Overview

Dataset statistics

Number of variables10
Number of observations230
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.4 KiB
Average record size in memory86.6 B

Variable types

Categorical2
Text3
Numeric5

Dataset

Description행사축제 원가회계 정보 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=OMP3GERBUN31LY7R9HGE22974974&infSeq=1

Alerts

회계연도 is highly overall correlated with 개최시작일자 and 2 other fieldsHigh correlation
시군명 is highly overall correlated with 회계연도High correlation
총비용금액(원) is highly overall correlated with 원가금액(원)High correlation
원가금액(원) is highly overall correlated with 총비용금액(원)High correlation
개최시작일자 is highly overall correlated with 회계연도High correlation
개최종료일자 is highly overall correlated with 회계연도High correlation
시군명 is highly imbalanced (69.3%)Imbalance
총비용금액(원) has 4 (1.7%) zerosZeros
사업수익금액(원) has 155 (67.4%) zerosZeros
원가금액(원) has 4 (1.7%) zerosZeros

Reproduction

Analysis started2023-12-10 21:14:34.094341
Analysis finished2023-12-10 21:14:37.653792
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회계연도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2020
189 
2021
41 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2020 189
82.2%
2021 41
 
17.8%

Length

2023-12-11T06:14:37.704795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:14:37.784848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 189
82.2%
2021 41
 
17.8%

시군명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
189 
경기도
 
14
부천시
 
5
수원시
 
5
의정부시
 
4
Other values (12)
 
13

Length

Max length4
Median length4
Mean length3.8434783
Min length3

Unique

Unique11 ?
Unique (%)4.8%

Sample

1st row가평군
2nd row경기도
3rd row경기도
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
<NA> 189
82.2%
경기도 14
 
6.1%
부천시 5
 
2.2%
수원시 5
 
2.2%
의정부시 4
 
1.7%
여주시 2
 
0.9%
양주시 1
 
0.4%
구리시 1
 
0.4%
남양주시 1
 
0.4%
성남시 1
 
0.4%
Other values (7) 7
 
3.0%

Length

2023-12-11T06:14:37.875207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 189
82.2%
경기도 14
 
6.1%
부천시 5
 
2.2%
수원시 5
 
2.2%
의정부시 4
 
1.7%
여주시 2
 
0.9%
파주시 1
 
0.4%
양평군 1
 
0.4%
화성시 1
 
0.4%
연천군 1
 
0.4%
Other values (7) 7
 
3.0%

자치단체명
Text

Distinct92
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-11T06:14:38.118603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.7173913
Min length4

Characters and Unicode

Total characters1085
Distinct characters79
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

Unique47 ?
Unique (%)20.4%

Sample

1st row경기가평군
2nd row경기본청
3rd row경기본청
4th row경기본청
5th row경기본청
ValueCountFrequency (%)
경기본청 23
 
10.0%
부산본청 9
 
3.9%
경기부천시 9
 
3.9%
서울본청 7
 
3.0%
경기수원시 7
 
3.0%
전남순천시 7
 
3.0%
광주본청 6
 
2.6%
강원본청 6
 
2.6%
경남창원시 6
 
2.6%
경기의정부시 6
 
2.6%
Other values (82) 144
62.6%
2023-12-11T06:14:38.586881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 105
 
9.7%
경 97
 
8.9%
청 76
 
7.0%
본 73
 
6.7%
기 66
 
6.1%
남 46
 
4.2%
북 44
 
4.1%
원 43
 
4.0%
군 41
 
3.8%
주 40
 
3.7%
Other values (69) 454
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1085
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 105
 
9.7%
경 97
 
8.9%
청 76
 
7.0%
본 73
 
6.7%
기 66
 
6.1%
남 46
 
4.2%
북 44
 
4.1%
원 43
 
4.0%
군 41
 
3.8%
주 40
 
3.7%
Other values (69) 454
41.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1085
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 105
 
9.7%
경 97
 
8.9%
청 76
 
7.0%
본 73
 
6.7%
기 66
 
6.1%
남 46
 
4.2%
북 44
 
4.1%
원 43
 
4.0%
군 41
 
3.8%
주 40
 
3.7%
Other values (69) 454
41.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1085
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 105
 
9.7%
경 97
 
8.9%
청 76
 
7.0%
본 73
 
6.7%
기 66
 
6.1%
남 46
 
4.2%
북 44
 
4.1%
원 43
 
4.0%
군 41
 
3.8%
주 40
 
3.7%
Other values (69) 454
41.8%

행사축제명
Text

Distinct208
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-11T06:14:38.965358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length25
Mean length10.495652
Min length3

Characters and Unicode

Total characters2414
Distinct characters367
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)81.3%

Sample

1st row자라섬 국제재즈페스티벌
2nd row경기국제보트쇼
3rd row퓨처 쇼 개최
4th row플레이엑스포
5th row대한민국 우수상품 전시회(G-FAIR KOREA)
ValueCountFrequency (%)
개최 10
 
2.3%
대한민국 9
 
2.0%
2020 9
 
2.0%
문화재 7
 
1.6%
야행 6
 
1.4%
페스티벌 6
 
1.4%
행사 5
 
1.1%
운영 5
 
1.1%
dmz 5
 
1.1%
및 5
 
1.1%
Other values (320) 377
84.9%
2023-12-11T06:14:39.434945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
214
 
8.9%
제 139
 
5.8%
국 71
 
2.9%
화 71
 
2.9%
축 50
 
2.1%
대 49
 
2.0%
전 45
 
1.9%
문 41
 
1.7%
산 36
 
1.5%
회 36
 
1.5%
Other values (357) 1662
68.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2000
82.9%
Space Separator 214
 
8.9%
Uppercase Letter 90
 
3.7%
Decimal Number 58
 
2.4%
Lowercase Letter 18
 
0.7%
Close Punctuation 10
 
0.4%
Open Punctuation 10
 
0.4%
Other Punctuation 9
 
0.4%
Dash Punctuation 4
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 139
 
7.0%
국 71
 
3.5%
화 71
 
3.5%
축 50
 
2.5%
대 49
 
2.5%
전 45
 
2.2%
문 41
 
2.1%
산 36
 
1.8%
회 36
 
1.8%
스 35
 
1.8%
Other values (308) 1427
71.4%
Uppercase Letter
ValueCountFrequency (%)
A 10
 
11.1%
M 8
 
8.9%
O 7
 
7.8%
D 7
 
7.8%
Z 7
 
7.8%
P 6
 
6.7%
E 5
 
5.6%
F 5
 
5.6%
I 5
 
5.6%
K 5
 
5.6%
Other values (11) 25
27.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
16.7%
n 3
16.7%
t 2
11.1%
s 2
11.1%
i 2
11.1%
a 1
 
5.6%
r 1
 
5.6%
u 1
 
5.6%
c 1
 
5.6%
h 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 22
37.9%
0 22
37.9%
1 3
 
5.2%
7 3
 
5.2%
6 3
 
5.2%
5 2
 
3.4%
3 2
 
3.4%
9 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
' 6
66.7%
. 1
 
11.1%
& 1
 
11.1%
! 1
 
11.1%
Space Separator
ValueCountFrequency (%)
214
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
× 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2000
82.9%
Common 306
 
12.7%
Latin 108
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 139
 
7.0%
국 71
 
3.5%
화 71
 
3.5%
축 50
 
2.5%
대 49
 
2.5%
전 45
 
2.2%
문 41
 
2.1%
산 36
 
1.8%
회 36
 
1.8%
스 35
 
1.8%
Other values (308) 1427
71.4%
Latin
ValueCountFrequency (%)
A 10
 
9.3%
M 8
 
7.4%
O 7
 
6.5%
D 7
 
6.5%
Z 7
 
6.5%
P 6
 
5.6%
E 5
 
4.6%
F 5
 
4.6%
I 5
 
4.6%
K 5
 
4.6%
Other values (22) 43
39.8%
Common
ValueCountFrequency (%)
214
69.9%
2 22
 
7.2%
0 22
 
7.2%
) 10
 
3.3%
( 10
 
3.3%
' 6
 
2.0%
- 4
 
1.3%
1 3
 
1.0%
7 3
 
1.0%
6 3
 
1.0%
Other values (7) 9
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2000
82.9%
ASCII 413
 
17.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
214
51.8%
2 22
 
5.3%
0 22
 
5.3%
A 10
 
2.4%
) 10
 
2.4%
( 10
 
2.4%
M 8
 
1.9%
O 7
 
1.7%
D 7
 
1.7%
Z 7
 
1.7%
Other values (38) 96
23.2%
Hangul
ValueCountFrequency (%)
제 139
 
7.0%
국 71
 
3.5%
화 71
 
3.5%
축 50
 
2.5%
대 49
 
2.5%
전 45
 
2.2%
문 41
 
2.1%
산 36
 
1.8%
회 36
 
1.8%
스 35
 
1.8%
Other values (308) 1427
71.4%
None
ValueCountFrequency (%)
× 1
100.0%

사업내용
Text

Distinct226
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-11T06:14:39.840291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length419
Median length142
Mean length82.330435
Min length9

Characters and Unicode

Total characters18936
Distinct characters694
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique222 ?
Unique (%)96.5%

Sample

1st row야외 재즈공연 및 부대행사
2nd row전시회 개최 및 컨퍼런스 개최, 수출상담회, 교육 및 체험 프로그램 등
3rd row슬로건 : 디지털 산책(Meet The Future) 운영방식 : 비대면 워킹스루 행사구성 : 19개 프로그램(AR증강현실, 로보틱스, VR패션쇼, 디지털 사이니지 등)
4th row전시회, B2B, e스포츠대회, 기타 부대행사 등
5th row대한민국 우수 중소기업 기술 및 제품 전시, 국내외 바이어 초청, 수출상담회, 구매상담회, 부대행사(세미나, 특강, 설명회 등) 개최
ValueCountFrequency (%)
352
 
8.3%
등 146
 
3.4%
및 116
 
2.7%
○ 69
 
1.6%
온라인 56
 
1.3%
운영 54
 
1.3%
프로그램 54
 
1.3%
전시 40
 
0.9%
개최 37
 
0.9%
공연 37
 
0.9%
Other values (2203) 3291
77.4%
2023-12-11T06:14:40.337673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4022
 
21.2%
, 684
 
3.6%
0 253
 
1.3%
2 250
 
1.3%
1 236
 
1.2%
) 213
 
1.1%
전 210
 
1.1%
( 209
 
1.1%
로 209
 
1.1%
. 202
 
1.1%
Other values (684) 12448
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11359
60.0%
Space Separator 4022
 
21.2%
Other Punctuation 1203
 
6.4%
Decimal Number 1116
 
5.9%
Uppercase Letter 289
 
1.5%
Close Punctuation 215
 
1.1%
Open Punctuation 211
 
1.1%
Dash Punctuation 180
 
1.0%
Lowercase Letter 175
 
0.9%
Other Symbol 88
 
0.5%
Other values (5) 78
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 210
 
1.8%
로 209
 
1.8%
시 200
 
1.8%
화 187
 
1.6%
사 178
 
1.6%
제 171
 
1.5%
등 164
 
1.4%
대 164
 
1.4%
영 159
 
1.4%
연 156
 
1.4%
Other values (586) 9561
84.2%
Uppercase Letter
ValueCountFrequency (%)
B 27
 
9.3%
D 21
 
7.3%
M 21
 
7.3%
T 18
 
6.2%
S 17
 
5.9%
I 16
 
5.5%
P 16
 
5.5%
E 15
 
5.2%
A 15
 
5.2%
K 15
 
5.2%
Other values (14) 108
37.4%
Lowercase Letter
ValueCountFrequency (%)
e 23
13.1%
o 20
11.4%
n 20
11.4%
i 15
8.6%
t 13
 
7.4%
a 13
 
7.4%
r 12
 
6.9%
u 10
 
5.7%
s 7
 
4.0%
w 6
 
3.4%
Other values (13) 36
20.6%
Other Punctuation
ValueCountFrequency (%)
, 684
56.9%
. 202
 
16.8%
: 201
 
16.7%
/ 40
 
3.3%
· 27
 
2.2%
' 17
 
1.4%
* 9
 
0.7%
& 8
 
0.7%
! 3
 
0.2%
% 3
 
0.2%
Other values (5) 9
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 253
22.7%
2 250
22.4%
1 236
21.1%
8 68
 
6.1%
3 61
 
5.5%
5 59
 
5.3%
9 58
 
5.2%
6 51
 
4.6%
4 46
 
4.1%
7 34
 
3.0%
Math Symbol
ValueCountFrequency (%)
~ 44
67.7%
> 8
 
12.3%
< 7
 
10.8%
+ 3
 
4.6%
→ 2
 
3.1%
～ 1
 
1.5%
Other Symbol
ValueCountFrequency (%)
○ 76
86.4%
◎ 7
 
8.0%
□ 3
 
3.4%
☞ 2
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 213
99.1%
】 1
 
0.5%
」 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 209
99.1%
【 1
 
0.5%
「 1
 
0.5%
Other Number
ValueCountFrequency (%)
① 1
33.3%
② 1
33.3%
③ 1
33.3%
Final Punctuation
ValueCountFrequency (%)
” 2
66.7%
’ 1
33.3%
Initial Punctuation
ValueCountFrequency (%)
“ 2
66.7%
‘ 1
33.3%
Space Separator
ValueCountFrequency (%)
4022
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 180
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11353
60.0%
Common 7113
37.6%
Latin 464
 
2.5%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 210
 
1.8%
로 209
 
1.8%
시 200
 
1.8%
화 187
 
1.6%
사 178
 
1.6%
제 171
 
1.5%
등 164
 
1.4%
대 164
 
1.4%
영 159
 
1.4%
연 156
 
1.4%
Other values (585) 9555
84.2%
Common
ValueCountFrequency (%)
4022
56.5%
, 684
 
9.6%
0 253
 
3.6%
2 250
 
3.5%
1 236
 
3.3%
) 213
 
3.0%
( 209
 
2.9%
. 202
 
2.8%
: 201
 
2.8%
- 180
 
2.5%
Other values (41) 663
 
9.3%
Latin
ValueCountFrequency (%)
B 27
 
5.8%
e 23
 
5.0%
D 21
 
4.5%
M 21
 
4.5%
o 20
 
4.3%
n 20
 
4.3%
T 18
 
3.9%
S 17
 
3.7%
I 16
 
3.4%
P 16
 
3.4%
Other values (37) 265
57.1%
Han
ValueCountFrequency (%)
夜 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11325
59.8%
ASCII 7442
39.3%
Geometric Shapes 86
 
0.5%
None 34
 
0.2%
Compat Jamo 28
 
0.1%
Punctuation 8
 
< 0.1%
CJK 6
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Arrows 2
 
< 0.1%
Misc Symbols 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4022
54.0%
, 684
 
9.2%
0 253
 
3.4%
2 250
 
3.4%
1 236
 
3.2%
) 213
 
2.9%
( 209
 
2.8%
. 202
 
2.7%
: 201
 
2.7%
- 180
 
2.4%
Other values (68) 992
 
13.3%
Hangul
ValueCountFrequency (%)
전 210
 
1.9%
로 209
 
1.8%
시 200
 
1.8%
화 187
 
1.7%
사 178
 
1.6%
제 171
 
1.5%
등 164
 
1.4%
대 164
 
1.4%
영 159
 
1.4%
연 156
 
1.4%
Other values (583) 9527
84.1%
Geometric Shapes
ValueCountFrequency (%)
○ 76
88.4%
◎ 7
 
8.1%
□ 3
 
3.5%
None
ValueCountFrequency (%)
· 27
79.4%
？ 2
 
5.9%
～ 1
 
2.9%
【 1
 
2.9%
】 1
 
2.9%
「 1
 
2.9%
」 1
 
2.9%
Compat Jamo
ValueCountFrequency (%)
ㅇ 24
85.7%
ㆍ 4
 
14.3%
CJK
ValueCountFrequency (%)
夜 6
100.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Misc Symbols
ValueCountFrequency (%)
☞ 2
100.0%
Punctuation
ValueCountFrequency (%)
※ 2
25.0%
” 2
25.0%
“ 2
25.0%
‘ 1
12.5%
’ 1
12.5%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
33.3%
② 1
33.3%
③ 1
33.3%

총비용금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct217
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2548999 × 108
Minimum0
Maximum4.5398137 × 109
Zeros4
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-11T06:14:40.478899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.0330885 × 108
Q14.2495888 × 108
median5.9992 × 108
Q39.7670862 × 108
95-th percentile2.4002106 × 109
Maximum4.5398137 × 109
Range4.5398137 × 109
Interquartile range (IQR)5.5174975 × 108

Descriptive statistics

Standard deviation6.6304887 × 108
Coefficient of variation (CV)0.80321854
Kurtosis6.895117
Mean8.2548999 × 108
Median Absolute Deviation (MAD)2.1057226 × 108
Skewness2.3685697
Sum1.898627 × 1011
Variance4.396338 × 1017
MonotonicityNot monotonic
2023-12-11T06:14:40.613237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400000000 4
 
1.7%
0 4
 
1.7%
500000000 4
 
1.7%
300000000 3
 
1.3%
570000000 2
 
0.9%
600000000 2
 
0.9%
360000000 1
 
0.4%
560297216 1
 
0.4%
619066590 1
 
0.4%
383000000 1
 
0.4%
Other values (207) 207
90.0%
ValueCountFrequency (%)
0 4
1.7%
141213127 1
 
0.4%
235889000 1
 
0.4%
300000000 3
1.3%
300700267 1
 
0.4%
301521360 1
 
0.4%
301700000 1
 
0.4%
305275230 1
 
0.4%
305569500 1
 
0.4%
310749170 1
 
0.4%
ValueCountFrequency (%)
4539813687 1
0.4%
3494912770 1
0.4%
3411483077 1
0.4%
2899464800 1
0.4%
2868681781 1
0.4%
2866823977 1
0.4%
2835288884 1
0.4%
2692026940 1
0.4%
2637607230 1
0.4%
2590333000 1
0.4%

사업수익금액(원)
Real number (ℝ)

ZEROS 

Distinct64
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77023581
Minimum0
Maximum1.0814831 × 109
Zeros155
Zeros (%)67.4%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-11T06:14:40.765188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q368600000
95-th percentile4.7050418 × 108
Maximum1.0814831 × 109
Range1.0814831 × 109
Interquartile range (IQR)68600000

Descriptive statistics

Standard deviation1.7199063 × 108
Coefficient of variation (CV)2.2329607
Kurtosis11.054588
Mean77023581
Median Absolute Deviation (MAD)0
Skewness3.11614
Sum1.7715424 × 1010
Variance2.9580776 × 1016
MonotonicityNot monotonic
2023-12-11T06:14:40.889056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
67.4%
150000000 4
 
1.7%
80000000 3
 
1.3%
290000000 2
 
0.9%
100000000 2
 
0.9%
250000000 2
 
0.9%
45450000 2
 
0.9%
50000000 2
 
0.9%
75000000 2
 
0.9%
85000000 2
 
0.9%
Other values (54) 54
 
23.5%
ValueCountFrequency (%)
0 155
67.4%
141440 1
 
0.4%
2700000 1
 
0.4%
5182000 1
 
0.4%
5878500 1
 
0.4%
13891740 1
 
0.4%
18211960 1
 
0.4%
25000000 1
 
0.4%
44766000 1
 
0.4%
45450000 2
 
0.9%
ValueCountFrequency (%)
1081483077 1
0.4%
996632880 1
0.4%
752870000 1
0.4%
733307900 1
0.4%
705000000 1
0.4%
665575000 1
0.4%
634536138 1
0.4%
533049420 1
0.4%
528212503 1
0.4%
502304180 1
0.4%

원가금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct217
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4846641 × 108
Minimum0
Maximum4.5398137 × 109
Zeros4
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-11T06:14:41.027538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.753837 × 108
Q13.5755943 × 108
median5.4502072 × 108
Q39.1761541 × 108
95-th percentile2.3469171 × 109
Maximum4.5398137 × 109
Range4.5398137 × 109
Interquartile range (IQR)5.6005598 × 108

Descriptive statistics

Standard deviation6.5892333 × 108
Coefficient of variation (CV)0.8803646
Kurtosis7.2718368
Mean7.4846641 × 108
Median Absolute Deviation (MAD)2.323916 × 108
Skewness2.4045673
Sum1.7214727 × 1011
Variance4.3417996 × 1017
MonotonicityNot monotonic
2023-12-11T06:14:41.160800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400000000 4
 
1.7%
0 4
 
1.7%
250000000 3
 
1.3%
650000000 2
 
0.9%
570000000 2
 
0.9%
450000000 2
 
0.9%
500000000 2
 
0.9%
300000000 2
 
0.9%
630000000 1
 
0.4%
150000000 1
 
0.4%
Other values (207) 207
90.0%
ValueCountFrequency (%)
0 4
1.7%
69355150 1
 
0.4%
71035872 1
 
0.4%
100720495 1
 
0.4%
111900267 1
 
0.4%
141213127 1
 
0.4%
150000000 1
 
0.4%
161700000 1
 
0.4%
170397584 1
 
0.4%
181477837 1
 
0.4%
ValueCountFrequency (%)
4539813687 1
0.4%
3494912770 1
0.4%
2899464800 1
0.4%
2868681781 1
0.4%
2866823977 1
0.4%
2835288884 1
0.4%
2692026940 1
0.4%
2637607230 1
0.4%
2590333000 1
0.4%
2475546259 1
0.4%

개최시작일자
Real number (ℝ)

HIGH CORRELATION 

Distinct134
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20202544
Minimum20200101
Maximum20211214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-11T06:14:41.279339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200101
5-th percentile20200101
Q120200803
median20201016
Q320201115
95-th percentile20211008
Maximum20211214
Range11113
Interquartile range (IQR)311.75

Descriptive statistics

Standard deviation3786.9579
Coefficient of variation (CV)0.00018744955
Kurtosis0.99578933
Mean20202544
Median Absolute Deviation (MAD)194
Skewness1.7107128
Sum4.6465852 × 109
Variance14341050
MonotonicityNot monotonic
2023-12-11T06:14:41.408370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200101 18
 
7.8%
20201023 8
 
3.5%
20201016 5
 
2.2%
20201030 5
 
2.2%
20210101 5
 
2.2%
20201105 5
 
2.2%
20201009 4
 
1.7%
20201015 4
 
1.7%
20201112 3
 
1.3%
20201007 3
 
1.3%
Other values (124) 170
73.9%
ValueCountFrequency (%)
20200101 18
7.8%
20200103 1
 
0.4%
20200114 1
 
0.4%
20200118 1
 
0.4%
20200122 1
 
0.4%
20200127 1
 
0.4%
20200130 1
 
0.4%
20200201 3
 
1.3%
20200209 1
 
0.4%
20200301 1
 
0.4%
ValueCountFrequency (%)
20211214 1
0.4%
20211203 1
0.4%
20211130 1
0.4%
20211126 1
0.4%
20211125 1
0.4%
20211112 1
0.4%
20211105 1
0.4%
20211027 1
0.4%
20211022 1
0.4%
20211015 1
0.4%

개최종료일자
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20203350
Minimum20200105
Maximum20221024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-11T06:14:41.536916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200105
5-th percentile20200721
Q120201018
median20201115
Q320201231
95-th percentile20211211
Maximum20221024
Range20919
Interquartile range (IQR)213

Descriptive statistics

Standard deviation4495.39
Coefficient of variation (CV)0.00022250716
Kurtosis1.8064431
Mean20203350
Median Absolute Deviation (MAD)116
Skewness1.6703006
Sum4.6467705 × 109
Variance20208531
MonotonicityNot monotonic
2023-12-11T06:14:41.960229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20201231 30
 
13.0%
20201031 8
 
3.5%
20201108 8
 
3.5%
20201024 7
 
3.0%
20201115 7
 
3.0%
20211231 7
 
3.0%
20201018 6
 
2.6%
20201101 6
 
2.6%
20201130 5
 
2.2%
20201025 5
 
2.2%
Other values (95) 141
61.3%
ValueCountFrequency (%)
20200105 1
0.4%
20200127 2
0.9%
20200211 1
0.4%
20200216 1
0.4%
20200412 1
0.4%
20200505 1
0.4%
20200623 1
0.4%
20200628 1
0.4%
20200708 1
0.4%
20200716 1
0.4%
ValueCountFrequency (%)
20221024 1
 
0.4%
20221016 1
 
0.4%
20220320 1
 
0.4%
20211231 7
3.0%
20211226 1
 
0.4%
20211212 1
 
0.4%
20211209 1
 
0.4%
20211203 1
 
0.4%
20211129 2
 
0.9%
20211128 3
1.3%

Interactions

2023-12-11T06:14:37.035541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.062089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.506602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.039918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.482538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:37.109022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.140939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.584665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.131013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.566297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:37.182507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.240027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.690918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.228414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.685479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:37.260277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.326891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.810942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.319191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.813490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:37.355288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.427205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:35.926103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.405082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:14:36.939924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:14:42.064857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명자치단체명총비용금액(원)사업수익금액(원)원가금액(원)개최시작일자개최종료일자
회계연도1.000NaN0.7050.1320.1010.1681.0000.974
시군명NaN1.0001.0000.0000.0000.0000.9660.000
자치단체명0.7051.0001.0000.0000.0000.0000.5870.593
총비용금액(원)0.1320.0000.0001.0000.4590.9940.0000.000
사업수익금액(원)0.1010.0000.0000.4591.0000.0740.0000.000
원가금액(원)0.1680.0000.0000.9940.0741.0000.1010.000
개최시작일자1.0000.9660.5870.0000.0000.1011.0000.858
개최종료일자0.9740.0000.5930.0000.0000.0000.8581.000
2023-12-11T06:14:42.199432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회계연도시군명
회계연도1.0001.000
시군명1.0001.000
2023-12-11T06:14:42.302160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총비용금액(원)사업수익금액(원)원가금액(원)개최시작일자개최종료일자회계연도시군명
총비용금액(원)1.000-0.0400.9080.002-0.0470.1290.000
사업수익금액(원)-0.0401.000-0.3700.039-0.0310.0740.000
원가금액(원)0.908-0.3701.0000.0350.0140.1650.000
개최시작일자0.0020.0390.0351.0000.4790.9810.255
개최종료일자-0.047-0.0310.0140.4791.0000.8520.000
회계연도0.1290.0740.1650.9810.8521.0001.000
시군명0.0000.0000.0000.2550.0001.0001.000

Missing values

2023-12-11T06:14:37.461399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:14:37.590368image/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

회계연도시군명자치단체명행사축제명사업내용총비용금액(원)사업수익금액(원)원가금액(원)개최시작일자개최종료일자
02021가평군경기가평군자라섬 국제재즈페스티벌야외 재즈공연 및 부대행사40000000004000000002021110520211107
12021경기도경기본청경기국제보트쇼전시회 개최 및 컨퍼런스 개최, 수출상담회, 교육 및 체험 프로그램 등1402322642014023226422021100120211003
22021경기도경기본청퓨처 쇼 개최슬로건 : 디지털 산책(Meet The Future) 운영방식 : 비대면 워킹스루 행사구성 : 19개 프로그램(AR증강현실, 로보틱스, VR패션쇼, 디지털 사이니지 등)1043756000010437560002021100720211010
32021경기도경기본청플레이엑스포전시회, B2B, e스포츠대회, 기타 부대행사 등152008295617715600013429269562021051020210514
42021경기도경기본청대한민국 우수상품 전시회(G-FAIR KOREA)대한민국 우수 중소기업 기술 및 제품 전시, 국내외 바이어 초청, 수출상담회, 구매상담회, 부대행사(세미나, 특강, 설명회 등) 개최1199585000011995850002021102720211030
52021경기도경기본청DMZ국제다큐영화제DMZ국제다큐멘터리영화제 개최, 제작지원 및 다큐멘터리 산업행사개최, 다큐저변확대를 위한 상시사업 운영2868681781028686817812021090920210916
62021경기도경기본청경기정원문화박람회정원작품 공모전, 모델정원 조성, 컨퍼런스 개최, 정원문화 프로그램 및 콘텐츠 제공59984000005998400002021100820211024
72021경기도경기본청웹툰 페어 개최웹툰 전시회(B2C)는 행사 개최, 수출상담회(B2B) 및 컨퍼런스는 온라인생중계63053900058785006246605002021100720211010
82021경기도경기본청DMZ 포럼개회식, 기조연설, 한반도 비핵화와 남북관계 등 20개 주제를 특별, 기획, 평화운동협력 3개 분야로 구분하여 운영, DMZ포럼 경기평화선언1099752357010997523572021052120210522
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2202020<NA>경기본청Let's DMZDMZ 일원 대규모 음악공연, 전시·체험 등 통합 개최(Live in DMZ/DMZ 빌리지/찾아가는 Let's DMZ)2637607230026376072302020102320201025
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