Overview

Dataset statistics

Number of variables5
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory46.7 B

Variable types

Categorical1
Numeric1
Text3

Dataset

Description년도,연번,쇼핑몰명,취급품목,총 접수건/미처리건
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21169/S/1/datasetView.do

Alerts

연번 is highly overall correlated with 년도High correlation
년도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-05-04 03:48:40.022479
Analysis finished2024-05-04 03:48:41.469566
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2022
15 
2023
11 
2024
2 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024
2nd row2024
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2022 15
53.6%
2023 11
39.3%
2024 2
 
7.1%

Length

2024-05-04T03:48:41.797185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T03:48:42.270081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 15
53.6%
2023 11
39.3%
2024 2
 
7.1%

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean543.78571
Minimum530
Maximum558
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2024-05-04T03:48:42.885650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum530
5-th percentile531.35
Q1536.75
median543.5
Q3551.25
95-th percentile556.65
Maximum558
Range28
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.590939
Coefficient of variation (CV)0.01579839
Kurtosis-1.2033642
Mean543.78571
Median Absolute Deviation (MAD)7.5
Skewness0.067015218
Sum15226
Variance73.804233
MonotonicityNot monotonic
2024-05-04T03:48:43.291251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
557 1
 
3.6%
534 1
 
3.6%
536 1
 
3.6%
535 1
 
3.6%
541 1
 
3.6%
538 1
 
3.6%
539 1
 
3.6%
540 1
 
3.6%
544 1
 
3.6%
543 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
530 1
3.6%
531 1
3.6%
532 1
3.6%
533 1
3.6%
534 1
3.6%
535 1
3.6%
536 1
3.6%
537 1
3.6%
538 1
3.6%
539 1
3.6%
ValueCountFrequency (%)
558 1
3.6%
557 1
3.6%
556 1
3.6%
555 1
3.6%
554 1
3.6%
553 1
3.6%
552 1
3.6%
551 1
3.6%
549 1
3.6%
548 1
3.6%

쇼핑몰명
Text

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-04T03:48:43.695186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length8.6428571
Min length2

Characters and Unicode

Total characters242
Distinct characters119
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)85.7%

Sample

1st row웁스(WHOOPS)
2nd row캐쉬메이커
3rd row슈즈오페라
4th row맘앤마트 / MOMNMART
5th row피규어세상 / Figure Sesang
ValueCountFrequency (%)
5
 
11.6%
맘앤마트 2
 
4.7%
momnmart 2
 
4.7%
애슬리트 2
 
4.7%
figure 2
 
4.7%
트렌디슈즈 1
 
2.3%
보네르 1
 
2.3%
풀문(fullmoon)/럭스돌(luxxdoll 1
 
2.3%
오시싸 1
 
2.3%
뷰티히어로 1
 
2.3%
Other values (25) 25
58.1%
2024-05-04T03:48:44.526329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
6.2%
/ 10
 
4.1%
트 7
 
2.9%
스 6
 
2.5%
M 6
 
2.5%
E 6
 
2.5%
S 5
 
2.1%
R 5
 
2.1%
이 5
 
2.1%
라 5
 
2.1%
Other values (109) 172
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
50.8%
Uppercase Letter 62
25.6%
Lowercase Letter 24
 
9.9%
Space Separator 15
 
6.2%
Other Punctuation 10
 
4.1%
Open Punctuation 4
 
1.7%
Close Punctuation 4
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 7
 
5.7%
스 6
 
4.9%
이 5
 
4.1%
라 5
 
4.1%
리 4
 
3.3%
어 3
 
2.4%
슈 3
 
2.4%
크 2
 
1.6%
션 2
 
1.6%
시 2
 
1.6%
Other values (70) 84
68.3%
Uppercase Letter
ValueCountFrequency (%)
M 6
 
9.7%
E 6
 
9.7%
S 5
 
8.1%
R 5
 
8.1%
O 5
 
8.1%
N 5
 
8.1%
F 4
 
6.5%
A 4
 
6.5%
T 3
 
4.8%
H 2
 
3.2%
Other values (12) 17
27.4%
Lowercase Letter
ValueCountFrequency (%)
l 4
16.7%
o 3
12.5%
u 3
12.5%
x 2
8.3%
n 2
8.3%
e 2
8.3%
g 2
8.3%
m 1
 
4.2%
d 1
 
4.2%
a 1
 
4.2%
Other values (3) 3
12.5%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
50.8%
Latin 86
35.5%
Common 33
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 7
 
5.7%
스 6
 
4.9%
이 5
 
4.1%
라 5
 
4.1%
리 4
 
3.3%
어 3
 
2.4%
슈 3
 
2.4%
크 2
 
1.6%
션 2
 
1.6%
시 2
 
1.6%
Other values (70) 84
68.3%
Latin
ValueCountFrequency (%)
M 6
 
7.0%
E 6
 
7.0%
S 5
 
5.8%
R 5
 
5.8%
O 5
 
5.8%
N 5
 
5.8%
F 4
 
4.7%
l 4
 
4.7%
A 4
 
4.7%
T 3
 
3.5%
Other values (25) 39
45.3%
Common
ValueCountFrequency (%)
15
45.5%
/ 10
30.3%
( 4
 
12.1%
) 4
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
50.8%
ASCII 119
49.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
 
12.6%
/ 10
 
8.4%
M 6
 
5.0%
E 6
 
5.0%
S 5
 
4.2%
R 5
 
4.2%
O 5
 
4.2%
N 5
 
4.2%
( 4
 
3.4%
) 4
 
3.4%
Other values (29) 54
45.4%
Hangul
ValueCountFrequency (%)
트 7
 
5.7%
스 6
 
4.9%
이 5
 
4.1%
라 5
 
4.1%
리 4
 
3.3%
어 3
 
2.4%
슈 3
 
2.4%
크 2
 
1.6%
션 2
 
1.6%
시 2
 
1.6%
Other values (70) 84
68.3%

취급품목
Text

Distinct19
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-04T03:48:45.004095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length15.928571
Min length3

Characters and Unicode

Total characters446
Distinct characters64
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)46.4%

Sample

1st row식품, 건강식품, 화장품, 전자제품, 의류 및 신발 등
2nd row유튜브프리미엄 구독권
3rd row운동화 등.
4th row식품, 건강식품, 화장품, 의류 등.
5th row캐릭터 피규어. 키덜트 토이 등.
ValueCountFrequency (%)
등 25
19.7%
및 14
 
11.0%
잡화 11
 
8.7%
의류 9
 
7.1%
화장품 8
 
6.3%
식품 7
 
5.5%
운동화 6
 
4.7%
건강식품 5
 
3.9%
명품브랜드 4
 
3.1%
캐릭터 3
 
2.4%
Other values (21) 35
27.6%
2024-05-04T03:48:46.020901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
22.2%
, 29
 
6.5%
품 26
 
5.8%
화 25
 
5.6%
등 25
 
5.6%
. 19
 
4.3%
의 14
 
3.1%
식 14
 
3.1%
및 14
 
3.1%
류 14
 
3.1%
Other values (54) 167
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 299
67.0%
Space Separator 99
 
22.2%
Other Punctuation 48
 
10.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 26
 
8.7%
화 25
 
8.4%
등 25
 
8.4%
의 14
 
4.7%
식 14
 
4.7%
및 14
 
4.7%
류 14
 
4.7%
잡 11
 
3.7%
동 9
 
3.0%
운 8
 
2.7%
Other values (51) 139
46.5%
Other Punctuation
ValueCountFrequency (%)
, 29
60.4%
. 19
39.6%
Space Separator
ValueCountFrequency (%)
99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 299
67.0%
Common 147
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 26
 
8.7%
화 25
 
8.4%
등 25
 
8.4%
의 14
 
4.7%
식 14
 
4.7%
및 14
 
4.7%
류 14
 
4.7%
잡 11
 
3.7%
동 9
 
3.0%
운 8
 
2.7%
Other values (51) 139
46.5%
Common
ValueCountFrequency (%)
99
67.3%
, 29
 
19.7%
. 19
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 299
67.0%
ASCII 147
33.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
67.3%
, 29
 
19.7%
. 19
 
12.9%
Hangul
ValueCountFrequency (%)
품 26
 
8.7%
화 25
 
8.4%
등 25
 
8.4%
의 14
 
4.7%
식 14
 
4.7%
및 14
 
4.7%
류 14
 
4.7%
잡 11
 
3.7%
동 9
 
3.0%
운 8
 
2.7%
Other values (51) 139
46.5%

총 접수건/미처리건
Text

Distinct26
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
2024-05-04T03:48:46.492381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.7857143
Min length5

Characters and Unicode

Total characters162
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)89.3%

Sample

1st row517/81
2nd row114/109
3rd row14/12
4th row253/253
5th row51/12
ValueCountFrequency (%)
26/26 3
 
10.7%
517/81 1
 
3.6%
114/109 1
 
3.6%
72/57 1
 
3.6%
746/165 1
 
3.6%
394/251 1
 
3.6%
221/221 1
 
3.6%
165/100 1
 
3.6%
94/94 1
 
3.6%
90/82 1
 
3.6%
Other values (16) 16
57.1%
2024-05-04T03:48:47.739178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 28
17.3%
2 26
16.0%
1 22
13.6%
4 18
11.1%
5 13
8.0%
0 13
8.0%
6 11
 
6.8%
9 9
 
5.6%
3 8
 
4.9%
8 7
 
4.3%
Other values (2) 7
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 133
82.1%
Other Punctuation 29
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 26
19.5%
1 22
16.5%
4 18
13.5%
5 13
9.8%
0 13
9.8%
6 11
8.3%
9 9
 
6.8%
3 8
 
6.0%
8 7
 
5.3%
7 6
 
4.5%
Other Punctuation
ValueCountFrequency (%)
/ 28
96.6%
, 1
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Common 162
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 28
17.3%
2 26
16.0%
1 22
13.6%
4 18
11.1%
5 13
8.0%
0 13
8.0%
6 11
 
6.8%
9 9
 
5.6%
3 8
 
4.9%
8 7
 
4.3%
Other values (2) 7
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 162
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 28
17.3%
2 26
16.0%
1 22
13.6%
4 18
11.1%
5 13
8.0%
0 13
8.0%
6 11
 
6.8%
9 9
 
5.6%
3 8
 
4.9%
8 7
 
4.3%
Other values (2) 7
 
4.3%

Interactions

2024-05-04T03:48:40.511708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T03:48:48.076825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도연번쇼핑몰명취급품목총 접수건/미처리건
년도1.0000.8930.7290.7981.000
연번0.8931.0000.8490.7390.929
쇼핑몰명0.7290.8491.0001.0000.960
취급품목0.7980.7391.0001.0000.893
총 접수건/미처리건1.0000.9290.9600.8931.000
2024-05-04T03:48:48.347318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번년도
연번1.0000.712
년도0.7121.000

Missing values

2024-05-04T03:48:40.813038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T03:48:41.199636image/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

년도연번쇼핑몰명취급품목총 접수건/미처리건
02024557웁스(WHOOPS)식품, 건강식품, 화장품, 전자제품, 의류 및 신발 등517/81
12024558캐쉬메이커유튜브프리미엄 구독권114/109
22023546슈즈오페라운동화 등.14/12
32023545맘앤마트 / MOMNMART식품, 건강식품, 화장품, 의류 등.253/253
42023548피규어세상 / Figure Sesang캐릭터 피규어. 키덜트 토이 등.51/12
52023549에스디컬렉션 /SD컬렉션해외 명품브랜드 의류 및 잡화 등58/35
62023556리빙꿀템여성 가방 및 잡화 등.20/20
72023551시크헤라여성의류, 잡화, 식품 등75/40
82023552이엔지샵 / ENZ샵 / ENZ SHOP해외 명품브랜드 의류 및 잡화 등.108/108
92023555센트베리/SCENTVERY운동화 등.29/28
년도연번쇼핑몰명취급품목총 접수건/미처리건
182022537오시싸화장품, 여성의류 및 잡화, 신발 등90/82
192022542뷰티히어로화장품, 건강보조식품, 식품 등.94/94
202022543싹딜식품, 건강식품, 화장품, 전자기기 및 의류 등.165/100
212022544맘앤마트 / MOMNMART식품, 건강식품, 화장품, 의류 등.221/221
222022540트렌디슈즈운동화26/26
232022539애슬리트운동복, 요가복, 스포츠레깅스 등.394/251
242022538스타일브이식품, 건강식품, 화장품, 전자기기 및 의류 등.746/165
252022541슈스톱운동화 등.26/26
262022535피규어바이/ FIGURE BUY캐릭터 피규어. 키덜트 토이 등.72/57
272022536더키월드캐릭터 문구 및 식기, 키덜트토이 및 잡화 등.1,040/39