Overview

Dataset statistics

Number of variables9
Number of observations48
Missing cells38
Missing cells (%)8.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory78.8 B

Variable types

Numeric4
Categorical1
Text3
Unsupported1

Dataset

Description180360농촌축제지원사업현황
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=203034

Alerts

구분 is highly overall correlated with 계(백만원) and 2 other fieldsHigh correlation
계(백만원) is highly overall correlated with 구분 and 2 other fieldsHigh correlation
국비 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
시군비 is highly overall correlated with 구분 and 2 other fieldsHigh correlation
축제명 has 3 (6.2%) missing valuesMissing
기간 has 6 (12.5%) missing valuesMissing
계(백만원) has 6 (12.5%) missing valuesMissing
국비 has 6 (12.5%) missing valuesMissing
시군비 has 6 (12.5%) missing valuesMissing
자담 has 11 (22.9%) missing valuesMissing
자담 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 03:14:30.815824
Analysis finished2024-03-14 03:14:32.684574
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.2083
Minimum2008
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-03-14T12:14:32.766817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2009
Q12012
median2014.5
Q32017
95-th percentile2018
Maximum2018
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9961559
Coefficient of variation (CV)0.0014875104
Kurtosis-0.83845891
Mean2014.2083
Median Absolute Deviation (MAD)2.5
Skewness-0.44255168
Sum96682
Variance8.9769504
MonotonicityDecreasing
2024-03-14T12:14:32.871947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2018 8
16.7%
2017 6
12.5%
2014 6
12.5%
2016 5
10.4%
2015 5
10.4%
2013 4
8.3%
2012 4
8.3%
2011 3
 
6.2%
2010 3
 
6.2%
2009 2
 
4.2%
ValueCountFrequency (%)
2008 2
 
4.2%
2009 2
 
4.2%
2010 3
6.2%
2011 3
6.2%
2012 4
8.3%
2013 4
8.3%
2014 6
12.5%
2015 5
10.4%
2016 5
10.4%
2017 6
12.5%
ValueCountFrequency (%)
2018 8
16.7%
2017 6
12.5%
2016 5
10.4%
2015 5
10.4%
2014 6
12.5%
2013 4
8.3%
2012 4
8.3%
2011 3
 
6.2%
2010 3
 
6.2%
2009 2
 
4.2%

시군
Categorical

Distinct12
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
익산
7 
남원
7 
정읍
6 
진안
6 
완주
4 
Other values (7)
18 

Length

Max length3
Median length2
Mean length2.0416667
Min length2

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row익산
2nd row정읍
3rd row정읍
4th row남원
5th row완주

Common Values

ValueCountFrequency (%)
익산 7
14.6%
남원 7
14.6%
정읍 6
12.5%
진안 6
12.5%
완주 4
8.3%
임실 4
8.3%
고창 4
8.3%
장수 3
6.2%
임실 2
 
4.2%
부안 2
 
4.2%
Other values (2) 3
6.2%

Length

2024-03-14T12:14:32.979469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
익산 7
14.6%
남원 7
14.6%
정읍 6
12.5%
진안 6
12.5%
임실 6
12.5%
완주 4
8.3%
고창 4
8.3%
장수 3
6.2%
부안 2
 
4.2%
김제 2
 
4.2%

축제명
Text

MISSING 

Distinct32
Distinct (%)71.1%
Missing3
Missing (%)6.2%
Memory size516.0 B
2024-03-14T12:14:33.159477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length11.777778
Min length4

Characters and Unicode

Total characters530
Distinct characters137
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)51.1%

Sample

1st row용머리 고을 억새 축제(신규)
2nd row다 같이 노~올자 동네한바퀴
3rd row신기 복드림 축제 (신규)
4th row노봉마을 산행길 축제
5th row완주-GUN 포차축제 (신규)
ValueCountFrequency (%)
축제 30
 
21.6%
다 4
 
2.9%
같이 4
 
2.9%
송천 3
 
2.2%
꽃잔디 3
 
2.2%
말천방 3
 
2.2%
들노래 3
 
2.2%
생생 3
 
2.2%
하전마을 3
 
2.2%
블루베리 3
 
2.2%
Other values (59) 80
57.6%
2024-03-14T12:14:33.650858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
 
17.7%
축 40
 
7.5%
제 40
 
7.5%
마 15
 
2.8%
을 15
 
2.8%
이 9
 
1.7%
노 9
 
1.7%
) 8
 
1.5%
( 8
 
1.5%
산 8
 
1.5%
Other values (127) 284
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
76.4%
Space Separator 94
 
17.7%
Close Punctuation 8
 
1.5%
Open Punctuation 8
 
1.5%
Lowercase Letter 4
 
0.8%
Math Symbol 3
 
0.6%
Uppercase Letter 3
 
0.6%
Other Punctuation 2
 
0.4%
Final Punctuation 1
 
0.2%
Initial Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
축 40
 
9.9%
제 40
 
9.9%
마 15
 
3.7%
을 15
 
3.7%
이 9
 
2.2%
노 9
 
2.2%
산 8
 
2.0%
천 7
 
1.7%
생 7
 
1.7%
리 7
 
1.7%
Other values (113) 248
61.2%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
g 1
25.0%
d 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
U 1
33.3%
N 1
33.3%
Space Separator
ValueCountFrequency (%)
94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
․ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
76.0%
Common 118
 
22.3%
Latin 7
 
1.3%
Han 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
축 40
 
9.9%
제 40
 
9.9%
마 15
 
3.7%
을 15
 
3.7%
이 9
 
2.2%
노 9
 
2.2%
산 8
 
2.0%
천 7
 
1.7%
생 7
 
1.7%
리 7
 
1.7%
Other values (111) 246
61.0%
Common
ValueCountFrequency (%)
94
79.7%
) 8
 
6.8%
( 8
 
6.8%
~ 3
 
2.5%
․ 2
 
1.7%
’ 1
 
0.8%
‘ 1
 
0.8%
- 1
 
0.8%
Latin
ValueCountFrequency (%)
o 2
28.6%
G 1
14.3%
U 1
14.3%
N 1
14.3%
g 1
14.3%
d 1
14.3%
Han
ValueCountFrequency (%)
夜 1
50.0%
月 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 403
76.0%
ASCII 121
 
22.8%
Punctuation 4
 
0.8%
CJK 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
77.7%
) 8
 
6.6%
( 8
 
6.6%
~ 3
 
2.5%
o 2
 
1.7%
- 1
 
0.8%
G 1
 
0.8%
U 1
 
0.8%
N 1
 
0.8%
g 1
 
0.8%
Hangul
ValueCountFrequency (%)
축 40
 
9.9%
제 40
 
9.9%
마 15
 
3.7%
을 15
 
3.7%
이 9
 
2.2%
노 9
 
2.2%
산 8
 
2.0%
천 7
 
1.7%
생 7
 
1.7%
리 7
 
1.7%
Other values (111) 246
61.0%
Punctuation
ValueCountFrequency (%)
․ 2
50.0%
’ 1
25.0%
‘ 1
25.0%
CJK
ValueCountFrequency (%)
夜 1
50.0%
月 1
50.0%

기간
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing6
Missing (%)12.5%
Memory size516.0 B
2024-03-14T12:14:33.805640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19.5
Mean length17.619048
Min length10

Characters and Unicode

Total characters740
Distinct characters21
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)100.0%

Sample

1st row11. 11 (1일간)
2nd row6. 23 (1일간)
3rd row10. 01 (1일간)
4th row10. 13 (2일간)
5th row7월중순 (1일간)
ValueCountFrequency (%)
33
14.9%
2일간 22
 
10.0%
10 19
 
8.6%
5 16
 
7.2%
6 13
 
5.9%
9 11
 
5.0%
8 10
 
4.5%
11 10
 
4.5%
7 9
 
4.1%
3 7
 
3.2%
Other values (35) 71
32.1%
2024-03-14T12:14:34.062041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
24.3%
1 79
10.7%
. 78
10.5%
2 46
 
6.2%
( 42
 
5.7%
일 42
 
5.7%
간 42
 
5.7%
) 42
 
5.7%
~ 35
 
4.7%
0 32
 
4.3%
Other values (11) 122
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 275
37.2%
Space Separator 180
24.3%
Other Letter 87
 
11.8%
Other Punctuation 78
 
10.5%
Open Punctuation 42
 
5.7%
Close Punctuation 42
 
5.7%
Math Symbol 36
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 79
28.7%
2 46
16.7%
0 32
11.6%
3 23
 
8.4%
5 21
 
7.6%
6 20
 
7.3%
9 16
 
5.8%
7 15
 
5.5%
4 12
 
4.4%
8 11
 
4.0%
Other Letter
ValueCountFrequency (%)
일 42
48.3%
간 42
48.3%
월 1
 
1.1%
중 1
 
1.1%
순 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
~ 35
97.2%
～ 1
 
2.8%
Space Separator
ValueCountFrequency (%)
180
100.0%
Other Punctuation
ValueCountFrequency (%)
. 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 653
88.2%
Hangul 87
 
11.8%

Most frequent character per script

Common
ValueCountFrequency (%)
180
27.6%
1 79
12.1%
. 78
11.9%
2 46
 
7.0%
( 42
 
6.4%
) 42
 
6.4%
~ 35
 
5.4%
0 32
 
4.9%
3 23
 
3.5%
5 21
 
3.2%
Other values (6) 75
11.5%
Hangul
ValueCountFrequency (%)
일 42
48.3%
간 42
48.3%
월 1
 
1.1%
중 1
 
1.1%
순 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 652
88.1%
Hangul 87
 
11.8%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
27.6%
1 79
12.1%
. 78
12.0%
2 46
 
7.1%
( 42
 
6.4%
) 42
 
6.4%
~ 35
 
5.4%
0 32
 
4.9%
3 23
 
3.5%
5 21
 
3.2%
Other values (5) 74
11.3%
Hangul
ValueCountFrequency (%)
일 42
48.3%
간 42
48.3%
월 1
 
1.1%
중 1
 
1.1%
순 1
 
1.1%
None
ValueCountFrequency (%)
～ 1
100.0%

장소
Text

Distinct37
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-14T12:14:34.313153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length14.166667
Min length6

Characters and Unicode

Total characters680
Distinct characters149
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)60.4%

Sample

1st row익산시 용안면 석동리 일원
2nd row억새밭 미로 찾기, 마을별 풍물놀이 등
3rd row정읍시 입암면 대흥리 일원
4th row6개마을 및 노인당 합창대회 등
5th row모정음악회, 보물찾기, 자전거타기 등
ValueCountFrequency (%)
및 8
 
4.9%
등 6
 
3.7%
일원 6
 
3.7%
남원 5
 
3.0%
노봉마을(혼불권역 4
 
2.4%
정읍시 4
 
2.4%
입암면 4
 
2.4%
사매면 4
 
2.4%
주천면 3
 
1.8%
꽃잔디동산 3
 
1.8%
Other values (78) 117
71.3%
2024-03-14T12:14:34.651383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
17.1%
면 28
 
4.1%
마 26
 
3.8%
을 26
 
3.8%
원 23
 
3.4%
리 13
 
1.9%
산 11
 
1.6%
시 10
 
1.5%
천 9
 
1.3%
안 9
 
1.3%
Other values (139) 409
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 530
77.9%
Space Separator 116
 
17.1%
Decimal Number 11
 
1.6%
Other Punctuation 6
 
0.9%
Close Punctuation 6
 
0.9%
Open Punctuation 6
 
0.9%
Dash Punctuation 3
 
0.4%
Lowercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 28
 
5.3%
마 26
 
4.9%
을 26
 
4.9%
원 23
 
4.3%
리 13
 
2.5%
산 11
 
2.1%
시 10
 
1.9%
천 9
 
1.7%
안 9
 
1.7%
군 8
 
1.5%
Other values (126) 367
69.2%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
0 3
27.3%
6 2
18.2%
1 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
h 1
50.0%
Space Separator
ValueCountFrequency (%)
116
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 530
77.9%
Common 148
 
21.8%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 28
 
5.3%
마 26
 
4.9%
을 26
 
4.9%
원 23
 
4.3%
리 13
 
2.5%
산 11
 
2.1%
시 10
 
1.9%
천 9
 
1.7%
안 9
 
1.7%
군 8
 
1.5%
Other values (126) 367
69.2%
Common
ValueCountFrequency (%)
116
78.4%
, 6
 
4.1%
) 6
 
4.1%
( 6
 
4.1%
- 3
 
2.0%
2 3
 
2.0%
0 3
 
2.0%
6 2
 
1.4%
1 1
 
0.7%
5 1
 
0.7%
Latin
ValueCountFrequency (%)
a 1
50.0%
h 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 530
77.9%
ASCII 150
 
22.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
77.3%
, 6
 
4.0%
) 6
 
4.0%
( 6
 
4.0%
- 3
 
2.0%
2 3
 
2.0%
0 3
 
2.0%
6 2
 
1.3%
1 1
 
0.7%
5 1
 
0.7%
Other values (3) 3
 
2.0%
Hangul
ValueCountFrequency (%)
면 28
 
5.3%
마 26
 
4.9%
을 26
 
4.9%
원 23
 
4.3%
리 13
 
2.5%
산 11
 
2.1%
시 10
 
1.9%
천 9
 
1.7%
안 9
 
1.7%
군 8
 
1.5%
Other values (126) 367
69.2%

계(백만원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)61.9%
Missing6
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean31.895238
Minimum10
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-03-14T12:14:34.770203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12.2
Q120
median30.5
Q339.625
95-th percentile53.7
Maximum110
Range100
Interquartile range (IQR)19.625

Descriptive statistics

Standard deviation17.170877
Coefficient of variation (CV)0.53835235
Kurtosis9.5299806
Mean31.895238
Median Absolute Deviation (MAD)9.5
Skewness2.3603324
Sum1339.6
Variance294.839
MonotonicityNot monotonic
2024-03-14T12:14:34.896977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
33.0 4
 
8.3%
40.0 4
 
8.3%
20.0 4
 
8.3%
16.0 3
 
6.2%
18.0 3
 
6.2%
30.0 2
 
4.2%
10.0 2
 
4.2%
25.0 2
 
4.2%
26.0 1
 
2.1%
60.0 1
 
2.1%
Other values (16) 16
33.3%
(Missing) 6
 
12.5%
ValueCountFrequency (%)
10.0 2
4.2%
12.0 1
 
2.1%
16.0 3
6.2%
18.0 3
6.2%
20.0 4
8.3%
22.0 1
 
2.1%
25.0 2
4.2%
26.0 1
 
2.1%
28.0 1
 
2.1%
29.0 1
 
2.1%
ValueCountFrequency (%)
110.0 1
 
2.1%
60.0 1
 
2.1%
54.0 1
 
2.1%
48.0 1
 
2.1%
47.6 1
 
2.1%
45.0 1
 
2.1%
44.0 1
 
2.1%
40.0 4
8.3%
38.5 1
 
2.1%
37.0 1
 
2.1%

국비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)38.1%
Missing6
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean13.659524
Minimum5
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-03-14T12:14:35.030734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6.1
Q110
median14
Q317.75
95-th percentile20
Maximum25
Range20
Interquartile range (IQR)7.75

Descriptive statistics

Standard deviation4.9189063
Coefficient of variation (CV)0.36010818
Kurtosis-0.77757073
Mean13.659524
Median Absolute Deviation (MAD)4
Skewness0.17185257
Sum573.7
Variance24.195639
MonotonicityNot monotonic
2024-03-14T12:14:35.152504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20.0 8
16.7%
10.0 7
14.6%
15.0 5
10.4%
9.0 3
 
6.2%
14.0 3
 
6.2%
8.0 3
 
6.2%
16.0 2
 
4.2%
5.0 2
 
4.2%
12.0 2
 
4.2%
13.0 1
 
2.1%
Other values (6) 6
12.5%
(Missing) 6
12.5%
ValueCountFrequency (%)
5.0 2
 
4.2%
6.0 1
 
2.1%
8.0 3
6.2%
9.0 3
6.2%
10.0 7
14.6%
12.0 2
 
4.2%
12.5 1
 
2.1%
13.0 1
 
2.1%
14.0 3
6.2%
15.0 5
10.4%
ValueCountFrequency (%)
25.0 1
 
2.1%
20.0 8
16.7%
18.2 1
 
2.1%
18.0 1
 
2.1%
17.0 1
 
2.1%
16.0 2
 
4.2%
15.0 5
10.4%
14.0 3
 
6.2%
13.0 1
 
2.1%
12.5 1
 
2.1%

시군비
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)38.1%
Missing6
Missing (%)12.5%
Infinite0
Infinite (%)0.0%
Mean14.564286
Minimum5
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-03-14T12:14:35.272899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5.05
Q110
median14
Q317.9
95-th percentile27.6
Maximum50
Range45
Interquartile range (IQR)7.9

Descriptive statistics

Standard deviation7.9072619
Coefficient of variation (CV)0.54292137
Kurtosis8.9731285
Mean14.564286
Median Absolute Deviation (MAD)4.1
Skewness2.3467585
Sum611.7
Variance62.524791
MonotonicityNot monotonic
2024-03-14T12:14:35.393649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20.0 7
14.6%
10.0 6
12.5%
15.0 5
10.4%
9.0 3
6.2%
14.0 3
6.2%
5.0 3
6.2%
8.0 3
6.2%
16.0 2
 
4.2%
28.0 2
 
4.2%
12.0 2
 
4.2%
Other values (6) 6
12.5%
(Missing) 6
12.5%
ValueCountFrequency (%)
5.0 3
6.2%
6.0 1
 
2.1%
8.0 3
6.2%
9.0 3
6.2%
10.0 6
12.5%
12.0 2
 
4.2%
12.5 1
 
2.1%
13.0 1
 
2.1%
14.0 3
6.2%
15.0 5
10.4%
ValueCountFrequency (%)
50.0 1
 
2.1%
28.0 2
 
4.2%
20.0 7
14.6%
18.2 1
 
2.1%
17.0 1
 
2.1%
16.0 2
 
4.2%
15.0 5
10.4%
14.0 3
6.2%
13.0 1
 
2.1%
12.5 1
 
2.1%

자담
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing11
Missing (%)22.9%
Memory size516.0 B

Interactions

2024-03-14T12:14:32.063104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.166310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.443366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.763573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:32.122449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.227204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.517768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.852950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:32.183555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.287471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.602657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.923406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:32.263869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.367149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.686068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:14:31.998416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T12:14:35.460170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군축제명기간장소계(백만원)국비시군비
구분1.0000.0000.0001.0000.5650.7950.4140.773
시군0.0001.0000.9891.0000.9740.6950.5620.823
축제명0.0000.9891.0001.0000.9910.9440.9020.948
기간1.0001.0001.0001.0001.0001.0001.0001.000
장소0.5650.9740.9911.0001.0000.9240.8480.929
계(백만원)0.7950.6950.9441.0000.9241.0000.8770.991
국비0.4140.5620.9021.0000.8480.8771.0000.937
시군비0.7730.8230.9481.0000.9290.9910.9371.000
2024-03-14T12:14:35.553612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분계(백만원)국비시군비시군
구분1.000-0.770-0.788-0.7320.000
계(백만원)-0.7701.0000.9800.9810.239
국비-0.7880.9801.0000.9810.233
시군비-0.7320.9810.9811.0000.453
시군0.0000.2390.2330.4531.000

Missing values

2024-03-14T12:14:32.365813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:14:32.483590image/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.
2024-03-14T12:14:32.596208image/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

구분시군축제명기간장소계(백만원)국비시군비자담
02018익산용머리 고을 억새 축제(신규)11. 11 (1일간)익산시 용안면 석동리 일원16.08.08.0NaN
12018정읍다 같이 노~올자 동네한바퀴<NA>억새밭 미로 찾기, 마을별 풍물놀이 등<NA><NA><NA>NaN
22018정읍신기 복드림 축제 (신규)6. 23 (1일간)정읍시 입암면 대흥리 일원20.010.010.0NaN
32018남원노봉마을 산행길 축제<NA>6개마을 및 노인당 합창대회 등<NA><NA><NA>NaN
42018완주완주-GUN 포차축제 (신규)10. 01 (1일간)모정음악회, 보물찾기, 자전거타기 등10.05.05.0NaN
52018장수월현마을 정월대보름축제(신규)10. 13 (2일간)남원 사매면 노봉마을(혼불권역)20.010.010.0NaN
62018임실말천방 들노래 한마당 축제<NA>소설 혼불의 신행길 재현 및 주민혼례<NA><NA><NA>NaN
72018임실둔데기 백중절7월중순 (1일간)글로벌푸드 포차, 문화체험행사 등10.05.05.0NaN
82017익산용머리 고을 억새 축제(신규)11. 10 ~ 11. 12(3일간)익산시 용안면 석동리 일원12.06.06.0
92017정읍<NA><NA>-억새밭 미로 찾기, 마을별 풍물놀이 등<NA><NA><NA>NaN
구분시군축제명기간장소계(백만원)국비시군비자담
382011익산송천 블루베리 축제7. 1 ~ 7. 3 (3일간)웅포문화센터44.020.020.04
392011완주소양 꽃 축제10. 29 ~ 10. 30 (2일간)소양초등학교33.015.015.03
402011진안원연장 꽃잔디 축제5. 5 ~ 5. 8 (4일간)원연장마을 및 꽃잔디동산45.020.020.05
412010익산송천 블루베리 축제6. 19 ~ 6. 20 (2일간)웅포문화센터33.015.015.03
422010완주물고기 마을 축제10. 9 ~ 10. 13 (5일간)이서 물고기마을47.618.218.211.2
432010진안금지(배넘실) 마을축제12. 3 ~ 12. 5 (3일간)상전면 금지마을 및 광장40.020.020.0
442009익산송천 블루베리 축제6. 12 ~ 6. 14 (3일간)웅포면 송천마을40.020.020.0
452009진안귀농․귀촌체험축제7. 31 ~ 8. 9 (10일간)진안군내 20개 마을만들기 지구40.020.020.0
462008진안귀농․귀촌체험축제8. 7 ~ 8. 16 (10일간)진안군내 20개 마을만들기 지구40.020.020.0
472008고창청보리밭 축제4. 12 ~ 5. 12 (31일간)공음면 학원농장 청보리밭 일원110.025.050.035