Overview

Dataset statistics

Number of variables19
Number of observations100
Missing cells42
Missing cells (%)2.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.8 KiB
Average record size in memory161.3 B

Variable types

Numeric5
Categorical12
Text2

Alerts

pblprfr_place_nm is highly overall correlated with seq_no and 14 other fieldsHigh correlation
signgu_nm is highly overall correlated with seq_no and 12 other fieldsHigh correlation
fstvl_nm is highly overall correlated with seq_no and 15 other fieldsHigh correlation
adstrd_nm is highly overall correlated with seq_no and 14 other fieldsHigh correlation
instt_nm is highly overall correlated with seq_no and 14 other fieldsHigh correlation
genre_nm is highly overall correlated with seq_no and 15 other fieldsHigh correlation
base_year is highly overall correlated with base_de and 8 other fieldsHigh correlation
signgu_cd is highly overall correlated with seq_no and 12 other fieldsHigh correlation
bsns_nm is highly overall correlated with seq_no and 15 other fieldsHigh correlation
ctprvn_nm is highly overall correlated with seq_no and 12 other fieldsHigh correlation
ctprvn_cd is highly overall correlated with seq_no and 12 other fieldsHigh correlation
seq_no is highly overall correlated with adstrd_cd and 12 other fieldsHigh correlation
base_de is highly overall correlated with adstrd_cd and 8 other fieldsHigh correlation
adstrd_cd is highly overall correlated with seq_no and 12 other fieldsHigh correlation
fclty_la is highly overall correlated with seq_no and 11 other fieldsHigh correlation
fclty_lo is highly overall correlated with base_year and 11 other fieldsHigh correlation
pblprfr_time_dc is highly overall correlated with seq_no and 6 other fieldsHigh correlation
ctprvn_cd is highly imbalanced (78.9%)Imbalance
ctprvn_nm is highly imbalanced (78.9%)Imbalance
signgu_cd is highly imbalanced (61.8%)Imbalance
signgu_nm is highly imbalanced (61.8%)Imbalance
afltion_group_nm has 42 (42.0%) missing valuesMissing
seq_no has unique valuesUnique

Reproduction

Analysis started2023-12-10 10:16:59.510521
Analysis finished2023-12-10 10:17:05.149400
Duration5.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

seq_no
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1043.05
Minimum1
Maximum33100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:05.251136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.95
Q127.75
median53.5
Q378.25
95-th percentile98.05
Maximum33100
Range33099
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation5665.9298
Coefficient of variation (CV)5.4320788
Kurtosis29.896146
Mean1043.05
Median Absolute Deviation (MAD)25.5
Skewness5.5944284
Sum104305
Variance32102761
MonotonicityNot monotonic
2023-12-10T19:17:05.443602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
9 1
1.0%
10 1
1.0%
11 1
1.0%
12 1
1.0%
ValueCountFrequency (%)
33100 1
1.0%
33099 1
1.0%
33098 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%

base_year
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2017
42 
2018
27 
2019
18 
2020
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2020
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 42
42.0%
2018 27
27.0%
2019 18
18.0%
2020 13
 
13.0%

Length

2023-12-10T19:17:05.664669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:05.803692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 42
42.0%
2018 27
27.0%
2019 18
18.0%
2020 13
 
13.0%

base_de
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20181076
Minimum20170710
Maximum20201128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:05.952878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20170710
5-th percentile20170808
Q120170812
median20181012
Q320190615
95-th percentile20201107
Maximum20201128
Range30418
Interquartile range (IQR)19803

Descriptive statistics

Standard deviation10679.993
Coefficient of variation (CV)0.00052920831
Kurtosis-0.87711337
Mean20181076
Median Absolute Deviation (MAD)10198
Skewness0.62704723
Sum2.0181076 × 109
Variance1.1406225 × 108
MonotonicityNot monotonic
2023-12-10T19:17:06.121867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20181013 13
 
13.0%
20181012 12
 
12.0%
20170810 7
 
7.0%
20170813 6
 
6.0%
20170814 6
 
6.0%
20170812 6
 
6.0%
20170811 5
 
5.0%
20170808 4
 
4.0%
20201128 3
 
3.0%
20170809 3
 
3.0%
Other values (27) 35
35.0%
ValueCountFrequency (%)
20170710 1
 
1.0%
20170711 1
 
1.0%
20170805 1
 
1.0%
20170806 1
 
1.0%
20170807 1
 
1.0%
20170808 4
4.0%
20170809 3
3.0%
20170810 7
7.0%
20170811 5
5.0%
20170812 6
6.0%
ValueCountFrequency (%)
20201128 3
3.0%
20201121 1
 
1.0%
20201114 1
 
1.0%
20201107 1
 
1.0%
20201031 2
2.0%
20201024 1
 
1.0%
20201017 1
 
1.0%
20200923 1
 
1.0%
20200824 1
 
1.0%
20200801 1
 
1.0%

instt_nm
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주국제관악제조직위원회
40 
제주문화예술재단
27 
전통공연예술진흥재단
25 
<NA>
 
3
세종시문화재단
 
3

Length

Max length12
Median length11
Mean length10.01
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row통영연극예술축제위원회
2nd row<NA>
3rd row제주국제관악제조직위원회
4th row제주국제관악제조직위원회
5th row제주국제관악제조직위원회

Common Values

ValueCountFrequency (%)
제주국제관악제조직위원회 40
40.0%
제주문화예술재단 27
27.0%
전통공연예술진흥재단 25
25.0%
<NA> 3
 
3.0%
세종시문화재단 3
 
3.0%
통영연극예술축제위원회 2
 
2.0%

Length

2023-12-10T19:17:06.367042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:06.541913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주국제관악제조직위원회 40
40.0%
제주문화예술재단 27
27.0%
전통공연예술진흥재단 25
25.0%
na 3
 
3.0%
세종시문화재단 3
 
3.0%
통영연극예술축제위원회 2
 
2.0%

bsns_nm
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
<NA>
45 
공연장상주단체육성지원사업
30 
한국민속예술제
25 

Length

Max length13
Median length7
Mean length7.45
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 45
45.0%
공연장상주단체육성지원사업 30
30.0%
한국민속예술제 25
25.0%

Length

2023-12-10T19:17:06.705804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:06.856638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
45.0%
공연장상주단체육성지원사업 30
30.0%
한국민속예술제 25
25.0%

fstvl_nm
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주국제관악제 및 제주국제관악콩쿠르
40 
<NA>
33 
제59회 한국민속예술축제
13 
제25회 전국청소년민속예술제
12 
통영연극예술축제
 
2

Length

Max length19
Median length15
Mean length12.57
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row통영연극예술축제
2nd row<NA>
3rd row제주국제관악제 및 제주국제관악콩쿠르
4th row제주국제관악제 및 제주국제관악콩쿠르
5th row제주국제관악제 및 제주국제관악콩쿠르

Common Values

ValueCountFrequency (%)
제주국제관악제 및 제주국제관악콩쿠르 40
40.0%
<NA> 33
33.0%
제59회 한국민속예술축제 13
 
13.0%
제25회 전국청소년민속예술제 12
 
12.0%
통영연극예술축제 2
 
2.0%

Length

2023-12-10T19:17:07.045748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:07.222020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주국제관악제 40
19.5%
및 40
19.5%
제주국제관악콩쿠르 40
19.5%
na 33
16.1%
제59회 13
 
6.3%
한국민속예술축제 13
 
6.3%
제25회 12
 
5.9%
전국청소년민속예술제 12
 
5.9%
통영연극예술축제 2
 
1.0%

afltion_group_nm
Text

MISSING 

Distinct33
Distinct (%)56.9%
Missing42
Missing (%)42.0%
Memory size932.0 B
2023-12-10T19:17:07.478328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.4655172
Min length4

Characters and Unicode

Total characters491
Distinct characters126
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

Unique28 ?
Unique (%)48.3%

Sample

1st row인연극단
2nd row평양예술단
3rd row오퍼커션앙상블
4th row오퍼커션앙상블
5th row오퍼커션앙상블
ValueCountFrequency (%)
오퍼커션앙상블 11
 
16.9%
제주빌레앙상블 6
 
9.2%
제주체임버오케스트라 5
 
7.7%
사)전통예술공연개발원 5
 
7.7%
퓨전국악그룹 3
 
4.6%
풍류 3
 
4.6%
보성군 1
 
1.5%
진영여자중학교 1
 
1.5%
문경모전들소리보존회 1
 
1.5%
봉평중학교 1
 
1.5%
Other values (28) 28
43.1%
2023-12-10T19:17:07.898297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
오 17
 
3.5%
앙 17
 
3.5%
상 17
 
3.5%
블 17
 
3.5%
주 13
 
2.6%
학 13
 
2.6%
교 12
 
2.4%
퍼 11
 
2.2%
보 11
 
2.2%
제 11
 
2.2%
Other values (116) 352
71.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
95.9%
Space Separator 7
 
1.4%
Close Punctuation 7
 
1.4%
Open Punctuation 6
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
오 17
 
3.6%
앙 17
 
3.6%
상 17
 
3.6%
블 17
 
3.6%
주 13
 
2.8%
학 13
 
2.8%
교 12
 
2.5%
퍼 11
 
2.3%
보 11
 
2.3%
제 11
 
2.3%
Other values (113) 332
70.5%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
95.9%
Common 20
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
오 17
 
3.6%
앙 17
 
3.6%
상 17
 
3.6%
블 17
 
3.6%
주 13
 
2.8%
학 13
 
2.8%
교 12
 
2.5%
퍼 11
 
2.3%
보 11
 
2.3%
제 11
 
2.3%
Other values (113) 332
70.5%
Common
ValueCountFrequency (%)
7
35.0%
) 7
35.0%
( 6
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
95.9%
ASCII 20
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
오 17
 
3.6%
앙 17
 
3.6%
상 17
 
3.6%
블 17
 
3.6%
주 13
 
2.8%
학 13
 
2.8%
교 12
 
2.5%
퍼 11
 
2.3%
보 11
 
2.3%
제 11
 
2.3%
Other values (113) 332
70.5%
ASCII
ValueCountFrequency (%)
7
35.0%
) 7
35.0%
( 6
30.0%

genre_nm
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
음악
63 
전통
25 
전통예술
8 
연극
 
2
문화일반
 
1

Length

Max length4
Median length2
Mean length2.2
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row연극
2nd row문화일반
3rd row음악
4th row음악
5th row음악

Common Values

ValueCountFrequency (%)
음악 63
63.0%
전통 25
 
25.0%
전통예술 8
 
8.0%
연극 2
 
2.0%
문화일반 1
 
1.0%
예술일반 1
 
1.0%

Length

2023-12-10T19:17:08.075402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:08.238041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
음악 63
63.0%
전통 25
 
25.0%
전통예술 8
 
8.0%
연극 2
 
2.0%
문화일반 1
 
1.0%
예술일반 1
 
1.0%

pblprfr_nm
Text

Distinct80
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:17:08.615223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length63
Mean length18.16
Min length2

Characters and Unicode

Total characters1816
Distinct characters304
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)67.0%

Sample

1st row양파
2nd row강원권_비포장도로
3rd rowKMC 빅밴드 / Phoenix Foundation
4th rowThe Northstar-Optimist Alumni Band (Canada) / 해군군악대(의장대)
5th rowYendo Quartet (France) / Qiartet Piri Clarinet Ensemble (Korea)
ValueCountFrequency (%)
26
 
8.0%
토요쿵쿵따 8
 
2.5%
ensemble 7
 
2.2%
spain 5
 
1.5%
아싸 4
 
1.2%
piri 4
 
1.2%
quartet 4
 
1.2%
명곡 4
 
1.2%
인싸 4
 
1.2%
band 4
 
1.2%
Other values (189) 253
78.3%
2023-12-10T19:17:09.208760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
 
12.3%
a 71
 
3.9%
n 57
 
3.1%
e 51
 
2.8%
t 44
 
2.4%
i 39
 
2.1%
r 39
 
2.1%
악 33
 
1.8%
s 32
 
1.8%
o 26
 
1.4%
Other values (294) 1201
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 865
47.6%
Lowercase Letter 500
27.5%
Space Separator 223
 
12.3%
Uppercase Letter 120
 
6.6%
Other Punctuation 45
 
2.5%
Close Punctuation 22
 
1.2%
Open Punctuation 22
 
1.2%
Dash Punctuation 9
 
0.5%
Decimal Number 9
 
0.5%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
악 33
 
3.8%
스 17
 
2.0%
주 17
 
2.0%
이 16
 
1.8%
쿵 16
 
1.8%
트 15
 
1.7%
의 13
 
1.5%
연 12
 
1.4%
경 12
 
1.4%
요 12
 
1.4%
Other values (237) 702
81.2%
Lowercase Letter
ValueCountFrequency (%)
a 71
14.2%
n 57
11.4%
e 51
10.2%
t 44
8.8%
i 39
 
7.8%
r 39
 
7.8%
s 32
 
6.4%
o 26
 
5.2%
l 22
 
4.4%
u 16
 
3.2%
Other values (14) 103
20.6%
Uppercase Letter
ValueCountFrequency (%)
S 22
18.3%
B 15
12.5%
C 10
8.3%
A 9
7.5%
P 9
7.5%
N 9
7.5%
K 8
 
6.7%
E 7
 
5.8%
Q 5
 
4.2%
F 5
 
4.2%
Other values (9) 21
17.5%
Other Punctuation
ValueCountFrequency (%)
/ 25
55.6%
' 12
26.7%
, 5
 
11.1%
: 2
 
4.4%
& 1
 
2.2%
Decimal Number
ValueCountFrequency (%)
5 3
33.3%
1 3
33.3%
2 2
22.2%
7 1
 
11.1%
Space Separator
ValueCountFrequency (%)
223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 863
47.5%
Latin 620
34.1%
Common 331
 
18.2%
Han 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
악 33
 
3.8%
스 17
 
2.0%
주 17
 
2.0%
이 16
 
1.9%
쿵 16
 
1.9%
트 15
 
1.7%
의 13
 
1.5%
연 12
 
1.4%
경 12
 
1.4%
요 12
 
1.4%
Other values (235) 700
81.1%
Latin
ValueCountFrequency (%)
a 71
 
11.5%
n 57
 
9.2%
e 51
 
8.2%
t 44
 
7.1%
i 39
 
6.3%
r 39
 
6.3%
s 32
 
5.2%
o 26
 
4.2%
l 22
 
3.5%
S 22
 
3.5%
Other values (33) 217
35.0%
Common
ValueCountFrequency (%)
223
67.4%
/ 25
 
7.6%
) 22
 
6.6%
( 22
 
6.6%
' 12
 
3.6%
- 9
 
2.7%
, 5
 
1.5%
5 3
 
0.9%
1 3
 
0.9%
: 2
 
0.6%
Other values (4) 5
 
1.5%
Han
ValueCountFrequency (%)
幸 1
50.0%
巡 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 951
52.4%
Hangul 861
47.4%
Jamo 2
 
0.1%
CJK 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
23.4%
a 71
 
7.5%
n 57
 
6.0%
e 51
 
5.4%
t 44
 
4.6%
i 39
 
4.1%
r 39
 
4.1%
s 32
 
3.4%
o 26
 
2.7%
/ 25
 
2.6%
Other values (47) 344
36.2%
Hangul
ValueCountFrequency (%)
악 33
 
3.8%
스 17
 
2.0%
주 17
 
2.0%
이 16
 
1.9%
쿵 16
 
1.9%
트 15
 
1.7%
의 13
 
1.5%
연 12
 
1.4%
경 12
 
1.4%
요 12
 
1.4%
Other values (233) 698
81.1%
Jamo
ValueCountFrequency (%)
ᆞ 1
50.0%
ᄇ 1
50.0%
CJK
ValueCountFrequency (%)
幸 1
50.0%
巡 1
50.0%

pblprfr_time_dc
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20:00
11 
14:00
10 
19:30
9 
17:00
9 
10:00
7 
Other values (38)
54 

Length

Max length12
Median length5
Mean length6.54
Min length2

Unique

Unique30 ?
Unique (%)30.0%

Sample

1st row19:30
2nd row13:30
3rd row20:00
4th row19:30
5th row18:30

Common Values

ValueCountFrequency (%)
20:00 11
 
11.0%
14:00 10
 
10.0%
19:30 9
 
9.0%
17:00 9
 
9.0%
10:00 7
 
7.0%
18:30 5
 
5.0%
19:00 4
 
4.0%
전일 4
 
4.0%
15:00 3
 
3.0%
16:30 2
 
2.0%
Other values (33) 36
36.0%

Length

2023-12-10T19:17:09.407757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:00 11
 
10.9%
14:00 11
 
10.9%
19:30 9
 
8.9%
17:00 9
 
8.9%
10:00 7
 
6.9%
18:30 5
 
5.0%
19:00 4
 
4.0%
전일 4
 
4.0%
15:00 3
 
3.0%
16:00 2
 
2.0%
Other values (33) 36
35.6%

pblprfr_place_nm
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서귀포김정문화회관
28 
제주도 성읍민속마을
25 
제주대학교 아라뮤즈홀, 서귀포 예술의전당(소극장)
11 
천지연폭포야외공연장
6 
서귀포관광극장
5 
Other values (16)
25 

Length

Max length27
Median length14
Mean length11.1
Min length5

Unique

Unique11 ?
Unique (%)11.0%

Sample

1st row벅수골소극장
2nd row대진중학교
3rd row대평리 난드르 해상공연장
4th row자구리문화예술공원
5th row서귀포관광극장

Common Values

ValueCountFrequency (%)
서귀포김정문화회관 28
28.0%
제주도 성읍민속마을 25
25.0%
제주대학교 아라뮤즈홀, 서귀포 예술의전당(소극장) 11
 
11.0%
천지연폭포야외공연장 6
 
6.0%
서귀포관광극장 5
 
5.0%
서귀포시 착한서점 북타임 4
 
4.0%
탐라표류기 4
 
4.0%
제주해비치호텔 2
 
2.0%
벅수골소극장 2
 
2.0%
금능 꿈차롱 도서관 2
 
2.0%
Other values (11) 11
 
11.0%

Length

2023-12-10T19:17:09.872448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서귀포김정문화회관 28
15.7%
성읍민속마을 25
14.0%
제주도 25
14.0%
제주대학교 11
 
6.2%
아라뮤즈홀 11
 
6.2%
서귀포 11
 
6.2%
예술의전당(소극장 11
 
6.2%
천지연폭포야외공연장 6
 
3.4%
서귀포관광극장 5
 
2.8%
서귀포시 4
 
2.2%
Other values (27) 41
23.0%

ctprvn_cd
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
39
95 
32
 
3
38
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38
2nd row32
3rd row39
4th row39
5th row39

Common Values

ValueCountFrequency (%)
39 95
95.0%
32 3
 
3.0%
38 2
 
2.0%

Length

2023-12-10T19:17:10.006552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:10.105452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
39 95
95.0%
32 3
 
3.0%
38 2
 
2.0%

ctprvn_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
제주특별자치도
95 
강원도
 
3
경상남도
 
2

Length

Max length7
Median length7
Mean length6.82
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도
2nd row강원도
3rd row제주특별자치도
4th row제주특별자치도
5th row제주특별자치도

Common Values

ValueCountFrequency (%)
제주특별자치도 95
95.0%
강원도 3
 
3.0%
경상남도 2
 
2.0%

Length

2023-12-10T19:17:10.221931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:10.331133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주특별자치도 95
95.0%
강원도 3
 
3.0%
경상남도 2
 
2.0%

signgu_cd
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
39020
86 
39010
9 
32400
 
3
38050
 
2

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38050
2nd row32400
3rd row39020
4th row39020
5th row39020

Common Values

ValueCountFrequency (%)
39020 86
86.0%
39010 9
 
9.0%
32400 3
 
3.0%
38050 2
 
2.0%

Length

2023-12-10T19:17:10.450916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:10.550772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
39020 86
86.0%
39010 9
 
9.0%
32400 3
 
3.0%
38050 2
 
2.0%

signgu_nm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서귀포시
86 
제주시
9 
고성군
 
3
통영시
 
2

Length

Max length4
Median length4
Mean length3.86
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row통영시
2nd row고성군
3rd row서귀포시
4th row서귀포시
5th row서귀포시

Common Values

ValueCountFrequency (%)
서귀포시 86
86.0%
제주시 9
 
9.0%
고성군 3
 
3.0%
통영시 2
 
2.0%

Length

2023-12-10T19:17:10.654693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:17:10.775203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서귀포시 86
86.0%
제주시 9
 
9.0%
고성군 3
 
3.0%
통영시 2
 
2.0%

adstrd_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3880155.1
Minimum3240031
Maximum3902060
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:10.881431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3240031
5-th percentile3896213.1
Q13902032
median3902052
Q33902060
95-th percentile3902060
Maximum3902060
Range662029
Interquartile range (IQR)28

Descriptive statistics

Standard deviation113959.74
Coefficient of variation (CV)0.029369892
Kurtosis28.964726
Mean3880155.1
Median Absolute Deviation (MAD)8
Skewness-5.4792698
Sum3.8801551 × 108
Variance1.2986822 × 1010
MonotonicityNot monotonic
2023-12-10T19:17:11.003200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
3902060 28
28.0%
3902032 28
28.0%
3902054 21
21.0%
3902052 5
 
5.0%
3901031 5
 
5.0%
3901011 4
 
4.0%
3240031 3
 
3.0%
3805053 2
 
2.0%
3902051 2
 
2.0%
3902031 1
 
1.0%
ValueCountFrequency (%)
3240031 3
 
3.0%
3805053 2
 
2.0%
3901011 4
 
4.0%
3901031 5
 
5.0%
3902013 1
 
1.0%
3902031 1
 
1.0%
3902032 28
28.0%
3902051 2
 
2.0%
3902052 5
 
5.0%
3902054 21
21.0%
ValueCountFrequency (%)
3902060 28
28.0%
3902054 21
21.0%
3902052 5
 
5.0%
3902051 2
 
2.0%
3902032 28
28.0%
3902031 1
 
1.0%
3902013 1
 
1.0%
3901031 5
 
5.0%
3901011 4
 
4.0%
3805053 2
 
2.0%

adstrd_nm
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
대천동
28 
표선면
28 
천지동
21 
정방동
5 
한경면
5 
Other values (6)
13 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row중앙동
2nd row현내면
3rd row안덕면
4th row송산동
5th row정방동

Common Values

ValueCountFrequency (%)
대천동 28
28.0%
표선면 28
28.0%
천지동 21
21.0%
정방동 5
 
5.0%
한경면 5
 
5.0%
한림읍 4
 
4.0%
현내면 3
 
3.0%
중앙동 2
 
2.0%
송산동 2
 
2.0%
안덕면 1
 
1.0%

Length

2023-12-10T19:17:11.125853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대천동 28
28.0%
표선면 28
28.0%
천지동 21
21.0%
정방동 5
 
5.0%
한경면 5
 
5.0%
한림읍 4
 
4.0%
현내면 3
 
3.0%
중앙동 2
 
2.0%
송산동 2
 
2.0%
안덕면 1
 
1.0%

fclty_la
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.485777
Minimum33.236487
Maximum38.514802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:11.282871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.236487
5-th percentile33.24591
Q133.251054
median33.251054
Q333.38655
95-th percentile33.460866
Maximum38.514802
Range5.2783148
Interquartile range (IQR)0.1354954

Descriptive statistics

Standard deviation0.91394471
Coefficient of variation (CV)0.027293519
Kurtosis26.095095
Mean33.485777
Median Absolute Deviation (MAD)0.0051438
Skewness5.1512631
Sum3348.5777
Variance0.83529493
MonotonicityNot monotonic
2023-12-10T19:17:11.428969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
33.2510541 28
28.0%
33.3865495 25
25.0%
33.2463334 11
 
11.0%
33.2484138 6
 
6.0%
33.2459103 5
 
5.0%
33.2534295 4
 
4.0%
33.3414192 4
 
4.0%
34.8451628 2
 
2.0%
33.388008 2
 
2.0%
33.3233654 2
 
2.0%
Other values (11) 11
 
11.0%
ValueCountFrequency (%)
33.236487 1
 
1.0%
33.2432792 1
 
1.0%
33.2459103 5
 
5.0%
33.2463334 11
 
11.0%
33.2484138 6
 
6.0%
33.2510541 28
28.0%
33.2534295 4
 
4.0%
33.2580481 1
 
1.0%
33.3092641 1
 
1.0%
33.3233654 2
 
2.0%
ValueCountFrequency (%)
38.5148018 1
 
1.0%
38.4892848 1
 
1.0%
38.4841014 1
 
1.0%
34.8451628 2
 
2.0%
33.388008 2
 
2.0%
33.3865495 25
25.0%
33.3845315 1
 
1.0%
33.3723798 1
 
1.0%
33.3414192 4
 
4.0%
33.3392001 1
 
1.0%

fclty_lo
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.67849
Minimum126.16543
Maximum128.43299
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:17:11.564329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.16543
5-th percentile126.25737
Q1126.50866
median126.55459
Q3126.79973
95-th percentile126.93241
Maximum128.43299
Range2.2675631
Interquartile range (IQR)0.2910708

Descriptive statistics

Standard deviation0.43574438
Coefficient of variation (CV)0.0034397661
Kurtosis10.89351
Mean126.67849
Median Absolute Deviation (MAD)0.0459276
Skewness3.2073763
Sum12667.849
Variance0.18987317
MonotonicityNot monotonic
2023-12-10T19:17:11.706944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
126.5086609 28
28.0%
126.7997317 25
25.0%
126.5507911 11
 
11.0%
126.5545885 6
 
6.0%
126.5643221 5
 
5.0%
126.5605504 4
 
4.0%
126.2573688 4
 
4.0%
128.4239437 2
 
2.0%
126.2271499 2
 
2.0%
126.8447489 2
 
2.0%
Other values (11) 11
 
11.0%
ValueCountFrequency (%)
126.165428 1
 
1.0%
126.2271499 2
 
2.0%
126.2482377 1
 
1.0%
126.2573688 4
 
4.0%
126.2704791 1
 
1.0%
126.362011 1
 
1.0%
126.5086609 28
28.0%
126.5507911 11
 
11.0%
126.5545885 6
 
6.0%
126.5605504 4
 
4.0%
ValueCountFrequency (%)
128.4329911 1
 
1.0%
128.4300815 1
 
1.0%
128.4239437 2
 
2.0%
128.4174206 1
 
1.0%
126.8542528 1
 
1.0%
126.8447489 2
 
2.0%
126.830525 1
 
1.0%
126.7997317 25
25.0%
126.5681941 1
 
1.0%
126.5643221 5
 
5.0%

Interactions

2023-12-10T19:17:04.078135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:01.764560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.362097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.942057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.543776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:04.194803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:01.898828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.488516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.082782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.671558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:04.335351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.028576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.597375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.222123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.773736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:04.463775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.157275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.708459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.340690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.890943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:04.578889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.267341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:02.819655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.438032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:17:03.986019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:17:11.832950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
seq_nobase_yearbase_deinstt_nmbsns_nmfstvl_nmafltion_group_nmgenre_nmpblprfr_nmpblprfr_time_dcpblprfr_place_nmctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nmfclty_lafclty_lo
seq_no1.0000.1960.192NaNNaNNaN1.0000.9511.0000.7871.0001.0001.0001.0001.000NaN1.0001.0000.628
base_year0.1961.0001.0000.8361.0001.0000.9980.7891.0000.9560.9210.0880.0880.4800.4800.0000.8700.0880.607
base_de0.1921.0001.0000.8361.0001.0000.9980.7861.0000.9580.9210.0000.0000.4590.4590.0000.8700.0000.611
instt_nmNaN0.8360.8361.0001.0001.0001.0000.8951.0000.8140.9801.0001.0000.7450.7451.0000.9861.0000.956
bsns_nmNaN1.0001.0001.0001.000NaN1.0001.0001.0001.0001.000NaNNaNNaNNaNNaN0.985NaN0.985
fstvl_nmNaN1.0001.0001.000NaN1.0001.0001.0000.9880.9650.9601.0001.0000.6930.6931.0000.8721.0000.822
afltion_group_nm1.0000.9980.9981.0001.0001.0001.0001.0000.9990.9970.9881.0001.0001.0001.000NaN0.9991.0000.999
genre_nm0.9510.7890.7860.8951.0001.0001.0001.0001.0000.9150.9850.9940.9940.8700.8701.0000.8710.9940.750
pblprfr_nm1.0001.0001.0001.0001.0000.9880.9991.0001.0000.9970.9941.0001.0000.9980.9981.0000.9921.0000.999
pblprfr_time_dc0.7870.9560.9580.8141.0000.9650.9970.9150.9971.0000.8210.4060.4060.7140.7140.0000.8770.4060.936
pblprfr_place_nm1.0000.9210.9210.9801.0000.9600.9880.9850.9940.8211.0001.0001.0001.0001.0001.0001.0001.0001.000
ctprvn_cd1.0000.0880.0001.000NaN1.0001.0000.9941.0000.4061.0001.0001.0001.0001.0000.9191.0001.0000.707
ctprvn_nm1.0000.0880.0001.000NaN1.0001.0000.9941.0000.4061.0001.0001.0001.0001.0000.9191.0001.0000.707
signgu_cd1.0000.4800.4590.745NaN0.6931.0000.8700.9980.7141.0001.0001.0001.0001.0001.0001.0001.0000.818
signgu_nm1.0000.4800.4590.745NaN0.6931.0000.8700.9980.7141.0001.0001.0001.0001.0001.0001.0001.0000.818
adstrd_cdNaN0.0000.0001.000NaN1.000NaN1.0001.0000.0001.0000.9190.9191.0001.0001.0001.0000.9191.000
adstrd_nm1.0000.8700.8700.9860.9850.8720.9990.8710.9920.8771.0001.0001.0001.0001.0001.0001.0001.0001.000
fclty_la1.0000.0880.0001.000NaN1.0001.0000.9941.0000.4061.0001.0001.0001.0001.0000.9191.0001.0000.707
fclty_lo0.6280.6070.6110.9560.9850.8220.9990.7500.9990.9361.0000.7070.7070.8180.8181.0001.0000.7071.000
2023-12-10T19:17:12.031597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
pblprfr_place_nmsigngu_nmfstvl_nmadstrd_nminstt_nmgenre_nmbase_yearsigngu_cdpblprfr_time_dcbsns_nmctprvn_nmctprvn_cd
pblprfr_place_nm1.0000.9070.6780.9420.8750.8370.7040.9070.2780.9910.9020.902
signgu_nm0.9071.0000.7210.9630.7360.7340.2031.0000.3401.0000.9950.995
fstvl_nm0.6780.7211.0000.7410.9920.9920.9840.7210.5561.0000.9840.984
adstrd_nm0.9420.9630.7411.0000.8100.6700.7150.9630.4140.8910.9580.958
instt_nm0.8750.7360.9920.8101.0000.8900.8040.7360.4170.9910.9840.984
genre_nm0.8370.7340.9920.6700.8901.0000.6280.7340.5330.9910.8920.892
base_year0.7040.2030.9840.7150.8040.6281.0000.2030.6310.9910.0810.081
signgu_cd0.9071.0000.7210.9630.7360.7340.2031.0000.3401.0000.9950.995
pblprfr_time_dc0.2780.3400.5560.4140.4170.5330.6310.3401.0000.6290.1560.156
bsns_nm0.9911.0001.0000.8910.9910.9910.9911.0000.6291.0001.0001.000
ctprvn_nm0.9020.9950.9840.9580.9840.8920.0810.9950.1561.0001.0001.000
ctprvn_cd0.9020.9950.9840.9580.9840.8920.0810.9950.1561.0001.0001.000
2023-12-10T19:17:12.214161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
seq_nobase_deadstrd_cdfclty_lafclty_lobase_yearinstt_nmbsns_nmfstvl_nmgenre_nmpblprfr_time_dcpblprfr_place_nmctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_nm
seq_no1.0000.141-0.5710.9190.3780.1281.0001.0001.0000.7860.5190.8980.9950.9950.9900.9900.953
base_de0.1411.0000.5240.071-0.1061.0000.8040.9910.9840.6280.6310.7040.0810.0810.2030.2030.715
adstrd_cd-0.5710.5241.000-0.649-0.4840.0810.9841.0000.9840.8920.1560.9021.0001.0000.9950.9950.958
fclty_la0.9190.071-0.6491.0000.4530.0810.9841.0000.9840.8920.1560.9021.0001.0000.9950.9950.958
fclty_lo0.378-0.106-0.4840.4531.0000.5320.7020.8910.7830.6200.5850.9120.6850.6850.7800.7800.968
base_year0.1281.0000.0810.0810.5321.0000.8040.9910.9840.6280.6310.7040.0810.0810.2030.2030.715
instt_nm1.0000.8040.9840.9840.7020.8041.0000.9910.9920.8900.4170.8750.9840.9840.7360.7360.810
bsns_nm1.0000.9911.0001.0000.8910.9910.9911.0001.0000.9910.6290.9911.0001.0001.0001.0000.891
fstvl_nm1.0000.9840.9840.9840.7830.9840.9921.0001.0000.9920.5560.6780.9840.9840.7210.7210.741
genre_nm0.7860.6280.8920.8920.6200.6280.8900.9910.9921.0000.5330.8370.8920.8920.7340.7340.670
pblprfr_time_dc0.5190.6310.1560.1560.5850.6310.4170.6290.5560.5331.0000.2780.1560.1560.3400.3400.414
pblprfr_place_nm0.8980.7040.9020.9020.9120.7040.8750.9910.6780.8370.2781.0000.9020.9020.9070.9070.942
ctprvn_cd0.9950.0811.0001.0000.6850.0810.9841.0000.9840.8920.1560.9021.0001.0000.9950.9950.958
ctprvn_nm0.9950.0811.0001.0000.6850.0810.9841.0000.9840.8920.1560.9021.0001.0000.9950.9950.958
signgu_cd0.9900.2030.9950.9950.7800.2030.7361.0000.7210.7340.3400.9070.9950.9951.0001.0000.963
signgu_nm0.9900.2030.9950.9950.7800.2030.7361.0000.7210.7340.3400.9070.9950.9951.0001.0000.963
adstrd_nm0.9530.7150.9580.9580.9680.7150.8100.8910.7410.6700.4140.9420.9580.9580.9630.9631.000

Missing values

2023-12-10T19:17:04.749904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:17:05.016878image/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

seq_nobase_yearbase_deinstt_nmbsns_nmfstvl_nmafltion_group_nmgenre_nmpblprfr_nmpblprfr_time_dcpblprfr_place_nmctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nmfclty_lafclty_lo
01201720170711통영연극예술축제위원회<NA>통영연극예술축제<NA>연극양파19:30벅수골소극장38경상남도38050통영시3805053중앙동34.845163128.423944
133098202020200923<NA><NA><NA>인연극단문화일반강원권_비포장도로13:30대진중학교32강원도32400고성군3240031현내면38.484101128.432991
23201720170813제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악KMC 빅밴드 / Phoenix Foundation20:00대평리 난드르 해상공연장39제주특별자치도39020서귀포시3902031안덕면33.236487126.362011
34201720170813제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악The Northstar-Optimist Alumni Band (Canada) / 해군군악대(의장대)19:30자구리문화예술공원39제주특별자치도39020서귀포시3902051송산동33.243279126.568194
45201720170813제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악Yendo Quartet (France) / Qiartet Piri Clarinet Ensemble (Korea)18:30서귀포관광극장39제주특별자치도39020서귀포시3902052정방동33.24591126.564322
56201720170810제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악칼로스플루트앙상블 / kazakh State wind quintet (Kazakhstan) / 대간중학교 수페르나 오케스트라18:30서귀포관광극장39제주특별자치도39020서귀포시3902052정방동33.24591126.564322
67201720170814제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악SATB Ensemble (Korea)18:30서귀포관광극장39제주특별자치도39020서귀포시3902052정방동33.24591126.564322
733099201820180917<NA><NA><NA>평양예술단예술일반찾아가는 통일음악회11:00초도2리경로당32강원도32400고성군3240031현내면38.489285128.430082
89201720170812제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악핫 사운드 빅 / SoundNNBrass (Austria)18:30서귀포관광극장39제주특별자치도39020서귀포시3902052정방동33.24591126.564322
910201720170811제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악강원명진학교 관악단 / Spain Brass LUUR Metal (Spain)18:30서귀포관광극장39제주특별자치도39020서귀포시3902052정방동33.24591126.564322
seq_nobase_yearbase_deinstt_nmbsns_nmfstvl_nmafltion_group_nmgenre_nmpblprfr_nmpblprfr_time_dcpblprfr_place_nmctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nmfclty_lafclty_lo
9091201820181013전통공연예술진흥재단한국민속예술제제59회 한국민속예술축제보성군 율어면 밤골농악단전통밤골 마당 밟이13:24~13:52제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9192201820181013전통공연예술진흥재단한국민속예술제제59회 한국민속예술축제영천명주농악보존회전통영천명주농악12:56~13:24제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9293201820181013전통공연예술진흥재단한국민속예술제제59회 한국민속예술축제사)굿마당남도문화연구회전통광주산월농악12:28~12:56제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9394201820181012전통공연예술진흥재단한국민속예술제제25회 전국청소년민속예술제봉평중학교전통평창 순행(巡幸) 취타 아라리12:32~12:55제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9495201820181012전통공연예술진흥재단한국민속예술제제25회 전국청소년민속예술제대촌중학교전통광산농악15:30~15:53제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9596201820181012전통공연예술진흥재단한국민속예술제제25회 전국청소년민속예술제진영여자중학교전통창원퇴촌농악15:53~16:16제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9697201820181013전통공연예술진흥재단한국민속예술제제59회 한국민속예술축제최영장군당굿보존회전통최영장군당굿12:00~12:28제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9798201820181012전통공연예술진흥재단한국민속예술제제25회 전국청소년민속예술제충현고등학교(광명문화원)전통철산리 두레농악16:16~16:39제주도 성읍민속마을39제주특별자치도39020서귀포시3902032표선면33.38655126.799732
9899201720170808제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악포톡스 SATB 앙상블19:00금능 꿈차롱 도서관39제주특별자치도39010제주시3901011한림읍33.388008126.22715
99100201720170809제주국제관악제조직위원회<NA>제주국제관악제 및 제주국제관악콩쿠르<NA>음악플루트 조준범19:00금능 꿈차롱 도서관39제주특별자치도39010제주시3901011한림읍33.388008126.22715