Overview

Dataset statistics

Number of variables4
Number of observations142
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory33.9 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description전국 우수프랜차이즈 현황에 대한 데이터로 소상공인시장진흥공단에서 진행하는 우수 프랜차이즈 평가정보(선정년도, 브랜드명, 소재지주소, 취급품목)을 항목으로 제공합니다.
Author소상공인시장진흥공단
URLhttps://www.data.go.kr/data/3060388/fileData.do

Reproduction

Analysis started2023-12-12 16:12:45.236080
Analysis finished2023-12-12 16:12:45.789972
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

선정년도
Real number (ℝ)

Distinct6
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.1901
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T01:12:45.844072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2019
Q32020.75
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation1.6628315
Coefficient of variation (CV)0.00082351406
Kurtosis-1.1593721
Mean2019.1901
Median Absolute Deviation (MAD)1
Skewness0.14337047
Sum286725
Variance2.7650085
MonotonicityIncreasing
2023-12-13T01:12:45.952557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2017 33
23.2%
2019 29
20.4%
2020 25
17.6%
2021 21
14.8%
2018 19
13.4%
2022 15
10.6%
ValueCountFrequency (%)
2017 33
23.2%
2018 19
13.4%
2019 29
20.4%
2020 25
17.6%
2021 21
14.8%
2022 15
10.6%
ValueCountFrequency (%)
2022 15
10.6%
2021 21
14.8%
2020 25
17.6%
2019 29
20.4%
2018 19
13.4%
2017 33
23.2%

브랜드명
Text

Distinct74
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T01:12:46.224289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.2816901
Min length2

Characters and Unicode

Total characters750
Distinct characters189
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)26.1%

Sample

1st row혼자라고굶지마라!1인용
2nd row개미인력개발
3rd row곽두리쪽갈비
4th row깐깐한족발
5th row꼬지사께
ValueCountFrequency (%)
깐깐한족발 6
 
3.9%
에듀플렉스 6
 
3.9%
수유리우동집 6
 
3.9%
커피베이 5
 
3.3%
이차돌 4
 
2.6%
메가엠지씨커피 4
 
2.6%
유가네닭갈비 4
 
2.6%
바른치킨 4
 
2.6%
아소비 4
 
2.6%
얌샘김밥 4
 
2.6%
Other values (71) 105
69.1%
2023-12-13T01:12:46.669683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 28
 
3.7%
피 23
 
3.1%
스 17
 
2.3%
라 16
 
2.1%
리 16
 
2.1%
비 15
 
2.0%
커 15
 
2.0%
킨 13
 
1.7%
치 13
 
1.7%
가 12
 
1.6%
Other values (179) 582
77.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 704
93.9%
Decimal Number 16
 
2.1%
Lowercase Letter 12
 
1.6%
Space Separator 10
 
1.3%
Uppercase Letter 6
 
0.8%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 28
 
4.0%
피 23
 
3.3%
스 17
 
2.4%
라 16
 
2.3%
리 16
 
2.3%
비 15
 
2.1%
커 15
 
2.1%
킨 13
 
1.8%
치 13
 
1.8%
가 12
 
1.7%
Other values (162) 536
76.1%
Decimal Number
ValueCountFrequency (%)
3 4
25.0%
1 4
25.0%
9 3
18.8%
8 2
12.5%
2 2
12.5%
7 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
s 2
16.7%
v 2
16.7%
r 2
16.7%
c 2
16.7%
u 2
16.7%
Uppercase Letter
ValueCountFrequency (%)
M 2
33.3%
G 2
33.3%
C 2
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
! 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 704
93.9%
Common 28
 
3.7%
Latin 18
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 28
 
4.0%
피 23
 
3.3%
스 17
 
2.4%
라 16
 
2.3%
리 16
 
2.3%
비 15
 
2.1%
커 15
 
2.1%
킨 13
 
1.8%
치 13
 
1.8%
가 12
 
1.7%
Other values (162) 536
76.1%
Latin
ValueCountFrequency (%)
e 2
11.1%
s 2
11.1%
v 2
11.1%
r 2
11.1%
M 2
11.1%
G 2
11.1%
C 2
11.1%
c 2
11.1%
u 2
11.1%
Common
ValueCountFrequency (%)
10
35.7%
3 4
 
14.3%
1 4
 
14.3%
9 3
 
10.7%
! 2
 
7.1%
8 2
 
7.1%
2 2
 
7.1%
7 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 704
93.9%
ASCII 46
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 28
 
4.0%
피 23
 
3.3%
스 17
 
2.4%
라 16
 
2.3%
리 16
 
2.3%
비 15
 
2.1%
커 15
 
2.1%
킨 13
 
1.8%
치 13
 
1.8%
가 12
 
1.7%
Other values (162) 536
76.1%
ASCII
ValueCountFrequency (%)
10
21.7%
3 4
 
8.7%
1 4
 
8.7%
9 3
 
6.5%
! 2
 
4.3%
e 2
 
4.3%
s 2
 
4.3%
v 2
 
4.3%
8 2
 
4.3%
r 2
 
4.3%
Other values (7) 13
28.3%

소재지주소
Text

Distinct63
Distinct (%)44.7%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
2023-12-13T01:12:46.976597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length38
Mean length32.602837
Min length17

Characters and Unicode

Total characters4597
Distinct characters225
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

Unique24 ?
Unique (%)17.0%

Sample

1st row경기도 의정부시 시민로 19번길 22-10
2nd row충청남도 천안시 서북구 성거읍 성거길 186 개미빌딩 2층
3rd row경기도 용인시 기흥구 동백중앙로 199, 406호 (중동, 동백에이스프라자)
4th row광주광역시 광산구 첨단중앙로182번길 16-1 가동 201호(쌍암동)
5th row서울특별시 송파구 송파대로20길 10, 2층 (문정동)
ValueCountFrequency (%)
서울특별시 84
 
9.4%
금천구 18
 
2.0%
경기도 15
 
1.7%
10층 12
 
1.3%
광주광역시 10
 
1.1%
송파구 10
 
1.1%
마포구 9
 
1.0%
가산디지털1로 9
 
1.0%
강동구 8
 
0.9%
광산구 8
 
0.9%
Other values (284) 708
79.5%
2023-12-13T01:12:47.504353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
750
 
16.3%
1 201
 
4.4%
시 145
 
3.2%
구 133
 
2.9%
로 129
 
2.8%
동 127
 
2.8%
0 118
 
2.6%
서 112
 
2.4%
2 107
 
2.3%
, 102
 
2.2%
Other values (215) 2673
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2651
57.7%
Decimal Number 812
 
17.7%
Space Separator 750
 
16.3%
Other Punctuation 103
 
2.2%
Open Punctuation 90
 
2.0%
Close Punctuation 90
 
2.0%
Uppercase Letter 58
 
1.3%
Dash Punctuation 39
 
0.8%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 145
 
5.5%
구 133
 
5.0%
로 129
 
4.9%
동 127
 
4.8%
서 112
 
4.2%
울 84
 
3.2%
특 84
 
3.2%
별 84
 
3.2%
층 82
 
3.1%
호 58
 
2.2%
Other values (185) 1613
60.8%
Uppercase Letter
ValueCountFrequency (%)
B 11
19.0%
S 8
13.8%
X 6
10.3%
V 6
10.3%
T 6
10.3%
P 4
 
6.9%
C 4
 
6.9%
A 4
 
6.9%
H 3
 
5.2%
R 2
 
3.4%
Other values (3) 4
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 201
24.8%
0 118
14.5%
2 107
13.2%
3 75
 
9.2%
6 75
 
9.2%
4 54
 
6.7%
5 54
 
6.7%
7 52
 
6.4%
9 42
 
5.2%
8 34
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 102
99.0%
/ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
750
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2651
57.7%
Common 1888
41.1%
Latin 58
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 145
 
5.5%
구 133
 
5.0%
로 129
 
4.9%
동 127
 
4.8%
서 112
 
4.2%
울 84
 
3.2%
특 84
 
3.2%
별 84
 
3.2%
층 82
 
3.1%
호 58
 
2.2%
Other values (185) 1613
60.8%
Common
ValueCountFrequency (%)
750
39.7%
1 201
 
10.6%
0 118
 
6.2%
2 107
 
5.7%
, 102
 
5.4%
( 90
 
4.8%
) 90
 
4.8%
3 75
 
4.0%
6 75
 
4.0%
4 54
 
2.9%
Other values (7) 226
 
12.0%
Latin
ValueCountFrequency (%)
B 11
19.0%
S 8
13.8%
X 6
10.3%
V 6
10.3%
T 6
10.3%
P 4
 
6.9%
C 4
 
6.9%
A 4
 
6.9%
H 3
 
5.2%
R 2
 
3.4%
Other values (3) 4
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2651
57.7%
ASCII 1946
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
750
38.5%
1 201
 
10.3%
0 118
 
6.1%
2 107
 
5.5%
, 102
 
5.2%
( 90
 
4.6%
) 90
 
4.6%
3 75
 
3.9%
6 75
 
3.9%
4 54
 
2.8%
Other values (20) 284
 
14.6%
Hangul
ValueCountFrequency (%)
시 145
 
5.5%
구 133
 
5.0%
로 129
 
4.9%
동 127
 
4.8%
서 112
 
4.2%
울 84
 
3.2%
특 84
 
3.2%
별 84
 
3.2%
층 82
 
3.1%
호 58
 
2.2%
Other values (185) 1613
60.8%

취급품목
Categorical

Distinct42
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
커피
19 
치킨
15 
우동
 
7
족발
 
6
주점
 
6
Other values (37)
89 

Length

Max length15
Median length2
Mean length3.2183099
Min length1

Unique

Unique13 ?
Unique (%)9.2%

Sample

1st row갈비찜
2nd row기타 서비스
3rd row쪽갈비
4th row족발
5th row꼬지

Common Values

ValueCountFrequency (%)
커피 19
 
13.4%
치킨 15
 
10.6%
우동 7
 
4.9%
족발 6
 
4.2%
주점 6
 
4.2%
기타 교육 6
 
4.2%
김밥 6
 
4.2%
피자 6
 
4.2%
세탁 5
 
3.5%
닭갈비 4
 
2.8%
Other values (32) 62
43.7%

Length

2023-12-13T01:12:47.694023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피 19
 
11.0%
치킨 15
 
8.7%
교육 10
 
5.8%
우동 7
 
4.0%
기타 7
 
4.0%
족발 6
 
3.5%
주점 6
 
3.5%
김밥 6
 
3.5%
피자 6
 
3.5%
세탁 5
 
2.9%
Other values (40) 86
49.7%

Interactions

2023-12-13T01:12:45.536056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:12:47.802254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선정년도브랜드명소재지주소취급품목
선정년도1.0000.0000.0000.000
브랜드명0.0001.0001.0001.000
소재지주소0.0001.0001.0001.000
취급품목0.0001.0001.0001.000
2023-12-13T01:12:47.923057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
선정년도취급품목
선정년도1.0000.000
취급품목0.0001.000

Missing values

2023-12-13T01:12:45.656893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:12:45.755922image/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

선정년도브랜드명소재지주소취급품목
02017혼자라고굶지마라!1인용경기도 의정부시 시민로 19번길 22-10갈비찜
12017개미인력개발충청남도 천안시 서북구 성거읍 성거길 186 개미빌딩 2층기타 서비스
22017곽두리쪽갈비경기도 용인시 기흥구 동백중앙로 199, 406호 (중동, 동백에이스프라자)쪽갈비
32017깐깐한족발광주광역시 광산구 첨단중앙로182번길 16-1 가동 201호(쌍암동)족발
42017꼬지사께서울특별시 송파구 송파대로20길 10, 2층 (문정동)꼬지
52017덤인서울특별시 서초구 효령로 320 4, 5층인력 파견
62017도이첸<NA><NA>
72017땅땅치킨대구광역시 북구 검단북로2길 6 (산격동)치킨
82017회덮밥전문점인마루대전광역시 동구 안골로28번길 15-4 (구도동)회덮밥
92017맛깔참죽경기도 고양시 일산서구 덕이로 247, 3층 9(덕이동,블레스빌딩)죽
선정년도브랜드명소재지주소취급품목
1322022푸라닭 치킨서울특별시 강서구 양천로 376 7층, 8층, 9층치킨
1332022버거앤프라이즈인천광역시 연수구 송도미래로 30 에이동 1210호 (송도동, 송도 BRC스마트밸리 지식산업센터)햄버거
1342022아이세이버광주광역시 광산구 장신로 52 3층, 306,307호(장덕동,BYC 수완 비스타 오피스텔)안경
1352022메가엠지씨커피서울특별시 마포구 월드컵북로4길 81, 1층커피
1362022땅스부대찌개경기도 광명시 가학로 93 (가학동)부대찌개
1372022에듀플렉스서울특별시 금천구 가산디지털1로 128 STX-V 타워 10층 1006호기타 교육
1382022바른치킨서울특별시 강동구 양재대로89가길 34 5층, 성내동, 천지빌딩치킨
1392022얌샘김밥서울특별시 영등포구 영등포로 347(한독타워) 9, 10층김밥
1402022고돼지서울특별시 관악구 관천로 91, 4층삼겹살
1412022택이네조개전골경기 화성시 남양읍 주석로 116-6조개전골