Overview

Dataset statistics

Number of variables10
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory88.1 B

Variable types

Numeric3
DateTime1
Text2
Categorical4

Dataset

Description2023년 김천시 국,도정 평가 수상현황으로 수상명, 포상금 등을 보여주며 한해 동안 우리시가 국정방향에 맞게 업무를 수행하여 나타난 성과를 공유합니다.
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15126967/fileData.do

Alerts

데이터기준일 has constant value ""Constant
시상금(단위_천원) is highly overall correlated with 특별교부세(단위_천원)High correlation
상사업비(단위_천원) is highly overall correlated with 시상기관High correlation
시상기관 is highly overall correlated with 상사업비(단위_천원)High correlation
특별교부세(단위_천원) is highly overall correlated with 시상금(단위_천원)High correlation
특별교부세(단위_천원) is highly imbalanced (79.9%)Imbalance
기금(단위_천원) is highly imbalanced (84.1%)Imbalance
연번 has unique valuesUnique
수상내용 has unique valuesUnique
시상금(단위_천원) has 12 (27.9%) zerosZeros
상사업비(단위_천원) has 36 (83.7%) zerosZeros

Reproduction

Analysis started2024-03-16 06:40:04.620257
Analysis finished2024-03-16 06:40:10.534182
Duration5.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T06:40:10.892346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2024-03-16T06:40:11.566951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

수상일
Date

Distinct32
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2023-03-17 00:00:00
Maximum2023-12-28 00:00:00
2024-03-16T06:40:12.141019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:12.747627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

수상내용
Text

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-03-16T06:40:13.631650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length24.651163
Min length13

Characters and Unicode

Total characters1060
Distinct characters172
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st row2023년 『세계 물의 날』 기념 유공기관 최우수
2nd row민선8기 전국 기초단체장 공약 실천계획 종합평가SA(최우수)
3rd row2022년 시군평가 우수
4th row2023년 농식품수출정책 대상
5th row2022년 과수생산유통지원사업 도 자율 평가 우수
ValueCountFrequency (%)
2023년 34
 
16.0%
우수 15
 
7.0%
평가 12
 
5.6%
최우수 10
 
4.7%
우수기관 6
 
2.8%
시군평가 4
 
1.9%
경상북도 4
 
1.9%
장려 4
 
1.9%
전국 3
 
1.4%
우수사례 3
 
1.4%
Other values (106) 118
55.4%
2024-03-16T06:40:15.156942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
 
16.0%
2 86
 
8.1%
수 47
 
4.4%
우 42
 
4.0%
0 41
 
3.9%
년 40
 
3.8%
3 36
 
3.4%
가 28
 
2.6%
평 25
 
2.4%
관 18
 
1.7%
Other values (162) 527
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 700
66.0%
Space Separator 170
 
16.0%
Decimal Number 169
 
15.9%
Close Punctuation 9
 
0.8%
Open Punctuation 9
 
0.8%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 47
 
6.7%
우 42
 
6.0%
년 40
 
5.7%
가 28
 
4.0%
평 25
 
3.6%
관 18
 
2.6%
지 17
 
2.4%
사 16
 
2.3%
업 15
 
2.1%
기 15
 
2.1%
Other values (148) 437
62.4%
Decimal Number
ValueCountFrequency (%)
2 86
50.9%
0 41
24.3%
3 36
21.3%
1 2
 
1.2%
8 2
 
1.2%
9 1
 
0.6%
4 1
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 8
88.9%
』 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 8
88.9%
『 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 700
66.0%
Common 357
33.7%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 47
 
6.7%
우 42
 
6.0%
년 40
 
5.7%
가 28
 
4.0%
평 25
 
3.6%
관 18
 
2.6%
지 17
 
2.4%
사 16
 
2.3%
업 15
 
2.1%
기 15
 
2.1%
Other values (148) 437
62.4%
Common
ValueCountFrequency (%)
170
47.6%
2 86
24.1%
0 41
 
11.5%
3 36
 
10.1%
) 8
 
2.2%
( 8
 
2.2%
1 2
 
0.6%
8 2
 
0.6%
9 1
 
0.3%
』 1
 
0.3%
Other values (2) 2
 
0.6%
Latin
ValueCountFrequency (%)
A 2
66.7%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 700
66.0%
ASCII 358
33.8%
None 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
47.5%
2 86
24.0%
0 41
 
11.5%
3 36
 
10.1%
) 8
 
2.2%
( 8
 
2.2%
1 2
 
0.6%
A 2
 
0.6%
8 2
 
0.6%
9 1
 
0.3%
Other values (2) 2
 
0.6%
Hangul
ValueCountFrequency (%)
수 47
 
6.7%
우 42
 
6.0%
년 40
 
5.7%
가 28
 
4.0%
평 25
 
3.6%
관 18
 
2.6%
지 17
 
2.4%
사 16
 
2.3%
업 15
 
2.1%
기 15
 
2.1%
Other values (148) 437
62.4%
None
ValueCountFrequency (%)
』 1
50.0%
『 1
50.0%

시상기관
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
경상북도
24 
보건복지부
4 
행정안전부
3 
고용노동부
 
2
(사)한국 메니페스토실천본부
 
1
Other values (9)
9 

Length

Max length15
Median length4
Mean length5.1162791
Min length4

Unique

Unique10 ?
Unique (%)23.3%

Sample

1st row경상북도
2nd row(사)한국 메니페스토실천본부
3rd row경상북도
4th row경상북도
5th row경상북도

Common Values

ValueCountFrequency (%)
경상북도 24
55.8%
보건복지부 4
 
9.3%
행정안전부 3
 
7.0%
고용노동부 2
 
4.7%
(사)한국 메니페스토실천본부 1
 
2.3%
한국환경공단 1
 
2.3%
중소벤처기업부 1
 
2.3%
주택도시보증공사 1
 
2.3%
국립재활원 1
 
2.3%
산업통상자원부 1
 
2.3%
Other values (4) 4
 
9.3%

Length

2024-03-16T06:40:15.620491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 24
54.5%
보건복지부 4
 
9.1%
행정안전부 3
 
6.8%
고용노동부 2
 
4.5%
사)한국 1
 
2.3%
메니페스토실천본부 1
 
2.3%
한국환경공단 1
 
2.3%
중소벤처기업부 1
 
2.3%
주택도시보증공사 1
 
2.3%
국립재활원 1
 
2.3%
Other values (5) 5
 
11.4%

시상금(단위_천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1625.5814
Minimum0
Maximum13000
Zeros12
Zeros (%)27.9%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T06:40:16.141152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median700
Q31500
95-th percentile9400
Maximum13000
Range13000
Interquartile range (IQR)1500

Descriptive statistics

Standard deviation2800.348
Coefficient of variation (CV)1.7226748
Kurtosis8.7094483
Mean1625.5814
Median Absolute Deviation (MAD)700
Skewness2.9539509
Sum69900
Variance7841949.1
MonotonicityNot monotonic
2024-03-16T06:40:16.624144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 12
27.9%
1000 6
14.0%
1500 4
 
9.3%
3000 3
 
7.0%
2000 3
 
7.0%
10000 2
 
4.7%
300 2
 
4.7%
500 2
 
4.7%
700 2
 
4.7%
600 2
 
4.7%
Other values (5) 5
11.6%
ValueCountFrequency (%)
0 12
27.9%
100 1
 
2.3%
300 2
 
4.7%
400 1
 
2.3%
500 2
 
4.7%
600 2
 
4.7%
700 2
 
4.7%
1000 6
14.0%
1200 1
 
2.3%
1500 4
 
9.3%
ValueCountFrequency (%)
13000 1
 
2.3%
10000 2
 
4.7%
4000 1
 
2.3%
3000 3
7.0%
2000 3
7.0%
1500 4
9.3%
1200 1
 
2.3%
1000 6
14.0%
700 2
 
4.7%
600 2
 
4.7%

상사업비(단위_천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38651.163
Minimum0
Maximum1350000
Zeros36
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size519.0 B
2024-03-16T06:40:17.159624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile79000
Maximum1350000
Range1350000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation205989.82
Coefficient of variation (CV)5.3294597
Kurtosis41.889393
Mean38651.163
Median Absolute Deviation (MAD)0
Skewness6.4372911
Sum1662000
Variance4.2431804 × 1010
MonotonicityNot monotonic
2024-03-16T06:40:17.795131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 36
83.7%
80000 1
 
2.3%
50000 1
 
2.3%
7000 1
 
2.3%
70000 1
 
2.3%
5000 1
 
2.3%
1350000 1
 
2.3%
100000 1
 
2.3%
ValueCountFrequency (%)
0 36
83.7%
5000 1
 
2.3%
7000 1
 
2.3%
50000 1
 
2.3%
70000 1
 
2.3%
80000 1
 
2.3%
100000 1
 
2.3%
1350000 1
 
2.3%
ValueCountFrequency (%)
1350000 1
 
2.3%
100000 1
 
2.3%
80000 1
 
2.3%
70000 1
 
2.3%
50000 1
 
2.3%
7000 1
 
2.3%
5000 1
 
2.3%
0 36
83.7%

특별교부세(단위_천원)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
0
41 
100000
 
1
230000
 
1

Length

Max length6
Median length1
Mean length1.2325581
Min length1

Unique

Unique2 ?
Unique (%)4.7%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 41
95.3%
100000 1
 
2.3%
230000 1
 
2.3%

Length

2024-03-16T06:40:18.318014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T06:40:19.149930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 41
95.3%
100000 1
 
2.3%
230000 1
 
2.3%

기금(단위_천원)
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
0
42 
280000
 
1

Length

Max length6
Median length1
Mean length1.1162791
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 42
97.7%
280000 1
 
2.3%

Length

2024-03-16T06:40:19.912701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T06:40:20.389854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
97.7%
280000 1
 
2.3%

해당부서
Text

Distinct22
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-03-16T06:40:21.149127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2790698
Min length3

Characters and Unicode

Total characters227
Distinct characters74
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

Unique11 ?
Unique (%)25.6%

Sample

1st row상하수도과
2nd row기획예산실
3rd row청렴감사실
4th row농식품유통과
5th row농업정책과
ValueCountFrequency (%)
건강증진과 6
14.0%
안전재난과 4
 
9.3%
산림녹지과 3
 
7.0%
일자리경제과 3
 
7.0%
중앙보건지소 3
 
7.0%
상하수도과 3
 
7.0%
농업정책과 2
 
4.7%
농식품유통과 2
 
4.7%
원도심재생과 2
 
4.7%
기획예산실 2
 
4.7%
Other values (12) 13
30.2%
2024-03-16T06:40:22.654086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 35
 
15.4%
건 11
 
4.8%
지 8
 
3.5%
산 7
 
3.1%
도 7
 
3.1%
증 6
 
2.6%
진 6
 
2.6%
재 6
 
2.6%
강 6
 
2.6%
농 5
 
2.2%
Other values (64) 130
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 227
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 35
 
15.4%
건 11
 
4.8%
지 8
 
3.5%
산 7
 
3.1%
도 7
 
3.1%
증 6
 
2.6%
진 6
 
2.6%
재 6
 
2.6%
강 6
 
2.6%
농 5
 
2.2%
Other values (64) 130
57.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 35
 
15.4%
건 11
 
4.8%
지 8
 
3.5%
산 7
 
3.1%
도 7
 
3.1%
증 6
 
2.6%
진 6
 
2.6%
재 6
 
2.6%
강 6
 
2.6%
농 5
 
2.2%
Other values (64) 130
57.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 35
 
15.4%
건 11
 
4.8%
지 8
 
3.5%
산 7
 
3.1%
도 7
 
3.1%
증 6
 
2.6%
진 6
 
2.6%
재 6
 
2.6%
강 6
 
2.6%
농 5
 
2.2%
Other values (64) 130
57.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
2024-03-05
43 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-05
2nd row2024-03-05
3rd row2024-03-05
4th row2024-03-05
5th row2024-03-05

Common Values

ValueCountFrequency (%)
2024-03-05 43
100.0%

Length

2024-03-16T06:40:23.220244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T06:40:23.600454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-05 43
100.0%

Interactions

2024-03-16T06:40:08.322812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:05.745816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:06.781380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:08.767532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:05.971529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:07.182367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:09.131141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:06.384277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T06:40:07.867936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T06:40:23.901636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수상일수상내용시상기관시상금(단위_천원)상사업비(단위_천원)특별교부세(단위_천원)기금(단위_천원)해당부서
연번1.0000.9821.0000.5460.0000.2220.2710.2220.722
수상일0.9821.0001.0000.8740.4820.0001.0001.0000.657
수상내용1.0001.0001.0001.0001.0001.0001.0001.0001.000
시상기관0.5460.8741.0001.0000.6581.0000.3100.1880.634
시상금(단위_천원)0.0000.4821.0000.6581.0000.0000.9220.0000.666
상사업비(단위_천원)0.2220.0001.0001.0000.0001.0000.0000.0001.000
특별교부세(단위_천원)0.2711.0001.0000.3100.9220.0001.0000.0000.000
기금(단위_천원)0.2221.0001.0000.1880.0000.0000.0001.0000.000
해당부서0.7220.6571.0000.6340.6661.0000.0000.0001.000
2024-03-16T06:40:24.271327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특별교부세(단위_천원)시상기관기금(단위_천원)
특별교부세(단위_천원)1.0000.1280.000
시상기관0.1281.0000.090
기금(단위_천원)0.0000.0901.000
2024-03-16T06:40:24.700168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시상금(단위_천원)상사업비(단위_천원)시상기관특별교부세(단위_천원)기금(단위_천원)
연번1.0000.163-0.4160.2040.1350.000
시상금(단위_천원)0.1631.000-0.2290.3420.6370.000
상사업비(단위_천원)-0.416-0.2291.0000.8410.0000.000
시상기관0.2040.3420.8411.0000.1280.090
특별교부세(단위_천원)0.1350.6370.0000.1281.0000.000
기금(단위_천원)0.0000.0000.0000.0900.0001.000

Missing values

2024-03-16T06:40:09.647812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T06:40:10.293585image/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

연번수상일수상내용시상기관시상금(단위_천원)상사업비(단위_천원)특별교부세(단위_천원)기금(단위_천원)해당부서데이터기준일
012023-03-172023년 『세계 물의 날』 기념 유공기관 최우수경상북도3000000상하수도과2024-03-05
122023-04-17민선8기 전국 기초단체장 공약 실천계획 종합평가SA(최우수)(사)한국 메니페스토실천본부0000기획예산실2024-03-05
232023-05-122022년 시군평가 우수경상북도100008000000청렴감사실2024-03-05
342023-06-082023년 농식품수출정책 대상경상북도20005000000농식품유통과2024-03-05
452023-06-132022년 과수생산유통지원사업 도 자율 평가 우수경상북도0700000농업정책과2024-03-05
562023-06-152023년 산불방지 우수기관 장려경상북도1000000산림녹지과2024-03-05
672023-06-152023년 산불방지 우수기관 특별상경상북도2000000산림녹지과2024-03-05
782023-06-212022년도 악취기술진단 완료시설 운영 관리 평가 최우수한국환경공단1500000상하수도과2024-03-05
892023-07-072023년 지역사회 통합건강증진사업 우수사례 최우수 (전략부문)보건복지부300000중앙보건지소2024-03-05
9102023-07-162023년 상반기 지방물가 안정관리 나등급행정안전부001000000일자리경제과2024-03-05
연번수상일수상내용시상기관시상금(단위_천원)상사업비(단위_천원)특별교부세(단위_천원)기금(단위_천원)해당부서데이터기준일
33342023-12-152023년 과수산업육성 시책 평가 우수경상북도1500000농업정책과2024-03-05
34352023-12-152023년 경상북도 건축디자인분야 평가 최우수 (주택행정분야)경상북도1200000건축디자인과2024-03-05
35362023-12-202023년 금연지원서비스사업 평가 우수경상북도1000000건강증진과2024-03-05
36372023-12-212023년 경상북도 공공도서관 운영평가 우수경상북도1000000시립도서관2024-03-05
37382023-12-212023년 산지유통시책평가 최우수경상북도2000000농식품유통과2024-03-05
38392023-12-222023년 강소농육성사업 우수기관경상북도1000000농촌지도과2024-03-05
39402023-12-222023년 산림복지서비스 활용 우수기관사례 공모전 우수 (산림치유분야)한국산림복지진흥원500000건강증진과2024-03-05
40412023-12-262023년 시군 보안감사 평가 최우수경상북도0000총무새마을과2024-03-05
41422023-12-282023년 을지연습 시군평가 장려경상북도600000안전재난과2024-03-05
42432023-12-282023년 재난대응 안전한국훈련 평가 장려경상북도1000000안전재난과2024-03-05