Overview

Dataset statistics

Number of variables5
Number of observations425
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory42.3 B

Variable types

Numeric2
DateTime2
Boolean1

Dataset

Description충북농업기술원 농가 경영기록장 "바로바로"의 농업회계분석 정보제공 관련 자산, 부채, 감가상각비 등 계정과목 관리시스템으로 건물일련번호, 전표일련번호, 등록일시, 수정일시, 상태를 제공해드립니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050293/fileData.do

Alerts

상태 has constant value ""Constant
건물일련번호 is highly overall correlated with 전표일련번호High correlation
전표일련번호 is highly overall correlated with 건물일련번호High correlation
전표일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:12:19.031402
Analysis finished2023-12-12 12:12:19.861583
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건물일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct358
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3770.0753
Minimum965
Maximum4000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T21:12:19.945701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum965
5-th percentile3654.2
Q13731
median3825
Q33924
95-th percentile3985.8
Maximum4000
Range3035
Interquartile range (IQR)193

Descriptive statistics

Standard deviation312.9659
Coefficient of variation (CV)0.08301317
Kurtosis25.574274
Mean3770.0753
Median Absolute Deviation (MAD)97
Skewness-4.4746946
Sum1602282
Variance97947.655
MonotonicityIncreasing
2023-12-12T21:12:20.107652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3831 3
 
0.7%
3976 3
 
0.7%
3725 3
 
0.7%
3790 3
 
0.7%
3865 3
 
0.7%
3951 3
 
0.7%
3950 3
 
0.7%
3995 2
 
0.5%
3969 2
 
0.5%
3967 2
 
0.5%
Other values (348) 398
93.6%
ValueCountFrequency (%)
965 1
0.2%
1716 1
0.2%
2282 1
0.2%
2306 1
0.2%
2323 1
0.2%
2360 1
0.2%
2416 1
0.2%
2501 1
0.2%
2597 1
0.2%
2679 1
0.2%
ValueCountFrequency (%)
4000 2
0.5%
3999 2
0.5%
3998 2
0.5%
3997 2
0.5%
3996 1
0.2%
3995 2
0.5%
3994 1
0.2%
3993 2
0.5%
3992 2
0.5%
3991 1
0.2%

전표일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct425
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean795007.24
Minimum713069
Maximum876634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T21:12:20.265612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum713069
5-th percentile716620.8
Q1748081
median786297
Q3858086
95-th percentile874486.4
Maximum876634
Range163565
Interquartile range (IQR)110005

Descriptive statistics

Standard deviation56434.71
Coefficient of variation (CV)0.07098641
Kurtosis-1.4958591
Mean795007.24
Median Absolute Deviation (MAD)57910
Skewness0.080628225
Sum3.3787808 × 108
Variance3.1848765 × 109
MonotonicityNot monotonic
2023-12-12T21:12:20.452267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
727528 1
 
0.2%
834538 1
 
0.2%
828551 1
 
0.2%
827856 1
 
0.2%
824481 1
 
0.2%
822732 1
 
0.2%
822728 1
 
0.2%
822724 1
 
0.2%
822578 1
 
0.2%
822576 1
 
0.2%
Other values (415) 415
97.6%
ValueCountFrequency (%)
713069 1
0.2%
713071 1
0.2%
713072 1
0.2%
713078 1
0.2%
713082 1
0.2%
713083 1
0.2%
713405 1
0.2%
715197 1
0.2%
715199 1
0.2%
715203 1
0.2%
ValueCountFrequency (%)
876634 1
0.2%
876633 1
0.2%
876373 1
0.2%
876372 1
0.2%
876113 1
0.2%
876111 1
0.2%
876110 1
0.2%
874972 1
0.2%
874970 1
0.2%
874969 1
0.2%

등록일시
Date

Distinct357
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2017-03-10 21:20:13
Maximum2019-11-05 09:41:46
2023-12-12T21:12:20.609895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:20.741311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

Distinct357
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
Minimum2017-03-10 21:20:13
Maximum2019-11-05 09:41:46
2023-12-12T21:12:20.887474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:21.026807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size557.0 B
False
425 
ValueCountFrequency (%)
False 425
100.0%
2023-12-12T21:12:21.135133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T21:12:19.415710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:19.147670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:19.560717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:12:19.275898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:12:21.506349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물일련번호전표일련번호
건물일련번호1.0000.572
전표일련번호0.5721.000
2023-12-12T21:12:21.571835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물일련번호전표일련번호
건물일련번호1.0000.903
전표일련번호0.9031.000

Missing values

2023-12-12T21:12:19.718275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:12:19.822052image/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

건물일련번호전표일련번호등록일시수정일시상태
09657275282017-05-26 16:24:142017-05-26 16:24:14N
117167690992018-03-12 18:35:462018-03-12 18:35:46N
222827275262017-05-26 16:22:542017-05-26 16:22:54N
323067275222017-05-26 16:21:102017-05-26 16:21:10N
423237275202017-05-26 16:20:232017-05-26 16:20:23N
523607261632017-05-19 16:23:212017-05-19 16:23:21N
624167275162017-05-26 16:19:352017-05-26 16:19:35N
725017782452018-05-01 05:23:262018-05-01 05:23:26N
825977134052017-03-13 09:38:232017-03-13 09:38:23N
926797170822017-03-31 11:47:112017-03-31 11:47:11N
건물일련번호전표일련번호등록일시수정일시상태
41539958747922019-10-30 19:32:572019-10-30 19:32:57N
41639968761132019-11-03 19:27:542019-11-03 19:27:54N
41739978761112019-11-03 19:27:112019-11-03 19:27:11N
41839978761102019-11-03 19:27:112019-11-03 19:27:11N
41939988749702019-10-30 23:27:522019-10-30 23:27:52N
42039988749692019-10-30 23:27:522019-10-30 23:27:52N
42139998763732019-11-05 09:16:032019-11-05 09:16:03N
42239998763722019-11-05 09:16:032019-11-05 09:16:03N
42340008766342019-11-05 09:41:462019-11-05 09:41:46N
42440008766332019-11-05 09:41:462019-11-05 09:41:46N