Overview

Dataset statistics

Number of variables16
Number of observations63
Missing cells6
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory136.1 B

Variable types

Numeric5
Categorical4
Text5
DateTime2

Dataset

Description구분자(PK),중분류 코드,중분류,그룹레벨 코드,그룹레벨,기업명,지정기간 시작일,지정기간 종료일,기업 웹사이트주소,기업 요약소개,상세주소,위치(위도,경도),위도,경도,생성일시,수정일시
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21094/S/1/datasetView.do

Alerts

중분류 코드 is highly overall correlated with 중분류High correlation
중분류 is highly overall correlated with 중분류 코드High correlation
그룹레벨 코드 is highly overall correlated with 그룹레벨High correlation
그룹레벨 is highly overall correlated with 그룹레벨 코드High correlation
구분자(PK) is highly overall correlated with 생성일시High correlation
생성일시 is highly overall correlated with 구분자(PK)High correlation
기업 웹사이트주소 has 2 (3.2%) missing valuesMissing
수정일시 has 4 (6.3%) missing valuesMissing
구분자(PK) has unique valuesUnique
기업 요약소개 has unique valuesUnique
상세주소 has unique valuesUnique
생성일시 has unique valuesUnique

Reproduction

Analysis started2024-04-29 20:58:41.810986
Analysis finished2024-04-29 20:58:46.617137
Duration4.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분자(PK)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259.36508
Minimum227
Maximum291
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-30T05:58:46.684344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum227
5-th percentile230.1
Q1242.5
median260
Q3275.5
95-th percentile287.9
Maximum291
Range64
Interquartile range (IQR)33

Descriptive statistics

Standard deviation19.090026
Coefficient of variation (CV)0.073602914
Kurtosis-1.2161962
Mean259.36508
Median Absolute Deviation (MAD)17
Skewness-0.050944863
Sum16340
Variance364.42908
MonotonicityStrictly decreasing
2024-04-30T05:58:46.798403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
291 1
 
1.6%
290 1
 
1.6%
257 1
 
1.6%
256 1
 
1.6%
255 1
 
1.6%
254 1
 
1.6%
253 1
 
1.6%
252 1
 
1.6%
251 1
 
1.6%
249 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
227 1
1.6%
228 1
1.6%
229 1
1.6%
230 1
1.6%
231 1
1.6%
232 1
1.6%
233 1
1.6%
234 1
1.6%
235 1
1.6%
236 1
1.6%
ValueCountFrequency (%)
291 1
1.6%
290 1
1.6%
289 1
1.6%
288 1
1.6%
287 1
1.6%
286 1
1.6%
285 1
1.6%
284 1
1.6%
283 1
1.6%
282 1
1.6%

중분류 코드
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
6
28 
7
16 
5
14 
8
4 
9
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row7
2nd row5
3rd row7
4th row5
5th row6

Common Values

ValueCountFrequency (%)
6 28
44.4%
7 16
25.4%
5 14
22.2%
8 4
 
6.3%
9 1
 
1.6%

Length

2024-04-30T05:58:46.915747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:58:47.022384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6 28
44.4%
7 16
25.4%
5 14
22.2%
8 4
 
6.3%
9 1
 
1.6%

중분류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
공간
28 
재능,지식
16 
물품
14 
데이터
4 
이동수단
 
1

Length

Max length5
Median length2
Mean length2.8571429
Min length2

Unique

Unique1 ?
Unique (%)1.6%

Sample

1st row재능,지식
2nd row물품
3rd row재능,지식
4th row물품
5th row공간

Common Values

ValueCountFrequency (%)
공간 28
44.4%
재능,지식 16
25.4%
물품 14
22.2%
데이터 4
 
6.3%
이동수단 1
 
1.6%

Length

2024-04-30T05:58:47.118150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:58:47.210385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공간 28
44.4%
재능,지식 16
25.4%
물품 14
22.2%
데이터 4
 
6.3%
이동수단 1
 
1.6%

그룹레벨 코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
C1
50 
C2
13 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowC2
2nd rowC2
3rd rowC1
4th rowC1
5th rowC1

Common Values

ValueCountFrequency (%)
C1 50
79.4%
C2 13
 
20.6%

Length

2024-04-30T05:58:47.515812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:58:47.604606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c1 50
79.4%
c2 13
 
20.6%

그룹레벨
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
기업
50 
단체-비영리기관
13 

Length

Max length8
Median length2
Mean length3.2380952
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단체-비영리기관
2nd row단체-비영리기관
3rd row기업
4th row기업
5th row기업

Common Values

ValueCountFrequency (%)
기업 50
79.4%
단체-비영리기관 13
 
20.6%

Length

2024-04-30T05:58:47.701121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:58:47.781343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기업 50
79.4%
단체-비영리기관 13
 
20.6%

기업명
Text

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-04-30T05:58:47.943918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.9365079
Min length2

Characters and Unicode

Total characters563
Distinct characters183
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)96.8%

Sample

1st row사단법인 성북청년시민회
2nd row사회복지법인 한벗재단
3rd row문화예술협동조합 몽당
4th row(주)펴다
5th row주식회사 옐로우클립
ValueCountFrequency (%)
주식회사 14
 
15.2%
사회적협동조합 7
 
7.6%
마을발전소 2
 
2.2%
도시재생 2
 
2.2%
사단법인 2
 
2.2%
주차장만드는사람들(주 1
 
1.1%
건강한농부사회적협동조합 1
 
1.1%
히든북 1
 
1.1%
주)선랩건축사사무소 1
 
1.1%
협동조합고개엔마을 1
 
1.1%
Other values (60) 60
65.2%
2024-04-30T05:58:48.292625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 34
 
6.0%
주 34
 
6.0%
29
 
5.2%
회 26
 
4.6%
) 20
 
3.6%
( 20
 
3.6%
식 15
 
2.7%
조 14
 
2.5%
합 14
 
2.5%
협 13
 
2.3%
Other values (173) 344
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 484
86.0%
Space Separator 29
 
5.2%
Close Punctuation 20
 
3.6%
Open Punctuation 20
 
3.6%
Uppercase Letter 6
 
1.1%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%
Other Symbol 1
 
0.2%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 34
 
7.0%
주 34
 
7.0%
회 26
 
5.4%
식 15
 
3.1%
조 14
 
2.9%
합 14
 
2.9%
협 13
 
2.7%
동 13
 
2.7%
이 9
 
1.9%
적 9
 
1.9%
Other values (161) 303
62.6%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
R 1
16.7%
I 1
16.7%
D 1
16.7%
W 1
16.7%
Space Separator
ValueCountFrequency (%)
29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
! 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 485
86.1%
Common 72
 
12.8%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 34
 
7.0%
주 34
 
7.0%
회 26
 
5.4%
식 15
 
3.1%
조 14
 
2.9%
합 14
 
2.9%
협 13
 
2.7%
동 13
 
2.7%
이 9
 
1.9%
적 9
 
1.9%
Other values (162) 304
62.7%
Common
ValueCountFrequency (%)
29
40.3%
) 20
27.8%
( 20
27.8%
- 1
 
1.4%
! 1
 
1.4%
2 1
 
1.4%
Latin
ValueCountFrequency (%)
E 2
33.3%
R 1
16.7%
I 1
16.7%
D 1
16.7%
W 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 484
86.0%
ASCII 78
 
13.9%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 34
 
7.0%
주 34
 
7.0%
회 26
 
5.4%
식 15
 
3.1%
조 14
 
2.9%
합 14
 
2.9%
협 13
 
2.7%
동 13
 
2.7%
이 9
 
1.9%
적 9
 
1.9%
Other values (161) 303
62.6%
ASCII
ValueCountFrequency (%)
29
37.2%
) 20
25.6%
( 20
25.6%
E 2
 
2.6%
R 1
 
1.3%
I 1
 
1.3%
- 1
 
1.3%
D 1
 
1.3%
W 1
 
1.3%
! 1
 
1.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

지정기간 시작일
Date

Distinct19
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum2013-08-21 00:00:00
Maximum2023-06-01 00:00:00
2024-04-30T05:58:48.402970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:48.501326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

지정기간 종료일
Date

Distinct15
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum2022-05-07 00:00:00
Maximum2026-05-31 00:00:00
2024-04-30T05:58:48.607820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:48.727605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

기업 웹사이트주소
Text

MISSING 

Distinct58
Distinct (%)95.1%
Missing2
Missing (%)3.2%
Memory size636.0 B
2024-04-30T05:58:48.965156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length27
Mean length21.262295
Min length9

Characters and Unicode

Total characters1297
Distinct characters42
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)90.2%

Sample

1st rowwww.bibil.co
2nd rowhttp://www.hanbeot.org/
3rd rowhttp://www.pyeoda.co.kr
4th rowhttps://theaterplot.oopy.io/
5th rowwww.hummingb.co.kr
ValueCountFrequency (%)
https://www.moduparking.com 2
 
3.3%
www.i-baby.co.kr 2
 
3.3%
www.hummingb.co.kr 2
 
3.3%
http://되살림.org 1
 
1.6%
www.wetourplus.com 1
 
1.6%
https://farmerscoops.wixsite.com/mysite 1
 
1.6%
www.hiddenbook.co.kr 1
 
1.6%
https://theopencloset.net 1
 
1.6%
www.ahaclass.co.kr 1
 
1.6%
https://cafe.naver.com/sungmisansm 1
 
1.6%
Other values (48) 48
78.7%
2024-04-30T05:58:49.439312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 116
 
8.9%
w 108
 
8.3%
t 105
 
8.1%
/ 101
 
7.8%
o 99
 
7.6%
c 63
 
4.9%
h 63
 
4.9%
s 61
 
4.7%
a 54
 
4.2%
r 52
 
4.0%
Other values (32) 475
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1020
78.6%
Other Punctuation 254
 
19.6%
Decimal Number 16
 
1.2%
Dash Punctuation 4
 
0.3%
Other Letter 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 108
 
10.6%
t 105
 
10.3%
o 99
 
9.7%
c 63
 
6.2%
h 63
 
6.2%
s 61
 
6.0%
a 54
 
5.3%
r 52
 
5.1%
m 51
 
5.0%
p 51
 
5.0%
Other values (16) 313
30.7%
Decimal Number
ValueCountFrequency (%)
6 3
18.8%
5 2
12.5%
4 2
12.5%
9 2
12.5%
1 2
12.5%
2 2
12.5%
7 1
 
6.2%
3 1
 
6.2%
0 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 116
45.7%
/ 101
39.8%
: 37
 
14.6%
Other Letter
ValueCountFrequency (%)
되 1
33.3%
살 1
33.3%
림 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1020
78.6%
Common 274
 
21.1%
Hangul 3
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 108
 
10.6%
t 105
 
10.3%
o 99
 
9.7%
c 63
 
6.2%
h 63
 
6.2%
s 61
 
6.0%
a 54
 
5.3%
r 52
 
5.1%
m 51
 
5.0%
p 51
 
5.0%
Other values (16) 313
30.7%
Common
ValueCountFrequency (%)
. 116
42.3%
/ 101
36.9%
: 37
 
13.5%
- 4
 
1.5%
6 3
 
1.1%
5 2
 
0.7%
4 2
 
0.7%
9 2
 
0.7%
1 2
 
0.7%
2 2
 
0.7%
Other values (3) 3
 
1.1%
Hangul
ValueCountFrequency (%)
되 1
33.3%
살 1
33.3%
림 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1294
99.8%
Hangul 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 116
 
9.0%
w 108
 
8.3%
t 105
 
8.1%
/ 101
 
7.8%
o 99
 
7.7%
c 63
 
4.9%
h 63
 
4.9%
s 61
 
4.7%
a 54
 
4.2%
r 52
 
4.0%
Other values (29) 472
36.5%
Hangul
ValueCountFrequency (%)
되 1
33.3%
살 1
33.3%
림 1
33.3%

기업 요약소개
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-04-30T05:58:49.748470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length72
Mean length57.777778
Min length10

Characters and Unicode

Total characters3640
Distinct characters434
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

Unique63 ?
Unique (%)100.0%

Sample

1st row청년들이 지역사회에서 안전하고 안정적으로 살 수 있는 방법을 고민합니다. 서로의 환대와 연대가 사회를 바꾸어 나갈 수 있다고 믿습니다.
2nd row장애인 시설 운영 및 빈곤국 유아차, 휠체어 기증사업 등의 사회사업을 수행하는 사회복지법인입니다.
3rd row문화예술을 기반으로 행사와 교육 서비스를 제공합니다.
4th row[무인 스마트 우산공유 서비스 '펴다'] 누적 280만톤 유해가스와 4천억원 손실 '우산 파생 쓰레기'를 해결
5th row옐로우클립은 자생가능한 예술생태계 조성과 문화다양성 확보를 위한 복합문화공간 PLOT을 운영합니다.
ValueCountFrequency (%)
14
 
1.7%
수 11
 
1.4%
위한 10
 
1.2%
및 9
 
1.1%
있는 8
 
1.0%
통해 8
 
1.0%
플랫폼 7
 
0.9%
공간을 6
 
0.7%
서비스 6
 
0.7%
함께 6
 
0.7%
Other values (627) 729
89.6%
2024-04-30T05:58:50.128365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
765
 
21.0%
공 71
 
2.0%
을 66
 
1.8%
는 54
 
1.5%
다 52
 
1.4%
하 52
 
1.4%
의 52
 
1.4%
. 50
 
1.4%
니 48
 
1.3%
고 45
 
1.2%
Other values (424) 2385
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2663
73.2%
Space Separator 765
 
21.0%
Other Punctuation 116
 
3.2%
Decimal Number 25
 
0.7%
Lowercase Letter 21
 
0.6%
Uppercase Letter 16
 
0.4%
Math Symbol 9
 
0.2%
Close Punctuation 7
 
0.2%
Open Punctuation 7
 
0.2%
Final Punctuation 4
 
0.1%
Other values (2) 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 71
 
2.7%
을 66
 
2.5%
는 54
 
2.0%
다 52
 
2.0%
하 52
 
2.0%
의 52
 
2.0%
니 48
 
1.8%
고 45
 
1.7%
한 45
 
1.7%
유 44
 
1.7%
Other values (375) 2134
80.1%
Uppercase Letter
ValueCountFrequency (%)
S 3
18.8%
I 2
12.5%
T 2
12.5%
A 2
12.5%
D 1
 
6.2%
G 1
 
6.2%
P 1
 
6.2%
L 1
 
6.2%
O 1
 
6.2%
B 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 7
28.0%
2 5
20.0%
0 5
20.0%
9 2
 
8.0%
5 2
 
8.0%
3 1
 
4.0%
4 1
 
4.0%
8 1
 
4.0%
6 1
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
b 5
23.8%
r 5
23.8%
o 3
14.3%
l 2
 
9.5%
e 2
 
9.5%
u 1
 
4.8%
i 1
 
4.8%
n 1
 
4.8%
p 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 50
43.1%
, 42
36.2%
' 12
 
10.3%
/ 5
 
4.3%
! 3
 
2.6%
? 2
 
1.7%
& 2
 
1.7%
Math Symbol
ValueCountFrequency (%)
> 4
44.4%
< 4
44.4%
+ 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 6
85.7%
] 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 6
85.7%
[ 1
 
14.3%
Final Punctuation
ValueCountFrequency (%)
’ 3
75.0%
” 1
 
25.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 3
75.0%
“ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
765
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2663
73.2%
Common 940
 
25.8%
Latin 37
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 71
 
2.7%
을 66
 
2.5%
는 54
 
2.0%
다 52
 
2.0%
하 52
 
2.0%
의 52
 
2.0%
니 48
 
1.8%
고 45
 
1.7%
한 45
 
1.7%
유 44
 
1.7%
Other values (375) 2134
80.1%
Common
ValueCountFrequency (%)
765
81.4%
. 50
 
5.3%
, 42
 
4.5%
' 12
 
1.3%
1 7
 
0.7%
) 6
 
0.6%
( 6
 
0.6%
/ 5
 
0.5%
2 5
 
0.5%
0 5
 
0.5%
Other values (19) 37
 
3.9%
Latin
ValueCountFrequency (%)
b 5
13.5%
r 5
13.5%
S 3
 
8.1%
o 3
 
8.1%
l 2
 
5.4%
I 2
 
5.4%
T 2
 
5.4%
A 2
 
5.4%
e 2
 
5.4%
u 1
 
2.7%
Other values (10) 10
27.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2661
73.1%
ASCII 969
 
26.6%
Punctuation 8
 
0.2%
Compat Jamo 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
765
78.9%
. 50
 
5.2%
, 42
 
4.3%
' 12
 
1.2%
1 7
 
0.7%
) 6
 
0.6%
( 6
 
0.6%
/ 5
 
0.5%
2 5
 
0.5%
0 5
 
0.5%
Other values (35) 66
 
6.8%
Hangul
ValueCountFrequency (%)
공 71
 
2.7%
을 66
 
2.5%
는 54
 
2.0%
다 52
 
2.0%
하 52
 
2.0%
의 52
 
2.0%
니 48
 
1.8%
고 45
 
1.7%
한 45
 
1.7%
유 44
 
1.7%
Other values (374) 2132
80.1%
Punctuation
ValueCountFrequency (%)
’ 3
37.5%
‘ 3
37.5%
“ 1
 
12.5%
” 1
 
12.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

상세주소
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-04-30T05:58:50.390664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length28
Mean length20.52381
Min length6

Characters and Unicode

Total characters1293
Distinct characters188
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

Unique63 ?
Unique (%)100.0%

Sample

1st row서울특별시 성북구 종암로 25길 29, 성북구마을사회적경제센터
2nd row효창원로69길 42-3
3rd row서울특별시 성북구 종암동 80-8
4th row서울특별시 종로구 종로 6, 광화문 우체국 6층 스타트업빌리지
5th row연세로4길 27
ValueCountFrequency (%)
서울특별시 32
 
11.8%
서울시 8
 
2.9%
강남구 7
 
2.6%
마포구 6
 
2.2%
성동구 6
 
2.2%
3층 5
 
1.8%
성북구 4
 
1.5%
구로구 3
 
1.1%
통일로 3
 
1.1%
684 3
 
1.1%
Other values (170) 195
71.7%
2024-04-30T05:58:50.801754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
213
 
16.5%
서 52
 
4.0%
로 50
 
3.9%
1 49
 
3.8%
구 48
 
3.7%
울 44
 
3.4%
2 44
 
3.4%
시 42
 
3.2%
3 34
 
2.6%
별 32
 
2.5%
Other values (178) 685
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 757
58.5%
Decimal Number 281
 
21.7%
Space Separator 213
 
16.5%
Dash Punctuation 19
 
1.5%
Other Punctuation 19
 
1.5%
Uppercase Letter 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 52
 
6.9%
로 50
 
6.6%
구 48
 
6.3%
울 44
 
5.8%
시 42
 
5.5%
별 32
 
4.2%
특 32
 
4.2%
동 27
 
3.6%
길 27
 
3.6%
성 15
 
2.0%
Other values (160) 388
51.3%
Decimal Number
ValueCountFrequency (%)
1 49
17.4%
2 44
15.7%
3 34
12.1%
6 30
10.7%
4 29
10.3%
0 27
9.6%
7 20
7.1%
8 20
7.1%
5 17
 
6.0%
9 11
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 16
84.2%
' 2
 
10.5%
. 1
 
5.3%
Space Separator
ValueCountFrequency (%)
213
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 757
58.5%
Common 534
41.3%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 52
 
6.9%
로 50
 
6.6%
구 48
 
6.3%
울 44
 
5.8%
시 42
 
5.5%
별 32
 
4.2%
특 32
 
4.2%
동 27
 
3.6%
길 27
 
3.6%
성 15
 
2.0%
Other values (160) 388
51.3%
Common
ValueCountFrequency (%)
213
39.9%
1 49
 
9.2%
2 44
 
8.2%
3 34
 
6.4%
6 30
 
5.6%
4 29
 
5.4%
0 27
 
5.1%
7 20
 
3.7%
8 20
 
3.7%
- 19
 
3.6%
Other values (7) 49
 
9.2%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 757
58.5%
ASCII 536
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
213
39.7%
1 49
 
9.1%
2 44
 
8.2%
3 34
 
6.3%
6 30
 
5.6%
4 29
 
5.4%
0 27
 
5.0%
7 20
 
3.7%
8 20
 
3.7%
- 19
 
3.5%
Other values (8) 51
 
9.5%
Hangul
ValueCountFrequency (%)
서 52
 
6.9%
로 50
 
6.6%
구 48
 
6.3%
울 44
 
5.8%
시 42
 
5.5%
별 32
 
4.2%
특 32
 
4.2%
동 27
 
3.6%
길 27
 
3.6%
성 15
 
2.0%
Other values (160) 388
51.3%

위치(위도,경도)
Text

Distinct58
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-04-30T05:58:51.021023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length21.873016
Min length20

Characters and Unicode

Total characters1378
Distinct characters12
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

Unique54 ?
Unique (%)85.7%

Sample

1st row37.600094,127.0314682
2nd row37.5428506,126.9601857
3rd row37.6001273,127.0315485
4th row37.5698231,126.9781051
5th row37.5576025,126.9382167
ValueCountFrequency (%)
37.6087643,126.9341572 3
 
4.8%
37.5595913,126.9672256 2
 
3.2%
37.5466768,126.9497275 2
 
3.2%
37.6001273,127.0315485 2
 
3.2%
37.5586021,126.9097046 1
 
1.6%
37.5130574,126.8833545 1
 
1.6%
37.600094,127.0314682 1
 
1.6%
37.4799926,126.8770398 1
 
1.6%
37.5535252,126.9217041 1
 
1.6%
37.5576685,126.9258931 1
 
1.6%
Other values (48) 48
76.2%
2024-04-30T05:58:51.360528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 157
11.4%
2 139
10.1%
1 136
9.9%
3 133
9.7%
5 131
9.5%
. 126
9.1%
6 116
8.4%
9 110
8.0%
8 93
6.7%
4 89
6.5%
Other values (2) 148
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1189
86.3%
Other Punctuation 189
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 157
13.2%
2 139
11.7%
1 136
11.4%
3 133
11.2%
5 131
11.0%
6 116
9.8%
9 110
9.3%
8 93
7.8%
4 89
7.5%
0 85
7.1%
Other Punctuation
ValueCountFrequency (%)
. 126
66.7%
, 63
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1378
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 157
11.4%
2 139
10.1%
1 136
9.9%
3 133
9.7%
5 131
9.5%
. 126
9.1%
6 116
8.4%
9 110
8.0%
8 93
6.7%
4 89
6.5%
Other values (2) 148
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1378
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 157
11.4%
2 139
10.1%
1 136
9.9%
3 133
9.7%
5 131
9.5%
. 126
9.1%
6 116
8.4%
9 110
8.0%
8 93
6.7%
4 89
6.5%
Other values (2) 148
10.7%

위도
Real number (ℝ)

Distinct58
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.545411
Minimum37.453554
Maximum37.619195
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-30T05:58:51.510578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.453554
5-th percentile37.484143
Q137.512851
median37.546751
Q337.566213
95-th percentile37.608764
Maximum37.619195
Range0.165641
Interquartile range (IQR)0.05336185

Descriptive statistics

Standard deviation0.037340908
Coefficient of variation (CV)0.00099455316
Kurtosis-0.28625179
Mean37.545411
Median Absolute Deviation (MAD)0.0230723
Skewness-0.14460275
Sum2365.3609
Variance0.0013943434
MonotonicityNot monotonic
2024-04-30T05:58:51.629875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6087643 3
 
4.8%
37.6001273 2
 
3.2%
37.5595913 2
 
3.2%
37.5466768 2
 
3.2%
37.600094 1
 
1.6%
37.4799926 1
 
1.6%
37.5535252 1
 
1.6%
37.5576685 1
 
1.6%
37.4535542 1
 
1.6%
37.4714486 1
 
1.6%
Other values (48) 48
76.2%
ValueCountFrequency (%)
37.4535542 1
1.6%
37.4714486 1
1.6%
37.4799926 1
1.6%
37.4833911 1
1.6%
37.4909121 1
1.6%
37.4965038 1
1.6%
37.497379 1
1.6%
37.4992676 1
1.6%
37.5020509 1
1.6%
37.5054829 1
1.6%
ValueCountFrequency (%)
37.6191952 1
 
1.6%
37.6138919 1
 
1.6%
37.6087643 3
4.8%
37.6001273 2
3.2%
37.600094 1
 
1.6%
37.5925158 1
 
1.6%
37.5804888 1
 
1.6%
37.5723808 1
 
1.6%
37.5703467 1
 
1.6%
37.5698231 1
 
1.6%

경도
Real number (ℝ)

Distinct58
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97629
Minimum126.85684
Maximum127.13146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-30T05:58:51.743941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.85684
5-th percentile126.88034
Q1126.93003
median126.96723
Q3127.03086
95-th percentile127.06139
Maximum127.13146
Range0.2746285
Interquartile range (IQR)0.1008354

Descriptive statistics

Standard deviation0.063034727
Coefficient of variation (CV)0.00049642912
Kurtosis-0.89650197
Mean126.97629
Median Absolute Deviation (MAD)0.0578929
Skewness0.077111246
Sum7999.5062
Variance0.0039733768
MonotonicityNot monotonic
2024-04-30T05:58:51.898569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9341572 3
 
4.8%
127.0315485 2
 
3.2%
126.9672256 2
 
3.2%
126.9497275 2
 
3.2%
127.0314682 1
 
1.6%
126.8770398 1
 
1.6%
126.9217041 1
 
1.6%
126.9258931 1
 
1.6%
126.8990001 1
 
1.6%
126.9403638 1
 
1.6%
Other values (48) 48
76.2%
ValueCountFrequency (%)
126.8568355 1
1.6%
126.8739936 1
1.6%
126.8770398 1
1.6%
126.8800019 1
1.6%
126.8833545 1
1.6%
126.8950314 1
1.6%
126.8964263 1
1.6%
126.8968868 1
1.6%
126.8975368 1
1.6%
126.8990001 1
1.6%
ValueCountFrequency (%)
127.131464 1
1.6%
127.0811867 1
1.6%
127.0672043 1
1.6%
127.0618985 1
1.6%
127.0568389 1
1.6%
127.0499022 1
1.6%
127.0482567 1
1.6%
127.0469759 1
1.6%
127.0465885 1
1.6%
127.0441214 1
1.6%

생성일시
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0214255 × 1013
Minimum2.0210611 × 1013
Maximum2.0230804 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-30T05:58:52.020023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210611 × 1013
5-th percentile2.0210611 × 1013
Q12.0210623 × 1013
median2.0210625 × 1013
Q32.0210702 × 1013
95-th percentile2.0230681 × 1013
Maximum2.0230804 × 1013
Range2.0193007 × 1010
Interquartile range (IQR)79475167

Descriptive statistics

Standard deviation7.1965919 × 109
Coefficient of variation (CV)0.00035601569
Kurtosis1.0853316
Mean2.0214255 × 1013
Median Absolute Deviation (MAD)7065383
Skewness1.6683679
Sum1.2734981 × 1015
Variance5.1790935 × 1019
MonotonicityStrictly decreasing
2024-04-30T05:58:52.154886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230804153316 1
 
1.6%
20230801150425 1
 
1.6%
20210625153621 1
 
1.6%
20210625153401 1
 
1.6%
20210625134548 1
 
1.6%
20210625122128 1
 
1.6%
20210624175757 1
 
1.6%
20210624102948 1
 
1.6%
20210623202948 1
 
1.6%
20210623182239 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
20210611145835 1
1.6%
20210611160912 1
1.6%
20210611171931 1
1.6%
20210611173417 1
1.6%
20210611184237 1
1.6%
20210614105407 1
1.6%
20210616152952 1
1.6%
20210616155227 1
1.6%
20210616164638 1
1.6%
20210617153838 1
1.6%
ValueCountFrequency (%)
20230804153316 1
1.6%
20230801150425 1
1.6%
20230728124704 1
1.6%
20230721164250 1
1.6%
20230320152558 1
1.6%
20230220163826 1
1.6%
20230213142710 1
1.6%
20230208154409 1
1.6%
20230201101353 1
1.6%
20220616161148 1
1.6%

수정일시
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)100.0%
Missing4
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean2.0215764 × 1013
Minimum2.0210611 × 1013
Maximum2.0230825 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-04-30T05:58:52.291504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0210611 × 1013
5-th percentile2.021063 × 1013
Q12.0210702 × 1013
median2.0210712 × 1013
Q32.0220606 × 1013
95-th percentile2.0230801 × 1013
Maximum2.0230825 × 1013
Range2.0213932 × 1010
Interquartile range (IQR)9.9045487 × 109

Descriptive statistics

Standard deviation7.920533 × 109
Coefficient of variation (CV)0.00039179983
Kurtosis-0.39877971
Mean2.0215764 × 1013
Median Absolute Deviation (MAD)11019554
Skewness1.1461157
Sum1.1927301 × 1015
Variance6.2734843 × 1019
MonotonicityNot monotonic
2024-04-30T05:58:52.419235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230801154351 1
 
1.6%
20220616074353 1
 
1.6%
20210723184058 1
 
1.6%
20210723103250 1
 
1.6%
20210713091545 1
 
1.6%
20220523155935 1
 
1.6%
20210702105118 1
 
1.6%
20210709101714 1
 
1.6%
20210701154621 1
 
1.6%
20210701174253 1
 
1.6%
Other values (49) 49
77.8%
(Missing) 4
 
6.3%
ValueCountFrequency (%)
20210611171953 1
1.6%
20210616165443 1
1.6%
20210628154149 1
1.6%
20210630151931 1
1.6%
20210630153703 1
1.6%
20210701145800 1
1.6%
20210701154621 1
1.6%
20210701154823 1
1.6%
20210701155652 1
1.6%
20210701160615 1
1.6%
ValueCountFrequency (%)
20230825103611 1
1.6%
20230807161055 1
1.6%
20230801164519 1
1.6%
20230801154351 1
1.6%
20230801150954 1
1.6%
20230728124737 1
1.6%
20230724151621 1
1.6%
20230721164358 1
1.6%
20230323093911 1
1.6%
20230213143244 1
1.6%

Interactions

2024-04-30T05:58:45.842069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.078478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.572640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.997778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.393190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.923351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.211335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.655667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.072903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.480811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:46.012967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.300959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.738923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.159037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.569665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:46.088366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.378138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.809796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.226419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.649619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:46.170103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.476448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:44.908395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.307929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:58:45.738317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T05:58:52.510078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분자(PK)중분류 코드중분류그룹레벨 코드그룹레벨기업명지정기간 시작일지정기간 종료일기업 웹사이트주소기업 요약소개상세주소위치(위도,경도)위도경도생성일시수정일시
구분자(PK)1.0000.2850.2850.6950.6950.9510.6640.6450.7921.0001.0000.6610.1490.5430.8720.724
중분류 코드0.2851.0001.0000.2190.2191.0000.0000.0001.0001.0001.0000.8750.3690.0000.0000.000
중분류0.2851.0001.0000.2190.2191.0000.0000.0001.0001.0001.0000.8750.3690.0000.0000.000
그룹레벨 코드0.6950.2190.2191.0000.9971.0000.0000.0001.0001.0001.0000.6960.0000.3900.0310.000
그룹레벨0.6950.2190.2190.9971.0001.0000.0000.0001.0001.0001.0000.6960.0000.3900.0310.000
기업명0.9511.0001.0001.0001.0001.0000.9830.9720.9921.0001.0000.9910.9391.0000.0000.653
지정기간 시작일0.6640.0000.0000.0000.0000.9831.0000.9930.0001.0001.0000.0000.0000.5730.7920.942
지정기간 종료일0.6450.0000.0000.0000.0000.9720.9931.0000.9541.0001.0000.0000.3760.6650.8940.990
기업 웹사이트주소0.7921.0001.0001.0001.0000.9920.0000.9541.0001.0001.0000.9911.0001.0000.0000.572
기업 요약소개1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상세주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위치(위도,경도)0.6610.8750.8750.6960.6960.9910.0000.0000.9911.0001.0001.0001.0001.0000.8130.707
위도0.1490.3690.3690.0000.0000.9390.0000.3761.0001.0001.0001.0001.0000.5990.0000.453
경도0.5430.0000.0000.3900.3901.0000.5730.6651.0001.0001.0001.0000.5991.0000.0000.174
생성일시0.8720.0000.0000.0310.0310.0000.7920.8940.0001.0001.0000.8130.0000.0001.0000.948
수정일시0.7240.0000.0000.0000.0000.6530.9420.9900.5721.0001.0000.7070.4530.1740.9481.000
2024-04-30T05:58:52.642711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
중분류 코드중분류그룹레벨 코드그룹레벨
중분류 코드1.0001.0000.2590.259
중분류1.0001.0000.2590.259
그룹레벨 코드0.2590.2591.0000.951
그룹레벨0.2590.2590.9511.000
2024-04-30T05:58:52.722739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분자(PK)위도경도생성일시수정일시중분류 코드중분류그룹레벨 코드그룹레벨
구분자(PK)1.0000.0030.0591.0000.4280.1360.1360.4980.498
위도0.0031.000-0.0190.0030.1500.1470.1470.0000.000
경도0.059-0.0191.0000.0590.1270.0000.0000.2750.275
생성일시1.0000.0030.0591.0000.4280.0000.0000.0500.050
수정일시0.4280.1500.1270.4281.0000.0000.0000.0000.000
중분류 코드0.1360.1470.0000.0000.0001.0001.0000.2590.259
중분류0.1360.1470.0000.0000.0001.0001.0000.2590.259
그룹레벨 코드0.4980.0000.2750.0500.0000.2590.2591.0000.951
그룹레벨0.4980.0000.2750.0500.0000.2590.2590.9511.000

Missing values

2024-04-30T05:58:46.296057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T05:58:46.462322image/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.
2024-04-30T05:58:46.570194image/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

구분자(PK)중분류 코드중분류그룹레벨 코드그룹레벨기업명지정기간 시작일지정기간 종료일기업 웹사이트주소기업 요약소개상세주소위치(위도,경도)위도경도생성일시수정일시
02917재능,지식C2단체-비영리기관사단법인 성북청년시민회2023-06-012026-05-31www.bibil.co청년들이 지역사회에서 안전하고 안정적으로 살 수 있는 방법을 고민합니다. 서로의 환대와 연대가 사회를 바꾸어 나갈 수 있다고 믿습니다.서울특별시 성북구 종암로 25길 29, 성북구마을사회적경제센터37.600094,127.031468237.600094127.0314682023080415331620230807161055
12905물품C2단체-비영리기관사회복지법인 한벗재단2023-06-012026-05-31http://www.hanbeot.org/장애인 시설 운영 및 빈곤국 유아차, 휠체어 기증사업 등의 사회사업을 수행하는 사회복지법인입니다.효창원로69길 42-337.5428506,126.960185737.542851126.9601862023080115042520230801154351
22897재능,지식C1기업문화예술협동조합 몽당2023-06-012026-05-31<NA>문화예술을 기반으로 행사와 교육 서비스를 제공합니다.서울특별시 성북구 종암동 80-837.6001273,127.031548537.600127127.0315482023072812470420230728124737
32885물품C1기업(주)펴다2023-06-012026-05-31http://www.pyeoda.co.kr[무인 스마트 우산공유 서비스 '펴다'] 누적 280만톤 유해가스와 4천억원 손실 '우산 파생 쓰레기'를 해결서울특별시 종로구 종로 6, 광화문 우체국 6층 스타트업빌리지37.5698231,126.978105137.569823126.9781052023072116425020230721164358
42876공간C1기업주식회사 옐로우클립2022-12-202025-12-19https://theaterplot.oopy.io/옐로우클립은 자생가능한 예술생태계 조성과 문화다양성 확보를 위한 복합문화공간 PLOT을 운영합니다.연세로4길 2737.5576025,126.938216737.557603126.93821720230320152558<NA>
52867재능,지식C1기업주식회사허밍비2022-12-202025-12-19www.hummingb.co.kr소셜벤처 허밍비는 1인가구를 위한 라이프 큐레이터로서 자유롭고 유쾌한 삶을 함께 만들어 갑니다.서울특별시 중구 서소문로6길 3437.5595913,126.967225637.559591126.96722620230220163826<NA>
62857재능,지식C2단체-비영리기관마을발전소 사회적협동조합2022-12-202025-12-19https://band.us/band/54799616동네에서 필요한 일은 무엇이든 이웃과 함께 사회적경제 방식으로 풀어가는 공동체입니다. 장난감병원을 통해 일자리를 만들고 환경을 살립니다.서울특별시 동작구 상도동 463-437.4992676,126.951650937.499268126.9516512023021314271020230213143244
72845물품C1기업주식회사 문샤인2022-12-202025-12-19www.i-baby.co.kr<엄마와 아이가 행복한 중고거래 플랫폼, 아이베이비!> 우리 아이와 우리 가족의 물건을 쉽게 정리하고 또 알뜰하게 채울 수 있는 안전한 중고마켓서울시 강남구 봉은사로129, 122137.5059195,127.02833937.505919127.02833920230208154409<NA>
82836공간C1기업㈜모두컴퍼니2022-12-202025-12-19https://www.moduparking.com/모두가 쓰는 쉽고 편리한 대한민국 1등 주차앱 ‘모두의주차장’을 운영하고 있는 (주)모두컴퍼니입니다.서울특별시 성동구 왕십리로 83-21, 디타워 3층37.5441547,127.043357737.544155127.0433582023020110135320230203114530
92825물품C1기업지와이아이엔씨 주식회사2020-05-272023-05-26www.zennycloset.com폐자원을 활용한 제로 탄소, 제로폐기물를 실천하고, 물 사용하지 않는 인쇄법으로 자원과 에너지를 아끼는 업사이클링 제품을 만듭니다.서울특별시 중구 소공로6길 13-7 2층37.5588872,126.983795937.558887126.9837962022061616114820220616161220
구분자(PK)중분류 코드중분류그룹레벨 코드그룹레벨기업명지정기간 시작일지정기간 종료일기업 웹사이트주소기업 요약소개상세주소위치(위도,경도)위도경도생성일시수정일시
532365물품C1기업(주)자락당-마켓인유2013-11-122022-05-07www.marketinu.com자락당은 자원 재순환 극대화를 통해 지속 가능한 소비 문화를 확대한다는 미션을 갖고 있는 사회적 기업이며 마켓인유를 운영하고 있습니다.서울특별시 성동구 아차산로 16637.5424996,127.061898537.5425127.0618982021061715383820210712180430
542358데이터C1기업에이에스엔2019-05-082022-05-07https://anyman.co.kr/서비스 중개 플랫폼서울특별시 구로구 구로동 222-737.4833911,126.896426337.483391126.8964262021061616463820210616165443
552346공간C1기업(주)페어스페이스2021-06-162023-12-31www.market-factory.com도시 유휴공간 공유시스템의 정착을 통한 청년창업, 여성 공예인, 사회적경제기업의 자립 지원통일로 684, 공유동 101호37.6087643,126.934157237.608764126.9341572021061615522720210701175906
562336공간C1기업(주)블루웨일컴퍼니2020-10-192023-10-18https://www.lugstay.com/상점의 빈 공간 이용해 언제 어디서나 물품의 보관, 배송, 픽업할 수 있도록 도와주는 '상점 유휴공간 중개 플랫폼'.청계천로 85 삼일빌딩 9층 블루웨일컴퍼니37.5686402,126.987159637.56864126.987162021061615295220210701164757
572326공간C2단체-비영리기관재단법인 홍합밸리2021-04-292024-04-28https://honghapvalley.org/스타트업 및 벤처기업을 위한 자생적 생태계를 구축하기 위해, 스타트업들이 자유롭고 소통하고 함께 공유하며 성장해나가는 공간을 제공한다.서울시 마포구 월드컵북로4길 7737.5593929,126.922668437.559393126.9226682021061410540720210713110551
582317재능,지식C1기업주식회사 허밍비2016-09-262022-09-03www.hummingb.co.kr1인가구와 노인세대의 외로움ㆍ고립감을 해소하기 위해 기술과 중장년층의 재능ㆍ지식 공유를 통한 사회관계망 조성하며 일상의 즐거움을 만들어갑니다.서울특별시 서소문로6길 34, 105호37.5595913,126.967225637.559591126.9672262021061118423720210701182047
592305물품C1기업되살림사회적협동조합2023-06-012026-05-31http://되살림.org- 기부와 수리수선 등을 통한 재이용품 판매<br> - 친환경 및 무포장제품 판매<br> - 자원순환의 인식개선과 확산을 위한 홍보 및 교육서울특별시 노원구 화랑로 486, 1층 되살림물류센터37.6191952,127.081186737.619195127.0811872021061117341720230801150954
602297재능,지식C2단체-비영리기관에이유디 사회적협동조합2021-04-292024-04-28http://audsc.org/소리를 보여주는 실시간 문자통역 쉐어타이핑 플랫폼으로 청각장애인 의사소통의 어려움 해소통일로 684 상상청 309호37.6087643,126.934157237.608764126.9341572021061117193120210611171953
612287재능,지식C1기업협동조합고개엔마을2023-06-012026-05-31https://blog.naver.com/hillnvill성북구를 중심으로 활동하는 문화예술 기반의 협동조합서울시 성북구 보문로34가길 2437.5925158,127.020280237.592516127.020282021061116091220230724151621
622277재능,지식C1기업(주)2교시2020-05-272023-05-26https://www.2gyosi.com직장인들을 위한 취미 공유 플랫폼서울시 강남구 언주로 432-8, 6층37.5020509,127.043993237.502051127.0439932021061114583520210702005350