Overview

Dataset statistics

Number of variables13
Number of observations720
Missing cells1434
Missing cells (%)15.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory75.4 KiB
Average record size in memory107.2 B

Variable types

Numeric3
Categorical2
Text7
DateTime1

Alerts

최종수정일 has constant value ""Constant
연번 is highly overall correlated with 표준모델번호 and 1 other fieldsHigh correlation
표준모델번호 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
분야 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
공표주기 is highly imbalanced (50.6%)Imbalance
최종수정일 has 719 (99.9%) missing valuesMissing
비고 has 715 (99.3%) missing valuesMissing
연번 has unique valuesUnique
표준모델번호 has unique valuesUnique
공표목록 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:35:11.832352
Analysis finished2023-12-10 21:35:14.359281
Duration2.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct720
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean360.5
Minimum1
Maximum720
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-11T06:35:14.442866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.95
Q1180.75
median360.5
Q3540.25
95-th percentile684.05
Maximum720
Range719
Interquartile range (IQR)359.5

Descriptive statistics

Standard deviation207.99038
Coefficient of variation (CV)0.57694975
Kurtosis-1.2
Mean360.5
Median Absolute Deviation (MAD)180
Skewness0
Sum259560
Variance43260
MonotonicityNot monotonic
2023-12-11T06:35:14.609059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144 1
 
0.1%
528 1
 
0.1%
530 1
 
0.1%
531 1
 
0.1%
532 1
 
0.1%
533 1
 
0.1%
534 1
 
0.1%
535 1
 
0.1%
536 1
 
0.1%
537 1
 
0.1%
Other values (710) 710
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
720 1
0.1%
719 1
0.1%
718 1
0.1%
717 1
0.1%
716 1
0.1%
715 1
0.1%
714 1
0.1%
713 1
0.1%
712 1
0.1%
711 1
0.1%

표준모델번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct720
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean360.5
Minimum1
Maximum720
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-11T06:35:14.801005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.95
Q1180.75
median360.5
Q3540.25
95-th percentile684.05
Maximum720
Range719
Interquartile range (IQR)359.5

Descriptive statistics

Standard deviation207.99038
Coefficient of variation (CV)0.57694975
Kurtosis-1.2
Mean360.5
Median Absolute Deviation (MAD)180
Skewness0
Sum259560
Variance43260
MonotonicityNot monotonic
2023-12-11T06:35:15.255693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144 1
 
0.1%
528 1
 
0.1%
530 1
 
0.1%
531 1
 
0.1%
532 1
 
0.1%
533 1
 
0.1%
534 1
 
0.1%
535 1
 
0.1%
536 1
 
0.1%
537 1
 
0.1%
Other values (710) 710
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
720 1
0.1%
719 1
0.1%
718 1
0.1%
717 1
0.1%
716 1
0.1%
715 1
0.1%
714 1
0.1%
713 1
0.1%
712 1
0.1%
711 1
0.1%

분야별
Real number (ℝ)

Distinct147
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.723611
Minimum1
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2023-12-11T06:35:15.423903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median42
Q381
95-th percentile119.05
Maximum147
Range146
Interquartile range (IQR)60.25

Descriptive statistics

Standard deviation37.329194
Coefficient of variation (CV)0.7217051
Kurtosis-0.7383017
Mean51.723611
Median Absolute Deviation (MAD)27
Skewness0.58273924
Sum37241
Variance1393.4687
MonotonicityNot monotonic
2023-12-11T06:35:15.566964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19 9
 
1.2%
13 9
 
1.2%
29 9
 
1.2%
26 9
 
1.2%
25 9
 
1.2%
24 9
 
1.2%
23 9
 
1.2%
22 9
 
1.2%
21 9
 
1.2%
20 9
 
1.2%
Other values (137) 630
87.5%
ValueCountFrequency (%)
1 9
1.2%
2 9
1.2%
3 9
1.2%
4 9
1.2%
5 9
1.2%
6 9
1.2%
7 9
1.2%
8 9
1.2%
9 9
1.2%
10 9
1.2%
ValueCountFrequency (%)
147 1
0.1%
146 1
0.1%
145 1
0.1%
144 1
0.1%
143 1
0.1%
142 1
0.1%
141 1
0.1%
140 1
0.1%
139 1
0.1%
138 1
0.1%

분야
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
조세/법무/행정
147 
교통/건설/환경
127 
가족/보건/복지
119 
농림/축산/해양
108 
도시/주택
63 
Other values (4)
156 

Length

Max length8
Median length8
Mean length7.45
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조세/법무/행정
2nd row조세/법무/행정
3rd row조세/법무/행정
4th row조세/법무/행정
5th row가족/보건/복지

Common Values

ValueCountFrequency (%)
조세/법무/행정 147
20.4%
교통/건설/환경 127
17.6%
가족/보건/복지 119
16.5%
농림/축산/해양 108
15.0%
도시/주택 63
8.8%
관광/문화/체육 45
 
6.2%
소방/재난/안전 42
 
5.8%
산업/경제 40
 
5.6%
교육/취업 29
 
4.0%

Length

2023-12-11T06:35:15.755153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:35:15.917055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조세/법무/행정 147
20.4%
교통/건설/환경 127
17.6%
가족/보건/복지 119
16.5%
농림/축산/해양 108
15.0%
도시/주택 63
8.8%
관광/문화/체육 45
 
6.2%
소방/재난/안전 42
 
5.8%
산업/경제 40
 
5.6%
교육/취업 29
 
4.0%

공표목록
Text

UNIQUE 

Distinct720
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T06:35:16.218650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length12.131944
Min length4

Characters and Unicode

Total characters8735
Distinct characters403
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

Unique720 ?
Unique (%)100.0%

Sample

1st row포상금지급현황
2nd row상품권 구매내역
3rd row경기도 내 공공기관 현황
4th row기부금품 모집등록 현황
5th row보건소(지소) 및 보건진료소 현황
ValueCountFrequency (%)
현황 254
 
12.2%
및 70
 
3.4%
정보 32
 
1.5%
결과 31
 
1.5%
운영 28
 
1.3%
안내 22
 
1.1%
행정처분 21
 
1.0%
경기도 16
 
0.8%
관련 14
 
0.7%
등 14
 
0.7%
Other values (1143) 1587
76.0%
2023-12-11T06:35:16.682121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1371
 
15.7%
현 361
 
4.1%
황 356
 
4.1%
사 195
 
2.2%
업 176
 
2.0%
지 170
 
1.9%
정 154
 
1.8%
기 146
 
1.7%
관 128
 
1.5%
공 121
 
1.4%
Other values (393) 5557
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7229
82.8%
Space Separator 1371
 
15.7%
Other Punctuation 48
 
0.5%
Uppercase Letter 25
 
0.3%
Close Punctuation 21
 
0.2%
Open Punctuation 21
 
0.2%
Decimal Number 19
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
현 361
 
5.0%
황 356
 
4.9%
사 195
 
2.7%
업 176
 
2.4%
지 170
 
2.4%
정 154
 
2.1%
기 146
 
2.0%
관 128
 
1.8%
공 121
 
1.7%
시 117
 
1.6%
Other values (363) 5305
73.4%
Uppercase Letter
ValueCountFrequency (%)
G 3
12.0%
T 3
12.0%
B 2
 
8.0%
C 2
 
8.0%
Q 2
 
8.0%
A 2
 
8.0%
E 2
 
8.0%
D 2
 
8.0%
X 1
 
4.0%
K 1
 
4.0%
Other values (5) 5
20.0%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
0 5
26.3%
5 2
 
10.5%
3 2
 
10.5%
9 2
 
10.5%
2 1
 
5.3%
6 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 27
56.2%
· 14
29.2%
/ 5
 
10.4%
& 2
 
4.2%
Space Separator
ValueCountFrequency (%)
1371
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7229
82.8%
Common 1481
 
17.0%
Latin 25
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
현 361
 
5.0%
황 356
 
4.9%
사 195
 
2.7%
업 176
 
2.4%
지 170
 
2.4%
정 154
 
2.1%
기 146
 
2.0%
관 128
 
1.8%
공 121
 
1.7%
시 117
 
1.6%
Other values (363) 5305
73.4%
Common
ValueCountFrequency (%)
1371
92.6%
, 27
 
1.8%
) 21
 
1.4%
( 21
 
1.4%
· 14
 
0.9%
1 6
 
0.4%
0 5
 
0.3%
/ 5
 
0.3%
5 2
 
0.1%
& 2
 
0.1%
Other values (5) 7
 
0.5%
Latin
ValueCountFrequency (%)
G 3
12.0%
T 3
12.0%
B 2
 
8.0%
C 2
 
8.0%
Q 2
 
8.0%
A 2
 
8.0%
E 2
 
8.0%
D 2
 
8.0%
X 1
 
4.0%
K 1
 
4.0%
Other values (5) 5
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7229
82.8%
ASCII 1492
 
17.1%
None 14
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1371
91.9%
, 27
 
1.8%
) 21
 
1.4%
( 21
 
1.4%
1 6
 
0.4%
0 5
 
0.3%
/ 5
 
0.3%
G 3
 
0.2%
T 3
 
0.2%
5 2
 
0.1%
Other values (19) 28
 
1.9%
Hangul
ValueCountFrequency (%)
현 361
 
5.0%
황 356
 
4.9%
사 195
 
2.7%
업 176
 
2.4%
지 170
 
2.4%
정 154
 
2.1%
기 146
 
2.0%
관 128
 
1.8%
공 121
 
1.7%
시 117
 
1.6%
Other values (363) 5305
73.4%
None
ValueCountFrequency (%)
· 14
100.0%

공표항목
Text

Distinct700
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T06:35:17.029721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length156
Median length64
Mean length32.6875
Min length7

Characters and Unicode

Total characters23535
Distinct characters446
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique690 ?
Unique (%)95.8%

Sample

1st row부서명, 지급내용, 지급대상, 포상금액 등
2nd row부서명, 상품권종류, 용도, 구매내역
3rd row기관명, 주소, 주요기능, 대표전화 등
4th row기부금품 모집자, 모집목적, 목표액, 모집기간, 사용기한, 사용명세 등
5th row보건소명, 주소, 전화번호, 홈페이지 링크
ValueCountFrequency (%)
등 312
 
6.5%
및 185
 
3.9%
소재지 93
 
1.9%
현황 74
 
1.5%
시군별 66
 
1.4%
전화번호 42
 
0.9%
면적 33
 
0.7%
위치 31
 
0.6%
연락처 31
 
0.6%
주소 30
 
0.6%
Other values (2453) 3897
81.3%
2023-12-11T06:35:17.591069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4099
 
17.4%
, 2228
 
9.5%
사 539
 
2.3%
업 437
 
1.9%
지 426
 
1.8%
시 398
 
1.7%
등 367
 
1.6%
명 332
 
1.4%
( 330
 
1.4%
) 328
 
1.4%
Other values (436) 14051
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16423
69.8%
Space Separator 4099
 
17.4%
Other Punctuation 2287
 
9.7%
Open Punctuation 330
 
1.4%
Close Punctuation 328
 
1.4%
Uppercase Letter 33
 
0.1%
Decimal Number 27
 
0.1%
Dash Punctuation 7
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 539
 
3.3%
업 437
 
2.7%
지 426
 
2.6%
시 398
 
2.4%
등 367
 
2.2%
명 332
 
2.0%
기 323
 
2.0%
수 291
 
1.8%
소 257
 
1.6%
자 247
 
1.5%
Other values (398) 12806
78.0%
Uppercase Letter
ValueCountFrequency (%)
S 4
12.1%
D 4
12.1%
E 3
 
9.1%
G 3
 
9.1%
T 2
 
6.1%
C 2
 
6.1%
M 2
 
6.1%
B 2
 
6.1%
A 2
 
6.1%
O 1
 
3.0%
Other values (8) 8
24.2%
Decimal Number
ValueCountFrequency (%)
1 13
48.1%
2 4
 
14.8%
0 3
 
11.1%
3 3
 
11.1%
8 1
 
3.7%
5 1
 
3.7%
9 1
 
3.7%
4 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 2228
97.4%
· 44
 
1.9%
/ 7
 
0.3%
. 4
 
0.2%
* 2
 
0.1%
． 1
 
< 0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4099
100.0%
Open Punctuation
ValueCountFrequency (%)
( 330
100.0%
Close Punctuation
ValueCountFrequency (%)
) 328
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
× 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16423
69.8%
Common 7079
30.1%
Latin 33
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 539
 
3.3%
업 437
 
2.7%
지 426
 
2.6%
시 398
 
2.4%
등 367
 
2.2%
명 332
 
2.0%
기 323
 
2.0%
수 291
 
1.8%
소 257
 
1.6%
자 247
 
1.5%
Other values (398) 12806
78.0%
Common
ValueCountFrequency (%)
4099
57.9%
, 2228
31.5%
( 330
 
4.7%
) 328
 
4.6%
· 44
 
0.6%
1 13
 
0.2%
- 7
 
0.1%
/ 7
 
0.1%
. 4
 
0.1%
2 4
 
0.1%
Other values (10) 15
 
0.2%
Latin
ValueCountFrequency (%)
S 4
12.1%
D 4
12.1%
E 3
 
9.1%
G 3
 
9.1%
T 2
 
6.1%
C 2
 
6.1%
M 2
 
6.1%
B 2
 
6.1%
A 2
 
6.1%
O 1
 
3.0%
Other values (8) 8
24.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16423
69.8%
ASCII 7066
30.0%
None 46
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4099
58.0%
, 2228
31.5%
( 330
 
4.7%
) 328
 
4.6%
1 13
 
0.2%
- 7
 
0.1%
/ 7
 
0.1%
. 4
 
0.1%
S 4
 
0.1%
2 4
 
0.1%
Other values (25) 42
 
0.6%
Hangul
ValueCountFrequency (%)
사 539
 
3.3%
업 437
 
2.7%
지 426
 
2.6%
시 398
 
2.4%
등 367
 
2.2%
명 332
 
2.0%
기 323
 
2.0%
수 291
 
1.8%
소 257
 
1.6%
자 247
 
1.5%
Other values (398) 12806
78.0%
None
ValueCountFrequency (%)
· 44
95.7%
． 1
 
2.2%
× 1
 
2.2%

공표주기
Categorical

IMBALANCE 

Distinct12
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
매년
419 
수시
172 
분기
51 
반기
49 
매월
 
11
Other values (7)
 
18

Length

Max length10
Median length2
Mean length2.0111111
Min length2

Unique

Unique3 ?
Unique (%)0.4%

Sample

1st row분기
2nd row분기
3rd row매년
4th row분기
5th row매년

Common Values

ValueCountFrequency (%)
매년 419
58.2%
수시 172
23.9%
분기 51
 
7.1%
반기 49
 
6.8%
매월 11
 
1.5%
매주 5
 
0.7%
격년 4
 
0.6%
5년 4
 
0.6%
매일 2
 
0.3%
5월 1
 
0.1%
Other values (2) 2
 
0.3%

Length

2023-12-11T06:35:17.732831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
매년 419
58.2%
수시 172
23.9%
분기 51
 
7.1%
반기 49
 
6.8%
매월 11
 
1.5%
매주 5
 
0.7%
격년 4
 
0.6%
5년 4
 
0.6%
매일 2
 
0.3%
5월 1
 
0.1%
Other values (2) 2
 
0.3%

공표시기
Text

Distinct128
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T06:35:17.958859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length2
Mean length4.8638889
Min length1

Characters and Unicode

Total characters3502
Distinct characters109
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)11.9%

Sample

1st row1월, 4월, 7월, 10월
2nd row1월, 4월, 7월, 10월
3rd row7월
4th row1월, 4월, 7월, 10월
5th row1월
ValueCountFrequency (%)
1월 148
 
14.3%
4월 98
 
9.5%
7월 87
 
8.4%
3월 66
 
6.4%
자료변동시 64
 
6.2%
10월 52
 
5.0%
2월 49
 
4.7%
6월 39
 
3.8%
5월 32
 
3.1%
12월 24
 
2.3%
Other values (129) 375
36.3%
2023-12-11T06:35:18.337315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
월 727
20.8%
1 338
 
9.7%
314
 
9.0%
, 209
 
6.0%
료 145
 
4.1%
자 143
 
4.1%
시 142
 
4.1%
0 124
 
3.5%
7 115
 
3.3%
4 111
 
3.2%
Other values (99) 1134
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1976
56.4%
Decimal Number 980
28.0%
Space Separator 314
 
9.0%
Other Punctuation 215
 
6.1%
Math Symbol 5
 
0.1%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 727
36.8%
료 145
 
7.3%
자 143
 
7.2%
시 142
 
7.2%
생 88
 
4.5%
일 82
 
4.1%
변 77
 
3.9%
발 75
 
3.8%
이 66
 
3.3%
내 66
 
3.3%
Other values (82) 365
18.5%
Decimal Number
ValueCountFrequency (%)
1 338
34.5%
0 124
 
12.7%
7 115
 
11.7%
4 111
 
11.3%
2 109
 
11.1%
3 74
 
7.6%
6 41
 
4.2%
5 41
 
4.2%
8 16
 
1.6%
9 11
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 209
97.2%
. 6
 
2.8%
Space Separator
ValueCountFrequency (%)
314
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1976
56.4%
Common 1526
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
월 727
36.8%
료 145
 
7.3%
자 143
 
7.2%
시 142
 
7.2%
생 88
 
4.5%
일 82
 
4.1%
변 77
 
3.9%
발 75
 
3.8%
이 66
 
3.3%
내 66
 
3.3%
Other values (82) 365
18.5%
Common
ValueCountFrequency (%)
1 338
22.1%
314
20.6%
, 209
13.7%
0 124
 
8.1%
7 115
 
7.5%
4 111
 
7.3%
2 109
 
7.1%
3 74
 
4.8%
6 41
 
2.7%
5 41
 
2.7%
Other values (7) 50
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1976
56.4%
ASCII 1526
43.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
월 727
36.8%
료 145
 
7.3%
자 143
 
7.2%
시 142
 
7.2%
생 88
 
4.5%
일 82
 
4.1%
변 77
 
3.9%
발 75
 
3.8%
이 66
 
3.3%
내 66
 
3.3%
Other values (82) 365
18.5%
ASCII
ValueCountFrequency (%)
1 338
22.1%
314
20.6%
, 209
13.7%
0 124
 
8.1%
7 115
 
7.5%
4 111
 
7.3%
2 109
 
7.1%
3 74
 
4.8%
6 41
 
2.7%
5 41
 
2.7%
Other values (7) 50
 
3.3%

URL
Text

Distinct709
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T06:35:18.578967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length300
Median length54
Mean length58.781944
Min length20

Characters and Unicode

Total characters42323
Distinct characters79
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique701 ?
Unique (%)97.4%

Sample

1st rowhttp://gg.go.kr/opendata/openDataBoard.do?boardIdx=UHC
2nd rowhttp://gg.go.kr/opendata/openDataBoard.do?boardIdx=VHC
3rd rowhttp://gg.go.kr/opendata/openDataBoard.do?boardIdx=WHC
4th rowhttps://www.gg.go.kr/bbs/board.do?bsIdx=570&menuId=1590&bcIdx=531#page=1#keyfield=SUBJECT#keyword=%EA%B8%B0%EB%B6%80
5th rowhttps://www.gg.go.kr/bbs/boardView.do?bsIdx=652&bIdx=81716&page=1&menuId=2336&bcIdx=0
ValueCountFrequency (%)
https://www.kicox.or.kr/user/bbs/bd_selectbbs.do?q_bbscode=1036&q_bbscttsn=20220615163003712&q_order=&q_clcode=2 5
 
0.7%
http://gg.go.kr/opendata/opendataboard.do?boardidx=kyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=xyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=wyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=nzb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=vyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=jyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=gyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=fyb 2
 
0.3%
http://gg.go.kr/opendata/opendataboard.do?boardidx=eyb 2
 
0.3%
Other values (525) 697
96.8%
2023-12-11T06:35:19.025561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 3761
 
8.9%
a 3363
 
7.9%
d 3159
 
7.5%
/ 2954
 
7.0%
t 2858
 
6.8%
. 2338
 
5.5%
g 2245
 
5.3%
r 2005
 
4.7%
p 1904
 
4.5%
e 1642
 
3.9%
Other values (69) 16094
38.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28506
67.4%
Other Punctuation 7193
 
17.0%
Uppercase Letter 3561
 
8.4%
Decimal Number 1943
 
4.6%
Math Symbol 1005
 
2.4%
Connector Punctuation 106
 
0.3%
Other Letter 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 3761
13.2%
a 3363
11.8%
d 3159
11.1%
t 2858
10.0%
g 2245
7.9%
r 2005
 
7.0%
p 1904
 
6.7%
e 1642
 
5.8%
n 1474
 
5.2%
b 963
 
3.4%
Other values (16) 5132
18.0%
Uppercase Letter
ValueCountFrequency (%)
B 1052
29.5%
I 789
22.2%
D 530
14.9%
C 142
 
4.0%
S 110
 
3.1%
V 94
 
2.6%
T 93
 
2.6%
U 83
 
2.3%
E 83
 
2.3%
Y 74
 
2.1%
Other values (16) 511
14.3%
Decimal Number
ValueCountFrequency (%)
1 332
17.1%
0 283
14.6%
2 220
11.3%
6 194
10.0%
8 177
9.1%
5 171
8.8%
9 153
7.9%
4 146
7.5%
3 139
7.2%
7 128
 
6.6%
Other Punctuation
ValueCountFrequency (%)
/ 2954
41.1%
. 2338
32.5%
: 722
 
10.0%
? 657
 
9.1%
& 326
 
4.5%
% 164
 
2.3%
# 32
 
0.4%
Other Letter
ValueCountFrequency (%)
경 1
20.0%
기 1
20.0%
차 1
20.0%
산 1
20.0%
업 1
20.0%
Math Symbol
ValueCountFrequency (%)
= 1005
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32067
75.8%
Common 10251
 
24.2%
Hangul 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 3761
11.7%
a 3363
 
10.5%
d 3159
 
9.9%
t 2858
 
8.9%
g 2245
 
7.0%
r 2005
 
6.3%
p 1904
 
5.9%
e 1642
 
5.1%
n 1474
 
4.6%
B 1052
 
3.3%
Other values (42) 8604
26.8%
Common
ValueCountFrequency (%)
/ 2954
28.8%
. 2338
22.8%
= 1005
 
9.8%
: 722
 
7.0%
? 657
 
6.4%
1 332
 
3.2%
& 326
 
3.2%
0 283
 
2.8%
2 220
 
2.1%
6 194
 
1.9%
Other values (12) 1220
11.9%
Hangul
ValueCountFrequency (%)
경 1
20.0%
기 1
20.0%
차 1
20.0%
산 1
20.0%
업 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42318
> 99.9%
Hangul 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 3761
 
8.9%
a 3363
 
7.9%
d 3159
 
7.5%
/ 2954
 
7.0%
t 2858
 
6.8%
. 2338
 
5.5%
g 2245
 
5.3%
r 2005
 
4.7%
p 1904
 
4.5%
e 1642
 
3.9%
Other values (64) 16089
38.0%
Hangul
ValueCountFrequency (%)
경 1
20.0%
기 1
20.0%
차 1
20.0%
산 1
20.0%
업 1
20.0%

담당부서
Text

Distinct154
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T06:35:19.330673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length5
Mean length5.3555556
Min length2

Characters and Unicode

Total characters3856
Distinct characters179
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

Unique25 ?
Unique (%)3.5%

Sample

1st row공통
2nd row공통
3rd row공통
4th row세정과
5th row보건의료과
ValueCountFrequency (%)
공통 22
 
3.1%
토지정보과 17
 
2.4%
관광과 16
 
2.2%
예산담당관 15
 
2.1%
동물방역위생과 15
 
2.1%
회계과 13
 
1.8%
산림과 13
 
1.8%
상하수과 13
 
1.8%
도시재생과 12
 
1.7%
식품안전과 12
 
1.7%
Other values (144) 572
79.4%
2023-12-11T06:35:19.813881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 558
 
14.5%
정 190
 
4.9%
관 148
 
3.8%
책 132
 
3.4%
지 101
 
2.6%
당 92
 
2.4%
담 92
 
2.4%
산 69
 
1.8%
공 69
 
1.8%
경 62
 
1.6%
Other values (169) 2343
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3853
99.9%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 558
 
14.5%
정 190
 
4.9%
관 148
 
3.8%
책 132
 
3.4%
지 101
 
2.6%
당 92
 
2.4%
담 92
 
2.4%
산 69
 
1.8%
공 69
 
1.8%
경 62
 
1.6%
Other values (166) 2340
60.7%
Uppercase Letter
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3853
99.9%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 558
 
14.5%
정 190
 
4.9%
관 148
 
3.8%
책 132
 
3.4%
지 101
 
2.6%
당 92
 
2.4%
담 92
 
2.4%
산 69
 
1.8%
공 69
 
1.8%
경 62
 
1.6%
Other values (166) 2340
60.7%
Latin
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3853
99.9%
ASCII 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 558
 
14.5%
정 190
 
4.9%
관 148
 
3.8%
책 132
 
3.4%
지 101
 
2.6%
당 92
 
2.4%
담 92
 
2.4%
산 69
 
1.8%
공 69
 
1.8%
경 62
 
1.6%
Other values (166) 2340
60.7%
ASCII
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%

담당자
Text

Distinct519
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-11T06:35:20.177518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.2736111
Min length2

Characters and Unicode

Total characters2357
Distinct characters184
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

Unique396 ?
Unique (%)55.0%

Sample

1st row신영광
2nd row신영광
3rd row신영광
4th row황민정
5th row박상욱
ValueCountFrequency (%)
경기도 13
 
1.8%
콜센터 13
 
1.8%
임건희 8
 
1.1%
최용효 7
 
1.0%
권두용 6
 
0.8%
신영광 5
 
0.7%
김은서 5
 
0.7%
김혜원 5
 
0.7%
황시현 5
 
0.7%
한성원 5
 
0.7%
Other values (510) 661
90.2%
2023-12-11T06:35:20.642254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 141
 
6.0%
이 98
 
4.2%
정 93
 
3.9%
현 70
 
3.0%
영 61
 
2.6%
박 57
 
2.4%
은 56
 
2.4%
경 43
 
1.8%
진 42
 
1.8%
희 41
 
1.7%
Other values (174) 1655
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2307
97.9%
Other Punctuation 37
 
1.6%
Space Separator 13
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 141
 
6.1%
이 98
 
4.2%
정 93
 
4.0%
현 70
 
3.0%
영 61
 
2.6%
박 57
 
2.5%
은 56
 
2.4%
경 43
 
1.9%
진 42
 
1.8%
희 41
 
1.8%
Other values (172) 1605
69.6%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2307
97.9%
Common 50
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 141
 
6.1%
이 98
 
4.2%
정 93
 
4.0%
현 70
 
3.0%
영 61
 
2.6%
박 57
 
2.5%
은 56
 
2.4%
경 43
 
1.9%
진 42
 
1.8%
희 41
 
1.8%
Other values (172) 1605
69.6%
Common
ValueCountFrequency (%)
, 37
74.0%
13
 
26.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2307
97.9%
ASCII 50
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 141
 
6.1%
이 98
 
4.2%
정 93
 
4.0%
현 70
 
3.0%
영 61
 
2.6%
박 57
 
2.5%
은 56
 
2.4%
경 43
 
1.9%
진 42
 
1.8%
희 41
 
1.8%
Other values (172) 1605
69.6%
ASCII
ValueCountFrequency (%)
, 37
74.0%
13
 
26.0%

최종수정일
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing719
Missing (%)99.9%
Memory size5.8 KiB
Minimum2022-02-24 00:00:00
Maximum2022-02-24 00:00:00
2023-12-11T06:35:20.790109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:20.915793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

비고
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing715
Missing (%)99.3%
Memory size5.8 KiB
2023-12-11T06:35:21.077084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length11.8
Min length9

Characters and Unicode

Total characters59
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row여성상담기관현황에 포함 요망
2nd row여성상담기관현황에 포함 요망
3rd row2021년 수정예정
4th row21.2월 업데이트
5th row2019년 미실시
ValueCountFrequency (%)
여성상담기관현황에 2
16.7%
포함 2
16.7%
요망 2
16.7%
2021년 1
8.3%
수정예정 1
8.3%
21.2월 1
8.3%
업데이트 1
8.3%
2019년 1
8.3%
미실시 1
8.3%
2023-12-11T06:35:21.420759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
11.9%
2 5
 
8.5%
1 3
 
5.1%
여 2
 
3.4%
함 2
 
3.4%
정 2
 
3.4%
년 2
 
3.4%
성 2
 
3.4%
망 2
 
3.4%
요 2
 
3.4%
Other values (21) 30
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 40
67.8%
Decimal Number 11
 
18.6%
Space Separator 7
 
11.9%
Other Punctuation 1
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 2
 
5.0%
함 2
 
5.0%
정 2
 
5.0%
년 2
 
5.0%
성 2
 
5.0%
망 2
 
5.0%
요 2
 
5.0%
포 2
 
5.0%
황 2
 
5.0%
현 2
 
5.0%
Other values (15) 20
50.0%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 3
27.3%
0 2
 
18.2%
9 1
 
9.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 40
67.8%
Common 19
32.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 2
 
5.0%
함 2
 
5.0%
정 2
 
5.0%
년 2
 
5.0%
성 2
 
5.0%
망 2
 
5.0%
요 2
 
5.0%
포 2
 
5.0%
황 2
 
5.0%
현 2
 
5.0%
Other values (15) 20
50.0%
Common
ValueCountFrequency (%)
7
36.8%
2 5
26.3%
1 3
15.8%
0 2
 
10.5%
9 1
 
5.3%
. 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 40
67.8%
ASCII 19
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
36.8%
2 5
26.3%
1 3
15.8%
0 2
 
10.5%
9 1
 
5.3%
. 1
 
5.3%
Hangul
ValueCountFrequency (%)
여 2
 
5.0%
함 2
 
5.0%
정 2
 
5.0%
년 2
 
5.0%
성 2
 
5.0%
망 2
 
5.0%
요 2
 
5.0%
포 2
 
5.0%
황 2
 
5.0%
현 2
 
5.0%
Other values (15) 20
50.0%

Interactions

2023-12-11T06:35:13.587821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:12.777954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:13.149075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:13.709104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:12.947436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:13.288431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:13.822170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:13.039733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:35:13.455778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:35:21.531995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번표준모델번호분야별분야공표주기비고
연번1.0001.0000.7510.9330.3061.000
표준모델번호1.0001.0000.7510.9330.3061.000
분야별0.7510.7511.0000.4430.0000.598
분야0.9330.9330.4431.0000.3611.000
공표주기0.3060.3060.0000.3611.0001.000
비고1.0001.0000.5981.0001.0001.000
2023-12-11T06:35:21.632814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공표주기분야
공표주기1.0000.162
분야0.1621.000
2023-12-11T06:35:21.747268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번표준모델번호분야별분야공표주기
연번1.0001.000-0.3410.7770.133
표준모델번호1.0001.000-0.3410.7770.133
분야별-0.341-0.3411.0000.2190.021
분야0.7770.7770.2191.0000.162
공표주기0.1330.1330.0210.1621.000

Missing values

2023-12-11T06:35:13.989967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:35:14.204625image/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.
2023-12-11T06:35:14.310929image/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

연번표준모델번호분야별분야공표목록공표항목공표주기공표시기URL담당부서담당자최종수정일비고
0144144144조세/법무/행정포상금지급현황부서명, 지급내용, 지급대상, 포상금액 등분기1월, 4월, 7월, 10월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=UHC공통신영광<NA><NA>
1145145145조세/법무/행정상품권 구매내역부서명, 상품권종류, 용도, 구매내역분기1월, 4월, 7월, 10월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=VHC공통신영광<NA><NA>
2146146146조세/법무/행정경기도 내 공공기관 현황기관명, 주소, 주요기능, 대표전화 등매년7월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=WHC공통신영광<NA><NA>
3147147147조세/법무/행정기부금품 모집등록 현황기부금품 모집자, 모집목적, 목표액, 모집기간, 사용기한, 사용명세 등분기1월, 4월, 7월, 10월https://www.gg.go.kr/bbs/board.do?bsIdx=570&menuId=1590&bcIdx=531#page=1#keyfield=SUBJECT#keyword=%EA%B8%B0%EB%B6%80세정과황민정<NA><NA>
41481481가족/보건/복지보건소(지소) 및 보건진료소 현황보건소명, 주소, 전화번호, 홈페이지 링크매년1월https://www.gg.go.kr/bbs/boardView.do?bsIdx=652&bIdx=81716&page=1&menuId=2336&bcIdx=0보건의료과박상욱<NA><NA>
51491492가족/보건/복지건강보험 거짓청구기관 현황기관명, 소재지, 요양기관 종류, 위반내용, 처분내용 등반기1월, 8월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=ySB보건의료과원주혜<NA><NA>
61501503가족/보건/복지공공의료기관 현황경기도의료원 병원별 홈페이지(링크)수시자료발생 후 20일 이내https://www.gg.go.kr/bbs/boardView.do?bsIdx=652&bIdx=81712&page=1&menuId=2336&bcIdx=0공공의료과여소희<NA><NA>
71511514가족/보건/복지의료기관 현황도내 종합병원 현황(병원명, 소재지, 연락처)반기1월, 7월https://www.gg.go.kr/bbs/board.do?bsIdx=652&menuId=2336보건의료과이미진<NA><NA>
81521525가족/보건/복지응급의료기관 현황응급환자 발생시 처리흐름도, 경기도 응급의료기관 현황(개소수, 기관명, 지정일자, 소재지 등)매년10월https://www.gg.go.kr/bbs/boardView.do?bsIdx=652&bIdx=81714&page=1&menuId=2336&bcIdx=0보건의료과정선미<NA><NA>
91531536가족/보건/복지산후조리원 현황시군별 산후조리원명, 소재지, 연락처, 시설규모(정원)매년8월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=zSB건강증진과김상희<NA><NA>
연번표준모델번호분야별분야공표목록공표항목공표주기공표시기URL담당부서담당자최종수정일비고
71040840815농림/축산/해양농수산물 도매시장 현황기본현황(개장일, 시설현황, 도매법인, 중도매인, 매매참가인 등), 거래량 등수시자료변동시http://gg.go.kr/opendata/openDataBoard.do?boardIdx=1VB농식품유통과윤자영<NA><NA>
71140940916농림/축산/해양농작물 현황식량작물, 원예작물 생산면적 및 생산량매년10월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=2VB친환경농업과이용현,조현<NA><NA>
71241041017농림/축산/해양시군별 과실생산량 조사결과과실별, 생산량, 재배면적, 농가수매년6월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=3VB친환경농업과박찬은<NA><NA>
71341141118농림/축산/해양농작물 병해충 발생정보병해충 종합관리 요령, 시기별, 작물별 농작물 병해충 발생· 예방정보 등매월(4월~12월)5일~10일http://nongup.gg.go.kr/data/57기술보급과권혜림<NA><NA>
71441241219농림/축산/해양축산물 이력관리가축 및 축산물 이력관리에 관한 법률 위반사실 공표수시위반사항(연2회이상) 확정시https://www.mtrace.go.kr/violAnnounceList.jsp동물방역위생과이지은<NA><NA>
71541341320농림/축산/해양가축통계농업통계(가축별 호수,두수), 전년 동기 대비 증감현황매년1월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=4VB축산정책과이승철<NA><NA>
71641441421농림/축산/해양축산물위생 관련업 현황도축장 현황(사업장명, 소재지, 가축종류, 전화번호),집유장 현황(사업장명, 소재지, 연락처),축산물가공업 현황(사업장명, 소재지,가공업구분(식육가공업, 유가공업, 알가공업))분기1월, 4월, 7월, 10월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=5VB동물방역위생과서준용<NA><NA>
71741541522농림/축산/해양축산물위생 관련업 행정처분업종, 영업장명, 소재지, 위반내용(적용법령), 처분내용, 처분일자 등수시자료발생후 5일 이내http://www.foodsafetykorea.go.kr/portal/specialinfo/searchInfoCompany.do?menu_grp=MENU_NEW04&menu_no=2813동물방역위생과한지훈<NA><NA>
71841641623농림/축산/해양축산물 학교급식 공급업체 점검결과점검업체 내역, 점검결과, 수거검사 내역 및 한우고기감별 DNA검사 결과 등분기5월중, 8월중, 11월중, 12월말http://gg.go.kr/opendata/openDataBoard.do?boardIdx=6VB경기도동물위생시험소김예은<NA><NA>
71941741724농림/축산/해양축산물 도축검사 결과검사품목(소·돼지), 검사월별 도축두수, 검사결과 불합격품 건수, 처리내역분기1월, 4월, 7월, 10월http://gg.go.kr/opendata/openDataBoard.do?boardIdx=7VB경기도동물위생시험소박정훈<NA><NA>