Overview

Dataset statistics

Number of variables12
Number of observations75
Missing cells25
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory100.8 B

Variable types

Numeric1
Categorical5
Text5
DateTime1

Dataset

Description부산관광공사_기업지원센터_입주기업현황_20220520
Author부산관광공사
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15100392

Alerts

순번 is highly overall correlated with 입주연도 and 1 other fieldsHigh correlation
입주연도 is highly overall correlated with 순번High correlation
모집분야 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
현입주공간 is highly overall correlated with 모집분야High correlation
법인번호 is highly imbalanced (52.5%)Imbalance
호실 has 7 (9.3%) missing valuesMissing
사업자번호 has 8 (10.7%) missing valuesMissing
개업연월일 has 10 (13.3%) missing valuesMissing
순번 has unique valuesUnique
기업명 has unique valuesUnique
대표 has unique valuesUnique
사업내용 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:35:19.746469
Analysis finished2023-12-10 16:35:21.665419
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.866667
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T01:35:21.772133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.7
Q120.5
median39
Q357.5
95-th percentile72.6
Maximum77
Range76
Interquartile range (IQR)37

Descriptive statistics

Standard deviation22.149573
Coefficient of variation (CV)0.56988611
Kurtosis-1.1687794
Mean38.866667
Median Absolute Deviation (MAD)19
Skewness-0.014000389
Sum2915
Variance490.6036
MonotonicityStrictly increasing
2023-12-11T01:35:22.005671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%

입주연도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023
31 
2021
23 
2022
21 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2023 31
41.3%
2021 23
30.7%
2022 21
28.0%

Length

2023-12-11T01:35:22.198767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:35:22.352444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 31
41.3%
2021 23
30.7%
2022 21
28.0%

모집분야
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
초기관광스타트업
34 
예비관광스타트업
13 
성장관광스타트업
9 
예비관광 스타트업
9 
비상주협력기업
5 
Other values (4)
5 

Length

Max length10
Median length8
Mean length8.1066667
Min length7

Unique

Unique3 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
초기관광스타트업 34
45.3%
예비관광스타트업 13
 
17.3%
성장관광스타트업 9
 
12.0%
예비관광 스타트업 9
 
12.0%
비상주협력기업 5
 
6.7%
지역상생스타트업 2
 
2.7%
지역상생관광스타트업 1
 
1.3%
초기관광 스타트업 1
 
1.3%
지역상생 스타트업 1
 
1.3%

Length

2023-12-11T01:35:22.561478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:35:22.752874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초기관광스타트업 34
39.5%
예비관광스타트업 13
 
15.1%
스타트업 11
 
12.8%
성장관광스타트업 9
 
10.5%
예비관광 9
 
10.5%
비상주협력기업 5
 
5.8%
지역상생스타트업 2
 
2.3%
지역상생관광스타트업 1
 
1.2%
초기관광 1
 
1.2%
지역상생 1
 
1.2%

기업명
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-11T01:35:23.117366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length14
Mean length7.7066667
Min length2

Characters and Unicode

Total characters578
Distinct characters207
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)100.0%

Sample

1st row넥솔루션(NEXOLUTION)명소 P.D.M
2nd row윤미당lab
3rd row모티브빌리지
4th row비튼즈(beatnz)
5th row로쿠
ValueCountFrequency (%)
주식회사 15
 
14.3%
2
 
1.9%
넥솔루션(nexolution)명소 1
 
1.0%
이야기보따리 1
 
1.0%
비바인사이트 1
 
1.0%
주)관광지포토서비스 1
 
1.0%
투어프린지 1
 
1.0%
부산프린지 1
 
1.0%
포부(pobu 1
 
1.0%
지식여행사 1
 
1.0%
Other values (80) 80
76.2%
2023-12-11T01:35:23.690010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
5.2%
주 24
 
4.2%
이 23
 
4.0%
사 21
 
3.6%
식 19
 
3.3%
스 18
 
3.1%
회 17
 
2.9%
) 14
 
2.4%
( 14
 
2.4%
트 9
 
1.6%
Other values (197) 389
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
82.2%
Space Separator 30
 
5.2%
Uppercase Letter 21
 
3.6%
Close Punctuation 14
 
2.4%
Open Punctuation 14
 
2.4%
Lowercase Letter 9
 
1.6%
Other Symbol 7
 
1.2%
Other Punctuation 3
 
0.5%
Decimal Number 3
 
0.5%
Math Symbol 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
 
5.1%
이 23
 
4.8%
사 21
 
4.4%
식 19
 
4.0%
스 18
 
3.8%
회 17
 
3.6%
트 9
 
1.9%
프 9
 
1.9%
리 8
 
1.7%
지 8
 
1.7%
Other values (166) 319
67.2%
Uppercase Letter
ValueCountFrequency (%)
O 3
14.3%
U 2
9.5%
L 2
9.5%
N 2
9.5%
B 2
9.5%
P 2
9.5%
M 1
 
4.8%
D 1
 
4.8%
I 1
 
4.8%
T 1
 
4.8%
Other values (4) 4
19.0%
Lowercase Letter
ValueCountFrequency (%)
a 2
22.2%
b 2
22.2%
l 1
11.1%
z 1
11.1%
n 1
11.1%
t 1
11.1%
e 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
5 1
33.3%
2 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Math Symbol
ValueCountFrequency (%)
> 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 482
83.4%
Common 66
 
11.4%
Latin 30
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
 
5.0%
이 23
 
4.8%
사 21
 
4.4%
식 19
 
3.9%
스 18
 
3.7%
회 17
 
3.5%
트 9
 
1.9%
프 9
 
1.9%
리 8
 
1.7%
지 8
 
1.7%
Other values (167) 326
67.6%
Latin
ValueCountFrequency (%)
O 3
 
10.0%
U 2
 
6.7%
L 2
 
6.7%
a 2
 
6.7%
N 2
 
6.7%
B 2
 
6.7%
b 2
 
6.7%
P 2
 
6.7%
l 1
 
3.3%
z 1
 
3.3%
Other values (11) 11
36.7%
Common
ValueCountFrequency (%)
30
45.5%
) 14
21.2%
( 14
21.2%
> 2
 
3.0%
. 2
 
3.0%
1 1
 
1.5%
5 1
 
1.5%
2 1
 
1.5%
& 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
82.2%
ASCII 96
 
16.6%
None 7
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
31.2%
) 14
14.6%
( 14
14.6%
O 3
 
3.1%
U 2
 
2.1%
L 2
 
2.1%
> 2
 
2.1%
a 2
 
2.1%
N 2
 
2.1%
B 2
 
2.1%
Other values (20) 23
24.0%
Hangul
ValueCountFrequency (%)
주 24
 
5.1%
이 23
 
4.8%
사 21
 
4.4%
식 19
 
4.0%
스 18
 
3.8%
회 17
 
3.6%
트 9
 
1.9%
프 9
 
1.9%
리 8
 
1.7%
지 8
 
1.7%
Other values (166) 319
67.2%
None
ValueCountFrequency (%)
㈜ 7
100.0%

대표
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-11T01:35:24.028630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.16
Min length2

Characters and Unicode

Total characters237
Distinct characters97
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

Unique75 ?
Unique (%)100.0%

Sample

1st row황진웅
2nd row윤희택
3rd row조기상
4th row김영진
5th row김태근
ValueCountFrequency (%)
황진웅 1
 
1.3%
강원석 1
 
1.3%
김유진 1
 
1.3%
신충기 1
 
1.3%
김부민 1
 
1.3%
최은정 1
 
1.3%
임영아 1
 
1.3%
오종희 1
 
1.3%
하은미 1
 
1.3%
최정 1
 
1.3%
Other values (68) 68
87.2%
2023-12-11T01:35:24.850965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 16
 
6.8%
정 13
 
5.5%
이 12
 
5.1%
진 8
 
3.4%
박 6
 
2.5%
은 6
 
2.5%
민 6
 
2.5%
영 6
 
2.5%
최 5
 
2.1%
형 5
 
2.1%
Other values (87) 154
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
97.9%
Space Separator 3
 
1.3%
Other Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 16
 
6.9%
정 13
 
5.6%
이 12
 
5.2%
진 8
 
3.4%
박 6
 
2.6%
은 6
 
2.6%
민 6
 
2.6%
영 6
 
2.6%
최 5
 
2.2%
형 5
 
2.2%
Other values (85) 149
64.2%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
97.9%
Common 5
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 16
 
6.9%
정 13
 
5.6%
이 12
 
5.2%
진 8
 
3.4%
박 6
 
2.6%
은 6
 
2.6%
민 6
 
2.6%
영 6
 
2.6%
최 5
 
2.2%
형 5
 
2.2%
Other values (85) 149
64.2%
Common
ValueCountFrequency (%)
3
60.0%
, 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
97.9%
ASCII 5
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 16
 
6.9%
정 13
 
5.6%
이 12
 
5.2%
진 8
 
3.4%
박 6
 
2.6%
은 6
 
2.6%
민 6
 
2.6%
영 6
 
2.6%
최 5
 
2.2%
형 5
 
2.2%
Other values (85) 149
64.2%
ASCII
ValueCountFrequency (%)
3
60.0%
, 2
40.0%

분류
Categorical

Distinct6
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
관광IT·플랫폼
21 
관광콘텐츠·여행상품
19 
관광기념품·캐릭터
17 
체험·테마관광
15 
SNS·마케팅
 
2

Length

Max length10
Median length9
Mean length8.4666667
Min length5

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row관광IT·플랫폼
2nd row관광콘텐츠·여행상품
3rd row관광기념품·캐릭터
4th row관광IT·플랫폼
5th row관광콘텐츠·여행상품

Common Values

ValueCountFrequency (%)
관광IT·플랫폼 21
28.0%
관광콘텐츠·여행상품 19
25.3%
관광기념품·캐릭터 17
22.7%
체험·테마관광 15
20.0%
SNS·마케팅 2
 
2.7%
해양·레저 1
 
1.3%

Length

2023-12-11T01:35:25.015920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:35:25.139591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광it·플랫폼 21
28.0%
관광콘텐츠·여행상품 19
25.3%
관광기념품·캐릭터 17
22.7%
체험·테마관광 15
20.0%
sns·마케팅 2
 
2.7%
해양·레저 1
 
1.3%

사업내용
Text

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-11T01:35:25.509978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length49
Mean length37.906667
Min length16

Characters and Unicode

Total characters2843
Distinct characters405
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)100.0%

Sample

1st row체험형 6차 산업과 관광 플랫폼 앱 개발과 분양 사업(쌍방향 커뮤니케이션 특허 개발) 운영
2nd row부산지역 문화와 전통 먹거리를 융합한 새로운 우리 쌀 가공제품 및 체험 교육형 관광 상품 개발
3rd row부산의 제철 로컬푸드를 활용하여 특색 있는 계절 별 반려동물 관광기념품 제조 및 유통
4th row한국에서 성형수술을 하고 싶다면? 뷰티브릿지앱을 이용하세요!
5th row부산의 특화골목 6개 지역을 중심으로 한 비즈니스 관점의 로컬투어 및 매거진 제작
ValueCountFrequency (%)
부산 16
 
2.3%
관광 14
 
2.0%
및 14
 
2.0%
개발 13
 
1.9%
플랫폼 13
 
1.9%
통한 10
 
1.4%
체험 9
 
1.3%
운영 8
 
1.2%
서비스 8
 
1.2%
부산의 7
 
1.0%
Other values (469) 579
83.8%
2023-12-11T01:35:26.051756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
618
 
21.7%
관 54
 
1.9%
광 52
 
1.8%
산 48
 
1.7%
한 42
 
1.5%
부 42
 
1.5%
이 40
 
1.4%
로 34
 
1.2%
스 34
 
1.2%
을 31
 
1.1%
Other values (395) 1848
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2086
73.4%
Space Separator 618
 
21.7%
Other Punctuation 55
 
1.9%
Uppercase Letter 43
 
1.5%
Close Punctuation 11
 
0.4%
Open Punctuation 11
 
0.4%
Decimal Number 7
 
0.2%
Math Symbol 4
 
0.1%
Lowercase Letter 3
 
0.1%
Final Punctuation 2
 
0.1%
Other values (2) 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 54
 
2.6%
광 52
 
2.5%
산 48
 
2.3%
한 42
 
2.0%
부 42
 
2.0%
이 40
 
1.9%
로 34
 
1.6%
스 34
 
1.6%
을 31
 
1.5%
기 30
 
1.4%
Other values (353) 1679
80.5%
Uppercase Letter
ValueCountFrequency (%)
I 9
20.9%
E 5
11.6%
R 3
 
7.0%
V 3
 
7.0%
D 2
 
4.7%
Y 2
 
4.7%
M 2
 
4.7%
C 2
 
4.7%
T 2
 
4.7%
O 2
 
4.7%
Other values (9) 11
25.6%
Other Punctuation
ValueCountFrequency (%)
, 21
38.2%
' 16
29.1%
/ 6
 
10.9%
" 4
 
7.3%
& 3
 
5.5%
· 3
 
5.5%
! 1
 
1.8%
? 1
 
1.8%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
2 2
28.6%
6 2
28.6%
3 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
e 1
33.3%
t 1
33.3%
Math Symbol
ValueCountFrequency (%)
> 2
50.0%
< 2
50.0%
Space Separator
ValueCountFrequency (%)
618
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2086
73.4%
Common 711
 
25.0%
Latin 46
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 54
 
2.6%
광 52
 
2.5%
산 48
 
2.3%
한 42
 
2.0%
부 42
 
2.0%
이 40
 
1.9%
로 34
 
1.6%
스 34
 
1.6%
을 31
 
1.5%
기 30
 
1.4%
Other values (353) 1679
80.5%
Latin
ValueCountFrequency (%)
I 9
19.6%
E 5
 
10.9%
R 3
 
6.5%
V 3
 
6.5%
D 2
 
4.3%
Y 2
 
4.3%
M 2
 
4.3%
C 2
 
4.3%
T 2
 
4.3%
O 2
 
4.3%
Other values (12) 14
30.4%
Common
ValueCountFrequency (%)
618
86.9%
, 21
 
3.0%
' 16
 
2.3%
) 11
 
1.5%
( 11
 
1.5%
/ 6
 
0.8%
" 4
 
0.6%
& 3
 
0.4%
· 3
 
0.4%
0 2
 
0.3%
Other values (10) 16
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2086
73.4%
ASCII 751
 
26.4%
None 3
 
0.1%
Punctuation 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
618
82.3%
, 21
 
2.8%
' 16
 
2.1%
) 11
 
1.5%
( 11
 
1.5%
I 9
 
1.2%
/ 6
 
0.8%
E 5
 
0.7%
" 4
 
0.5%
R 3
 
0.4%
Other values (29) 47
 
6.3%
Hangul
ValueCountFrequency (%)
관 54
 
2.6%
광 52
 
2.5%
산 48
 
2.3%
한 42
 
2.0%
부 42
 
2.0%
이 40
 
1.9%
로 34
 
1.6%
스 34
 
1.6%
을 31
 
1.5%
기 30
 
1.4%
Other values (353) 1679
80.5%
None
ValueCountFrequency (%)
· 3
100.0%
Punctuation
ValueCountFrequency (%)
’ 2
66.7%
‘ 1
33.3%

현입주공간
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
공유오피스
46 
<NA>
9 
비상주협력기업
9 
3인실
 
3
2인실
 
3
Other values (3)
5 

Length

Max length7
Median length5
Mean length4.8266667
Min length3

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row<NA>
2nd row공유오피스
3rd row공유오피스
4th row공유오피스
5th row비상주협력기업

Common Values

ValueCountFrequency (%)
공유오피스 46
61.3%
<NA> 9
 
12.0%
비상주협력기업 9
 
12.0%
3인실 3
 
4.0%
2인실 3
 
4.0%
6인실 2
 
2.7%
5인실 2
 
2.7%
4인실 1
 
1.3%

Length

2023-12-11T01:35:26.196435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:35:26.315774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공유오피스 46
61.3%
na 9
 
12.0%
비상주협력기업 9
 
12.0%
3인실 3
 
4.0%
2인실 3
 
4.0%
6인실 2
 
2.7%
5인실 2
 
2.7%
4인실 1
 
1.3%

호실
Text

MISSING 

Distinct67
Distinct (%)98.5%
Missing7
Missing (%)9.3%
Memory size732.0 B
2023-12-11T01:35:26.534788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.3970588
Min length1

Characters and Unicode

Total characters367
Distinct characters11
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

Unique66 ?
Unique (%)97.1%

Sample

1st row103
2nd row306-52
3rd row306-53
4th row306-91
5th row306-60
ValueCountFrequency (%)
2
 
2.9%
306-121 1
 
1.5%
103 1
 
1.5%
306-117 1
 
1.5%
306-120 1
 
1.5%
306-119 1
 
1.5%
309 1
 
1.5%
306-118 1
 
1.5%
308 1
 
1.5%
307 1
 
1.5%
Other values (57) 57
83.8%
2023-12-11T01:35:26.893174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 75
20.4%
3 67
18.3%
1 56
15.3%
6 55
15.0%
- 47
12.8%
2 26
 
7.1%
5 10
 
2.7%
8 8
 
2.2%
9 8
 
2.2%
4 8
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
87.2%
Dash Punctuation 47
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 75
23.4%
3 67
20.9%
1 56
17.5%
6 55
17.2%
2 26
 
8.1%
5 10
 
3.1%
8 8
 
2.5%
9 8
 
2.5%
4 8
 
2.5%
7 7
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 367
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 75
20.4%
3 67
18.3%
1 56
15.3%
6 55
15.0%
- 47
12.8%
2 26
 
7.1%
5 10
 
2.7%
8 8
 
2.2%
9 8
 
2.2%
4 8
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 75
20.4%
3 67
18.3%
1 56
15.3%
6 55
15.0%
- 47
12.8%
2 26
 
7.1%
5 10
 
2.7%
8 8
 
2.2%
9 8
 
2.2%
4 8
 
2.2%

사업자번호
Text

MISSING 

Distinct67
Distinct (%)100.0%
Missing8
Missing (%)10.7%
Memory size732.0 B
2023-12-11T01:35:27.136019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters804
Distinct characters11
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

Unique67 ?
Unique (%)100.0%

Sample

1st row364-30-01123
2nd row677-22-01233
3rd row583-48-00661
4th row159-19-01448
5th row597-23-01273
ValueCountFrequency (%)
322-87-01045 1
 
1.5%
520-81-02331 1
 
1.5%
226-81-52531 1
 
1.5%
719-86-02106 1
 
1.5%
766-81-02562 1
 
1.5%
647-69-00524 1
 
1.5%
732-81-01987 1
 
1.5%
696-43-01001 1
 
1.5%
240-86-00150 1
 
1.5%
677-22-01233 1
 
1.5%
Other values (57) 57
85.1%
2023-12-11T01:35:27.502336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 134
16.7%
0 117
14.6%
1 99
12.3%
2 82
10.2%
8 69
8.6%
6 62
7.7%
7 59
7.3%
3 53
 
6.6%
4 51
 
6.3%
5 43
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 670
83.3%
Dash Punctuation 134
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 117
17.5%
1 99
14.8%
2 82
12.2%
8 69
10.3%
6 62
9.3%
7 59
8.8%
3 53
7.9%
4 51
7.6%
5 43
 
6.4%
9 35
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 134
16.7%
0 117
14.6%
1 99
12.3%
2 82
10.2%
8 69
8.6%
6 62
7.7%
7 59
7.3%
3 53
 
6.6%
4 51
 
6.3%
5 43
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 134
16.7%
0 117
14.6%
1 99
12.3%
2 82
10.2%
8 69
8.6%
6 62
7.7%
7 59
7.3%
3 53
 
6.6%
4 51
 
6.3%
5 43
 
5.3%

법인번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
53 
1801110000000
17 
1101120000000
 
2
180111000000
 
1
2301110000000
 
1

Length

Max length13
Median length4
Mean length6.6266667
Min length4

Unique

Unique3 ?
Unique (%)4.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 53
70.7%
1801110000000 17
 
22.7%
1101120000000 2
 
2.7%
180111000000 1
 
1.3%
2301110000000 1
 
1.3%
1801510000000 1
 
1.3%

Length

2023-12-11T01:35:27.656886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:35:27.812228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
70.7%
1801110000000 17
 
22.7%
1101120000000 2
 
2.7%
180111000000 1
 
1.3%
2301110000000 1
 
1.3%
1801510000000 1
 
1.3%

개업연월일
Date

MISSING 

Distinct61
Distinct (%)93.8%
Missing10
Missing (%)13.3%
Memory size732.0 B
Minimum2009-04-22 00:00:00
Maximum2023-03-01 00:00:00
2023-12-11T01:35:28.023193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:35:28.289025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-11T01:35:21.010130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:35:28.406400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번입주연도모집분야기업명대표분류사업내용현입주공간호실사업자번호법인번호개업연월일
순번1.0000.9580.8221.0001.0000.4101.0000.5350.9481.0000.3200.894
입주연도0.9581.0000.7691.0001.0000.4831.0000.3751.0001.0000.0000.925
모집분야0.8220.7691.0001.0001.0000.2891.0000.7530.9651.0000.6060.986
기업명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
분류0.4100.4830.2891.0001.0001.0001.0000.0000.9581.0000.3080.990
사업내용1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
현입주공간0.5350.3750.7531.0001.0000.0001.0001.0001.0001.0000.0000.335
호실0.9481.0000.9651.0001.0000.9581.0001.0001.0001.0000.0000.990
사업자번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
법인번호0.3200.0000.6061.0001.0000.3081.0000.0000.0001.0001.0001.000
개업연월일0.8940.9250.9861.0001.0000.9901.0000.3350.9901.0001.0001.000
2023-12-11T01:35:28.561729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류입주연도법인번호현입주공간모집분야
분류1.0000.2210.2290.0000.139
입주연도0.2211.0000.0000.2610.452
법인번호0.2290.0001.0000.0000.440
현입주공간0.0000.2610.0001.0000.520
모집분야0.1390.4520.4400.5201.000
2023-12-11T01:35:28.688682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번입주연도모집분야분류현입주공간법인번호
순번1.0000.9090.5550.2190.2950.185
입주연도0.9091.0000.4520.2210.2610.000
모집분야0.5550.4521.0000.1390.5200.440
분류0.2190.2210.1391.0000.0000.229
현입주공간0.2950.2610.5200.0001.0000.000
법인번호0.1850.0000.4400.2290.0001.000

Missing values

2023-12-11T01:35:21.186302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:35:21.418921image/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.
2023-12-11T01:35:21.563853image/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

순번입주연도모집분야기업명대표분류사업내용현입주공간호실사업자번호법인번호개업연월일
012021예비관광스타트업넥솔루션(NEXOLUTION)명소 P.D.M황진웅관광IT·플랫폼체험형 6차 산업과 관광 플랫폼 앱 개발과 분양 사업(쌍방향 커뮤니케이션 특허 개발) 운영<NA>103364-30-01123<NA>2021-06-11
122021예비관광스타트업윤미당lab윤희택관광콘텐츠·여행상품부산지역 문화와 전통 먹거리를 융합한 새로운 우리 쌀 가공제품 및 체험 교육형 관광 상품 개발공유오피스306-52677-22-01233<NA>2021-07-26
232021예비관광스타트업모티브빌리지조기상관광기념품·캐릭터부산의 제철 로컬푸드를 활용하여 특색 있는 계절 별 반려동물 관광기념품 제조 및 유통공유오피스306-53583-48-00661<NA>2021-07-07
342021예비관광스타트업비튼즈(beatnz)김영진관광IT·플랫폼한국에서 성형수술을 하고 싶다면? 뷰티브릿지앱을 이용하세요!공유오피스306-91159-19-01448<NA>2021-06-08
452021예비관광스타트업로쿠김태근관광콘텐츠·여행상품부산의 특화골목 6개 지역을 중심으로 한 비즈니스 관점의 로컬투어 및 매거진 제작비상주협력기업<NA>597-23-01273<NA>2021-06-23
562021초기관광스타트업㈜손끝송정화관광콘텐츠·여행상품금정구 황산도길 걷기 콘텐츠와 친환경 밀랍 관광기념품 개발을 통한 융·복합 힐링콘텐츠 '소산역B' 운영공유오피스306-60524-85-01948<NA>2021-05-14
672021초기관광스타트업주식회사 링크오브투데이박성훈관광IT·플랫폼관광콘테스트를 열어 리워드를 제공하는 O2O기반 플랫폼 제작<NA>302852-88-01674<NA>2020-05-22
782021초기관광스타트업주식회사 이중섭문화마을원성보체험·테마관광이중섭마을 스토리텔링'을 주제로 한 동구 이바구길 관광아트체험 투어 운영<NA>205471-87-01560<NA>2019-04-12
892021초기관광스타트업주식회사 더블유엘씨허남연체험·테마관광부산에서 생산되는 먹거리(식자재)를 이용한 체험관광 '테이스트 부산' 운영공유오피스306-68322-87-01045<NA>2018-04-01
9102021초기관광스타트업주식회사 케즈 영도지점조원준관광IT·플랫폼스마트밴드를 통한 해양레포츠 이용객 안전관리 모니터링 시스템 운영<NA>206386-85-01763<NA>2021-06-11
순번입주연도모집분야기업명대표분류사업내용현입주공간호실사업자번호법인번호개업연월일
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