Overview

Dataset statistics

Number of variables13
Number of observations185
Missing cells84
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory108.7 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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-20401/S/1/datasetView.do

Alerts

자치구(시)구분 has constant value ""Constant
시군구코드 has constant value ""Constant
시군구명 has constant value ""Constant
시설종류상세명(시설종류) is highly overall correlated with 시설종류명(시설유형)High correlation
시설종류명(시설유형) is highly overall correlated with 정원(수용인원) and 2 other fieldsHigh correlation
정원(수용인원) is highly overall correlated with 시설종류명(시설유형)High correlation
현인원 is highly overall correlated with 시설종류명(시설유형)High correlation
정원(수용인원) has 28 (15.1%) missing valuesMissing
현인원 has 55 (29.7%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 26 (14.1%) zerosZeros
현인원 has 5 (2.7%) zerosZeros

Reproduction

Analysis started2024-05-11 01:08:50.659910
Analysis finished2024-05-11 01:08:57.749386
Duration7.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct181
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T01:08:58.222012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length9.8108108
Min length2

Characters and Unicode

Total characters1815
Distinct characters250
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)95.7%

Sample

1st row시립고덕양로원
2nd row성가정데이케어센터
3rd row성암장수마을
4th row시립강동노인복지관데이케어센터
5th row강동구립해공데이케어센터
ValueCountFrequency (%)
우리동네키움센터 5
 
2.3%
방문요양센터 4
 
1.8%
a 3
 
1.4%
강동천호실버센터2호 2
 
0.9%
2호점 2
 
0.9%
재가노인복지센터 2
 
0.9%
정원실버요양원 2
 
0.9%
강동포도나무요양원 2
 
0.9%
재가방문요양센터 2
 
0.9%
암사지역아동센터 2
 
0.9%
Other values (193) 195
88.2%
2024-05-11T01:08:59.435867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 121
 
6.7%
센 116
 
6.4%
동 101
 
5.6%
지 72
 
4.0%
강 54
 
3.0%
아 47
 
2.6%
복 40
 
2.2%
36
 
2.0%
호 34
 
1.9%
이 32
 
1.8%
Other values (240) 1162
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1717
94.6%
Space Separator 36
 
2.0%
Decimal Number 21
 
1.2%
Open Punctuation 16
 
0.9%
Close Punctuation 16
 
0.9%
Uppercase Letter 5
 
0.3%
Other Punctuation 2
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 121
 
7.0%
센 116
 
6.8%
동 101
 
5.9%
지 72
 
4.2%
강 54
 
3.1%
아 47
 
2.7%
복 40
 
2.3%
호 34
 
2.0%
이 32
 
1.9%
인 30
 
1.7%
Other values (228) 1070
62.3%
Decimal Number
ValueCountFrequency (%)
2 13
61.9%
1 6
28.6%
9 1
 
4.8%
3 1
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
B 1
 
20.0%
K 1
 
20.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
' 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1716
94.5%
Common 93
 
5.1%
Latin 5
 
0.3%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 121
 
7.1%
센 116
 
6.8%
동 101
 
5.9%
지 72
 
4.2%
강 54
 
3.1%
아 47
 
2.7%
복 40
 
2.3%
호 34
 
2.0%
이 32
 
1.9%
인 30
 
1.7%
Other values (227) 1069
62.3%
Common
ValueCountFrequency (%)
36
38.7%
( 16
17.2%
) 16
17.2%
2 13
 
14.0%
1 6
 
6.5%
' 2
 
2.2%
- 2
 
2.2%
9 1
 
1.1%
3 1
 
1.1%
Latin
ValueCountFrequency (%)
A 3
60.0%
B 1
 
20.0%
K 1
 
20.0%
Han
ValueCountFrequency (%)
來 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1716
94.5%
ASCII 98
 
5.4%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 121
 
7.1%
센 116
 
6.8%
동 101
 
5.9%
지 72
 
4.2%
강 54
 
3.1%
아 47
 
2.7%
복 40
 
2.3%
호 34
 
2.0%
이 32
 
1.9%
인 30
 
1.7%
Other values (227) 1069
62.3%
ASCII
ValueCountFrequency (%)
36
36.7%
( 16
16.3%
) 16
16.3%
2 13
 
13.3%
1 6
 
6.1%
A 3
 
3.1%
' 2
 
2.0%
- 2
 
2.0%
9 1
 
1.0%
3 1
 
1.0%
Other values (2) 2
 
2.0%
CJK
ValueCountFrequency (%)
來 1
100.0%

시설코드
Text

UNIQUE 

Distinct185
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T01:09:00.744910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0540541
Min length5

Characters and Unicode

Total characters935
Distinct characters23
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

Unique185 ?
Unique (%)100.0%

Sample

1st rowA0098
2nd rowA3430
3rd rowA3710
4th rowA4272
5th rowA5817
ValueCountFrequency (%)
a0098 1
 
0.5%
g8816 1
 
0.5%
k0976 1
 
0.5%
g6497 1
 
0.5%
g7024 1
 
0.5%
g7152 1
 
0.5%
g7160 1
 
0.5%
g7231 1
 
0.5%
g7310 1
 
0.5%
g7414 1
 
0.5%
Other values (175) 175
94.6%
2024-05-11T01:09:02.808768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 107
11.4%
1 100
10.7%
4 84
9.0%
7 75
8.0%
5 75
8.0%
8 73
 
7.8%
3 65
 
7.0%
9 64
 
6.8%
6 54
 
5.8%
2 53
 
5.7%
Other values (13) 185
19.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 750
80.2%
Uppercase Letter 185
 
19.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 46
24.9%
G 31
16.8%
P 19
10.3%
K 19
10.3%
A 19
10.3%
B 18
 
9.7%
F 13
 
7.0%
J 5
 
2.7%
M 5
 
2.7%
Z 4
 
2.2%
Other values (3) 6
 
3.2%
Decimal Number
ValueCountFrequency (%)
0 107
14.3%
1 100
13.3%
4 84
11.2%
7 75
10.0%
5 75
10.0%
8 73
9.7%
3 65
8.7%
9 64
8.5%
6 54
7.2%
2 53
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 750
80.2%
Latin 185
 
19.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 46
24.9%
G 31
16.8%
P 19
10.3%
K 19
10.3%
A 19
10.3%
B 18
 
9.7%
F 13
 
7.0%
J 5
 
2.7%
M 5
 
2.7%
Z 4
 
2.2%
Other values (3) 6
 
3.2%
Common
ValueCountFrequency (%)
0 107
14.3%
1 100
13.3%
4 84
11.2%
7 75
10.0%
5 75
10.0%
8 73
9.7%
3 65
8.7%
9 64
8.5%
6 54
7.2%
2 53
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 935
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 107
11.4%
1 100
10.7%
4 84
9.0%
7 75
8.0%
5 75
8.0%
8 73
 
7.8%
3 65
 
7.0%
9 64
 
6.8%
6 54
 
5.8%
2 53
 
5.7%
Other values (13) 185
19.8%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
(노인) 재가노인복지시설
47 
(아동) 지역아동센터
25 
(노인) 노인요양공동생활가정
18 
(장애인) 장애인보호작업장
12 
(장애인) 장애인공동생활가정
11 
Other values (31)
72 

Length

Max length22
Median length21
Mean length13.362162
Min length9

Unique

Unique16 ?
Unique (%)8.6%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 47
25.4%
(아동) 지역아동센터 25
13.5%
(노인) 노인요양공동생활가정 18
 
9.7%
(장애인) 장애인보호작업장 12
 
6.5%
(장애인) 장애인공동생활가정 11
 
5.9%
(노인) 노인요양시설 11
 
5.9%
(아동) 다함께돌봄센터 7
 
3.8%
(장애인) 장애인주간보호시설 5
 
2.7%
(장애인) 장애인재활치료시설 4
 
2.2%
(장애인) 장애인복지관 4
 
2.2%
Other values (26) 41
22.2%

Length

2024-05-11T01:09:03.319912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 81
21.9%
장애인 51
13.8%
재가노인복지시설 47
12.7%
아동 37
10.0%
지역아동센터 25
 
6.8%
노인요양공동생활가정 18
 
4.9%
장애인보호작업장 12
 
3.2%
장애인공동생활가정 11
 
3.0%
노인요양시설 11
 
3.0%
다함께돌봄센터 7
 
1.9%
Other values (39) 70
18.9%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
재가노인복지시설
47 
아동복지시설
37 
노인의료복지시설
29 
장애인거주시설
20 
장애인지역사회재활시설
14 
Other values (16)
38 

Length

Max length11
Median length9
Mean length7.6378378
Min length4

Unique

Unique10 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 47
25.4%
아동복지시설 37
20.0%
노인의료복지시설 29
15.7%
장애인거주시설 20
10.8%
장애인지역사회재활시설 14
 
7.6%
장애인직업재활시설 13
 
7.0%
정신재활시설 4
 
2.2%
노인여가복지시설 3
 
1.6%
장애인기타 3
 
1.6%
청소년복지시설 3
 
1.6%
Other values (11) 12
 
6.5%

Length

2024-05-11T01:09:03.943304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재가노인복지시설 47
25.4%
아동복지시설 37
20.0%
노인의료복지시설 29
15.7%
장애인거주시설 20
10.8%
장애인지역사회재활시설 14
 
7.6%
장애인직업재활시설 13
 
7.0%
정신재활시설 4
 
2.2%
노인여가복지시설 3
 
1.6%
장애인기타 3
 
1.6%
청소년복지시설 3
 
1.6%
Other values (11) 12
 
6.5%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
자치구
185 

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 185
100.0%

Length

2024-05-11T01:09:04.510695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:04.916872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 185
100.0%

시설장명
Text

Distinct172
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T01:09:05.811641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters555
Distinct characters122
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

Unique159 ?
Unique (%)85.9%

Sample

1st row박기아
2nd row최은영
3rd row황용규
4th row성미선
5th row전아미
ValueCountFrequency (%)
선순제 2
 
1.1%
성미선 2
 
1.1%
이광진 2
 
1.1%
신인희 2
 
1.1%
정미향 2
 
1.1%
이춘석 2
 
1.1%
오성섭 2
 
1.1%
유형진 2
 
1.1%
정해월 2
 
1.1%
은홍수 2
 
1.1%
Other values (162) 165
89.2%
2024-05-11T01:09:07.496583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 36
 
6.5%
이 32
 
5.8%
정 31
 
5.6%
영 20
 
3.6%
미 17
 
3.1%
은 16
 
2.9%
박 14
 
2.5%
경 14
 
2.5%
순 13
 
2.3%
희 13
 
2.3%
Other values (112) 349
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 555
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 36
 
6.5%
이 32
 
5.8%
정 31
 
5.6%
영 20
 
3.6%
미 17
 
3.1%
은 16
 
2.9%
박 14
 
2.5%
경 14
 
2.5%
순 13
 
2.3%
희 13
 
2.3%
Other values (112) 349
62.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 555
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 36
 
6.5%
이 32
 
5.8%
정 31
 
5.6%
영 20
 
3.6%
미 17
 
3.1%
은 16
 
2.9%
박 14
 
2.5%
경 14
 
2.5%
순 13
 
2.3%
희 13
 
2.3%
Other values (112) 349
62.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 555
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 36
 
6.5%
이 32
 
5.8%
정 31
 
5.6%
영 20
 
3.6%
미 17
 
3.1%
은 16
 
2.9%
박 14
 
2.5%
경 14
 
2.5%
순 13
 
2.3%
희 13
 
2.3%
Other values (112) 349
62.9%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1174000000
185 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1174000000
2nd row1174000000
3rd row1174000000
4th row1174000000
5th row1174000000

Common Values

ValueCountFrequency (%)
1174000000 185
100.0%

Length

2024-05-11T01:09:08.259999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:08.764191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1174000000 185
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
강동구
185 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강동구 185
100.0%

Length

2024-05-11T01:09:09.106248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:09:09.543804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강동구 185
100.0%

시설주소
Text

Distinct178
Distinct (%)96.7%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-05-11T01:09:10.324780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length29.211957
Min length14

Characters and Unicode

Total characters5375
Distinct characters142
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)93.5%

Sample

1st row서울특별시 강동구 고덕로 199(고덕동)
2nd row서울특별시 강동구 양재대로156길 28(고덕동)
3rd row서울특별시 강동구 구천면로68길 46 (천호동)
4th row서울특별시 강동구 명일2동 48-1032-5
5th row서울특별시 강동구 천중로17길 42-16(천호2동)
ValueCountFrequency (%)
강동구 182
 
18.2%
서울특별시 181
 
18.1%
천호동 30
 
3.0%
성내동 22
 
2.2%
암사동 21
 
2.1%
2층 18
 
1.8%
길동 17
 
1.7%
3층 16
 
1.6%
고덕로 14
 
1.4%
둔촌동 13
 
1.3%
Other values (312) 486
48.6%
2024-05-11T01:09:12.064904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
821
 
15.3%
동 372
 
6.9%
1 220
 
4.1%
구 209
 
3.9%
강 202
 
3.8%
시 189
 
3.5%
서 182
 
3.4%
울 181
 
3.4%
별 181
 
3.4%
특 181
 
3.4%
Other values (132) 2637
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3078
57.3%
Decimal Number 993
 
18.5%
Space Separator 821
 
15.3%
Close Punctuation 161
 
3.0%
Open Punctuation 161
 
3.0%
Other Punctuation 111
 
2.1%
Dash Punctuation 42
 
0.8%
Math Symbol 4
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 372
 
12.1%
구 209
 
6.8%
강 202
 
6.6%
시 189
 
6.1%
서 182
 
5.9%
울 181
 
5.9%
별 181
 
5.9%
특 181
 
5.9%
로 177
 
5.8%
길 114
 
3.7%
Other values (115) 1090
35.4%
Decimal Number
ValueCountFrequency (%)
1 220
22.2%
2 154
15.5%
3 124
12.5%
4 92
9.3%
0 88
 
8.9%
5 80
 
8.1%
8 67
 
6.7%
6 64
 
6.4%
9 59
 
5.9%
7 45
 
4.5%
Space Separator
ValueCountFrequency (%)
821
100.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Other Punctuation
ValueCountFrequency (%)
, 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3078
57.3%
Common 2293
42.7%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 372
 
12.1%
구 209
 
6.8%
강 202
 
6.6%
시 189
 
6.1%
서 182
 
5.9%
울 181
 
5.9%
별 181
 
5.9%
특 181
 
5.9%
로 177
 
5.8%
길 114
 
3.7%
Other values (115) 1090
35.4%
Common
ValueCountFrequency (%)
821
35.8%
1 220
 
9.6%
) 161
 
7.0%
( 161
 
7.0%
2 154
 
6.7%
3 124
 
5.4%
, 111
 
4.8%
4 92
 
4.0%
0 88
 
3.8%
5 80
 
3.5%
Other values (6) 281
 
12.3%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3078
57.3%
ASCII 2297
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
821
35.7%
1 220
 
9.6%
) 161
 
7.0%
( 161
 
7.0%
2 154
 
6.7%
3 124
 
5.4%
, 111
 
4.8%
4 92
 
4.0%
0 88
 
3.8%
5 80
 
3.5%
Other values (7) 285
 
12.4%
Hangul
ValueCountFrequency (%)
동 372
 
12.1%
구 209
 
6.8%
강 202
 
6.6%
시 189
 
6.1%
서 182
 
5.9%
울 181
 
5.9%
별 181
 
5.9%
특 181
 
5.9%
로 177
 
5.8%
길 114
 
3.7%
Other values (115) 1090
35.4%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct47
Distinct (%)29.9%
Missing28
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean39.834395
Minimum0
Maximum1695
Zeros26
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T01:09:12.757864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median19
Q335
95-th percentile102
Maximum1695
Range1695
Interquartile range (IQR)31

Descriptive statistics

Standard deviation146.45608
Coefficient of variation (CV)3.6766236
Kurtosis108.37383
Mean39.834395
Median Absolute Deviation (MAD)15
Skewness9.9725881
Sum6254
Variance21449.383
MonotonicityNot monotonic
2024-05-11T01:09:13.355729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 26
14.1%
9 18
 
9.7%
4 11
 
5.9%
35 10
 
5.4%
29 10
 
5.4%
10 8
 
4.3%
20 6
 
3.2%
21 6
 
3.2%
50 5
 
2.7%
25 5
 
2.7%
Other values (37) 52
28.1%
(Missing) 28
15.1%
ValueCountFrequency (%)
0 26
14.1%
2 3
 
1.6%
4 11
5.9%
5 1
 
0.5%
7 1
 
0.5%
8 2
 
1.1%
9 18
9.7%
10 8
 
4.3%
14 1
 
0.5%
15 2
 
1.1%
ValueCountFrequency (%)
1695 1
0.5%
700 1
0.5%
163 1
0.5%
150 1
0.5%
132 1
0.5%
129 1
0.5%
124 1
0.5%
110 1
0.5%
100 1
0.5%
86 1
0.5%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct59
Distinct (%)45.4%
Missing55
Missing (%)29.7%
Infinite0
Infinite (%)0.0%
Mean149.23846
Minimum0
Maximum6038
Zeros5
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T01:09:13.899916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.45
Q19
median23
Q340
95-th percentile655
Maximum6038
Range6038
Interquartile range (IQR)31

Descriptive statistics

Standard deviation622.21625
Coefficient of variation (CV)4.1692755
Kurtosis65.100549
Mean149.23846
Median Absolute Deviation (MAD)14
Skewness7.50711
Sum19401
Variance387153.07
MonotonicityNot monotonic
2024-05-11T01:09:14.494160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 14
 
7.6%
10 8
 
4.3%
4 8
 
4.3%
0 5
 
2.7%
21 5
 
2.7%
29 4
 
2.2%
30 4
 
2.2%
8 3
 
1.6%
25 3
 
1.6%
15 3
 
1.6%
Other values (49) 73
39.5%
(Missing) 55
29.7%
ValueCountFrequency (%)
0 5
 
2.7%
2 2
 
1.1%
3 3
 
1.6%
4 8
4.3%
5 1
 
0.5%
6 1
 
0.5%
7 1
 
0.5%
8 3
 
1.6%
9 14
7.6%
10 8
4.3%
ValueCountFrequency (%)
6038 1
0.5%
2674 1
0.5%
2000 1
0.5%
1350 1
0.5%
1000 2
1.1%
700 1
0.5%
600 1
0.5%
580 1
0.5%
200 1
0.5%
150 1
0.5%

전화번호
Text

Distinct174
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T01:09:15.294337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.367568
Min length9

Characters and Unicode

Total characters1918
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)89.2%

Sample

1st row02-441-8886
2nd row02-481-2217
3rd row02-489-2081
4th row02-426-2048
5th row02-478-0601
ValueCountFrequency (%)
024830707 4
 
2.2%
024276888 2
 
1.1%
024854701 2
 
1.1%
02-482-6400 2
 
1.1%
02-442-9664 2
 
1.1%
02-481-2217 2
 
1.1%
02-478-0601 2
 
1.1%
02-2041-7800 2
 
1.1%
024816562 2
 
1.1%
02-485-1006 1
 
0.5%
Other values (164) 164
88.6%
2024-05-11T01:09:16.755737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 362
18.9%
2 298
15.5%
4 252
13.1%
- 191
10.0%
8 167
8.7%
7 139
 
7.2%
3 115
 
6.0%
1 110
 
5.7%
6 103
 
5.4%
5 102
 
5.3%
Other values (2) 79
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1726
90.0%
Dash Punctuation 191
 
10.0%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 362
21.0%
2 298
17.3%
4 252
14.6%
8 167
9.7%
7 139
 
8.1%
3 115
 
6.7%
1 110
 
6.4%
6 103
 
6.0%
5 102
 
5.9%
9 78
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 191
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1918
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 362
18.9%
2 298
15.5%
4 252
13.1%
- 191
10.0%
8 167
8.7%
7 139
 
7.2%
3 115
 
6.0%
1 110
 
5.7%
6 103
 
5.4%
5 102
 
5.3%
Other values (2) 79
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1918
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 362
18.9%
2 298
15.5%
4 252
13.1%
- 191
10.0%
8 167
8.7%
7 139
 
7.2%
3 115
 
6.0%
1 110
 
5.7%
6 103
 
5.4%
5 102
 
5.3%
Other values (2) 79
 
4.1%

우편번호
Real number (ℝ)

Distinct93
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16920.227
Minimum5207
Maximum464883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T01:09:17.436388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5207
5-th percentile5217.4
Q15265
median5312
Q35361
95-th percentile134600
Maximum464883
Range459676
Interquartile range (IQR)96

Descriptive statistics

Standard deviation46846.19
Coefficient of variation (CV)2.7686502
Kurtosis46.813456
Mean16920.227
Median Absolute Deviation (MAD)48
Skewness5.9234458
Sum3130242
Variance2.1945655 × 109
MonotonicityNot monotonic
2024-05-11T01:09:18.076043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
134600 7
 
3.8%
5306 7
 
3.8%
5211 6
 
3.2%
5334 6
 
3.2%
5328 5
 
2.7%
5295 5
 
2.7%
5265 5
 
2.7%
5235 5
 
2.7%
5360 5
 
2.7%
5320 4
 
2.2%
Other values (83) 130
70.3%
ValueCountFrequency (%)
5207 1
 
0.5%
5211 6
3.2%
5213 1
 
0.5%
5216 1
 
0.5%
5217 1
 
0.5%
5219 2
 
1.1%
5220 1
 
0.5%
5222 2
 
1.1%
5225 3
1.6%
5226 4
2.2%
ValueCountFrequency (%)
464883 1
 
0.5%
134878 1
 
0.5%
134867 1
 
0.5%
134830 1
 
0.5%
134814 1
 
0.5%
134803 1
 
0.5%
134600 7
3.8%
134050 1
 
0.5%
12814 1
 
0.5%
5408 3
1.6%

Interactions

2024-05-11T01:08:55.142678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:52.832406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:53.896097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:55.572292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:53.224569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:54.382675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:55.921777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:53.525505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:08:54.783894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T01:09:18.475247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0000.9700.9250.202
시설종류상세명(시설종류)1.0001.0000.7670.8380.000
정원(수용인원)0.9700.7671.0000.9350.000
현인원0.9250.8380.9351.0000.743
우편번호0.2020.0000.0000.7431.000
2024-05-11T01:09:18.791550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류상세명(시설종류)시설종류명(시설유형)
시설종류상세명(시설종류)1.0000.953
시설종류명(시설유형)0.9531.000
2024-05-11T01:09:19.148084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.469-0.0520.7420.474
현인원0.4691.0000.1410.6310.479
우편번호-0.0520.1411.0000.0870.000
시설종류명(시설유형)0.7420.6310.0871.0000.953
시설종류상세명(시설종류)0.4740.4790.0000.9531.000

Missing values

2024-05-11T01:08:56.302750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T01:08:57.011933image/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.
2024-05-11T01:08:57.539941image/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
0시립고덕양로원A0098(노인) 양로시설노인주거복지시설자치구박기아1174000000강동구서울특별시 강동구 고덕로 199(고덕동)1248702-441-88865235
1성가정데이케어센터A3430(노인) 재가노인복지시설재가노인복지시설자치구최은영1174000000강동구서울특별시 강동구 양재대로156길 28(고덕동)212102-481-22175235
2성암장수마을A3710(노인) 노인요양시설노인의료복지시설자치구황용규1174000000강동구서울특별시 강동구 구천면로68길 46 (천호동)1007502-489-20815306
3시립강동노인복지관데이케어센터A4272(노인) 재가노인복지시설재가노인복지시설자치구성미선1174000000강동구서울특별시 강동구 명일2동 48-1032-5242402-426-20485269
4강동구립해공데이케어센터A5817(노인) 재가노인복지시설재가노인복지시설자치구전아미1174000000강동구서울특별시 강동구 천중로17길 42-16(천호2동)171702-478-0601134867
5강동구립해공노인복지관A5818(노인) 노인복지관(소규모)노인여가복지시설자치구이상엽1174000000강동구서울특별시 강동구 천중로17길 42-16강동구립해공노인복지관 (천호동)169558002-478-06015321
6성가정노인종합복지관A6010(노인) 노인복지관노인여가복지시설자치구최은영1174000000강동구서울특별시 강동구 양재대로156길 280100002-481-2217134878
7(사)굿하트전문사례관리강동재가센터A6163(노인) 재가노인복지시설재가노인복지시설자치구김혜영1174000000강동구서울특별시 강동구 천호대로198길 8 (둔촌동)0002-442-70905360
8늘편한요양센터2호A7017(노인) 노인요양공동생활가정노인의료복지시설자치구이동욱1174000000강동구서울특별시 강동구 구천면로318, 2층 (천호동)99024743135134600
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