Overview

Dataset statistics

Number of variables6
Number of observations2376
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory113.8 KiB
Average record size in memory49.1 B

Variable types

Categorical4
Text1
Numeric1

Dataset

Description업종별 광고효과에 대한 시장분석 설문조사 데이터 정보를 제공합니다. 업종별, 연령대별, 성별, KBF 순위, 광고영향력, 구매 경험 및 구매 의향 등의 조사 결과 데이터를 제공합니다.
Author한국방송광고진흥공사
URLhttps://www.data.go.kr/data/15111068/fileData.do

Alerts

응답수 has 306 (12.9%) zerosZeros

Reproduction

Analysis started2023-12-12 21:35:22.681536
Analysis finished2023-12-12 21:35:23.427704
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
스킨케어
400 
건강보조기구
344 
캠핑용품
344 
인테리어 서비스
344 
뷰티 디바이스
336 
Other values (2)
608 

Length

Max length11
Median length8
Mean length6.3939394
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row스킨케어
2nd row스킨케어
3rd row스킨케어
4th row스킨케어
5th row스킨케어

Common Values

ValueCountFrequency (%)
스킨케어 400
16.8%
건강보조기구 344
14.5%
캠핑용품 344
14.5%
인테리어 서비스 344
14.5%
뷰티 디바이스 336
14.1%
건강기능식품 328
13.8%
국내 숙박 예약서비스 280
11.8%

Length

2023-12-13T06:35:23.788703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:35:23.939773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스킨케어 400
11.1%
건강보조기구 344
9.5%
캠핑용품 344
9.5%
인테리어 344
9.5%
서비스 344
9.5%
뷰티 336
9.3%
디바이스 336
9.3%
건강기능식품 328
9.1%
국내 280
7.7%
숙박 280
7.7%

연령대
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
20~29세
594 
30~39세
594 
40~49세
594 
50~59세
594 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20~29세
2nd row20~29세
3rd row20~29세
4th row20~29세
5th row20~29세

Common Values

ValueCountFrequency (%)
20~29세 594
25.0%
30~39세 594
25.0%
40~49세 594
25.0%
50~59세 594
25.0%

Length

2023-12-13T06:35:24.070728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:35:24.169403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20~29세 594
25.0%
30~39세 594
25.0%
40~49세 594
25.0%
50~59세 594
25.0%

성별
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
남성
1188 
여성
1188 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남성
2nd row남성
3rd row남성
4th row남성
5th row남성

Common Values

ValueCountFrequency (%)
남성 1188
50.0%
여성 1188
50.0%

Length

2023-12-13T06:35:24.282906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:35:24.383839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남성 1188
50.0%
여성 1188
50.0%

구분
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
KBF 1,2,3순위 (중복응답)
952 
KBF 1순위
920 
광고영향력
280 
최근 6개월 내 구매 경험
112 
향후 6개월 내 구매 의향
112 

Length

Max length18
Median length14
Mean length11.83165
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKBF 1순위
2nd rowKBF 1순위
3rd rowKBF 1순위
4th rowKBF 1순위
5th rowKBF 1순위

Common Values

ValueCountFrequency (%)
KBF 1,2,3순위 (중복응답) 952
40.1%
KBF 1순위 920
38.7%
광고영향력 280
 
11.8%
최근 6개월 내 구매 경험 112
 
4.7%
향후 6개월 내 구매 의향 112
 
4.7%

Length

2023-12-13T06:35:24.483962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:35:24.599221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kbf 1872
30.7%
1,2,3순위 952
15.6%
중복응답 952
15.6%
1순위 920
15.1%
광고영향력 280
 
4.6%
6개월 224
 
3.7%
내 224
 
3.7%
구매 224
 
3.7%
최근 112
 
1.8%
경험 112
 
1.8%
Other values (2) 224
 
3.7%

항목
Text

Distinct77
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size18.7 KiB
2023-12-13T06:35:24.907916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length9.03367
Min length1

Characters and Unicode

Total characters21464
Distinct characters200
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보습력/유분감
2nd row기능성(미백, 주름개선 등)
3rd row저자극성
4th row함유성분/원료
5th row가격
ValueCountFrequency (%)
등 432
 
7.8%
있다 168
 
3.0%
없다 168
 
3.0%
광고(스토리 112
 
2.0%
다양한 112
 
2.0%
모델 112
 
2.0%
편이다 112
 
2.0%
주위의 112
 
2.0%
이미지 112
 
2.0%
브랜드(인지도 112
 
2.0%
Other values (134) 3984
72.0%
2023-12-13T06:35:25.367115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3160
 
14.7%
, 768
 
3.6%
다 616
 
2.9%
/ 592
 
2.8%
( 576
 
2.7%
) 576
 
2.7%
이 496
 
2.3%
등 432
 
2.0%
인 432
 
2.0%
지 400
 
1.9%
Other values (190) 13416
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15480
72.1%
Space Separator 3160
 
14.7%
Other Punctuation 1360
 
6.3%
Open Punctuation 576
 
2.7%
Close Punctuation 576
 
2.7%
Uppercase Letter 232
 
1.1%
Lowercase Letter 64
 
0.3%
Decimal Number 16
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 616
 
4.0%
이 496
 
3.2%
등 432
 
2.8%
인 432
 
2.8%
지 400
 
2.6%
성 384
 
2.5%
리 328
 
2.1%
도 312
 
2.0%
의 312
 
2.0%
매 288
 
1.9%
Other values (176) 11480
74.2%
Uppercase Letter
ValueCountFrequency (%)
A 80
34.5%
S 56
24.1%
I 32
 
13.8%
U 32
 
13.8%
D 16
 
6.9%
E 8
 
3.4%
G 8
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 768
56.5%
/ 592
43.5%
Space Separator
ValueCountFrequency (%)
3160
100.0%
Open Punctuation
ValueCountFrequency (%)
( 576
100.0%
Close Punctuation
ValueCountFrequency (%)
) 576
100.0%
Lowercase Letter
ValueCountFrequency (%)
p 64
100.0%
Decimal Number
ValueCountFrequency (%)
3 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15480
72.1%
Common 5688
 
26.5%
Latin 296
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 616
 
4.0%
이 496
 
3.2%
등 432
 
2.8%
인 432
 
2.8%
지 400
 
2.6%
성 384
 
2.5%
리 328
 
2.1%
도 312
 
2.0%
의 312
 
2.0%
매 288
 
1.9%
Other values (176) 11480
74.2%
Latin
ValueCountFrequency (%)
A 80
27.0%
p 64
21.6%
S 56
18.9%
I 32
 
10.8%
U 32
 
10.8%
D 16
 
5.4%
E 8
 
2.7%
G 8
 
2.7%
Common
ValueCountFrequency (%)
3160
55.6%
, 768
 
13.5%
/ 592
 
10.4%
( 576
 
10.1%
) 576
 
10.1%
3 16
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15480
72.1%
ASCII 5984
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3160
52.8%
, 768
 
12.8%
/ 592
 
9.9%
( 576
 
9.6%
) 576
 
9.6%
A 80
 
1.3%
p 64
 
1.1%
S 56
 
0.9%
I 32
 
0.5%
U 32
 
0.5%
Other values (4) 48
 
0.8%
Hangul
ValueCountFrequency (%)
다 616
 
4.0%
이 496
 
3.2%
등 432
 
2.8%
인 432
 
2.8%
지 400
 
2.6%
성 384
 
2.5%
리 328
 
2.1%
도 312
 
2.0%
의 312
 
2.0%
매 288
 
1.9%
Other values (176) 11480
74.2%

응답수
Real number (ℝ)

ZEROS 

Distinct158
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.180135
Minimum0
Maximum254
Zeros306
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size21.0 KiB
2023-12-13T06:35:25.504276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q323.25
95-th percentile83
Maximum254
Range254
Interquartile range (IQR)21.25

Descriptive statistics

Standard deviation32.156112
Coefficient of variation (CV)1.5934538
Kurtosis12.513274
Mean20.180135
Median Absolute Deviation (MAD)7
Skewness3.1735015
Sum47948
Variance1034.0155
MonotonicityNot monotonic
2023-12-13T06:35:25.627502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 306
 
12.9%
1 201
 
8.5%
2 150
 
6.3%
3 115
 
4.8%
5 110
 
4.6%
4 102
 
4.3%
7 86
 
3.6%
8 84
 
3.5%
6 83
 
3.5%
10 64
 
2.7%
Other values (148) 1075
45.2%
ValueCountFrequency (%)
0 306
12.9%
1 201
8.5%
2 150
6.3%
3 115
 
4.8%
4 102
 
4.3%
5 110
 
4.6%
6 83
 
3.5%
7 86
 
3.6%
8 84
 
3.5%
9 50
 
2.1%
ValueCountFrequency (%)
254 1
< 0.1%
238 1
< 0.1%
236 1
< 0.1%
216 1
< 0.1%
212 1
< 0.1%
211 1
< 0.1%
205 1
< 0.1%
204 2
0.1%
202 1
< 0.1%
201 1
< 0.1%

Interactions

2023-12-13T06:35:23.105849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:35:25.699567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종연령대성별구분항목응답수
업종1.0000.0000.0000.0000.9070.222
연령대0.0001.0000.0000.0000.0000.068
성별0.0000.0001.0000.0000.0000.000
구분0.0000.0000.0001.0000.9540.732
항목0.9070.0000.0000.9541.0000.701
응답수0.2220.0680.0000.7320.7011.000
2023-12-13T06:35:25.786400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연령대업종성별
구분1.0000.0000.0000.000
연령대0.0001.0000.0000.000
업종0.0000.0001.0000.000
성별0.0000.0000.0001.000
2023-12-13T06:35:25.871018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
응답수업종연령대성별구분
응답수1.0000.1140.0410.0000.391
업종0.1141.0000.0000.0000.000
연령대0.0410.0001.0000.0000.000
성별0.0000.0000.0001.0000.000
구분0.3910.0000.0000.0001.000

Missing values

2023-12-13T06:35:23.250018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:35:23.361676image/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

업종연령대성별구분항목응답수
0스킨케어20~29세남성KBF 1순위보습력/유분감15
1스킨케어20~29세남성KBF 1순위기능성(미백, 주름개선 등)11
2스킨케어20~29세남성KBF 1순위저자극성10
3스킨케어20~29세남성KBF 1순위함유성분/원료4
4스킨케어20~29세남성KBF 1순위가격13
5스킨케어20~29세남성KBF 1순위주위의 평판/입소문6
6스킨케어20~29세남성KBF 1순위브랜드(인지도, 이미지 등)7
7스킨케어20~29세남성KBF 1순위할인/이벤트7
8스킨케어20~29세남성KBF 1순위질감/농도4
9스킨케어20~29세남성KBF 1순위양/용량8
업종연령대성별구분항목응답수
2366인테리어 서비스50~59세여성KBF 1,2,3순위 (중복응답)광고(스토리, 모델, 메시지)2
2367인테리어 서비스50~59세여성KBF 1,2,3순위 (중복응답)가격1
2368인테리어 서비스50~59세여성KBF 1,2,3순위 (중복응답)품질0
2369인테리어 서비스50~59세여성KBF 1,2,3순위 (중복응답)배송속도0
2370인테리어 서비스50~59세여성KBF 1,2,3순위 (중복응답)접근성0
2371인테리어 서비스50~59세여성광고영향력전혀 없다1
2372인테리어 서비스50~59세여성광고영향력없는 편이다2
2373인테리어 서비스50~59세여성광고영향력보통이다33
2374인테리어 서비스50~59세여성광고영향력있는 편이다89
2375인테리어 서비스50~59세여성광고영향력매우 있다9