Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells9903
Missing cells (%)19.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

Numeric1
DateTime2
Boolean1
Text1

Dataset

Description충청북도 농업기술원 농가경영기록장(농가의 소득을 증진시킬 수 있는 회원전용 농가경영 관리 프로그램)의 수입지출관련 이용자 접속기록, 거래, 거래처 등의 관리시스템으로 일련번호, 등록일시, 수정일시, 상태코드, 비고 등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050327/fileData.do

Alerts

상태코드 has constant value ""Constant
비고 has 9903 (99.0%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:05:53.524671
Analysis finished2023-12-12 02:05:54.261979
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32718.97
Minimum41
Maximum61510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:05:54.348548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile3828.85
Q116524.75
median34652
Q348083.25
95-th percentile58880.65
Maximum61510
Range61469
Interquartile range (IQR)31558.5

Descriptive statistics

Standard deviation17860.288
Coefficient of variation (CV)0.54586951
Kurtosis-1.1942648
Mean32718.97
Median Absolute Deviation (MAD)15854
Skewness-0.17539167
Sum3.271897 × 108
Variance3.189899 × 108
MonotonicityNot monotonic
2023-12-12T11:05:54.532509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52606 1
 
< 0.1%
5872 1
 
< 0.1%
8625 1
 
< 0.1%
54163 1
 
< 0.1%
42782 1
 
< 0.1%
47089 1
 
< 0.1%
4991 1
 
< 0.1%
31828 1
 
< 0.1%
11822 1
 
< 0.1%
43381 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
41 1
< 0.1%
43 1
< 0.1%
60 1
< 0.1%
77 1
< 0.1%
84 1
< 0.1%
93 1
< 0.1%
217 1
< 0.1%
224 1
< 0.1%
227 1
< 0.1%
249 1
< 0.1%
ValueCountFrequency (%)
61510 1
< 0.1%
61509 1
< 0.1%
61505 1
< 0.1%
61494 1
< 0.1%
61490 1
< 0.1%
61482 1
< 0.1%
61480 1
< 0.1%
61477 1
< 0.1%
61468 1
< 0.1%
61465 1
< 0.1%

등록일시
Date

Distinct931
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-03-09 19:08:00
Maximum2019-11-10 21:57:00
2023-12-12T11:05:54.706991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:54.869685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Date

Distinct935
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-03-09 19:08:00
Maximum2019-11-10 21:57:00
2023-12-12T11:05:55.040308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:05:55.203320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상태코드
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2023-12-12T11:05:55.316686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

비고
Text

MISSING 

Distinct95
Distinct (%)97.9%
Missing9903
Missing (%)99.0%
Memory size156.2 KiB
2023-12-12T11:05:55.589466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length20
Mean length8.1340206
Min length2

Characters and Unicode

Total characters789
Distinct characters255
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)95.9%

Sample

1st row모종판매
2nd row박사장
3rd row관내농협
4th row단양 소백농협
5th row모종, 농약 등
ValueCountFrequency (%)
외환은행 2
 
1.2%
농약 2
 
1.2%
카네이션클럽 2
 
1.2%
및 2
 
1.2%
배추 2
 
1.2%
알땅콩2 1
 
0.6%
붉은팥2 1
 
0.6%
대추칼라 1
 
0.6%
750그람 1
 
0.6%
20팩 1
 
0.6%
Other values (147) 147
90.7%
2023-12-12T11:05:56.043510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71
 
9.0%
0 32
 
4.1%
2 26
 
3.3%
농 16
 
2.0%
1 16
 
2.0%
4 15
 
1.9%
리 13
 
1.6%
5 12
 
1.5%
기 12
 
1.5%
3 11
 
1.4%
Other values (245) 565
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 534
67.7%
Decimal Number 139
 
17.6%
Space Separator 71
 
9.0%
Other Punctuation 25
 
3.2%
Dash Punctuation 7
 
0.9%
Lowercase Letter 6
 
0.8%
Uppercase Letter 3
 
0.4%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 16
 
3.0%
리 13
 
2.4%
기 12
 
2.2%
자 10
 
1.9%
스 8
 
1.5%
포 7
 
1.3%
약 7
 
1.3%
마 7
 
1.3%
지 7
 
1.3%
매 7
 
1.3%
Other values (222) 440
82.4%
Decimal Number
ValueCountFrequency (%)
0 32
23.0%
2 26
18.7%
1 16
11.5%
4 15
10.8%
5 12
 
8.6%
3 11
 
7.9%
8 10
 
7.2%
6 8
 
5.8%
7 6
 
4.3%
9 3
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 10
40.0%
, 10
40.0%
: 2
 
8.0%
/ 2
 
8.0%
% 1
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
k 2
33.3%
m 2
33.3%
g 2
33.3%
Space Separator
ValueCountFrequency (%)
71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 534
67.7%
Common 246
31.2%
Latin 9
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 16
 
3.0%
리 13
 
2.4%
기 12
 
2.2%
자 10
 
1.9%
스 8
 
1.5%
포 7
 
1.3%
약 7
 
1.3%
마 7
 
1.3%
지 7
 
1.3%
매 7
 
1.3%
Other values (222) 440
82.4%
Common
ValueCountFrequency (%)
71
28.9%
0 32
13.0%
2 26
 
10.6%
1 16
 
6.5%
4 15
 
6.1%
5 12
 
4.9%
3 11
 
4.5%
. 10
 
4.1%
, 10
 
4.1%
8 10
 
4.1%
Other values (9) 33
13.4%
Latin
ValueCountFrequency (%)
I 3
33.3%
k 2
22.2%
m 2
22.2%
g 2
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 534
67.7%
ASCII 255
32.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71
27.8%
0 32
12.5%
2 26
 
10.2%
1 16
 
6.3%
4 15
 
5.9%
5 12
 
4.7%
3 11
 
4.3%
. 10
 
3.9%
, 10
 
3.9%
8 10
 
3.9%
Other values (13) 42
16.5%
Hangul
ValueCountFrequency (%)
농 16
 
3.0%
리 13
 
2.4%
기 12
 
2.2%
자 10
 
1.9%
스 8
 
1.5%
포 7
 
1.3%
약 7
 
1.3%
마 7
 
1.3%
지 7
 
1.3%
매 7
 
1.3%
Other values (222) 440
82.4%

Interactions

2023-12-12T11:05:53.886168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:05:56.143275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호비고
일련번호1.0001.000
비고1.0001.000

Missing values

2023-12-12T11:05:54.074423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:05:54.209194image/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

일련번호등록일시수정일시상태코드비고
43165526062017-03-09 19:082017-03-09 19:08N<NA>
48924585652019-02-03 20:582019-02-03 20:58N<NA>
13721172102017-03-09 19:082017-03-09 19:08N<NA>
341846602017-03-09 19:082017-03-09 19:08N<NA>
647188872017-03-09 19:082017-03-09 19:08N<NA>
9800124882017-03-09 19:082017-03-09 19:08N<NA>
39103482952017-03-09 19:082017-03-09 19:08N<NA>
559077512017-03-09 19:082017-03-09 19:08N<NA>
16039195542017-03-09 19:082017-03-09 19:08N<NA>
14733182382017-03-09 19:082017-03-09 19:08N<NA>
일련번호등록일시수정일시상태코드비고
49339589912019-04-18 14:542019-04-18 14:54N<NA>
279940092017-03-09 19:082017-03-09 19:08N<NA>
19450277772017-03-09 19:082017-03-09 19:08N<NA>
41386507972017-03-09 19:082017-03-09 19:08N<NA>
20747291002017-03-09 19:082017-03-09 19:08N<NA>
34207431502017-03-09 19:082017-03-09 19:08N<NA>
28414371172017-03-09 19:082017-03-09 19:08N<NA>
43112525532017-03-09 19:082017-03-09 19:08N<NA>
37983469982017-03-09 19:082017-03-09 19:08N<NA>
22186306512017-03-09 19:082017-03-09 19:08N<NA>