Overview

Dataset statistics

Number of variables4
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory35.1 B

Variable types

Categorical2
Boolean1
Numeric1

Dataset

Description충청북도 농업기술원 농가경영기록장(농가의 소득을 증진시킬 수 있는 회원전용 농가경영 관리 프로그램)의 수입지출관련 이용자 접속기록, 거래, 거래처 등의 관리시스템으로 등록일시, 수정일시, 상태, 정렬순서 등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050316/fileData.do

Alerts

상태 has constant value ""Constant
수정일시 is highly overall correlated with 등록일시High correlation
등록일시 is highly overall correlated with 수정일시High correlation

Reproduction

Analysis started2023-12-12 22:47:52.953234
Analysis finished2023-12-12 22:47:53.340019
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록일시
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
2015-10-04 17:04
19 
2015-10-13 18:09
6 
2017-02-06 15:22
4 
2015-12-01 00:00
3 
2015-11-10 00:00
3 
Other values (23)
28 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique18 ?
Unique (%)28.6%

Sample

1st row2015-10-04 17:04
2nd row2016-06-07 18:12
3rd row2016-06-07 18:12
4th row2016-12-21 17:47
5th row2015-12-01 00:00

Common Values

ValueCountFrequency (%)
2015-10-04 17:04 19
30.2%
2015-10-13 18:09 6
 
9.5%
2017-02-06 15:22 4
 
6.3%
2015-12-01 00:00 3
 
4.8%
2015-11-10 00:00 3
 
4.8%
2017-01-03 13:08 2
 
3.2%
2016-06-07 18:12 2
 
3.2%
2016-08-18 11:21 2
 
3.2%
2015-11-03 00:00 2
 
3.2%
2016-06-22 15:01 2
 
3.2%
Other values (18) 18
28.6%

Length

2023-12-13T07:47:53.415112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2015-10-04 19
15.1%
17:04 19
15.1%
00:00 14
 
11.1%
2015-10-13 6
 
4.8%
18:09 6
 
4.8%
2017-02-06 4
 
3.2%
15:22 4
 
3.2%
2015-12-01 3
 
2.4%
2015-11-10 3
 
2.4%
2016-08-18 3
 
2.4%
Other values (35) 45
35.7%

수정일시
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
2015-10-04 17:04
19 
2015-10-13 18:09
6 
2017-02-06 15:22
4 
2015-12-01 00:00
3 
2015-11-10 00:00
3 
Other values (23)
28 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique18 ?
Unique (%)28.6%

Sample

1st row2015-10-04 17:04
2nd row2016-06-07 18:12
3rd row2016-06-07 18:12
4th row2016-12-21 17:47
5th row2015-12-01 00:00

Common Values

ValueCountFrequency (%)
2015-10-04 17:04 19
30.2%
2015-10-13 18:09 6
 
9.5%
2017-02-06 15:22 4
 
6.3%
2015-12-01 00:00 3
 
4.8%
2015-11-10 00:00 3
 
4.8%
2017-01-03 13:08 2
 
3.2%
2016-06-07 18:12 2
 
3.2%
2016-08-18 11:21 2
 
3.2%
2015-11-03 00:00 2
 
3.2%
2016-06-22 15:01 2
 
3.2%
Other values (18) 18
28.6%

Length

2023-12-13T07:47:53.552966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2015-10-04 19
15.1%
17:04 19
15.1%
00:00 14
 
11.1%
2015-10-13 6
 
4.8%
18:09 6
 
4.8%
2017-02-06 4
 
3.2%
15:22 4
 
3.2%
2015-12-01 3
 
2.4%
2015-11-10 3
 
2.4%
2016-08-18 3
 
2.4%
Other values (35) 45
35.7%

상태
Boolean

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size195.0 B
False
63 
ValueCountFrequency (%)
False 63
100.0%
2023-12-13T07:47:53.669942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

정렬순서
Real number (ℝ)

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3160955.5
Minimum1000000
Maximum5001004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-13T07:47:53.812303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000000
5-th percentile1101700
Q12006003
median3001009
Q34003000.5
95-th percentile5001000.9
Maximum5001004
Range4001004
Interquartile range (IQR)1996997.5

Descriptive statistics

Standard deviation1124496.3
Coefficient of variation (CV)0.35574569
Kurtosis-1.0420415
Mean3160955.5
Median Absolute Deviation (MAD)1000994
Skewness-0.25346015
Sum1.991402 × 108
Variance1.2644919 × 1012
MonotonicityNot monotonic
2023-12-13T07:47:53.992075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1002000 2
 
3.2%
1000000 1
 
1.6%
4002000 1
 
1.6%
3001008 1
 
1.6%
3001004 1
 
1.6%
3001005 1
 
1.6%
3001006 1
 
1.6%
3001007 1
 
1.6%
3001001 1
 
1.6%
3001009 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
1000000 1
1.6%
1001000 1
1.6%
1002000 2
3.2%
1999000 1
1.6%
1999001 1
1.6%
1999002 1
1.6%
2000000 1
1.6%
2001001 1
1.6%
2002000 1
1.6%
2002001 1
1.6%
ValueCountFrequency (%)
5001004 1
1.6%
5001003 1
1.6%
5001002 1
1.6%
5001001 1
1.6%
5001000 1
1.6%
4006000 1
1.6%
4005002 1
1.6%
4005000 1
1.6%
4004003 1
1.6%
4004000 1
1.6%

Interactions

2023-12-13T07:47:53.078688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:47:54.084619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록일시수정일시정렬순서
등록일시1.0001.0000.887
수정일시1.0001.0000.887
정렬순서0.8870.8871.000
2023-12-13T07:47:54.165660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수정일시등록일시
수정일시1.0001.000
등록일시1.0001.000
2023-12-13T07:47:54.246782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정렬순서등록일시수정일시
정렬순서1.0000.4530.453
등록일시0.4531.0001.000
수정일시0.4531.0001.000

Missing values

2023-12-13T07:47:53.212481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:47:53.307763image/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

등록일시수정일시상태정렬순서
02015-10-04 17:042015-10-04 17:04NO1000000
12016-06-07 18:122016-06-07 18:12NO1001000
22016-06-07 18:122016-06-07 18:12NO1002000
32016-12-21 17:472016-12-21 17:47NO1002000
42015-12-01 00:002015-12-01 00:00NO1999000
52015-12-01 00:002015-12-01 00:00NO1999001
62015-12-01 00:002015-12-01 00:00NO1999002
72015-10-04 17:042015-10-04 17:04NO2000000
82015-10-04 17:042015-10-04 17:04NO2001001
92015-12-03 16:122015-12-03 16:12NO2006008
등록일시수정일시상태정렬순서
532015-10-13 18:092015-10-13 18:09NO4002009
542017-01-03 13:082017-01-03 13:08NO4002007
552017-01-03 13:082017-01-03 13:08NO4002008
562017-03-24 00:002017-03-24 00:00NO4002003
572016-03-31 00:002016-03-31 00:00NO5001000
582017-02-06 15:222017-02-06 15:22NO5001001
592017-02-06 15:222017-02-06 15:22NO5001002
602017-02-06 15:222017-02-06 15:22NO5001003
612017-02-06 15:222017-02-06 15:22NO5001004
622015-11-10 00:002015-11-10 00:00NO4006000