%
1 20
 
2.9%
, 17
 
2.5%
4 16
 
2.3%
주 16
 
2.3%
5 16
 
2.3%
지 16
 
2.3%
초 15
 
2.2%
Other values (93) 365
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 411
60.2%
Space Separator 117
 
17.1%
Decimal Number 113
 
16.5%
Other Punctuation 17
 
2.5%
Math Symbol 10
 
1.5%
Close Punctuation 7
 
1.0%
Open Punctuation 7
 
1.0%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 57
 
13.9%
일 28
 
6.8%
주 16
 
3.9%
지 16
 
3.9%
초 15
 
3.6%
기 12
 
2.9%
진 10
 
2.4%
까 10
 
2.4%
행 10
 
2.4%
로 9
 
2.2%
Other values (77) 228
55.5%
Decimal Number
ValueCountFrequency (%)
1 20
17.7%
4 16
14.2%
5 16
14.2%
2 15
13.3%
3 13
11.5%
9 9
8.0%
7 8
 
7.1%
6 7
 
6.2%
8 6
 
5.3%
0 3
 
2.7%
Space Separator
ValueCountFrequency (%)
117
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 411
60.2%
Common 271
39.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
월 57
 
13.9%
일 28
 
6.8%
주 16
 
3.9%
지 16
 
3.9%
초 15
 
3.6%
기 12
 
2.9%
진 10
 
2.4%
까 10
 
2.4%
행 10
 
2.4%
로 9
 
2.2%
Other values (77) 228
55.5%
Common
ValueCountFrequency (%)
117
43.2%
1 20
 
7.4%
, 17
 
6.3%
4 16
 
5.9%
5 16
 
5.9%
2 15
 
5.5%
3 13
 
4.8%
~ 10
 
3.7%
9 9
 
3.3%
7 8
 
3.0%
Other values (5) 30
 
11.1%
Latin
ValueCountFrequency (%)
X 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 411
60.2%
ASCII 272
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
43.0%
1 20
 
7.4%
, 17
 
6.2%
4 16
 
5.9%
5 16
 
5.9%
2 15
 
5.5%
3 13
 
4.8%
~ 10
 
3.7%
9 9
 
3.3%
7 8
 
2.9%
Other values (6) 31
 
11.4%
Hangul
ValueCountFrequency (%)
월 57
 
13.9%
일 28
 
6.8%
주 16
 
3.9%
지 16
 
3.9%
초 15
 
3.6%
기 12
 
2.9%
진 10
 
2.4%
까 10
 
2.4%
행 10
 
2.4%
로 9
 
2.2%
Other values (77) 228
55.5%

Interactions

2023-12-12T17:41:14.768259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:12.754182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.174144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.748760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.246651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.849459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:12.831639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.276449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.859550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.340659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.941335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:12.909803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.376182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.951460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.430714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:15.038914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:12.981735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.473685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.036784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.550248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:15.139829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.073377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:13.591027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.152534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:41:14.676871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:41:20.506446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대상 아이디아이디농가키실행타입실행량실행량 단위기타사항
구분1.0001.0001.0000.9260.3820.7150.5580.832
대상 아이디1.0001.0001.0000.9260.3800.7780.5210.832
아이디1.0001.0001.0000.9260.3820.7150.5580.832
농가키0.9260.9260.9261.0000.2050.4540.5240.842
실행타입0.3820.3800.3820.2051.000NaNNaN1.000
실행량0.7150.7780.7150.454NaN1.0000.0001.000
실행량 단위0.5580.5210.5580.524NaN0.0001.0001.000
기타사항0.8320.8320.8320.8421.0001.0001.0001.000
2023-12-12T17:41:20.641221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실행타입실행량 단위
실행타입1.0001.000
실행량 단위1.0001.000
2023-12-12T17:41:20.752208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대상 아이디아이디농가키실행량실행타입실행량 단위
구분1.0001.0001.0000.264-0.3060.2100.340
대상 아이디1.0001.0001.0000.264-0.3060.2100.340
아이디1.0001.0001.0000.264-0.3060.2100.340
농가키0.2640.2640.2641.000-0.6170.1080.305
실행량-0.306-0.306-0.306-0.6171.0001.0000.000
실행타입0.2100.2100.2100.1081.0001.0001.000
실행량 단위0.3400.3400.3400.3050.0001.0001.000

Missing values

2023-12-12T17:41:15.295614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:41:15.468361image/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.
2023-12-12T17:41:15.592242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분대상 아이디아이디농가키실행타입실행일실행량실행량 단위약제명기타사항
01134030000113관수2021-08-1530000리터<NA><NA>
12134030000223관수2021-07-2021000리터<NA><NA>
23134030000333적과2021-07-15<NA><NA><NA>7월중순
34134030000443전정2021-02-27<NA><NA><NA><NA>
45134030000553방제2021-09-11<NA><NA>인트라콜,산마루,똑소리(살충제)8월28일~9월11일 사이 총 10번
56134030000663시비2021-02-13<NA><NA>유기농,특호<NA>
67134030000773시비2021-03-28<NA><NA>복합비료<NA>
78134030000883시비2021-06-26<NA><NA>맞춤30호<NA>
89134030000993피복2021-06-19<NA><NA><NA><NA>
91013403000101022관수2021-08-302000리터<NA><NA>
구분대상 아이디아이디농가키실행타입실행일실행량실행량 단위약제명기타사항
244245134030024524525전정2021-02-23<NA><NA><NA><NA>
245246134030024624625방제2021-05-03<NA><NA>다이쉔, 델라, 대양병,잿빛곰팡이,기계유액13일 주기, 비올 때는 7일 주기
246247134030024724725시비2021-03-14<NA><NA>복합비료, (꽃비료는 요소)비료 줄때 잎파리 영양제도 같이 사용
247248134030024824825피복2021-05-29<NA><NA><NA><NA>
24824913403002492498적과2021-07-16<NA><NA><NA><NA>
24925013403002502508전정2021-03-21<NA><NA><NA><NA>
25025113403002512518방제2021-04-24<NA><NA>보르도, 기계유액<NA>
25125213403002522528시비2021-03-05<NA><NA>야라밀라, 야라라보<NA>
25225313403002532538시비2021-05-21<NA><NA>야라밀라, 야라라보<NA>
25325413403002542548피복2021-05-28<NA><NA><NA><NA>