Overview

Dataset statistics

Number of variables5
Number of observations1625
Missing cells0
Missing cells (%)0.0%
Duplicate rows48
Duplicate rows (%)3.0%
Total size in memory65.2 KiB
Average record size in memory41.1 B

Variable types

DateTime1
Categorical1
Boolean2
Numeric1

Dataset

Description농가의 일일 영농활동(교육, 시비 작업 등), 생산, 판매 활동 등 기록 관리시스템으로 등록일시, 수정일시, 상태, 표출여부, 표출순번 등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050310/fileData.do

Alerts

상태 has constant value ""Constant
표출여부 has constant value ""Constant
Dataset has 48 (3.0%) duplicate rowsDuplicates
수정일시 is highly imbalanced (72.7%)Imbalance

Reproduction

Analysis started2023-12-12 07:03:28.788710
Analysis finished2023-12-12 07:03:29.238776
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록일시
Date

Distinct53
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
Minimum1900-01-01 00:00:00
Maximum2019-11-01 13:32:00
2023-12-12T16:03:29.325970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:03:29.489652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Categorical

IMBALANCE 

Distinct22
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size12.8 KiB
1900-01-01 00:00
1364 
2019-05-10 10:49
 
50
2019-07-04 09:35
 
32
2019-05-09 17:32
 
30
2019-11-01 13:21
 
25
Other values (17)
 
124

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row2017-04-13 11:34
2nd row2017-04-13 11:34
3rd row2017-04-13 11:34
4th row2017-04-13 11:34
5th row2017-04-13 11:34

Common Values

ValueCountFrequency (%)
1900-01-01 00:00 1364
83.9%
2019-05-10 10:49 50
 
3.1%
2019-07-04 09:35 32
 
2.0%
2019-05-09 17:32 30
 
1.8%
2019-11-01 13:21 25
 
1.5%
2019-11-01 13:32 24
 
1.5%
2017-04-13 11:34 23
 
1.4%
2018-03-26 17:46 19
 
1.2%
2018-01-05 17:31 14
 
0.9%
2018-01-05 17:20 9
 
0.6%
Other values (12) 35
 
2.2%

Length

2023-12-12T16:03:29.656452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1900-01-01 1364
42.0%
00:00 1364
42.0%
2019-05-10 50
 
1.5%
10:49 50
 
1.5%
2019-11-01 49
 
1.5%
2019-07-04 38
 
1.2%
2019-05-09 34
 
1.0%
09:35 32
 
1.0%
17:32 30
 
0.9%
13:21 25
 
0.8%
Other values (26) 214
 
6.6%

상태
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
False
1625 
ValueCountFrequency (%)
False 1625
100.0%
2023-12-12T16:03:29.789516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

표출여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
True
1625 
ValueCountFrequency (%)
True 1625
100.0%
2023-12-12T16:03:29.889501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

표출순번
Real number (ℝ)

Distinct32
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5046154
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.4 KiB
2023-12-12T16:03:29.999856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q312
95-th percentile20
Maximum32
Range31
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.0223422
Coefficient of variation (CV)0.70812634
Kurtosis0.66581491
Mean8.5046154
Median Absolute Deviation (MAD)4
Skewness0.92729679
Sum13820
Variance36.268606
MonotonicityNot monotonic
2023-12-12T16:03:30.152462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 168
 
10.3%
4 110
 
6.8%
5 109
 
6.7%
3 109
 
6.7%
2 109
 
6.7%
6 106
 
6.5%
7 104
 
6.4%
8 101
 
6.2%
9 95
 
5.8%
10 86
 
5.3%
Other values (22) 528
32.5%
ValueCountFrequency (%)
1 168
10.3%
2 109
6.7%
3 109
6.7%
4 110
6.8%
5 109
6.7%
6 106
6.5%
7 104
6.4%
8 101
6.2%
9 95
5.8%
10 86
5.3%
ValueCountFrequency (%)
32 1
 
0.1%
31 2
 
0.1%
30 3
 
0.2%
29 3
 
0.2%
28 3
 
0.2%
27 5
0.3%
26 6
0.4%
25 7
0.4%
24 8
0.5%
23 10
0.6%

Interactions

2023-12-12T16:03:28.947203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:03:30.267472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록일시수정일시표출순번
등록일시1.0000.9940.659
수정일시0.9941.0000.380
표출순번0.6590.3801.000
2023-12-12T16:03:30.358411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
표출순번수정일시
표출순번1.0000.150
수정일시0.1501.000

Missing values

2023-12-12T16:03:29.099615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:03:29.201399image/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

등록일시수정일시상태표출여부표출순번
01900-01-01 00:002017-04-13 11:34NY1
11900-01-01 00:002017-04-13 11:34NY13
21900-01-01 00:002017-04-13 11:34NY15
31900-01-01 00:002017-04-13 11:34NY16
41900-01-01 00:002017-04-13 11:34NY17
51900-01-01 00:002017-04-13 11:34NY18
61900-01-01 00:002017-04-13 11:34NY22
71900-01-01 00:002017-04-13 11:34NY19
81900-01-01 00:002017-04-13 11:34NY20
91900-01-01 00:002017-04-13 11:34NY12
등록일시수정일시상태표출여부표출순번
16152019-11-01 13:292019-11-01 13:32NY15
16162019-11-01 13:292019-11-01 13:32NY16
16172019-11-01 13:292019-11-01 13:32NY17
16182019-11-01 13:302019-11-01 13:32NY18
16192019-11-01 13:302019-11-01 13:32NY19
16202019-11-01 13:312019-11-01 13:32NY20
16212019-11-01 13:322019-11-01 13:32NY21
16222019-11-01 13:322019-11-01 13:32NY22
16232019-11-01 13:322019-11-01 13:32NY23
16242019-11-01 13:322019-11-01 13:32NY24

Duplicate rows

Most frequently occurring

등록일시수정일시상태표출여부표출순번# duplicates
01900-01-01 00:001900-01-01 00:00NY1151
41900-01-01 00:001900-01-01 00:00NY596
31900-01-01 00:001900-01-01 00:00NY495
11900-01-01 00:001900-01-01 00:00NY293
21900-01-01 00:001900-01-01 00:00NY393
51900-01-01 00:001900-01-01 00:00NY693
61900-01-01 00:001900-01-01 00:00NY793
71900-01-01 00:001900-01-01 00:00NY890
81900-01-01 00:001900-01-01 00:00NY984
91900-01-01 00:001900-01-01 00:00NY1077