Overview

Dataset statistics

Number of variables9
Number of observations270
Missing cells1852
Missing cells (%)76.2%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory19.6 KiB
Average record size in memory74.5 B

Variable types

Numeric2
Text6
Categorical1

Dataset

Description민법 제32조에 근거하여 농림축산식품부장관이 허가한 비영리 사단법인 및 재단법인의 구분, 법인명, 설립일자, 설립목적, 소재지 등 현황 을 제공 합니다.
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220217000000002037

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates
번호 is highly overall correlated with 허가 번호High correlation
허가 번호 is highly overall correlated with 번호High correlation
지도감독과 (신규) is highly imbalanced (72.9%)Imbalance
번호 has 235 (87.0%) missing valuesMissing
허가 번호 has 230 (85.2%) missing valuesMissing
단체명 has 230 (85.2%) missing valuesMissing
대표자 has 230 (85.2%) missing valuesMissing
소 재 지 has 230 (85.2%) missing valuesMissing
설립 일자 has 229 (84.8%) missing valuesMissing
설 립 목 적 has 230 (85.2%) missing valuesMissing
지도감독과 (기존) has 238 (88.1%) missing valuesMissing

Reproduction

Analysis started2023-12-11 03:30:58.345825
Analysis finished2023-12-11 03:30:59.960512
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct35
Distinct (%)100.0%
Missing235
Missing (%)87.0%
Infinite0
Infinite (%)0.0%
Mean18
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T12:31:00.036986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q19.5
median18
Q326.5
95-th percentile33.3
Maximum35
Range34
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.246951
Coefficient of variation (CV)0.56927504
Kurtosis-1.2
Mean18
Median Absolute Deviation (MAD)9
Skewness0
Sum630
Variance105
MonotonicityStrictly increasing
2023-12-11T12:31:00.217537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
2 1
 
0.4%
21 1
 
0.4%
22 1
 
0.4%
23 1
 
0.4%
24 1
 
0.4%
25 1
 
0.4%
26 1
 
0.4%
27 1
 
0.4%
28 1
 
0.4%
29 1
 
0.4%
Other values (25) 25
 
9.3%
(Missing) 235
87.0%
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 (%)
35 1
0.4%
34 1
0.4%
33 1
0.4%
32 1
0.4%
31 1
0.4%
30 1
0.4%
29 1
0.4%
28 1
0.4%
27 1
0.4%
26 1
0.4%

허가 번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct40
Distinct (%)100.0%
Missing230
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean342.75
Minimum11
Maximum691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-11T12:31:00.352207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile67.9
Q1144.75
median304.5
Q3550
95-th percentile672.2
Maximum691
Range680
Interquartile range (IQR)405.25

Descriptive statistics

Standard deviation211.19243
Coefficient of variation (CV)0.61617048
Kurtosis-1.3836954
Mean342.75
Median Absolute Deviation (MAD)194
Skewness0.16846525
Sum13710
Variance44602.244
MonotonicityStrictly increasing
2023-12-11T12:31:00.483181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
343 1
 
0.4%
355 1
 
0.4%
364 1
 
0.4%
471 1
 
0.4%
498 1
 
0.4%
520 1
 
0.4%
528 1
 
0.4%
547 1
 
0.4%
559 1
 
0.4%
562 1
 
0.4%
Other values (30) 30
 
11.1%
(Missing) 230
85.2%
ValueCountFrequency (%)
11 1
0.4%
47 1
0.4%
69 1
0.4%
84 1
0.4%
94 1
0.4%
95 1
0.4%
110 1
0.4%
118 1
0.4%
119 1
0.4%
126 1
0.4%
ValueCountFrequency (%)
691 1
0.4%
676 1
0.4%
672 1
0.4%
619 1
0.4%
614 1
0.4%
612 1
0.4%
611 1
0.4%
581 1
0.4%
562 1
0.4%
559 1
0.4%

단체명
Text

MISSING 

Distinct40
Distinct (%)100.0%
Missing230
Missing (%)85.2%
Memory size2.2 KiB
2023-12-11T12:31:00.708729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length12
Mean length8.6
Min length4

Characters and Unicode

Total characters344
Distinct characters157
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row이시돌농촌산업개발협회
2nd row눈비산마을
3rd row가나안복민회
4th row한국농촌연구원
5th row일가재단
ValueCountFrequency (%)
눈비산마을 1
 
2.2%
행복에프엔씨 1
 
2.2%
서울대학교상록문화재단 1
 
2.2%
한식재단 1
 
2.2%
한국식량안보연구재단 1
 
2.2%
국제蘭문화센타 1
 
2.2%
더푸른미래재단 1
 
2.2%
국제한식문화재단 1
 
2.2%
글로벌비젼네트워크 1
 
2.2%
한국의료기기검사원 1
 
2.2%
Other values (36) 36
78.3%
2023-12-11T12:31:01.150149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
단 25
 
7.3%
재 24
 
7.0%
국 12
 
3.5%
한 12
 
3.5%
화 10
 
2.9%
농 10
 
2.9%
문 9
 
2.6%
회 7
 
2.0%
촌 6
 
1.7%
원 6
 
1.7%
Other values (147) 223
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 312
90.7%
Lowercase Letter 8
 
2.3%
Uppercase Letter 7
 
2.0%
Decimal Number 6
 
1.7%
Space Separator 5
 
1.5%
Math Symbol 2
 
0.6%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Other Punctuation 1
 
0.3%
Control 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 25
 
8.0%
재 24
 
7.7%
국 12
 
3.8%
한 12
 
3.8%
화 10
 
3.2%
농 10
 
3.2%
문 9
 
2.9%
회 7
 
2.2%
촌 6
 
1.9%
원 6
 
1.9%
Other values (122) 191
61.2%
Uppercase Letter
ValueCountFrequency (%)
I 1
14.3%
J 1
14.3%
S 1
14.3%
G 1
14.3%
A 1
14.3%
R 1
14.3%
K 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
t 3
37.5%
u 1
 
12.5%
i 1
 
12.5%
s 1
 
12.5%
n 1
 
12.5%
e 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
4 2
33.3%
5 1
16.7%
1 1
16.7%
0 1
16.7%
2 1
16.7%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
90.4%
Common 17
 
4.9%
Latin 15
 
4.4%
Han 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 25
 
8.0%
재 24
 
7.7%
국 12
 
3.9%
한 12
 
3.9%
화 10
 
3.2%
농 10
 
3.2%
문 9
 
2.9%
회 7
 
2.3%
촌 6
 
1.9%
원 6
 
1.9%
Other values (121) 190
61.1%
Latin
ValueCountFrequency (%)
t 3
20.0%
u 1
 
6.7%
i 1
 
6.7%
s 1
 
6.7%
n 1
 
6.7%
I 1
 
6.7%
J 1
 
6.7%
S 1
 
6.7%
G 1
 
6.7%
A 1
 
6.7%
Other values (3) 3
20.0%
Common
ValueCountFrequency (%)
5
29.4%
4 2
 
11.8%
( 1
 
5.9%
) 1
 
5.9%
& 1
 
5.9%
5 1
 
5.9%
1 1
 
5.9%
0 1
 
5.9%
2 1
 
5.9%
< 1
 
5.9%
Other values (2) 2
 
11.8%
Han
ValueCountFrequency (%)
蘭 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
90.4%
ASCII 32
 
9.3%
CJK Compat Ideographs 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
단 25
 
8.0%
재 24
 
7.7%
국 12
 
3.9%
한 12
 
3.9%
화 10
 
3.2%
농 10
 
3.2%
문 9
 
2.9%
회 7
 
2.3%
촌 6
 
1.9%
원 6
 
1.9%
Other values (121) 190
61.1%
ASCII
ValueCountFrequency (%)
5
 
15.6%
t 3
 
9.4%
4 2
 
6.2%
( 1
 
3.1%
) 1
 
3.1%
u 1
 
3.1%
i 1
 
3.1%
s 1
 
3.1%
n 1
 
3.1%
I 1
 
3.1%
Other values (15) 15
46.9%
CJK Compat Ideographs
ValueCountFrequency (%)
蘭 1
100.0%

대표자
Text

MISSING 

Distinct39
Distinct (%)97.5%
Missing230
Missing (%)85.2%
Memory size2.2 KiB
2023-12-11T12:31:01.458498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.175
Min length3

Characters and Unicode

Total characters127
Distinct characters74
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row리어던 마이클 조셉
2nd row손영배
3rd row김종일
4th row허유만
5th row정희경
ValueCountFrequency (%)
김기용 2
 
4.8%
조셉 1
 
2.4%
장태평 1
 
2.4%
김인주 1
 
2.4%
정영일 1
 
2.4%
박혜선 1
 
2.4%
정윤환 1
 
2.4%
양일선 1
 
2.4%
이철호 1
 
2.4%
김진공 1
 
2.4%
Other values (31) 31
73.8%
2023-12-11T12:31:01.828378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 10
 
7.9%
이 5
 
3.9%
환 5
 
3.9%
정 5
 
3.9%
박 4
 
3.1%
인 4
 
3.1%
종 4
 
3.1%
일 4
 
3.1%
영 3
 
2.4%
조 3
 
2.4%
Other values (64) 80
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125
98.4%
Space Separator 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 10
 
8.0%
이 5
 
4.0%
환 5
 
4.0%
정 5
 
4.0%
박 4
 
3.2%
인 4
 
3.2%
종 4
 
3.2%
일 4
 
3.2%
영 3
 
2.4%
조 3
 
2.4%
Other values (63) 78
62.4%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125
98.4%
Common 2
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 10
 
8.0%
이 5
 
4.0%
환 5
 
4.0%
정 5
 
4.0%
박 4
 
3.2%
인 4
 
3.2%
종 4
 
3.2%
일 4
 
3.2%
영 3
 
2.4%
조 3
 
2.4%
Other values (63) 78
62.4%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125
98.4%
ASCII 2
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 10
 
8.0%
이 5
 
4.0%
환 5
 
4.0%
정 5
 
4.0%
박 4
 
3.2%
인 4
 
3.2%
종 4
 
3.2%
일 4
 
3.2%
영 3
 
2.4%
조 3
 
2.4%
Other values (63) 78
62.4%
ASCII
ValueCountFrequency (%)
2
100.0%

소 재 지
Text

MISSING 

Distinct40
Distinct (%)100.0%
Missing230
Missing (%)85.2%
Memory size2.2 KiB
2023-12-11T12:31:02.185613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length25.425
Min length14

Characters and Unicode

Total characters1017
Distinct characters171
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row제주도 북제주군 한림읍 금악리 116
2nd row충북 괴산군 소수면 입암리 570번지
3rd row강원도 원주시 신림면 용암리 274
4th row 경기 안양시 동안구 관양동 883번지
5th row서울 강남구 대치3동 1007-3 총회회관 802
ValueCountFrequency (%)
서울 15
 
6.6%
서울시 7
 
3.1%
경기 6
 
2.6%
서초구 6
 
2.6%
강남구 4
 
1.7%
경기도 4
 
1.7%
영등포구 3
 
1.3%
분당구 3
 
1.3%
8층 3
 
1.3%
성남 2
 
0.9%
Other values (168) 176
76.9%
2023-12-11T12:31:03.037576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
18.2%
동 37
 
3.6%
서 35
 
3.4%
1 33
 
3.2%
구 31
 
3.0%
0 30
 
2.9%
울 24
 
2.4%
3 24
 
2.4%
2 23
 
2.3%
시 21
 
2.1%
Other values (161) 574
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 579
56.9%
Decimal Number 196
 
19.3%
Space Separator 185
 
18.2%
Dash Punctuation 18
 
1.8%
Control 10
 
1.0%
Open Punctuation 8
 
0.8%
Close Punctuation 8
 
0.8%
Other Punctuation 7
 
0.7%
Uppercase Letter 3
 
0.3%
Lowercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 37
 
6.4%
서 35
 
6.0%
구 31
 
5.4%
울 24
 
4.1%
시 21
 
3.6%
로 15
 
2.6%
대 14
 
2.4%
남 12
 
2.1%
경 12
 
2.1%
층 12
 
2.1%
Other values (139) 366
63.2%
Decimal Number
ValueCountFrequency (%)
1 33
16.8%
0 30
15.3%
3 24
12.2%
2 23
11.7%
6 20
10.2%
8 15
7.7%
4 15
7.7%
5 14
7.1%
7 12
 
6.1%
9 10
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
B 1
33.3%
A 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Control
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 579
56.9%
Common 433
42.6%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 37
 
6.4%
서 35
 
6.0%
구 31
 
5.4%
울 24
 
4.1%
시 21
 
3.6%
로 15
 
2.6%
대 14
 
2.4%
남 12
 
2.1%
경 12
 
2.1%
층 12
 
2.1%
Other values (139) 366
63.2%
Common
ValueCountFrequency (%)
185
42.7%
1 33
 
7.6%
0 30
 
6.9%
3 24
 
5.5%
2 23
 
5.3%
6 20
 
4.6%
- 18
 
4.2%
8 15
 
3.5%
4 15
 
3.5%
5 14
 
3.2%
Other values (7) 56
 
12.9%
Latin
ValueCountFrequency (%)
T 1
20.0%
a 1
20.0%
B 1
20.0%
t 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 579
56.9%
ASCII 438
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
42.2%
1 33
 
7.5%
0 30
 
6.8%
3 24
 
5.5%
2 23
 
5.3%
6 20
 
4.6%
- 18
 
4.1%
8 15
 
3.4%
4 15
 
3.4%
5 14
 
3.2%
Other values (12) 61
 
13.9%
Hangul
ValueCountFrequency (%)
동 37
 
6.4%
서 35
 
6.0%
구 31
 
5.4%
울 24
 
4.1%
시 21
 
3.6%
로 15
 
2.6%
대 14
 
2.4%
남 12
 
2.1%
경 12
 
2.1%
층 12
 
2.1%
Other values (139) 366
63.2%

설립 일자
Text

MISSING 

Distinct41
Distinct (%)100.0%
Missing229
Missing (%)84.8%
Memory size2.2 KiB
2023-12-11T12:31:03.271810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9.1463415
Min length7

Characters and Unicode

Total characters375
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row62.10.26
2nd row74. 7.12
3rd row73. 9.13
4th row1985.10. 8
5th row1989.12.15
ValueCountFrequency (%)
2000 2
 
4.0%
1993 1
 
2.0%
2010.8.27 1
 
2.0%
2007.4.9 1
 
2.0%
2007.11.1 1
 
2.0%
2014.6.18 1
 
2.0%
2011.4.29 1
 
2.0%
2009.11.07 1
 
2.0%
2008.1.21 1
 
2.0%
2009.12.10 1
 
2.0%
Other values (39) 39
78.0%
2023-12-11T12:31:03.663828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 83
22.1%
0 65
17.3%
1 63
16.8%
2 60
16.0%
9 27
 
7.2%
3 15
 
4.0%
4 14
 
3.7%
7 12
 
3.2%
8 12
 
3.2%
9
 
2.4%
Other values (2) 15
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283
75.5%
Other Punctuation 83
 
22.1%
Space Separator 9
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 65
23.0%
1 63
22.3%
2 60
21.2%
9 27
9.5%
3 15
 
5.3%
4 14
 
4.9%
7 12
 
4.2%
8 12
 
4.2%
5 8
 
2.8%
6 7
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 83
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 375
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 83
22.1%
0 65
17.3%
1 63
16.8%
2 60
16.0%
9 27
 
7.2%
3 15
 
4.0%
4 14
 
3.7%
7 12
 
3.2%
8 12
 
3.2%
9
 
2.4%
Other values (2) 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 375
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 83
22.1%
0 65
17.3%
1 63
16.8%
2 60
16.0%
9 27
 
7.2%
3 15
 
4.0%
4 14
 
3.7%
7 12
 
3.2%
8 12
 
3.2%
9
 
2.4%
Other values (2) 15
 
4.0%

설 립 목 적
Text

MISSING 

Distinct40
Distinct (%)100.0%
Missing230
Missing (%)85.2%
Memory size2.2 KiB
2023-12-11T12:31:03.933738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length194
Median length79.5
Mean length72.875
Min length28

Characters and Unicode

Total characters2915
Distinct characters303
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row축산장려,목야개량,생산물가공 및 이에 수반되는 사회사업 및 육영사업
2nd row자연생태계에 어울리는 농업을 실천하고 도시와 농촌의 공동체적 나눔으로 살기좋은 농촌만들기에 이바지
3rd row기독교정신에 입각한 농촌 ·사회지도자 양성하여 농촌과 사회발전에 기여
4th row농업기반조성, 농촌개발사업 분야의 제도 및 기술 조사연구와 그 성과보급
5th row독립 ·농민운동, 사회교육 등 신앙운동을 펼쳐온 일가 김용기 선생의 유지를 계승발전
ValueCountFrequency (%)
및 28
 
4.3%
기여 14
 
2.1%
위한 12
 
1.8%
지원 10
 
1.5%
발전에 8
 
1.2%
등 7
 
1.1%
통해 6
 
0.9%
등을 5
 
0.8%
기여하고 5
 
0.8%
난 5
 
0.8%
Other values (457) 552
84.7%
2023-12-11T12:31:04.407415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
612
 
21.0%
의 72
 
2.5%
업 65
 
2.2%
농 55
 
1.9%
을 55
 
1.9%
사 55
 
1.9%
기 49
 
1.7%
, 48
 
1.6%
발 45
 
1.5%
전 44
 
1.5%
Other values (293) 1815
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2208
75.7%
Space Separator 612
 
21.0%
Other Punctuation 63
 
2.2%
Lowercase Letter 9
 
0.3%
Decimal Number 8
 
0.3%
Uppercase Letter 6
 
0.2%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 72
 
3.3%
업 65
 
2.9%
농 55
 
2.5%
을 55
 
2.5%
사 55
 
2.5%
기 49
 
2.2%
발 45
 
2.0%
전 44
 
2.0%
한 42
 
1.9%
산 42
 
1.9%
Other values (265) 1684
76.3%
Lowercase Letter
ValueCountFrequency (%)
e 2
22.2%
s 1
11.1%
h 1
11.1%
i 1
11.1%
p 1
11.1%
d 1
11.1%
r 1
11.1%
a 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
2 2
25.0%
5 1
12.5%
3 1
12.5%
7 1
12.5%
0 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 48
76.2%
? 6
 
9.5%
· 6
 
9.5%
" 2
 
3.2%
. 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
S 1
16.7%
H 1
16.7%
A 1
16.7%
O 1
16.7%
Space Separator
ValueCountFrequency (%)
612
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2207
75.7%
Common 692
 
23.7%
Latin 15
 
0.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 72
 
3.3%
업 65
 
2.9%
농 55
 
2.5%
을 55
 
2.5%
사 55
 
2.5%
기 49
 
2.2%
발 45
 
2.0%
전 44
 
2.0%
한 42
 
1.9%
산 42
 
1.9%
Other values (264) 1683
76.3%
Common
ValueCountFrequency (%)
612
88.4%
, 48
 
6.9%
? 6
 
0.9%
· 6
 
0.9%
( 4
 
0.6%
) 4
 
0.6%
1 2
 
0.3%
2 2
 
0.3%
" 2
 
0.3%
5 1
 
0.1%
Other values (5) 5
 
0.7%
Latin
ValueCountFrequency (%)
L 2
13.3%
e 2
13.3%
s 1
 
6.7%
h 1
 
6.7%
S 1
 
6.7%
H 1
 
6.7%
i 1
 
6.7%
A 1
 
6.7%
p 1
 
6.7%
O 1
 
6.7%
Other values (3) 3
20.0%
Han
ValueCountFrequency (%)
蘭 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2206
75.7%
ASCII 701
 
24.0%
None 6
 
0.2%
Compat Jamo 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
612
87.3%
, 48
 
6.8%
? 6
 
0.9%
( 4
 
0.6%
) 4
 
0.6%
1 2
 
0.3%
2 2
 
0.3%
L 2
 
0.3%
e 2
 
0.3%
" 2
 
0.3%
Other values (17) 17
 
2.4%
Hangul
ValueCountFrequency (%)
의 72
 
3.3%
업 65
 
2.9%
농 55
 
2.5%
을 55
 
2.5%
사 55
 
2.5%
기 49
 
2.2%
발 45
 
2.0%
전 44
 
2.0%
한 42
 
1.9%
산 42
 
1.9%
Other values (263) 1682
76.2%
None
ValueCountFrequency (%)
· 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
蘭 1
100.0%

지도감독과 (신규)
Categorical

IMBALANCE 

Distinct20
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
<NA>
230 
축산경영과
 
7
농촌복지여성과
 
6
외식산업진흥과
 
5
방역총괄과
 
3
Other values (15)
 
19

Length

Max length7
Median length4
Mean length4.262963
Min length4

Unique

Unique12 ?
Unique (%)4.4%

Sample

1st row축산경영과
2nd row축산경영과
3rd row농촌복지여성과
4th row농업기반과
5th row농촌복지여성과

Common Values

ValueCountFrequency (%)
<NA> 230
85.2%
축산경영과 7
 
2.6%
농촌복지여성과 6
 
2.2%
외식산업진흥과 5
 
1.9%
방역총괄과 3
 
1.1%
지역개발과 3
 
1.1%
경영인력과 2
 
0.7%
식품산업정책과 2
 
0.7%
방역관리과 1
 
0.4%
축산정책과 1
 
0.4%
Other values (10) 10
 
3.7%

Length

2023-12-11T12:31:04.626182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 230
85.2%
축산경영과 7
 
2.6%
농촌복지여성과 6
 
2.2%
외식산업진흥과 5
 
1.9%
방역총괄과 3
 
1.1%
지역개발과 3
 
1.1%
경영인력과 2
 
0.7%
식품산업정책과 2
 
0.7%
원예경영과 1
 
0.4%
유통정책과 1
 
0.4%
Other values (10) 10
 
3.7%

지도감독과 (기존)
Text

MISSING 

Distinct16
Distinct (%)50.0%
Missing238
Missing (%)88.1%
Memory size2.2 KiB
2023-12-11T12:31:04.838527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.6875
Min length5

Characters and Unicode

Total characters182
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)28.1%

Sample

1st row축산경영과
2nd row축산경영과
3rd row농촌사회여성팀
4th row농업기반과
5th row농촌사회과
ValueCountFrequency (%)
축산경영과 6
18.8%
농촌사회여성팀 5
15.6%
지역개발과 3
9.4%
식품산업정책과 3
9.4%
동물방역과 2
 
6.2%
경영조직과 2
 
6.2%
외식산업진흥팀 2
 
6.2%
농업정책과 1
 
3.1%
축산정책과 1
 
3.1%
과수화훼과 1
 
3.1%
Other values (6) 6
18.8%
2023-12-11T12:31:05.211231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 26
 
14.3%
산 12
 
6.6%
농 9
 
4.9%
경 8
 
4.4%
영 8
 
4.4%
정 8
 
4.4%
책 8
 
4.4%
업 8
 
4.4%
축 7
 
3.8%
팀 7
 
3.8%
Other values (33) 81
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 26
 
14.3%
산 12
 
6.6%
농 9
 
4.9%
경 8
 
4.4%
영 8
 
4.4%
정 8
 
4.4%
책 8
 
4.4%
업 8
 
4.4%
축 7
 
3.8%
팀 7
 
3.8%
Other values (33) 81
44.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 26
 
14.3%
산 12
 
6.6%
농 9
 
4.9%
경 8
 
4.4%
영 8
 
4.4%
정 8
 
4.4%
책 8
 
4.4%
업 8
 
4.4%
축 7
 
3.8%
팀 7
 
3.8%
Other values (33) 81
44.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 26
 
14.3%
산 12
 
6.6%
농 9
 
4.9%
경 8
 
4.4%
영 8
 
4.4%
정 8
 
4.4%
책 8
 
4.4%
업 8
 
4.4%
축 7
 
3.8%
팀 7
 
3.8%
Other values (33) 81
44.5%

Interactions

2023-12-11T12:30:59.226127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:30:59.019719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:30:59.336470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:30:59.113653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:31:05.302810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호허가 번호단체명대표자소 재 지설립 일자설 립 목 적지도감독과 (신규)지도감독과 (기존)
번호1.0000.9651.0000.8981.0001.0001.0000.2740.508
허가\n번호0.9651.0001.0000.9571.0001.0001.0000.0000.388
단체명1.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자0.8980.9571.0001.0001.0001.0001.0000.9480.938
소 재 지1.0001.0001.0001.0001.0001.0001.0001.0001.000
설립\n일자1.0001.0001.0001.0001.0001.0001.0001.0001.000
설 립 목 적1.0001.0001.0001.0001.0001.0001.0001.0001.000
지도감독과\n(신규)0.2740.0001.0000.9481.0001.0001.0001.0000.993
지도감독과\n(기존)0.5080.3881.0000.9381.0001.0001.0000.9931.000
2023-12-11T12:31:05.424460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호허가 번호지도감독과 (신규)
번호1.0001.0000.000
허가\n번호1.0001.0000.000
지도감독과\n(신규)0.0000.0001.000

Missing values

2023-12-11T12:30:59.497147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:30:59.684399image/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.
2023-12-11T12:30:59.836075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

번호허가 번호단체명대표자소 재 지설립 일자설 립 목 적지도감독과 (신규)지도감독과 (기존)
0111이시돌농촌산업개발협회리어던 마이클 조셉제주도 북제주군 한림읍 금악리 11662.10.26축산장려,목야개량,생산물가공 및 이에 수반되는 사회사업 및 육영사업축산경영과축산경영과
1247눈비산마을손영배충북 괴산군 소수면 입암리 570번지74. 7.12자연생태계에 어울리는 농업을 실천하고 도시와 농촌의 공동체적 나눔으로 살기좋은 농촌만들기에 이바지축산경영과축산경영과
2369가나안복민회김종일강원도 원주시 신림면 용암리 27473. 9.13기독교정신에 입각한 농촌 ·사회지도자 양성하여 농촌과 사회발전에 기여농촌복지여성과농촌사회여성팀
3484한국농촌연구원허유만경기 안양시 동안구 관양동 883번지1985.10. 8농업기반조성, 농촌개발사업 분야의 제도 및 기술 조사연구와 그 성과보급농업기반과농업기반과
4594일가재단정희경서울 강남구 대치3동 1007-3 총회회관 8021989.12.15독립 ·농민운동, 사회교육 등 신앙운동을 펼쳐온 일가 김용기 선생의 유지를 계승발전농촌복지여성과농촌사회과
5695국제농업개발원이병화서울 송파구 가락동 600 농수산물도매시장 수산동3층 1호1989.12.20농업조사연구, 정보전달, 홍보, 유통개선사업 수행, 수출입과 해외시장 개척국제개발협력과국제협력과
67110한국동물보호협회금선란대구시 남구 대명 10동 1593-191991.12. 4동물학대행위방지,유기동물보호조치,멸종위기에처한 동물보존 등 동물보호로 우리사회 정서함양과 박애정신 구현방역총괄과동물방역과
78118대산농촌문화재단오교철서울 동대문구 신설동 98-32 교보재단빌딩 9층1991.11.20대산 신용호 선생의 뜻을 받들어 농촌사회 복리증진 도모농촌복지여성과농촌사회여성팀
89119정옥애향사업회라종익경기 오산시 세교동 5061970. 9.29향토개발과 농촌복지향상, 농업기술교육, 장학사업 등을 통하여 향토개발과 농촌복지에 기여축산경영과축산경영과
910126농어촌환경기술연구소권상필서울 서초구 서초대로 26길 3, 경수빌딩 401호1993. 2.24농어촌 생산기반 정비 및 소득기반확충 등 개발과 환경이 조화되는 쾌적한 생활환경을 위한 연구로 복지농어촌 건설에 기여지역개발과지역개발과
번호허가 번호단체명대표자소 재 지설립 일자설 립 목 적지도감독과 (신규)지도감독과 (기존)
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