Overview

Dataset statistics

Number of variables12
Number of observations38
Missing cells112
Missing cells (%)24.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory104.5 B

Variable types

Text4
Numeric5
Categorical3

Dataset

Description광교비즈니스센터 입주기업 현황
Author경기도경제과학진흥원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=VPDP2AOMRMFBEYYE41CF31616908&infSeq=1

Alerts

설립년도 is highly overall correlated with 사업자등록번호 and 3 other fieldsHigh correlation
사업자등록번호 is highly overall correlated with 설립년도 and 1 other fieldsHigh correlation
종사자수 is highly overall correlated with 설립년도 and 2 other fieldsHigh correlation
입주공간근무자수 is highly overall correlated with 종사자수High correlation
기업규모 is highly overall correlated with 설립년도 and 3 other fieldsHigh correlation
인증 is highly overall correlated with 설립년도 and 2 other fieldsHigh correlation
입주목적 is highly overall correlated with 기업규모High correlation
설립년도 has 3 (7.9%) missing valuesMissing
업종 has 1 (2.6%) missing valuesMissing
주요생산품 has 13 (34.2%) missing valuesMissing
종사자수 has 13 (34.2%) missing valuesMissing
입주년도 has 19 (50.0%) missing valuesMissing
입주공간근무자수 has 28 (73.7%) missing valuesMissing
홈페이지 has 35 (92.1%) missing valuesMissing
기업명 has unique valuesUnique
사업자등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:55:30.388399
Analysis finished2023-12-10 21:55:35.005944
Duration4.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기업명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-11T06:55:35.138458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length8.8421053
Min length3

Characters and Unicode

Total characters336
Distinct characters124
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row카이스 주식회사
2nd row피에이치에이㈜
3rd row이콜랩(유)
4th row(재)대건청소년회
5th row(재)경기콘텐츠진흥원
ValueCountFrequency (%)
주식회사 4
 
9.3%
카이스 1
 
2.3%
주)리얼위드 1
 
2.3%
주)지놈앤컴퍼니 1
 
2.3%
발루프코리아(유 1
 
2.3%
큐롬바이오사이언스 1
 
2.3%
주)큐어세라퓨틱스 1
 
2.3%
주)피노바이오 1
 
2.3%
피움바이오 1
 
2.3%
이온어스(주 1
 
2.3%
Other values (30) 30
69.8%
2023-12-11T06:55:35.592985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 25
 
7.4%
) 25
 
7.4%
주 21
 
6.2%
스 15
 
4.5%
이 15
 
4.5%
에 7
 
2.1%
리 7
 
2.1%
유 7
 
2.1%
사 7
 
2.1%
회 7
 
2.1%
Other values (114) 200
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 274
81.5%
Open Punctuation 25
 
7.4%
Close Punctuation 25
 
7.4%
Other Symbol 5
 
1.5%
Space Separator 5
 
1.5%
Uppercase Letter 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 21
 
7.7%
스 15
 
5.5%
이 15
 
5.5%
에 7
 
2.6%
리 7
 
2.6%
유 7
 
2.6%
사 7
 
2.6%
회 7
 
2.6%
코 6
 
2.2%
원 5
 
1.8%
Other values (108) 177
64.6%
Uppercase Letter
ValueCountFrequency (%)
U 1
50.0%
C 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 279
83.0%
Common 55
 
16.4%
Latin 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 21
 
7.5%
스 15
 
5.4%
이 15
 
5.4%
에 7
 
2.5%
리 7
 
2.5%
유 7
 
2.5%
사 7
 
2.5%
회 7
 
2.5%
코 6
 
2.2%
원 5
 
1.8%
Other values (109) 182
65.2%
Common
ValueCountFrequency (%)
( 25
45.5%
) 25
45.5%
5
 
9.1%
Latin
ValueCountFrequency (%)
U 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 274
81.5%
ASCII 57
 
17.0%
None 5
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 25
43.9%
) 25
43.9%
5
 
8.8%
U 1
 
1.8%
C 1
 
1.8%
Hangul
ValueCountFrequency (%)
주 21
 
7.7%
스 15
 
5.5%
이 15
 
5.5%
에 7
 
2.6%
리 7
 
2.6%
유 7
 
2.6%
사 7
 
2.6%
회 7
 
2.6%
코 6
 
2.2%
원 5
 
1.8%
Other values (108) 177
64.6%
None
ValueCountFrequency (%)
㈜ 5
100.0%

설립년도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)60.0%
Missing3
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean2008.5143
Minimum1985
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T06:55:35.707778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1988.5
Q12002.5
median2012
Q32016.5
95-th percentile2020
Maximum2020
Range35
Interquartile range (IQR)14

Descriptive statistics

Standard deviation9.9243356
Coefficient of variation (CV)0.0049411327
Kurtosis0.12714301
Mean2008.5143
Median Absolute Deviation (MAD)5
Skewness-0.97614272
Sum70298
Variance98.492437
MonotonicityNot monotonic
2023-12-11T06:55:35.824587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2017 4
 
10.5%
2020 3
 
7.9%
2015 3
 
7.9%
2013 3
 
7.9%
2008 2
 
5.3%
2018 2
 
5.3%
1985 2
 
5.3%
2004 2
 
5.3%
2001 2
 
5.3%
2009 1
 
2.6%
Other values (11) 11
28.9%
(Missing) 3
 
7.9%
ValueCountFrequency (%)
1985 2
5.3%
1990 1
2.6%
1992 1
2.6%
1997 1
2.6%
1998 1
2.6%
2001 2
5.3%
2002 1
2.6%
2003 1
2.6%
2004 2
5.3%
2008 2
5.3%
ValueCountFrequency (%)
2020 3
7.9%
2018 2
5.3%
2017 4
10.5%
2016 1
 
2.6%
2015 3
7.9%
2014 1
 
2.6%
2013 3
7.9%
2012 1
 
2.6%
2011 1
 
2.6%
2010 1
 
2.6%

사업자등록번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5898693 × 109
Minimum1.1308304 × 109
Maximum8.8588002 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T06:55:35.924537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1308304 × 109
5-th percentile1.1385762 × 109
Q11.2636182 × 109
median2.158837 × 109
Q36.2361838 × 109
95-th percentile7.9512008 × 109
Maximum8.8588002 × 109
Range7.7279698 × 109
Interquartile range (IQR)4.9725655 × 109

Descriptive statistics

Standard deviation2.6550275 × 109
Coefficient of variation (CV)0.73958889
Kurtosis-1.3226895
Mean3.5898693 × 109
Median Absolute Deviation (MAD)1.0054452 × 109
Skewness0.5761269
Sum1.3641504 × 1011
Variance7.0491709 × 1018
MonotonicityNot monotonic
2023-12-11T06:55:36.027889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1358102865 1
 
2.6%
6388102078 1
 
2.6%
6808600310 1
 
2.6%
7928700643 1
 
2.6%
6108634408 1
 
2.6%
6508600532 1
 
2.6%
7418601098 1
 
2.6%
7748101583 1
 
2.6%
5138601848 1
 
2.6%
5810302696 1
 
2.6%
Other values (28) 28
73.7%
ValueCountFrequency (%)
1130830392 1
2.6%
1138192222 1
2.6%
1138644012 1
2.6%
1168139551 1
2.6%
1208664767 1
2.6%
1238174992 1
2.6%
1248208755 1
2.6%
1248218476 1
2.6%
1248301609 1
2.6%
1248753459 1
2.6%
ValueCountFrequency (%)
8858800151 1
2.6%
8078701944 1
2.6%
7928700643 1
2.6%
7748101583 1
2.6%
7418601098 1
2.6%
6808600310 1
2.6%
6558700359 1
2.6%
6508600532 1
2.6%
6388102078 1
2.6%
6278700257 1
2.6%

업종
Text

MISSING 

Distinct27
Distinct (%)73.0%
Missing1
Missing (%)2.6%
Memory size436.0 B
2023-12-11T06:55:36.211485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length14.216216
Min length2

Characters and Unicode

Total characters526
Distinct characters104
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

Unique22 ?
Unique (%)59.5%

Sample

1st row그 외 자동차용 신품 부품 제조업
2nd row그 외 자동차용 신품 부품 제조업
3rd row그 외 기타 분류 안된 화학제품 제조업
4th row그 외 기타 협회 및 단체
5th row문화 및 관광 행정
ValueCountFrequency (%)
및 17
 
11.0%
외 11
 
7.1%
기타 11
 
7.1%
그 11
 
7.1%
연구개발업 8
 
5.2%
제조업 8
 
5.2%
부품 5
 
3.2%
신품 5
 
3.2%
의학 5
 
3.2%
약학 5
 
3.2%
Other values (49) 68
44.2%
2023-12-11T06:55:36.545712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
22.2%
업 30
 
5.7%
기 19
 
3.6%
학 18
 
3.4%
및 17
 
3.2%
품 15
 
2.9%
제 14
 
2.7%
타 12
 
2.3%
그 11
 
2.1%
외 11
 
2.1%
Other values (94) 262
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 400
76.0%
Space Separator 117
 
22.2%
Uppercase Letter 4
 
0.8%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 30
 
7.5%
기 19
 
4.8%
학 18
 
4.5%
및 17
 
4.2%
품 15
 
3.8%
제 14
 
3.5%
타 12
 
3.0%
그 11
 
2.8%
외 11
 
2.8%
발 11
 
2.8%
Other values (87) 242
60.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
I 1
25.0%
B 1
25.0%
Space Separator
ValueCountFrequency (%)
117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 400
76.0%
Common 122
 
23.2%
Latin 4
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 30
 
7.5%
기 19
 
4.8%
학 18
 
4.5%
및 17
 
4.2%
품 15
 
3.8%
제 14
 
3.5%
타 12
 
3.0%
그 11
 
2.8%
외 11
 
2.8%
발 11
 
2.8%
Other values (87) 242
60.5%
Common
ValueCountFrequency (%)
117
95.9%
) 2
 
1.6%
( 2
 
1.6%
, 1
 
0.8%
Latin
ValueCountFrequency (%)
T 2
50.0%
I 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 400
76.0%
ASCII 126
 
24.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
92.9%
) 2
 
1.6%
( 2
 
1.6%
T 2
 
1.6%
I 1
 
0.8%
, 1
 
0.8%
B 1
 
0.8%
Hangul
ValueCountFrequency (%)
업 30
 
7.5%
기 19
 
4.8%
학 18
 
4.5%
및 17
 
4.2%
품 15
 
3.8%
제 14
 
3.5%
타 12
 
3.0%
그 11
 
2.8%
외 11
 
2.8%
발 11
 
2.8%
Other values (87) 242
60.5%

기업규모
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size436.0 B
중소기업
18 
소기업
5 
<NA>
4 
소상공인
3 
중견기업
2 
Other values (5)
6 

Length

Max length8
Median length4
Mean length3.9210526
Min length3

Unique

Unique4 ?
Unique (%)10.5%

Sample

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

Common Values

ValueCountFrequency (%)
중소기업 18
47.4%
소기업 5
 
13.2%
<NA> 4
 
10.5%
소상공인 3
 
7.9%
중견기업 2
 
5.3%
중기업 2
 
5.3%
대기업 1
 
2.6%
개인사업자 1
 
2.6%
판단제외 1
 
2.6%
보호대상중견기업 1
 
2.6%

Length

2023-12-11T06:55:36.658081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:55:36.785553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중소기업 18
47.4%
소기업 5
 
13.2%
na 4
 
10.5%
소상공인 3
 
7.9%
중견기업 2
 
5.3%
중기업 2
 
5.3%
대기업 1
 
2.6%
개인사업자 1
 
2.6%
판단제외 1
 
2.6%
보호대상중견기업 1
 
2.6%

인증
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size436.0 B
<NA>
30 
벤처기업
7 
기업부설연구소
 
1

Length

Max length7
Median length4
Mean length4.0789474
Min length4

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
78.9%
벤처기업 7
 
18.4%
기업부설연구소 1
 
2.6%

Length

2023-12-11T06:55:36.949594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:55:37.047374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
78.9%
벤처기업 7
 
18.4%
기업부설연구소 1
 
2.6%

주요생산품
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing13
Missing (%)34.2%
Memory size436.0 B
2023-12-11T06:55:37.243432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length22
Mean length15
Min length2

Characters and Unicode

Total characters375
Distinct characters139
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st rowDoor Trim, Floor Mat 외
2nd rowD/Module Ass'Y류, Hinge Ass'y류, Latch ass'Y류, 기타제품
3rd row정유공정첨가제, 수처리약품 등
4th rowMold Cleaning Rubber Sheet 외
5th row자동차부품
ValueCountFrequency (%)
외 5
 
6.0%
등 5
 
6.0%
및 4
 
4.8%
기타 3
 
3.6%
ass'y류 3
 
3.6%
제조 3
 
3.6%
치료제 2
 
2.4%
연구개발 2
 
2.4%
플라스틱 2
 
2.4%
부품 2
 
2.4%
Other values (51) 53
63.1%
2023-12-11T06:55:37.559424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
15.7%
제 12
 
3.2%
, 11
 
2.9%
기 9
 
2.4%
품 7
 
1.9%
스 6
 
1.6%
e 6
 
1.6%
s 6
 
1.6%
료 6
 
1.6%
o 6
 
1.6%
Other values (129) 247
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 225
60.0%
Space Separator 59
 
15.7%
Lowercase Letter 54
 
14.4%
Uppercase Letter 20
 
5.3%
Other Punctuation 15
 
4.0%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 12
 
5.3%
기 9
 
4.0%
품 7
 
3.1%
스 6
 
2.7%
료 6
 
2.7%
외 5
 
2.2%
등 5
 
2.2%
발 5
 
2.2%
개 5
 
2.2%
치 5
 
2.2%
Other values (94) 160
71.1%
Lowercase Letter
ValueCountFrequency (%)
e 6
11.1%
s 6
11.1%
o 6
11.1%
a 5
9.3%
i 4
 
7.4%
r 4
 
7.4%
l 4
 
7.4%
t 3
 
5.6%
n 3
 
5.6%
d 2
 
3.7%
Other values (7) 11
20.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
15.0%
R 3
15.0%
M 3
15.0%
D 2
10.0%
Y 2
10.0%
F 1
 
5.0%
V 1
 
5.0%
T 1
 
5.0%
S 1
 
5.0%
C 1
 
5.0%
Other values (2) 2
10.0%
Other Punctuation
ValueCountFrequency (%)
, 11
73.3%
' 3
 
20.0%
/ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 225
60.0%
Common 76
 
20.3%
Latin 74
 
19.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 12
 
5.3%
기 9
 
4.0%
품 7
 
3.1%
스 6
 
2.7%
료 6
 
2.7%
외 5
 
2.2%
등 5
 
2.2%
발 5
 
2.2%
개 5
 
2.2%
치 5
 
2.2%
Other values (94) 160
71.1%
Latin
ValueCountFrequency (%)
e 6
 
8.1%
s 6
 
8.1%
o 6
 
8.1%
a 5
 
6.8%
i 4
 
5.4%
r 4
 
5.4%
l 4
 
5.4%
A 3
 
4.1%
t 3
 
4.1%
R 3
 
4.1%
Other values (19) 30
40.5%
Common
ValueCountFrequency (%)
59
77.6%
, 11
 
14.5%
' 3
 
3.9%
) 1
 
1.3%
( 1
 
1.3%
/ 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 225
60.0%
ASCII 150
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
39.3%
, 11
 
7.3%
e 6
 
4.0%
s 6
 
4.0%
o 6
 
4.0%
a 5
 
3.3%
i 4
 
2.7%
r 4
 
2.7%
l 4
 
2.7%
A 3
 
2.0%
Other values (25) 42
28.0%
Hangul
ValueCountFrequency (%)
제 12
 
5.3%
기 9
 
4.0%
품 7
 
3.1%
스 6
 
2.7%
료 6
 
2.7%
외 5
 
2.2%
등 5
 
2.2%
발 5
 
2.2%
개 5
 
2.2%
치 5
 
2.2%
Other values (94) 160
71.1%

종사자수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct22
Distinct (%)88.0%
Missing13
Missing (%)34.2%
Infinite0
Infinite (%)0.0%
Mean84.52
Minimum1
Maximum668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T06:55:37.666549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.6
Q18
median21
Q397
95-th percentile337.4
Maximum668
Range667
Interquartile range (IQR)89

Descriptive statistics

Standard deviation148.92647
Coefficient of variation (CV)1.7620264
Kurtosis9.9635113
Mean84.52
Median Absolute Deviation (MAD)16
Skewness2.9880492
Sum2113
Variance22179.093
MonotonicityNot monotonic
2023-12-11T06:55:37.781488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
10 2
 
5.3%
5 2
 
5.3%
6 2
 
5.3%
8 1
 
2.6%
364 1
 
2.6%
97 1
 
2.6%
21 1
 
2.6%
12 1
 
2.6%
1 1
 
2.6%
30 1
 
2.6%
Other values (12) 12
31.6%
(Missing) 13
34.2%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
5 2
5.3%
6 2
5.3%
8 1
2.6%
10 2
5.3%
11 1
2.6%
12 1
2.6%
19 1
2.6%
21 1
2.6%
ValueCountFrequency (%)
668 1
2.6%
364 1
2.6%
231 1
2.6%
150 1
2.6%
136 1
2.6%
120 1
2.6%
97 1
2.6%
84 1
2.6%
42 1
2.6%
40 1
2.6%

입주년도
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)31.6%
Missing19
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean2018.4737
Minimum2015
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T06:55:37.883306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2018
Q32020
95-th percentile2022
Maximum2022
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4351231
Coefficient of variation (CV)0.0012064181
Kurtosis-1.1048852
Mean2018.4737
Median Absolute Deviation (MAD)2
Skewness-0.054601782
Sum38351
Variance5.9298246
MonotonicityNot monotonic
2023-12-11T06:55:38.014520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 5
 
13.2%
2015 4
 
10.5%
2020 4
 
10.5%
2022 3
 
7.9%
2017 2
 
5.3%
2021 1
 
2.6%
(Missing) 19
50.0%
ValueCountFrequency (%)
2015 4
10.5%
2017 2
 
5.3%
2018 5
13.2%
2020 4
10.5%
2021 1
 
2.6%
2022 3
7.9%
ValueCountFrequency (%)
2022 3
7.9%
2021 1
 
2.6%
2020 4
10.5%
2018 5
13.2%
2017 2
 
5.3%
2015 4
10.5%

입주목적
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
사무실
19 
<NA>
13 
사무실 실험실
5 
휴게음식점
 
1

Length

Max length7
Median length6
Mean length3.9210526
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
사무실 19
50.0%
<NA> 13
34.2%
사무실 실험실 5
 
13.2%
휴게음식점 1
 
2.6%

Length

2023-12-11T06:55:38.129985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:55:38.243098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사무실 24
55.8%
na 13
30.2%
실험실 5
 
11.6%
휴게음식점 1
 
2.3%

입주공간근무자수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)80.0%
Missing28
Missing (%)73.7%
Infinite0
Infinite (%)0.0%
Mean13
Minimum2
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-11T06:55:38.333477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.35
Q15.25
median10
Q317
95-th percentile31.9
Maximum40
Range38
Interquartile range (IQR)11.75

Descriptive statistics

Standard deviation11.382247
Coefficient of variation (CV)0.87555749
Kurtosis3.0037484
Mean13
Median Absolute Deviation (MAD)5
Skewness1.6829042
Sum130
Variance129.55556
MonotonicityNot monotonic
2023-12-11T06:55:38.421559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 2
 
5.3%
10 2
 
5.3%
11 1
 
2.6%
40 1
 
2.6%
2 1
 
2.6%
19 1
 
2.6%
22 1
 
2.6%
6 1
 
2.6%
(Missing) 28
73.7%
ValueCountFrequency (%)
2 1
2.6%
5 2
5.3%
6 1
2.6%
10 2
5.3%
11 1
2.6%
19 1
2.6%
22 1
2.6%
40 1
2.6%
ValueCountFrequency (%)
40 1
2.6%
22 1
2.6%
19 1
2.6%
11 1
2.6%
10 2
5.3%
6 1
2.6%
5 2
5.3%
2 1
2.6%

홈페이지
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing35
Missing (%)92.1%
Memory size436.0 B
2023-12-11T06:55:38.556917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length14
Mean length19
Min length12

Characters and Unicode

Total characters57
Distinct characters20
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowwww.ecolab.com
2nd rowblog.naver.com/curetherapeutics
3rd rowpinotbio.com
ValueCountFrequency (%)
www.ecolab.com 1
33.3%
blog.naver.com/curetherapeutics 1
33.3%
pinotbio.com 1
33.3%
2023-12-11T06:55:38.809016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 7
12.3%
c 6
 
10.5%
e 5
 
8.8%
. 5
 
8.8%
w 3
 
5.3%
i 3
 
5.3%
a 3
 
5.3%
b 3
 
5.3%
m 3
 
5.3%
t 3
 
5.3%
Other values (10) 16
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51
89.5%
Other Punctuation 6
 
10.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 7
13.7%
c 6
11.8%
e 5
9.8%
w 3
 
5.9%
i 3
 
5.9%
a 3
 
5.9%
b 3
 
5.9%
m 3
 
5.9%
t 3
 
5.9%
r 3
 
5.9%
Other values (8) 12
23.5%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
/ 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 51
89.5%
Common 6
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 7
13.7%
c 6
11.8%
e 5
9.8%
w 3
 
5.9%
i 3
 
5.9%
a 3
 
5.9%
b 3
 
5.9%
m 3
 
5.9%
t 3
 
5.9%
r 3
 
5.9%
Other values (8) 12
23.5%
Common
ValueCountFrequency (%)
. 5
83.3%
/ 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 7
12.3%
c 6
 
10.5%
e 5
 
8.8%
. 5
 
8.8%
w 3
 
5.3%
i 3
 
5.3%
a 3
 
5.3%
b 3
 
5.3%
m 3
 
5.3%
t 3
 
5.3%
Other values (10) 16
28.1%

Interactions

2023-12-11T06:55:34.213899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:32.411614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:32.955811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.379078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.796926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:34.296869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:32.572098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.049202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.477178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.877366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:34.383086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:32.665371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.132692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.560658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.962378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:34.458915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:32.766119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.215134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.635954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:34.051454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:34.532535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:32.863922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.296157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:33.719505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:55:34.133376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:55:38.898034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업명설립년도사업자등록번호업종기업규모인증주요생산품종사자수입주년도입주목적입주공간근무자수홈페이지
기업명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립년도1.0001.0000.5020.9420.6651.0001.0000.7800.6180.4170.6401.000
사업자등록번호1.0000.5021.0000.6610.0001.0001.0000.0000.0000.0000.0001.000
업종1.0000.9420.6611.0000.9311.0000.9090.8240.0000.7700.0001.000
기업규모1.0000.6650.0000.9311.0001.0001.0000.7320.5160.5610.0001.000
인증1.0001.0001.0001.0001.0001.0001.0000.3960.0000.0000.0001.000
주요생산품1.0001.0001.0000.9091.0001.0001.0001.0000.9741.0001.0001.000
종사자수1.0000.7800.0000.8240.7320.3961.0001.0000.0000.0000.0001.000
입주년도1.0000.6180.0000.0000.5160.0000.9740.0001.0000.4460.7971.000
입주목적1.0000.4170.0000.7700.5610.0001.0000.0000.4461.0000.8001.000
입주공간근무자수1.0000.6400.0000.0000.0000.0001.0000.0000.7970.8001.0001.000
홈페이지1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-11T06:55:39.021937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업규모입주목적인증
기업규모1.0000.6280.816
입주목적0.6281.0000.000
인증0.8160.0001.000
2023-12-11T06:55:39.101488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립년도사업자등록번호종사자수입주년도입주공간근무자수기업규모인증입주목적
설립년도1.0000.638-0.6140.305-0.0370.5360.9130.365
사업자등록번호0.6381.000-0.2390.2470.1340.0000.7070.000
종사자수-0.614-0.2391.000-0.4500.9260.5240.2180.000
입주년도0.3050.247-0.4501.0000.0750.3250.0000.378
입주공간근무자수-0.0370.1340.9260.0751.0000.0000.0000.378
기업규모0.5360.0000.5240.3250.0001.0000.8160.628
인증0.9130.7070.2180.0000.0000.8161.0000.000
입주목적0.3650.0000.0000.3780.3780.6280.0001.000

Missing values

2023-12-11T06:55:34.643251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:55:34.778745image/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.
2023-12-11T06:55:34.910807image/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

기업명설립년도사업자등록번호업종기업규모인증주요생산품종사자수입주년도입주목적입주공간근무자수홈페이지
0카이스 주식회사19851358102865그 외 자동차용 신품 부품 제조업중견기업<NA>Door Trim, Floor Mat 외150<NA>사무실<NA><NA>
1피에이치에이㈜19855038106628그 외 자동차용 신품 부품 제조업중견기업<NA>D/Module Ass'Y류, Hinge Ass'y류, Latch ass'Y류, 기타제품6682015사무실<NA><NA>
2이콜랩(유)19901168139551그 외 기타 분류 안된 화학제품 제조업대기업기업부설연구소정유공정첨가제, 수처리약품 등1202018사무실 실험실11www.ecolab.com
3(재)대건청소년회19981358207488그 외 기타 협회 및 단체<NA><NA><NA><NA><NA><NA><NA><NA>
4(재)경기콘텐츠진흥원20011308212609문화 및 관광 행정소기업<NA><NA><NA><NA><NA><NA><NA>
5(주)나라켐20013128149318산업용 그 외 비경화 고무제품 제조업소기업<NA>Mold Cleaning Rubber Sheet 외<NA>2022<NA><NA><NA>
6(주)일신이앤씨20021238174992건출설계 및 관련 서비스업중소기업<NA><NA>231<NA>사무실<NA><NA>
7브로제코리아(주)20031348608726그 외 자동차용 신품 부품 제조업중소기업<NA>자동차부품842015사무실<NA><NA>
8에이유옵트로닉스코리아(유)20041138192222<NA>중소기업<NA>기타 표시장치 제조<NA><NA>사무실<NA><NA>
9(주)제노스20041208664767의료용품 및 기타 의약 관련제품 제조업중소기업<NA>치과용골이식재(오스테온) 외1362015사무실<NA><NA>
기업명설립년도사업자등록번호업종기업규모인증주요생산품종사자수입주년도입주목적입주공간근무자수홈페이지
28(주)셀라퓨틱스바이오20205138601848의학 및 약학 연구개발업소기업<NA><NA><NA>2022사무실 실험실<NA><NA>
29이글원주식회사<NA>6388102078휴게음식점<NA><NA><NA>12022휴게음식점<NA><NA>
30씨유(CU) 광교비즈니스센터점<NA>5810302696체인화 편의점개인사업자<NA><NA><NA>2018<NA><NA><NA>
31수원벤처센터<NA>1248301609지방행정 집행기관판단제외<NA><NA><NA><NA><NA><NA><NA>
32㈜듀코젠20156558700359응용소프트웨어 개발 및 공급업소상공인벤처기업소프트웨어개발12<NA><NA><NA><NA>
33㈜에어딥20208078701944응용소프트웨어 개발 및 공급업소기업벤처기업공기질진단제어ai서비스21<NA><NA><NA><NA>
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