gimi9 Pandas Profiling

Dataset statistics

Number of variables	6
Number of observations	56
Missing cells	264
Missing cells (%)	78.6%
Duplicate rows	1
Duplicate rows (%)	1.8%
Total size in memory	2.9 KiB
Average record size in memory	53.4 B

Variable types

Text	3
Unsupported	3

Dataset

Description	샘플 데이터
Author	MBN
URL	https://kdx.kr/data/view/140

Alerts

Dataset has 1 (1.8%) duplicate rows	Duplicates
`RSTRC_VID_ESSN_NO` has 24 (42.9%) missing values	Missing
`VID_SJ_CN` has 36 (64.3%) missing values	Missing
`VID_CN` has 36 (64.3%) missing values	Missing
`REG_DATE` has 56 (100.0%) missing values	Missing
`VOD_CRS_NM` has 56 (100.0%) missing values	Missing
`Unnamed: 5` has 56 (100.0%) missing values	Missing
`REG_DATE` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`VOD_CRS_NM` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Unnamed: 5` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2024-04-19 00:21:38.498557
Analysis finished	2024-04-19 00:21:39.039511
Duration	0.54 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

RSTRC_VID_ESSN_NO
Text

MISSING

Distinct	32
Distinct (%)	100.0%
Missing	24
Missing (%)	42.9%
Memory size	580.0 B

Length

Max length	52
Median length	40
Mean length	24.8125
Min length	7

Characters and Unicode

Total characters	794
Distinct characters	193
Distinct categories	6 ?
Distinct scripts	3 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	32 ?
Unique (%)	100.0%

Sample

1st row	1010571
2nd row	호리호리한 팔다리와는 달라도 너무 다른 그녀의 뱃살.
3rd row	그녀는 허리둘레가 38인치로 심각한 복부비만이라는 진단을 받았는데...
4th row	건강의 적신호를 알려주는 뱃살과 관련된 질병들은 무엇일까?
5th row	1010572

Value	Count	Frequency (%)
하는데	5	2.6%
과연	4	2.1%
수	3	1.6%
파인애플	3	1.6%
이	3	1.6%
식초	3	1.6%
그	2	1.0%
진단을	2	1.0%
뱃살을	2	1.0%
그녀가	2	1.0%
Other values (150)	163	84.9%

Most occurring characters

Value	Count	Frequency (%)
	160	20.2%
는	28	3.5%
0	24	3.0%
1	21	2.6%
다	16	2.0%
을	14	1.8%
.	14	1.8%
이	13	1.6%
그	13	1.6%
만	13	1.6%
Other values (183)	478	60.2%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	522	65.7%
Space Separator	160	20.2%
Decimal Number	75	9.4%
Other Punctuation	32	4.0%
Math Symbol	3	0.4%
Lowercase Letter	2	0.3%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
는	28	5.4%
다	16	3.1%
을	14	2.7%
이	13	2.5%
그	13	2.5%
만	13	2.5%
의	11	2.1%
한	11	2.1%
데	10	1.9%
과	10	1.9%
Other values (165)	383	73.4%

Decimal Number

Value	Count	Frequency (%)
0	24	32.0%
1	21	28.0%
5	7	9.3%
8	6	8.0%
7	4	5.3%
3	4	5.3%
6	4	5.3%
2	3	4.0%
9	2	2.7%

Other Punctuation

Value	Count	Frequency (%)
.	14	43.8%
?	8	25.0%
!	7	21.9%
'	2	6.2%
,	1	3.1%

Lowercase Letter

Value	Count	Frequency (%)
g	1	50.0%
k	1	50.0%

Space Separator

Value	Count	Frequency (%)
	160	100.0%

Math Symbol

Value	Count	Frequency (%)
~	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	522	65.7%
Common	270	34.0%
Latin	2	0.3%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
는	28	5.4%
다	16	3.1%
을	14	2.7%
이	13	2.5%
그	13	2.5%
만	13	2.5%
의	11	2.1%
한	11	2.1%
데	10	1.9%
과	10	1.9%
Other values (165)	383	73.4%

Common

Value	Count	Frequency (%)
	160	59.3%
0	24	8.9%
1	21	7.8%
.	14	5.2%
?	8	3.0%
5	7	2.6%
!	7	2.6%
8	6	2.2%
7	4	1.5%
3	4	1.5%
Other values (6)	15	5.6%

Latin

Value	Count	Frequency (%)
g	1	50.0%
k	1	50.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	522	65.7%
ASCII	272	34.3%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	160	58.8%
0	24	8.8%
1	21	7.7%
.	14	5.1%
?	8	2.9%
5	7	2.6%
!	7	2.6%
8	6	2.2%
7	4	1.5%
3	4	1.5%
Other values (8)	17	6.2%

Hangul

Value	Count	Frequency (%)
는	28	5.4%
다	16	3.1%
을	14	2.7%
이	13	2.5%
그	13	2.5%
만	13	2.5%
의	11	2.1%
한	11	2.1%
데	10	1.9%
과	10	1.9%
Other values (165)	383	73.4%

VID_SJ_CN
Text

MISSING

Distinct	11
Distinct (%)	55.0%
Missing	36
Missing (%)	64.3%
Memory size	580.0 B

Length

Max length	31
Median length	30.5
Mean length	16.65
Min length	8

Characters and Unicode

Total characters	333
Distinct characters	101
Distinct categories	5 ?
Distinct scripts	3 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10 ?
Unique (%)	50.0%

Sample

1st row	만병의 근원! 건강의 적신호인 뱃살을 잡아라!
2nd row	20160106
3rd row	파인애플식초 만드는 법! 개미허리 만드는 비법 '화제'
4th row	20160106
5th row	파인애플 식초의 놀라운 단백질 분해 효과!

Value	Count	Frequency (%)
20160106	10	13.3%
만드는	4	5.3%
비법	3	4.0%
염증	2	2.7%
잡아라	2	2.7%
잡는	2	2.7%
해독차	2	2.7%
돕는	2	2.7%
파인애플	2	2.7%
놀라운	2	2.7%
Other values (44)	44	58.7%

Most occurring characters

Value	Count	Frequency (%)
	55	16.5%
0	32	9.6%
1	22	6.6%
6	21	6.3%
는	12	3.6%
!	11	3.3%
2	10	3.0%
만	7	2.1%
인	5	1.5%
라	5	1.5%
Other values (91)	153	45.9%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	172	51.7%
Decimal Number	86	25.8%
Space Separator	55	16.5%
Other Punctuation	18	5.4%
Lowercase Letter	2	0.6%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
는	12	7.0%
만	7	4.1%
인	5	2.9%
라	5	2.9%
의	5	2.9%
법	5	2.9%
잡	4	2.3%
드	4	2.3%
해	4	2.3%
비	4	2.3%
Other values (78)	117	68.0%

Decimal Number

Value	Count	Frequency (%)
0	32	37.2%
1	22	25.6%
6	21	24.4%
2	10	11.6%
5	1	1.2%

Other Punctuation

Value	Count	Frequency (%)
!	11	61.1%
'	4	22.2%
%	1	5.6%
?	1	5.6%
,	1	5.6%

Lowercase Letter

Value	Count	Frequency (%)
k	1	50.0%
g	1	50.0%

Space Separator

Value	Count	Frequency (%)
	55	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	172	51.7%
Common	159	47.7%
Latin	2	0.6%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
는	12	7.0%
만	7	4.1%
인	5	2.9%
라	5	2.9%
의	5	2.9%
법	5	2.9%
잡	4	2.3%
드	4	2.3%
해	4	2.3%
비	4	2.3%
Other values (78)	117	68.0%

Common

Value	Count	Frequency (%)
	55	34.6%
0	32	20.1%
1	22	13.8%
6	21	13.2%
!	11	6.9%
2	10	6.3%
'	4	2.5%
%	1	0.6%
?	1	0.6%
,	1	0.6%

Latin

Value	Count	Frequency (%)
k	1	50.0%
g	1	50.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	172	51.7%
ASCII	161	48.3%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	55	34.2%
0	32	19.9%
1	22	13.7%
6	21	13.0%
!	11	6.8%
2	10	6.2%
'	4	2.5%
%	1	0.6%
?	1	0.6%
,	1	0.6%
Other values (3)	3	1.9%

Hangul

Value	Count	Frequency (%)
는	12	7.0%
만	7	4.1%
인	5	2.9%
라	5	2.9%
의	5	2.9%
법	5	2.9%
잡	4	2.3%
드	4	2.3%
해	4	2.3%
비	4	2.3%
Other values (78)	117	68.0%

VID_CN
Text

MISSING

Distinct	20
Distinct (%)	100.0%
Missing	36
Missing (%)	64.3%
Memory size	580.0 B

Length

Max length	82
Median length	59
Mean length	54.7
Min length	12

Characters and Unicode

Total characters	1094
Distinct characters	154
Distinct categories	8 ?
Distinct scripts	3 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	20 ?
Unique (%)	100.0%

Sample

1st row	나이가 들면서 무섭게 뱃살이 늘었다는 최은정 씨.
2nd row	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1010571
3rd row	열량이 높은 중국요리를 먹고도 뱃살을 잡을 수 있다는 그녀들!
4th row	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1010572
5th row	파인애플 식초를 먹으면서 놀라운 몸의 변화를 느꼈다는 송영미 씨.

Value	Count	Frequency (%)
씨	3	3.8%
다이어트	2	2.6%
비만을	2	2.6%
염증	2	2.6%
송영미	2	2.6%
해독차	1	1.3%
3일간의	1	1.3%
시작한	1	1.3%
실험자와	1	1.3%
3명의	1	1.3%
Other values (62)	62	79.5%

Most occurring characters

Value	Count	Frequency (%)
t	80	7.3%
n	80	7.3%
	59	5.4%
e	50	4.6%
c	50	4.6%
o	50	4.6%
.	45	4.1%
/	40	3.7%
1	33	3.0%
_	30	2.7%
Other values (144)	577	52.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	562	51.4%
Other Letter	194	17.7%
Other Punctuation	121	11.1%
Decimal Number	98	9.0%
Space Separator	59	5.4%
Connector Punctuation	30	2.7%
Math Symbol	20	1.8%
Uppercase Letter	10	0.9%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
다	10	5.2%
는	9	4.6%
을	6	3.1%
이	6	3.1%
씨	5	2.6%
의	4	2.1%
게	4	2.1%
실	3	1.5%
에	3	1.5%
를	3	1.5%
Other values (104)	141	72.7%

Lowercase Letter

Value	Count	Frequency (%)
t	80	14.2%
n	80	14.2%
e	50	8.9%
c	50	8.9%
o	50	8.9%
m	30	5.3%
w	30	5.3%
i	20	3.6%
s	20	3.6%
l	20	3.6%
Other values (10)	132	23.5%

Decimal Number

Value	Count	Frequency (%)
1	33	33.7%
0	26	26.5%
2	12	12.2%
5	8	8.2%
8	5	5.1%
6	5	5.1%
7	4	4.1%
3	3	3.1%
9	2	2.0%

Other Punctuation

Value	Count	Frequency (%)
.	45	37.2%
/	40	33.1%
?	10	8.3%
:	10	8.3%
&	10	8.3%
!	5	4.1%
%	1	0.8%

Space Separator

Value	Count	Frequency (%)
	59	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	30	100.0%

Math Symbol

Value	Count	Frequency (%)
=	20	100.0%

Uppercase Letter

Value	Count	Frequency (%)
C	10	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	572	52.3%
Common	328	30.0%
Hangul	194	17.7%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
다	10	5.2%
는	9	4.6%
을	6	3.1%
이	6	3.1%
씨	5	2.6%
의	4	2.1%
게	4	2.1%
실	3	1.5%
에	3	1.5%
를	3	1.5%
Other values (104)	141	72.7%

Latin

Value	Count	Frequency (%)
t	80	14.0%
n	80	14.0%
e	50	8.7%
c	50	8.7%
o	50	8.7%
m	30	5.2%
w	30	5.2%
i	20	3.5%
s	20	3.5%
l	20	3.5%
Other values (11)	142	24.8%

Common

Value	Count	Frequency (%)
	59	18.0%
.	45	13.7%
/	40	12.2%
1	33	10.1%
_	30	9.1%
0	26	7.9%
=	20	6.1%
2	12	3.7%
?	10	3.0%
:	10	3.0%
Other values (9)	43	13.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	900	82.3%
Hangul	194	17.7%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	80	8.9%
n	80	8.9%
	59	6.6%
e	50	5.6%
c	50	5.6%
o	50	5.6%
.	45	5.0%
/	40	4.4%
1	33	3.7%
_	30	3.3%
Other values (30)	383	42.6%

Hangul

Value	Count	Frequency (%)
다	10	5.2%
는	9	4.6%
을	6	3.1%
이	6	3.1%
씨	5	2.6%
의	4	2.1%
게	4	2.1%
실	3	1.5%
에	3	1.5%
를	3	1.5%
Other values (104)	141	72.7%

REG_DATE
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	56
Missing (%)	100.0%
Memory size	636.0 B

VOD_CRS_NM
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	56
Missing (%)	100.0%
Memory size	636.0 B

Unnamed: 5
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	56
Missing (%)	100.0%
Memory size	636.0 B

Phik (φk)

Heatmap
Table

	RSTRC_VID_ESSN_NO	VID_SJ_CN	VID_CN
RSTRC_VID_ESSN_NO	1.000	1.000	1.000
VID_SJ_CN	1.000	1.000	1.000
VID_CN	1.000	1.000	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	RSTRC_VID_ESSN_NO	VID_SJ_CN	VID_CN	REG_DATE	VOD_CRS_NM	Unnamed: 5
0	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
1	1010571	만병의 근원! 건강의 적신호인 뱃살을 잡아라!	나이가 들면서 무섭게 뱃살이 늘었다는 최은정 씨.	<NA>	<NA>	<NA>
2	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
3	호리호리한 팔다리와는 달라도 너무 다른 그녀의 뱃살.	<NA>	<NA>	<NA>	<NA>	<NA>
4	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
5	그녀는 허리둘레가 38인치로 심각한 복부비만이라는 진단을 받았는데...	<NA>	<NA>	<NA>	<NA>	<NA>
6	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
7	건강의 적신호를 알려주는 뱃살과 관련된 질병들은 무엇일까?	20160106	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1010571	<NA>	<NA>	<NA>
8	1010572	파인애플식초 만드는 법! 개미허리 만드는 비법 '화제'	열량이 높은 중국요리를 먹고도 뱃살을 잡을 수 있다는 그녀들!	<NA>	<NA>	<NA>
9	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>

	RSTRC_VID_ESSN_NO	VID_SJ_CN	VID_CN	REG_DATE	VOD_CRS_NM	Unnamed: 5
46	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
47	그런데 폐경이 한참 지난 권이현 씨는 날씬한 몸매를 유지하고 있었는데...	<NA>	<NA>	<NA>	<NA>	<NA>
48	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
49	그녀가 늘 찾는다는 비만 예방을 돕는 '이것'의 정체는?	20160106	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1010603	<NA>	<NA>	<NA>
50	1010608	다이어트를 돕는 아마 씨 100% 활용법!	아마 씨로 갱년기 비만을 관리한다는 권이현 씨의 100% 활용법!	<NA>	<NA>	<NA>
51	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
52	그녀는 씨앗 자체가 아닌 가루로 만들어 활용한다고 하는데~	<NA>	<NA>	<NA>	<NA>	<NA>
53	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>
54	그녀가 아마 씨 가루를 활용하는 다양한 방법은 무엇일까?	20160106	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1010608	<NA>	<NA>	<NA>
55	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>

Most frequently occurring

	RSTRC_VID_ESSN_NO	VID_SJ_CN	VID_CN	# duplicates
0	<NA>	<NA>	<NA>	24

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Other Punctuation

Lowercase Letter

Space Separator

Math Symbol

Most occurring scripts

Most frequent character per script

Hangul

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Other Punctuation

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Hangul

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Lowercase Letter

Decimal Number

Other Punctuation

Space Separator

Connector Punctuation

Math Symbol

Uppercase Letter

Most occurring scripts

Most frequent character per script

Hangul

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Correlations

Missing values

Sample

Duplicate rows

Most frequently occurring