Overview

Dataset statistics

Number of variables9
Number of observations1599
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory121.9 KiB
Average record size in memory78.1 B

Variable types

Numeric6
Categorical1
Text2

Dataset

Description평가년도,연번,쇼핑몰 구분,쇼핑몰 명,도메인명,소비자보호평가,이용자만족평가,피해발생평가,전체평가
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21171/S/1/datasetView.do

Alerts

평가년도 is highly overall correlated with 연번High correlation
연번 is highly overall correlated with 평가년도High correlation
소비자보호평가 is highly overall correlated with 전체평가High correlation
이용자만족평가 is highly overall correlated with 전체평가High correlation
전체평가 is highly overall correlated with 소비자보호평가 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-05-03 21:14:36.715593
Analysis finished2024-05-03 21:14:53.968738
Duration17.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

평가년도
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.5328
Minimum2007
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-03T21:14:54.229270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007
Q12010.5
median2015
Q32018.5
95-th percentile2022
Maximum2023
Range16
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.6660724
Coefficient of variation (CV)0.0023162057
Kurtosis-1.1565701
Mean2014.5328
Median Absolute Deviation (MAD)4
Skewness0.038245482
Sum3221238
Variance21.772232
MonotonicityDecreasing
2024-05-03T21:14:54.679319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2014 100
 
6.3%
2008 100
 
6.3%
2021 100
 
6.3%
2020 100
 
6.3%
2019 100
 
6.3%
2018 100
 
6.3%
2017 100
 
6.3%
2016 100
 
6.3%
2015 100
 
6.3%
2007 100
 
6.3%
Other values (7) 599
37.5%
ValueCountFrequency (%)
2007 100
6.3%
2008 100
6.3%
2009 100
6.3%
2010 100
6.3%
2011 100
6.3%
2012 99
6.2%
2013 100
6.3%
2014 100
6.3%
2015 100
6.3%
2016 100
6.3%
ValueCountFrequency (%)
2023 50
3.1%
2022 50
3.1%
2021 100
6.3%
2020 100
6.3%
2019 100
6.3%
2018 100
6.3%
2017 100
6.3%
2016 100
6.3%
2015 100
6.3%
2014 100
6.3%

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1599
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2050.6573
Minimum1200
Maximum3250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-03T21:14:55.274345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile1279.9
Q11599.5
median1999
Q32398.5
95-th percentile3118.1
Maximum3250
Range2050
Interquartile range (IQR)799

Descriptive statistics

Standard deviation547.25925
Coefficient of variation (CV)0.26687016
Kurtosis-0.67406274
Mean2050.6573
Median Absolute Deviation (MAD)400
Skewness0.4428869
Sum3279001
Variance299492.68
MonotonicityNot monotonic
2024-05-03T21:14:55.713258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3229 1
 
0.1%
1751 1
 
0.1%
1721 1
 
0.1%
1755 1
 
0.1%
1729 1
 
0.1%
1785 1
 
0.1%
1797 1
 
0.1%
1719 1
 
0.1%
1754 1
 
0.1%
1753 1
 
0.1%
Other values (1589) 1589
99.4%
ValueCountFrequency (%)
1200 1
0.1%
1201 1
0.1%
1202 1
0.1%
1203 1
0.1%
1204 1
0.1%
1205 1
0.1%
1206 1
0.1%
1207 1
0.1%
1208 1
0.1%
1209 1
0.1%
ValueCountFrequency (%)
3250 1
0.1%
3249 1
0.1%
3248 1
0.1%
3247 1
0.1%
3246 1
0.1%
3245 1
0.1%
3244 1
0.1%
3243 1
0.1%
3242 1
0.1%
3241 1
0.1%

쇼핑몰 구분
Categorical

Distinct13
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
종합쇼핑몰
480 
의류
352 
컴퓨터
103 
가전
101 
오픈마켓
93 
Other values (8)
470 

Length

Max length6
Median length5
Mean length3.4402752
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품
2nd row종합쇼핑몰
3rd row의류
4th row화장품
5th row소셜커머스

Common Values

ValueCountFrequency (%)
종합쇼핑몰 480
30.0%
의류 352
22.0%
컴퓨터 103
 
6.4%
가전 101
 
6.3%
오픈마켓 93
 
5.8%
화장품 81
 
5.1%
도서 79
 
4.9%
해외구매대행 79
 
4.9%
식품 63
 
3.9%
여행 59
 
3.7%
Other values (3) 109
 
6.8%

Length

2024-05-03T21:14:56.248623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종합쇼핑몰 480
30.0%
의류 352
22.0%
컴퓨터 103
 
6.4%
가전 101
 
6.3%
오픈마켓 93
 
5.8%
화장품 81
 
5.1%
도서 79
 
4.9%
해외구매대행 79
 
4.9%
식품 63
 
3.9%
여행 59
 
3.7%
Other values (3) 109
 
6.8%

쇼핑몰 명
Text

Distinct522
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2024-05-03T21:14:57.198815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.4903064
Min length1

Characters and Unicode

Total characters7180
Distinct characters397
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

Unique234 ?
Unique (%)14.6%

Sample

1st row샵풀무원
2nd row코스트코
3rd row젝시믹스
4th row클리오
5th row유튜브뮤직
ValueCountFrequency (%)
쇼핑몰 27
 
1.6%
11번가 16
 
0.9%
우체국쇼핑 15
 
0.9%
옥션 15
 
0.9%
하프클럽 15
 
0.9%
g마켓 15
 
0.9%
예스24 15
 
0.9%
쿠팡 15
 
0.9%
교보문고 14
 
0.8%
하이마트 14
 
0.8%
Other values (520) 1547
90.6%
2024-05-03T21:14:58.845814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 314
 
4.4%
스 277
 
3.9%
몰 183
 
2.5%
아 161
 
2.2%
리 144
 
2.0%
마 138
 
1.9%
핑 137
 
1.9%
쇼 134
 
1.9%
111
 
1.5%
l 107
 
1.5%
Other values (387) 5474
76.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6070
84.5%
Uppercase Letter 408
 
5.7%
Lowercase Letter 382
 
5.3%
Decimal Number 181
 
2.5%
Space Separator 111
 
1.5%
Other Punctuation 10
 
0.1%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 314
 
5.2%
스 277
 
4.6%
몰 183
 
3.0%
아 161
 
2.7%
리 144
 
2.4%
마 138
 
2.3%
핑 137
 
2.3%
쇼 134
 
2.2%
컴 93
 
1.5%
트 92
 
1.5%
Other values (334) 4397
72.4%
Uppercase Letter
ValueCountFrequency (%)
S 57
14.0%
N 38
9.3%
C 38
9.3%
G 38
9.3%
H 37
9.1%
O 33
8.1%
K 28
 
6.9%
J 26
 
6.4%
T 20
 
4.9%
P 16
 
3.9%
Other values (10) 77
18.9%
Lowercase Letter
ValueCountFrequency (%)
l 107
28.0%
a 74
19.4%
m 56
14.7%
e 24
 
6.3%
t 21
 
5.5%
o 19
 
5.0%
r 14
 
3.7%
i 13
 
3.4%
s 12
 
3.1%
n 11
 
2.9%
Other values (8) 31
 
8.1%
Decimal Number
ValueCountFrequency (%)
1 66
36.5%
2 37
20.4%
4 31
17.1%
0 20
 
11.0%
5 6
 
3.3%
9 6
 
3.3%
7 5
 
2.8%
3 4
 
2.2%
8 3
 
1.7%
6 3
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 6
60.0%
. 4
40.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6070
84.5%
Latin 790
 
11.0%
Common 320
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 314
 
5.2%
스 277
 
4.6%
몰 183
 
3.0%
아 161
 
2.7%
리 144
 
2.4%
마 138
 
2.3%
핑 137
 
2.3%
쇼 134
 
2.2%
컴 93
 
1.5%
트 92
 
1.5%
Other values (334) 4397
72.4%
Latin
ValueCountFrequency (%)
l 107
 
13.5%
a 74
 
9.4%
S 57
 
7.2%
m 56
 
7.1%
N 38
 
4.8%
C 38
 
4.8%
G 38
 
4.8%
H 37
 
4.7%
O 33
 
4.2%
K 28
 
3.5%
Other values (28) 284
35.9%
Common
ValueCountFrequency (%)
111
34.7%
1 66
20.6%
2 37
 
11.6%
4 31
 
9.7%
0 20
 
6.2%
( 9
 
2.8%
) 9
 
2.8%
5 6
 
1.9%
9 6
 
1.9%
/ 6
 
1.9%
Other values (5) 19
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6070
84.5%
ASCII 1110
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 314
 
5.2%
스 277
 
4.6%
몰 183
 
3.0%
아 161
 
2.7%
리 144
 
2.4%
마 138
 
2.3%
핑 137
 
2.3%
쇼 134
 
2.2%
컴 93
 
1.5%
트 92
 
1.5%
Other values (334) 4397
72.4%
ASCII
ValueCountFrequency (%)
111
 
10.0%
l 107
 
9.6%
a 74
 
6.7%
1 66
 
5.9%
S 57
 
5.1%
m 56
 
5.0%
N 38
 
3.4%
C 38
 
3.4%
G 38
 
3.4%
2 37
 
3.3%
Other values (43) 488
44.0%

도메인명
Text

Distinct599
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size12.6 KiB
2024-05-03T21:14:59.639684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length17.241401
Min length7

Characters and Unicode

Total characters27569
Distinct characters65
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique284 ?
Unique (%)17.8%

Sample

1st rowshop.pulmuone.co.kr
2nd rowwww.costco.co.kr
3rd rowwww.xexymix.com
4th rowwww.clubclio.co.kr
5th rowmusic.youtube.com
ValueCountFrequency (%)
www.gmarket.co.kr 18
 
1.1%
www.11st.co.kr 16
 
1.0%
www.interpark.com 14
 
0.9%
www.auction.co.kr 14
 
0.9%
www.wizwid.com 14
 
0.9%
www.compuzone.co.kr 14
 
0.9%
www.e-himart.co.kr 13
 
0.8%
모바일앱 13
 
0.8%
www.ticketlink.co.kr 13
 
0.8%
www.kyobobook.co.kr 13
 
0.8%
Other values (578) 1475
91.2%
2024-05-03T21:15:01.121537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 4386
15.9%
. 3838
13.9%
o 2677
 
9.7%
c 1887
 
6.8%
m 1493
 
5.4%
r 1334
 
4.8%
a 1181
 
4.3%
k 1049
 
3.8%
t 1036
 
3.8%
l 978
 
3.5%
Other values (55) 7710
28.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22705
82.4%
Other Punctuation 4440
 
16.1%
Decimal Number 235
 
0.9%
Other Letter 91
 
0.3%
Dash Punctuation 65
 
0.2%
Space Separator 23
 
0.1%
Uppercase Letter 4
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 4386
19.3%
o 2677
11.8%
c 1887
 
8.3%
m 1493
 
6.6%
r 1334
 
5.9%
a 1181
 
5.2%
k 1049
 
4.6%
t 1036
 
4.6%
l 978
 
4.3%
e 932
 
4.1%
Other values (16) 5752
25.3%
Other Letter
ValueCountFrequency (%)
바 14
15.4%
일 14
15.4%
모 14
15.4%
앱 13
14.3%
쿠 6
6.6%
팡 6
6.6%
요 6
6.6%
기 3
 
3.3%
츠 3
 
3.3%
이 3
 
3.3%
Other values (7) 9
9.9%
Decimal Number
ValueCountFrequency (%)
1 72
30.6%
2 51
21.7%
4 39
16.6%
0 31
13.2%
9 17
 
7.2%
5 7
 
3.0%
7 5
 
2.1%
3 5
 
2.1%
6 4
 
1.7%
8 4
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 3838
86.4%
/ 457
 
10.3%
: 142
 
3.2%
, 3
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
R 1
25.0%
G 1
25.0%
P 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22709
82.4%
Common 4769
 
17.3%
Hangul 91
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 4386
19.3%
o 2677
11.8%
c 1887
 
8.3%
m 1493
 
6.6%
r 1334
 
5.9%
a 1181
 
5.2%
k 1049
 
4.6%
t 1036
 
4.6%
l 978
 
4.3%
e 932
 
4.1%
Other values (20) 5756
25.3%
Common
ValueCountFrequency (%)
. 3838
80.5%
/ 457
 
9.6%
: 142
 
3.0%
1 72
 
1.5%
- 65
 
1.4%
2 51
 
1.1%
4 39
 
0.8%
0 31
 
0.7%
23
 
0.5%
9 17
 
0.4%
Other values (8) 34
 
0.7%
Hangul
ValueCountFrequency (%)
바 14
15.4%
일 14
15.4%
모 14
15.4%
앱 13
14.3%
쿠 6
6.6%
팡 6
6.6%
요 6
6.6%
기 3
 
3.3%
츠 3
 
3.3%
이 3
 
3.3%
Other values (7) 9
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27478
99.7%
Hangul 91
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 4386
16.0%
. 3838
14.0%
o 2677
 
9.7%
c 1887
 
6.9%
m 1493
 
5.4%
r 1334
 
4.9%
a 1181
 
4.3%
k 1049
 
3.8%
t 1036
 
3.8%
l 978
 
3.6%
Other values (38) 7619
27.7%
Hangul
ValueCountFrequency (%)
바 14
15.4%
일 14
15.4%
모 14
15.4%
앱 13
14.3%
쿠 6
6.6%
팡 6
6.6%
요 6
6.6%
기 3
 
3.3%
츠 3
 
3.3%
이 3
 
3.3%
Other values (7) 9
9.9%

소비자보호평가
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.924953
Minimum0
Maximum50
Zeros5
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-03T21:15:01.645700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile39
Q144
median46
Q347
95-th percentile48
Maximum50
Range50
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9790593
Coefficient of variation (CV)0.08857125
Kurtosis51.375489
Mean44.924953
Median Absolute Deviation (MAD)1
Skewness-5.36456
Sum71835
Variance15.832913
MonotonicityNot monotonic
2024-05-03T21:15:02.309289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
47 377
23.6%
46 256
16.0%
45 227
14.2%
48 204
12.8%
44 141
 
8.8%
43 83
 
5.2%
42 72
 
4.5%
40 53
 
3.3%
49 48
 
3.0%
41 41
 
2.6%
Other values (15) 97
 
6.1%
ValueCountFrequency (%)
0 5
0.3%
20 1
 
0.1%
25 1
 
0.1%
28 1
 
0.1%
29 1
 
0.1%
31 2
 
0.1%
32 3
 
0.2%
33 5
0.3%
34 4
0.3%
35 8
0.5%
ValueCountFrequency (%)
50 3
 
0.2%
49 48
 
3.0%
48 204
12.8%
47 377
23.6%
46 256
16.0%
45 227
14.2%
44 141
 
8.8%
43 83
 
5.2%
42 72
 
4.5%
41 41
 
2.6%

이용자만족평가
Real number (ℝ)

HIGH CORRELATION 

Distinct452
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.755103
Minimum0
Maximum31.13
Zeros3
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-03T21:15:02.962799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24.219
Q126
median27
Q327.905
95-th percentile29
Maximum31.13
Range31.13
Interquartile range (IQR)1.905

Descriptive statistics

Standard deviation1.8579775
Coefficient of variation (CV)0.069443857
Kurtosis79.380586
Mean26.755103
Median Absolute Deviation (MAD)1
Skewness-5.6556098
Sum42781.41
Variance3.4520806
MonotonicityNot monotonic
2024-05-03T21:15:03.588586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27.0 192
 
12.0%
26.0 168
 
10.5%
28.0 121
 
7.6%
25.0 92
 
5.8%
29.0 69
 
4.3%
24.0 32
 
2.0%
30.0 15
 
0.9%
27.16 9
 
0.6%
26.26 9
 
0.6%
27.32 7
 
0.4%
Other values (442) 885
55.3%
ValueCountFrequency (%)
0.0 3
0.2%
20.0 2
0.1%
21.0 1
 
0.1%
22.0 1
 
0.1%
22.36 1
 
0.1%
22.48 1
 
0.1%
22.61 1
 
0.1%
22.62 1
 
0.1%
22.7 1
 
0.1%
22.79 1
 
0.1%
ValueCountFrequency (%)
31.13 1
 
0.1%
31.0 4
0.3%
30.85 1
 
0.1%
30.76 1
 
0.1%
30.7 1
 
0.1%
30.63 1
 
0.1%
30.29 1
 
0.1%
30.25 1
 
0.1%
30.17 1
 
0.1%
30.11 1
 
0.1%

피해발생평가
Real number (ℝ)

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7911194
Minimum0
Maximum10
Zeros3
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-03T21:15:04.160542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q110
median10
Q310
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.80526813
Coefficient of variation (CV)0.082244745
Kurtosis53.048112
Mean9.7911194
Median Absolute Deviation (MAD)0
Skewness-6.1915826
Sum15656
Variance0.64845676
MonotonicityNot monotonic
2024-05-03T21:15:04.650797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
10 1438
89.9%
9 76
 
4.8%
8 41
 
2.6%
7 31
 
1.9%
4 5
 
0.3%
5 3
 
0.2%
0 3
 
0.2%
6 2
 
0.1%
ValueCountFrequency (%)
0 3
 
0.2%
4 5
 
0.3%
5 3
 
0.2%
6 2
 
0.1%
7 31
 
1.9%
8 41
 
2.6%
9 76
 
4.8%
10 1438
89.9%
ValueCountFrequency (%)
10 1438
89.9%
9 76
 
4.8%
8 41
 
2.6%
7 31
 
1.9%
6 2
 
0.1%
5 3
 
0.2%
4 5
 
0.3%
0 3
 
0.2%

전체평가
Real number (ℝ)

HIGH CORRELATION 

Distinct622
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.473052
Minimum0
Maximum89
Zeros3
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size14.2 KiB
2024-05-03T21:15:05.130598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile74.175
Q180
median82.34
Q384
95-th percentile86
Maximum89
Range89
Interquartile range (IQR)4

Descriptive statistics

Standard deviation5.3224548
Coefficient of variation (CV)0.065327794
Kurtosis108.74686
Mean81.473052
Median Absolute Deviation (MAD)1.97
Skewness-7.9783878
Sum130275.41
Variance28.328525
MonotonicityNot monotonic
2024-05-03T21:15:05.743173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.0 102
 
6.4%
83.0 93
 
5.8%
84.0 88
 
5.5%
80.0 65
 
4.1%
81.0 64
 
4.0%
85.0 52
 
3.3%
79.0 43
 
2.7%
78.0 32
 
2.0%
77.0 31
 
1.9%
76.0 25
 
1.6%
Other values (612) 1004
62.8%
ValueCountFrequency (%)
0.0 3
0.2%
35.0 1
 
0.1%
37.0 1
 
0.1%
57.0 1
 
0.1%
58.0 1
 
0.1%
61.0 1
 
0.1%
63.0 1
 
0.1%
65.0 1
 
0.1%
67.0 1
 
0.1%
68.0 5
0.3%
ValueCountFrequency (%)
89.0 1
0.1%
88.79 1
0.1%
88.29 1
0.1%
87.77 1
0.1%
87.55 1
0.1%
87.49 1
0.1%
87.27 1
0.1%
87.26 1
0.1%
87.15 1
0.1%
87.05 1
0.1%

Interactions

2024-05-03T21:14:50.522141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:38.989430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:41.332811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:43.471631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:45.941282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:48.393607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:50.909388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:39.399411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:41.743079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:43.903460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:46.364981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:48.724885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:51.290707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:39.764747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:42.077681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:44.286433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:46.737840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:49.017054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:51.619480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:40.164149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:42.444565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:44.816953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:47.110198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:49.395777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:52.000063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:40.531726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:42.762775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:45.183935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:47.555635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:49.809420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:52.375099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:40.930406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:43.091083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:45.570350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:48.015126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T21:14:50.196356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T21:15:06.167796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가년도연번쇼핑몰 구분소비자보호평가이용자만족평가피해발생평가전체평가
평가년도1.0000.9880.1660.2810.3840.1650.234
연번0.9881.0000.2540.2950.3610.1430.236
쇼핑몰 구분0.1660.2541.0000.2470.3410.1830.247
소비자보호평가0.2810.2950.2471.0000.5880.7060.955
이용자만족평가0.3840.3610.3410.5881.0000.6560.710
피해발생평가0.1650.1430.1830.7060.6561.0000.812
전체평가0.2340.2360.2470.9550.7100.8121.000
2024-05-03T21:15:06.503539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
평가년도연번소비자보호평가이용자만족평가피해발생평가전체평가쇼핑몰 구분
평가년도1.0000.9980.3080.0050.0140.2360.087
연번0.9981.0000.2950.0020.0220.2270.109
소비자보호평가0.3080.2951.0000.138-0.1130.8140.111
이용자만족평가0.0050.0020.1381.000-0.0130.5900.195
피해발생평가0.0140.022-0.113-0.0131.0000.1030.079
전체평가0.2360.2270.8140.5900.1031.0000.122
쇼핑몰 구분0.0870.1090.1110.1950.0790.1221.000

Missing values

2024-05-03T21:14:52.872527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T21:14:53.661045image/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

평가년도연번쇼핑몰 구분쇼핑몰 명도메인명소비자보호평가이용자만족평가피해발생평가전체평가
020233229식품샵풀무원shop.pulmuone.co.kr4929.791088.79
120233201종합쇼핑몰코스트코www.costco.co.kr5027.551087.55
220233213의류젝시믹스www.xexymix.com4928.271087.27
320233226화장품클리오www.clubclio.co.kr4829.151087.15
420233245소셜커머스유튜브뮤직music.youtube.com4927.931086.93
520233230식품마켓컬리www.kurly.com4729.371086.37
620233214의류안다르andar.co.kr4827.811085.81
720233223가전삼성닷컴www.samsung.com/sec4827.681085.68
820233202종합쇼핑몰홈플러스front.homeplus.co.kr4728.611085.61
920233239컴퓨터네이버 쇼핑라이브shoppinglive.naver.com/4827.61085.6
평가년도연번쇼핑몰 구분쇼핑몰 명도메인명소비자보호평가이용자만족평가피해발생평가전체평가
158920071269컴퓨터아이클럽www.iclub.co.kr3726.01073.0
159020071244종합쇼핑몰아사달쇼핑http://shop.asadal.com/3725.01072.0
159120071245종합쇼핑몰스코어마트www.scoremart.com3824.01072.0
159220071260해외구매대행예스뉴욕www.yesny.co.kr3625.01071.0
159320071246종합쇼핑몰컬쳐랜드http://cultureland.co.kr/3328.01071.0
159420071247종합쇼핑몰부자마켓vuza.com3623.01069.0
159520071248종합쇼핑몰유진시스템www.eused.co.kr3325.01068.0
159620071249종합쇼핑몰셀투바이닷컴sell2buy.com3226.01068.0
159720071275의류윙스몰www.wingsmall.co.kr3126.01067.0
159820071279의류핑크마티니www.pinkmartini.tv3421.01065.0