Overview

Dataset statistics

Number of variables7
Number of observations790
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.4 KiB
Average record size in memory60.2 B

Variable types

Numeric4
DateTime2
Boolean1

Dataset

Description충북농업기술원 농가 경영기록장 "바로바로"의 농업회계분석 정보제공 관련 자산, 부채, 감가상각비 등 계정과목 관리시스템으로 시설물감가상각비일련번호, 등록일시, 수정일시, 상태, 품목일련번호, 시설물일련번호, 감가상각율을 제공해드립니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050292/fileData.do

Alerts

상태 has constant value ""Constant
시설물감가상각비일련번호 is highly overall correlated with 시설물일련번호High correlation
시설물일련번호 is highly overall correlated with 시설물감가상각비일련번호High correlation
시설물감가상각비일련번호 has unique valuesUnique
감가상각율 has 305 (38.6%) zerosZeros

Reproduction

Analysis started2023-12-12 19:37:08.331552
Analysis finished2023-12-12 19:37:11.733335
Duration3.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설물감가상각비일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct790
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1570.1329
Minimum8
Maximum2709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-13T04:37:11.838200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile225.45
Q1812.25
median1642.5
Q32365.75
95-th percentile2649.55
Maximum2709
Range2701
Interquartile range (IQR)1553.5

Descriptive statistics

Standard deviation832.95332
Coefficient of variation (CV)0.53049861
Kurtosis-1.3817709
Mean1570.1329
Median Absolute Deviation (MAD)738
Skewness-0.22835304
Sum1240405
Variance693811.23
MonotonicityStrictly increasing
2023-12-13T04:37:12.042287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 1
 
0.1%
2199 1
 
0.1%
2201 1
 
0.1%
2202 1
 
0.1%
2203 1
 
0.1%
2204 1
 
0.1%
2205 1
 
0.1%
2211 1
 
0.1%
2216 1
 
0.1%
2221 1
 
0.1%
Other values (780) 780
98.7%
ValueCountFrequency (%)
8 1
0.1%
9 1
0.1%
10 1
0.1%
13 1
0.1%
23 1
0.1%
43 1
0.1%
50 1
0.1%
70 1
0.1%
77 1
0.1%
79 1
0.1%
ValueCountFrequency (%)
2709 1
0.1%
2708 1
0.1%
2707 1
0.1%
2706 1
0.1%
2705 1
0.1%
2704 1
0.1%
2703 1
0.1%
2702 1
0.1%
2701 1
0.1%
2700 1
0.1%

등록일시
Date

Distinct90
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum1900-01-01 00:00:00
Maximum2019-10-30 14:31:48
2023-12-13T04:37:12.218145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:12.412335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

Distinct85
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum1900-01-01 00:00:00
Maximum2019-11-05 13:26:37
2023-12-13T04:37:12.611976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:12.774470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size922.0 B
False
790 
ValueCountFrequency (%)
False 790
100.0%
2023-12-13T04:37:12.950527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

품목일련번호
Real number (ℝ)

Distinct160
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.18987
Minimum1
Maximum607
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-13T04:37:13.098367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q134
median63
Q3178.75
95-th percentile455
Maximum607
Range606
Interquartile range (IQR)144.75

Descriptive statistics

Standard deviation143.9998
Coefficient of variation (CV)1.1146369
Kurtosis1.4679784
Mean129.18987
Median Absolute Deviation (MAD)43
Skewness1.5244706
Sum102060
Variance20735.941
MonotonicityNot monotonic
2023-12-13T04:37:13.259591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 39
 
4.9%
13 29
 
3.7%
145 24
 
3.0%
42 23
 
2.9%
66 22
 
2.8%
22 19
 
2.4%
4 18
 
2.3%
297 16
 
2.0%
74 16
 
2.0%
63 16
 
2.0%
Other values (150) 568
71.9%
ValueCountFrequency (%)
1 2
 
0.3%
4 18
2.3%
5 12
1.5%
6 1
 
0.1%
7 1
 
0.1%
8 2
 
0.3%
9 3
 
0.4%
10 12
1.5%
12 3
 
0.4%
13 29
3.7%
ValueCountFrequency (%)
607 5
0.6%
602 2
 
0.3%
600 2
 
0.3%
577 1
 
0.1%
576 1
 
0.1%
573 1
 
0.1%
572 3
0.4%
564 1
 
0.1%
559 1
 
0.1%
548 1
 
0.1%

시설물일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct308
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2267.6215
Minimum11
Maximum3994
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-13T04:37:13.438633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile122.35
Q11056.75
median2243
Q33764
95-th percentile3942.3
Maximum3994
Range3983
Interquartile range (IQR)2707.25

Descriptive statistics

Standard deviation1360.8299
Coefficient of variation (CV)0.60011332
Kurtosis-1.4707456
Mean2267.6215
Median Absolute Deviation (MAD)1495
Skewness-0.08764194
Sum1791421
Variance1851857.9
MonotonicityNot monotonic
2023-12-13T04:37:13.654533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3920 10
 
1.3%
748 10
 
1.3%
1441 10
 
1.3%
3917 10
 
1.3%
2243 10
 
1.3%
2244 10
 
1.3%
704 10
 
1.3%
11 9
 
1.1%
3902 9
 
1.1%
3746 9
 
1.1%
Other values (298) 693
87.7%
ValueCountFrequency (%)
11 9
1.1%
18 6
0.8%
25 2
 
0.3%
38 1
 
0.1%
50 6
0.8%
52 6
0.8%
64 6
0.8%
66 1
 
0.1%
112 1
 
0.1%
119 1
 
0.1%
ValueCountFrequency (%)
3994 3
 
0.4%
3992 2
 
0.3%
3991 8
1.0%
3990 2
 
0.3%
3974 4
0.5%
3973 2
 
0.3%
3972 2
 
0.3%
3971 2
 
0.3%
3967 1
 
0.1%
3965 3
 
0.4%

감가상각율
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.094937
Minimum0
Maximum100
Zeros305
Zeros (%)38.6%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2023-12-13T04:37:13.843070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q360
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)60

Descriptive statistics

Standard deviation39.642923
Coefficient of variation (CV)1.1627217
Kurtosis-1.0795414
Mean34.094937
Median Absolute Deviation (MAD)10
Skewness0.75146991
Sum26935
Variance1571.5613
MonotonicityNot monotonic
2023-12-13T04:37:14.027578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 305
38.6%
100 164
20.8%
50 66
 
8.4%
10 62
 
7.8%
20 47
 
5.9%
30 31
 
3.9%
5 20
 
2.5%
60 15
 
1.9%
80 12
 
1.5%
40 12
 
1.5%
Other values (21) 56
 
7.1%
ValueCountFrequency (%)
0 305
38.6%
1 1
 
0.1%
2 5
 
0.6%
3 1
 
0.1%
4 1
 
0.1%
5 20
 
2.5%
6 1
 
0.1%
7 1
 
0.1%
8 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
100 164
20.8%
99 1
 
0.1%
95 1
 
0.1%
90 7
 
0.9%
80 12
 
1.5%
75 3
 
0.4%
70 5
 
0.6%
60 15
 
1.9%
55 2
 
0.3%
50 66
8.4%

Interactions

2023-12-13T04:37:10.931099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:08.986352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:09.849387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:10.376988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:11.073735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:09.101866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:09.960881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:10.488947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:11.209107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:09.218790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:10.078677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:10.645905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:11.344826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:09.358875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:10.223771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:37:10.799274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:37:14.164984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물감가상각비일련번호등록일시수정일시품목일련번호시설물일련번호감가상각율
시설물감가상각비일련번호1.0000.8710.8530.5640.9540.491
등록일시0.8711.0001.0000.7480.8090.199
수정일시0.8531.0001.0000.7110.8150.288
품목일련번호0.5640.7480.7111.0000.5260.236
시설물일련번호0.9540.8090.8150.5261.0000.361
감가상각율0.4910.1990.2880.2360.3611.000
2023-12-13T04:37:14.283899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설물감가상각비일련번호품목일련번호시설물일련번호감가상각율
시설물감가상각비일련번호1.0000.0880.905-0.175
품목일련번호0.0881.0000.065-0.008
시설물일련번호0.9050.0651.000-0.100
감가상각율-0.175-0.008-0.1001.000

Missing values

2023-12-13T04:37:11.502646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:37:11.664621image/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

시설물감가상각비일련번호등록일시수정일시상태품목일련번호시설물일련번호감가상각율
081900-01-01 00:00:002018-05-15 13:29:30N691110
191900-01-01 00:00:002018-05-15 13:29:30N671160
2101900-01-01 00:00:002017-11-07 11:37:07N751130
3131900-01-01 00:00:001900-01-01 00:00:00N1571130
4231900-01-01 00:00:001900-01-01 00:00:00N152185
5431900-01-01 00:00:001900-01-01 00:00:00N34380
6501900-01-01 00:00:001900-01-01 00:00:00N766640
7701900-01-01 00:00:001900-01-01 00:00:00N47112100
8771900-01-01 00:00:001900-01-01 00:00:00N2911940
9791900-01-01 00:00:001900-01-01 00:00:00N2912150
시설물감가상각비일련번호등록일시수정일시상태품목일련번호시설물일련번호감가상각율
78027002019-10-30 14:28:142019-10-30 14:28:14N8039910
78127012019-10-30 14:28:142019-10-30 14:28:14N7539910
78227022019-10-30 14:28:142019-10-30 14:28:14N60739910
78327032019-10-30 14:28:142019-10-30 14:28:14N2939910
78427042019-10-30 14:28:142019-10-30 14:28:14N139910
78527052019-10-30 14:28:292019-10-30 14:28:29N60739710
78627062019-10-30 14:28:292019-10-30 14:28:29N213971100
78727072019-10-30 14:31:482019-11-05 13:26:37N305399450
78827082019-10-30 14:31:482019-11-05 13:26:37N304399450
78927092019-10-30 14:31:482019-11-05 13:26:37N5739940