Overview

Dataset statistics

Number of variables15
Number of observations25
Missing cells68
Missing cells (%)18.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory135.3 B

Variable types

Text3
Categorical3
DateTime1
Numeric8

Dataset

Description샘플 데이터
Author한양대
URLhttps://bigdata-region.kr/#/dataset/8ac70a63-287f-4e28-beed-efaf52194290

Alerts

개선도지수수집일자 has constant value ""Constant
최근6개월개선도 is highly overall correlated with 최근12개월개선도 and 3 other fieldsHigh correlation
최근12개월개선도 is highly overall correlated with 최근6개월개선도 and 2 other fieldsHigh correlation
최근개선도지수 is highly overall correlated with 최근6개월개선도 and 1 other fieldsHigh correlation
최근6개월표준점수 is highly overall correlated with 최초12개월개선도High correlation
최근12개월표준점수 is highly overall correlated with 최초12개월개선도High correlation
최초6개월표준점수 is highly overall correlated with 최근6개월개선도 and 1 other fieldsHigh correlation
최초12개월표준점수 is highly overall correlated with 최초12개월개선도High correlation
개선도최근표준점수 is highly overall correlated with 최초6개월개선도 and 1 other fieldsHigh correlation
최초6개월개선도 is highly overall correlated with 최근12개월개선도 and 2 other fieldsHigh correlation
최초12개월개선도 is highly overall correlated with 최근6개월개선도 and 6 other fieldsHigh correlation
개선도지수채널설명 has 6 (24.0%) missing valuesMissing
개선도채널생성일자 has 6 (24.0%) missing valuesMissing
최근6개월개선도 has 17 (68.0%) missing valuesMissing
최근12개월개선도 has 15 (60.0%) missing valuesMissing
최근개선도지수 has 12 (48.0%) missing valuesMissing
최근6개월표준점수 has 8 (32.0%) missing valuesMissing
최근12개월표준점수 has 4 (16.0%) missing valuesMissing
개선도지수채널ID has unique valuesUnique
개선도지수채널명 has unique valuesUnique
최근6개월개선도 has 1 (4.0%) zerosZeros
최근12개월개선도 has 2 (8.0%) zerosZeros
최근개선도지수 has 5 (20.0%) zerosZeros

Reproduction

Analysis started2023-12-10 14:04:54.644768
Analysis finished2023-12-10 14:05:06.340039
Duration11.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개선도지수채널ID
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:05:06.596212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters600
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowUC0hk2D145ogyBYMKjylWkkw
2nd rowUC-gWrEGYpG2jYfl8A_KIGnQ
3rd rowUC0ru5w57PyGpbsEKwN4LuwA
4th rowUC0sfSZeoSUeWxys7OKkTelQ
5th rowUC1dMe0fYTM4r9mNQc9v1ziA
ValueCountFrequency (%)
uc0hk2d145ogybymkjylwkkw 1
 
4.0%
uc4qw1ue9kwui4ccax9hztxw 1
 
4.0%
uc8jolz-ya34ylqtz2tqslgw 1
 
4.0%
uc7zbyqjdslcy4sh7nasfgya 1
 
4.0%
uc85mxewraycnlfmrhbdaalg 1
 
4.0%
uc7qzaxgxsbobtjv4ppgdsxg 1
 
4.0%
uc7bqxkhltafctwwwhuzoouq 1
 
4.0%
uc6dtags0tiobtojlnlwzdqw 1
 
4.0%
uc69dhld0fumlgp9bsxitbdw 1
 
4.0%
uc5oft5dvf43m2cfmhpjlvgq 1
 
4.0%
Other values (15) 15
60.0%
2023-12-10T23:05:07.283269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 33
 
5.5%
C 32
 
5.3%
Q 20
 
3.3%
w 17
 
2.8%
g 16
 
2.7%
A 14
 
2.3%
4 13
 
2.2%
Z 13
 
2.2%
W 12
 
2.0%
o 12
 
2.0%
Other values (54) 418
69.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 269
44.8%
Lowercase Letter 228
38.0%
Decimal Number 91
 
15.2%
Dash Punctuation 7
 
1.2%
Connector Punctuation 5
 
0.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 33
 
12.3%
C 32
 
11.9%
Q 20
 
7.4%
A 14
 
5.2%
Z 13
 
4.8%
W 12
 
4.5%
G 11
 
4.1%
Y 10
 
3.7%
D 10
 
3.7%
L 10
 
3.7%
Other values (16) 104
38.7%
Lowercase Letter
ValueCountFrequency (%)
w 17
 
7.5%
g 16
 
7.0%
o 12
 
5.3%
l 11
 
4.8%
d 11
 
4.8%
s 10
 
4.4%
f 10
 
4.4%
k 9
 
3.9%
e 9
 
3.9%
b 9
 
3.9%
Other values (16) 114
50.0%
Decimal Number
ValueCountFrequency (%)
4 13
14.3%
7 11
12.1%
2 11
12.1%
0 10
11.0%
5 10
11.0%
9 10
11.0%
8 7
7.7%
6 7
7.7%
3 7
7.7%
1 5
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 497
82.8%
Common 103
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 33
 
6.6%
C 32
 
6.4%
Q 20
 
4.0%
w 17
 
3.4%
g 16
 
3.2%
A 14
 
2.8%
Z 13
 
2.6%
W 12
 
2.4%
o 12
 
2.4%
G 11
 
2.2%
Other values (42) 317
63.8%
Common
ValueCountFrequency (%)
4 13
12.6%
7 11
10.7%
2 11
10.7%
0 10
9.7%
5 10
9.7%
9 10
9.7%
- 7
6.8%
8 7
6.8%
6 7
6.8%
3 7
6.8%
Other values (2) 10
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 33
 
5.5%
C 32
 
5.3%
Q 20
 
3.3%
w 17
 
2.8%
g 16
 
2.7%
A 14
 
2.3%
4 13
 
2.2%
Z 13
 
2.2%
W 12
 
2.0%
o 12
 
2.0%
Other values (54) 418
69.7%

개선도지수채널명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-10T23:05:07.704494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length9.88
Min length3

Characters and Unicode

Total characters247
Distinct characters126
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row안녕히_계세요
2nd row[KERI]한국전기연구원
3rd row재민정
4th rowTBS fm 95.1MHz
5th rowSaehyeon세현
ValueCountFrequency (%)
3
 
6.5%
안녕히_계세요 1
 
2.2%
gabiekook 1
 
2.2%
사모장 1
 
2.2%
한국전력 1
 
2.2%
kepco 1
 
2.2%
애주가tv참pd 1
 
2.2%
잡아바 1
 
2.2%
tv 1
 
2.2%
경기도일자리재단 1
 
2.2%
Other values (34) 34
73.9%
2023-12-10T23:05:08.240242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
8.5%
T 8
 
3.2%
e 7
 
2.8%
o 6
 
2.4%
V 6
 
2.4%
S 6
 
2.4%
a 5
 
2.0%
E 5
 
2.0%
D 4
 
1.6%
s 4
 
1.6%
Other values (116) 175
70.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 98
39.7%
Uppercase Letter 64
25.9%
Lowercase Letter 50
20.2%
Space Separator 21
 
8.5%
Open Punctuation 3
 
1.2%
Close Punctuation 3
 
1.2%
Decimal Number 3
 
1.2%
Dash Punctuation 2
 
0.8%
Other Punctuation 2
 
0.8%
Connector Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3
 
3.1%
국 3
 
3.1%
한 3
 
3.1%
자 2
 
2.0%
선 2
 
2.0%
장 2
 
2.0%
애 2
 
2.0%
제 2
 
2.0%
김 2
 
2.0%
소 2
 
2.0%
Other values (67) 75
76.5%
Lowercase Letter
ValueCountFrequency (%)
e 7
14.0%
o 6
12.0%
a 5
10.0%
s 4
 
8.0%
f 4
 
8.0%
c 3
 
6.0%
i 3
 
6.0%
r 3
 
6.0%
y 2
 
4.0%
k 2
 
4.0%
Other values (10) 11
22.0%
Uppercase Letter
ValueCountFrequency (%)
T 8
12.5%
V 6
 
9.4%
S 6
 
9.4%
E 5
 
7.8%
D 4
 
6.2%
C 4
 
6.2%
H 3
 
4.7%
I 3
 
4.7%
P 3
 
4.7%
N 3
 
4.7%
Other values (9) 19
29.7%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
5 1
33.3%
9 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
] 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 114
46.2%
Hangul 98
39.7%
Common 35
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3
 
3.1%
국 3
 
3.1%
한 3
 
3.1%
자 2
 
2.0%
선 2
 
2.0%
장 2
 
2.0%
애 2
 
2.0%
제 2
 
2.0%
김 2
 
2.0%
소 2
 
2.0%
Other values (67) 75
76.5%
Latin
ValueCountFrequency (%)
T 8
 
7.0%
e 7
 
6.1%
o 6
 
5.3%
V 6
 
5.3%
S 6
 
5.3%
a 5
 
4.4%
E 5
 
4.4%
D 4
 
3.5%
s 4
 
3.5%
C 4
 
3.5%
Other values (29) 59
51.8%
Common
ValueCountFrequency (%)
21
60.0%
[ 3
 
8.6%
] 3
 
8.6%
- 2
 
5.7%
1 1
 
2.9%
. 1
 
2.9%
5 1
 
2.9%
9 1
 
2.9%
_ 1
 
2.9%
· 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
59.9%
Hangul 98
39.7%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
 
14.2%
T 8
 
5.4%
e 7
 
4.7%
o 6
 
4.1%
V 6
 
4.1%
S 6
 
4.1%
a 5
 
3.4%
E 5
 
3.4%
D 4
 
2.7%
s 4
 
2.7%
Other values (38) 76
51.4%
Hangul
ValueCountFrequency (%)
주 3
 
3.1%
국 3
 
3.1%
한 3
 
3.1%
자 2
 
2.0%
선 2
 
2.0%
장 2
 
2.0%
애 2
 
2.0%
제 2
 
2.0%
김 2
 
2.0%
소 2
 
2.0%
Other values (67) 75
76.5%
None
ValueCountFrequency (%)
· 1
100.0%

개선도지수수집일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2021-07-31
25 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-07-31
2nd row2021-07-31
3rd row2021-07-31
4th row2021-07-31
5th row2021-07-31

Common Values

ValueCountFrequency (%)
2021-07-31 25
100.0%

Length

2023-12-10T23:05:08.485924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:05:08.626725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-31 25
100.0%

개선도지수채널설명
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing6
Missing (%)24.0%
Memory size332.0 B
2023-12-10T23:05:08.916328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length943
Median length95
Mean length209.26316
Min length1

Characters and Unicode

Total characters3976
Distinct characters414
Distinct categories15 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row.
2nd row전기전문 정부출연연구기관 한국전기연구원의 공식 유튜브 채널입니다. - 전기기술관련 연구성과 영상 - 주요 행사관련 영상 - 과학문화확산을 위한 다채로운 영상 등이 여러분께 제공되고 있습니다. 많은 관심과 참여 부탁드립니다. ============================ -홈 페 이 지 : http:www.keri.re.kr -네이버BLOG: http:blog.naver.comkeri_on -네이버POST: http:post.naver.comkeri_on -네이버 T V : http:tv.naver.comkeri -페 이 스 북 : http:www.facebook.comkeristory -인스타그램 : http:www.instagram.comkokoma_keri
3rd row시민의 눈으로 한걸음 더 시민의 방송 TBS FM입니다. [평일] ▶ 김어준의 뉴스공장 [월~금 07:06 ~ 09:00] ▶ 경제발전소 박연미입니다 [월~금 09:00 ~ 09:57] ▶ 이은미와 함께라면 [월~금 10:06 ~ 12:00] ▶ 배칠수; 박희진의 9595쇼 [매일 12:11 ~ 14:00] ▶ 최일구의 허리케인라디오 [매일 14:06 ~ 16:00] ▶ 함춘호의 포크송 [월~금 16:06 ~ 17:30] ▶ 자동차의 모든 것 으랏차차 김필수입니다 [월~금 17:30 ~ 18:00] ▶ 명랑시사 이승원입니다 [월~금 18:11 ~ 19:30] ▶ 천만의 말씀 황현희입니다 [월~금 19:30 ~ 20:00] ▶ 아닌 밤중에 주진우입니다 [월~금 20:06 ~ 21:00] ▶ 이가희의 러브레터 [월~금 21:00 ~ 21:43] ▶ 달콤한 밤 황진하입니다 [매일 22:06 ~ 24:00] ▶ 라디오를 켜라 정연주입니다 [월~토 05:00 ~ 07:00] [주말] ▶ 뉴스공장 주말특근 [토 07:00 ~ 08:00] ▶ 오늘도 읽음 [토 08:06 ~ 09:00] TBS 아고라 [일 08:06 ~ 09:00] ▶ 기분좋은 토;일요일 조현아입니다 [주말 9:00 ~ 12:00] ▶ 박성호의 4X6=24 [주말16:06 ~ 18:00] ▶ 웅산의 스윗멜로디 [주말 18:11 ~ 20:00] ▶ 주말이 좋다 나선홍입니다 [주말 20:06 ~ 22:00] ▶ 일요클래식 최영옥입니다 [일 05:00 ~ 08:00] ------------------------------------------------------------------------------------------------------------------------------------------------------------------- ▶TBS 홈페이지 http:tbs.seoul.kr
4th row뷰티와 일상을 기록하는 유튜버 세현입니다 비즈니스 문의- saehyeon031105@gmail.com 으로 주시면 감사하겠습니다!
5th row인스타 @jj_d_m_pp 고양이를 좋아하는 사람의 소소한채널; [고양이와 소소한생활] 입니다. 16년 3월 25일; 길냥이였던 쫄냥이를 만났고; 출산이 임박해보이는 커다란 배를 보고 멸치라도 줄까 집에 들인 이후 쭉; 집사의 길을 걸어가고 있습니다. 초보 집사로 좌충우돌 해 가며 현재 반려묘 네마리; 쫄냥까망단추뿌꾸를 키우고 있습니다. 고양이로 인해 많이 웃게되는 나날을 함께하고 싶습니다~^^
ValueCountFrequency (%)
52
 
7.8%
▶ 20
 
3.0%
월~금 9
 
1.4%
공식 6
 
0.9%
you 5
 
0.8%
있습니다 5
 
0.8%
for 5
 
0.8%
매일 4
 
0.6%
채널입니다 4
 
0.6%
주말 4
 
0.6%
Other values (474) 551
82.9%
2023-12-10T23:05:09.482114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
722
 
18.2%
- 181
 
4.6%
o 100
 
2.5%
0 85
 
2.1%
e 83
 
2.1%
: 79
 
2.0%
. 77
 
1.9%
t 72
 
1.8%
a 63
 
1.6%
i 60
 
1.5%
Other values (404) 2454
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1428
35.9%
Lowercase Letter 937
23.6%
Space Separator 722
18.2%
Other Punctuation 220
 
5.5%
Decimal Number 214
 
5.4%
Dash Punctuation 181
 
4.6%
Uppercase Letter 99
 
2.5%
Math Symbol 70
 
1.8%
Close Punctuation 33
 
0.8%
Open Punctuation 33
 
0.8%
Other values (5) 39
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 44
 
3.1%
니 41
 
2.9%
이 37
 
2.6%
요 28
 
2.0%
의 27
 
1.9%
는 24
 
1.7%
입 23
 
1.6%
하 23
 
1.6%
주 21
 
1.5%
리 21
 
1.5%
Other values (321) 1139
79.8%
Uppercase Letter
ValueCountFrequency (%)
T 16
16.2%
D 9
 
9.1%
S 8
 
8.1%
V 6
 
6.1%
O 5
 
5.1%
B 5
 
5.1%
H 4
 
4.0%
L 4
 
4.0%
P 4
 
4.0%
N 4
 
4.0%
Other values (16) 34
34.3%
Lowercase Letter
ValueCountFrequency (%)
o 100
 
10.7%
e 83
 
8.9%
t 72
 
7.7%
a 63
 
6.7%
i 60
 
6.4%
s 56
 
6.0%
h 53
 
5.7%
n 53
 
5.7%
r 46
 
4.9%
w 43
 
4.6%
Other values (15) 308
32.9%
Decimal Number
ValueCountFrequency (%)
0 85
39.7%
1 40
18.7%
2 19
 
8.9%
6 18
 
8.4%
9 12
 
5.6%
8 9
 
4.2%
5 9
 
4.2%
7 8
 
3.7%
4 7
 
3.3%
3 7
 
3.3%
Other Punctuation
ValueCountFrequency (%)
: 79
35.9%
. 77
35.0%
; 22
 
10.0%
! 16
 
7.3%
? 15
 
6.8%
@ 6
 
2.7%
* 3
 
1.4%
' 2
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 40
57.1%
= 30
42.9%
Close Punctuation
ValueCountFrequency (%)
] 25
75.8%
) 8
 
24.2%
Open Punctuation
ValueCountFrequency (%)
[ 25
75.8%
( 8
 
24.2%
Other Symbol
ValueCountFrequency (%)
▶ 21
84.0%
♥ 4
 
16.0%
Space Separator
ValueCountFrequency (%)
722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 181
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1512
38.0%
Hangul 1428
35.9%
Latin 1036
26.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 44
 
3.1%
니 41
 
2.9%
이 37
 
2.6%
요 28
 
2.0%
의 27
 
1.9%
는 24
 
1.7%
입 23
 
1.6%
하 23
 
1.6%
주 21
 
1.5%
리 21
 
1.5%
Other values (321) 1139
79.8%
Latin
ValueCountFrequency (%)
o 100
 
9.7%
e 83
 
8.0%
t 72
 
6.9%
a 63
 
6.1%
i 60
 
5.8%
s 56
 
5.4%
h 53
 
5.1%
n 53
 
5.1%
r 46
 
4.4%
w 43
 
4.2%
Other values (41) 407
39.3%
Common
ValueCountFrequency (%)
722
47.8%
- 181
 
12.0%
0 85
 
5.6%
: 79
 
5.2%
. 77
 
5.1%
~ 40
 
2.6%
1 40
 
2.6%
= 30
 
2.0%
] 25
 
1.7%
[ 25
 
1.7%
Other values (22) 208
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2521
63.4%
Hangul 1428
35.9%
Geometric Shapes 21
 
0.5%
Misc Symbols 4
 
0.1%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
722
28.6%
- 181
 
7.2%
o 100
 
4.0%
0 85
 
3.4%
e 83
 
3.3%
: 79
 
3.1%
. 77
 
3.1%
t 72
 
2.9%
a 63
 
2.5%
i 60
 
2.4%
Other values (69) 999
39.6%
Hangul
ValueCountFrequency (%)
다 44
 
3.1%
니 41
 
2.9%
이 37
 
2.6%
요 28
 
2.0%
의 27
 
1.9%
는 24
 
1.7%
입 23
 
1.6%
하 23
 
1.6%
주 21
 
1.5%
리 21
 
1.5%
Other values (321) 1139
79.8%
Geometric Shapes
ValueCountFrequency (%)
▶ 21
100.0%
Misc Symbols
ValueCountFrequency (%)
♥ 4
100.0%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

개선도채널생성일자
Date

MISSING 

Distinct19
Distinct (%)100.0%
Missing6
Missing (%)24.0%
Memory size332.0 B
Minimum2011-05-18 00:00:00
Maximum2019-03-13 00:00:00
2023-12-10T23:05:09.674493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:09.994981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

최근6개월개선도
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct7
Distinct (%)87.5%
Missing17
Missing (%)68.0%
Infinite0
Infinite (%)0.0%
Mean-13.75
Minimum-149
Maximum60
Zeros1
Zeros (%)4.0%
Negative6
Negative (%)24.0%
Memory size357.0 B
2023-12-10T23:05:10.180002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-149
5-th percentile-99.65
Q1-6.5
median-2.5
Q3-1.5
95-th percentile39
Maximum60
Range209
Interquartile range (IQR)5

Descriptive statistics

Standard deviation59.046592
Coefficient of variation (CV)-4.2942976
Kurtosis5.3750723
Mean-13.75
Median Absolute Deviation (MAD)3
Skewness-1.9108101
Sum-110
Variance3486.5
MonotonicityNot monotonic
2023-12-10T23:05:10.337576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
-2 2
 
8.0%
0 1
 
4.0%
-149 1
 
4.0%
-3 1
 
4.0%
-8 1
 
4.0%
60 1
 
4.0%
-6 1
 
4.0%
(Missing) 17
68.0%
ValueCountFrequency (%)
-149 1
4.0%
-8 1
4.0%
-6 1
4.0%
-3 1
4.0%
-2 2
8.0%
0 1
4.0%
60 1
4.0%
ValueCountFrequency (%)
60 1
4.0%
0 1
4.0%
-2 2
8.0%
-3 1
4.0%
-6 1
4.0%
-8 1
4.0%
-149 1
4.0%

최근12개월개선도
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct8
Distinct (%)80.0%
Missing15
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean-22.8
Minimum-195
Maximum12
Zeros2
Zeros (%)8.0%
Negative7
Negative (%)28.0%
Memory size357.0 B
2023-12-10T23:05:10.494958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-195
5-th percentile-117.15
Q1-11.75
median-1.5
Q3-0.25
95-th percentile6.6
Maximum12
Range207
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation61.175158
Coefficient of variation (CV)-2.683121
Kurtosis9.4059323
Mean-22.8
Median Absolute Deviation (MAD)2.5
Skewness-3.0359041
Sum-228
Variance3742.4
MonotonicityNot monotonic
2023-12-10T23:05:10.667421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 2
 
8.0%
-1 2
 
8.0%
-22 1
 
4.0%
-195 1
 
4.0%
-5 1
 
4.0%
-14 1
 
4.0%
-2 1
 
4.0%
12 1
 
4.0%
(Missing) 15
60.0%
ValueCountFrequency (%)
-195 1
4.0%
-22 1
4.0%
-14 1
4.0%
-5 1
4.0%
-2 1
4.0%
-1 2
8.0%
0 2
8.0%
12 1
4.0%
ValueCountFrequency (%)
12 1
4.0%
0 2
8.0%
-1 2
8.0%
-2 1
4.0%
-5 1
4.0%
-14 1
4.0%
-22 1
4.0%
-195 1
4.0%

최초6개월개선도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
<NA>
17 
0
5 
1
3 

Length

Max length4
Median length4
Mean length3.04
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 17
68.0%
0 5
 
20.0%
1 3
 
12.0%

Length

2023-12-10T23:05:10.918769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:05:11.125106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
68.0%
0 5
 
20.0%
1 3
 
12.0%

최초12개월개선도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
<NA>
17 
0
6 
-1
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.08
Min length1

Unique

Unique2 ?
Unique (%)8.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 17
68.0%
0 6
 
24.0%
-1 1
 
4.0%
1 1
 
4.0%

Length

2023-12-10T23:05:11.387668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:05:11.607920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
68.0%
0 6
 
24.0%
1 2
 
8.0%

최근개선도지수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct9
Distinct (%)69.2%
Missing12
Missing (%)48.0%
Infinite0
Infinite (%)0.0%
Mean18.686154
Minimum0
Maximum52.56
Zeros5
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-10T23:05:11.769171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median14.38
Q333.16
95-th percentile50.538
Maximum52.56
Range52.56
Interquartile range (IQR)33.16

Descriptive statistics

Standard deviation20.104274
Coefficient of variation (CV)1.0758915
Kurtosis-1.2677228
Mean18.686154
Median Absolute Deviation (MAD)14.38
Skewness0.58422647
Sum242.92
Variance404.18184
MonotonicityNot monotonic
2023-12-10T23:05:11.966148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 5
20.0%
18.04 1
 
4.0%
33.16 1
 
4.0%
28.6 1
 
4.0%
41.57 1
 
4.0%
52.56 1
 
4.0%
14.38 1
 
4.0%
5.42 1
 
4.0%
49.19 1
 
4.0%
(Missing) 12
48.0%
ValueCountFrequency (%)
0.0 5
20.0%
5.42 1
 
4.0%
14.38 1
 
4.0%
18.04 1
 
4.0%
28.6 1
 
4.0%
33.16 1
 
4.0%
41.57 1
 
4.0%
49.19 1
 
4.0%
52.56 1
 
4.0%
ValueCountFrequency (%)
52.56 1
 
4.0%
49.19 1
 
4.0%
41.57 1
 
4.0%
33.16 1
 
4.0%
28.6 1
 
4.0%
18.04 1
 
4.0%
14.38 1
 
4.0%
5.42 1
 
4.0%
0.0 5
20.0%

최근6개월표준점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)100.0%
Missing8
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean-4.4970588
Minimum-40.68
Maximum10.57
Zeros0
Zeros (%)0.0%
Negative9
Negative (%)36.0%
Memory size357.0 B
2023-12-10T23:05:12.175679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-40.68
5-th percentile-28.832
Q1-7.2
median-0.32
Q34.08
95-th percentile9.01
Maximum10.57
Range51.25
Interquartile range (IQR)11.28

Descriptive statistics

Standard deviation13.478868
Coefficient of variation (CV)-2.9972629
Kurtosis2.1193601
Mean-4.4970588
Median Absolute Deviation (MAD)6.68
Skewness-1.4738195
Sum-76.45
Variance181.67987
MonotonicityNot monotonic
2023-12-10T23:05:12.357364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
-7.2 1
 
4.0%
-19.16 1
 
4.0%
2.36 1
 
4.0%
4.08 1
 
4.0%
10.57 1
 
4.0%
7.8 1
 
4.0%
4.14 1
 
4.0%
-1.65 1
 
4.0%
-7.0 1
 
4.0%
-3.99 1
 
4.0%
Other values (7) 7
28.0%
(Missing) 8
32.0%
ValueCountFrequency (%)
-40.68 1
4.0%
-25.87 1
4.0%
-19.16 1
4.0%
-12.02 1
4.0%
-7.2 1
4.0%
-7.0 1
4.0%
-3.99 1
4.0%
-1.65 1
4.0%
-0.32 1
4.0%
1.02 1
4.0%
ValueCountFrequency (%)
10.57 1
4.0%
8.62 1
4.0%
7.8 1
4.0%
4.14 1
4.0%
4.08 1
4.0%
2.85 1
4.0%
2.36 1
4.0%
1.02 1
4.0%
-0.32 1
4.0%
-1.65 1
4.0%

최근12개월표준점수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)81.0%
Missing4
Missing (%)16.0%
Infinite0
Infinite (%)0.0%
Mean-16.130476
Minimum-31.39
Maximum67.66
Zeros0
Zeros (%)0.0%
Negative19
Negative (%)76.0%
Memory size357.0 B
2023-12-10T23:05:12.533688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-31.39
5-th percentile-30.95
Q1-29.46
median-28.79
Q3-3.93
95-th percentile4.13
Maximum67.66
Range99.05
Interquartile range (IQR)25.53

Descriptive statistics

Standard deviation23.07171
Coefficient of variation (CV)-1.430318
Kurtosis8.4285268
Mean-16.130476
Median Absolute Deviation (MAD)2.16
Skewness2.6032204
Sum-338.74
Variance532.30381
MonotonicityNot monotonic
2023-12-10T23:05:12.843595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
-29.46 5
20.0%
-0.35 1
 
4.0%
-27.91 1
 
4.0%
-30.46 1
 
4.0%
-12.16 1
 
4.0%
-28.79 1
 
4.0%
-0.37 1
 
4.0%
67.66 1
 
4.0%
-30.95 1
 
4.0%
-1.52 1
 
4.0%
Other values (7) 7
28.0%
(Missing) 4
16.0%
ValueCountFrequency (%)
-31.39 1
 
4.0%
-30.95 1
 
4.0%
-30.46 1
 
4.0%
-30.21 1
 
4.0%
-29.46 5
20.0%
-29.05 1
 
4.0%
-28.79 1
 
4.0%
-27.91 1
 
4.0%
-25.86 1
 
4.0%
-12.16 1
 
4.0%
ValueCountFrequency (%)
67.66 1
4.0%
4.13 1
4.0%
-0.35 1
4.0%
-0.37 1
4.0%
-1.52 1
4.0%
-3.93 1
4.0%
-10.28 1
4.0%
-12.16 1
4.0%
-25.86 1
4.0%
-27.91 1
4.0%

최초6개월표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1436
Minimum-2.62
Maximum2.04
Zeros0
Zeros (%)0.0%
Negative4
Negative (%)16.0%
Memory size357.0 B
2023-12-10T23:05:13.017294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.62
5-th percentile-1.678
Q10.18
median0.18
Q30.21
95-th percentile1.786
Maximum2.04
Range4.66
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.92195842
Coefficient of variation (CV)6.4203233
Kurtosis4.5712269
Mean0.1436
Median Absolute Deviation (MAD)0.01
Skewness-1.0652368
Sum3.59
Variance0.85000733
MonotonicityNot monotonic
2023-12-10T23:05:13.250541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.18 11
44.0%
0.21 2
 
8.0%
0.29 1
 
4.0%
-2.08 1
 
4.0%
-0.03 1
 
4.0%
0.97 1
 
4.0%
1.99 1
 
4.0%
-2.62 1
 
4.0%
0.17 1
 
4.0%
-0.07 1
 
4.0%
Other values (4) 4
 
16.0%
ValueCountFrequency (%)
-2.62 1
 
4.0%
-2.08 1
 
4.0%
-0.07 1
 
4.0%
-0.03 1
 
4.0%
0.12 1
 
4.0%
0.17 1
 
4.0%
0.18 11
44.0%
0.19 1
 
4.0%
0.21 2
 
8.0%
0.22 1
 
4.0%
ValueCountFrequency (%)
2.04 1
 
4.0%
1.99 1
 
4.0%
0.97 1
 
4.0%
0.29 1
 
4.0%
0.22 1
 
4.0%
0.21 2
 
8.0%
0.19 1
 
4.0%
0.18 11
44.0%
0.17 1
 
4.0%
0.12 1
 
4.0%

최초12개월표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2768
Minimum-1.16
Maximum2.23
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)12.0%
Memory size357.0 B
2023-12-10T23:05:13.561257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.16
5-th percentile-0.318
Q10.26
median0.26
Q30.29
95-th percentile0.582
Maximum2.23
Range3.39
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.52607604
Coefficient of variation (CV)1.9005637
Kurtosis9.8821347
Mean0.2768
Median Absolute Deviation (MAD)0.01
Skewness1.3054839
Sum6.92
Variance0.276756
MonotonicityNot monotonic
2023-12-10T23:05:13.893526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.26 9
36.0%
0.27 4
16.0%
0.25 2
 
8.0%
0.31 1
 
4.0%
2.23 1
 
4.0%
-0.15 1
 
4.0%
-1.16 1
 
4.0%
0.29 1
 
4.0%
0.41 1
 
4.0%
0.62 1
 
4.0%
Other values (3) 3
 
12.0%
ValueCountFrequency (%)
-1.16 1
 
4.0%
-0.36 1
 
4.0%
-0.15 1
 
4.0%
0.25 2
 
8.0%
0.26 9
36.0%
0.27 4
16.0%
0.29 1
 
4.0%
0.31 1
 
4.0%
0.38 1
 
4.0%
0.41 1
 
4.0%
ValueCountFrequency (%)
2.23 1
 
4.0%
0.62 1
 
4.0%
0.43 1
 
4.0%
0.41 1
 
4.0%
0.38 1
 
4.0%
0.31 1
 
4.0%
0.29 1
 
4.0%
0.27 4
16.0%
0.26 9
36.0%
0.25 2
 
8.0%

개선도최근표준점수
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.3412
Minimum-148.33
Maximum331.88
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)8.0%
Memory size357.0 B
2023-12-10T23:05:14.145540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-148.33
5-th percentile-1.014
Q117.22
median18.29
Q318.6
95-th percentile21.9
Maximum331.88
Range480.21
Interquartile range (IQR)1.38

Descriptive statistics

Standard deviation72.604831
Coefficient of variation (CV)3.2498179
Kurtosis15.903109
Mean22.3412
Median Absolute Deviation (MAD)1.06
Skewness2.9180397
Sum558.53
Variance5271.4615
MonotonicityNot monotonic
2023-12-10T23:05:14.332076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
18.41 2
 
8.0%
18.39 2
 
8.0%
18.26 1
 
4.0%
-2.57 1
 
4.0%
19.44 1
 
4.0%
18.6 1
 
4.0%
12.96 1
 
4.0%
21.02 1
 
4.0%
17.91 1
 
4.0%
18.42 1
 
4.0%
Other values (13) 13
52.0%
ValueCountFrequency (%)
-148.33 1
4.0%
-2.57 1
4.0%
5.21 1
4.0%
5.76 1
4.0%
12.96 1
4.0%
15.98 1
4.0%
17.22 1
4.0%
17.84 1
4.0%
17.91 1
4.0%
17.93 1
4.0%
ValueCountFrequency (%)
331.88 1
4.0%
22.12 1
4.0%
21.02 1
4.0%
19.44 1
4.0%
19.36 1
4.0%
19.35 1
4.0%
18.6 1
4.0%
18.42 1
4.0%
18.41 2
8.0%
18.39 2
8.0%

Interactions

2023-12-10T23:05:04.167113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:55.803007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.885389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.977112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.179867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.328180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:01.441962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.658024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.278077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:55.929044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.993924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:58.110553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.321054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.456553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:01.582637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.829388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.385561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.049490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.111452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:58.233783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.460445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.588506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:01.727159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.957321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.517526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.172600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.240543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:58.359516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.618991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.720704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:01.888070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:03.486889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.655753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.342977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.399407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:58.514432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.759836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.858634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.051640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:03.627831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.790040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.484064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.539088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:58.633250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.893916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.974783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.232509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:03.810143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.906847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.609506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.702024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:58.781837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.018919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:01.126591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.353234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:03.927199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:05.030919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:56.756092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:57.846609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:04:59.017333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:00.181481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:01.324404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:02.484702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:05:04.051435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:05:14.486924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개선도지수채널ID개선도지수채널명개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
개선도지수채널ID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도지수채널명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도지수채널설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
개선도채널생성일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
최근6개월개선도1.0001.0001.0001.0001.0000.0000.0000.0000.9130.2610.0000.0000.0000.193
최근12개월개선도1.0001.0001.0001.0000.0001.0000.000NaN1.0001.0000.0000.000NaN0.000
최초6개월개선도1.0001.0001.0001.0000.0000.0001.0000.1381.0000.4920.6850.5650.000NaN
최초12개월개선도1.0001.0001.0001.0000.000NaN0.1381.0000.3231.0001.0001.0001.000NaN
최근개선도지수1.0001.0001.0001.0000.9131.0001.0000.3231.0000.0000.0000.4740.0001.000
최근6개월표준점수1.0001.0001.0001.0000.2611.0000.4921.0000.0001.0000.2700.0000.0000.414
최근12개월표준점수1.0001.0001.0001.0000.0000.0000.6851.0000.0000.2701.0000.8160.5370.287
최초6개월표준점수1.0001.0001.0001.0000.0000.0000.5651.0000.4740.0000.8161.0000.9000.000
최초12개월표준점수1.0001.0001.0001.0000.000NaN0.0001.0000.0000.0000.5370.9001.0000.000
개선도최근표준점수1.0001.0001.0001.0000.1930.000NaNNaN1.0000.4140.2870.0000.0001.000
2023-12-10T23:05:14.763809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최초12개월개선도최초6개월개선도
최초12개월개선도1.0000.061
최초6개월개선도0.0611.000
2023-12-10T23:05:15.293209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
최근6개월개선도최근12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수최초6개월개선도최초12개월개선도
최근6개월개선도1.0000.685-0.6750.0860.342-0.8040.221-0.1080.0001.000
최근12개월개선도0.6851.000-0.2560.4910.108-0.1100.468-0.4511.0001.000
최근개선도지수-0.675-0.2561.0000.2940.3860.221-0.170-0.2430.6320.000
최근6개월표준점수0.0860.4910.2941.000-0.132-0.2760.302-0.0960.0000.816
최근12개월표준점수0.3420.1080.386-0.1321.0000.3120.226-0.1710.2740.775
최초6개월표준점수-0.804-0.1100.221-0.2760.3121.000-0.067-0.0240.4350.775
최초12개월표준점수0.2210.468-0.1700.3020.226-0.0671.0000.0600.0000.894
개선도최근표준점수-0.108-0.451-0.243-0.096-0.171-0.0240.0601.0001.0001.000
최초6개월개선도0.0001.0000.6320.0000.2740.4350.0001.0001.0000.061
최초12개월개선도1.0001.0000.0000.8160.7750.7750.8941.0000.0611.000

Missing values

2023-12-10T23:05:05.239883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:05:05.651093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-10T23:05:06.069694image/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

개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
0UC0hk2D145ogyBYMKjylWkkw안녕히_계세요2021-07-31.2013-03-16<NA><NA><NA><NA><NA><NA>-29.460.180.2618.26
1UC-gWrEGYpG2jYfl8A_KIGnQ[KERI]한국전기연구원2021-07-31전기전문 정부출연연구기관 한국전기연구원의 공식 유튜브 채널입니다. - 전기기술관련 연구성과 영상 - 주요 행사관련 영상 - 과학문화확산을 위한 다채로운 영상 등이 여러분께 제공되고 있습니다. 많은 관심과 참여 부탁드립니다. ============================ -홈 페 이 지 : http:www.keri.re.kr -네이버BLOG: http:blog.naver.comkeri_on -네이버POST: http:post.naver.comkeri_on -네이버 T V : http:tv.naver.comkeri -페 이 스 북 : http:www.facebook.comkeristory -인스타그램 : http:www.instagram.comkokoma_keri2012-03-07<NA><NA><NA><NA><NA>-7.0-30.950.180.2717.84
2UC0ru5w57PyGpbsEKwN4LuwA재민정2021-07-31<NA>2013-05-13<NA><NA><NA><NA><NA><NA>-29.460.180.2618.28
3UC0sfSZeoSUeWxys7OKkTelQTBS fm 95.1MHz2021-07-31시민의 눈으로 한걸음 더 시민의 방송 TBS FM입니다. [평일] ▶ 김어준의 뉴스공장 [월~금 07:06 ~ 09:00] ▶ 경제발전소 박연미입니다 [월~금 09:00 ~ 09:57] ▶ 이은미와 함께라면 [월~금 10:06 ~ 12:00] ▶ 배칠수; 박희진의 9595쇼 [매일 12:11 ~ 14:00] ▶ 최일구의 허리케인라디오 [매일 14:06 ~ 16:00] ▶ 함춘호의 포크송 [월~금 16:06 ~ 17:30] ▶ 자동차의 모든 것 으랏차차 김필수입니다 [월~금 17:30 ~ 18:00] ▶ 명랑시사 이승원입니다 [월~금 18:11 ~ 19:30] ▶ 천만의 말씀 황현희입니다 [월~금 19:30 ~ 20:00] ▶ 아닌 밤중에 주진우입니다 [월~금 20:06 ~ 21:00] ▶ 이가희의 러브레터 [월~금 21:00 ~ 21:43] ▶ 달콤한 밤 황진하입니다 [매일 22:06 ~ 24:00] ▶ 라디오를 켜라 정연주입니다 [월~토 05:00 ~ 07:00] [주말] ▶ 뉴스공장 주말특근 [토 07:00 ~ 08:00] ▶ 오늘도 읽음 [토 08:06 ~ 09:00] TBS 아고라 [일 08:06 ~ 09:00] ▶ 기분좋은 토;일요일 조현아입니다 [주말 9:00 ~ 12:00] ▶ 박성호의 4X6=24 [주말16:06 ~ 18:00] ▶ 웅산의 스윗멜로디 [주말 18:11 ~ 20:00] ▶ 주말이 좋다 나선홍입니다 [주말 20:06 ~ 22:00] ▶ 일요클래식 최영옥입니다 [일 05:00 ~ 08:00] ------------------------------------------------------------------------------------------------------------------------------------------------------------------- ▶TBS 홈페이지 http:tbs.seoul.kr2016-09-19-2-22<NA><NA>18.04-7.2-0.350.180.25331.88
4UC1dMe0fYTM4r9mNQc9v1ziASaehyeon세현2021-07-31뷰티와 일상을 기록하는 유튜버 세현입니다 비즈니스 문의- saehyeon031105@gmail.com 으로 주시면 감사하겠습니다!<NA><NA><NA>000.0<NA>-29.460.290.3118.41
5UC28lbdOHnj-leok6tHIx7ew고양이와 소소한생활2021-07-31인스타 @jj_d_m_pp 고양이를 좋아하는 사람의 소소한채널; [고양이와 소소한생활] 입니다. 16년 3월 25일; 길냥이였던 쫄냥이를 만났고; 출산이 임박해보이는 커다란 배를 보고 멸치라도 줄까 집에 들인 이후 쭉; 집사의 길을 걸어가고 있습니다. 초보 집사로 좌충우돌 해 가며 현재 반려묘 네마리; 쫄냥까망단추뿌꾸를 키우고 있습니다. 고양이로 인해 많이 웃게되는 나날을 함께하고 싶습니다~^^2013-09-30<NA><NA><NA><NA><NA><NA>-29.460.180.2618.41
6UC2BoyzFAwgfRFc5aJrYsGZg후투브2021-07-31<NA>2012-09-09<NA><NA><NA><NA><NA><NA>-29.460.180.2618.39
7UC2Zi06YjNBM37g8d0IkHPMATVCHOSUN PLUS - TV조선 플러스2021-07-31TV조선 방송 채널에; 더한 클립과; 더한 영상들을 모아둔 더한 채널 TV조선 플러스2019-01-180<NA>0-10.02.85<NA>-2.082.2319.36
8UC2d79S4T-z8gTY2ceICWhMg김제시·김제지평선TV2021-07-31김제시 공식 유튜브 채널 '김제지평선TV' 입니다. https:www.youtube.comgimjecity2016-03-16<NA><NA><NA><NA><NA>-12.02-27.910.180.2617.93
9UC3WJ-rb5w_ShKQw06rNZfuwDiscovery Music Records2021-07-31<NA>2013-09-14<NA><NA>10<NA>8.62-30.46-0.03-0.1515.98
개선도지수채널ID개선도지수채널명개선도지수수집일자개선도지수채널설명개선도채널생성일자최근6개월개선도최근12개월개선도최초6개월개선도최초12개월개선도최근개선도지수최근6개월표준점수최근12개월표준점수최초6개월표준점수최초12개월표준점수개선도최근표준점수
15UC5UYeBQdzHjOh_vBoDQDkDQ한국전력 KEPCO2021-07-31한국전력공사 공식 유튜브 채널입니다. 안전하고 깨끗한 에너지 세상을 만들기 위한 한국전력의 노력; 한전 직무 소개; 채용 정보; 메세나 활동 등 다양하고 재미있는 콘텐츠를 만나실 수 있습니다.2012-07-05<NA>-2<NA><NA>52.56-3.99<NA>0.210.2917.22
16UC5oft5dVf43M2cFmhpJLVGQ애주가TV참PD2021-07-31세상 모든 안주를 리뷰하는 애주가TV 참PD입니다. 각종문의 이메일주소 : ilovechampd@gmail.com 인스타그램 : ilovechampd2011-05-186012<NA><NA>14.381.02-1.520.180.265.21
17UC69DhLD0FUmLgP9BsxitbDw잡아바 TV [경기도일자리재단]2021-07-31안녕하세요; 경기도일자리재단 공식 유튜브입니다. 자주 방문 및 구독신청하셔서 유용한 정보 얻어가세요! 일자리플랫폼 잡아바(www.jobaba.net) 페이스북(https:www.facebook.comjobabanet) 인스타그램(https:www.instagram.comjobabanet) 네이버포스트(http:post.naver.comgjf_job) 유튜브(https:www.youtube.comchannelUC69DhLD0FUmLgP9BsxitbDw) 잡아바 앱 다운로드 : 구글플레이스토어나 앱스토어 등에서 ‘경기도일자리재단’ 검색 * 안드로이드 : https:goo.glNLD4CX * IOS : https:goo.glJ5Q1ZP2016-10-17<NA>0<NA><NA>0.0-1.65-10.281.990.4119.35
18UC6DTags0tiObToJLnLWZdQwEBS 디딤돌 발달장애2021-07-31<NA><NA><NA><NA><NA><NA><NA><NA>-25.86-2.620.6218.42
19UC7bQXKhLtAfCTWWWHUzOoUQ광주동구2021-07-31<NA>2016-12-09<NA><NA><NA><NA><NA>4.14-31.390.170.2517.91
20UC7qzaxgXSbOBtjv4ppGDsxg화니의 주방2021-07-31오늘은~ 주말에는 뭘 해 먹을까? 짜장면? 짬뽕? 라멘? 베트남 쌀국수? 팟타이? 중화요리; 태국요리; 베트남 요리등등... 아시아 요리를 포함한 이국적인 요리를 여러분께 소개해 드립니다. 요리과정이 복잡하거나 많이 어렵진 않을까요? 걱정마세요~! 난해하고; 보통 사람들이 따라할수 없는 레시피는 No~! 전직 요리사인 화니샘이 기존의 어렵고 두리뭉실했던 요리공식을 풀이해서 여러분께 알려드려요~ 집에서 요리를 자주 하시는 주부님들에게는 보다 풍요로운 식탁을; 독신남녀에게는 음식으로 힐링을~ 요리사 지망생에는 요리의 기초 스킬을! 일반인들은 알지 못하는 요리의 키 포인트까지~! 차근차근 따라하다보면 어느덧 전문가가 되어버린 자신을 발견하실수 있을거에요. 화니샘의 개인 블로그 : http:gorsia.egloos.com 늄냠티비 공식 블로그 : http:www.jhcooking.co.kr What are you going to cook for dinner or weekends? Noodles? rice? ramen? Chinese? Thai? Vietnamese? No worries...as you have just found this channel. Funny; who used to be a professional chef; is here for you. His videos will show you easy-to-follow recipes even for the most challenging dishes with his hard-earned knowledge and his scientific understanding behind cooking. His healing recipes will southe both your soul and stomach.2015-08-08<NA><NA>005.427.8-29.05-0.070.4321.02
21UC85mXeWRaycnlFmrhBdaAlg남자커피 Namja Coffee2021-07-31안녕하세요 커피와 음료를 사랑하는 남자커피 입니다!! 집에서 쉽게 만들수있는 음료 레시피 소개와 재미있는 커피상식들을 알려 드리고 싶어 운영하는 채널입니다. 부족할수있지만 재미있게 봐주세요!! 문의 - bakasa0817@gmail.com2018-08-18-6-11049.1910.574.132.040.3812.96
22UC7zbYQjdsLcy4Sh7NasFgyA중림TV2021-07-31<NA>2019-03-13<NA>-1<NA><NA><NA>4.08<NA>0.120.2718.39
23UC8JOLZ-YA34ylQTz2tqSlGwKAIST2021-07-31한국과학기술원(KAIST)의 공식 유튜브 채널입니다. This is the official YouTube channel of KAIST.2013-07-28<NA><NA><NA><NA><NA>2.36<NA>0.190.2718.6
24UC8Zv-JxGPLW0oZG4ZQaFQlQ또히DDOHEE2021-07-31또히DDOHEE 채널은 재미있는 일상과 다양한 컨텐츠로 함께 즐기고 나눌 수 있는 공간입니다. ♥ 구독과 좋아요 이쁜 댓글 감사합니다♥ - 첫영상 시작 : 2017.11.11 - 업로드 : 자유 업로딩 ♥함께소통해요♥ - 인스타 만남 : https:www.instagram.comddohee_0126?hl=ko - 비지니스 문의 : mariandk@naver.com [ 해당 영상의 저작권은 또히DDOHEE에게 있습니다. 이 영상을 공유하는 것은 가능하나 허가 없이 변경배포 하는 것은 불가합니다. ]<NA><NA><NA>000.0-19.16-30.210.22-0.3619.44