Overview

Dataset statistics

Number of variables13
Number of observations73
Missing cells48
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.8 KiB
Average record size in memory108.8 B

Variable types

Text6
Categorical5
Numeric2

Dataset

Description시설명,시설코드,시설종류명(시설유형),시설종류상세명(시설종류),자치구(시)구분,시설장명,시군구코드,시군구명,시설주소,정원(수용인원),현인원,전화번호,우편번호
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-20378/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 현인원 and 1 other fieldsHigh correlation
현인원 is highly overall correlated with 시설종류명(시설유형)High correlation
정원(수용인원) has 19 (26.0%) missing valuesMissing
현인원 has 29 (39.7%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 10 (13.7%) zerosZeros

Reproduction

Analysis started2024-05-17 23:02:24.233790
Analysis finished2024-05-17 23:02:31.208151
Duration6.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct71
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-05-18T08:02:31.854815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length18
Mean length13.739726
Min length2

Characters and Unicode

Total characters1003
Distinct characters164
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

Unique69 ?
Unique (%)94.5%

Sample

1st row남산실버복지센터
2nd row약수노인복지관
3rd row중구재가노인지원센터
4th row정동상림원
5th row효심원 노인요양공동생활가정
ValueCountFrequency (%)
중구 17
 
11.4%
서울특별시 15
 
10.1%
학교돌봄터(중구형 8
 
5.4%
초등돌봄 8
 
5.4%
우리동네키움센터 7
 
4.7%
남산실버복지센터 2
 
1.3%
재가노인복지센터 2
 
1.3%
서울중구지역자활센터 2
 
1.3%
다산방문요양센터 1
 
0.7%
5호점 1
 
0.7%
Other values (86) 86
57.7%
2024-05-18T08:02:33.263031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
7.6%
터 61
 
6.1%
센 53
 
5.3%
구 45
 
4.5%
중 41
 
4.1%
지 28
 
2.8%
서 25
 
2.5%
울 25
 
2.5%
초 24
 
2.4%
시 20
 
2.0%
Other values (154) 605
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 896
89.3%
Space Separator 76
 
7.6%
Open Punctuation 11
 
1.1%
Close Punctuation 11
 
1.1%
Decimal Number 8
 
0.8%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 61
 
6.8%
센 53
 
5.9%
구 45
 
5.0%
중 41
 
4.6%
지 28
 
3.1%
서 25
 
2.8%
울 25
 
2.8%
초 24
 
2.7%
시 20
 
2.2%
인 18
 
2.0%
Other values (143) 556
62.1%
Decimal Number
ValueCountFrequency (%)
4 2
25.0%
3 1
12.5%
1 1
12.5%
2 1
12.5%
5 1
12.5%
6 1
12.5%
7 1
12.5%
Space Separator
ValueCountFrequency (%)
76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
89.3%
Common 106
 
10.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 61
 
6.8%
센 53
 
5.9%
구 45
 
5.0%
중 41
 
4.6%
지 28
 
3.1%
서 25
 
2.8%
울 25
 
2.8%
초 24
 
2.7%
시 20
 
2.2%
인 18
 
2.0%
Other values (143) 556
62.1%
Common
ValueCountFrequency (%)
76
71.7%
( 11
 
10.4%
) 11
 
10.4%
4 2
 
1.9%
3 1
 
0.9%
1 1
 
0.9%
2 1
 
0.9%
5 1
 
0.9%
6 1
 
0.9%
7 1
 
0.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 896
89.3%
ASCII 107
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
71.0%
( 11
 
10.3%
) 11
 
10.3%
4 2
 
1.9%
3 1
 
0.9%
1 1
 
0.9%
A 1
 
0.9%
2 1
 
0.9%
5 1
 
0.9%
6 1
 
0.9%
Hangul
ValueCountFrequency (%)
터 61
 
6.8%
센 53
 
5.9%
구 45
 
5.0%
중 41
 
4.6%
지 28
 
3.1%
서 25
 
2.8%
울 25
 
2.8%
초 24
 
2.7%
시 20
 
2.2%
인 18
 
2.0%
Other values (143) 556
62.1%

시설코드
Text

UNIQUE 

Distinct73
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-05-18T08:02:33.947769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0273973
Min length5

Characters and Unicode

Total characters367
Distinct characters21
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

Unique73 ?
Unique (%)100.0%

Sample

1st rowA0839
2nd rowA2255
3rd rowA5556
4th rowA6971
5th rowA7231
ValueCountFrequency (%)
a0839 1
 
1.4%
g5342 1
 
1.4%
k2034 1
 
1.4%
k2033 1
 
1.4%
k1472 1
 
1.4%
k0939 1
 
1.4%
k0937 1
 
1.4%
k0936 1
 
1.4%
k0935 1
 
1.4%
k0934 1
 
1.4%
Other values (63) 63
86.3%
2024-05-18T08:02:34.948652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51
13.9%
2 47
12.8%
3 28
 
7.6%
1 27
 
7.4%
5 26
 
7.1%
7 26
 
7.1%
9 25
 
6.8%
4 24
 
6.5%
8 22
 
6.0%
6 18
 
4.9%
Other values (11) 73
19.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 294
80.1%
Uppercase Letter 73
 
19.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 16
21.9%
G 12
16.4%
C 11
15.1%
A 7
9.6%
B 7
9.6%
Z 6
 
8.2%
P 5
 
6.8%
F 4
 
5.5%
E 3
 
4.1%
J 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
0 51
17.3%
2 47
16.0%
3 28
9.5%
1 27
9.2%
5 26
8.8%
7 26
8.8%
9 25
8.5%
4 24
8.2%
8 22
7.5%
6 18
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common 294
80.1%
Latin 73
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 16
21.9%
G 12
16.4%
C 11
15.1%
A 7
9.6%
B 7
9.6%
Z 6
 
8.2%
P 5
 
6.8%
F 4
 
5.5%
E 3
 
4.1%
J 1
 
1.4%
Common
ValueCountFrequency (%)
0 51
17.3%
2 47
16.0%
3 28
9.5%
1 27
9.2%
5 26
8.8%
7 26
8.8%
9 25
8.5%
4 24
8.2%
8 22
7.5%
6 18
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51
13.9%
2 47
12.8%
3 28
 
7.6%
1 27
 
7.4%
5 26
 
7.1%
7 26
 
7.1%
9 25
 
6.8%
4 24
 
6.5%
8 22
 
6.0%
6 18
 
4.9%
Other values (11) 73
19.9%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
(노인) 재가노인복지시설
19 
(아동) 다함께돌봄센터
15 
(장애인) 장애인주간보호시설
6 
(아동) 지역아동센터
5 
(일반) 사회복지관
3 
Other values (21)
25 

Length

Max length28
Median length17
Mean length12.890411
Min length10

Unique

Unique17 ?
Unique (%)23.3%

Sample

1st row(노인) 재가노인복지시설
2nd row(노인) 노인복지관
3rd row(노인) 재가노인복지시설
4th row(노인) 노인복지주택
5th row(노인) 노인요양공동생활가정

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 19
26.0%
(아동) 다함께돌봄센터 15
20.5%
(장애인) 장애인주간보호시설 6
 
8.2%
(아동) 지역아동센터 5
 
6.8%
(일반) 사회복지관 3
 
4.1%
(아동) 아동양육시설 2
 
2.7%
(장애인) 장애인공동생활가정 2
 
2.7%
(노인) 노인요양시설 2
 
2.7%
(노인) 노인복지주택 2
 
2.7%
(노숙인등) 노숙인급식시설 1
 
1.4%
Other values (16) 16
21.9%

Length

2024-05-18T08:02:35.382023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 26
17.8%
아동 23
15.8%
재가노인복지시설 19
13.0%
다함께돌봄센터 15
10.3%
장애인 12
 
8.2%
장애인주간보호시설 6
 
4.1%
지역아동센터 5
 
3.4%
일반 3
 
2.1%
사회복지관 3
 
2.1%
노숙인등 3
 
2.1%
Other values (26) 31
21.2%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size716.0 B
아동복지시설
23 
재가노인복지시설
19 
장애인지역사회재활시설
8 
일반사회복지시설
3 
노인의료복지시설
3 
Other values (13)
17 

Length

Max length11
Median length9
Mean length7.4931507
Min length4

Unique

Unique9 ?
Unique (%)12.3%

Sample

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

Common Values

ValueCountFrequency (%)
아동복지시설 23
31.5%
재가노인복지시설 19
26.0%
장애인지역사회재활시설 8
 
11.0%
일반사회복지시설 3
 
4.1%
노인의료복지시설 3
 
4.1%
노인여가복지시설 2
 
2.7%
노숙인등이용시설 2
 
2.7%
장애인거주시설 2
 
2.7%
노인주거복지시설 2
 
2.7%
장애인기타 1
 
1.4%
Other values (8) 8
 
11.0%

Length

2024-05-18T08:02:35.827303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동복지시설 23
31.5%
재가노인복지시설 19
26.0%
장애인지역사회재활시설 8
 
11.0%
일반사회복지시설 3
 
4.1%
노인의료복지시설 3
 
4.1%
노인여가복지시설 2
 
2.7%
노숙인등이용시설 2
 
2.7%
장애인거주시설 2
 
2.7%
노인주거복지시설 2
 
2.7%
장애인직업재활시설 1
 
1.4%
Other values (8) 8
 
11.0%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
자치구
73 

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 73
100.0%

Length

2024-05-18T08:02:36.216418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:36.465040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 73
100.0%

시설장명
Text

Distinct66
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-05-18T08:02:36.869729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9863014
Min length2

Characters and Unicode

Total characters218
Distinct characters85
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

Unique61 ?
Unique (%)83.6%

Sample

1st row박창남
2nd row윤동인
3rd row김정애
4th row김민철
5th row김응종
ValueCountFrequency (%)
김경일 3
 
4.1%
서신자 3
 
4.1%
박창남 2
 
2.7%
정주원 2
 
2.7%
김유미 2
 
2.7%
박은경 1
 
1.4%
김지선 1
 
1.4%
허진옥 1
 
1.4%
차지영 1
 
1.4%
박진수 1
 
1.4%
Other values (56) 56
76.7%
2024-05-18T08:02:37.716188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 20
 
9.2%
정 11
 
5.0%
박 8
 
3.7%
영 8
 
3.7%
윤 8
 
3.7%
이 8
 
3.7%
경 7
 
3.2%
희 6
 
2.8%
지 5
 
2.3%
선 5
 
2.3%
Other values (75) 132
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 218
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 20
 
9.2%
정 11
 
5.0%
박 8
 
3.7%
영 8
 
3.7%
윤 8
 
3.7%
이 8
 
3.7%
경 7
 
3.2%
희 6
 
2.8%
지 5
 
2.3%
선 5
 
2.3%
Other values (75) 132
60.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 218
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 20
 
9.2%
정 11
 
5.0%
박 8
 
3.7%
영 8
 
3.7%
윤 8
 
3.7%
이 8
 
3.7%
경 7
 
3.2%
희 6
 
2.8%
지 5
 
2.3%
선 5
 
2.3%
Other values (75) 132
60.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 218
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 20
 
9.2%
정 11
 
5.0%
박 8
 
3.7%
영 8
 
3.7%
윤 8
 
3.7%
이 8
 
3.7%
경 7
 
3.2%
희 6
 
2.8%
지 5
 
2.3%
선 5
 
2.3%
Other values (75) 132
60.6%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
1114000000
73 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1114000000
2nd row1114000000
3rd row1114000000
4th row1114000000
5th row1114000000

Common Values

ValueCountFrequency (%)
1114000000 73
100.0%

Length

2024-05-18T08:02:38.137849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:38.571546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1114000000 73
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
중구
73 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 73
100.0%

Length

2024-05-18T08:02:39.030982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:02:39.447895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 73
100.0%

시설주소
Text

Distinct70
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-05-18T08:02:40.172297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length36
Mean length28.479452
Min length17

Characters and Unicode

Total characters2079
Distinct characters118
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)91.8%

Sample

1st row서울특별시 중구 동호로5길 189 (신당동)
2nd row서울특별시 중구 다산로6길 11신당동
3rd row서울특별시 중구 퇴계로88길 37(신당5동)
4th row서울특별시 중구 정동길 21-31 (정동)
5th row서울특별시 중구 청구로17길98 (신당동)
ValueCountFrequency (%)
서울특별시 73
 
18.0%
중구 72
 
17.8%
신당동 30
 
7.4%
2층 9
 
2.2%
중림동 8
 
2.0%
서소문로6길 6
 
1.5%
1층 6
 
1.5%
다산로 5
 
1.2%
4층 5
 
1.2%
3층 5
 
1.2%
Other values (157) 186
45.9%
2024-05-18T08:02:41.431418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
332
 
16.0%
중 89
 
4.3%
서 87
 
4.2%
구 83
 
4.0%
울 80
 
3.8%
동 78
 
3.8%
1 76
 
3.7%
시 75
 
3.6%
특 73
 
3.5%
별 73
 
3.5%
Other values (108) 1033
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1236
59.5%
Decimal Number 337
 
16.2%
Space Separator 333
 
16.0%
Open Punctuation 61
 
2.9%
Close Punctuation 61
 
2.9%
Other Punctuation 43
 
2.1%
Dash Punctuation 8
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 89
 
7.2%
서 87
 
7.0%
구 83
 
6.7%
울 80
 
6.5%
동 78
 
6.3%
시 75
 
6.1%
특 73
 
5.9%
별 73
 
5.9%
로 71
 
5.7%
길 50
 
4.0%
Other values (92) 477
38.6%
Decimal Number
ValueCountFrequency (%)
1 76
22.6%
2 62
18.4%
0 41
12.2%
3 35
10.4%
6 33
9.8%
4 25
 
7.4%
5 21
 
6.2%
8 16
 
4.7%
9 15
 
4.5%
7 13
 
3.9%
Space Separator
ValueCountFrequency (%)
332
99.7%
　 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1236
59.5%
Common 843
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 89
 
7.2%
서 87
 
7.0%
구 83
 
6.7%
울 80
 
6.5%
동 78
 
6.3%
시 75
 
6.1%
특 73
 
5.9%
별 73
 
5.9%
로 71
 
5.7%
길 50
 
4.0%
Other values (92) 477
38.6%
Common
ValueCountFrequency (%)
332
39.4%
1 76
 
9.0%
2 62
 
7.4%
( 61
 
7.2%
) 61
 
7.2%
, 43
 
5.1%
0 41
 
4.9%
3 35
 
4.2%
6 33
 
3.9%
4 25
 
3.0%
Other values (6) 74
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1236
59.5%
ASCII 842
40.5%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
332
39.4%
1 76
 
9.0%
2 62
 
7.4%
( 61
 
7.2%
) 61
 
7.2%
, 43
 
5.1%
0 41
 
4.9%
3 35
 
4.2%
6 33
 
3.9%
4 25
 
3.0%
Other values (5) 73
 
8.7%
Hangul
ValueCountFrequency (%)
중 89
 
7.2%
서 87
 
7.0%
구 83
 
6.7%
울 80
 
6.5%
동 78
 
6.3%
시 75
 
6.1%
특 73
 
5.9%
별 73
 
5.9%
로 71
 
5.7%
길 50
 
4.0%
Other values (92) 477
38.6%
None
ValueCountFrequency (%)
　 1
100.0%

정원(수용인원)
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)51.9%
Missing19
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean50.296296
Minimum0
Maximum1100
Zeros10
Zeros (%)13.7%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-05-18T08:02:41.969340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.25
median20.5
Q341.5
95-th percentile107.45
Maximum1100
Range1100
Interquartile range (IQR)36.25

Descriptive statistics

Standard deviation149.06876
Coefficient of variation (CV)2.9638119
Kurtosis48.787072
Mean50.296296
Median Absolute Deviation (MAD)19.5
Skewness6.8360532
Sum2716
Variance22221.495
MonotonicityNot monotonic
2024-05-18T08:02:42.498373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 10
13.7%
20 4
 
5.5%
40 4
 
5.5%
60 3
 
4.1%
30 3
 
4.1%
15 3
 
4.1%
1 2
 
2.7%
4 2
 
2.7%
80 2
 
2.7%
21 2
 
2.7%
Other values (18) 19
26.0%
(Missing) 19
26.0%
ValueCountFrequency (%)
0 10
13.7%
1 2
 
2.7%
4 2
 
2.7%
9 1
 
1.4%
10 1
 
1.4%
12 2
 
2.7%
14 1
 
1.4%
15 3
 
4.1%
19 1
 
1.4%
20 4
 
5.5%
ValueCountFrequency (%)
1100 1
 
1.4%
144 1
 
1.4%
125 1
 
1.4%
98 1
 
1.4%
90 1
 
1.4%
80 2
2.7%
60 3
4.1%
58 1
 
1.4%
50 1
 
1.4%
44 1
 
1.4%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)81.8%
Missing29
Missing (%)39.7%
Infinite0
Infinite (%)0.0%
Mean180.52273
Minimum1
Maximum2092
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size789.0 B
2024-05-18T08:02:43.060926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q115
median31.5
Q3106.75
95-th percentile944.55
Maximum2092
Range2091
Interquartile range (IQR)91.75

Descriptive statistics

Standard deviation394.94236
Coefficient of variation (CV)2.1877708
Kurtosis13.327441
Mean180.52273
Median Absolute Deviation (MAD)20.5
Skewness3.4675461
Sum7943
Variance155979.46
MonotonicityNot monotonic
2024-05-18T08:02:43.628405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
80 2
 
2.7%
13 2
 
2.7%
30 2
 
2.7%
60 2
 
2.7%
1 2
 
2.7%
29 2
 
2.7%
15 2
 
2.7%
20 2
 
2.7%
24 1
 
1.4%
398 1
 
1.4%
Other values (26) 26
35.6%
(Missing) 29
39.7%
ValueCountFrequency (%)
1 2
2.7%
3 1
1.4%
4 1
1.4%
9 1
1.4%
10 1
1.4%
12 1
1.4%
13 2
2.7%
14 1
1.4%
15 2
2.7%
19 1
1.4%
ValueCountFrequency (%)
2092 1
1.4%
1200 1
1.4%
957 1
1.4%
874 1
1.4%
500 1
1.4%
398 1
1.4%
270 1
1.4%
200 1
1.4%
190 1
1.4%
150 1
1.4%

전화번호
Text

Distinct72
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-05-18T08:02:44.357790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.849315
Min length9

Characters and Unicode

Total characters792
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

Unique71 ?
Unique (%)97.3%

Sample

1st row02-2238-9941
2nd row02-2234-3515
3rd row02-2238-8017
4th row027733477
5th row02-2254-0833
ValueCountFrequency (%)
02-2238-9941 2
 
2.7%
02-2234-3515 1
 
1.4%
07088276352 1
 
1.4%
023628467 1
 
1.4%
07043533005 1
 
1.4%
07044208290 1
 
1.4%
07042618910 1
 
1.4%
023628789 1
 
1.4%
07046513777 1
 
1.4%
0222313019 1
 
1.4%
Other values (62) 62
84.9%
2024-05-18T08:02:45.723309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 176
22.2%
0 131
16.5%
3 84
10.6%
7 65
 
8.2%
- 64
 
8.1%
1 54
 
6.8%
8 53
 
6.7%
5 46
 
5.8%
6 45
 
5.7%
9 40
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 728
91.9%
Dash Punctuation 64
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 176
24.2%
0 131
18.0%
3 84
11.5%
7 65
 
8.9%
1 54
 
7.4%
8 53
 
7.3%
5 46
 
6.3%
6 45
 
6.2%
9 40
 
5.5%
4 34
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 792
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 176
22.2%
0 131
16.5%
3 84
10.6%
7 65
 
8.2%
- 64
 
8.1%
1 54
 
6.8%
8 53
 
6.7%
5 46
 
5.8%
6 45
 
5.7%
9 40
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 792
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 176
22.2%
0 131
16.5%
3 84
10.6%
7 65
 
8.2%
- 64
 
8.1%
1 54
 
6.8%
8 53
 
6.7%
5 46
 
5.8%
6 45
 
5.7%
9 40
 
5.1%

우편번호
Text

Distinct47
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size716.0 B
2024-05-18T08:02:46.318798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0684932
Min length3

Characters and Unicode

Total characters370
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)41.1%

Sample

1st row04595
2nd row04597
3rd row04578
4th row04518
5th row04607
ValueCountFrequency (%)
04506 6
 
8.2%
04629 4
 
5.5%
04583 3
 
4.1%
04579 3
 
4.1%
04595 3
 
4.1%
100699 2
 
2.7%
04586 2
 
2.7%
04589 2
 
2.7%
04607 2
 
2.7%
04608 2
 
2.7%
Other values (37) 44
60.3%
2024-05-18T08:02:47.461298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 101
27.3%
4 69
18.6%
5 54
14.6%
6 36
 
9.7%
9 31
 
8.4%
8 23
 
6.2%
1 18
 
4.9%
7 16
 
4.3%
2 14
 
3.8%
3 5
 
1.4%
Other values (3) 3
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 367
99.2%
Other Letter 3
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
27.5%
4 69
18.8%
5 54
14.7%
6 36
 
9.8%
9 31
 
8.4%
8 23
 
6.3%
1 18
 
4.9%
7 16
 
4.4%
2 14
 
3.8%
3 5
 
1.4%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
울 1
33.3%
특 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 367
99.2%
Hangul 3
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 101
27.5%
4 69
18.8%
5 54
14.7%
6 36
 
9.8%
9 31
 
8.4%
8 23
 
6.3%
1 18
 
4.9%
7 16
 
4.4%
2 14
 
3.8%
3 5
 
1.4%
Hangul
ValueCountFrequency (%)
서 1
33.3%
울 1
33.3%
특 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 367
99.2%
Hangul 3
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 101
27.5%
4 69
18.8%
5 54
14.7%
6 36
 
9.8%
9 31
 
8.4%
8 23
 
6.3%
1 18
 
4.9%
7 16
 
4.4%
2 14
 
3.8%
3 5
 
1.4%
Hangul
ValueCountFrequency (%)
서 1
33.3%
울 1
33.3%
특 1
33.3%

Interactions

2024-05-18T08:02:28.366956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:02:27.550188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:02:28.967097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:02:27.884320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T08:02:47.849346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)시설장명시설주소정원(수용인원)현인원전화번호우편번호
시설명1.0001.0000.9310.0000.9970.9981.0001.0001.0001.000
시설코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시설종류명(시설유형)0.9311.0001.0001.0000.9680.0000.8560.9400.9890.000
시설종류상세명(시설종류)0.0001.0001.0001.0000.8400.0000.0000.7450.9870.000
시설장명0.9971.0000.9680.8401.0000.9981.0001.0001.0000.983
시설주소0.9981.0000.0000.0000.9981.0001.0000.8951.0001.000
정원(수용인원)1.0001.0000.8560.0001.0001.0001.0000.9201.0000.000
현인원1.0001.0000.9400.7451.0000.8950.9201.0001.0000.000
전화번호1.0001.0000.9890.9871.0001.0001.0001.0001.0001.000
우편번호1.0001.0000.0000.0000.9831.0000.0000.0001.0001.000
2024-05-18T08:02:48.180929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류상세명(시설종류)시설종류명(시설유형)
시설종류상세명(시설종류)1.0000.924
시설종류명(시설유형)0.9241.000
2024-05-18T08:02:48.476403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.0860.4660.000
현인원0.0861.0000.5940.397
시설종류명(시설유형)0.4660.5941.0000.924
시설종류상세명(시설종류)0.0000.3970.9241.000

Missing values

2024-05-18T08:02:29.447252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T08:02:30.163474image/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.
2024-05-18T08:02:30.783409image/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
0남산실버복지센터A0839(노인) 재가노인복지시설재가노인복지시설자치구박창남1114000000중구서울특별시 중구 동호로5길 189 (신당동)343402-2238-994104595
1약수노인복지관A2255(노인) 노인복지관노인여가복지시설자치구윤동인1114000000중구서울특별시 중구 다산로6길 11신당동0120002-2234-351504597
2중구재가노인지원센터A5556(노인) 재가노인복지시설재가노인복지시설자치구김정애1114000000중구서울특별시 중구 퇴계로88길 37(신당5동)808002-2238-801704578
3정동상림원A6971(노인) 노인복지주택노인주거복지시설자치구김민철1114000000중구서울특별시 중구 정동길 21-31 (정동)989802773347704518
4효심원 노인요양공동생활가정A7231(노인) 노인요양공동생활가정노인의료복지시설자치구김응종1114000000중구서울특별시 중구 청구로17길98 (신당동)9902-2254-083304607
5남산실버복지센터A7928(노인) 노인요양시설노인의료복지시설자치구박창남1114000000중구서울특별시 중구 동호로5길 189 (신당동)141402-2238-994104595
6신당데이케어센터A9412(노인) 재가노인복지시설재가노인복지시설자치구김영태1114000000중구서울특별시 중구 다산로25길 6신당동584602-2231-194904608
7남산원B0002(아동) 아동양육시설아동복지시설자치구박흥식1114000000중구서울특별시 중구 소파로2길 31남산원604902-752-983604628
8리라아동복지관B0009(아동) 아동양육시설아동복지시설자치구김두식1114000000중구경기도 안성시 용소길 65-0리라아동복지관5032031-653-3281456812
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시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
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