Overview

Dataset statistics

Number of variables5
Number of observations279
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory44.5 B

Variable types

Numeric4
Text1

Dataset

Description충청남도 청양군의 농기계임대사업관리시스템의 농기계 기종에 관한 정보로 테이블관리번호, 코드, 코드1, 코드2, 코드명에 관한 데이터를 나타냅니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=330&beforeMenuCd=DOM_000000201001001000&publicdatapk=15089534

Alerts

테이블관리번호 is highly overall correlated with 코드 and 1 other fieldsHigh correlation
코드 is highly overall correlated with 테이블관리번호 and 1 other fieldsHigh correlation
코드1 is highly overall correlated with 테이블관리번호 and 1 other fieldsHigh correlation
테이블관리번호 has unique valuesUnique
코드 has unique valuesUnique
코드2 has 159 (57.0%) zerosZeros

Reproduction

Analysis started2024-01-09 21:20:37.019910
Analysis finished2024-01-09 21:20:38.310808
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

테이블관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct279
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140
Minimum1
Maximum279
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-10T06:20:38.364845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.9
Q170.5
median140
Q3209.5
95-th percentile265.1
Maximum279
Range278
Interquartile range (IQR)139

Descriptive statistics

Standard deviation80.684571
Coefficient of variation (CV)0.57631836
Kurtosis-1.2
Mean140
Median Absolute Deviation (MAD)70
Skewness0
Sum39060
Variance6510
MonotonicityStrictly increasing
2024-01-10T06:20:38.478538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
185 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
184 1
 
0.4%
193 1
 
0.4%
Other values (269) 269
96.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
279 1
0.4%
278 1
0.4%
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%

코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct279
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13602.423
Minimum100
Maximum91200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-10T06:20:38.591100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile113.9
Q1701.5
median5500
Q322250
95-th percentile80310
Maximum91200
Range91100
Interquartile range (IQR)21548.5

Descriptive statistics

Standard deviation21116.383
Coefficient of variation (CV)1.5523986
Kurtosis6.6959136
Mean13602.423
Median Absolute Deviation (MAD)5297
Skewness2.6013031
Sum3795076
Variance4.4590163 × 108
MonotonicityNot monotonic
2024-01-10T06:20:38.706047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 1
 
0.4%
10600 1
 
0.4%
20400 1
 
0.4%
20300 1
 
0.4%
20200 1
 
0.4%
20100 1
 
0.4%
10900 1
 
0.4%
10800 1
 
0.4%
10500 1
 
0.4%
20600 1
 
0.4%
Other values (269) 269
96.4%
ValueCountFrequency (%)
100 1
0.4%
101 1
0.4%
102 1
0.4%
103 1
0.4%
104 1
0.4%
105 1
0.4%
106 1
0.4%
107 1
0.4%
108 1
0.4%
109 1
0.4%
ValueCountFrequency (%)
91200 1
0.4%
91100 1
0.4%
91000 1
0.4%
90900 1
0.4%
90800 1
0.4%
90700 1
0.4%
90600 1
0.4%
90500 1
0.4%
90400 1
0.4%
90300 1
0.4%

코드1
Real number (ℝ)

HIGH CORRELATION 

Distinct159
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.95341
Minimum1
Maximum912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-10T06:20:38.819243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median55
Q3222.5
95-th percentile803.1
Maximum912
Range911
Interquartile range (IQR)215.5

Descriptive statistics

Standard deviation211.19283
Coefficient of variation (CV)1.5534207
Kurtosis6.6943503
Mean135.95341
Median Absolute Deviation (MAD)53
Skewness2.6008629
Sum37931
Variance44602.411
MonotonicityNot monotonic
2024-01-10T06:20:38.922062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 43
 
15.4%
248 28
 
10.0%
7 22
 
7.9%
2 18
 
6.5%
8 8
 
2.9%
4 4
 
1.4%
78 4
 
1.4%
217 1
 
0.4%
211 1
 
0.4%
212 1
 
0.4%
Other values (149) 149
53.4%
ValueCountFrequency (%)
1 43
15.4%
2 18
6.5%
3 1
 
0.4%
4 4
 
1.4%
5 1
 
0.4%
6 1
 
0.4%
7 22
7.9%
8 8
 
2.9%
9 1
 
0.4%
10 1
 
0.4%
ValueCountFrequency (%)
912 1
0.4%
911 1
0.4%
910 1
0.4%
909 1
0.4%
908 1
0.4%
907 1
0.4%
906 1
0.4%
905 1
0.4%
904 1
0.4%
903 1
0.4%

코드2
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0824373
Minimum0
Maximum46
Zeros159
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-10T06:20:39.046592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q311.5
95-th percentile32.1
Maximum46
Range46
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation11.287783
Coefficient of variation (CV)1.593771
Kurtosis1.7539847
Mean7.0824373
Median Absolute Deviation (MAD)0
Skewness1.6262834
Sum1976
Variance127.41404
MonotonicityNot monotonic
2024-01-10T06:20:39.179940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 159
57.0%
1 7
 
2.5%
3 6
 
2.2%
2 5
 
1.8%
4 5
 
1.8%
6 5
 
1.8%
8 5
 
1.8%
25 4
 
1.4%
16 4
 
1.4%
15 4
 
1.4%
Other values (37) 75
26.9%
ValueCountFrequency (%)
0 159
57.0%
1 7
 
2.5%
2 5
 
1.8%
3 6
 
2.2%
4 5
 
1.8%
5 3
 
1.1%
6 5
 
1.8%
7 4
 
1.4%
8 5
 
1.8%
9 3
 
1.1%
ValueCountFrequency (%)
46 1
0.4%
45 1
0.4%
44 1
0.4%
43 1
0.4%
42 1
0.4%
41 1
0.4%
40 1
0.4%
39 1
0.4%
38 1
0.4%
37 1
0.4%

코드명
Text

Distinct233
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-01-10T06:20:39.448490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.3835125
Min length2

Characters and Unicode

Total characters1502
Distinct characters251
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)73.1%

Sample

1st row농용트랙터
2nd row결속기
3rd row결속볏짚절단기
4th row계사청소기
5th row구굴기
ValueCountFrequency (%)
비료살포기 4
 
1.4%
제초기 4
 
1.4%
동력분무기 4
 
1.4%
휴립피복기 3
 
1.1%
파종기 3
 
1.1%
배토기 3
 
1.1%
잔가지파쇄기 3
 
1.1%
중경제초기 3
 
1.1%
비닐피복기 3
 
1.1%
퇴비살포기 3
 
1.1%
Other values (223) 246
88.2%
2024-01-10T06:20:39.796549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 231
 
15.4%
용 47
 
3.1%
동 38
 
2.5%
농 38
 
2.5%
제 32
 
2.1%
력 29
 
1.9%
수 28
 
1.9%
물 21
 
1.4%
이 21
 
1.4%
자 20
 
1.3%
Other values (241) 997
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1496
99.6%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 231
 
15.4%
용 47
 
3.1%
동 38
 
2.5%
농 38
 
2.5%
제 32
 
2.1%
력 29
 
1.9%
수 28
 
1.9%
물 21
 
1.4%
이 21
 
1.4%
자 20
 
1.3%
Other values (239) 991
66.2%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1496
99.6%
Common 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 231
 
15.4%
용 47
 
3.1%
동 38
 
2.5%
농 38
 
2.5%
제 32
 
2.1%
력 29
 
1.9%
수 28
 
1.9%
물 21
 
1.4%
이 21
 
1.4%
자 20
 
1.3%
Other values (239) 991
66.2%
Common
ValueCountFrequency (%)
) 3
50.0%
( 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1496
99.6%
ASCII 6
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 231
 
15.4%
용 47
 
3.1%
동 38
 
2.5%
농 38
 
2.5%
제 32
 
2.1%
력 29
 
1.9%
수 28
 
1.9%
물 21
 
1.4%
이 21
 
1.4%
자 20
 
1.3%
Other values (239) 991
66.2%
ASCII
ValueCountFrequency (%)
) 3
50.0%
( 3
50.0%

Interactions

2024-01-10T06:20:37.941507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.217201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.466599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.706582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:38.003357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.284967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.530940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.767823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:38.061898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.347214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.586997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.827140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:38.122129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.407798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.644254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:37.883946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:20:39.872904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
테이블관리번호코드코드1코드2
테이블관리번호1.0000.9440.9440.729
코드0.9441.0001.0000.000
코드10.9441.0001.0000.000
코드20.7290.0000.0001.000
2024-01-10T06:20:39.946715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
테이블관리번호코드코드1코드2
테이블관리번호1.0001.0000.997-0.473
코드1.0001.0000.997-0.473
코드10.9970.9971.000-0.498
코드2-0.473-0.473-0.4981.000

Missing values

2024-01-10T06:20:38.206176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:20:38.281748image/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

테이블관리번호코드코드1코드2코드명
0110010농용트랙터
1210111결속기
2310212결속볏짚절단기
3410313계사청소기
4510414구굴기
5610515굴삭기
6710616그래플
7810717그레이더
8910818논두렁조성기
91010919농용크레인
테이블관리번호코드코드1코드2코드명
269270908009080적심기
270271909009090제설기
271272910009100채소자동결속기
272273911009110채소정식기
273274912009120콩수확기
274275801008010밀링
275276802008020범용선반
276277803008030승용경운기
277278804008040지계차
278279805008050추레라