gimi9 Pandas Profiling

Dataset statistics

Number of variables	6
Number of observations	30
Missing cells	112
Missing cells (%)	62.2%
Duplicate rows	1
Duplicate rows (%)	3.3%
Total size in memory	1.6 KiB
Average record size in memory	55.4 B

Variable types

Text	3
Unsupported	3

Dataset

Description	샘플 데이터
Author	MBN
URL	https://kdx.kr/data/view/162

Alerts

Dataset has 1 (3.3%) duplicate rows	Duplicates
`RSTRC_VID_ESSN_NO` has 2 (6.7%) missing values	Missing
`VID_SJ_CN` has 10 (33.3%) missing values	Missing
`VID_CN` has 10 (33.3%) missing values	Missing
`REG_DATE` has 30 (100.0%) missing values	Missing
`VOD_CRS_NM` has 30 (100.0%) missing values	Missing
`Unnamed: 5` has 30 (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	2023-12-11 21:16:14.814823
Analysis finished	2023-12-11 21:16:15.308428
Duration	0.49 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

RSTRC_VID_ESSN_NO
Text

MISSING

Distinct	28
Distinct (%)	100.0%
Missing	2
Missing (%)	6.7%
Memory size	372.0 B

Length

Max length	49
Median length	27
Mean length	16.571429
Min length	7

Characters and Unicode

Total characters	464
Distinct characters	142
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

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

Unique

Unique	28 ?
Unique (%)	100.0%

Sample

1st row	1005566
2nd row	10가지 종류의 잡곡을 이용한
3rd row	떡갈나무 잎밥 만드는 방법은?
4th row	1005567
5th row	평균적인 신체온도는 36.5도지만 40대 이후에는 평균 체온을 유지하기가 어렵다는데...

Value	Count	Frequency (%)
김치	2	1.8%
금박의	2	1.8%
식용	2	1.8%
겨울	2	1.8%
최고의	2	1.8%
맛은	2	1.8%
꼭	2	1.8%
서류상으로	1	0.9%
더	1	0.9%
부분에서	1	0.9%
Other values (94)	94	84.7%

Most occurring characters

Value	Count	Frequency (%)
	84	18.1%
0	25	5.4%
는	16	3.4%
5	15	3.2%
1	12	2.6%
6	12	2.6%
의	9	1.9%
이	8	1.7%
?	8	1.7%
가	8	1.7%
Other values (132)	267	57.5%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	283	61.0%
Space Separator	84	18.1%
Decimal Number	77	16.6%
Other Punctuation	20	4.3%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
는	16	5.7%
의	9	3.2%
이	8	2.8%
가	8	2.8%
은	7	2.5%
을	6	2.1%
하	6	2.1%
에	5	1.8%
서	5	1.8%
법	5	1.8%
Other values (117)	208	73.5%

Decimal Number

Value	Count	Frequency (%)
0	25	32.5%
5	15	19.5%
1	12	15.6%
6	12	15.6%
3	5	6.5%
9	2	2.6%
4	2	2.6%
8	2	2.6%
7	1	1.3%
2	1	1.3%

Other Punctuation

Value	Count	Frequency (%)
?	8	40.0%
.	7	35.0%
!	4	20.0%
,	1	5.0%

Space Separator

Value	Count	Frequency (%)
	84	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	283	61.0%
Common	181	39.0%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
는	16	5.7%
의	9	3.2%
이	8	2.8%
가	8	2.8%
은	7	2.5%
을	6	2.1%
하	6	2.1%
에	5	1.8%
서	5	1.8%
법	5	1.8%
Other values (117)	208	73.5%

Common

Value	Count	Frequency (%)
	84	46.4%
0	25	13.8%
5	15	8.3%
1	12	6.6%
6	12	6.6%
?	8	4.4%
.	7	3.9%
3	5	2.8%
!	4	2.2%
9	2	1.1%
Other values (5)	7	3.9%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	283	61.0%
ASCII	181	39.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	84	46.4%
0	25	13.8%
5	15	8.3%
1	12	6.6%
6	12	6.6%
?	8	4.4%
.	7	3.9%
3	5	2.8%
!	4	2.2%
9	2	1.1%
Other values (5)	7	3.9%

Hangul

Value	Count	Frequency (%)
는	16	5.7%
의	9	3.2%
이	8	2.8%
가	8	2.8%
은	7	2.5%
을	6	2.1%
하	6	2.1%
에	5	1.8%
서	5	1.8%
법	5	1.8%
Other values (117)	208	73.5%

VID_SJ_CN
Text

MISSING

Distinct	14
Distinct (%)	70.0%
Missing	10
Missing (%)	33.3%
Memory size	372.0 B

Length

Max length	18
Median length	17.5
Mean length	11.6
Min length	8

Characters and Unicode

Total characters	232
Distinct characters	87
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

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

Unique

Unique	11 ?
Unique (%)	55.0%

Sample

1st row	약이 되는 떡갈나무 잎밥
2nd row	20150105
3rd row	이경제 멘토가 추천하는 겨울 차
4th row	20150105
5th row	갱년기 여성에게 제격! 겨우살이

Value	Count	Frequency (%)
20150105	3	5.8%
20150119	3	5.8%
20150112	3	5.8%
강순의	2	3.8%
은행보단	1	1.9%
담그는	1	1.9%
법	1	1.9%
금반지	1	1.9%
싸게	1	1.9%
사는	1	1.9%
Other values (35)	35	67.3%

Most occurring characters

Value	Count	Frequency (%)
	32	13.8%
1	26	11.2%
0	23	9.9%
2	14	6.0%
5	13	5.6%
는	5	2.2%
금	4	1.7%
이	4	1.7%
은	4	1.7%
!	3	1.3%
Other values (77)	104	44.8%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	115	49.6%
Decimal Number	80	34.5%
Space Separator	32	13.8%
Other Punctuation	5	2.2%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
는	5	4.3%
금	4	3.5%
이	4	3.5%
은	4	3.5%
김	3	2.6%
치	3	2.6%
의	3	2.6%
겨	3	2.6%
증	3	2.6%
법	2	1.7%
Other values (67)	81	70.4%

Decimal Number

Value	Count	Frequency (%)
1	26	32.5%
0	23	28.7%
2	14	17.5%
5	13	16.2%
9	3	3.8%
6	1	1.2%

Other Punctuation

Value	Count	Frequency (%)
!	3	60.0%
,	1	20.0%
?	1	20.0%

Space Separator

Value	Count	Frequency (%)
	32	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	117	50.4%
Hangul	115	49.6%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
는	5	4.3%
금	4	3.5%
이	4	3.5%
은	4	3.5%
김	3	2.6%
치	3	2.6%
의	3	2.6%
겨	3	2.6%
증	3	2.6%
법	2	1.7%
Other values (67)	81	70.4%

Common

Value	Count	Frequency (%)
	32	27.4%
1	26	22.2%
0	23	19.7%
2	14	12.0%
5	13	11.1%
!	3	2.6%
9	3	2.6%
,	1	0.9%
?	1	0.9%
6	1	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	117	50.4%
Hangul	115	49.6%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	32	27.4%
1	26	22.2%
0	23	19.7%
2	14	12.0%
5	13	11.1%
!	3	2.6%
9	3	2.6%
,	1	0.9%
?	1	0.9%
6	1	0.9%

Hangul

Value	Count	Frequency (%)
는	5	4.3%
금	4	3.5%
이	4	3.5%
은	4	3.5%
김	3	2.6%
치	3	2.6%
의	3	2.6%
겨	3	2.6%
증	3	2.6%
법	2	1.7%
Other values (67)	81	70.4%

VID_CN
Text

MISSING

Distinct	20
Distinct (%)	100.0%
Missing	10
Missing (%)	33.3%
Memory size	372.0 B

Length

Max length	82
Median length	57
Mean length	51.7
Min length	10

Characters and Unicode

Total characters	1034
Distinct characters	135
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	건강을 되찾아 준다는 보약 밥상!
2nd row	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005566
3rd row	겨울은 중풍과 심장마비가 상승하는 계절!
4th row	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005567
5th row	많고 많은 약초 중에서 겨울에 필요한 약초는 따로 있다?!

Value	Count	Frequency (%)
김치	2	3.0%
금을	2	3.0%
건강을	1	1.5%
http://www.mbn.co.kr/player/moviecontents.mbn?content_cls_cd=21&content_id=1005600	1	1.5%
강순의가	1	1.5%
알려주는	1	1.5%
http://www.mbn.co.kr/player/moviecontents.mbn?content_cls_cd=21&content_id=1005601	1	1.5%
순금으로	1	1.5%
속지	1	1.5%
않고	1	1.5%
Other values (54)	54	81.8%

Most occurring characters

Value	Count	Frequency (%)
n	80	7.7%
t	80	7.7%
c	50	4.8%
o	50	4.8%
e	50	4.8%
	48	4.6%
.	40	3.9%
/	40	3.9%
m	30	2.9%
w	30	2.9%
Other values (125)	536	51.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	560	54.2%
Other Letter	158	15.3%
Other Punctuation	118	11.4%
Decimal Number	90	8.7%
Space Separator	48	4.6%
Connector Punctuation	30	2.9%
Math Symbol	20	1.9%
Uppercase Letter	10	1.0%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
는	8	5.1%
금	5	3.2%
을	4	2.5%
의	4	2.5%
가	4	2.5%
다	4	2.5%
보	4	2.5%
순	3	1.9%
강	3	1.9%
지	3	1.9%
Other values (86)	116	73.4%

Lowercase Letter

Value	Count	Frequency (%)
n	80	14.3%
t	80	14.3%
c	50	8.9%
o	50	8.9%
e	50	8.9%
m	30	5.4%
w	30	5.4%
r	20	3.6%
p	20	3.6%
b	20	3.6%
Other values (9)	130	23.2%

Decimal Number

Value	Count	Frequency (%)
0	23	25.6%
1	21	23.3%
5	14	15.6%
2	11	12.2%
6	11	12.2%
3	4	4.4%
9	2	2.2%
8	2	2.2%
4	1	1.1%
7	1	1.1%

Other Punctuation

Value	Count	Frequency (%)
.	40	33.9%
/	40	33.9%
?	11	9.3%
&	10	8.5%
:	10	8.5%
!	7	5.9%

Space Separator

Value	Count	Frequency (%)
	48	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	570	55.1%
Common	306	29.6%
Hangul	158	15.3%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
는	8	5.1%
금	5	3.2%
을	4	2.5%
의	4	2.5%
가	4	2.5%
다	4	2.5%
보	4	2.5%
순	3	1.9%
강	3	1.9%
지	3	1.9%
Other values (86)	116	73.4%

Latin

Value	Count	Frequency (%)
n	80	14.0%
t	80	14.0%
c	50	8.8%
o	50	8.8%
e	50	8.8%
m	30	5.3%
w	30	5.3%
r	20	3.5%
p	20	3.5%
b	20	3.5%
Other values (10)	140	24.6%

Common

Value	Count	Frequency (%)
	48	15.7%
.	40	13.1%
/	40	13.1%
_	30	9.8%
0	23	7.5%
1	21	6.9%
=	20	6.5%
5	14	4.6%
?	11	3.6%
2	11	3.6%
Other values (9)	48	15.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	876	84.7%
Hangul	158	15.3%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	80	9.1%
t	80	9.1%
c	50	5.7%
o	50	5.7%
e	50	5.7%
	48	5.5%
.	40	4.6%
/	40	4.6%
m	30	3.4%
w	30	3.4%
Other values (29)	378	43.2%

Hangul

Value	Count	Frequency (%)
는	8	5.1%
금	5	3.2%
을	4	2.5%
의	4	2.5%
가	4	2.5%
다	4	2.5%
보	4	2.5%
순	3	1.9%
강	3	1.9%
지	3	1.9%
Other values (86)	116	73.4%

REG_DATE
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	30
Missing (%)	100.0%
Memory size	402.0 B

VOD_CRS_NM
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	30
Missing (%)	100.0%
Memory size	402.0 B

Unnamed: 5
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	30
Missing (%)	100.0%
Memory size	402.0 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	1005566	약이 되는 떡갈나무 잎밥	건강을 되찾아 준다는 보약 밥상!	<NA>	<NA>	<NA>
2	10가지 종류의 잡곡을 이용한	<NA>	<NA>	<NA>	<NA>	<NA>
3	떡갈나무 잎밥 만드는 방법은?	20150105	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005566	<NA>	<NA>	<NA>
4	1005567	이경제 멘토가 추천하는 겨울 차	겨울은 중풍과 심장마비가 상승하는 계절!	<NA>	<NA>	<NA>
5	평균적인 신체온도는 36.5도지만 40대 이후에는 평균 체온을 유지하기가 어렵다는데...	20150105	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005567	<NA>	<NA>	<NA>
6	1005568	갱년기 여성에게 제격! 겨우살이	많고 많은 약초 중에서 겨울에 필요한 약초는 따로 있다?!	<NA>	<NA>	<NA>
7	약초 전문가가 추천하는 최고의 겨울 약초는?!	20150105	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005568	<NA>	<NA>	<NA>
8	1005599	김치 명인 강순의 집을 가다	실내를 가득 채운 수 십여개의 장아찌 항아리!	<NA>	<NA>	<NA>
9	김치 전문가 강순의가 직접 만든	<NA>	<NA>	<NA>	<NA>	<NA>

	RSTRC_VID_ESSN_NO	VID_SJ_CN	VID_CN	REG_DATE	VOD_CRS_NM	Unnamed: 5
20	1005633	금, 은행보단 증권사를 이용하라!	증권사에서 금을 판매한다는것이 다소 생소한 정보	<NA>	<NA>	<NA>
21	현물이 아닌 서류상으로 금을 구매할 경우	<NA>	<NA>	<NA>	<NA>	<NA>
22	과연 어떤 부분에서 더 이득을 볼 수 있는 것일까	20150119	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005633	<NA>	<NA>	<NA>
23	1005634	보증서와 현금영수증은 꼭 챙겨라!	금을 구매했을 때 꼭 들어있는 보증서!	<NA>	<NA>	<NA>
24	보증서에 가장 중요한 것과 꼭 확인해야 할 부분은?	<NA>	<NA>	<NA>	<NA>	<NA>
25	그리고 현금영수증을 꼭 챙겨야 하는 이유는?	20150119	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005634	<NA>	<NA>	<NA>
26	1005668	식용 금박의 맛과 효능은?	보기만 해도 황홀해지는 금!	<NA>	<NA>	<NA>
27	시중에 판매하는 식용 금박의 맛은?	<NA>	<NA>	<NA>	<NA>	<NA>
28	한의사 이경제가 말하는 식용 금박의 효능!	20150126	http://www.mbn.co.kr/player/movieContents.mbn?content_cls_cd=21&content_id=1005668	<NA>	<NA>	<NA>
29	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>

Most frequently occurring

	RSTRC_VID_ESSN_NO	VID_SJ_CN	VID_CN	# duplicates
0	<NA>	<NA>	<NA>	2

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Hangul

Common

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

Space Separator

Most occurring scripts

Most frequent character per script

Hangul

Common

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