Overview

Dataset statistics

Number of variables13
Number of observations155
Missing cells62
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory108.9 B

Variable types

Text5
Categorical5
Numeric3

Dataset

Description시설명,시설코드,시설종류명(시설유형),시설종류상세명(시설종류),자치구(시)구분,시설장명,시군구코드,시군구명,시설주소,정원(수용인원),현인원,전화번호,우편번호
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-20394/S/1/datasetView.do

Alerts

자치구(시)구분 has constant value ""Constant
시군구코드 has constant value ""Constant
시군구명 has constant value ""Constant
시설종류명(시설유형) is highly overall correlated with 현인원 and 1 other fieldsHigh correlation
시설종류상세명(시설종류) is highly overall correlated with 현인원 and 1 other fieldsHigh correlation
현인원 is highly overall correlated with 시설종류명(시설유형) and 1 other fieldsHigh correlation
정원(수용인원) has 16 (10.3%) missing valuesMissing
현인원 has 46 (29.7%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 26 (16.8%) zerosZeros

Reproduction

Analysis started2024-05-11 00:41:19.368006
Analysis finished2024-05-11 00:41:30.176010
Duration10.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct139
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:41:30.627352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length9.3806452
Min length3

Characters and Unicode

Total characters1454
Distinct characters221
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

Unique124 ?
Unique (%)80.0%

Sample

1st row혜명양로원
2nd row노인요양센터 인영실버
3rd row남부실버요양원
4th row청담노인복지센터
5th row섭리의집
ValueCountFrequency (%)
금천구 4
 
2.1%
지역아동센터 4
 
2.1%
금천한내어르신복지센터 3
 
1.5%
함사람지역아동센터 2
 
1.0%
우리동네키움센터(시흥1동 2
 
1.0%
요양원 2
 
1.0%
세림지역아동센터 2
 
1.0%
집 2
 
1.0%
강남가정요양원 2
 
1.0%
금천노인종합복지관 2
 
1.0%
Other values (156) 170
87.2%
2024-05-11T00:41:31.862946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 92
 
6.3%
센 90
 
6.2%
지 70
 
4.8%
동 56
 
3.9%
아 47
 
3.2%
금 44
 
3.0%
역 44
 
3.0%
천 42
 
2.9%
40
 
2.8%
어 28
 
1.9%
Other values (211) 901
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1368
94.1%
Space Separator 40
 
2.8%
Decimal Number 17
 
1.2%
Uppercase Letter 10
 
0.7%
Close Punctuation 9
 
0.6%
Open Punctuation 9
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 92
 
6.7%
센 90
 
6.6%
지 70
 
5.1%
동 56
 
4.1%
아 47
 
3.4%
금 44
 
3.2%
역 44
 
3.2%
천 42
 
3.1%
어 28
 
2.0%
원 27
 
2.0%
Other values (196) 828
60.5%
Uppercase Letter
ValueCountFrequency (%)
G 2
20.0%
S 2
20.0%
C 2
20.0%
A 1
10.0%
M 1
10.0%
E 1
10.0%
L 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 7
41.2%
4 4
23.5%
3 3
17.6%
2 3
17.6%
Space Separator
ValueCountFrequency (%)
40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1368
94.1%
Common 76
 
5.2%
Latin 10
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 92
 
6.7%
센 90
 
6.6%
지 70
 
5.1%
동 56
 
4.1%
아 47
 
3.4%
금 44
 
3.2%
역 44
 
3.2%
천 42
 
3.1%
어 28
 
2.0%
원 27
 
2.0%
Other values (196) 828
60.5%
Common
ValueCountFrequency (%)
40
52.6%
) 9
 
11.8%
( 9
 
11.8%
1 7
 
9.2%
4 4
 
5.3%
3 3
 
3.9%
2 3
 
3.9%
, 1
 
1.3%
Latin
ValueCountFrequency (%)
G 2
20.0%
S 2
20.0%
C 2
20.0%
A 1
10.0%
M 1
10.0%
E 1
10.0%
L 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1368
94.1%
ASCII 86
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 92
 
6.7%
센 90
 
6.6%
지 70
 
5.1%
동 56
 
4.1%
아 47
 
3.4%
금 44
 
3.2%
역 44
 
3.2%
천 42
 
3.1%
어 28
 
2.0%
원 27
 
2.0%
Other values (196) 828
60.5%
ASCII
ValueCountFrequency (%)
40
46.5%
) 9
 
10.5%
( 9
 
10.5%
1 7
 
8.1%
4 4
 
4.7%
3 3
 
3.5%
2 3
 
3.5%
G 2
 
2.3%
S 2
 
2.3%
C 2
 
2.3%
Other values (5) 5
 
5.8%

시설코드
Text

UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:41:32.795876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.083871
Min length5

Characters and Unicode

Total characters788
Distinct characters22
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

Unique155 ?
Unique (%)100.0%

Sample

1st rowA0019
2nd rowA0099
3rd rowA1307
4th rowA1980
5th rowA3167
ValueCountFrequency (%)
a0019 1
 
0.6%
g5788 1
 
0.6%
g8847 1
 
0.6%
g4592 1
 
0.6%
g4593 1
 
0.6%
g5193 1
 
0.6%
g5323 1
 
0.6%
g5409 1
 
0.6%
g5632 1
 
0.6%
g6471 1
 
0.6%
Other values (145) 145
93.5%
2024-05-11T00:41:34.323139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 83
10.5%
0 74
9.4%
3 71
9.0%
9 64
8.1%
4 64
8.1%
2 61
 
7.7%
6 57
 
7.2%
5 53
 
6.7%
7 53
 
6.7%
8 53
 
6.7%
Other values (12) 155
19.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 633
80.3%
Uppercase Letter 155
 
19.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 34
21.9%
B 27
17.4%
C 22
14.2%
K 21
13.5%
A 15
9.7%
F 15
9.7%
P 10
 
6.5%
Z 5
 
3.2%
W 3
 
1.9%
E 1
 
0.6%
Other values (2) 2
 
1.3%
Decimal Number
ValueCountFrequency (%)
1 83
13.1%
0 74
11.7%
3 71
11.2%
9 64
10.1%
4 64
10.1%
2 61
9.6%
6 57
9.0%
5 53
8.4%
7 53
8.4%
8 53
8.4%

Most occurring scripts

ValueCountFrequency (%)
Common 633
80.3%
Latin 155
 
19.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 34
21.9%
B 27
17.4%
C 22
14.2%
K 21
13.5%
A 15
9.7%
F 15
9.7%
P 10
 
6.5%
Z 5
 
3.2%
W 3
 
1.9%
E 1
 
0.6%
Other values (2) 2
 
1.3%
Common
ValueCountFrequency (%)
1 83
13.1%
0 74
11.7%
3 71
11.2%
9 64
10.1%
4 64
10.1%
2 61
9.6%
6 57
9.0%
5 53
8.4%
7 53
8.4%
8 53
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 788
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 83
10.5%
0 74
9.4%
3 71
9.0%
9 64
8.1%
4 64
8.1%
2 61
 
7.7%
6 57
 
7.2%
5 53
 
6.7%
7 53
 
6.7%
8 53
 
6.7%
Other values (12) 155
19.7%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
(아동) 지역아동센터
43 
(노인) 재가노인복지시설
25 
(노인) 노인요양공동생활가정
15 
(노인) 노인요양시설
12 
(노인) 노인교실
9 
Other values (25)
51 

Length

Max length27
Median length23
Mean length12.516129
Min length9

Unique

Unique15 ?
Unique (%)9.7%

Sample

1st row(노인) 양로시설
2nd row(노인) 노인요양시설
3rd row(노인) 노인요양시설
4th row(노인) 재가노인복지시설
5th row(노인) 양로시설

Common Values

ValueCountFrequency (%)
(아동) 지역아동센터 43
27.7%
(노인) 재가노인복지시설 25
16.1%
(노인) 노인요양공동생활가정 15
 
9.7%
(노인) 노인요양시설 12
 
7.7%
(노인) 노인교실 9
 
5.8%
(장애인) 장애인공동생활가정 7
 
4.5%
(장애인) 장애인보호작업장 7
 
4.5%
(노인) 노인복지관 4
 
2.6%
(장애인) 장애인주간보호시설 4
 
2.6%
(아동) 다함께돌봄센터 4
 
2.6%
Other values (20) 25
16.1%

Length

2024-05-11T00:41:34.931315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 69
22.3%
아동 49
15.8%
지역아동센터 43
13.9%
재가노인복지시설 25
 
8.1%
장애인 24
 
7.7%
노인요양공동생활가정 15
 
4.8%
노인요양시설 12
 
3.9%
노인교실 9
 
2.9%
장애인보호작업장 7
 
2.3%
장애인공동생활가정 7
 
2.3%
Other values (33) 50
16.1%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
아동복지시설
49 
노인의료복지시설
27 
재가노인복지시설
25 
노인여가복지시설
14 
장애인거주시설
9 
Other values (15)
31 

Length

Max length11
Median length9
Mean length7.3483871
Min length4

Unique

Unique10 ?
Unique (%)6.5%

Sample

1st row노인주거복지시설
2nd row노인의료복지시설
3rd row노인의료복지시설
4th row재가노인복지시설
5th row노인주거복지시설

Common Values

ValueCountFrequency (%)
아동복지시설 49
31.6%
노인의료복지시설 27
17.4%
재가노인복지시설 25
16.1%
노인여가복지시설 14
 
9.0%
장애인거주시설 9
 
5.8%
장애인지역사회재활시설 7
 
4.5%
장애인직업재활시설 7
 
4.5%
정신재활시설 3
 
1.9%
일반사회복지시설 2
 
1.3%
노인주거복지시설 2
 
1.3%
Other values (10) 10
 
6.5%

Length

2024-05-11T00:41:35.558940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동복지시설 49
31.6%
노인의료복지시설 27
17.4%
재가노인복지시설 25
16.1%
노인여가복지시설 14
 
9.0%
장애인거주시설 9
 
5.8%
장애인지역사회재활시설 7
 
4.5%
장애인직업재활시설 7
 
4.5%
정신재활시설 3
 
1.9%
일반사회복지시설 2
 
1.3%
노인주거복지시설 2
 
1.3%
Other values (10) 10
 
6.5%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
자치구
155 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자치구 155
100.0%

Length

2024-05-11T00:41:36.068910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:36.686282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 155
100.0%

시설장명
Text

Distinct123
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:41:37.616135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9870968
Min length2

Characters and Unicode

Total characters463
Distinct characters107
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)60.6%

Sample

1st row채명석
2nd row이희법
3rd row송평섭
4th row유지훈
5th row박정희
ValueCountFrequency (%)
조영표 4
 
2.6%
유지훈 3
 
1.9%
이상옥 2
 
1.3%
김영숙 2
 
1.3%
조윤주 2
 
1.3%
강선영 2
 
1.3%
유승재 2
 
1.3%
최용규 2
 
1.3%
장희주 2
 
1.3%
이숙희 2
 
1.3%
Other values (113) 132
85.2%
2024-05-11T00:41:39.405513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 37
 
8.0%
정 22
 
4.8%
이 20
 
4.3%
영 16
 
3.5%
희 15
 
3.2%
미 14
 
3.0%
선 12
 
2.6%
경 12
 
2.6%
유 11
 
2.4%
박 11
 
2.4%
Other values (97) 293
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 463
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 37
 
8.0%
정 22
 
4.8%
이 20
 
4.3%
영 16
 
3.5%
희 15
 
3.2%
미 14
 
3.0%
선 12
 
2.6%
경 12
 
2.6%
유 11
 
2.4%
박 11
 
2.4%
Other values (97) 293
63.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 463
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 37
 
8.0%
정 22
 
4.8%
이 20
 
4.3%
영 16
 
3.5%
희 15
 
3.2%
미 14
 
3.0%
선 12
 
2.6%
경 12
 
2.6%
유 11
 
2.4%
박 11
 
2.4%
Other values (97) 293
63.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 463
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 37
 
8.0%
정 22
 
4.8%
이 20
 
4.3%
영 16
 
3.5%
희 15
 
3.2%
미 14
 
3.0%
선 12
 
2.6%
경 12
 
2.6%
유 11
 
2.4%
박 11
 
2.4%
Other values (97) 293
63.3%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1154500000
155 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1154500000
2nd row1154500000
3rd row1154500000
4th row1154500000
5th row1154500000

Common Values

ValueCountFrequency (%)
1154500000 155
100.0%

Length

2024-05-11T00:41:40.089712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:40.400088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1154500000 155
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
금천구
155 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금천구 155
100.0%

Length

2024-05-11T00:41:40.729905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:41:41.074522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금천구 155
100.0%

시설주소
Text

Distinct146
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:41:41.815367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length39
Mean length28.787097
Min length10

Characters and Unicode

Total characters4462
Distinct characters156
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

Unique138 ?
Unique (%)89.0%

Sample

1st row서울특별시 금천구 금하로29길 36(시흥동)
2nd row서울특별시 금천구 금하로 596-0
3rd row서울특별시 금천구 범안로12가길 59
4th row서울특별시 금천구 금하로29길 36(시흥2동)
5th row서울특별시 금천구 시흥대로40길 111-5섭리의집
ValueCountFrequency (%)
서울특별시 154
18.7%
금천구 154
18.7%
독산동 55
 
6.7%
시흥동 39
 
4.7%
시흥대로 17
 
2.1%
독산로 15
 
1.8%
3층 14
 
1.7%
2층 13
 
1.6%
4층 10
 
1.2%
가산동 9
 
1.1%
Other values (251) 343
41.7%
2024-05-11T00:41:43.485734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
671
 
15.0%
시 259
 
5.8%
금 183
 
4.1%
1 170
 
3.8%
천 159
 
3.6%
서 155
 
3.5%
별 155
 
3.5%
구 155
 
3.5%
울 155
 
3.5%
로 155
 
3.5%
Other values (146) 2245
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2604
58.4%
Decimal Number 811
 
18.2%
Space Separator 671
 
15.0%
Open Punctuation 121
 
2.7%
Close Punctuation 121
 
2.7%
Other Punctuation 89
 
2.0%
Dash Punctuation 36
 
0.8%
Uppercase Letter 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 259
 
9.9%
금 183
 
7.0%
천 159
 
6.1%
서 155
 
6.0%
별 155
 
6.0%
구 155
 
6.0%
울 155
 
6.0%
로 155
 
6.0%
특 154
 
5.9%
동 130
 
5.0%
Other values (124) 944
36.3%
Decimal Number
ValueCountFrequency (%)
1 170
21.0%
2 136
16.8%
3 98
12.1%
0 85
10.5%
4 74
9.1%
6 68
 
8.4%
9 53
 
6.5%
5 50
 
6.2%
7 44
 
5.4%
8 33
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
C 3
33.3%
B 3
33.3%
Y 1
 
11.1%
A 1
 
11.1%
E 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 87
97.8%
/ 1
 
1.1%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
671
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2604
58.4%
Common 1849
41.4%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 259
 
9.9%
금 183
 
7.0%
천 159
 
6.1%
서 155
 
6.0%
별 155
 
6.0%
구 155
 
6.0%
울 155
 
6.0%
로 155
 
6.0%
특 154
 
5.9%
동 130
 
5.0%
Other values (124) 944
36.3%
Common
ValueCountFrequency (%)
671
36.3%
1 170
 
9.2%
2 136
 
7.4%
( 121
 
6.5%
) 121
 
6.5%
3 98
 
5.3%
, 87
 
4.7%
0 85
 
4.6%
4 74
 
4.0%
6 68
 
3.7%
Other values (7) 218
 
11.8%
Latin
ValueCountFrequency (%)
C 3
33.3%
B 3
33.3%
Y 1
 
11.1%
A 1
 
11.1%
E 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2604
58.4%
ASCII 1858
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
671
36.1%
1 170
 
9.1%
2 136
 
7.3%
( 121
 
6.5%
) 121
 
6.5%
3 98
 
5.3%
, 87
 
4.7%
0 85
 
4.6%
4 74
 
4.0%
6 68
 
3.7%
Other values (12) 227
 
12.2%
Hangul
ValueCountFrequency (%)
시 259
 
9.9%
금 183
 
7.0%
천 159
 
6.1%
서 155
 
6.0%
별 155
 
6.0%
구 155
 
6.0%
울 155
 
6.0%
로 155
 
6.0%
특 154
 
5.9%
동 130
 
5.0%
Other values (124) 944
36.3%

정원(수용인원)
Real number (ℝ)

MISSING  ZEROS 

Distinct39
Distinct (%)28.1%
Missing16
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean24.892086
Minimum0
Maximum250
Zeros26
Zeros (%)16.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:41:44.102547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.5
median20
Q333
95-th percentile64
Maximum250
Range250
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation30.925036
Coefficient of variation (CV)1.2423642
Kurtosis26.492366
Mean24.892086
Median Absolute Deviation (MAD)13
Skewness4.288518
Sum3460
Variance956.35784
MonotonicityNot monotonic
2024-05-11T00:41:44.743809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 26
16.8%
9 14
 
9.0%
49 10
 
6.5%
33 8
 
5.2%
29 7
 
4.5%
19 7
 
4.5%
20 6
 
3.9%
4 6
 
3.9%
24 6
 
3.9%
32 5
 
3.2%
Other values (29) 44
28.4%
(Missing) 16
 
10.3%
ValueCountFrequency (%)
0 26
16.8%
2 1
 
0.6%
4 6
 
3.9%
7 1
 
0.6%
8 1
 
0.6%
9 14
9.0%
10 4
 
2.6%
12 1
 
0.6%
13 1
 
0.6%
15 3
 
1.9%
ValueCountFrequency (%)
250 1
 
0.6%
200 1
 
0.6%
96 1
 
0.6%
74 1
 
0.6%
72 1
 
0.6%
70 1
 
0.6%
64 2
 
1.3%
63 1
 
0.6%
49 10
6.5%
48 1
 
0.6%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct51
Distinct (%)46.8%
Missing46
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean97.614679
Minimum2
Maximum1088
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:41:45.472469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q110
median27
Q345
95-th percentile700.4
Maximum1088
Range1086
Interquartile range (IQR)35

Descriptive statistics

Standard deviation227.0889
Coefficient of variation (CV)2.3263807
Kurtosis10.992014
Mean97.614679
Median Absolute Deviation (MAD)17
Skewness3.4436658
Sum10640
Variance51569.369
MonotonicityNot monotonic
2024-05-11T00:41:46.098457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 12
 
7.7%
4 6
 
3.9%
27 5
 
3.2%
10 5
 
3.2%
45 4
 
2.6%
7 4
 
2.6%
30 3
 
1.9%
25 3
 
1.9%
33 3
 
1.9%
31 3
 
1.9%
Other values (41) 61
39.4%
(Missing) 46
29.7%
ValueCountFrequency (%)
2 1
 
0.6%
4 6
3.9%
7 4
 
2.6%
9 12
7.7%
10 5
3.2%
13 1
 
0.6%
15 2
 
1.3%
17 2
 
1.3%
18 3
 
1.9%
19 3
 
1.9%
ValueCountFrequency (%)
1088 1
0.6%
1054 1
0.6%
1000 2
1.3%
886 1
0.6%
800 1
0.6%
551 1
0.6%
485 1
0.6%
300 1
0.6%
227 1
0.6%
200 1
0.6%

전화번호
Text

Distinct140
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-05-11T00:41:47.151512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.580645
Min length9

Characters and Unicode

Total characters1640
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

Unique127 ?
Unique (%)81.9%

Sample

1st row02-802-6765
2nd row02-804-6141
3rd row02-804-1957
4th row070-4680-2461
5th row02-803-3055
ValueCountFrequency (%)
028389993 4
 
2.6%
02-866-1314 2
 
1.3%
02-859-6690 2
 
1.3%
02-803-7747 2
 
1.3%
02-893-9630 2
 
1.3%
028300101 2
 
1.3%
028975104 2
 
1.3%
02-3665-3831 2
 
1.3%
028028020 2
 
1.3%
02-804-1957 2
 
1.3%
Other values (130) 133
85.8%
2024-05-11T00:41:48.561539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 338
20.6%
2 235
14.3%
- 200
12.2%
8 179
10.9%
9 126
 
7.7%
3 108
 
6.6%
1 102
 
6.2%
5 98
 
6.0%
7 96
 
5.9%
6 90
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1440
87.8%
Dash Punctuation 200
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 338
23.5%
2 235
16.3%
8 179
12.4%
9 126
 
8.8%
3 108
 
7.5%
1 102
 
7.1%
5 98
 
6.8%
7 96
 
6.7%
6 90
 
6.2%
4 68
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1640
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 338
20.6%
2 235
14.3%
- 200
12.2%
8 179
10.9%
9 126
 
7.7%
3 108
 
6.6%
1 102
 
6.2%
5 98
 
6.0%
7 96
 
5.9%
6 90
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1640
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 338
20.6%
2 235
14.3%
- 200
12.2%
8 179
10.9%
9 126
 
7.7%
3 108
 
6.6%
1 102
 
6.2%
5 98
 
6.0%
7 96
 
5.9%
6 90
 
5.5%

우편번호
Real number (ℝ)

Distinct82
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21698.116
Minimum8503
Maximum153858
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-11T00:41:49.067788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8503
5-th percentile8523
Q18556.5
median8598
Q38631
95-th percentile153600
Maximum153858
Range145355
Interquartile range (IQR)74.5

Descriptive statistics

Standard deviation41735.357
Coefficient of variation (CV)1.9234553
Kurtosis6.414246
Mean21698.116
Median Absolute Deviation (MAD)37
Skewness2.8864547
Sum3363208
Variance1.74184 × 109
MonotonicityNot monotonic
2024-05-11T00:41:49.525001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8656 7
 
4.5%
153600 7
 
4.5%
8628 7
 
4.5%
8629 5
 
3.2%
8574 5
 
3.2%
8554 5
 
3.2%
8533 3
 
1.9%
8617 3
 
1.9%
8602 3
 
1.9%
8575 3
 
1.9%
Other values (72) 107
69.0%
ValueCountFrequency (%)
8503 1
0.6%
8504 1
0.6%
8506 1
0.6%
8512 1
0.6%
8513 1
0.6%
8516 1
0.6%
8518 1
0.6%
8523 2
1.3%
8526 1
0.6%
8527 1
0.6%
ValueCountFrequency (%)
153858 1
 
0.6%
153857 1
 
0.6%
153847 1
 
0.6%
153842 1
 
0.6%
153830 1
 
0.6%
153829 1
 
0.6%
153808 1
 
0.6%
153600 7
4.5%
8657 1
 
0.6%
8656 7
4.5%

Interactions

2024-05-11T00:41:27.513578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:25.248239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:26.096047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:27.795996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:25.538355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:26.691574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:28.207048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:25.780738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:26.950076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T00:41:49.822303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0000.8370.9600.492
시설종류상세명(시설종류)1.0001.0000.7390.8990.000
정원(수용인원)0.8370.7391.0000.1160.000
현인원0.9600.8990.1161.0000.000
우편번호0.4920.0000.0000.0001.000
2024-05-11T00:41:50.117392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)
시설종류명(시설유형)1.0000.962
시설종류상세명(시설종류)0.9621.000
2024-05-11T00:41:50.376935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.0830.0790.4700.438
현인원0.0831.0000.0190.7060.598
우편번호0.0790.0191.0000.3560.000
시설종류명(시설유형)0.4700.7060.3561.0000.962
시설종류상세명(시설종류)0.4380.5980.0000.9621.000

Missing values

2024-05-11T00:41:28.748395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T00:41:29.475589image/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.
2024-05-11T00:41:29.965981image/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

시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
0혜명양로원A0019(노인) 양로시설노인주거복지시설자치구채명석1154500000금천구서울특별시 금천구 금하로29길 36(시흥동)645502-802-67658656
1노인요양센터 인영실버A0099(노인) 노인요양시설노인의료복지시설자치구이희법1154500000금천구서울특별시 금천구 금하로 596-0968402-804-61418632
2남부실버요양원A1307(노인) 노인요양시설노인의료복지시설자치구송평섭1154500000금천구서울특별시 금천구 범안로12가길 59282702-804-19578602
3청담노인복지센터A1980(노인) 재가노인복지시설재가노인복지시설자치구유지훈1154500000금천구서울특별시 금천구 금하로29길 36(시흥2동)2121070-4680-24618656
4섭리의집A3167(노인) 양로시설노인주거복지시설자치구박정희1154500000금천구서울특별시 금천구 시흥대로40길 111-5섭리의집282702-803-30558648
5남부실버요양센터 다솔관A3370(노인) 노인요양시설노인의료복지시설자치구이경옥1154500000금천구서울특별시 금천구 범안로12가길 59636302-804-19578602
6금천노인종합복지관A6079(노인) 노인복지관노인여가복지시설자치구구자훈1154500000금천구서울특별시 금천구 시흥대로51길 93-320108802-804-4058153847
7금천호암노인종합복지관A6518(노인) 노인복지관노인여가복지시설자치구조영표1154500000금천구서울특별시 금천구 독산로72길 86-5080002-853-72038556
8굿하트 금천재가노인지원센터A6676(노인) 재가노인복지시설재가노인복지시설자치구김정미1154500000금천구서울특별시 금천구 시흥대로 399-0시티렉스 314호04202-805-70908584
9실버캐슬A7065(노인) 노인요양공동생활가정노인의료복지시설자치구정은주1154500000금천구서울특별시 금천구 시흥대로 202대의빌딩 6층 (시흥동)9902-805-05338629
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