Overview

Dataset statistics

Number of variables7
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory61.6 B

Variable types

Numeric3
Text2
Categorical2

Dataset

Description경기도 광주시 농업기술센터에서 보유하고 있는 농기계 현황에 대한 데이터로 기종명, 모델명, 수량, 임대료 등을 제공합니다.
URLhttps://www.data.go.kr/data/3079337/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:22:02.674966
Analysis finished2023-12-12 23:22:03.664704
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.5
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-13T08:22:03.721500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.15
Q121.75
median42.5
Q363.25
95-th percentile79.85
Maximum84
Range83
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation24.392622
Coefficient of variation (CV)0.57394404
Kurtosis-1.2
Mean42.5
Median Absolute Deviation (MAD)21
Skewness0
Sum3570
Variance595
MonotonicityStrictly increasing
2023-12-13T08:22:03.824681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%

기종명
Text

Distinct58
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T08:22:04.016774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.297619
Min length3

Characters and Unicode

Total characters529
Distinct characters104
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)51.2%

Sample

1st row트랙터
2nd row트랙터
3rd row트랙터
4th row트랙터
5th row콤바인
ValueCountFrequency (%)
보행관리기 6
 
6.6%
땅속수확기(트 5
 
5.5%
트랙터 4
 
4.4%
승용이앙기 3
 
3.3%
콤바인 3
 
3.3%
동력경운기 3
 
3.3%
콩탈곡기(모 3
 
3.3%
체인형 3
 
3.3%
로터베이터 2
 
2.2%
돌수집기 2
 
2.2%
Other values (51) 57
62.6%
2023-12-13T08:22:04.338895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 72
 
13.6%
( 36
 
6.8%
) 36
 
6.8%
관 17
 
3.2%
트 17
 
3.2%
터 15
 
2.8%
경 13
 
2.5%
동 13
 
2.5%
리 12
 
2.3%
이 12
 
2.3%
Other values (94) 286
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
83.9%
Open Punctuation 36
 
6.8%
Close Punctuation 36
 
6.8%
Space Separator 11
 
2.1%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 72
 
16.2%
관 17
 
3.8%
트 17
 
3.8%
터 15
 
3.4%
경 13
 
2.9%
동 13
 
2.9%
리 12
 
2.7%
이 12
 
2.7%
수 11
 
2.5%
곡 9
 
2.0%
Other values (89) 253
57.0%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
4 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
83.9%
Common 85
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 72
 
16.2%
관 17
 
3.8%
트 17
 
3.8%
터 15
 
3.4%
경 13
 
2.9%
동 13
 
2.9%
리 12
 
2.7%
이 12
 
2.7%
수 11
 
2.5%
곡 9
 
2.0%
Other values (89) 253
57.0%
Common
ValueCountFrequency (%)
( 36
42.4%
) 36
42.4%
11
 
12.9%
6 1
 
1.2%
4 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
83.9%
ASCII 85
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 72
 
16.2%
관 17
 
3.8%
트 17
 
3.8%
터 15
 
3.4%
경 13
 
2.9%
동 13
 
2.9%
리 12
 
2.7%
이 12
 
2.7%
수 11
 
2.5%
곡 9
 
2.0%
Other values (89) 253
57.0%
ASCII
ValueCountFrequency (%)
( 36
42.4%
) 36
42.4%
11
 
12.9%
6 1
 
1.2%
4 1
 
1.2%

모델명
Text

Distinct75
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T08:22:04.576654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.8214286
Min length4

Characters and Unicode

Total characters573
Distinct characters43
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)82.1%

Sample

1st rowNS550SC
2nd rowDK450RG
3rd rowCK400
4th rowRX730VC5
5th rowDSM72GB
ValueCountFrequency (%)
ams-880sm 4
 
4.3%
dt10e 3
 
3.2%
amc-1000 2
 
2.2%
r60d 2
 
2.2%
hg10a 2
 
2.2%
ys 2
 
2.2%
2600 2
 
2.2%
tc 2
 
2.2%
am-180 1
 
1.1%
ap25 1
 
1.1%
Other values (72) 72
77.4%
2023-12-13T08:22:04.963344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 106
18.5%
- 56
 
9.8%
1 40
 
7.0%
S 34
 
5.9%
D 31
 
5.4%
5 21
 
3.7%
R 20
 
3.5%
8 19
 
3.3%
T 18
 
3.1%
6 16
 
2.8%
Other values (33) 212
37.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 255
44.5%
Decimal Number 244
42.6%
Dash Punctuation 56
 
9.8%
Space Separator 9
 
1.6%
Other Letter 8
 
1.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 34
13.3%
D 31
12.2%
R 20
 
7.8%
T 18
 
7.1%
A 16
 
6.3%
G 14
 
5.5%
M 14
 
5.5%
C 13
 
5.1%
K 12
 
4.7%
H 11
 
4.3%
Other values (13) 72
28.2%
Decimal Number
ValueCountFrequency (%)
0 106
43.4%
1 40
 
16.4%
5 21
 
8.6%
8 19
 
7.8%
6 16
 
6.6%
2 16
 
6.6%
3 11
 
4.5%
4 7
 
2.9%
7 7
 
2.9%
9 1
 
0.4%
Other Letter
ValueCountFrequency (%)
식 2
25.0%
홀 1
12.5%
랙 1
12.5%
블 1
12.5%
터 1
12.5%
조 1
12.5%
모 1
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 310
54.1%
Latin 255
44.5%
Hangul 8
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 34
13.3%
D 31
12.2%
R 20
 
7.8%
T 18
 
7.1%
A 16
 
6.3%
G 14
 
5.5%
M 14
 
5.5%
C 13
 
5.1%
K 12
 
4.7%
H 11
 
4.3%
Other values (13) 72
28.2%
Common
ValueCountFrequency (%)
0 106
34.2%
- 56
18.1%
1 40
 
12.9%
5 21
 
6.8%
8 19
 
6.1%
6 16
 
5.2%
2 16
 
5.2%
3 11
 
3.5%
9
 
2.9%
4 7
 
2.3%
Other values (3) 9
 
2.9%
Hangul
ValueCountFrequency (%)
식 2
25.0%
홀 1
12.5%
랙 1
12.5%
블 1
12.5%
터 1
12.5%
조 1
12.5%
모 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 565
98.6%
Hangul 8
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 106
18.8%
- 56
 
9.9%
1 40
 
7.1%
S 34
 
6.0%
D 31
 
5.5%
5 21
 
3.7%
R 20
 
3.5%
8 19
 
3.4%
T 18
 
3.2%
6 16
 
2.8%
Other values (26) 204
36.1%
Hangul
ValueCountFrequency (%)
식 2
25.0%
홀 1
12.5%
랙 1
12.5%
블 1
12.5%
터 1
12.5%
조 1
12.5%
모 1
12.5%

수량
Categorical

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
1
57 
2
24 
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 57
67.9%
2 24
28.6%
3 3
 
3.6%

Length

2023-12-13T08:22:05.084485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:22:05.172994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 57
67.9%
2 24
28.6%
3 3
 
3.6%

임대료
Real number (ℝ)

Distinct15
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35714.286
Minimum5000
Maximum210000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-13T08:22:05.288416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile5750
Q112000
median15000
Q325000
95-th percentile172500
Maximum210000
Range205000
Interquartile range (IQR)13000

Descriptive statistics

Standard deviation49304.457
Coefficient of variation (CV)1.3805248
Kurtosis5.2007809
Mean35714.286
Median Absolute Deviation (MAD)5000
Skewness2.4476455
Sum3000000
Variance2.4309294 × 109
MonotonicityNot monotonic
2023-12-13T08:22:05.398105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
20000 16
19.0%
12000 15
17.9%
10000 13
15.5%
15000 11
13.1%
25000 5
 
6.0%
5000 5
 
6.0%
100000 4
 
4.8%
200000 3
 
3.6%
60000 3
 
3.6%
130000 2
 
2.4%
Other values (5) 7
8.3%
ValueCountFrequency (%)
5000 5
 
6.0%
10000 13
15.5%
12000 15
17.9%
15000 11
13.1%
20000 16
19.0%
25000 5
 
6.0%
30000 2
 
2.4%
40000 2
 
2.4%
60000 3
 
3.6%
85000 1
 
1.2%
ValueCountFrequency (%)
210000 1
 
1.2%
200000 3
3.6%
180000 1
 
1.2%
130000 2
 
2.4%
100000 4
4.8%
85000 1
 
1.2%
60000 3
3.6%
40000 2
 
2.4%
30000 2
 
2.4%
25000 5
6.0%

구입연도
Real number (ℝ)

Distinct11
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.3095
Minimum2007
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-13T08:22:05.517003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2010
Q12017
median2019
Q32020.25
95-th percentile2022
Maximum2023
Range16
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation3.6104807
Coefficient of variation (CV)0.0017888637
Kurtosis2.5338252
Mean2018.3095
Median Absolute Deviation (MAD)2
Skewness-1.5616574
Sum169538
Variance13.035571
MonotonicityNot monotonic
2023-12-13T08:22:05.622895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2020 16
19.0%
2019 14
16.7%
2016 10
11.9%
2021 9
10.7%
2022 8
9.5%
2017 8
9.5%
2018 7
8.3%
2023 4
 
4.8%
2010 4
 
4.8%
2007 3
 
3.6%
ValueCountFrequency (%)
2007 3
 
3.6%
2010 4
 
4.8%
2012 1
 
1.2%
2016 10
11.9%
2017 8
9.5%
2018 7
8.3%
2019 14
16.7%
2020 16
19.0%
2021 9
10.7%
2022 8
9.5%
ValueCountFrequency (%)
2023 4
 
4.8%
2022 8
9.5%
2021 9
10.7%
2020 16
19.0%
2019 14
16.7%
2018 7
8.3%
2017 8
9.5%
2016 10
11.9%
2012 1
 
1.2%
2010 4
 
4.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-08-25
84 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-25
2nd row2023-08-25
3rd row2023-08-25
4th row2023-08-25
5th row2023-08-25

Common Values

ValueCountFrequency (%)
2023-08-25 84
100.0%

Length

2023-12-13T08:22:05.732602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:22:05.829184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-25 84
100.0%

Interactions

2023-12-13T08:22:03.292690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:02.922897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:03.098238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:03.363075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:02.976858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:03.155290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:03.429436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:03.033585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:22:03.218616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:22:05.885597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기종명모델명수량임대료구입연도
연번1.0000.9870.9830.4290.5130.329
기종명0.9871.0001.0000.9330.0000.752
모델명0.9831.0001.0000.0001.0000.507
수량0.4290.9330.0001.0000.0000.197
임대료0.5130.0001.0000.0001.0000.000
구입연도0.3290.7520.5070.1970.0001.000
2023-12-13T08:22:05.977757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번임대료구입연도수량
연번1.000-0.4620.0360.271
임대료-0.4621.0000.0640.000
구입연도0.0360.0641.0000.183
수량0.2710.0000.1831.000

Missing values

2023-12-13T08:22:03.543426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:22:03.629397image/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

연번기종명모델명수량임대료구입연도데이터기준일자
01트랙터NS550SC118000020202023-08-25
12트랙터DK450RG113000020212023-08-25
23트랙터CK400110000020162023-08-25
34트랙터RX730VC5120000020232023-08-25
45콤바인DSM72GB120000020162023-08-25
56콤바인KC-800120000020182023-08-25
67콤바인ER575K121000020222023-08-25
78승용이앙기ERP60DZ110000020162023-08-25
89승용이앙기RGO-60DYH110000020192023-08-25
910승용이앙기RGO-60H18500020202023-08-25
연번기종명모델명수량임대료구입연도데이터기준일자
7475잡곡정선기SB-200GI11200020192023-08-25
7576돌수집기GWD-1400T12500020202023-08-25
7677돌수집기GWD-1100D12500020222023-08-25
7778땅속수확기(트) 진동형HD-D1600G12000020202023-08-25
7879땅속수확기(트) 진동형HD-C1000G11500020202023-08-25
7980줄기절단기(트)JYSC-150012000020202023-08-25
8081동력파종기SW-1012000020202023-08-25
8182씨앗파종기SH-200021000020202023-08-25
8283탈망기JK-53011200020202023-08-25
8384지주설치기RD-021M21500020222023-08-25