Overview

Dataset statistics

Number of variables10
Number of observations850
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory72.3 KiB
Average record size in memory87.2 B

Variable types

Categorical1
Text2
Numeric7

Dataset

Description전북특별자치도 장수군의 보조사업 현황(부서명, 정책사업, 세부사업, 예산액, 국고보조금, 균특보조금, 기금보조금, 도비보조금, 자체재원, 지방소멸대응기금)에 대한 데이터 정보를 제공하고자 합니다
Author전북특별자치도 장수군
URLhttps://www.data.go.kr/data/15040714/fileData.do

Alerts

예산액(천원) is highly overall correlated with 도비보조금(천원) and 1 other fieldsHigh correlation
도비보조금(천원) is highly overall correlated with 예산액(천원) and 1 other fieldsHigh correlation
자체재원(천원) is highly overall correlated with 예산액(천원) and 1 other fieldsHigh correlation
국고보조금(천원) is highly skewed (γ1 = 24.27611622)Skewed
기금보조금(천원) is highly skewed (γ1 = 24.83129911)Skewed
예산액(천원) has 33 (3.9%) zerosZeros
국고보조금(천원) has 605 (71.2%) zerosZeros
균특보조금(천원) has 812 (95.5%) zerosZeros
기금보조금(천원) has 743 (87.4%) zerosZeros
도비보조금(천원) has 202 (23.8%) zerosZeros
자체재원(천원) has 85 (10.0%) zerosZeros
지방소멸대응기금(천원) has 844 (99.3%) zerosZeros

Reproduction

Analysis started2024-04-06 09:05:22.480854
Analysis finished2024-04-06 09:05:33.111763
Duration10.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부서명
Categorical

Distinct19
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
주민복지과
172 
축산과
92 
산림공원과
69 
농업정책과
63 
환경위생과
59 
Other values (14)
395 

Length

Max length8
Median length5
Mean length4.8188235
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재무과
2nd row기획조정실
3rd row기획조정실
4th row행정지원과
5th row행정지원과

Common Values

ValueCountFrequency (%)
주민복지과 172
20.2%
축산과 92
10.8%
산림공원과 69
 
8.1%
농업정책과 63
 
7.4%
환경위생과 59
 
6.9%
민생경제과 45
 
5.3%
농산유통과 39
 
4.6%
농촌지원과 38
 
4.5%
보건사업과 36
 
4.2%
문화관광과 35
 
4.1%
Other values (9) 202
23.8%

Length

2024-04-06T18:05:33.247361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주민복지과 172
20.2%
축산과 92
10.8%
산림공원과 69
 
8.1%
농업정책과 63
 
7.4%
환경위생과 59
 
6.9%
민생경제과 45
 
5.3%
농산유통과 39
 
4.6%
농촌지원과 38
 
4.5%
보건사업과 36
 
4.2%
문화관광과 35
 
4.1%
Other values (9) 202
23.8%

정책사업
Text

Distinct71
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-04-06T18:05:33.686078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.4764706
Min length4

Characters and Unicode

Total characters6355
Distinct characters144
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

Unique6 ?
Unique (%)0.7%

Sample

1st row재정지원
2nd row군정 조정 지원
3rd row군정 조정 지원
4th row지방행정 역량 강화
5th row지방행정 역량 강화
ValueCountFrequency (%)
강화 107
 
7.2%
경쟁력 75
 
5.0%
군민건강증진 67
 
4.5%
축산 67
 
4.5%
산림자원화 61
 
4.1%
아동복지향상 51
 
3.4%
증진 48
 
3.2%
복지 48
 
3.2%
과학영농기술지원 38
 
2.6%
개선 35
 
2.4%
Other values (100) 892
59.9%
2024-04-06T18:05:34.360325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
639
 
10.1%
지 304
 
4.8%
화 276
 
4.3%
경 178
 
2.8%
산 177
 
2.8%
강 174
 
2.7%
농 170
 
2.7%
원 167
 
2.6%
복 145
 
2.3%
기 141
 
2.2%
Other values (134) 3984
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5702
89.7%
Space Separator 639
 
10.1%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 304
 
5.3%
화 276
 
4.8%
경 178
 
3.1%
산 177
 
3.1%
강 174
 
3.1%
농 170
 
3.0%
원 167
 
2.9%
복 145
 
2.5%
기 141
 
2.5%
진 127
 
2.2%
Other values (131) 3843
67.4%
Space Separator
ValueCountFrequency (%)
639
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5702
89.7%
Common 653
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 304
 
5.3%
화 276
 
4.8%
경 178
 
3.1%
산 177
 
3.1%
강 174
 
3.1%
농 170
 
3.0%
원 167
 
2.9%
복 145
 
2.5%
기 141
 
2.5%
진 127
 
2.2%
Other values (131) 3843
67.4%
Common
ValueCountFrequency (%)
639
97.9%
) 7
 
1.1%
( 7
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5702
89.7%
ASCII 653
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
639
97.9%
) 7
 
1.1%
( 7
 
1.1%
Hangul
ValueCountFrequency (%)
지 304
 
5.3%
화 276
 
4.8%
경 178
 
3.1%
산 177
 
3.1%
강 174
 
3.1%
농 170
 
3.0%
원 167
 
2.9%
복 145
 
2.5%
기 141
 
2.5%
진 127
 
2.2%
Other values (131) 3843
67.4%

세부사업
Text

Distinct847
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size6.8 KiB
2024-04-06T18:05:34.761277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length39
Mean length16.422353
Min length4

Characters and Unicode

Total characters13959
Distinct characters477
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

Unique846 ?
Unique (%)99.5%

Sample

1st row개별주택가격 관리
2nd row지방자치단체 합동평가 인센티브 지원사업
3rd row인권학교 운영
4th row군정 및 대민업무 수행
5th row군민과의 대화 및 행정지원
ValueCountFrequency (%)
지원 180
 
7.2%
지원사업 67
 
2.7%
및 45
 
1.8%
운영 39
 
1.6%
사업 32
 
1.3%
시범 13
 
0.5%
설치 13
 
0.5%
종사자 12
 
0.5%
운영지원 12
 
0.5%
어린이집 11
 
0.4%
Other values (1594) 2082
83.1%
2024-04-06T18:05:35.513831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1665
 
11.9%
지 693
 
5.0%
원 536
 
3.8%
사 530
 
3.8%
업 488
 
3.5%
) 336
 
2.4%
( 336
 
2.4%
비 212
 
1.5%
전 171
 
1.2%
농 160
 
1.1%
Other values (467) 8832
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11467
82.1%
Space Separator 1665
 
11.9%
Close Punctuation 336
 
2.4%
Open Punctuation 336
 
2.4%
Uppercase Letter 87
 
0.6%
Other Punctuation 39
 
0.3%
Decimal Number 23
 
0.2%
Dash Punctuation 3
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 693
 
6.0%
원 536
 
4.7%
사 530
 
4.6%
업 488
 
4.3%
비 212
 
1.8%
전 171
 
1.5%
농 160
 
1.4%
자 159
 
1.4%
기 155
 
1.4%
보 146
 
1.3%
Other values (434) 8217
71.7%
Uppercase Letter
ValueCountFrequency (%)
A 12
13.8%
P 12
13.8%
C 11
12.6%
I 10
11.5%
G 9
10.3%
T 8
9.2%
L 5
5.7%
S 4
 
4.6%
F 4
 
4.6%
B 3
 
3.4%
Other values (6) 9
10.3%
Decimal Number
ValueCountFrequency (%)
1 5
21.7%
2 4
17.4%
9 4
17.4%
0 3
13.0%
3 3
13.0%
7 2
 
8.7%
4 1
 
4.3%
5 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 19
48.7%
· 12
30.8%
. 7
 
17.9%
' 1
 
2.6%
Space Separator
ValueCountFrequency (%)
1665
100.0%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11467
82.1%
Common 2405
 
17.2%
Latin 87
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 693
 
6.0%
원 536
 
4.7%
사 530
 
4.6%
업 488
 
4.3%
비 212
 
1.8%
전 171
 
1.5%
농 160
 
1.4%
자 159
 
1.4%
기 155
 
1.4%
보 146
 
1.3%
Other values (434) 8217
71.7%
Common
ValueCountFrequency (%)
1665
69.2%
) 336
 
14.0%
( 336
 
14.0%
, 19
 
0.8%
· 12
 
0.5%
. 7
 
0.3%
1 5
 
0.2%
2 4
 
0.2%
9 4
 
0.2%
- 3
 
0.1%
Other values (7) 14
 
0.6%
Latin
ValueCountFrequency (%)
A 12
13.8%
P 12
13.8%
C 11
12.6%
I 10
11.5%
G 9
10.3%
T 8
9.2%
L 5
5.7%
S 4
 
4.6%
F 4
 
4.6%
B 3
 
3.4%
Other values (6) 9
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11467
82.1%
ASCII 2480
 
17.8%
None 12
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1665
67.1%
) 336
 
13.5%
( 336
 
13.5%
, 19
 
0.8%
A 12
 
0.5%
P 12
 
0.5%
C 11
 
0.4%
I 10
 
0.4%
G 9
 
0.4%
T 8
 
0.3%
Other values (22) 62
 
2.5%
Hangul
ValueCountFrequency (%)
지 693
 
6.0%
원 536
 
4.7%
사 530
 
4.6%
업 488
 
4.3%
비 212
 
1.8%
전 171
 
1.5%
농 160
 
1.4%
자 159
 
1.4%
기 155
 
1.4%
보 146
 
1.3%
Other values (434) 8217
71.7%
None
ValueCountFrequency (%)
· 12
100.0%

예산액(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct604
Distinct (%)71.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290761.95
Minimum0
Maximum25920376
Zeros33
Zeros (%)3.9%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:35.779542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile407.2
Q18651.75
median40000
Q3158811
95-th percentile1201100
Maximum25920376
Range25920376
Interquartile range (IQR)150159.25

Descriptive statistics

Standard deviation1195846.4
Coefficient of variation (CV)4.1128021
Kurtosis270.8591
Mean290761.95
Median Absolute Deviation (MAD)37650
Skewness14.359039
Sum2.4714766 × 108
Variance1.4300485 × 1012
MonotonicityNot monotonic
2024-04-06T18:05:36.123544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33
 
3.9%
30000 13
 
1.5%
20000 12
 
1.4%
200000 10
 
1.2%
10000 10
 
1.2%
50000 9
 
1.1%
100000 9
 
1.1%
1000 8
 
0.9%
3000 8
 
0.9%
18000 7
 
0.8%
Other values (594) 731
86.0%
ValueCountFrequency (%)
0 33
3.9%
80 1
 
0.1%
111 1
 
0.1%
199 1
 
0.1%
200 1
 
0.1%
220 1
 
0.1%
242 1
 
0.1%
325 1
 
0.1%
330 1
 
0.1%
390 1
 
0.1%
ValueCountFrequency (%)
25920376 1
0.1%
12155000 1
0.1%
11849966 1
0.1%
5920000 1
0.1%
5488646 1
0.1%
4112000 1
0.1%
4000000 1
0.1%
3605000 1
0.1%
3527000 1
0.1%
3499595 1
0.1%

국고보조금(천원)
Real number (ℝ)

SKEWED  ZEROS 

Distinct214
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79401.347
Minimum0
Maximum23328338
Zeros605
Zeros (%)71.2%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:36.379703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31515
95-th percentile211008.6
Maximum23328338
Range23328338
Interquartile range (IQR)1515

Descriptive statistics

Standard deviation855640.8
Coefficient of variation (CV)10.77615
Kurtosis647.03783
Mean79401.347
Median Absolute Deviation (MAD)0
Skewness24.276116
Sum67491145
Variance7.3212118 × 1011
MonotonicityNot monotonic
2024-04-06T18:05:36.612276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 605
71.2%
15000 5
 
0.6%
100000 5
 
0.6%
80000 4
 
0.5%
25000 3
 
0.4%
7800 3
 
0.4%
50000 3
 
0.4%
45000 2
 
0.2%
600 2
 
0.2%
720 2
 
0.2%
Other values (204) 216
 
25.4%
ValueCountFrequency (%)
0 605
71.2%
78 1
 
0.1%
195 1
 
0.1%
208 1
 
0.1%
277 1
 
0.1%
320 1
 
0.1%
375 1
 
0.1%
500 2
 
0.2%
507 1
 
0.1%
510 1
 
0.1%
ValueCountFrequency (%)
23328338 1
0.1%
5924983 1
0.1%
4390916 1
0.1%
2552500 1
0.1%
1900000 1
0.1%
1679559 1
0.1%
1372000 1
0.1%
1096000 1
0.1%
1017000 1
0.1%
1014825 1
0.1%

균특보조금(천원)
Real number (ℝ)

ZEROS 

Distinct37
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14315.562
Minimum0
Maximum2121000
Zeros812
Zeros (%)95.5%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:36.855659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2121000
Range2121000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation116695.63
Coefficient of variation (CV)8.1516622
Kurtosis171.11915
Mean14315.562
Median Absolute Deviation (MAD)0
Skewness11.892041
Sum12168228
Variance1.361787 × 1010
MonotonicityNot monotonic
2024-04-06T18:05:37.166052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 812
95.5%
15000 2
 
0.2%
500000 2
 
0.2%
406837 1
 
0.1%
432 1
 
0.1%
64386 1
 
0.1%
34728 1
 
0.1%
6300 1
 
0.1%
48340 1
 
0.1%
30000 1
 
0.1%
Other values (27) 27
 
3.2%
ValueCountFrequency (%)
0 812
95.5%
432 1
 
0.1%
5000 1
 
0.1%
6300 1
 
0.1%
9000 1
 
0.1%
12000 1
 
0.1%
15000 2
 
0.2%
18750 1
 
0.1%
25000 1
 
0.1%
28948 1
 
0.1%
ValueCountFrequency (%)
2121000 1
0.1%
1500000 1
0.1%
978000 1
0.1%
945000 1
0.1%
786005 1
0.1%
708470 1
0.1%
689000 1
0.1%
500000 2
0.2%
455000 1
0.1%
450000 1
0.1%

기금보조금(천원)
Real number (ℝ)

SKEWED  ZEROS 

Distinct104
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31478.156
Minimum0
Maximum12155000
Zeros743
Zeros (%)87.4%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:37.424738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile39274.35
Maximum12155000
Range12155000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation442291.81
Coefficient of variation (CV)14.050753
Kurtosis669.28358
Mean31478.156
Median Absolute Deviation (MAD)0
Skewness24.831299
Sum26756433
Variance1.9562205 × 1011
MonotonicityNot monotonic
2024-04-06T18:05:37.710178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 743
87.4%
500 3
 
0.4%
777000 2
 
0.2%
30898 2
 
0.2%
5500 1
 
0.1%
5000 1
 
0.1%
6500 1
 
0.1%
2700 1
 
0.1%
48042 1
 
0.1%
3601 1
 
0.1%
Other values (94) 94
 
11.1%
ValueCountFrequency (%)
0 743
87.4%
100 1
 
0.1%
170 1
 
0.1%
231 1
 
0.1%
259 1
 
0.1%
270 1
 
0.1%
300 1
 
0.1%
336 1
 
0.1%
500 3
 
0.4%
624 1
 
0.1%
ValueCountFrequency (%)
12155000 1
0.1%
2595030 1
0.1%
2177000 1
0.1%
2152000 1
0.1%
777000 2
0.2%
672000 1
0.1%
643261 1
0.1%
539609 1
0.1%
418030 1
0.1%
390810 1
0.1%

도비보조금(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct520
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63062.782
Minimum0
Maximum3360000
Zeros202
Zeros (%)23.8%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:37.942893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q178.75
median4500
Q322935
95-th percentile292224.15
Maximum3360000
Range3360000
Interquartile range (IQR)22856.25

Descriptive statistics

Standard deviation238532.49
Coefficient of variation (CV)3.7824607
Kurtosis79.382933
Mean63062.782
Median Absolute Deviation (MAD)4500
Skewness7.8888525
Sum53603365
Variance5.689775 × 1010
MonotonicityNot monotonic
2024-04-06T18:05:38.226773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 202
 
23.8%
1500 9
 
1.1%
6000 7
 
0.8%
1800 6
 
0.7%
18000 6
 
0.7%
10000 6
 
0.7%
15000 5
 
0.6%
1350 5
 
0.6%
4500 5
 
0.6%
50000 5
 
0.6%
Other values (510) 594
69.9%
ValueCountFrequency (%)
0 202
23.8%
11 1
 
0.1%
24 1
 
0.1%
33 1
 
0.1%
36 1
 
0.1%
42 1
 
0.1%
50 2
 
0.2%
54 1
 
0.1%
59 1
 
0.1%
60 1
 
0.1%
ValueCountFrequency (%)
3360000 1
0.1%
2520000 1
0.1%
2369993 1
0.1%
2300000 1
0.1%
1400000 1
0.1%
1278000 1
0.1%
1261920 1
0.1%
1239000 1
0.1%
1125000 1
0.1%
1100000 1
0.1%

자체재원(천원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct611
Distinct (%)71.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100121.75
Minimum0
Maximum3554990
Zeros85
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:38.483586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12580.5
median15970
Q356767.75
95-th percentile424346.4
Maximum3554990
Range3554990
Interquartile range (IQR)54187.25

Descriptive statistics

Standard deviation293949.19
Coefficient of variation (CV)2.9359174
Kurtosis46.559806
Mean100121.75
Median Absolute Deviation (MAD)15541
Skewness6.1040382
Sum85103489
Variance8.6406128 × 1010
MonotonicityNot monotonic
2024-04-06T18:05:39.119156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
 
10.0%
20000 9
 
1.1%
14000 8
 
0.9%
100000 7
 
0.8%
30000 7
 
0.8%
25000 7
 
0.8%
15000 6
 
0.7%
4000 6
 
0.7%
3500 6
 
0.7%
6300 5
 
0.6%
Other values (601) 704
82.8%
ValueCountFrequency (%)
0 85
10.0%
22 1
 
0.1%
33 1
 
0.1%
36 1
 
0.1%
42 1
 
0.1%
49 1
 
0.1%
50 1
 
0.1%
54 1
 
0.1%
56 1
 
0.1%
78 1
 
0.1%
ValueCountFrequency (%)
3554990 1
0.1%
2560000 1
0.1%
2382904 1
0.1%
2160000 1
0.1%
2100000 1
0.1%
2073630 1
0.1%
1935000 1
0.1%
1934953 1
0.1%
1905624 1
0.1%
1754000 1
0.1%

지방소멸대응기금(천원)
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2382.3529
Minimum0
Maximum700000
Zeros844
Zeros (%)99.3%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2024-04-06T18:05:39.343721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum700000
Range700000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation35200.933
Coefficient of variation (CV)14.7757
Kurtosis333.16562
Mean2382.3529
Median Absolute Deviation (MAD)0
Skewness17.743085
Sum2025000
Variance1.2391057 × 109
MonotonicityNot monotonic
2024-04-06T18:05:39.528085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 844
99.3%
700000 1
 
0.1%
250000 1
 
0.1%
110000 1
 
0.1%
100000 1
 
0.1%
200000 1
 
0.1%
665000 1
 
0.1%
ValueCountFrequency (%)
0 844
99.3%
100000 1
 
0.1%
110000 1
 
0.1%
200000 1
 
0.1%
250000 1
 
0.1%
665000 1
 
0.1%
700000 1
 
0.1%
ValueCountFrequency (%)
700000 1
 
0.1%
665000 1
 
0.1%
250000 1
 
0.1%
200000 1
 
0.1%
110000 1
 
0.1%
100000 1
 
0.1%
0 844
99.3%

Interactions

2024-04-06T18:05:31.336830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:23.477604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:24.843441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.995806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.326148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:28.903268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:30.163476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:31.505559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:23.637109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.000168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:26.150581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.477432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:29.077122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:30.330744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:31.688295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:23.789323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.173445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:26.331758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.628121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:29.236517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:30.477689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:31.885514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:23.949818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.316026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:26.488959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.803197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:29.405590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:30.623699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:32.086713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:24.149659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.445215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:26.698442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.983988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:29.588113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:30.785148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:32.324241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:24.407130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.619307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.014403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:28.158099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:29.776390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:30.953307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:32.513452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:24.646492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:25.797680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:27.192730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:28.708750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:29.979608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:05:31.160470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:05:39.694108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명정책사업예산액(천원)국고보조금(천원)균특보조금(천원)기금보조금(천원)도비보조금(천원)자체재원(천원)지방소멸대응기금(천원)
부서명1.0000.9990.0000.0000.1440.0840.2590.1860.000
정책사업0.9991.0000.3400.0000.0000.5690.4940.3740.742
예산액(천원)0.0000.3401.0000.8020.3140.5850.6830.7950.000
국고보조금(천원)0.0000.0000.8021.0000.0000.0000.7620.7800.000
균특보조금(천원)0.1440.0000.3140.0001.0000.0000.3140.4680.000
기금보조금(천원)0.0840.5690.5850.0000.0001.0000.0000.3620.000
도비보조금(천원)0.2590.4940.6830.7620.3140.0001.0000.7750.000
자체재원(천원)0.1860.3740.7950.7800.4680.3620.7751.0000.000
지방소멸대응기금(천원)0.0000.7420.0000.0000.0000.0000.0000.0001.000
2024-04-06T18:05:39.926734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산액(천원)국고보조금(천원)균특보조금(천원)기금보조금(천원)도비보조금(천원)자체재원(천원)지방소멸대응기금(천원)부서명
예산액(천원)1.0000.1880.1480.0160.5600.8160.0890.000
국고보조금(천원)0.1881.000-0.135-0.226-0.0450.101-0.0530.000
균특보조금(천원)0.148-0.1351.000-0.0820.0020.066-0.0180.063
기금보조금(천원)0.016-0.226-0.0821.000-0.198-0.064-0.0320.046
도비보조금(천원)0.560-0.0450.002-0.1981.0000.517-0.0720.110
자체재원(천원)0.8160.1010.066-0.0640.5171.000-0.1310.073
지방소멸대응기금(천원)0.089-0.053-0.018-0.032-0.072-0.1311.0000.000
부서명0.0000.0000.0630.0460.1100.0730.0001.000

Missing values

2024-04-06T18:05:32.754591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:05:33.016942image/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

부서명정책사업세부사업예산액(천원)국고보조금(천원)균특보조금(천원)기금보조금(천원)도비보조금(천원)자체재원(천원)지방소멸대응기금(천원)
0재무과재정지원개별주택가격 관리9985349848000500050
1기획조정실군정 조정 지원지방자치단체 합동평가 인센티브 지원사업486000004860000
2기획조정실군정 조정 지원인권학교 운영3750000150022500
3행정지원과지방행정 역량 강화군정 및 대민업무 수행930720000930720
4행정지원과지방행정 역량 강화군민과의 대화 및 행정지원316260000316260
5행정지원과지방행정 역량 강화이장단 상해보험 지원15260000763076300
6행정지원과지방행정 역량 강화도지사 민생탐방6500000650000
7행정지원과지방행정 역량 강화이장청원 체육대회 운영457930000457930
8행정지원과지방행정 역량 강화행정동우회 사업 지원4000000040000
9행정지원과지방행정 역량 강화읍면민의날 행사 추진 지원783000000783000
부서명정책사업세부사업예산액(천원)국고보조금(천원)균특보조금(천원)기금보조금(천원)도비보조금(천원)자체재원(천원)지방소멸대응기금(천원)
840건설교통과지역개발도시재생 아카데미 및 지원센터 운영4764200014285333570
841건설교통과지역개발전북형 도시재생 뉴딜사업(장수읍)183500000011000007350000
842건설교통과지역개발관광순환도로 터널 관리11208000001120800
843건설교통과지역개발주민참여예산사업(도비지원)35000000035000000
844민생경제과농공단지 조성 및 운영농공단지 활성화 지원사업180000000720001080000
845민생경제과농공단지 조성 및 운영노후농공단지 기반시설 정비(전환사업)2160000001080001080000
846재무과행정운영경비(재무과)도로관리원 보수4113270001873612239660
847재무과행정운영경비(재무과)치매안심센터 운영비 지원(인건비)6500000520000130000
848의료지원과행정운영경비(의료지원과)취약지역 응급의료센터·기관 운영비 지원(인력운영비)5706800025000003206800
849의료지원과행정운영경비(의료지원과)감염병관리(예방접종등록센터운영 인건비)4978100137130360680