Overview

Dataset statistics

Number of variables6
Number of observations51
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory52.5 B

Variable types

Numeric2
DateTime1
Text3

Dataset

Description임업 및 산촌 진흥촉진에 관한 법률 제9조의2에 의거한 36개 전문교육기관 현황과 관련된 자료입니다.본 데이터는 번호, 지정일, 지정기관, 프로그램 수, 연락처, 기관 주소 등을 포함하고 있습니다.
Author산림청
URLhttps://www.data.go.kr/data/15068877/fileData.do

Alerts

번호 has unique valuesUnique
지정기관 has unique valuesUnique
기관 주소 has unique valuesUnique
프로그램 수 has 15 (29.4%) zerosZeros

Reproduction

Analysis started2024-03-14 12:00:58.519109
Analysis finished2024-03-14 12:01:00.753038
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-14T21:01:00.979600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q113.5
median26
Q338.5
95-th percentile48.5
Maximum51
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.866069
Coefficient of variation (CV)0.57177187
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)13
Skewness0
Sum1326
Variance221
MonotonicityStrictly increasing
2024-03-14T21:01:01.442316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
2 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (41) 41
80.4%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
51 1
2.0%
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%

지정일
Date

Distinct11
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
Minimum2011-02-25 00:00:00
Maximum2023-03-08 00:00:00
2024-03-14T21:01:01.791653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:01:02.155913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

지정기관
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-03-14T21:01:03.049539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length11.156863
Min length3

Characters and Unicode

Total characters569
Distinct characters145
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row경상국립대학교 임업기술교육정보센터
2nd row충북대학교 산림사업전문교육기관
3rd row순천대학교 임업기술전문교육센터
4th row한국임업진흥원
5th row산림조합중앙회 산림버섯연구센터
ValueCountFrequency (%)
산림조합중앙회 5
 
6.4%
사단법인 4
 
5.1%
산학협력단 3
 
3.8%
협동조합 2
 
2.6%
주식회사 2
 
2.6%
화천현장귀농학교 1
 
1.3%
도시농업융복합아카데미 1
 
1.3%
미래교육원 1
 
1.3%
명지대학교 1
 
1.3%
이음숲 1
 
1.3%
Other values (57) 57
73.1%
2024-03-14T21:01:04.249902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 30
 
5.3%
28
 
4.9%
교 23
 
4.0%
림 18
 
3.2%
회 18
 
3.2%
사 17
 
3.0%
합 16
 
2.8%
학 15
 
2.6%
국 15
 
2.6%
한 14
 
2.5%
Other values (135) 375
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 520
91.4%
Space Separator 28
 
4.9%
Open Punctuation 7
 
1.2%
Close Punctuation 7
 
1.2%
Other Symbol 2
 
0.4%
Decimal Number 2
 
0.4%
Uppercase Letter 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 30
 
5.8%
교 23
 
4.4%
림 18
 
3.5%
회 18
 
3.5%
사 17
 
3.3%
합 16
 
3.1%
학 15
 
2.9%
국 15
 
2.9%
한 14
 
2.7%
인 13
 
2.5%
Other values (126) 341
65.6%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 522
91.7%
Common 45
 
7.9%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 30
 
5.7%
교 23
 
4.4%
림 18
 
3.4%
회 18
 
3.4%
사 17
 
3.3%
합 16
 
3.1%
학 15
 
2.9%
국 15
 
2.9%
한 14
 
2.7%
인 13
 
2.5%
Other values (127) 343
65.7%
Common
ValueCountFrequency (%)
28
62.2%
( 7
 
15.6%
) 7
 
15.6%
1 1
 
2.2%
2 1
 
2.2%
& 1
 
2.2%
Latin
ValueCountFrequency (%)
F 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 520
91.4%
ASCII 47
 
8.3%
None 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 30
 
5.8%
교 23
 
4.4%
림 18
 
3.5%
회 18
 
3.5%
사 17
 
3.3%
합 16
 
3.1%
학 15
 
2.9%
국 15
 
2.9%
한 14
 
2.7%
인 13
 
2.5%
Other values (126) 341
65.6%
ASCII
ValueCountFrequency (%)
28
59.6%
( 7
 
14.9%
) 7
 
14.9%
1 1
 
2.1%
2 1
 
2.1%
F 1
 
2.1%
& 1
 
2.1%
P 1
 
2.1%
None
ValueCountFrequency (%)
㈜ 2
100.0%

프로그램 수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5882353
Minimum0
Maximum16
Zeros15
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size587.0 B
2024-03-14T21:01:04.451585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile8.5
Maximum16
Range16
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.2259973
Coefficient of variation (CV)1.2464081
Kurtosis5.1128785
Mean2.5882353
Median Absolute Deviation (MAD)1
Skewness2.0134512
Sum132
Variance10.407059
MonotonicityNot monotonic
2024-03-14T21:01:04.727811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 15
29.4%
1 11
21.6%
3 7
13.7%
2 6
 
11.8%
6 3
 
5.9%
4 2
 
3.9%
7 2
 
3.9%
10 1
 
2.0%
16 1
 
2.0%
8 1
 
2.0%
Other values (2) 2
 
3.9%
ValueCountFrequency (%)
0 15
29.4%
1 11
21.6%
2 6
 
11.8%
3 7
13.7%
4 2
 
3.9%
5 1
 
2.0%
6 3
 
5.9%
7 2
 
3.9%
8 1
 
2.0%
9 1
 
2.0%
ValueCountFrequency (%)
16 1
 
2.0%
10 1
 
2.0%
9 1
 
2.0%
8 1
 
2.0%
7 2
 
3.9%
6 3
5.9%
5 1
 
2.0%
4 2
 
3.9%
3 7
13.7%
2 6
11.8%

연락처
Text

Distinct44
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-03-14T21:01:05.502759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.941176
Min length6

Characters and Unicode

Total characters558
Distinct characters17
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

Unique43 ?
Unique (%)84.3%

Sample

1st row055-772-1835
2nd row043-261-3448
3rd row061-750-3221
4th row02-6393-2577
5th row031-881-0231
ValueCountFrequency (%)
유선번호없음 8
 
15.7%
055-772-1835 1
 
2.0%
033-442-6233 1
 
2.0%
043-261-3448 1
 
2.0%
031-585-8597 1
 
2.0%
055-274-7755 1
 
2.0%
063-324-8500 1
 
2.0%
02-3431-4307 1
 
2.0%
033-260-3639 1
 
2.0%
02-784-7783 1
 
2.0%
Other values (34) 34
66.7%
2024-03-14T21:01:06.610920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 85
15.2%
0 69
12.4%
3 59
10.6%
2 56
10.0%
4 48
8.6%
6 37
6.6%
5 35
6.3%
7 35
6.3%
1 34
 
6.1%
8 32
 
5.7%
Other values (7) 68
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 425
76.2%
Dash Punctuation 85
 
15.2%
Other Letter 48
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 69
16.2%
3 59
13.9%
2 56
13.2%
4 48
11.3%
6 37
8.7%
5 35
8.2%
7 35
8.2%
1 34
8.0%
8 32
7.5%
9 20
 
4.7%
Other Letter
ValueCountFrequency (%)
음 8
16.7%
없 8
16.7%
선 8
16.7%
호 8
16.7%
번 8
16.7%
유 8
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 510
91.4%
Hangul 48
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
- 85
16.7%
0 69
13.5%
3 59
11.6%
2 56
11.0%
4 48
9.4%
6 37
7.3%
5 35
6.9%
7 35
6.9%
1 34
 
6.7%
8 32
 
6.3%
Hangul
ValueCountFrequency (%)
음 8
16.7%
없 8
16.7%
선 8
16.7%
호 8
16.7%
번 8
16.7%
유 8
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 510
91.4%
Hangul 48
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 85
16.7%
0 69
13.5%
3 59
11.6%
2 56
11.0%
4 48
9.4%
6 37
7.3%
5 35
6.9%
7 35
6.9%
1 34
 
6.7%
8 32
 
6.3%
Hangul
ValueCountFrequency (%)
음 8
16.7%
없 8
16.7%
선 8
16.7%
호 8
16.7%
번 8
16.7%
유 8
16.7%

기관 주소
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
2024-03-14T21:01:07.824745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length33
Mean length25.254902
Min length14

Characters and Unicode

Total characters1288
Distinct characters180
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st row경상남도 진주시 진주대로 501, 경상대학교 451동 107호
2nd row충청북도 청주시 서원구 충대로 1
3rd row전라남도 순천시 중앙로 255, 생명산업과학대학교 4층 411호
4th row서울특별시 강서구 공항대로 475, 한국임업진흥원
5th row경기도 여주시 농산로 62
ValueCountFrequency (%)
서울특별시 9
 
3.2%
경기도 7
 
2.5%
대전광역시 6
 
2.2%
강원도 6
 
2.2%
전라북도 4
 
1.4%
4층 4
 
1.4%
전라남도 4
 
1.4%
경상남도 4
 
1.4%
1 3
 
1.1%
경상북도 3
 
1.1%
Other values (212) 228
82.0%
2024-03-14T21:01:09.428087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
 
17.8%
시 44
 
3.4%
로 40
 
3.1%
1 37
 
2.9%
도 35
 
2.7%
3 31
 
2.4%
5 30
 
2.3%
서 26
 
2.0%
2 25
 
1.9%
구 25
 
1.9%
Other values (170) 766
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 794
61.6%
Space Separator 229
 
17.8%
Decimal Number 216
 
16.8%
Other Punctuation 20
 
1.6%
Dash Punctuation 14
 
1.1%
Close Punctuation 7
 
0.5%
Open Punctuation 7
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 44
 
5.5%
로 40
 
5.0%
도 35
 
4.4%
서 26
 
3.3%
구 25
 
3.1%
면 21
 
2.6%
대 21
 
2.6%
동 20
 
2.5%
산 19
 
2.4%
경 19
 
2.4%
Other values (154) 524
66.0%
Decimal Number
ValueCountFrequency (%)
1 37
17.1%
3 31
14.4%
5 30
13.9%
2 25
11.6%
4 21
9.7%
0 20
9.3%
6 16
7.4%
8 15
6.9%
7 12
 
5.6%
9 9
 
4.2%
Space Separator
ValueCountFrequency (%)
229
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 794
61.6%
Common 493
38.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 44
 
5.5%
로 40
 
5.0%
도 35
 
4.4%
서 26
 
3.3%
구 25
 
3.1%
면 21
 
2.6%
대 21
 
2.6%
동 20
 
2.5%
산 19
 
2.4%
경 19
 
2.4%
Other values (154) 524
66.0%
Common
ValueCountFrequency (%)
229
46.5%
1 37
 
7.5%
3 31
 
6.3%
5 30
 
6.1%
2 25
 
5.1%
4 21
 
4.3%
0 20
 
4.1%
, 20
 
4.1%
6 16
 
3.2%
8 15
 
3.0%
Other values (5) 49
 
9.9%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 794
61.6%
ASCII 494
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
46.4%
1 37
 
7.5%
3 31
 
6.3%
5 30
 
6.1%
2 25
 
5.1%
4 21
 
4.3%
0 20
 
4.0%
, 20
 
4.0%
6 16
 
3.2%
8 15
 
3.0%
Other values (6) 50
 
10.1%
Hangul
ValueCountFrequency (%)
시 44
 
5.5%
로 40
 
5.0%
도 35
 
4.4%
서 26
 
3.3%
구 25
 
3.1%
면 21
 
2.6%
대 21
 
2.6%
동 20
 
2.5%
산 19
 
2.4%
경 19
 
2.4%
Other values (154) 524
66.0%

Interactions

2024-03-14T21:00:59.431960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:00:58.939989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:00:59.679705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:00:59.174588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:01:09.696199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지정일지정기관프로그램 수연락처기관 주소
번호1.0000.9061.0000.0000.8231.000
지정일0.9061.0001.0000.6180.9981.000
지정기관1.0001.0001.0001.0001.0001.000
프로그램 수0.0000.6181.0001.0001.0001.000
연락처0.8230.9981.0001.0001.0001.000
기관 주소1.0001.0001.0001.0001.0001.000
2024-03-14T21:01:09.957500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호프로그램 수
번호1.000-0.496
프로그램 수-0.4961.000

Missing values

2024-03-14T21:01:00.060315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:01:00.621317image/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

번호지정일지정기관프로그램 수연락처기관 주소
012011-02-25경상국립대학교 임업기술교육정보센터10055-772-1835경상남도 진주시 진주대로 501, 경상대학교 451동 107호
122011-07-06충북대학교 산림사업전문교육기관3043-261-3448충청북도 청주시 서원구 충대로 1
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342014-09-16한국임업진흥원1602-6393-2577서울특별시 강서구 공항대로 475, 한국임업진흥원
452014-09-16산림조합중앙회 산림버섯연구센터8031-881-0231경기도 여주시 농산로 62
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9102014-09-16산림조합중앙회 양산교육원4055-382-7247경상남도 양산시 하북면 삼등로 10
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