Overview

Dataset statistics

Number of variables13
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory113.7 B

Variable types

Numeric4
Text6
DateTime3

Dataset

Description「벤처기업육성에 관한 특별조치법」에 따라 지정된 성남시 내 벤처기업 집적시설 현황으로, 시설명, 지정번호, 준공일, 지정일, 주소, 사명자명, 연락처, 전체입주기업수, 입주벤처기업수, 면적 항목을 포함하고 있습니다
URLhttps://www.data.go.kr/data/15076698/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 지정면적(제곱미터)High correlation
전체기업수 is highly overall correlated with 벤처기업수 and 1 other fieldsHigh correlation
벤처기업수 is highly overall correlated with 전체기업수 and 1 other fieldsHigh correlation
지정면적(제곱미터) is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 has unique valuesUnique
시설명 has unique valuesUnique
지정번호 has unique valuesUnique
지정면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:46:45.945635
Analysis finished2023-12-12 14:46:48.357068
Duration2.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:46:48.463802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-12T23:46:48.648583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

시설명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:46:48.871249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length10.130435
Min length4

Characters and Unicode

Total characters233
Distinct characters93
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

Unique23 ?
Unique (%)100.0%

Sample

1st row코리아바이오파크
2nd row판교디지털콘텐츠파크조성사업
3rd row판교이노밸리 (6BL) A동
4th row판교이노밸리 (6BL) B동
5th row판교이노밸리 (6BL) C동
ValueCountFrequency (%)
판교세븐벤처밸리1 3
 
7.7%
판교이노밸리 3
 
7.7%
6bl 3
 
7.7%
판교세븐벤처밸리2 2
 
5.1%
b동 2
 
5.1%
코리아벤처타운 1
 
2.6%
마이다스동 1
 
2.6%
1동 1
 
2.6%
아이앤씨빌딩 1
 
2.6%
씨즈타워 1
 
2.6%
Other values (21) 21
53.8%
2023-12-12T23:46:49.241693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16
 
6.9%
리 11
 
4.7%
판 11
 
4.7%
교 11
 
4.7%
동 9
 
3.9%
처 9
 
3.9%
벤 9
 
3.9%
밸 8
 
3.4%
이 7
 
3.0%
B 6
 
2.6%
Other values (83) 136
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
78.1%
Uppercase Letter 18
 
7.7%
Space Separator 16
 
6.9%
Decimal Number 11
 
4.7%
Open Punctuation 3
 
1.3%
Close Punctuation 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 11
 
6.0%
판 11
 
6.0%
교 11
 
6.0%
동 9
 
4.9%
처 9
 
4.9%
벤 9
 
4.9%
밸 8
 
4.4%
이 7
 
3.8%
븐 5
 
2.7%
세 5
 
2.7%
Other values (66) 97
53.3%
Uppercase Letter
ValueCountFrequency (%)
B 6
33.3%
L 3
16.7%
A 2
 
11.1%
C 1
 
5.6%
N 1
 
5.6%
T 1
 
5.6%
O 1
 
5.6%
W 1
 
5.6%
E 1
 
5.6%
R 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
2 3
27.3%
6 3
27.3%
3 1
 
9.1%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
78.1%
Common 33
 
14.2%
Latin 18
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 11
 
6.0%
판 11
 
6.0%
교 11
 
6.0%
동 9
 
4.9%
처 9
 
4.9%
벤 9
 
4.9%
밸 8
 
4.4%
이 7
 
3.8%
븐 5
 
2.7%
세 5
 
2.7%
Other values (66) 97
53.3%
Latin
ValueCountFrequency (%)
B 6
33.3%
L 3
16.7%
A 2
 
11.1%
C 1
 
5.6%
N 1
 
5.6%
T 1
 
5.6%
O 1
 
5.6%
W 1
 
5.6%
E 1
 
5.6%
R 1
 
5.6%
Common
ValueCountFrequency (%)
16
48.5%
1 4
 
12.1%
( 3
 
9.1%
2 3
 
9.1%
) 3
 
9.1%
6 3
 
9.1%
3 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
78.1%
ASCII 51
 
21.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
31.4%
B 6
 
11.8%
1 4
 
7.8%
( 3
 
5.9%
2 3
 
5.9%
) 3
 
5.9%
L 3
 
5.9%
6 3
 
5.9%
A 2
 
3.9%
C 1
 
2.0%
Other values (7) 7
13.7%
Hangul
ValueCountFrequency (%)
리 11
 
6.0%
판 11
 
6.0%
교 11
 
6.0%
동 9
 
4.9%
처 9
 
4.9%
벤 9
 
4.9%
밸 8
 
4.4%
이 7
 
3.8%
븐 5
 
2.7%
세 5
 
2.7%
Other values (66) 97
53.3%

지정번호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:46:49.447864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.1304348
Min length7

Characters and Unicode

Total characters164
Distinct characters12
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

Unique23 ?
Unique (%)100.0%

Sample

1st row2008-8호
2nd row2008-10호
3rd row2023-9호
4th row2008-12호
5th row2023-8호
ValueCountFrequency (%)
2008-8호 1
 
4.3%
2023-2호 1
 
4.3%
2018-2호 1
 
4.3%
2016-1호 1
 
4.3%
2012-4호 1
 
4.3%
2012-1호 1
 
4.3%
2011-7호 1
 
4.3%
2011-5호 1
 
4.3%
2023-7호 1
 
4.3%
2023-3호 1
 
4.3%
Other values (13) 13
56.5%
2023-12-12T23:46:49.798746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 38
23.2%
0 31
18.9%
- 23
14.0%
호 23
14.0%
1 16
9.8%
3 12
 
7.3%
8 8
 
4.9%
9 4
 
2.4%
4 3
 
1.8%
6 2
 
1.2%
Other values (2) 4
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118
72.0%
Dash Punctuation 23
 
14.0%
Other Letter 23
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 38
32.2%
0 31
26.3%
1 16
13.6%
3 12
 
10.2%
8 8
 
6.8%
9 4
 
3.4%
4 3
 
2.5%
6 2
 
1.7%
5 2
 
1.7%
7 2
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Letter
ValueCountFrequency (%)
호 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 141
86.0%
Hangul 23
 
14.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 38
27.0%
0 31
22.0%
- 23
16.3%
1 16
11.3%
3 12
 
8.5%
8 8
 
5.7%
9 4
 
2.8%
4 3
 
2.1%
6 2
 
1.4%
5 2
 
1.4%
Hangul
ValueCountFrequency (%)
호 23
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 141
86.0%
Hangul 23
 
14.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 38
27.0%
0 31
22.0%
- 23
16.3%
1 16
11.3%
3 12
 
8.5%
8 8
 
5.7%
9 4
 
2.8%
4 3
 
2.1%
6 2
 
1.4%
5 2
 
1.4%
Hangul
ValueCountFrequency (%)
호 23
100.0%

준공일
Date

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum1997-04-01 00:00:00
Maximum2014-10-02 00:00:00
2023-12-12T23:46:49.926308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:50.038289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

지정일
Date

Distinct15
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2008-10-06 00:00:00
Maximum2023-03-17 00:00:00
2023-12-12T23:46:50.130548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:50.227697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

소재지지번주소
Text

Distinct15
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:46:50.368734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length19.26087
Min length19

Characters and Unicode

Total characters443
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)43.5%

Sample

1st row경기도 성남시 분당구 삼평동 694-1
2nd row경기도 성남시 분당구 삼평동 624
3rd row경기도 성남시 분당구 삼평동 621
4th row경기도 성남시 분당구 삼평동 621
5th row경기도 성남시 분당구 삼평동 621
ValueCountFrequency (%)
경기도 23
20.0%
분당구 23
20.0%
성남시 23
20.0%
삼평동 21
18.3%
621 3
 
2.6%
672 3
 
2.6%
625 3
 
2.6%
690 2
 
1.7%
633 2
 
1.7%
613 1
 
0.9%
Other values (11) 11
9.6%
2023-12-12T23:46:50.726297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92
20.8%
경 23
 
5.2%
기 23
 
5.2%
도 23
 
5.2%
성 23
 
5.2%
남 23
 
5.2%
시 23
 
5.2%
분 23
 
5.2%
당 23
 
5.2%
구 23
 
5.2%
Other values (18) 144
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
62.3%
Space Separator 92
 
20.8%
Decimal Number 72
 
16.3%
Dash Punctuation 3
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 23
8.3%
기 23
8.3%
도 23
8.3%
성 23
8.3%
남 23
8.3%
시 23
8.3%
분 23
8.3%
당 23
8.3%
구 23
8.3%
동 23
8.3%
Other values (6) 46
16.7%
Decimal Number
ValueCountFrequency (%)
6 22
30.6%
2 13
18.1%
1 10
13.9%
3 6
 
8.3%
7 5
 
6.9%
4 5
 
6.9%
9 4
 
5.6%
5 3
 
4.2%
0 3
 
4.2%
8 1
 
1.4%
Space Separator
ValueCountFrequency (%)
92
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 276
62.3%
Common 167
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 23
8.3%
기 23
8.3%
도 23
8.3%
성 23
8.3%
남 23
8.3%
시 23
8.3%
분 23
8.3%
당 23
8.3%
구 23
8.3%
동 23
8.3%
Other values (6) 46
16.7%
Common
ValueCountFrequency (%)
92
55.1%
6 22
 
13.2%
2 13
 
7.8%
1 10
 
6.0%
3 6
 
3.6%
7 5
 
3.0%
4 5
 
3.0%
9 4
 
2.4%
5 3
 
1.8%
0 3
 
1.8%
Other values (2) 4
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
62.3%
ASCII 167
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
55.1%
6 22
 
13.2%
2 13
 
7.8%
1 10
 
6.0%
3 6
 
3.6%
7 5
 
3.0%
4 5
 
3.0%
9 4
 
2.4%
5 3
 
1.8%
0 3
 
1.8%
Other values (2) 4
 
2.4%
Hangul
ValueCountFrequency (%)
경 23
8.3%
기 23
8.3%
도 23
8.3%
성 23
8.3%
남 23
8.3%
시 23
8.3%
분 23
8.3%
당 23
8.3%
구 23
8.3%
동 23
8.3%
Other values (6) 46
16.7%

소재지도로명주소
Text

Distinct15
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:46:50.929336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length31
Mean length28.173913
Min length25

Characters and Unicode

Total characters648
Distinct characters50
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

Unique10 ?
Unique (%)43.5%

Sample

1st row경기도 성남시 분당구 대왕판교로 700 (삼평동)
2nd row경기도 성남시 분당구 판교로 242 (삼평동)
3rd row경기도 성남시 분당구 판교로 253 (삼평동)
4th row경기도 성남시 분당구 판교로 253 (삼평동)
5th row경기도 성남시 분당구 판교로 253 (삼평동)
ValueCountFrequency (%)
경기도 23
16.3%
성남시 23
16.3%
분당구 23
16.3%
삼평동 21
14.9%
판교로 8
 
5.7%
판교로228번길 5
 
3.5%
판교역로 4
 
2.8%
253 3
 
2.1%
221 3
 
2.1%
15 3
 
2.1%
Other values (22) 25
17.7%
2023-12-12T23:46:51.264637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
18.4%
2 30
 
4.6%
성 25
 
3.9%
남 25
 
3.9%
당 24
 
3.7%
분 24
 
3.7%
) 24
 
3.7%
( 24
 
3.7%
구 23
 
3.5%
기 23
 
3.5%
Other values (40) 307
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 389
60.0%
Space Separator 119
 
18.4%
Decimal Number 91
 
14.0%
Close Punctuation 24
 
3.7%
Open Punctuation 24
 
3.7%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 25
 
6.4%
남 25
 
6.4%
당 24
 
6.2%
분 24
 
6.2%
구 23
 
5.9%
기 23
 
5.9%
시 23
 
5.9%
로 23
 
5.9%
도 23
 
5.9%
동 23
 
5.9%
Other values (26) 153
39.3%
Decimal Number
ValueCountFrequency (%)
2 30
33.0%
5 16
17.6%
3 11
 
12.1%
1 11
 
12.1%
8 8
 
8.8%
7 5
 
5.5%
4 4
 
4.4%
6 2
 
2.2%
9 2
 
2.2%
0 2
 
2.2%
Space Separator
ValueCountFrequency (%)
119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 389
60.0%
Common 259
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 25
 
6.4%
남 25
 
6.4%
당 24
 
6.2%
분 24
 
6.2%
구 23
 
5.9%
기 23
 
5.9%
시 23
 
5.9%
로 23
 
5.9%
도 23
 
5.9%
동 23
 
5.9%
Other values (26) 153
39.3%
Common
ValueCountFrequency (%)
119
45.9%
2 30
 
11.6%
) 24
 
9.3%
( 24
 
9.3%
5 16
 
6.2%
3 11
 
4.2%
1 11
 
4.2%
8 8
 
3.1%
7 5
 
1.9%
4 4
 
1.5%
Other values (4) 7
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 389
60.0%
ASCII 259
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
45.9%
2 30
 
11.6%
) 24
 
9.3%
( 24
 
9.3%
5 16
 
6.2%
3 11
 
4.2%
1 11
 
4.2%
8 8
 
3.1%
7 5
 
1.9%
4 4
 
1.5%
Other values (4) 7
 
2.7%
Hangul
ValueCountFrequency (%)
성 25
 
6.4%
남 25
 
6.4%
당 24
 
6.2%
분 24
 
6.2%
구 23
 
5.9%
기 23
 
5.9%
시 23
 
5.9%
로 23
 
5.9%
도 23
 
5.9%
동 23
 
5.9%
Other values (26) 153
39.3%

사업자명
Text

Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:46:51.436205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length9.2608696
Min length4

Characters and Unicode

Total characters213
Distinct characters92
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)65.2%

Sample

1st row한국바이오협회 등
2nd row판교디지털콘텐츠파크조성사업컨소시엄
3rd row㈜이노밸리
4th row㈜이노밸리
5th row㈜이노밸리
ValueCountFrequency (%)
판교세븐벤처밸리관리(주 5
17.9%
㈜이노밸리 3
 
10.7%
등 2
 
7.1%
11개사 1
 
3.6%
㈜아이앤씨테크롤로지 1
 
3.6%
주)엔에스피 1
 
3.6%
병원 1
 
3.6%
분당서울대학교 1
 
3.6%
㈜엘오티베큠 1
 
3.6%
한국반도체산업협회 1
 
3.6%
Other values (11) 11
39.3%
2023-12-12T23:46:51.811139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 13
 
6.1%
리 13
 
6.1%
이 9
 
4.2%
밸 8
 
3.8%
교 7
 
3.3%
판 6
 
2.8%
) 6
 
2.8%
주 6
 
2.8%
( 6
 
2.8%
처 6
 
2.8%
Other values (82) 133
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 181
85.0%
Other Symbol 13
 
6.1%
Close Punctuation 6
 
2.8%
Open Punctuation 6
 
2.8%
Space Separator 5
 
2.3%
Decimal Number 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 13
 
7.2%
이 9
 
5.0%
밸 8
 
4.4%
교 7
 
3.9%
판 6
 
3.3%
주 6
 
3.3%
처 6
 
3.3%
벤 6
 
3.3%
관 5
 
2.8%
븐 5
 
2.8%
Other values (77) 110
60.8%
Other Symbol
ValueCountFrequency (%)
㈜ 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 194
91.1%
Common 19
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 13
 
6.7%
리 13
 
6.7%
이 9
 
4.6%
밸 8
 
4.1%
교 7
 
3.6%
판 6
 
3.1%
주 6
 
3.1%
처 6
 
3.1%
벤 6
 
3.1%
관 5
 
2.6%
Other values (78) 115
59.3%
Common
ValueCountFrequency (%)
) 6
31.6%
( 6
31.6%
5
26.3%
1 2
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 181
85.0%
ASCII 19
 
8.9%
None 13
 
6.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 13
100.0%
Hangul
ValueCountFrequency (%)
리 13
 
7.2%
이 9
 
5.0%
밸 8
 
4.4%
교 7
 
3.9%
판 6
 
3.3%
주 6
 
3.3%
처 6
 
3.3%
벤 6
 
3.3%
관 5
 
2.8%
븐 5
 
2.8%
Other values (77) 110
60.8%
ASCII
ValueCountFrequency (%)
) 6
31.6%
( 6
31.6%
5
26.3%
1 2
 
10.5%

연락처
Text

Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:46:51.990231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.391304
Min length11

Characters and Unicode

Total characters285
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

Unique15 ?
Unique (%)65.2%

Sample

1st row031-628-0077
2nd row031-8060-0123
3rd row031-8018-7494
4th row031-8018-7494
5th row031-8018-7494
ValueCountFrequency (%)
031-622-3773 5
21.7%
031-8018-7494 3
13.0%
031-8092-3990 1
 
4.3%
031-639-9026 1
 
4.3%
070-4012-1358 1
 
4.3%
031-787-8902 1
 
4.3%
031-678-6245 1
 
4.3%
02-570-5209 1
 
4.3%
070-7010-1910 1
 
4.3%
031-8060-0123 1
 
4.3%
Other values (7) 7
30.4%
2023-12-12T23:46:52.363203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48
16.8%
- 46
16.1%
3 35
12.3%
1 31
10.9%
2 27
9.5%
7 27
9.5%
6 18
 
6.3%
8 16
 
5.6%
4 13
 
4.6%
9 12
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 239
83.9%
Dash Punctuation 46
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48
20.1%
3 35
14.6%
1 31
13.0%
2 27
11.3%
7 27
11.3%
6 18
 
7.5%
8 16
 
6.7%
4 13
 
5.4%
9 12
 
5.0%
5 12
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 285
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48
16.8%
- 46
16.1%
3 35
12.3%
1 31
10.9%
2 27
9.5%
7 27
9.5%
6 18
 
6.3%
8 16
 
5.6%
4 13
 
4.6%
9 12
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48
16.8%
- 46
16.1%
3 35
12.3%
1 31
10.9%
2 27
9.5%
7 27
9.5%
6 18
 
6.3%
8 16
 
5.6%
4 13
 
4.6%
9 12
 
4.2%

전체기업수
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.434783
Minimum4
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:46:52.493641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q16
median9
Q321
95-th percentile30
Maximum31
Range27
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.3557279
Coefficient of variation (CV)0.69638104
Kurtosis-0.8834683
Mean13.434783
Median Absolute Deviation (MAD)4
Skewness0.81440584
Sum309
Variance87.529644
MonotonicityNot monotonic
2023-12-12T23:46:52.622109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
5 4
17.4%
7 3
13.0%
24 2
 
8.7%
30 2
 
8.7%
6 2
 
8.7%
31 1
 
4.3%
25 1
 
4.3%
8 1
 
4.3%
15 1
 
4.3%
17 1
 
4.3%
Other values (5) 5
21.7%
ValueCountFrequency (%)
4 1
 
4.3%
5 4
17.4%
6 2
8.7%
7 3
13.0%
8 1
 
4.3%
9 1
 
4.3%
10 1
 
4.3%
11 1
 
4.3%
15 1
 
4.3%
17 1
 
4.3%
ValueCountFrequency (%)
31 1
4.3%
30 2
8.7%
25 1
4.3%
24 2
8.7%
18 1
4.3%
17 1
4.3%
15 1
4.3%
11 1
4.3%
10 1
4.3%
9 1
4.3%

벤처기업수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5217391
Minimum2
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:46:52.743011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median6
Q310.5
95-th percentile14.9
Maximum20
Range18
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation4.7373714
Coefficient of variation (CV)0.62982394
Kurtosis0.57661785
Mean7.5217391
Median Absolute Deviation (MAD)2
Skewness1.1368645
Sum173
Variance22.442688
MonotonicityNot monotonic
2023-12-12T23:46:52.868431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4 5
21.7%
5 3
13.0%
13 2
 
8.7%
3 2
 
8.7%
7 2
 
8.7%
6 2
 
8.7%
15 1
 
4.3%
14 1
 
4.3%
9 1
 
4.3%
12 1
 
4.3%
Other values (3) 3
13.0%
ValueCountFrequency (%)
2 1
 
4.3%
3 2
 
8.7%
4 5
21.7%
5 3
13.0%
6 2
 
8.7%
7 2
 
8.7%
8 1
 
4.3%
9 1
 
4.3%
12 1
 
4.3%
13 2
 
8.7%
ValueCountFrequency (%)
20 1
 
4.3%
15 1
 
4.3%
14 1
 
4.3%
13 2
8.7%
12 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
7 2
8.7%
6 2
8.7%
5 3
13.0%

지정면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17405.469
Minimum3264.16
Maximum55710.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:46:52.996531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3264.16
5-th percentile4395.319
Q110895.185
median15071
Q320468.595
95-th percentile47566.705
Maximum55710.33
Range52446.17
Interquartile range (IQR)9573.41

Descriptive statistics

Standard deviation12598.588
Coefficient of variation (CV)0.72382929
Kurtosis4.7254496
Mean17405.469
Median Absolute Deviation (MAD)5318.33
Skewness2.062291
Sum400325.79
Variance1.5872443 × 108
MonotonicityNot monotonic
2023-12-12T23:46:53.129301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
50376.96 1
 
4.3%
55710.33 1
 
4.3%
14033.95 1
 
4.3%
3264.16 1
 
4.3%
14397.86 1
 
4.3%
4322.5 1
 
4.3%
5050.69 1
 
4.3%
21305.36 1
 
4.3%
20547.86 1
 
4.3%
12792.33 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
3264.16 1
4.3%
4322.5 1
4.3%
5050.69 1
4.3%
6605.51 1
4.3%
9644.23 1
4.3%
10390.4 1
4.3%
11399.97 1
4.3%
12792.33 1
4.3%
12813.32 1
4.3%
14033.95 1
4.3%
ValueCountFrequency (%)
55710.33 1
4.3%
50376.96 1
4.3%
22274.41 1
4.3%
21787.44 1
4.3%
21305.36 1
4.3%
20547.86 1
4.3%
20389.33 1
4.3%
18430.07 1
4.3%
17726.12 1
4.3%
16823.22 1
4.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2023-12-12T23:46:53.250747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:53.349352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T23:46:47.551123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.433210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.773239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.138141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.650060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.520872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.855072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.231441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.763401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.608379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.943477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.335320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.902946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:46.698384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.043748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:47.448838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:46:53.436263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명지정번호준공일지정일소재지지번주소소재지도로명주소사업자명연락처전체기업수벤처기업수지정면적(제곱미터)
연번1.0001.0001.0000.8470.5600.9000.9000.8790.8790.6330.0000.704
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지정번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
준공일0.8471.0001.0001.0000.9611.0001.0001.0001.0000.8470.6990.912
지정일0.5601.0001.0000.9611.0000.9730.9730.9600.9600.8400.8210.888
소재지지번주소0.9001.0001.0001.0000.9731.0001.0000.9820.9820.9080.7000.808
소재지도로명주소0.9001.0001.0001.0000.9731.0001.0000.9820.9820.9080.7000.808
사업자명0.8791.0001.0001.0000.9600.9820.9821.0001.0000.8260.0000.900
연락처0.8791.0001.0001.0000.9600.9820.9821.0001.0000.8260.0000.900
전체기업수0.6331.0001.0000.8470.8400.9080.9080.8260.8261.0000.6910.392
벤처기업수0.0001.0001.0000.6990.8210.7000.7000.0000.0000.6911.0000.637
지정면적(제곱미터)0.7041.0001.0000.9120.8880.8080.8080.9000.9000.3920.6371.000
2023-12-12T23:46:53.586800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전체기업수벤처기업수지정면적(제곱미터)
연번1.000-0.384-0.286-0.557
전체기업수-0.3841.0000.8740.712
벤처기업수-0.2860.8741.0000.597
지정면적(제곱미터)-0.5570.7120.5971.000

Missing values

2023-12-12T23:46:48.062257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:46:48.261455image/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

연번시설명지정번호준공일지정일소재지지번주소소재지도로명주소사업자명연락처전체기업수벤처기업수지정면적(제곱미터)데이터기준일자
01코리아바이오파크2008-8호2011-04-272008-10-06경기도 성남시 분당구 삼평동 694-1경기도 성남시 분당구 대왕판교로 700 (삼평동)한국바이오협회 등031-628-0077241550376.962023-06-01
12판교디지털콘텐츠파크조성사업2008-10호2013-09-112008-10-29경기도 성남시 분당구 삼평동 624경기도 성남시 분당구 판교로 242 (삼평동)판교디지털콘텐츠파크조성사업컨소시엄031-8060-0123301355710.332023-06-01
23판교이노밸리 (6BL) A동2023-9호2011-03-292023-03-17경기도 성남시 분당구 삼평동 621경기도 성남시 분당구 판교로 253 (삼평동)㈜이노밸리031-8018-74945410390.42023-06-01
34판교이노밸리 (6BL) B동2008-12호2011-03-292008-12-16경기도 성남시 분당구 삼평동 621경기도 성남시 분당구 판교로 253 (삼평동)㈜이노밸리031-8018-7494311418430.072023-06-01
45판교이노밸리 (6BL) C동2023-8호2011-03-292023-03-17경기도 성남시 분당구 삼평동 621경기도 성남시 분당구 판교로 253 (삼평동)㈜이노밸리031-8018-749430922274.412023-06-01
56ABN TOWER2008-13호2013-03-212008-12-23경기도 성남시 분당구 삼평동 690경기도 성남시 분당구 판교로 323 (삼평동)㈜아름방송네트워크070-8145-1255251321787.442023-06-01
67벤처포럼 벤처타워2023-6호2013-03-212023-03-15경기도 성남시 분당구 삼평동 690경기도 성남시 분당구 판교로 323 (삼평동)벤처포럼비아이㈜070-7124-35796315071.02023-06-01
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