Overview

Dataset statistics

Number of variables11
Number of observations625
Missing cells322
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory58.1 KiB
Average record size in memory95.2 B

Variable types

Numeric6
Categorical3
Text2

Dataset

Description경상남도 지방보조금 보조사업자교부에 대한 정보로, 해당 사업부서명, 보조사업명, 집행상태, 정산상태, 지급일자 등에 대한 데이터를 제공합니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15039724

Alerts

회계연도 has constant value ""Constant
신청금액 is highly overall correlated with 교부결정정보 and 2 other fieldsHigh correlation
교부결정정보 is highly overall correlated with 신청금액 and 2 other fieldsHigh correlation
지급정보 is highly overall correlated with 신청금액 and 1 other fieldsHigh correlation
집행정보 is highly overall correlated with 신청금액 and 1 other fieldsHigh correlation
지급일자 has 161 (25.8%) missing valuesMissing
지급정보 has 161 (25.8%) missing valuesMissing
신청금액 is highly skewed (γ1 = 22.93302809)Skewed
교부결정정보 is highly skewed (γ1 = 22.59636396)Skewed
집행정보 is highly skewed (γ1 = 20.00209244)Skewed
순번 has unique valuesUnique
신청금액 has 119 (19.0%) zerosZeros
교부결정정보 has 140 (22.4%) zerosZeros
집행정보 has 245 (39.2%) zerosZeros
집행잔액 has 381 (61.0%) zerosZeros

Reproduction

Analysis started2023-12-10 23:41:05.409283
Analysis finished2023-12-10 23:41:09.460611
Duration4.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313
Minimum1
Maximum625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T08:41:09.532607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.2
Q1157
median313
Q3469
95-th percentile593.8
Maximum625
Range624
Interquartile range (IQR)312

Descriptive statistics

Standard deviation180.56624
Coefficient of variation (CV)0.57688894
Kurtosis-1.2
Mean313
Median Absolute Deviation (MAD)156
Skewness0
Sum195625
Variance32604.167
MonotonicityStrictly increasing
2023-12-11T08:41:09.654186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
421 1
 
0.2%
414 1
 
0.2%
415 1
 
0.2%
416 1
 
0.2%
417 1
 
0.2%
418 1
 
0.2%
419 1
 
0.2%
420 1
 
0.2%
422 1
 
0.2%
Other values (615) 615
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
625 1
0.2%
624 1
0.2%
623 1
0.2%
622 1
0.2%
621 1
0.2%
620 1
0.2%
619 1
0.2%
618 1
0.2%
617 1
0.2%
616 1
0.2%

회계연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2022
625 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 625
100.0%

Length

2023-12-11T08:41:09.755584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:41:09.849199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 625
100.0%

단체구분
Categorical

Distinct16
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
사단법인
145 
주식회사
138 
비영리법인
125 
기타단체
73 
기타법인
56 
Other values (11)
88 

Length

Max length6
Median length4
Mean length4.2368
Min length3

Unique

Unique3 ?
Unique (%)0.5%

Sample

1st row사단법인
2nd row사단법인
3rd row사단법인
4th row비영리법인
5th row비영리법인

Common Values

ValueCountFrequency (%)
사단법인 145
23.2%
주식회사 138
22.1%
비영리법인 125
20.0%
기타단체 73
11.7%
기타법인 56
 
9.0%
<NA> 14
 
2.2%
협동조합 14
 
2.2%
교육기관 14
 
2.2%
공공법인 14
 
2.2%
사회복지법인 11
 
1.8%
Other values (6) 21
 
3.4%

Length

2023-12-11T08:41:09.952078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사단법인 145
23.2%
주식회사 138
22.1%
비영리법인 125
20.0%
기타단체 73
11.7%
기타법인 56
 
9.0%
na 14
 
2.2%
협동조합 14
 
2.2%
교육기관 14
 
2.2%
공공법인 14
 
2.2%
사회복지법인 11
 
1.8%
Other values (6) 21
 
3.4%

부서명
Categorical

Distinct41
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
소통담당관
150 
행정과
103 
여성정책과
68 
장애인복지과
66 
노인복지과
44 
Other values (36)
194 

Length

Max length11
Median length5
Mean length4.8992
Min length3

Unique

Unique12 ?
Unique (%)1.9%

Sample

1st row행정과
2nd row행정과
3rd row농업기술원 기술보급과
4th row행정과
5th row환경정책과

Common Values

ValueCountFrequency (%)
소통담당관 150
24.0%
행정과 103
16.5%
여성정책과 68
10.9%
장애인복지과 66
10.6%
노인복지과 44
 
7.0%
문화예술과 34
 
5.4%
환경정책과 32
 
5.1%
창업지원단 16
 
2.6%
가족지원과 16
 
2.6%
체육지원과 13
 
2.1%
Other values (31) 83
13.3%

Length

2023-12-11T08:41:10.058849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소통담당관 150
23.7%
행정과 103
16.2%
여성정책과 68
10.7%
장애인복지과 66
10.4%
노인복지과 44
 
6.9%
문화예술과 34
 
5.4%
환경정책과 32
 
5.0%
창업지원단 16
 
2.5%
가족지원과 16
 
2.5%
체육지원과 13
 
2.1%
Other values (32) 92
14.5%

보조사업명
Text

Distinct361
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2023-12-11T08:41:10.230871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length20.2064
Min length5

Characters and Unicode

Total characters12629
Distinct characters449
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique327 ?
Unique (%)52.3%

Sample

1st row3.15의거기념식
2nd row3.15의거기념행사
3rd row2022년도벤처농업신성장활력창출마케팅지원사업
4th row비영리민간단체공익활동지원사업
5th row민간단체환경보전활동지원
ValueCountFrequency (%)
비영리민간단체공익활동지원사업 68
 
10.9%
민간단체환경보전활동지원 28
 
4.5%
2022년지역창업보육센터운영지원 16
 
2.6%
경상남도지역신문발전지원사업(일반공모(공익광고)지원사업 15
 
2.4%
경상남도지역신문발전지원사업(일반공모(기획취재)지원사업 15
 
2.4%
경상남도지역신문발전지원사업(취재편집환경개선사업 14
 
2.2%
경상남도지역신문발전지원사업(기획취재지원사업1 14
 
2.2%
경상남도지역신문발전지원사업(우편발송료지원사업 14
 
2.2%
경상남도지역신문발전지원사업(지역경제활성화홍보지원사업 14
 
2.2%
경상남도지역신문발전지원사업(인턴사원지원사업 13
 
2.1%
Other values (351) 414
66.2%
2023-12-11T08:41:10.544113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 847
 
6.7%
원 604
 
4.8%
사 579
 
4.6%
업 509
 
4.0%
경 364
 
2.9%
) 330
 
2.6%
( 329
 
2.6%
남 278
 
2.2%
2 274
 
2.2%
전 260
 
2.1%
Other values (439) 8255
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11355
89.9%
Decimal Number 445
 
3.5%
Close Punctuation 331
 
2.6%
Open Punctuation 330
 
2.6%
Uppercase Letter 77
 
0.6%
Dash Punctuation 35
 
0.3%
Lowercase Letter 30
 
0.2%
Other Punctuation 25
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 847
 
7.5%
원 604
 
5.3%
사 579
 
5.1%
업 509
 
4.5%
경 364
 
3.2%
남 278
 
2.4%
전 260
 
2.3%
역 232
 
2.0%
상 211
 
1.9%
체 206
 
1.8%
Other values (389) 7265
64.0%
Uppercase Letter
ValueCountFrequency (%)
C 12
15.6%
Y 9
11.7%
A 9
11.7%
W 8
10.4%
V 5
 
6.5%
E 5
 
6.5%
T 5
 
6.5%
N 4
 
5.2%
O 4
 
5.2%
I 3
 
3.9%
Other values (10) 13
16.9%
Lowercase Letter
ValueCountFrequency (%)
a 5
16.7%
e 5
16.7%
r 4
13.3%
m 3
10.0%
v 3
10.0%
i 2
 
6.7%
t 2
 
6.7%
n 2
 
6.7%
k 1
 
3.3%
g 1
 
3.3%
Other values (2) 2
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 274
61.6%
0 85
 
19.1%
1 37
 
8.3%
5 15
 
3.4%
6 12
 
2.7%
3 9
 
2.0%
4 9
 
2.0%
9 2
 
0.4%
8 1
 
0.2%
7 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 330
99.7%
」 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 329
99.7%
「 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 19
76.0%
· 6
 
24.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11354
89.9%
Common 1167
 
9.2%
Latin 107
 
0.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 847
 
7.5%
원 604
 
5.3%
사 579
 
5.1%
업 509
 
4.5%
경 364
 
3.2%
남 278
 
2.4%
전 260
 
2.3%
역 232
 
2.0%
상 211
 
1.9%
체 206
 
1.8%
Other values (388) 7264
64.0%
Latin
ValueCountFrequency (%)
C 12
 
11.2%
Y 9
 
8.4%
A 9
 
8.4%
W 8
 
7.5%
V 5
 
4.7%
E 5
 
4.7%
T 5
 
4.7%
a 5
 
4.7%
e 5
 
4.7%
r 4
 
3.7%
Other values (22) 40
37.4%
Common
ValueCountFrequency (%)
) 330
28.3%
( 329
28.2%
2 274
23.5%
0 85
 
7.3%
1 37
 
3.2%
- 35
 
3.0%
. 19
 
1.6%
5 15
 
1.3%
6 12
 
1.0%
3 9
 
0.8%
Other values (8) 22
 
1.9%
Han
ValueCountFrequency (%)
展 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11354
89.9%
ASCII 1266
 
10.0%
None 8
 
0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 847
 
7.5%
원 604
 
5.3%
사 579
 
5.1%
업 509
 
4.5%
경 364
 
3.2%
남 278
 
2.4%
전 260
 
2.3%
역 232
 
2.0%
상 211
 
1.9%
체 206
 
1.8%
Other values (388) 7264
64.0%
ASCII
ValueCountFrequency (%)
) 330
26.1%
( 329
26.0%
2 274
21.6%
0 85
 
6.7%
1 37
 
2.9%
- 35
 
2.8%
. 19
 
1.5%
5 15
 
1.2%
C 12
 
0.9%
6 12
 
0.9%
Other values (37) 118
 
9.3%
None
ValueCountFrequency (%)
· 6
75.0%
「 1
 
12.5%
」 1
 
12.5%
CJK
ValueCountFrequency (%)
展 1
100.0%

지급일자
Text

MISSING 

Distinct161
Distinct (%)34.7%
Missing161
Missing (%)25.8%
Memory size5.0 KiB
2023-12-11T08:41:10.735559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length10
Mean length14.073276
Min length10

Characters and Unicode

Total characters6530
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)22.4%

Sample

1st row2022-04-22
2nd row2022-04-22
3rd row2022-02-09
4th row2022-01-20/n/r2022-09-14
5th row2022-01-17/n/r2022-09-06
ValueCountFrequency (%)
2022-04-22 82
 
17.7%
2022-04-11 70
 
15.1%
2022-04-27 17
 
3.7%
2022-03-28 13
 
2.8%
2022-01-14/n/r2022-06-10 13
 
2.8%
2022-01-17/n/r2022-09-06 11
 
2.4%
2022-01-20/n/r2022-07-25 8
 
1.7%
2022-04-20 8
 
1.7%
2022-01-20 7
 
1.5%
2022-01-17 7
 
1.5%
Other values (151) 228
49.1%
2023-12-11T08:41:11.087626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2200
33.7%
0 1338
20.5%
- 1198
18.3%
1 487
 
7.5%
4 278
 
4.3%
/ 270
 
4.1%
n 135
 
2.1%
r 135
 
2.1%
7 115
 
1.8%
3 94
 
1.4%
Other values (4) 280
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4792
73.4%
Dash Punctuation 1198
 
18.3%
Other Punctuation 270
 
4.1%
Lowercase Letter 270
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2200
45.9%
0 1338
27.9%
1 487
 
10.2%
4 278
 
5.8%
7 115
 
2.4%
3 94
 
2.0%
6 80
 
1.7%
5 70
 
1.5%
9 69
 
1.4%
8 61
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
n 135
50.0%
r 135
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1198
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6260
95.9%
Latin 270
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2200
35.1%
0 1338
21.4%
- 1198
19.1%
1 487
 
7.8%
4 278
 
4.4%
/ 270
 
4.3%
7 115
 
1.8%
3 94
 
1.5%
6 80
 
1.3%
5 70
 
1.1%
Other values (2) 130
 
2.1%
Latin
ValueCountFrequency (%)
n 135
50.0%
r 135
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2200
33.7%
0 1338
20.5%
- 1198
18.3%
1 487
 
7.5%
4 278
 
4.3%
/ 270
 
4.1%
n 135
 
2.1%
r 135
 
2.1%
7 115
 
1.8%
3 94
 
1.4%
Other values (4) 280
 
4.3%

신청금액
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct226
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40717397
Minimum0
Maximum8.59 × 109
Zeros119
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T08:41:11.205951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13000000
median7000000
Q320000000
95-th percentile96840000
Maximum8.59 × 109
Range8.59 × 109
Interquartile range (IQR)17000000

Descriptive statistics

Standard deviation3.5311281 × 108
Coefficient of variation (CV)8.6722836
Kurtosis553.26851
Mean40717397
Median Absolute Deviation (MAD)7000000
Skewness22.933028
Sum2.5448373 × 1010
Variance1.2468866 × 1017
MonotonicityNot monotonic
2023-12-11T08:41:11.353653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 119
 
19.0%
10000000 38
 
6.1%
3000000 26
 
4.2%
4000000 25
 
4.0%
5000000 25
 
4.0%
20000000 17
 
2.7%
15000000 15
 
2.4%
8000000 11
 
1.8%
7000000 11
 
1.8%
6000000 10
 
1.6%
Other values (216) 328
52.5%
ValueCountFrequency (%)
0 119
19.0%
6300 1
 
0.2%
30000 1
 
0.2%
360000 1
 
0.2%
561000 1
 
0.2%
745000 1
 
0.2%
840000 1
 
0.2%
929000 1
 
0.2%
956000 1
 
0.2%
1011000 1
 
0.2%
ValueCountFrequency (%)
8590000000 1
0.2%
1129800000 1
0.2%
1061000000 1
0.2%
745000000 1
0.2%
567400000 1
0.2%
500000000 1
0.2%
493500000 1
0.2%
414000000 1
0.2%
400000000 1
0.2%
297000000 1
0.2%

교부결정정보
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct219
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41096869
Minimum0
Maximum8.59 × 109
Zeros140
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T08:41:11.476811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12000000
median6250000
Q320000000
95-th percentile96840000
Maximum8.59 × 109
Range8.59 × 109
Interquartile range (IQR)18000000

Descriptive statistics

Standard deviation3.5502197 × 108
Coefficient of variation (CV)8.6386622
Kurtosis541.40707
Mean41096869
Median Absolute Deviation (MAD)6250000
Skewness22.596364
Sum2.5685543 × 1010
Variance1.260406 × 1017
MonotonicityNot monotonic
2023-12-11T08:41:11.629646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 140
22.4%
10000000 34
 
5.4%
3000000 26
 
4.2%
4000000 24
 
3.8%
5000000 24
 
3.8%
20000000 17
 
2.7%
15000000 15
 
2.4%
8000000 11
 
1.8%
7000000 11
 
1.8%
6000000 10
 
1.6%
Other values (209) 313
50.1%
ValueCountFrequency (%)
0 140
22.4%
6300 1
 
0.2%
360000 1
 
0.2%
561000 1
 
0.2%
745000 1
 
0.2%
840000 1
 
0.2%
929000 1
 
0.2%
956000 1
 
0.2%
1011000 1
 
0.2%
1082000 1
 
0.2%
ValueCountFrequency (%)
8590000000 1
0.2%
1129800000 1
0.2%
1061000000 1
0.2%
1060000000 1
0.2%
745000000 1
0.2%
567400000 1
0.2%
493500000 1
0.2%
414000000 1
0.2%
400000000 1
0.2%
297000000 1
0.2%

지급정보
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct200
Distinct (%)43.1%
Missing161
Missing (%)25.8%
Infinite0
Infinite (%)0.0%
Mean27986908
Minimum360000
Maximum3 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T08:41:11.762990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum360000
5-th percentile2500000
Q14737500
median9500000
Q320000000
95-th percentile84700000
Maximum3 × 109
Range2.99964 × 109
Interquartile range (IQR)15262500

Descriptive statistics

Standard deviation1.4479993 × 108
Coefficient of variation (CV)5.1738451
Kurtosis385.72743
Mean27986908
Median Absolute Deviation (MAD)5500000
Skewness18.915706
Sum1.2985926 × 1010
Variance2.096702 × 1016
MonotonicityNot monotonic
2023-12-11T08:41:11.875602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000000 34
 
5.4%
3000000 25
 
4.0%
5000000 24
 
3.8%
4000000 23
 
3.7%
15000000 18
 
2.9%
20000000 18
 
2.9%
8000000 14
 
2.2%
7000000 13
 
2.1%
6000000 9
 
1.4%
100000000 8
 
1.3%
Other values (190) 278
44.5%
(Missing) 161
25.8%
ValueCountFrequency (%)
360000 1
0.2%
561000 1
0.2%
745000 1
0.2%
840000 1
0.2%
929000 1
0.2%
956000 1
0.2%
1011000 1
0.2%
1082000 1
0.2%
1109000 1
0.2%
1144000 1
0.2%
ValueCountFrequency (%)
3000000000 1
0.2%
500000000 1
0.2%
430000000 1
0.2%
300000000 1
0.2%
292000000 1
0.2%
184200000 1
0.2%
170000000 1
0.2%
158550000 1
0.2%
136500000 1
0.2%
130000000 1
0.2%

집행정보
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct248
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27562134
Minimum0
Maximum5 × 109
Zeros245
Zeros (%)39.2%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-11T08:41:11.991241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3484000
Q310000000
95-th percentile74594359
Maximum5 × 109
Range5 × 109
Interquartile range (IQR)10000000

Descriptive statistics

Standard deviation2.1670651 × 108
Coefficient of variation (CV)7.8624721
Kurtosis448.07713
Mean27562134
Median Absolute Deviation (MAD)3484000
Skewness20.002092
Sum1.7226334 × 1010
Variance4.696171 × 1016
MonotonicityNot monotonic
2023-12-11T08:41:12.111469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 245
39.2%
10000000 25
 
4.0%
5000000 17
 
2.7%
4000000 15
 
2.4%
20000000 11
 
1.8%
3000000 10
 
1.6%
8000000 8
 
1.3%
15000000 7
 
1.1%
13000000 5
 
0.8%
80000000 5
 
0.8%
Other values (238) 277
44.3%
ValueCountFrequency (%)
0 245
39.2%
36340 1
 
0.2%
41530 1
 
0.2%
100000 1
 
0.2%
130000 1
 
0.2%
336490 1
 
0.2%
360000 1
 
0.2%
400000 1
 
0.2%
561000 1
 
0.2%
592500 1
 
0.2%
ValueCountFrequency (%)
5000000000 1
0.2%
1088271584 1
0.2%
1025349902 1
0.2%
1019597186 1
0.2%
697308070 1
0.2%
492781350 1
0.2%
399548452 1
0.2%
284442000 1
0.2%
281291511 1
0.2%
257400000 1
0.2%

집행잔액
Real number (ℝ)

ZEROS 

Distinct209
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4918714.5
Minimum-1.84442 × 108
Maximum2.265 × 108
Zeros381
Zeros (%)61.0%
Negative37
Negative (%)5.9%
Memory size5.6 KiB
2023-12-11T08:41:12.477715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.84442 × 108
5-th percentile-500
Q10
median0
Q3354550
95-th percentile32200000
Maximum2.265 × 108
Range4.10942 × 108
Interquartile range (IQR)354550

Descriptive statistics

Standard deviation22429386
Coefficient of variation (CV)4.5600097
Kurtosis51.248296
Mean4918714.5
Median Absolute Deviation (MAD)0
Skewness4.682837
Sum3.0741966 × 109
Variance5.0307734 × 1014
MonotonicityNot monotonic
2023-12-11T08:41:12.588422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 381
61.0%
3000000 7
 
1.1%
10000000 6
 
1.0%
15000000 5
 
0.8%
5000000 4
 
0.6%
20000000 4
 
0.6%
27000000 3
 
0.5%
4000000 3
 
0.5%
31000000 2
 
0.3%
3500000 2
 
0.3%
Other values (199) 208
33.3%
ValueCountFrequency (%)
-184442000 1
0.2%
-40016754 1
0.2%
-19918640 1
0.2%
-18000000 1
0.2%
-15000000 2
0.3%
-14988560 1
0.2%
-10000000 2
0.3%
-9998461 1
0.2%
-6883890 1
0.2%
-6000000 1
0.2%
ValueCountFrequency (%)
226500000 1
0.2%
200000000 1
0.2%
195000000 1
0.2%
185852560 1
0.2%
148000000 1
0.2%
141000000 1
0.2%
88000000 1
0.2%
80000000 1
0.2%
76780000 1
0.2%
70000000 1
0.2%

Interactions

2023-12-11T08:41:08.666105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:05.968743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.460721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.940360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.674315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.178813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.744915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.048412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.556338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.020927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.755268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.259632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.816192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.128402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.636234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.095986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.828069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.341455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.890934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.220587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.706358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.191554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.898628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.433792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.972376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.301787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.785119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.293711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.985564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.510446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:09.052933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.380832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:06.865804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:07.386618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.086408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:41:08.587979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:41:12.664990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단체구분부서명신청금액교부결정정보지급정보집행정보집행잔액
순번1.0000.6770.7220.1430.1040.1160.0840.101
단체구분0.6771.0000.8880.0000.0000.0000.0000.449
부서명0.7220.8881.0000.4200.5630.5670.5110.655
신청금액0.1430.0000.4201.0000.9950.9710.8420.200
교부결정정보0.1040.0000.5630.9951.0000.9951.0000.260
지급정보0.1160.0000.5670.9710.9951.0000.8410.299
집행정보0.0840.0000.5110.8421.0000.8411.0000.241
집행잔액0.1010.4490.6550.2000.2600.2990.2411.000
2023-12-11T08:41:12.756024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단체구분부서명
단체구분1.0000.487
부서명0.4871.000
2023-12-11T08:41:12.830942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번신청금액교부결정정보지급정보집행정보집행잔액단체구분부서명
순번1.0000.0490.016-0.045-0.0140.0180.3250.333
신청금액0.0491.0000.9440.9750.5970.3160.0000.223
교부결정정보0.0160.9441.0000.9730.6500.3420.0000.327
지급정보-0.0450.9750.9731.0000.4740.2650.0000.327
집행정보-0.0140.5970.6500.4741.000-0.2020.0000.275
집행잔액0.0180.3160.3420.265-0.2021.0000.2200.474
단체구분0.3250.0000.0000.0000.0000.2201.0000.487
부서명0.3330.2230.3270.3270.2750.4740.4871.000

Missing values

2023-12-11T08:41:09.161665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:41:09.301151image/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.
2023-12-11T08:41:09.402978image/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

순번회계연도단체구분부서명보조사업명지급일자신청금액교부결정정보지급정보집행정보집행잔액
012022사단법인행정과3.15의거기념식<NA>00<NA>00
122022사단법인행정과3.15의거기념행사<NA>00<NA>00
232022사단법인농업기술원 기술보급과2022년도벤처농업신성장활력창출마케팅지원사업<NA>1282500012825000<NA>00
342022비영리법인행정과비영리민간단체공익활동지원사업2022-04-22300000030000003000000297000030000
452022비영리법인환경정책과민간단체환경보전활동지원2022-04-223950000395000039500003950010-10
562022비영리법인환경정책과야생동물보호사업(경남수렵인참여연대)2022-02-098000000800000080000007999458542
672022비영리법인농식품유통과경남수출농식품단체(업체)역량강화지원(2022년경남수출파프리카수출전진대회)<NA>00<NA>00
782022사단법인장애인복지과장애인단체운영비보조(경남신체장애인복지회운영)2022-01-20/n/r2022-09-1411000000110000008800000011000000
892022사단법인장애인복지과장애인단체지원센터보조(장애인문화센터)2022-01-17/n/r2022-09-062265000002265000001585500000226500000
9102022사단법인장애인복지과장애인사회참여지원(영호남신체장애인복지증진대회)2022-10-31342000034200003420000333459085410
순번회계연도단체구분부서명보조사업명지급일자신청금액교부결정정보지급정보집행정보집행잔액
6156162022주식회사소통담당관경상남도지역신문발전지원사업(지역축제활성화사업)<NA>00<NA>00
6166172022주식회사소통담당관경상남도지역신문발전지원사업(취재편집환경개선사업)<NA>00<NA>00
6176182022개인사업자장애인복지과장애인단체운영비보조(한우리인성회운영)<NA>100000000<NA>00
6186192022개인사업자장애인복지과장애인사회적응훈련(야영대회)2022-06-22100000001000000010000000010000000
6196202022기타단체장애인복지과장애인재활프로그램지원(제14회한울타리장애인자립생활대회)2022-11-1525000002500000250000025000000
6206212022주식회사소통담당관경상남도지역신문발전지원사업(일반공모(공익광고)지원사업)<NA>00<NA>00
6216222022주식회사소통담당관경상남도지역신문발전지원사업(일반공모(기획취재)지원사업)<NA>00<NA>00
6226232022비영리법인환경정책과민간단체환경보전활동지원2022-04-22401500040150004015000401491090
6236242022기타단체행정과비영리민간단체공익활동지원사업2022-04-2270000007000000700000070000000
6246252022기타단체여성정책과양성평등사업지원(배우고나누고소통하고-희망나라)2022-05-0250000005000000500000050000000