Overview

Dataset statistics

Number of variables9
Number of observations112
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory75.2 B

Variable types

Text3
Categorical4
Numeric1
Boolean1

Dataset

Description산림과학기술정보서비스 참여연구기관의 비목코드에 관한 데이터 참여연구기관은 대학, 산업체, 연구기관, 협회, 기타 등으로 구분할 수 있음
Author산림청
URLhttps://www.data.go.kr/data/15040532/fileData.do

Alerts

최종수정일시 is highly overall correlated with 부모비목코드 and 2 other fieldsHigh correlation
최초작성일시 is highly overall correlated with 부모비목코드 and 1 other fieldsHigh correlation
사용여부 is highly overall correlated with 부모비목코드 and 1 other fieldsHigh correlation
부모비목코드 is highly overall correlated with 정렬순서 and 4 other fieldsHigh correlation
정렬순서 is highly overall correlated with 부모비목코드High correlation
비목레벨 is highly overall correlated with 부모비목코드High correlation
사용여부 is highly imbalanced (92.6%)Imbalance
비목코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:47:17.818202
Analysis finished2023-12-12 23:47:18.817819
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

비목코드
Text

UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T08:47:19.057349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.4375
Min length9

Characters and Unicode

Total characters1057
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)100.0%

Sample

1st rowC010503000
2nd rowC010504000
3rd rowC010601000
4th rowC010602000
5th rowC010603000
ValueCountFrequency (%)
c010503000 1
 
0.9%
c010504000 1
 
0.9%
102020700 1
 
0.9%
102020600 1
 
0.9%
102020500 1
 
0.9%
102020400 1
 
0.9%
102020300 1
 
0.9%
102020200 1
 
0.9%
102020100 1
 
0.9%
102020000 1
 
0.9%
Other values (102) 102
91.1%
2023-12-13T08:47:19.555888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 632
59.8%
1 196
 
18.5%
C 49
 
4.6%
2 48
 
4.5%
4 31
 
2.9%
3 30
 
2.8%
6 26
 
2.5%
5 21
 
2.0%
7 14
 
1.3%
8 5
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1008
95.4%
Uppercase Letter 49
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 632
62.7%
1 196
 
19.4%
2 48
 
4.8%
4 31
 
3.1%
3 30
 
3.0%
6 26
 
2.6%
5 21
 
2.1%
7 14
 
1.4%
8 5
 
0.5%
9 5
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
C 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1008
95.4%
Latin 49
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 632
62.7%
1 196
 
19.4%
2 48
 
4.8%
4 31
 
3.1%
3 30
 
3.0%
6 26
 
2.6%
5 21
 
2.1%
7 14
 
1.4%
8 5
 
0.5%
9 5
 
0.5%
Latin
ValueCountFrequency (%)
C 49
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 632
59.8%
1 196
 
18.5%
C 49
 
4.6%
2 48
 
4.5%
4 31
 
2.9%
3 30
 
2.8%
6 26
 
2.5%
5 21
 
2.0%
7 14
 
1.3%
8 5
 
0.5%

비목레벨
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
3
84 
2
20 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 84
75.0%
2 20
 
17.9%
1 8
 
7.1%

Length

2023-12-13T08:47:19.702826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:47:19.798374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 84
75.0%
2 20
 
17.9%
1 8
 
7.1%

비목코드명
Text

Distinct76
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T08:47:20.041599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length13
Mean length5.6785714
Min length1

Characters and Unicode

Total characters636
Distinct characters129
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)49.1%

Sample

1st row시제(작)품비
2nd row계
3rd row국외여비
4th row인쇄비
5th row공공요금/수수료
ValueCountFrequency (%)
소계 9
 
6.6%
계 7
 
5.1%
직접비 4
 
2.9%
인건비 3
 
2.2%
및 3
 
2.2%
간접비 3
 
2.2%
문헌구입비 2
 
1.5%
연구활동비 2
 
1.5%
운영비 2
 
1.5%
재료비 2
 
1.5%
Other values (84) 99
72.8%
2023-12-13T08:47:20.421273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 85
 
13.4%
24
 
3.8%
구 24
 
3.8%
연 23
 
3.6%
계 17
 
2.7%
지 16
 
2.5%
기 15
 
2.4%
· 14
 
2.2%
료 13
 
2.0%
인 12
 
1.9%
Other values (119) 393
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 584
91.8%
Space Separator 24
 
3.8%
Other Punctuation 18
 
2.8%
Open Punctuation 5
 
0.8%
Close Punctuation 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 85
 
14.6%
구 24
 
4.1%
연 23
 
3.9%
계 17
 
2.9%
지 16
 
2.7%
기 15
 
2.6%
료 13
 
2.2%
인 12
 
2.1%
시 11
 
1.9%
활 10
 
1.7%
Other values (112) 358
61.3%
Other Punctuation
ValueCountFrequency (%)
· 14
77.8%
/ 4
 
22.2%
Open Punctuation
ValueCountFrequency (%)
( 4
80.0%
[ 1
 
20.0%
Close Punctuation
ValueCountFrequency (%)
) 4
80.0%
] 1
 
20.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 584
91.8%
Common 52
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 85
 
14.6%
구 24
 
4.1%
연 23
 
3.9%
계 17
 
2.9%
지 16
 
2.7%
기 15
 
2.6%
료 13
 
2.2%
인 12
 
2.1%
시 11
 
1.9%
활 10
 
1.7%
Other values (112) 358
61.3%
Common
ValueCountFrequency (%)
24
46.2%
· 14
26.9%
( 4
 
7.7%
) 4
 
7.7%
/ 4
 
7.7%
] 1
 
1.9%
[ 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 584
91.8%
ASCII 38
 
6.0%
None 14
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 85
 
14.6%
구 24
 
4.1%
연 23
 
3.9%
계 17
 
2.9%
지 16
 
2.7%
기 15
 
2.6%
료 13
 
2.2%
인 12
 
2.1%
시 11
 
1.9%
활 10
 
1.7%
Other values (112) 358
61.3%
ASCII
ValueCountFrequency (%)
24
63.2%
( 4
 
10.5%
) 4
 
10.5%
/ 4
 
10.5%
] 1
 
2.6%
[ 1
 
2.6%
None
ValueCountFrequency (%)
· 14
100.0%

부모비목코드
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
101040000
16 
C010600000
16 
C010000000
9 
102020000
9 
<NA>
8 
Other values (20)
54 

Length

Max length10
Median length9
Mean length9.0535714
Min length4

Unique

Unique10 ?
Unique (%)8.9%

Sample

1st rowC010500000
2nd rowC010500000
3rd rowC010600000
4th rowC010600000
5th rowC010600000

Common Values

ValueCountFrequency (%)
101040000 16
14.3%
C010600000 16
14.3%
C010000000 9
 
8.0%
102020000 9
 
8.0%
<NA> 8
 
7.1%
C010700000 7
 
6.2%
101050000 7
 
6.2%
101030000 6
 
5.4%
101000000 4
 
3.6%
102030000 4
 
3.6%
Other values (15) 26
23.2%

Length

2023-12-13T08:47:20.563975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
101040000 16
14.3%
c010600000 16
14.3%
c010000000 9
 
8.0%
102020000 9
 
8.0%
na 8
 
7.1%
c010700000 7
 
6.2%
101050000 7
 
6.2%
101030000 6
 
5.4%
101000000 4
 
3.6%
102030000 4
 
3.6%
Other values (15) 26
23.2%

정렬순서
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)50.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.169643
Minimum1
Maximum101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T08:47:20.686200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18.75
median20.5
Q334
95-th percentile52.45
Maximum101
Range100
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation17.531895
Coefficient of variation (CV)0.75667526
Kurtosis2.0509552
Mean23.169643
Median Absolute Deviation (MAD)12.5
Skewness1.0517081
Sum2595
Variance307.36736
MonotonicityNot monotonic
2023-12-13T08:47:20.842252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 4
 
3.6%
1 4
 
3.6%
3 4
 
3.6%
2 4
 
3.6%
29 3
 
2.7%
6 3
 
2.7%
4 3
 
2.7%
8 3
 
2.7%
7 3
 
2.7%
9 3
 
2.7%
Other values (47) 78
69.6%
ValueCountFrequency (%)
1 4
3.6%
2 4
3.6%
3 4
3.6%
4 3
2.7%
5 4
3.6%
6 3
2.7%
7 3
2.7%
8 3
2.7%
9 3
2.7%
10 3
2.7%
ValueCountFrequency (%)
101 1
0.9%
56 1
0.9%
55 2
1.8%
54 1
0.9%
53 1
0.9%
52 1
0.9%
51 2
1.8%
50 1
0.9%
49 1
0.9%
48 1
0.9%

사용여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size244.0 B
True
111 
False
 
1
ValueCountFrequency (%)
True 111
99.1%
False 1
 
0.9%
2023-12-13T08:47:20.969769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전체비목코드명
Text

Distinct93
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T08:47:21.139725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length26.5
Mean length17.642857
Min length3

Characters and Unicode

Total characters1976
Distinct characters129
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)67.9%

Sample

1st row직접비 / 연구장비·재료비 / 시제(작)품비
2nd row직접비 / 연구장비·재료비 / 계
3rd row직접비 / 연구활동비 / 국외여비
4th row직접비 / 연구활동비 / 인쇄비
5th row직접비 / 연구활동비 / 공공요금/수수료
ValueCountFrequency (%)
189
36.8%
직접비 83
16.1%
연구활동비 34
 
6.6%
간접비 25
 
4.9%
인건비 19
 
3.7%
연구과제추진비 16
 
3.1%
연구장비·재료비 12
 
2.3%
연구지원비 10
 
1.9%
소계 9
 
1.8%
계 7
 
1.4%
Other values (82) 110
21.4%
2023-12-13T08:47:21.462284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
402
20.3%
비 282
14.3%
/ 193
 
9.8%
접 108
 
5.5%
구 92
 
4.7%
연 90
 
4.6%
직 83
 
4.2%
활 46
 
2.3%
동 39
 
2.0%
지 30
 
1.5%
Other values (119) 611
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1351
68.4%
Space Separator 402
 
20.3%
Other Punctuation 217
 
11.0%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 282
20.9%
접 108
 
8.0%
구 92
 
6.8%
연 90
 
6.7%
직 83
 
6.1%
활 46
 
3.4%
동 39
 
2.9%
지 30
 
2.2%
인 29
 
2.1%
과 26
 
1.9%
Other values (112) 526
38.9%
Other Punctuation
ValueCountFrequency (%)
/ 193
88.9%
· 24
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 2
66.7%
] 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 2
66.7%
[ 1
33.3%
Space Separator
ValueCountFrequency (%)
402
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1351
68.4%
Common 625
31.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 282
20.9%
접 108
 
8.0%
구 92
 
6.8%
연 90
 
6.7%
직 83
 
6.1%
활 46
 
3.4%
동 39
 
2.9%
지 30
 
2.2%
인 29
 
2.1%
과 26
 
1.9%
Other values (112) 526
38.9%
Common
ValueCountFrequency (%)
402
64.3%
/ 193
30.9%
· 24
 
3.8%
) 2
 
0.3%
( 2
 
0.3%
[ 1
 
0.2%
] 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1351
68.4%
ASCII 601
30.4%
None 24
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
402
66.9%
/ 193
32.1%
) 2
 
0.3%
( 2
 
0.3%
[ 1
 
0.2%
] 1
 
0.2%
Hangul
ValueCountFrequency (%)
비 282
20.9%
접 108
 
8.0%
구 92
 
6.8%
연 90
 
6.7%
직 83
 
6.1%
활 46
 
3.4%
동 39
 
2.9%
지 30
 
2.2%
인 29
 
2.1%
과 26
 
1.9%
Other values (112) 526
38.9%
None
ValueCountFrequency (%)
· 24
100.0%

최초작성일시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2016-09-27
63 
2016-12-08
49 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-12-08
2nd row2016-12-08
3rd row2016-12-08
4th row2016-12-08
5th row2016-12-08

Common Values

ValueCountFrequency (%)
2016-09-27 63
56.2%
2016-12-08 49
43.8%

Length

2023-12-13T08:47:21.565989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:47:21.637713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-09-27 63
56.2%
2016-12-08 49
43.8%

최종수정일시
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2016-09-27
62 
2016-12-08
49 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.9464286
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row2016-12-08
2nd row2016-12-08
3rd row2016-12-08
4th row2016-12-08
5th row2016-12-08

Common Values

ValueCountFrequency (%)
2016-09-27 62
55.4%
2016-12-08 49
43.8%
<NA> 1
 
0.9%

Length

2023-12-13T08:47:21.718040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:47:21.793143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-09-27 62
55.4%
2016-12-08 49
43.8%
na 1
 
0.9%

Interactions

2023-12-13T08:47:18.517094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:47:21.849927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비목레벨비목코드명부모비목코드정렬순서사용여부전체비목코드명최초작성일시최종수정일시
비목레벨1.0000.8251.0000.3570.1940.9800.0000.000
비목코드명0.8251.0000.0000.8741.0000.9990.0000.000
부모비목코드1.0000.0001.0000.922NaN0.9851.0001.000
정렬순서0.3570.8740.9221.0000.3120.9290.4050.398
사용여부0.1941.000NaN0.3121.0001.0000.000NaN
전체비목코드명0.9800.9990.9850.9291.0001.0000.0000.000
최초작성일시0.0000.0001.0000.4050.0000.0001.0001.000
최종수정일시0.0000.0001.0000.398NaN0.0001.0001.000
2023-12-13T08:47:21.944452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비목레벨최종수정일시최초작성일시사용여부부모비목코드
비목레벨1.0000.0000.0000.3160.886
최종수정일시0.0001.0000.9821.0000.886
최초작성일시0.0000.9821.0000.0000.886
사용여부0.3161.0000.0001.0001.000
부모비목코드0.8860.8860.8861.0001.000
2023-12-13T08:47:22.028327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정렬순서비목레벨부모비목코드사용여부최초작성일시최종수정일시
정렬순서1.0000.2630.6330.3260.4330.427
비목레벨0.2631.0000.8860.3160.0000.000
부모비목코드0.6330.8861.0001.0000.8860.886
사용여부0.3260.3161.0001.0000.0001.000
최초작성일시0.4330.0000.8860.0001.0000.982
최종수정일시0.4270.0000.8861.0000.9821.000

Missing values

2023-12-13T08:47:18.622582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:47:18.766891image/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

비목코드비목레벨비목코드명부모비목코드정렬순서사용여부전체비목코드명최초작성일시최종수정일시
0C0105030003시제(작)품비C0105000007Y직접비 / 연구장비·재료비 / 시제(작)품비2016-12-082016-12-08
1C0105040003계C0105000008Y직접비 / 연구장비·재료비 / 계2016-12-082016-12-08
2C0106010003국외여비C0106000009Y직접비 / 연구활동비 / 국외여비2016-12-082016-12-08
3C0106020003인쇄비C01060000010Y직접비 / 연구활동비 / 인쇄비2016-12-082016-12-08
4C0106030003공공요금/수수료C01060000011Y직접비 / 연구활동비 / 공공요금/수수료2016-12-082016-12-08
5C0106040003위탁정산수수료C01060000012Y직접비 / 연구활동비 / 위탁정산수수료2016-12-082016-12-08
6C0106050003전문가활용비C01060000013Y직접비 / 연구활동비 / 전문가활용비2016-12-082016-12-08
7C0106060003교육훈련비C01060000014Y직접비 / 연구활동비 / 교육훈련비2016-12-082016-12-08
8C0106070003기술정보수집비C01060000015Y직접비 / 연구활동비 / 기술정보수집비2016-12-082016-12-08
9C0106080003문헌구입비C01060000016Y직접비 / 연구활동비 / 문헌구입비2016-12-082016-12-08
비목코드비목레벨비목코드명부모비목코드정렬순서사용여부전체비목코드명최초작성일시최종수정일시
102C0108000002연구수당C0100000008Y직접비 / 연구수당2016-12-082016-12-08
103C0109000002위탁연구개발비C0100000009Y직접비 / 위탁연구개발비2016-12-082016-12-08
104C0201000002직접비C02000000010Y직접비 / 직접비2016-12-082016-12-08
105C0301000002간접비C03000000011Y간접비 / 간접비2016-12-082016-12-08
106C0101010003비지급C0101000001Y직접비 / 인건비 / 비지급2016-12-082016-12-08
107C0102010003지급C0102000002Y직접비 / 인건비 / 지급2016-12-082016-12-08
108C0103010003계C0103000003Y직접비 / 학생인건비 / 계2016-12-082016-12-08
109C0104010003계C0104000004Y직접비 / 인건비 / 계2016-12-082016-12-08
110C0105010003시설장비비C0105000005Y직접비 / 연구장비·재료비 / 시설장비비2016-12-082016-12-08
111C0105020003재료비C0105000006Y직접비 / 연구장비·재료비 / 재료비2016-12-082016-12-08