Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells811
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

Numeric1
Text3
DateTime1

Dataset

Description대전광역시 서구 통신판매업 등록현황(순번, 대표자명, 법인 또 는상호, 취급품목, 데이터기준일자) 입니다. 취급품목 종류는 교육, 도서, 완구, 컴퓨터, 사무용품, 건강, 식품, 의류, 패션 등입니다.
URLhttps://www.data.go.kr/data/15113172/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
취급품목 has 810 (8.1%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:00:29.674433
Analysis finished2023-12-12 13:00:31.116644
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6244.887
Minimum1
Maximum12564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:00:31.211884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile631.95
Q13108.5
median6240
Q39372.25
95-th percentile11910.05
Maximum12564
Range12563
Interquartile range (IQR)6263.75

Descriptive statistics

Standard deviation3616.6033
Coefficient of variation (CV)0.57913031
Kurtosis-1.1972293
Mean6244.887
Median Absolute Deviation (MAD)3132.5
Skewness0.0099538527
Sum62448870
Variance13079820
MonotonicityNot monotonic
2023-12-12T22:00:31.395979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12342 1
 
< 0.1%
9823 1
 
< 0.1%
1923 1
 
< 0.1%
10059 1
 
< 0.1%
3628 1
 
< 0.1%
1714 1
 
< 0.1%
9651 1
 
< 0.1%
1405 1
 
< 0.1%
10824 1
 
< 0.1%
7530 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
ValueCountFrequency (%)
12564 1
< 0.1%
12563 1
< 0.1%
12562 1
< 0.1%
12561 1
< 0.1%
12560 1
< 0.1%
12559 1
< 0.1%
12558 1
< 0.1%
12556 1
< 0.1%
12555 1
< 0.1%
12554 1
< 0.1%
Distinct300
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:00:31.683743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length3
Mean length3.0953
Min length1

Characters and Unicode

Total characters30953
Distinct characters148
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)1.6%

Sample

1st row이**
2nd row송**
3rd row최**
4th row오**
5th row김**
ValueCountFrequency (%)
2090
20.7%
1536
15.2%
840
 
8.3%
413
 
4.1%
406
 
4.0%
306
 
3.0%
242
 
2.4%
232
 
2.3%
222
 
2.2%
217
 
2.1%
Other values (235) 3605
35.7%
2023-12-12T22:00:32.142006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 20283
65.5%
2154
 
7.0%
1578
 
5.1%
869
 
2.8%
430
 
1.4%
411
 
1.3%
311
 
1.0%
249
 
0.8%
233
 
0.8%
226
 
0.7%
Other values (138) 4209
 
13.6%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 20417
66.0%
Other Letter 10189
32.9%
Uppercase Letter 177
 
0.6%
Space Separator 110
 
0.4%
Decimal Number 40
 
0.1%
Lowercase Letter 14
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2154
21.1%
1578
15.5%
869
 
8.5%
430
 
4.2%
411
 
4.0%
311
 
3.1%
249
 
2.4%
233
 
2.3%
226
 
2.2%
225
 
2.2%
Other values (98) 3503
34.4%
Uppercase Letter
ValueCountFrequency (%)
H 19
 
10.7%
A 19
 
10.7%
N 18
 
10.2%
I 16
 
9.0%
G 11
 
6.2%
E 11
 
6.2%
U 9
 
5.1%
R 8
 
4.5%
L 8
 
4.5%
O 7
 
4.0%
Other values (14) 51
28.8%
Lowercase Letter
ValueCountFrequency (%)
e 3
21.4%
i 2
14.3%
h 2
14.3%
o 2
14.3%
l 2
14.3%
n 1
 
7.1%
y 1
 
7.1%
c 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 38
95.0%
3 1
 
2.5%
2 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
* 20283
99.3%
134
 
0.7%
Space Separator
ValueCountFrequency (%)
110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20573
66.5%
Hangul 10189
32.9%
Latin 191
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2154
21.1%
1578
15.5%
869
 
8.5%
430
 
4.2%
411
 
4.0%
311
 
3.1%
249
 
2.4%
233
 
2.3%
226
 
2.2%
225
 
2.2%
Other values (98) 3503
34.4%
Latin
ValueCountFrequency (%)
H 19
 
9.9%
A 19
 
9.9%
N 18
 
9.4%
I 16
 
8.4%
G 11
 
5.8%
E 11
 
5.8%
U 9
 
4.7%
R 8
 
4.2%
L 8
 
4.2%
O 7
 
3.7%
Other values (22) 65
34.0%
Common
ValueCountFrequency (%)
* 20283
98.6%
134
 
0.7%
110
 
0.5%
1 38
 
0.2%
) 3
 
< 0.1%
( 3
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20630
66.6%
Hangul 10189
32.9%
None 134
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 20283
98.3%
110
 
0.5%
1 38
 
0.2%
H 19
 
0.1%
A 19
 
0.1%
N 18
 
0.1%
I 16
 
0.1%
G 11
 
0.1%
E 11
 
0.1%
U 9
 
< 0.1%
Other values (29) 96
 
0.5%
Hangul
ValueCountFrequency (%)
2154
21.1%
1578
15.5%
869
 
8.5%
430
 
4.2%
411
 
4.0%
311
 
3.1%
249
 
2.4%
233
 
2.3%
226
 
2.2%
225
 
2.2%
Other values (98) 3503
34.4%
None
ValueCountFrequency (%)
134
100.0%
Distinct9808
Distinct (%)98.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T22:00:32.599924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length6.549855
Min length1

Characters and Unicode

Total characters65492
Distinct characters1120
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9635 ?
Unique (%)96.4%

Sample

1st row에스컴
2nd row별에별미
3rd row주식회사 시즌그룹
4th row에스에이치
5th row라이프큐
ValueCountFrequency (%)
주식회사 615
 
4.9%
58
 
0.5%
유한회사 29
 
0.2%
company 24
 
0.2%
20
 
0.2%
컴퍼니 20
 
0.2%
korea 19
 
0.2%
대전점 16
 
0.1%
스토어 16
 
0.1%
농업회사법인 14
 
0.1%
Other values (10865) 11810
93.4%
2023-12-12T22:00:33.247595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2674
 
4.1%
2226
 
3.4%
1869
 
2.9%
) 1569
 
2.4%
( 1565
 
2.4%
1147
 
1.8%
1114
 
1.7%
1076
 
1.6%
835
 
1.3%
752
 
1.1%
Other values (1110) 50665
77.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48994
74.8%
Lowercase Letter 5584
 
8.5%
Uppercase Letter 4192
 
6.4%
Space Separator 2674
 
4.1%
Close Punctuation 1569
 
2.4%
Open Punctuation 1565
 
2.4%
Decimal Number 463
 
0.7%
Other Punctuation 224
 
0.3%
Other Symbol 142
 
0.2%
Dash Punctuation 69
 
0.1%
Other values (4) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2226
 
4.5%
1869
 
3.8%
1147
 
2.3%
1114
 
2.3%
1076
 
2.2%
835
 
1.7%
752
 
1.5%
731
 
1.5%
622
 
1.3%
617
 
1.3%
Other values (1027) 38005
77.6%
Lowercase Letter
ValueCountFrequency (%)
e 660
11.8%
o 587
 
10.5%
a 511
 
9.2%
n 418
 
7.5%
i 395
 
7.1%
l 345
 
6.2%
r 307
 
5.5%
t 291
 
5.2%
s 254
 
4.5%
m 237
 
4.2%
Other values (16) 1579
28.3%
Uppercase Letter
ValueCountFrequency (%)
A 331
 
7.9%
O 313
 
7.5%
S 307
 
7.3%
E 265
 
6.3%
M 253
 
6.0%
L 233
 
5.6%
N 225
 
5.4%
T 221
 
5.3%
I 215
 
5.1%
C 209
 
5.0%
Other values (16) 1620
38.6%
Other Punctuation
ValueCountFrequency (%)
. 117
52.2%
& 66
29.5%
' 16
 
7.1%
: 9
 
4.0%
# 6
 
2.7%
/ 4
 
1.8%
· 2
 
0.9%
! 2
 
0.9%
@ 1
 
0.4%
% 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 109
23.5%
2 70
15.1%
4 52
11.2%
3 46
9.9%
0 46
9.9%
9 37
 
8.0%
7 33
 
7.1%
5 24
 
5.2%
8 24
 
5.2%
6 22
 
4.8%
Math Symbol
ValueCountFrequency (%)
> 1
33.3%
< 1
33.3%
+ 1
33.3%
Space Separator
ValueCountFrequency (%)
2674
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1569
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1565
100.0%
Other Symbol
ValueCountFrequency (%)
142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49119
75.0%
Latin 9776
 
14.9%
Common 6580
 
10.0%
Han 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2226
 
4.5%
1869
 
3.8%
1147
 
2.3%
1114
 
2.3%
1076
 
2.2%
835
 
1.7%
752
 
1.5%
731
 
1.5%
622
 
1.3%
617
 
1.3%
Other values (1015) 38130
77.6%
Latin
ValueCountFrequency (%)
e 660
 
6.8%
o 587
 
6.0%
a 511
 
5.2%
n 418
 
4.3%
i 395
 
4.0%
l 345
 
3.5%
A 331
 
3.4%
O 313
 
3.2%
r 307
 
3.1%
S 307
 
3.1%
Other values (42) 5602
57.3%
Common
ValueCountFrequency (%)
2674
40.6%
) 1569
23.8%
( 1565
23.8%
. 117
 
1.8%
1 109
 
1.7%
2 70
 
1.1%
- 69
 
1.0%
& 66
 
1.0%
4 52
 
0.8%
3 46
 
0.7%
Other values (20) 243
 
3.7%
Han
ValueCountFrequency (%)
3
17.6%
2
11.8%
2
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (3) 3
17.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48977
74.8%
ASCII 16353
 
25.0%
None 144
 
0.2%
CJK 16
 
< 0.1%
Punctuation 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2674
 
16.4%
) 1569
 
9.6%
( 1565
 
9.6%
e 660
 
4.0%
o 587
 
3.6%
a 511
 
3.1%
n 418
 
2.6%
i 395
 
2.4%
l 345
 
2.1%
A 331
 
2.0%
Other values (70) 7298
44.6%
Hangul
ValueCountFrequency (%)
2226
 
4.5%
1869
 
3.8%
1147
 
2.3%
1114
 
2.3%
1076
 
2.2%
835
 
1.7%
752
 
1.5%
731
 
1.5%
622
 
1.3%
617
 
1.3%
Other values (1014) 37988
77.6%
None
ValueCountFrequency (%)
142
98.6%
· 2
 
1.4%
CJK
ValueCountFrequency (%)
3
18.8%
2
12.5%
2
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (2) 2
12.5%
Punctuation
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

취급품목
Text

MISSING 

Distinct444
Distinct (%)4.8%
Missing810
Missing (%)8.1%
Memory size156.2 KiB
2023-12-12T22:00:33.465782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length87
Median length84
Mean length9.0971708
Min length2

Characters and Unicode

Total characters83603
Distinct characters50
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

Unique271 ?
Unique (%)2.9%

Sample

1st row건강/식품
2nd row기타
3rd row종합몰 가전
4th row종합몰
5th row교육/도서/완구/오락 컴퓨터/사무용품 의류/패션/잡화/뷰티 건강/식품
ValueCountFrequency (%)
의류/패션/잡화/뷰티 3576
28.2%
종합몰 2586
20.4%
기타 2216
17.5%
건강/식품 1313
 
10.4%
교육/도서/완구/오락 624
 
4.9%
컴퓨터/사무용품 609
 
4.8%
가전 490
 
3.9%
가구/수납용품 430
 
3.4%
레져/여행/공연 326
 
2.6%
자동차/자동차용품 323
 
2.6%
Other values (2) 173
 
1.4%
2023-12-12T22:00:33.864566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 15996
19.1%
3576
 
4.3%
3576
 
4.3%
3576
 
4.3%
3576
 
4.3%
3576
 
4.3%
3576
 
4.3%
3576
 
4.3%
3576
 
4.3%
3476
 
4.2%
Other values (40) 35523
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64131
76.7%
Other Punctuation 15996
 
19.1%
Space Separator 3476
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
2848
 
4.4%
2586
 
4.0%
Other values (38) 30089
46.9%
Other Punctuation
ValueCountFrequency (%)
/ 15996
100.0%
Space Separator
ValueCountFrequency (%)
3476
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64131
76.7%
Common 19472
 
23.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
2848
 
4.4%
2586
 
4.0%
Other values (38) 30089
46.9%
Common
ValueCountFrequency (%)
/ 15996
82.1%
3476
 
17.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64131
76.7%
ASCII 19472
 
23.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 15996
82.1%
3476
 
17.9%
Hangul
ValueCountFrequency (%)
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
3576
 
5.6%
2848
 
4.4%
2586
 
4.0%
Other values (38) 30089
46.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-09-13 00:00:00
Maximum2022-09-13 00:00:00
2023-12-12T22:00:34.291547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:00:34.415483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:00:30.673403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T22:00:30.810379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:00:30.946394image/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.
2023-12-12T22:00:31.058717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번대표자명법인또는상호취급품목데이터기준일자
1234112342이**에스컴<NA>2022-09-13
39203921송**별에별미건강/식품2022-09-13
24992500최**주식회사 시즌그룹기타2022-09-13
51075108오**에스에이치종합몰 가전2022-09-13
44324433김**라이프큐종합몰2022-09-13
54325433장**주식회사 위즈맥교육/도서/완구/오락 컴퓨터/사무용품 의류/패션/잡화/뷰티 건강/식품2022-09-13
26062607한**우리동네사진관대전둔산점종합몰2022-09-13
55185519유**(주)신세계렌트카산업기타2022-09-13
60086009곽**애경이네의류/패션/잡화/뷰티2022-09-13
89838984이**로사드 (LOSAD)기타2022-09-13
순번대표자명법인또는상호취급품목데이터기준일자
82508251김**원동C&B. Jwon Ent종합몰2022-09-13
1144811449김**동양가전마트가전2022-09-13
20652066이**싱글벙글상점종합몰2022-09-13
17191720이**주식회사 붐붐컴퍼니종합몰2022-09-13
66606661김**이유앤(eun)의류/패션/잡화/뷰티2022-09-13
61966197전**남북통일교육/도서/완구/오락 건강/식품 기타2022-09-13
27312732김**,전**BH유통종합몰2022-09-13
1095210953성**(주)아이티앤컴퓨터/사무용품2022-09-13
483484김**쇼로라팜스건강/식품2022-09-13
69056906김**에이치 시스템컴퓨터/사무용품 기타2022-09-13