Overview

Dataset statistics

Number of variables7
Number of observations427
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.1 KiB
Average record size in memory60.3 B

Variable types

Numeric4
DateTime2
Boolean1

Dataset

Description충북농업기술원 농가 경영기록장 "바로바로"의 농업회계분석 정보제공 관련 자산, 부채, 감가상각비 등 계정과목 관리시스템으로 토지일련번호, 전표일련번호, 등록일시, 수정일시, 상태, 대변계정, 금액등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050287/fileData.do

Alerts

상태 has constant value ""Constant
토지일련번호 is highly overall correlated with 전표일련번호High correlation
전표일련번호 is highly overall correlated with 토지일련번호High correlation
전표일련번호 has unique valuesUnique
금액 has 52 (12.2%) zerosZeros

Reproduction

Analysis started2023-12-12 11:41:11.854062
Analysis finished2023-12-12 11:41:15.609633
Duration3.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

토지일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct344
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300.71663
Minimum58
Maximum524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:41:15.726414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum58
5-th percentile94.3
Q1201.5
median287
Q3413.5
95-th percentile497.4
Maximum524
Range466
Interquartile range (IQR)212

Descriptive statistics

Standard deviation128.3649
Coefficient of variation (CV)0.42686331
Kurtosis-1.1504544
Mean300.71663
Median Absolute Deviation (MAD)108
Skewness-0.014685291
Sum128406
Variance16477.546
MonotonicityIncreasing
2023-12-12T20:41:15.982281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
419 3
 
0.7%
100 3
 
0.7%
286 3
 
0.7%
283 3
 
0.7%
362 3
 
0.7%
464 3
 
0.7%
455 3
 
0.7%
432 3
 
0.7%
238 3
 
0.7%
237 3
 
0.7%
Other values (334) 397
93.0%
ValueCountFrequency (%)
58 1
0.2%
74 1
0.2%
75 2
0.5%
76 1
0.2%
77 2
0.5%
78 1
0.2%
79 1
0.2%
81 1
0.2%
82 1
0.2%
83 1
0.2%
ValueCountFrequency (%)
524 1
0.2%
523 1
0.2%
522 1
0.2%
521 1
0.2%
520 1
0.2%
519 1
0.2%
517 1
0.2%
515 2
0.5%
514 1
0.2%
513 1
0.2%

전표일련번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct427
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean790276.15
Minimum719638
Maximum877909
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:41:16.206656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum719638
5-th percentile721441
Q1758897
median774037
Q3824456.5
95-th percentile874434.4
Maximum877909
Range158271
Interquartile range (IQR)65559.5

Descriptive statistics

Standard deviation48285.996
Coefficient of variation (CV)0.061100156
Kurtosis-1.0980625
Mean790276.15
Median Absolute Deviation (MAD)40813
Skewness0.29080616
Sum3.3744792 × 108
Variance2.3315374 × 109
MonotonicityNot monotonic
2023-12-12T20:41:16.445028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
733638 1
 
0.2%
814856 1
 
0.2%
814850 1
 
0.2%
814638 1
 
0.2%
814637 1
 
0.2%
814445 1
 
0.2%
813954 1
 
0.2%
813133 1
 
0.2%
813131 1
 
0.2%
813129 1
 
0.2%
Other values (417) 417
97.7%
ValueCountFrequency (%)
719638 1
0.2%
719646 1
0.2%
719648 1
0.2%
719649 1
0.2%
719652 1
0.2%
719660 1
0.2%
719697 1
0.2%
719698 1
0.2%
719844 1
0.2%
719846 1
0.2%
ValueCountFrequency (%)
877909 1
0.2%
877065 1
0.2%
877061 1
0.2%
875340 1
0.2%
875338 1
0.2%
875336 1
0.2%
875332 1
0.2%
874946 1
0.2%
874942 1
0.2%
874941 1
0.2%

등록일시
Date

Distinct344
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2017-04-12 11:49:01
Maximum2019-11-10 20:26:13
2023-12-12T20:41:16.704331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:16.974869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

Distinct344
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
Minimum2017-04-12 11:49:01
Maximum2019-11-10 20:26:13
2023-12-12T20:41:17.247713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:17.522403image/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 size559.0 B
False
427 
ValueCountFrequency (%)
False 427
100.0%
2023-12-12T20:41:17.771982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

대변계정
Real number (ℝ)

Distinct26
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.22717
Minimum102
Maximum556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:41:17.934414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile102
Q1102
median155
Q3252
95-th percentile301
Maximum556
Range454
Interquartile range (IQR)150

Descriptive statistics

Standard deviation88.143648
Coefficient of variation (CV)0.50883271
Kurtosis3.089667
Mean173.22717
Median Absolute Deviation (MAD)53
Skewness1.5956225
Sum73968
Variance7769.3027
MonotonicityNot monotonic
2023-12-12T20:41:18.167645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
102 155
36.3%
155 113
26.5%
301 58
 
13.6%
252 48
 
11.2%
103 12
 
2.8%
202 7
 
1.6%
158 5
 
1.2%
106 4
 
0.9%
462 4
 
0.9%
556 3
 
0.7%
Other values (16) 18
 
4.2%
ValueCountFrequency (%)
102 155
36.3%
103 12
 
2.8%
104 2
 
0.5%
106 4
 
0.9%
107 1
 
0.2%
109 2
 
0.5%
112 1
 
0.2%
118 1
 
0.2%
121 1
 
0.2%
151 1
 
0.2%
ValueCountFrequency (%)
556 3
 
0.7%
555 1
 
0.2%
504 1
 
0.2%
469 1
 
0.2%
462 4
 
0.9%
301 58
13.6%
252 48
11.2%
251 1
 
0.2%
210 1
 
0.2%
203 1
 
0.2%

금액
Real number (ℝ)

ZEROS 

Distinct185
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84793262
Minimum0
Maximum2.3 × 109
Zeros52
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2023-12-12T20:41:18.389189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12000000
median40000000
Q31 × 108
95-th percentile3 × 108
Maximum2.3 × 109
Range2.3 × 109
Interquartile range (IQR)98000000

Descriptive statistics

Standard deviation1.5781234 × 108
Coefficient of variation (CV)1.8611425
Kurtosis93.467528
Mean84793262
Median Absolute Deviation (MAD)39995000
Skewness7.5964887
Sum3.6206723 × 1010
Variance2.4904735 × 1016
MonotonicityNot monotonic
2023-12-12T20:41:18.664884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52
 
12.2%
100000000 24
 
5.6%
30000000 14
 
3.3%
150000000 12
 
2.8%
40000000 9
 
2.1%
80000000 9
 
2.1%
50000000 9
 
2.1%
25000000 8
 
1.9%
200000000 8
 
1.9%
500000 8
 
1.9%
Other values (175) 274
64.2%
ValueCountFrequency (%)
0 52
12.2%
4 1
 
0.2%
10 1
 
0.2%
12 1
 
0.2%
500 1
 
0.2%
600 3
 
0.7%
1000 5
 
1.2%
4500 1
 
0.2%
4760 1
 
0.2%
5000 3
 
0.7%
ValueCountFrequency (%)
2300000000 1
 
0.2%
900000000 1
 
0.2%
800000000 1
 
0.2%
580000000 1
 
0.2%
504000000 1
 
0.2%
500000000 3
0.7%
497798400 1
 
0.2%
476666000 1
 
0.2%
450000000 1
 
0.2%
400000000 4
0.9%

Interactions

2023-12-12T20:41:14.580831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:12.118358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:12.773867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.012372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.728516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:12.275316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:13.446180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.143959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.953260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:12.457668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:13.664324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.313542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:15.140036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:12.610307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:13.844996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:41:14.449137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:41:18.843044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
토지일련번호전표일련번호대변계정금액
토지일련번호1.0000.9750.3860.000
전표일련번호0.9751.0000.3540.240
대변계정0.3860.3541.0000.000
금액0.0000.2400.0001.000
2023-12-12T20:41:19.017990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
토지일련번호전표일련번호대변계정금액
토지일련번호1.0000.9530.0990.085
전표일련번호0.9531.0000.1220.114
대변계정0.0990.1221.0000.228
금액0.0850.1140.2281.000

Missing values

2023-12-12T20:41:15.328598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:41:15.529228image/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

토지일련번호전표일련번호등록일시수정일시상태대변계정금액
0587336382017-07-03 16:22:542017-07-03 16:22:54N301600
1747196382017-04-12 11:49:012017-04-12 11:49:01N155120000000
2757196972017-04-12 14:01:222017-04-12 14:01:22N10220000000
3757196982017-04-12 14:01:222017-04-12 14:01:22N10625000000
4767196462017-04-12 11:52:392017-04-12 11:52:39N102150000000
5777196492017-04-12 11:52:512017-04-12 11:52:51N102300000
6777196482017-04-12 11:52:512017-04-12 11:52:51N102300000
7787196522017-04-12 11:54:012017-04-12 11:54:01N1020
8797196602017-04-12 11:57:052017-04-12 11:57:05N10276000000
9817198442017-04-13 11:35:172017-04-13 11:35:17N1020
토지일련번호전표일련번호등록일시수정일시상태대변계정금액
4175148744352019-10-30 14:19:292019-10-30 14:19:29N10224000000
4185158744372019-10-30 14:19:312019-10-30 14:19:31N252500000
4195158744382019-10-30 14:19:312019-10-30 14:19:31N102500000
4205178744462019-10-30 14:19:582019-10-30 14:19:58N106500000
4215198747882019-10-30 19:32:382019-10-30 19:32:38N30145000000
4225208747622019-10-30 19:32:212019-10-30 19:32:21N301130000000
4235218747602019-10-30 19:32:162019-10-30 19:32:16N4621200000
4245228770612019-11-06 22:37:392019-11-06 22:37:39N10255000000
4255238770652019-11-06 22:38:432019-11-06 22:38:43N10211000000
4265248779092019-11-10 20:26:132019-11-10 20:26:13N252190000000