Overview

Dataset statistics

Number of variables17
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)1.0%
Total size in memory13.8 KiB
Average record size in memory141.3 B

Variable types

Categorical4
Text6
DateTime3
Numeric4

Alerts

Dataset has 1 (1.0%) duplicate rowsDuplicates
area_lc is highly overall correlated with ctprvn_cd and 3 other fieldsHigh correlation
ctprvn_nm is highly overall correlated with ctprvn_cd and 3 other fieldsHigh correlation
ctprvn_cd is highly overall correlated with signgu_cd and 3 other fieldsHigh correlation
signgu_cd is highly overall correlated with ctprvn_cd and 3 other fieldsHigh correlation
adstrd_cd is highly overall correlated with ctprvn_cd and 3 other fieldsHigh correlation
btyp_dc is highly overall correlated with genre_clHigh correlation
genre_cl is highly overall correlated with btyp_dcHigh correlation
rcvfver_co has 40 (40.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:01:33.450493
Analysis finished2023-12-10 10:01:41.399091
Duration7.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

btyp_dc
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
신나는예술여행(청년예술형)
16 
(발굴형)문학순회사업
9 
(매칭형)일반시설순회
7 
(소규모)강원권순회사업
6 
(소규모)수도권순회사업
6 
Other values (20)
56 

Length

Max length27
Median length23
Mean length12.11
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row(매칭형)일반시설순회
2nd row국민일반
3rd row(매칭형)장애인시설순회
4th row(매칭형)아동시설순회
5th row(매칭형)노인시설순회

Common Values

ValueCountFrequency (%)
신나는예술여행(청년예술형) 16
16.0%
(발굴형)문학순회사업 9
 
9.0%
(매칭형)일반시설순회 7
 
7.0%
(소규모)강원권순회사업 6
 
6.0%
(소규모)수도권순회사업 6
 
6.0%
(매칭형)노인시설순회 6
 
6.0%
(소규모)충청권순회사업 5
 
5.0%
(매칭형)청소년시설순회 5
 
5.0%
청년형 5
 
5.0%
(매칭형)아동시설순회 4
 
4.0%
Other values (15) 31
31.0%

Length

2023-12-10T19:01:41.938752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신나는예술여행(청년예술형 16
16.0%
발굴형)문학순회사업 9
 
9.0%
매칭형)일반시설순회 7
 
7.0%
소규모)강원권순회사업 6
 
6.0%
소규모)수도권순회사업 6
 
6.0%
매칭형)노인시설순회 6
 
6.0%
소규모)충청권순회사업 5
 
5.0%
매칭형)청소년시설순회 5
 
5.0%
청년형 5
 
5.0%
매칭형)아동시설순회 4
 
4.0%
Other values (15) 31
31.0%

genre_cl
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
예술일반
30 
전통예술
21 
연극
13 
음악
12 
문학
9 
Other values (4)
15 

Length

Max length4
Median length4
Mean length3.28
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음악
2nd row문화일반
3rd row전통예술
4th row예술일반
5th row전통예술

Common Values

ValueCountFrequency (%)
예술일반 30
30.0%
전통예술 21
21.0%
연극 13
13.0%
음악 12
 
12.0%
문학 9
 
9.0%
문화일반 6
 
6.0%
시각예술 4
 
4.0%
다원예술 3
 
3.0%
무용 2
 
2.0%

Length

2023-12-10T19:01:42.262667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:01:42.585257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
예술일반 30
30.0%
전통예술 21
21.0%
연극 13
13.0%
음악 12
 
12.0%
문학 9
 
9.0%
문화일반 6
 
6.0%
시각예술 4
 
4.0%
다원예술 3
 
3.0%
무용 2
 
2.0%

art_grp_nm
Text

Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:43.252685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length6.89
Min length2

Characters and Unicode

Total characters689
Distinct characters239
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)76.0%

Sample

1st row어그레오
2nd row디아트렉쳐
3rd row2nd Edition
4th row씨앤씨미디어콘텐츠
5th row놀이집단 놀새
ValueCountFrequency (%)
청소년문화연대킥킥 4
 
3.1%
사단법인 4
 
3.1%
art 2
 
1.6%
극단 2
 
1.6%
자계예술촌 2
 
1.6%
인연극단 2
 
1.6%
그림책협회 2
 
1.6%
극단나무 2
 
1.6%
킴킴갤러리 2
 
1.6%
percussions 2
 
1.6%
Other values (98) 103
81.1%
2023-12-10T19:01:44.079323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
단 33
 
4.8%
27
 
3.9%
사 12
 
1.7%
극 12
 
1.7%
이 11
 
1.6%
인 11
 
1.6%
( 11
 
1.6%
) 11
 
1.6%
연 10
 
1.5%
예 10
 
1.5%
Other values (229) 541
78.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 559
81.1%
Lowercase Letter 41
 
6.0%
Uppercase Letter 32
 
4.6%
Space Separator 27
 
3.9%
Open Punctuation 11
 
1.6%
Close Punctuation 11
 
1.6%
Decimal Number 4
 
0.6%
Other Punctuation 3
 
0.4%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 33
 
5.9%
사 12
 
2.1%
극 12
 
2.1%
이 11
 
2.0%
인 11
 
2.0%
연 10
 
1.8%
예 10
 
1.8%
술 10
 
1.8%
소 10
 
1.8%
악 10
 
1.8%
Other values (190) 430
76.9%
Uppercase Letter
ValueCountFrequency (%)
A 7
21.9%
P 3
9.4%
L 2
 
6.2%
G 2
 
6.2%
N 2
 
6.2%
F 2
 
6.2%
I 2
 
6.2%
E 2
 
6.2%
T 2
 
6.2%
Z 2
 
6.2%
Other values (5) 6
18.8%
Lowercase Letter
ValueCountFrequency (%)
s 6
14.6%
n 5
12.2%
i 5
12.2%
r 4
9.8%
o 4
9.8%
t 3
7.3%
e 2
 
4.9%
c 2
 
4.9%
u 2
 
4.9%
d 2
 
4.9%
Other values (4) 6
14.6%
Decimal Number
ValueCountFrequency (%)
1 1
25.0%
0 1
25.0%
3 1
25.0%
2 1
25.0%
Other Punctuation
ValueCountFrequency (%)
' 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 560
81.3%
Latin 73
 
10.6%
Common 56
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 33
 
5.9%
사 12
 
2.1%
극 12
 
2.1%
이 11
 
2.0%
인 11
 
2.0%
연 10
 
1.8%
예 10
 
1.8%
술 10
 
1.8%
소 10
 
1.8%
악 10
 
1.8%
Other values (191) 431
77.0%
Latin
ValueCountFrequency (%)
A 7
 
9.6%
s 6
 
8.2%
n 5
 
6.8%
i 5
 
6.8%
r 4
 
5.5%
o 4
 
5.5%
P 3
 
4.1%
t 3
 
4.1%
L 2
 
2.7%
G 2
 
2.7%
Other values (19) 32
43.8%
Common
ValueCountFrequency (%)
27
48.2%
( 11
19.6%
) 11
19.6%
' 2
 
3.6%
. 1
 
1.8%
1 1
 
1.8%
0 1
 
1.8%
3 1
 
1.8%
2 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 559
81.1%
ASCII 129
 
18.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
단 33
 
5.9%
사 12
 
2.1%
극 12
 
2.1%
이 11
 
2.0%
인 11
 
2.0%
연 10
 
1.8%
예 10
 
1.8%
술 10
 
1.8%
소 10
 
1.8%
악 10
 
1.8%
Other values (190) 430
76.9%
ASCII
ValueCountFrequency (%)
27
20.9%
( 11
 
8.5%
) 11
 
8.5%
A 7
 
5.4%
s 6
 
4.7%
n 5
 
3.9%
i 5
 
3.9%
r 4
 
3.1%
o 4
 
3.1%
P 3
 
2.3%
Other values (28) 46
35.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

progrm_nm
Text

Distinct90
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:44.866044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length11.26
Min length3

Characters and Unicode

Total characters1126
Distinct characters328
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

Unique81 ?
Unique (%)81.0%

Sample

1st row매혹의탱고위드더모스트
2nd row모두의 밥상 展
3rd row생의 한 가운데
4th row찾아가는 가족뮤지컬 다노다노
5th row놀자! 새로운 세상에서
ValueCountFrequency (%)
콘서트 7
 
3.0%
찾아가는 7
 
3.0%
놀자 4
 
1.7%
문학 3
 
1.3%
성큼성큼 3
 
1.3%
작가와의만남 2
 
0.9%
연극 2
 
0.9%
展 2
 
0.9%
우리 2
 
0.9%
프로그램 2
 
0.9%
Other values (182) 199
85.4%
2023-12-10T19:01:45.846484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
11.8%
트 21
 
1.9%
가 21
 
1.9%
서 17
 
1.5%
" 16
 
1.4%
기 16
 
1.4%
리 16
 
1.4%
아 16
 
1.4%
악 16
 
1.4%
는 16
 
1.4%
Other values (318) 838
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 825
73.3%
Space Separator 133
 
11.8%
Other Punctuation 40
 
3.6%
Lowercase Letter 35
 
3.1%
Uppercase Letter 34
 
3.0%
Math Symbol 17
 
1.5%
Decimal Number 17
 
1.5%
Open Punctuation 9
 
0.8%
Close Punctuation 9
 
0.8%
Connector Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 21
 
2.5%
가 21
 
2.5%
서 17
 
2.1%
기 16
 
1.9%
리 16
 
1.9%
아 16
 
1.9%
악 16
 
1.9%
는 16
 
1.9%
의 15
 
1.8%
콘 15
 
1.8%
Other values (262) 656
79.5%
Lowercase Letter
ValueCountFrequency (%)
t 7
20.0%
i 3
8.6%
o 3
8.6%
s 3
8.6%
r 2
 
5.7%
e 2
 
5.7%
l 2
 
5.7%
w 2
 
5.7%
p 2
 
5.7%
a 2
 
5.7%
Other values (6) 7
20.0%
Uppercase Letter
ValueCountFrequency (%)
O 7
20.6%
A 5
14.7%
T 4
11.8%
N 3
8.8%
B 2
 
5.9%
S 2
 
5.9%
C 2
 
5.9%
H 2
 
5.9%
E 2
 
5.9%
J 2
 
5.9%
Other values (3) 3
8.8%
Other Punctuation
ValueCountFrequency (%)
" 16
40.0%
! 6
 
15.0%
' 6
 
15.0%
, 4
 
10.0%
. 3
 
7.5%
/ 2
 
5.0%
? 1
 
2.5%
& 1
 
2.5%
: 1
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 7
41.2%
0 3
17.6%
9 2
 
11.8%
6 1
 
5.9%
7 1
 
5.9%
4 1
 
5.9%
2 1
 
5.9%
5 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
< 8
47.1%
> 8
47.1%
+ 1
 
5.9%
Open Punctuation
ValueCountFrequency (%)
( 8
88.9%
[ 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 8
88.9%
] 1
 
11.1%
Space Separator
ValueCountFrequency (%)
133
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 818
72.6%
Common 232
 
20.6%
Latin 69
 
6.1%
Han 7
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 21
 
2.6%
가 21
 
2.6%
서 17
 
2.1%
기 16
 
2.0%
리 16
 
2.0%
아 16
 
2.0%
악 16
 
2.0%
는 16
 
2.0%
의 15
 
1.8%
콘 15
 
1.8%
Other values (257) 649
79.3%
Latin
ValueCountFrequency (%)
t 7
 
10.1%
O 7
 
10.1%
A 5
 
7.2%
T 4
 
5.8%
i 3
 
4.3%
N 3
 
4.3%
o 3
 
4.3%
s 3
 
4.3%
r 2
 
2.9%
e 2
 
2.9%
Other values (19) 30
43.5%
Common
ValueCountFrequency (%)
133
57.3%
" 16
 
6.9%
( 8
 
3.4%
) 8
 
3.4%
< 8
 
3.4%
> 8
 
3.4%
1 7
 
3.0%
! 6
 
2.6%
' 6
 
2.6%
_ 6
 
2.6%
Other values (17) 26
 
11.2%
Han
ValueCountFrequency (%)
詩 2
28.6%
展 2
28.6%
汽 1
14.3%
水 1
14.3%
笑 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 818
72.6%
ASCII 300
 
26.6%
CJK 7
 
0.6%
Punctuation 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
44.3%
" 16
 
5.3%
( 8
 
2.7%
) 8
 
2.7%
< 8
 
2.7%
> 8
 
2.7%
t 7
 
2.3%
O 7
 
2.3%
1 7
 
2.3%
! 6
 
2.0%
Other values (45) 92
30.7%
Hangul
ValueCountFrequency (%)
트 21
 
2.6%
가 21
 
2.6%
서 17
 
2.1%
기 16
 
2.0%
리 16
 
2.0%
아 16
 
2.0%
악 16
 
2.0%
는 16
 
2.0%
의 15
 
1.8%
콘 15
 
1.8%
Other values (257) 649
79.3%
CJK
ValueCountFrequency (%)
詩 2
28.6%
展 2
28.6%
汽 1
14.3%
水 1
14.3%
笑 1
14.3%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

rnd_trget_nm
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:46.345825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length13
Mean length6.92
Min length3

Characters and Unicode

Total characters692
Distinct characters210
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row양서농협
2nd row태백철암1
3rd row평창군지역사회보장협의체
4th row안양호암초등학교
5th row정읍사회복지관
ValueCountFrequency (%)
주택관리공단 3
 
2.4%
파르베 2
 
1.6%
집 2
 
1.6%
꿈이있는집 1
 
0.8%
예향원 1
 
0.8%
서부장애인종합복지관 1
 
0.8%
평창역 1
 
0.8%
서창도서관 1
 
0.8%
낭성초등학교 1
 
0.8%
전의중학교 1
 
0.8%
Other values (113) 113
89.0%
2023-12-10T19:01:47.203018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 28
 
4.0%
27
 
3.9%
교 27
 
3.9%
지 20
 
2.9%
관 16
 
2.3%
원 14
 
2.0%
초 13
 
1.9%
등 13
 
1.9%
대 12
 
1.7%
중 12
 
1.7%
Other values (200) 510
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 638
92.2%
Space Separator 27
 
3.9%
Decimal Number 21
 
3.0%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 28
 
4.4%
교 27
 
4.2%
지 20
 
3.1%
관 16
 
2.5%
원 14
 
2.2%
초 13
 
2.0%
등 13
 
2.0%
대 12
 
1.9%
중 12
 
1.9%
양 12
 
1.9%
Other values (187) 471
73.8%
Decimal Number
ValueCountFrequency (%)
5 4
19.0%
9 4
19.0%
1 3
14.3%
2 3
14.3%
6 3
14.3%
3 2
9.5%
0 1
 
4.8%
7 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
H 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 638
92.2%
Common 52
 
7.5%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 28
 
4.4%
교 27
 
4.2%
지 20
 
3.1%
관 16
 
2.5%
원 14
 
2.2%
초 13
 
2.0%
등 13
 
2.0%
대 12
 
1.9%
중 12
 
1.9%
양 12
 
1.9%
Other values (187) 471
73.8%
Common
ValueCountFrequency (%)
27
51.9%
5 4
 
7.7%
9 4
 
7.7%
1 3
 
5.8%
2 3
 
5.8%
6 3
 
5.8%
( 2
 
3.8%
) 2
 
3.8%
3 2
 
3.8%
0 1
 
1.9%
Latin
ValueCountFrequency (%)
H 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 638
92.2%
ASCII 54
 
7.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 28
 
4.4%
교 27
 
4.2%
지 20
 
3.1%
관 16
 
2.5%
원 14
 
2.2%
초 13
 
2.0%
등 13
 
2.0%
대 12
 
1.9%
중 12
 
1.9%
양 12
 
1.9%
Other values (187) 471
73.8%
ASCII
ValueCountFrequency (%)
27
50.0%
5 4
 
7.4%
9 4
 
7.4%
1 3
 
5.6%
2 3
 
5.6%
6 3
 
5.6%
( 2
 
3.7%
) 2
 
3.7%
3 2
 
3.7%
0 1
 
1.9%
Other values (3) 3
 
5.6%

pblprfr_begin_de
Date

Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2018-04-24 00:00:00
Maximum2021-08-27 00:00:00
2023-12-10T19:01:47.714040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:47.990180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

pblprfr_end_de
Date

Distinct87
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2018-04-24 00:00:00
Maximum2021-08-27 00:00:00
2023-12-10T19:01:48.385039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:48.782747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

pblprfr_tm
Date

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum2023-12-10 01:00:00
Maximum2023-12-10 20:00:00
2023-12-10T19:01:49.100960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:49.382152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

area_lc
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기
24 
강원
19 
전남
12 
충북
8 
서울
7 
Other values (10)
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row경기
2nd row강원
3rd row강원
4th row경기
5th row전북

Common Values

ValueCountFrequency (%)
경기 24
24.0%
강원 19
19.0%
전남 12
12.0%
충북 8
 
8.0%
서울 7
 
7.0%
충남 5
 
5.0%
광주 5
 
5.0%
전북 4
 
4.0%
경북 4
 
4.0%
부산 3
 
3.0%
Other values (5) 9
 
9.0%

Length

2023-12-10T19:01:49.704322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 24
24.0%
강원 19
19.0%
전남 12
12.0%
충북 8
 
8.0%
서울 7
 
7.0%
충남 5
 
5.0%
광주 5
 
5.0%
전북 4
 
4.0%
경북 4
 
4.0%
부산 3
 
3.0%
Other values (5) 9
 
9.0%

rcvfver_co
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.73
Minimum0
Maximum843
Zeros40
Zeros (%)40.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:49.957674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median24
Q3100
95-th percentile326.15
Maximum843
Range843
Interquartile range (IQR)100

Descriptive statistics

Standard deviation130.07192
Coefficient of variation (CV)1.7405583
Kurtosis14.170553
Mean74.73
Median Absolute Deviation (MAD)24
Skewness3.3387466
Sum7473
Variance16918.704
MonotonicityNot monotonic
2023-12-10T19:01:50.184690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 40
40.0%
100 5
 
5.0%
30 3
 
3.0%
60 2
 
2.0%
45 2
 
2.0%
21 2
 
2.0%
200 2
 
2.0%
72 2
 
2.0%
10 2
 
2.0%
24 2
 
2.0%
Other values (38) 38
38.0%
ValueCountFrequency (%)
0 40
40.0%
8 1
 
1.0%
9 1
 
1.0%
10 2
 
2.0%
12 1
 
1.0%
14 1
 
1.0%
21 2
 
2.0%
23 1
 
1.0%
24 2
 
2.0%
28 1
 
1.0%
ValueCountFrequency (%)
843 1
1.0%
575 1
1.0%
467 1
1.0%
399 1
1.0%
329 1
1.0%
326 1
1.0%
320 1
1.0%
230 1
1.0%
200 2
2.0%
185 1
1.0%

addr
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:50.657467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length19.75
Min length10

Characters and Unicode

Total characters1975
Distinct characters185
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row경기도 양평군 양서면 양수리 559-5 양서농협
2nd row강원 태백시 철암동 467
3rd row강원도 평창군 진부면 진벌1길 144-19
4th row경기도 안양시 만안구 석수동 221-40
5th row전라북도 정읍시 수성동 수성2로 13-18
ValueCountFrequency (%)
경기도 24
 
5.1%
강원도 16
 
3.4%
전라남도 12
 
2.6%
충청북도 7
 
1.5%
충청남도 5
 
1.1%
광주광역시 5
 
1.1%
서울특별시 4
 
0.9%
춘천시 4
 
0.9%
김포시 4
 
0.9%
전라북도 4
 
0.9%
Other values (336) 382
81.8%
2023-12-10T19:01:51.441410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
378
 
19.1%
도 77
 
3.9%
1 77
 
3.9%
시 69
 
3.5%
동 67
 
3.4%
2 43
 
2.2%
- 38
 
1.9%
구 35
 
1.8%
3 34
 
1.7%
4 33
 
1.7%
Other values (175) 1124
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1225
62.0%
Space Separator 379
 
19.2%
Decimal Number 330
 
16.7%
Dash Punctuation 38
 
1.9%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 77
 
6.3%
시 69
 
5.6%
동 67
 
5.5%
구 35
 
2.9%
남 31
 
2.5%
군 31
 
2.5%
경 31
 
2.5%
로 31
 
2.5%
기 30
 
2.4%
양 28
 
2.3%
Other values (159) 795
64.9%
Decimal Number
ValueCountFrequency (%)
1 77
23.3%
2 43
13.0%
3 34
10.3%
4 33
10.0%
5 29
 
8.8%
6 28
 
8.5%
7 27
 
8.2%
0 25
 
7.6%
8 18
 
5.5%
9 16
 
4.8%
Space Separator
ValueCountFrequency (%)
378
99.7%
  1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1225
62.0%
Common 749
37.9%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 77
 
6.3%
시 69
 
5.6%
동 67
 
5.5%
구 35
 
2.9%
남 31
 
2.5%
군 31
 
2.5%
경 31
 
2.5%
로 31
 
2.5%
기 30
 
2.4%
양 28
 
2.3%
Other values (159) 795
64.9%
Common
ValueCountFrequency (%)
378
50.5%
1 77
 
10.3%
2 43
 
5.7%
- 38
 
5.1%
3 34
 
4.5%
4 33
 
4.4%
5 29
 
3.9%
6 28
 
3.7%
7 27
 
3.6%
0 25
 
3.3%
Other values (5) 37
 
4.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1225
62.0%
ASCII 749
37.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
378
50.5%
1 77
 
10.3%
2 43
 
5.7%
- 38
 
5.1%
3 34
 
4.5%
4 33
 
4.4%
5 29
 
3.9%
6 28
 
3.7%
7 27
 
3.6%
0 25
 
3.3%
Other values (5) 37
 
4.9%
Hangul
ValueCountFrequency (%)
도 77
 
6.3%
시 69
 
5.6%
동 67
 
5.5%
구 35
 
2.9%
남 31
 
2.5%
군 31
 
2.5%
경 31
 
2.5%
로 31
 
2.5%
기 30
 
2.4%
양 28
 
2.3%
Other values (159) 795
64.9%
None
ValueCountFrequency (%)
  1
100.0%

ctprvn_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.04
Minimum11
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:51.676568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q131
median32
Q334
95-th percentile36.05
Maximum38
Range27
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.5503797
Coefficient of variation (CV)0.21805525
Kurtosis2.6925766
Mean30.04
Median Absolute Deviation (MAD)1
Skewness-1.7546182
Sum3004
Variance42.907475
MonotonicityNot monotonic
2023-12-10T19:01:51.925041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
31 24
24.0%
32 19
19.0%
36 12
12.0%
33 8
 
8.0%
11 7
 
7.0%
34 5
 
5.0%
24 5
 
5.0%
35 4
 
4.0%
37 4
 
4.0%
21 3
 
3.0%
Other values (5) 9
 
9.0%
ValueCountFrequency (%)
11 7
 
7.0%
21 3
 
3.0%
22 2
 
2.0%
23 1
 
1.0%
24 5
 
5.0%
25 3
 
3.0%
29 2
 
2.0%
31 24
24.0%
32 19
19.0%
33 8
 
8.0%
ValueCountFrequency (%)
38 1
 
1.0%
37 4
 
4.0%
36 12
12.0%
35 4
 
4.0%
34 5
 
5.0%
33 8
 
8.0%
32 19
19.0%
31 24
24.0%
29 2
 
2.0%
25 3
 
3.0%

ctprvn_nm
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
24 
강원도
19 
전라남도
12 
충청북도
8 
서울특별시
7 
Other values (10)
30 

Length

Max length7
Median length5
Mean length3.84
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row경기도
2nd row강원도
3rd row강원도
4th row경기도
5th row전라북도

Common Values

ValueCountFrequency (%)
경기도 24
24.0%
강원도 19
19.0%
전라남도 12
12.0%
충청북도 8
 
8.0%
서울특별시 7
 
7.0%
충청남도 5
 
5.0%
광주광역시 5
 
5.0%
전라북도 4
 
4.0%
경상북도 4
 
4.0%
부산광역시 3
 
3.0%
Other values (5) 9
 
9.0%

Length

2023-12-10T19:01:52.237892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 24
24.0%
강원도 19
19.0%
전라남도 12
12.0%
충청북도 8
 
8.0%
서울특별시 7
 
7.0%
충청남도 5
 
5.0%
광주광역시 5
 
5.0%
전라북도 4
 
4.0%
경상북도 4
 
4.0%
부산광역시 3
 
3.0%
Other values (5) 9
 
9.0%

signgu_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct74
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30206.38
Minimum11030
Maximum38030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:52.512233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11030
5-th percentile11167.5
Q131025.75
median32010
Q334065
95-th percentile36506.55
Maximum38030
Range27000
Interquartile range (IQR)3039.25

Descriptive statistics

Standard deviation6579.3539
Coefficient of variation (CV)0.21781339
Kurtosis2.657009
Mean30206.38
Median Absolute Deviation (MAD)1375
Skewness-1.7503873
Sum3020638
Variance43287898
MonotonicityNot monotonic
2023-12-10T19:01:52.808604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31380 4
 
4.0%
31230 4
 
4.0%
32010 4
 
4.0%
32050 2
 
2.0%
37030 2
 
2.0%
34370 2
 
2.0%
21310 2
 
2.0%
33340 2
 
2.0%
29010 2
 
2.0%
36320 2
 
2.0%
Other values (64) 74
74.0%
ValueCountFrequency (%)
11030 1
1.0%
11080 1
1.0%
11100 1
1.0%
11110 1
1.0%
11120 1
1.0%
11170 2
2.0%
21120 1
1.0%
21310 2
2.0%
22040 1
1.0%
22050 1
1.0%
ValueCountFrequency (%)
38030 1
1.0%
37400 1
1.0%
37030 2
2.0%
37011 1
1.0%
36480 1
1.0%
36400 1
1.0%
36320 2
2.0%
36310 1
1.0%
36060 2
2.0%
36030 2
2.0%

signgu_nm
Text

Distinct72
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:53.373274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.2
Min length2

Characters and Unicode

Total characters320
Distinct characters85
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)51.0%

Sample

1st row양평군
2nd row태백시
3rd row평창군
4th row안양시 만안구
5th row정읍시
ValueCountFrequency (%)
양평군 4
 
3.8%
김포시 4
 
3.8%
춘천시 4
 
3.8%
서구 3
 
2.9%
예산군 2
 
1.9%
남구 2
 
1.9%
수원시 2
 
1.9%
속초시 2
 
1.9%
곡성군 2
 
1.9%
동구 2
 
1.9%
Other values (65) 78
74.3%
2023-12-10T19:01:54.128482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 52
 
16.2%
군 31
 
9.7%
구 27
 
8.4%
양 14
 
4.4%
천 12
 
3.8%
주 12
 
3.8%
평 8
 
2.5%
성 7
 
2.2%
포 7
 
2.2%
동 6
 
1.9%
Other values (75) 144
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 315
98.4%
Space Separator 5
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 52
 
16.5%
군 31
 
9.8%
구 27
 
8.6%
양 14
 
4.4%
천 12
 
3.8%
주 12
 
3.8%
평 8
 
2.5%
성 7
 
2.2%
포 7
 
2.2%
동 6
 
1.9%
Other values (74) 139
44.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 315
98.4%
Common 5
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 52
 
16.5%
군 31
 
9.8%
구 27
 
8.6%
양 14
 
4.4%
천 12
 
3.8%
주 12
 
3.8%
평 8
 
2.5%
성 7
 
2.2%
포 7
 
2.2%
동 6
 
1.9%
Other values (74) 139
44.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 315
98.4%
ASCII 5
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 52
 
16.5%
군 31
 
9.8%
구 27
 
8.6%
양 14
 
4.4%
천 12
 
3.8%
주 12
 
3.8%
평 8
 
2.5%
성 7
 
2.2%
포 7
 
2.2%
동 6
 
1.9%
Other values (74) 139
44.1%
ASCII
ValueCountFrequency (%)
5
100.0%

adstrd_cd
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3020680.5
Minimum1103051
Maximum3803042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:01:54.505532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1103051
5-th percentile1116802.2
Q13102633.5
median3201058.5
Q33406533.2
95-th percentile3650669.3
Maximum3803042
Range2699991
Interquartile range (IQR)303899.75

Descriptive statistics

Standard deviation657928.24
Coefficient of variation (CV)0.21780796
Kurtosis2.6570606
Mean3020680.5
Median Absolute Deviation (MAD)137464.5
Skewness-1.7503972
Sum3.0206805 × 108
Variance4.3286957 × 1011
MonotonicityNot monotonic
2023-12-10T19:01:55.015778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3138011 3
 
3.0%
1117052 2
 
2.0%
2401062 2
 
2.0%
2503059 2
 
2.0%
3138033 1
 
1.0%
3648012 1
 
1.0%
2305072 1
 
1.0%
3304131 1
 
1.0%
2901037 1
 
1.0%
3123053 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
1103051 1
1.0%
1108076 1
1.0%
1110059 1
1.0%
1111065 1
1.0%
1112057 1
1.0%
1117052 2
2.0%
2112059 1
1.0%
2131011 1
1.0%
2131012 1
1.0%
2204056 1
1.0%
ValueCountFrequency (%)
3803042 1
1.0%
3740011 1
1.0%
3703062 1
1.0%
3703058 1
1.0%
3701158 1
1.0%
3648012 1
1.0%
3640035 1
1.0%
3632035 1
1.0%
3632033 1
1.0%
3631040 1
1.0%

adstrd_nm
Text

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:01:55.562629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.18
Min length2

Characters and Unicode

Total characters318
Distinct characters104
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)91.0%

Sample

1st row양서면
2nd row철암동
3rd row진부면
4th row석수1동
5th row수성동
ValueCountFrequency (%)
양평읍 3
 
3.0%
둔산1동 2
 
2.0%
구로1동 2
 
2.0%
지산1동 2
 
2.0%
서화면 1
 
1.0%
금호1동 1
 
1.0%
낭성면 1
 
1.0%
전의면 1
 
1.0%
사우동 1
 
1.0%
상월면 1
 
1.0%
Other values (85) 85
85.0%
2023-12-10T19:01:56.437124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 57
 
17.9%
면 29
 
9.1%
읍 20
 
6.3%
1 16
 
5.0%
산 9
 
2.8%
양 8
 
2.5%
곡 6
 
1.9%
평 6
 
1.9%
구 5
 
1.6%
장 5
 
1.6%
Other values (94) 157
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
94.3%
Decimal Number 18
 
5.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 57
 
19.0%
면 29
 
9.7%
읍 20
 
6.7%
산 9
 
3.0%
양 8
 
2.7%
곡 6
 
2.0%
평 6
 
2.0%
구 5
 
1.7%
장 5
 
1.7%
대 5
 
1.7%
Other values (91) 150
50.0%
Decimal Number
ValueCountFrequency (%)
1 16
88.9%
3 1
 
5.6%
2 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 300
94.3%
Common 18
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 57
 
19.0%
면 29
 
9.7%
읍 20
 
6.7%
산 9
 
3.0%
양 8
 
2.7%
곡 6
 
2.0%
평 6
 
2.0%
구 5
 
1.7%
장 5
 
1.7%
대 5
 
1.7%
Other values (91) 150
50.0%
Common
ValueCountFrequency (%)
1 16
88.9%
3 1
 
5.6%
2 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 300
94.3%
ASCII 18
 
5.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 57
 
19.0%
면 29
 
9.7%
읍 20
 
6.7%
산 9
 
3.0%
양 8
 
2.7%
곡 6
 
2.0%
평 6
 
2.0%
구 5
 
1.7%
장 5
 
1.7%
대 5
 
1.7%
Other values (91) 150
50.0%
ASCII
ValueCountFrequency (%)
1 16
88.9%
3 1
 
5.6%
2 1
 
5.6%

Interactions

2023-12-10T19:01:39.940605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:37.915835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:38.578689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:39.220915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:40.084872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:38.077976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:38.721794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:39.404810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:40.254058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:38.247196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:38.903503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:39.589396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:40.417647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:38.408044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:39.060721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:01:39.765436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:01:56.681780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
btyp_dcgenre_clart_grp_nmprogrm_nmrnd_trget_nmpblprfr_begin_depblprfr_end_depblprfr_tmarea_lcrcvfver_coaddrctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nm
btyp_dc1.0000.8721.0001.0001.0000.8720.8720.7360.6260.5781.0000.6090.6260.6600.7650.6600.986
genre_cl0.8721.0001.0001.0001.0000.8720.8720.4630.0570.1351.0000.2300.0570.2330.7700.2330.806
art_grp_nm1.0001.0001.0001.0001.0000.9750.9750.7550.9880.8551.0000.9820.9880.9800.9860.9800.995
progrm_nm1.0001.0001.0001.0001.0000.9430.9430.0000.9950.7031.0000.9820.9950.9800.9900.9800.996
rnd_trget_nm1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
pblprfr_begin_de0.8720.8720.9750.9431.0001.0001.0000.7880.9440.0001.0000.9270.9440.9230.9530.9230.989
pblprfr_end_de0.8720.8720.9750.9431.0001.0001.0000.7880.9440.0001.0000.9270.9440.9230.9530.9230.989
pblprfr_tm0.7360.4630.7550.0001.0000.7880.7881.0000.0000.5521.0000.6640.0000.6870.6560.6870.959
area_lc0.6260.0570.9880.9951.0000.9440.9440.0001.0000.1351.0001.0001.0001.0000.9941.0001.000
rcvfver_co0.5780.1350.8550.7031.0000.0000.0000.5520.1351.0001.0000.5730.1350.5880.8720.5881.000
addr1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
ctprvn_cd0.6090.2300.9820.9821.0000.9270.9270.6641.0000.5731.0001.0001.0001.0000.9971.0001.000
ctprvn_nm0.6260.0570.9880.9951.0000.9440.9440.0001.0000.1351.0001.0001.0001.0000.9941.0001.000
signgu_cd0.6600.2330.9800.9801.0000.9230.9230.6871.0000.5881.0001.0001.0001.0000.9931.0001.000
signgu_nm0.7650.7700.9860.9901.0000.9530.9530.6560.9940.8721.0000.9970.9940.9931.0000.9931.000
adstrd_cd0.6600.2330.9800.9801.0000.9230.9230.6871.0000.5881.0001.0001.0001.0000.9931.0001.000
adstrd_nm0.9860.8060.9950.9961.0000.9890.9890.9591.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-10T19:01:57.004510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
area_lcgenre_clbtyp_dcctprvn_nm
area_lc1.0000.0000.2171.000
genre_cl0.0001.0000.5210.000
btyp_dc0.2170.5211.0000.217
ctprvn_nm1.0000.0000.2171.000
2023-12-10T19:01:57.197842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
rcvfver_coctprvn_cdsigngu_cdadstrd_cdbtyp_dcgenre_clarea_lcctprvn_nm
rcvfver_co1.0000.0620.0620.0630.2410.0590.0400.040
ctprvn_cd0.0621.0000.9880.9880.2600.1100.9610.961
signgu_cd0.0620.9881.0001.0000.2600.1100.9610.961
adstrd_cd0.0630.9881.0001.0000.2600.1100.9610.961
btyp_dc0.2410.2600.2600.2601.0000.5210.2170.217
genre_cl0.0590.1100.1100.1100.5211.0000.0000.000
area_lc0.0400.9610.9610.9610.2170.0001.0001.000
ctprvn_nm0.0400.9610.9610.9610.2170.0001.0001.000

Missing values

2023-12-10T19:01:40.744946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:01:41.215740image/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

btyp_dcgenre_clart_grp_nmprogrm_nmrnd_trget_nmpblprfr_begin_depblprfr_end_depblprfr_tmarea_lcrcvfver_coaddrctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nm
0(매칭형)일반시설순회음악어그레오매혹의탱고위드더모스트양서농협2019-04-192019-04-1911:00경기181경기도 양평군 양서면 양수리 559-5 양서농협31경기도31380양평군3138033양서면
1국민일반문화일반디아트렉쳐모두의 밥상 展태백철암12021-08-192021-08-191:00강원0강원 태백시 철암동 46732강원도32050태백시3205058철암동
2(매칭형)장애인시설순회전통예술2nd Edition생의 한 가운데평창군지역사회보장협의체2019-05-022019-05-0214:00강원45강원도 평창군 진부면 진벌1길 144-1932강원도32340평창군3234036진부면
3(매칭형)아동시설순회예술일반씨앤씨미디어콘텐츠찾아가는 가족뮤지컬 다노다노안양호암초등학교2019-05-102019-05-1010:40경기90경기도 안양시 만안구 석수동 221-4031경기도31041안양시 만안구3104160석수1동
4(매칭형)노인시설순회전통예술놀이집단 놀새놀자! 새로운 세상에서정읍사회복지관2019-05-102019-05-1016:00전북94전라북도 정읍시 수성동 수성2로 13-1835전라북도35040정읍시3504051수성동
5(소규모)강원권순회사업전통예술단미아라리 아라리요성문노인전문요양원2018-05-022018-05-0215:10강원0강원도 원주시 행구동 12732강원도32020원주시3202066행구동
6(매칭형)장애인시설순회다원예술아이티 (IT) 뮤직카타신기한 과학음악콘서트운보원2019-05-312019-05-3114:00경기78경기도 포천시 내촌면 부마로 282번길 9931경기도31270포천시3127032내촌면
7특수음악킹덤엔터테인먼트푸르미야 놀자무지개 지역아동센터2021-08-192021-08-1916:00충북0충북 증평군 증평읍 교동리 18633충청북도33390증평군3339014증평읍
8(발굴형)지리적문화소외지역순회사업_농산어촌마을순회예술일반살판협동조합1.체험 프로그램덕정장2019-06-122019-06-1210:30경기85경기도 양주시 덕정동 132-331경기도31260양주시3126055회천3동
9(매칭형)특수계층시설순회전통예술국방국악문화진흥회우리는 면회실에서9059부대2019-06-122019-06-1215:00강원200강원도 양구군 동면32강원도32380양구군3238032동면
btyp_dcgenre_clart_grp_nmprogrm_nmrnd_trget_nmpblprfr_begin_depblprfr_end_depblprfr_tmarea_lcrcvfver_coaddrctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nm
90(소규모)수도권순회사업시각예술킴킴갤러리확장대행사양평읍사무소2018-11-102018-11-1011:00경기0경기도 양평군 양평읍 양근리 23431경기도31380양평군3138011양평읍
91(소규모)수도권순회사업시각예술킴킴갤러리확장대행사양평군 실내체육관2018-11-172018-11-1713:00경기0경기도 양평군 양평읍  양근리 51431경기도31380양평군3138011양평읍
92청년형문화일반인연극단강원권_비포장도로하랑중2020-11-112020-11-1113:30강원133강원 동해시 발한동 37732강원도32040동해시3204055동호동
93아동청소년연극극단아리초코렛혜심원2021-06-302021-06-3016:00서울0서울 용산구 후암동 435-211서울특별시11030용산구1103051후암동
94(매칭형)청소년시설순회전통예술천우스쿨 오브 난장 <JATI>새뜸중학교2019-04-082019-04-0811:00세종575세종특별자치시 새롬동 새롬중앙로 62-1229세종특별자치시29010세종특별자치시2901062새롬동
95청년형문화일반파르베수도권_소금꽃,OO에 피다파르베2020-12-152020-12-151:00서울100서울 구로구 구로동 41-811서울특별시11170구로구1117052구로1동
96청년형문화일반파르베수도권_소금꽃,OO에 피다파르베2020-12-152020-12-151:00서울100서울 구로구 구로동 41-811서울특별시11170구로구1117052구로1동
97아동청소년시각예술(주)예술상점온새미로 展부산한솔학교2021-07-152021-07-159:00부산0부산 강서구 명지동 3235-221부산광역시21120강서구2112059명지1동
98청년형문화일반인연극단강원권_비포장도로해랑중학교2020-08-072020-08-079:00강원185강원 속초시 금호동 625-3732강원도32060속초시3206054금호동
99청년형문화일반블루플레임인아트충청권_아파트의 예술가 아파티스트(Apartist)아파트생활예술공간2020-08-072020-08-079:00대전10대전 서구 둔산동 180525대전광역시25030서구2503059둔산1동

Duplicate rows

Most frequently occurring

btyp_dcgenre_clart_grp_nmprogrm_nmrnd_trget_nmpblprfr_begin_depblprfr_end_depblprfr_tmarea_lcrcvfver_coaddrctprvn_cdctprvn_nmsigngu_cdsigngu_nmadstrd_cdadstrd_nm# duplicates
0청년형문화일반파르베수도권_소금꽃,OO에 피다파르베2020-12-152020-12-151:00서울100서울 구로구 구로동 41-811서울특별시11170구로구1117052구로1동2