Overview

Dataset statistics

Number of variables7
Number of observations49
Missing cells45
Missing cells (%)13.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory59.7 B

Variable types

Numeric1
Text5
Categorical1

Dataset

Description인천광역시 부평구 청년 창업 기업 현황 데이터는 기업명, 기업소개, 대표제품, 소재지 등에 대한 데이터를 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104164&srcSe=7661IVAWM27C61E190

Alerts

순번 is highly overall correlated with 분류High correlation
분류 is highly overall correlated with 순번High correlation
대표제품_서비스 has 1 (2.0%) missing valuesMissing
소재지 has 20 (40.8%) missing valuesMissing
연락처 has 24 (49.0%) missing valuesMissing
순번 has unique valuesUnique
기업명 has unique valuesUnique
기업소개 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:11:09.567612
Analysis finished2024-03-18 05:11:12.046208
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-03-18T14:11:12.122570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4
Q113
median25
Q337
95-th percentile46.6
Maximum49
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.57154761
Kurtosis-1.2
Mean25
Median Absolute Deviation (MAD)12
Skewness0
Sum1225
Variance204.16667
MonotonicityStrictly increasing
2024-03-18T14:11:12.249212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1
 
2.0%
38 1
 
2.0%
28 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%
40 1
2.0%

기업명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-18T14:11:12.457709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length4.6530612
Min length2

Characters and Unicode

Total characters228
Distinct characters139
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

Unique49 ?
Unique (%)100.0%

Sample

1st row월드킷
2nd row바니그라운드
3rd row듀킨
4th row에브리테이티팟
5th row모양스튜디오
ValueCountFrequency (%)
월드킷 1
 
1.9%
바니그라운드 1
 
1.9%
뉴타입컬쳐 1
 
1.9%
초이스위츠 1
 
1.9%
헤세드 1
 
1.9%
두유럽미 1
 
1.9%
낮잠과바람 1
 
1.9%
제이솔스튜디오 1
 
1.9%
왈왈식당 1
 
1.9%
디어도그 1
 
1.9%
Other values (42) 42
80.8%
2024-03-18T14:11:12.792890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 11
 
4.8%
이 8
 
3.5%
디 7
 
3.1%
오 6
 
2.6%
드 5
 
2.2%
로 4
 
1.8%
아 4
 
1.8%
리 4
 
1.8%
트 4
 
1.8%
튜 4
 
1.8%
Other values (129) 171
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 220
96.5%
Space Separator 3
 
1.3%
Decimal Number 2
 
0.9%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Uppercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 11
 
5.0%
이 8
 
3.6%
디 7
 
3.2%
오 6
 
2.7%
드 5
 
2.3%
로 4
 
1.8%
아 4
 
1.8%
리 4
 
1.8%
트 4
 
1.8%
튜 4
 
1.8%
Other values (124) 163
74.1%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
8 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 220
96.5%
Common 7
 
3.1%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 11
 
5.0%
이 8
 
3.6%
디 7
 
3.2%
오 6
 
2.7%
드 5
 
2.3%
로 4
 
1.8%
아 4
 
1.8%
리 4
 
1.8%
트 4
 
1.8%
튜 4
 
1.8%
Other values (124) 163
74.1%
Common
ValueCountFrequency (%)
3
42.9%
8 2
28.6%
) 1
 
14.3%
( 1
 
14.3%
Latin
ValueCountFrequency (%)
K 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 220
96.5%
ASCII 8
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 11
 
5.0%
이 8
 
3.6%
디 7
 
3.2%
오 6
 
2.7%
드 5
 
2.3%
로 4
 
1.8%
아 4
 
1.8%
리 4
 
1.8%
트 4
 
1.8%
튜 4
 
1.8%
Other values (124) 163
74.1%
ASCII
ValueCountFrequency (%)
3
37.5%
8 2
25.0%
) 1
 
12.5%
( 1
 
12.5%
K 1
 
12.5%

분류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size524.0 B
일반상품(온라인판매)
16 
취미공간, 카페
6 
교육,공방
5 
스튜디오
5 
사회적기여
5 
Other values (4)
12 

Length

Max length11
Median length10
Mean length7.4285714
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row일반상품(온라인판매)
2nd row일반상품(온라인판매)
3rd row일반상품(온라인판매)
4th row일반상품(온라인판매)
5th row일반상품(온라인판매)

Common Values

ValueCountFrequency (%)
일반상품(온라인판매) 16
32.7%
취미공간, 카페 6
 
12.2%
교육,공방 5
 
10.2%
스튜디오 5
 
10.2%
사회적기여 5
 
10.2%
반려동물 4
 
8.2%
디자인,영상,웹제작 4
 
8.2%
도서문화 3
 
6.1%
조경 1
 
2.0%

Length

2024-03-18T14:11:12.921983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:11:13.033634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반상품(온라인판매 16
29.1%
취미공간 6
 
10.9%
카페 6
 
10.9%
교육,공방 5
 
9.1%
스튜디오 5
 
9.1%
사회적기여 5
 
9.1%
반려동물 4
 
7.3%
디자인,영상,웹제작 4
 
7.3%
도서문화 3
 
5.5%
조경 1
 
1.8%

기업소개
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-03-18T14:11:13.301352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length13.244898
Min length6

Characters and Unicode

Total characters649
Distinct characters215
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

Unique49 ?
Unique (%)100.0%

Sample

1st row세계요리 밀키트 판매
2nd row놀이키트 제작소
3rd row디지털프린팅 제품제작 및 판매
4th row차(TEA)
5th row타일가구 맞춤제작, DIY키트 판매
ValueCountFrequency (%)
스튜디오 8
 
4.8%
제작 6
 
3.6%
판매 6
 
3.6%
및 6
 
3.6%
교육 4
 
2.4%
서비스 3
 
1.8%
밀키트 3
 
1.8%
반려동물 3
 
1.8%
플랫폼 3
 
1.8%
제품 3
 
1.8%
Other values (111) 120
72.7%
2024-03-18T14:11:13.679697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
17.9%
스 20
 
3.1%
제 19
 
2.9%
디 19
 
2.9%
트 12
 
1.8%
작 11
 
1.7%
이 10
 
1.5%
튜 9
 
1.4%
오 9
 
1.4%
매 8
 
1.2%
Other values (205) 416
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 502
77.3%
Space Separator 116
 
17.9%
Uppercase Letter 12
 
1.8%
Other Punctuation 8
 
1.2%
Lowercase Letter 6
 
0.9%
Dash Punctuation 3
 
0.5%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 20
 
4.0%
제 19
 
3.8%
디 19
 
3.8%
트 12
 
2.4%
작 11
 
2.2%
이 10
 
2.0%
튜 9
 
1.8%
오 9
 
1.8%
매 8
 
1.6%
판 7
 
1.4%
Other values (183) 378
75.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
25.0%
C 1
 
8.3%
Y 1
 
8.3%
I 1
 
8.3%
D 1
 
8.3%
A 1
 
8.3%
E 1
 
8.3%
T 1
 
8.3%
Z 1
 
8.3%
M 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
u 2
33.3%
l 1
16.7%
t 1
16.7%
r 1
16.7%
e 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 5
62.5%
& 2
 
25.0%
· 1
 
12.5%
Space Separator
ValueCountFrequency (%)
116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
77.3%
Common 129
 
19.9%
Latin 18
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 20
 
4.0%
제 19
 
3.8%
디 19
 
3.8%
트 12
 
2.4%
작 11
 
2.2%
이 10
 
2.0%
튜 9
 
1.8%
오 9
 
1.8%
매 8
 
1.6%
판 7
 
1.4%
Other values (183) 378
75.3%
Latin
ValueCountFrequency (%)
K 3
16.7%
u 2
 
11.1%
l 1
 
5.6%
C 1
 
5.6%
t 1
 
5.6%
r 1
 
5.6%
e 1
 
5.6%
Y 1
 
5.6%
I 1
 
5.6%
D 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
116
89.9%
, 5
 
3.9%
- 3
 
2.3%
& 2
 
1.6%
· 1
 
0.8%
) 1
 
0.8%
( 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 502
77.3%
ASCII 146
 
22.5%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
79.5%
, 5
 
3.4%
- 3
 
2.1%
K 3
 
2.1%
u 2
 
1.4%
& 2
 
1.4%
l 1
 
0.7%
C 1
 
0.7%
t 1
 
0.7%
r 1
 
0.7%
Other values (11) 11
 
7.5%
Hangul
ValueCountFrequency (%)
스 20
 
4.0%
제 19
 
3.8%
디 19
 
3.8%
트 12
 
2.4%
작 11
 
2.2%
이 10
 
2.0%
튜 9
 
1.8%
오 9
 
1.8%
매 8
 
1.6%
판 7
 
1.4%
Other values (183) 378
75.3%
None
ValueCountFrequency (%)
· 1
100.0%

대표제품_서비스
Text

MISSING 

Distinct48
Distinct (%)100.0%
Missing1
Missing (%)2.0%
Memory size524.0 B
2024-03-18T14:11:13.978716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26.5
Mean length22.666667
Min length9

Characters and Unicode

Total characters1088
Distinct characters286
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row감바스, 훠궈, 마라탕, 와인플래터, 슈바인학센
2nd row공룡놀이, 개미집, 여름바다, 미술키트, 실버키트
3rd row휴대폰케이스, 티셔츠, 에코백, 패브릭포스터
4th row홍차, 허브차, 과일차로 구성된 고객 맞춤형 티백 패키지 판매
5th row오픈스페이스 협탁, 벤치, 시그니처 장식장
ValueCountFrequency (%)
및 10
 
3.9%
판매 7
 
2.7%
개발 4
 
1.6%
제작 3
 
1.2%
클래스 3
 
1.2%
등 3
 
1.2%
서비스 3
 
1.2%
라운드 2
 
0.8%
보조기 2
 
0.8%
출판 2
 
0.8%
Other values (200) 217
84.8%
2024-03-18T14:11:14.397384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
210
 
19.3%
, 68
 
6.2%
스 20
 
1.8%
라 12
 
1.1%
제 12
 
1.1%
이 11
 
1.0%
트 11
 
1.0%
판 11
 
1.0%
매 11
 
1.0%
및 10
 
0.9%
Other values (276) 712
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 789
72.5%
Space Separator 210
 
19.3%
Other Punctuation 72
 
6.6%
Open Punctuation 6
 
0.6%
Close Punctuation 6
 
0.6%
Decimal Number 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 20
 
2.5%
라 12
 
1.5%
제 12
 
1.5%
이 11
 
1.4%
트 11
 
1.4%
판 11
 
1.4%
매 11
 
1.4%
및 10
 
1.3%
인 9
 
1.1%
드 9
 
1.1%
Other values (266) 673
85.3%
Other Punctuation
ValueCountFrequency (%)
, 68
94.4%
& 2
 
2.8%
/ 1
 
1.4%
: 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
0 1
 
20.0%
2 1
 
20.0%
Space Separator
ValueCountFrequency (%)
210
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
72.5%
Common 299
 
27.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 20
 
2.5%
라 12
 
1.5%
제 12
 
1.5%
이 11
 
1.4%
트 11
 
1.4%
판 11
 
1.4%
매 11
 
1.4%
및 10
 
1.3%
인 9
 
1.1%
드 9
 
1.1%
Other values (266) 673
85.3%
Common
ValueCountFrequency (%)
210
70.2%
, 68
 
22.7%
( 6
 
2.0%
) 6
 
2.0%
1 3
 
1.0%
& 2
 
0.7%
/ 1
 
0.3%
: 1
 
0.3%
0 1
 
0.3%
2 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
72.5%
ASCII 299
 
27.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
210
70.2%
, 68
 
22.7%
( 6
 
2.0%
) 6
 
2.0%
1 3
 
1.0%
& 2
 
0.7%
/ 1
 
0.3%
: 1
 
0.3%
0 1
 
0.3%
2 1
 
0.3%
Hangul
ValueCountFrequency (%)
스 20
 
2.5%
라 12
 
1.5%
제 12
 
1.5%
이 11
 
1.4%
트 11
 
1.4%
판 11
 
1.4%
매 11
 
1.4%
및 10
 
1.3%
인 9
 
1.1%
드 9
 
1.1%
Other values (266) 673
85.3%

소재지
Text

MISSING 

Distinct28
Distinct (%)96.6%
Missing20
Missing (%)40.8%
Memory size524.0 B
2024-03-18T14:11:14.614562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length25.655172
Min length20

Characters and Unicode

Total characters744
Distinct characters64
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)93.1%

Sample

1st row인천광역시 부평구 충선로209번길 41(삼산동)
2nd row인천광역시 부평구 경원대로1403번길 38-18(부평동)
3rd row인천광역시 부평구 충선로209번길 41(삼산동)
4th row인천광역시 부평구 열우물로 90, 상가F동 302호
5th row인천광역시 부평구 장제로249번길 9, 1층
ValueCountFrequency (%)
인천광역시 29
20.1%
부평구 29
20.1%
1층 5
 
3.5%
충선로209번길 4
 
2.8%
12-4(부평동 2
 
1.4%
지하1층 2
 
1.4%
부평문화로 2
 
1.4%
2층 2
 
1.4%
201호 2
 
1.4%
41(삼산동 2
 
1.4%
Other values (65) 65
45.1%
2024-03-18T14:11:14.951634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115
 
15.5%
부 41
 
5.5%
1 38
 
5.1%
평 38
 
5.1%
인 31
 
4.2%
천 30
 
4.0%
시 29
 
3.9%
광 29
 
3.9%
구 29
 
3.9%
역 29
 
3.9%
Other values (54) 335
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 425
57.1%
Decimal Number 163
 
21.9%
Space Separator 115
 
15.5%
Other Punctuation 22
 
3.0%
Close Punctuation 7
 
0.9%
Open Punctuation 7
 
0.9%
Dash Punctuation 4
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 41
 
9.6%
평 38
 
8.9%
인 31
 
7.3%
천 30
 
7.1%
시 29
 
6.8%
광 29
 
6.8%
구 29
 
6.8%
역 29
 
6.8%
로 29
 
6.8%
길 18
 
4.2%
Other values (38) 122
28.7%
Decimal Number
ValueCountFrequency (%)
1 38
23.3%
2 24
14.7%
0 24
14.7%
9 16
9.8%
5 13
 
8.0%
4 13
 
8.0%
3 12
 
7.4%
7 10
 
6.1%
8 7
 
4.3%
6 6
 
3.7%
Space Separator
ValueCountFrequency (%)
115
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 425
57.1%
Common 318
42.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 41
 
9.6%
평 38
 
8.9%
인 31
 
7.3%
천 30
 
7.1%
시 29
 
6.8%
광 29
 
6.8%
구 29
 
6.8%
역 29
 
6.8%
로 29
 
6.8%
길 18
 
4.2%
Other values (38) 122
28.7%
Common
ValueCountFrequency (%)
115
36.2%
1 38
 
11.9%
2 24
 
7.5%
0 24
 
7.5%
, 22
 
6.9%
9 16
 
5.0%
5 13
 
4.1%
4 13
 
4.1%
3 12
 
3.8%
7 10
 
3.1%
Other values (5) 31
 
9.7%
Latin
ValueCountFrequency (%)
F 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 425
57.1%
ASCII 319
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115
36.1%
1 38
 
11.9%
2 24
 
7.5%
0 24
 
7.5%
, 22
 
6.9%
9 16
 
5.0%
5 13
 
4.1%
4 13
 
4.1%
3 12
 
3.8%
7 10
 
3.1%
Other values (6) 32
 
10.0%
Hangul
ValueCountFrequency (%)
부 41
 
9.6%
평 38
 
8.9%
인 31
 
7.3%
천 30
 
7.1%
시 29
 
6.8%
광 29
 
6.8%
구 29
 
6.8%
역 29
 
6.8%
로 29
 
6.8%
길 18
 
4.2%
Other values (38) 122
28.7%

연락처
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing24
Missing (%)49.0%
Memory size524.0 B
2024-03-18T14:11:15.157140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.36
Min length9

Characters and Unicode

Total characters334
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

Unique25 ?
Unique (%)100.0%

Sample

1st row070-8285-8566
2nd row02-6959-9426
3rd row0507-1378-9674
4th row0507-1471-0344
5th row0507-1444-7333
ValueCountFrequency (%)
070-8285-8566 1
 
4.0%
0507-1498-7854 1
 
4.0%
0507-1315-1803 1
 
4.0%
0507-1360-6709 1
 
4.0%
032-361-1971 1
 
4.0%
1800-9228 1
 
4.0%
0507-1353-8902 1
 
4.0%
0507-1457-3016 1
 
4.0%
070-4647-0424 1
 
4.0%
0507-1328-3629 1
 
4.0%
Other values (15) 15
60.0%
2024-03-18T14:11:15.446482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 60
18.0%
- 49
14.7%
7 39
11.7%
1 36
10.8%
5 31
9.3%
4 26
7.8%
3 23
 
6.9%
8 21
 
6.3%
6 20
 
6.0%
2 17
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 285
85.3%
Dash Punctuation 49
 
14.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60
21.1%
7 39
13.7%
1 36
12.6%
5 31
10.9%
4 26
9.1%
3 23
 
8.1%
8 21
 
7.4%
6 20
 
7.0%
2 17
 
6.0%
9 12
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 334
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 60
18.0%
- 49
14.7%
7 39
11.7%
1 36
10.8%
5 31
9.3%
4 26
7.8%
3 23
 
6.9%
8 21
 
6.3%
6 20
 
6.0%
2 17
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 60
18.0%
- 49
14.7%
7 39
11.7%
1 36
10.8%
5 31
9.3%
4 26
7.8%
3 23
 
6.9%
8 21
 
6.3%
6 20
 
6.0%
2 17
 
5.1%

Interactions

2024-03-18T14:11:11.606840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:11:15.534760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번기업명분류기업소개대표제품_서비스소재지연락처
순번1.0001.0000.9541.0001.0001.0001.000
기업명1.0001.0001.0001.0001.0001.0001.000
분류0.9541.0001.0001.0001.0001.0001.000
기업소개1.0001.0001.0001.0001.0001.0001.000
대표제품_서비스1.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.000
2024-03-18T14:11:15.652006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번분류
순번1.0000.800
분류0.8001.000

Missing values

2024-03-18T14:11:11.782999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:11:11.896773image/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.
2024-03-18T14:11:11.991836image/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

순번기업명분류기업소개대표제품_서비스소재지연락처
01월드킷일반상품(온라인판매)세계요리 밀키트 판매감바스, 훠궈, 마라탕, 와인플래터, 슈바인학센<NA>070-8285-8566
12바니그라운드일반상품(온라인판매)놀이키트 제작소공룡놀이, 개미집, 여름바다, 미술키트, 실버키트<NA><NA>
23듀킨일반상품(온라인판매)디지털프린팅 제품제작 및 판매휴대폰케이스, 티셔츠, 에코백, 패브릭포스터<NA>02-6959-9426
34에브리테이티팟일반상품(온라인판매)차(TEA)홍차, 허브차, 과일차로 구성된 고객 맞춤형 티백 패키지 판매<NA><NA>
45모양스튜디오일반상품(온라인판매)타일가구 맞춤제작, DIY키트 판매오픈스페이스 협탁, 벤치, 시그니처 장식장<NA><NA>
56스튜디오비숍일반상품(온라인판매)헬스케어 아이디어 제품 제작자세교정 라운드 솔더 보조기, 보조밴드인천광역시 부평구 충선로209번길 41(삼산동)<NA>
67지나공작소일반상품(온라인판매)느린아이를 위한 미술키트발달장애 아동용 미술키트(모양자, 한글스텐실)<NA><NA>
78오잠봉일반상품(온라인판매)잠봉 밀키트잠봉뵈르 파니니, 잠봉 크로무슈, 잠봉베이글인천광역시 부평구 경원대로1403번길 38-18(부평동)0507-1378-9674
89로로케어일반상품(온라인판매)헬스케어 아이디어 제품 제작 및 판매자세교정 라운드 숄더 보조기, 보조밴드인천광역시 부평구 충선로209번길 41(삼산동)<NA>
910꿈잉일반상품(온라인판매)천연염색의 현대화 및 정형화천연염색 자동화 설비 개발 및 천연염색 제품 제조<NA><NA>
순번기업명분류기업소개대표제품_서비스소재지연락처
3940페이스러너스튜디오사진 스튜디오셀프촬영, 제품촬영, 창업 컨설팅인천광역시 부평구 충선로209번길 21, 801호0507-1315-1803
4041블라코스튜디오자연광 조명 스튜디오흑백 셀프사진, 프로필사진, 제품촬영인천광역시 부평구 주부토로81번길 50, 3동 220호<NA>
4142더프레젠트스튜디오맞춤 촬영 스튜디오컬러프로필, 컬러증명사진, 세미웨딩인천광역시 부평구 장제로 45, 103동 175호<NA>
4243몰입스튜디오명상 스튜디오명상컨텐츠 기획, 명상클래스 운영인천광역시 부평구 경인로1059번길 10, 1층(부개동)<NA>
4344블랙씨스튜디오스튜디오미디어창작 스튜디오아트앤커머셜 미디어창작 스튜디오의 전문화인천광역시 부평구 경원대로 1377번길 29-40507-1450-2118
4445(주)아이앤지사회적기여수화번역 시스템 개발카메라 모션 인식 수화번역 시스템(개발중)인천광역시 부평구 수변로 56, 103호<NA>
4546가벼운오늘사회적기여제로웨이스트샵&비건카페친환경 생필품, 소품, 비건음료인천광역시 부평구 장제로257번길 27, 102호<NA>
4647부활피엔피사회적기여순환경 플라스틱 수경화분 제작재생플라스틱 활용 수경가드닝<NA><NA>
4748업모스트사회적기여폐비닐 재활용 소재로 디자인 제품 제작모자, 가방 등 디자인 제품 판매<NA><NA>
4849예술로사회적기여시니에세대 예술융합 교육 프로그램시니어세대 백세누리 프로그램(인지, 음악, 미술, 오감) 제공인천광역시 부평구 하정로 17, 1층 101호 우측<NA>