Overview

Dataset statistics

Number of variables5
Number of observations258
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory40.5 B

Variable types

Categorical2
Text2
DateTime1

Dataset

Description공주시 통신판매업, 방문판매업에 대한 현황정보 제공(판매형태, 법인또는상호, 소재지주소, 취급품목, 데이터 기준일 등)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=419&beforeMenuCd=DOM_000000201001001000&publicdatapk=3084532

Alerts

데이터 기준일 has constant value ""Constant
판매형태 is highly overall correlated with 취급품목High correlation
취급품목 is highly overall correlated with 판매형태High correlation

Reproduction

Analysis started2024-01-09 20:28:57.744860
Analysis finished2024-01-09 20:28:58.259195
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

판매형태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
통신판매업
219 
방문판매업
39 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
통신판매업 219
84.9%
방문판매업 39
 
15.1%

Length

2024-01-10T05:28:58.315099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:28:58.426083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통신판매업 219
84.9%
방문판매업 39
 
15.1%

법인또는상호
Text

Distinct257
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-10T05:28:58.616398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length18
Mean length7.2170543
Min length1

Characters and Unicode

Total characters1862
Distinct characters427
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

Unique256 ?
Unique (%)99.2%

Sample

1st row디어달링
2nd row배드민턴 창고
3rd row라보로(Lavoro)
4th row어진무역
5th row용배랜드
ValueCountFrequency (%)
주식회사 24
 
6.8%
농업회사법인 7
 
2.0%
공주대리점 3
 
0.8%
농원 3
 
0.8%
계룡산 2
 
0.6%
블루노트 2
 
0.6%
공주점 2
 
0.6%
네이처컬렉션 2
 
0.6%
공주신관점 2
 
0.6%
공주 2
 
0.6%
Other values (304) 306
86.2%
2024-01-10T05:28:58.955034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
5.2%
주 63
 
3.4%
이 50
 
2.7%
사 47
 
2.5%
회 38
 
2.0%
) 36
 
1.9%
( 36
 
1.9%
리 32
 
1.7%
스 32
 
1.7%
식 30
 
1.6%
Other values (417) 1401
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1488
79.9%
Lowercase Letter 118
 
6.3%
Space Separator 97
 
5.2%
Uppercase Letter 76
 
4.1%
Close Punctuation 36
 
1.9%
Open Punctuation 36
 
1.9%
Other Punctuation 4
 
0.2%
Decimal Number 4
 
0.2%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 63
 
4.2%
이 50
 
3.4%
사 47
 
3.2%
회 38
 
2.6%
리 32
 
2.2%
스 32
 
2.2%
식 30
 
2.0%
공 29
 
1.9%
농 27
 
1.8%
니 16
 
1.1%
Other values (366) 1124
75.5%
Lowercase Letter
ValueCountFrequency (%)
a 16
13.6%
o 14
11.9%
e 13
11.0%
r 10
 
8.5%
n 7
 
5.9%
t 7
 
5.9%
m 6
 
5.1%
u 5
 
4.2%
i 5
 
4.2%
s 5
 
4.2%
Other values (11) 30
25.4%
Uppercase Letter
ValueCountFrequency (%)
O 8
 
10.5%
E 7
 
9.2%
A 7
 
9.2%
D 4
 
5.3%
G 4
 
5.3%
L 4
 
5.3%
I 4
 
5.3%
T 4
 
5.3%
S 4
 
5.3%
M 4
 
5.3%
Other values (11) 26
34.2%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 1
25.0%
9 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
@ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1488
79.9%
Latin 194
 
10.4%
Common 180
 
9.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 63
 
4.2%
이 50
 
3.4%
사 47
 
3.2%
회 38
 
2.6%
리 32
 
2.2%
스 32
 
2.2%
식 30
 
2.0%
공 29
 
1.9%
농 27
 
1.8%
니 16
 
1.1%
Other values (366) 1124
75.5%
Latin
ValueCountFrequency (%)
a 16
 
8.2%
o 14
 
7.2%
e 13
 
6.7%
r 10
 
5.2%
O 8
 
4.1%
n 7
 
3.6%
E 7
 
3.6%
A 7
 
3.6%
t 7
 
3.6%
m 6
 
3.1%
Other values (32) 99
51.0%
Common
ValueCountFrequency (%)
97
53.9%
) 36
 
20.0%
( 36
 
20.0%
- 3
 
1.7%
. 3
 
1.7%
1 2
 
1.1%
2 1
 
0.6%
9 1
 
0.6%
@ 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1488
79.9%
ASCII 374
 
20.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
25.9%
) 36
 
9.6%
( 36
 
9.6%
a 16
 
4.3%
o 14
 
3.7%
e 13
 
3.5%
r 10
 
2.7%
O 8
 
2.1%
n 7
 
1.9%
E 7
 
1.9%
Other values (41) 130
34.8%
Hangul
ValueCountFrequency (%)
주 63
 
4.2%
이 50
 
3.4%
사 47
 
3.2%
회 38
 
2.6%
리 32
 
2.2%
스 32
 
2.2%
식 30
 
2.0%
공 29
 
1.9%
농 27
 
1.8%
니 16
 
1.1%
Other values (366) 1124
75.5%

소재지주소
Text

Distinct255
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-01-10T05:28:59.182703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length45
Mean length28.182171
Min length16

Characters and Unicode

Total characters7271
Distinct characters239
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)97.7%

Sample

1st row충청남도 공주시 의당면 연수원길 116， 202동 209호 (신한2차아파트)
2nd row충청남도 공주시 무령로 214 (중동)
3rd row충청남도 공주시 신금1길 72， 304동 1205호 (신관동， 새뜸현대3차아파트)
4th row충청남도 공주시 봉황산1길 46 (봉황동)
5th row충청남도 공주시 계룡면 차령로 824
ValueCountFrequency (%)
충청남도 258
 
16.9%
공주시 258
 
16.9%
신관동 33
 
2.2%
신관동， 24
 
1.6%
반포면 18
 
1.2%
무령로 17
 
1.1%
1층 16
 
1.0%
2층 15
 
1.0%
유구읍 14
 
0.9%
신풍면 13
 
0.9%
Other values (516) 860
56.4%
2024-01-10T05:28:59.537787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1268
 
17.4%
1 328
 
4.5%
공 285
 
3.9%
주 280
 
3.9%
청 269
 
3.7%
남 263
 
3.6%
시 262
 
3.6%
충 259
 
3.6%
도 258
 
3.5%
동 229
 
3.1%
Other values (229) 3570
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4147
57.0%
Decimal Number 1270
 
17.5%
Space Separator 1268
 
17.4%
Other Punctuation 156
 
2.1%
Close Punctuation 155
 
2.1%
Open Punctuation 155
 
2.1%
Dash Punctuation 116
 
1.6%
Uppercase Letter 3
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 285
 
6.9%
주 280
 
6.8%
청 269
 
6.5%
남 263
 
6.3%
시 262
 
6.3%
충 259
 
6.2%
도 258
 
6.2%
동 229
 
5.5%
길 166
 
4.0%
신 103
 
2.5%
Other values (211) 1773
42.8%
Decimal Number
ValueCountFrequency (%)
1 328
25.8%
2 200
15.7%
0 160
12.6%
3 156
12.3%
4 95
 
7.5%
5 78
 
6.1%
7 76
 
6.0%
9 66
 
5.2%
6 62
 
4.9%
8 49
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
1268
100.0%
Other Punctuation
ValueCountFrequency (%)
， 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4147
57.0%
Common 3120
42.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 285
 
6.9%
주 280
 
6.8%
청 269
 
6.5%
남 263
 
6.3%
시 262
 
6.3%
충 259
 
6.2%
도 258
 
6.2%
동 229
 
5.5%
길 166
 
4.0%
신 103
 
2.5%
Other values (211) 1773
42.8%
Common
ValueCountFrequency (%)
1268
40.6%
1 328
 
10.5%
2 200
 
6.4%
0 160
 
5.1%
3 156
 
5.0%
， 156
 
5.0%
) 155
 
5.0%
( 155
 
5.0%
- 116
 
3.7%
4 95
 
3.0%
Other values (5) 331
 
10.6%
Latin
ValueCountFrequency (%)
B 2
50.0%
A 1
25.0%
b 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4147
57.0%
ASCII 2968
40.8%
None 156
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1268
42.7%
1 328
 
11.1%
2 200
 
6.7%
0 160
 
5.4%
3 156
 
5.3%
) 155
 
5.2%
( 155
 
5.2%
- 116
 
3.9%
4 95
 
3.2%
5 78
 
2.6%
Other values (7) 257
 
8.7%
Hangul
ValueCountFrequency (%)
공 285
 
6.9%
주 280
 
6.8%
청 269
 
6.5%
남 263
 
6.3%
시 262
 
6.3%
충 259
 
6.2%
도 258
 
6.2%
동 229
 
5.5%
길 166
 
4.0%
신 103
 
2.5%
Other values (211) 1773
42.8%
None
ValueCountFrequency (%)
， 156
100.0%

취급품목
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
기타
52 
종합몰
50 
건강/식품
36 
의류/패션/잡화/뷰티
30 
건강식품
10 
Other values (43)
80 

Length

Max length62
Median length47
Mean length7.6666667
Min length1

Unique

Unique31 ?
Unique (%)12.0%

Sample

1st row의류/패션/잡화/뷰티
2nd row의류/패션/잡화/뷰티
3rd row의류/패션/잡화/뷰티
4th row종합몰
5th row종합몰

Common Values

ValueCountFrequency (%)
기타 52
20.2%
종합몰 50
19.4%
건강/식품 36
14.0%
의류/패션/잡화/뷰티 30
11.6%
건강식품 10
 
3.9%
자동차/자동차용품 8
 
3.1%
건강/식품 기타 8
 
3.1%
교육/도서/완구/오락 6
 
2.3%
종합몰 건강/식품 5
 
1.9%
레져/여행/공연 5
 
1.9%
Other values (38) 48
18.6%

Length

2024-01-10T05:28:59.675976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 78
21.9%
종합몰 71
19.9%
건강/식품 58
16.3%
의류/패션/잡화/뷰티 46
12.9%
건강식품 20
 
5.6%
교육/도서/완구/오락 15
 
4.2%
자동차/자동차용품 11
 
3.1%
화장품/미용용품 11
 
3.1%
가구/수납용품 10
 
2.8%
가전 10
 
2.8%
Other values (6) 26
 
7.3%

데이터 기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2020-09-07 00:00:00
Maximum2020-09-07 00:00:00
2024-01-10T05:28:59.772684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:28:59.847821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-01-10T05:28:59.908437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매형태취급품목
판매형태1.0000.938
취급품목0.9381.000
2024-01-10T05:28:59.977264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매형태취급품목
판매형태1.0000.747
취급품목0.7471.000
2024-01-10T05:29:00.051654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매형태취급품목
판매형태1.0000.747
취급품목0.7471.000

Missing values

2024-01-10T05:28:58.150835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:28:58.227206image/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

판매형태법인또는상호소재지주소취급품목데이터 기준일
0통신판매업디어달링충청남도 공주시 의당면 연수원길 116， 202동 209호 (신한2차아파트)의류/패션/잡화/뷰티2020-09-07
1통신판매업배드민턴 창고충청남도 공주시 무령로 214 (중동)의류/패션/잡화/뷰티2020-09-07
2통신판매업라보로(Lavoro)충청남도 공주시 신금1길 72， 304동 1205호 (신관동， 새뜸현대3차아파트)의류/패션/잡화/뷰티2020-09-07
3통신판매업어진무역충청남도 공주시 봉황산1길 46 (봉황동)종합몰2020-09-07
4통신판매업용배랜드충청남도 공주시 계룡면 차령로 824종합몰2020-09-07
5통신판매업마우리충청남도 공주시 무령로 599-40， 201동 2005호 (금흥동， 공주월송 흥화하브)기타2020-09-07
6통신판매업다 야 솔 뜰안충청남도 공주시 우성면 보흥2길 15-19기타2020-09-07
7통신판매업호스텔정중동충청남도 공주시 웅진로 145-9 (중동)종합몰2020-09-07
8통신판매업(주)해냄충청남도 공주시 동현동 463기타2020-09-07
9통신판매업주식회사 짐핏충청남도 공주시 신관로 69-11， 대동프라자 상가동 1층 106호 (신관동)종합몰2020-09-07
판매형태법인또는상호소재지주소취급품목데이터 기준일
248방문판매업한국야쿠르트 공주점충청남도 공주시 봉황로 129 (교동)건강식품2020-09-07
249방문판매업르노삼성자동차 공주대리점충청남도 공주시 관골1길 34-11 (신관동)자동차/자동차용품2020-09-07
250방문판매업쉐보레 공주대리점충청남도 공주시 무령로 330 (옥룡동)자동차/자동차용품2020-09-07
251방문판매업코웨이 주식회사충청남도 공주시 유구읍 유구마곡사로 136-23가전 화장품/미용용품2020-09-07
252방문판매업공주양잠농업협동조합충청남도 공주시 장척로 124-1 (송선동)건강식품2020-09-07
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