Overview

Dataset statistics

Number of variables13
Number of observations199
Missing cells99
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.1 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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-20397/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 정원(수용인원) and 2 other fieldsHigh correlation
시설종류명(시설유형) is highly overall correlated with 정원(수용인원) and 2 other fieldsHigh correlation
정원(수용인원) is highly overall correlated with 현인원 and 2 other fieldsHigh correlation
현인원 is highly overall correlated with 정원(수용인원) and 2 other fieldsHigh correlation
시설주소 has 2 (1.0%) missing valuesMissing
정원(수용인원) has 31 (15.6%) missing valuesMissing
현인원 has 66 (33.2%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 11 (5.5%) zerosZeros
현인원 has 7 (3.5%) zerosZeros

Reproduction

Analysis started2024-05-18 02:33:14.365723
Analysis finished2024-05-18 02:33:21.928941
Duration7.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct186
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-18T11:33:22.514551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length9.0954774
Min length3

Characters and Unicode

Total characters1810
Distinct characters241
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)87.4%

Sample

1st row동명노인복지센타
2nd row푸른햇살데이케어센터
3rd row한사랑복지센터
4th row관악노인종합사회복지관병설관악데이케어센터
5th row관악노인종합복지관
ValueCountFrequency (%)
지역아동센터 17
 
7.0%
난향요양원2 3
 
1.2%
우리동네키움센터 3
 
1.2%
신림요양원 3
 
1.2%
관악시니어클럽 2
 
0.8%
성산교회부설 2
 
0.8%
재가노인복지센터 2
 
0.8%
데이케어센터 2
 
0.8%
꿈나무공부방 2
 
0.8%
은빛요양원 2
 
0.8%
Other values (193) 204
84.3%
2024-05-18T11:33:23.602675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 116
 
6.4%
센 113
 
6.2%
지 78
 
4.3%
동 52
 
2.9%
양 52
 
2.9%
요 50
 
2.8%
원 46
 
2.5%
관 45
 
2.5%
43
 
2.4%
아 42
 
2.3%
Other values (231) 1173
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1708
94.4%
Space Separator 43
 
2.4%
Uppercase Letter 22
 
1.2%
Decimal Number 19
 
1.0%
Close Punctuation 7
 
0.4%
Open Punctuation 7
 
0.4%
Other Punctuation 3
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 116
 
6.8%
센 113
 
6.6%
지 78
 
4.6%
동 52
 
3.0%
양 52
 
3.0%
요 50
 
2.9%
원 46
 
2.7%
관 45
 
2.6%
아 42
 
2.5%
역 39
 
2.3%
Other values (213) 1075
62.9%
Uppercase Letter
ValueCountFrequency (%)
C 6
27.3%
S 5
22.7%
R 5
22.7%
I 2
 
9.1%
Y 1
 
4.5%
G 1
 
4.5%
W 1
 
4.5%
A 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
2 9
47.4%
1 7
36.8%
0 2
 
10.5%
3 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
' 2
66.7%
? 1
33.3%
Space Separator
ValueCountFrequency (%)
43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1708
94.4%
Common 79
 
4.4%
Latin 23
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 116
 
6.8%
센 113
 
6.6%
지 78
 
4.6%
동 52
 
3.0%
양 52
 
3.0%
요 50
 
2.9%
원 46
 
2.7%
관 45
 
2.6%
아 42
 
2.5%
역 39
 
2.3%
Other values (213) 1075
62.9%
Common
ValueCountFrequency (%)
43
54.4%
2 9
 
11.4%
) 7
 
8.9%
( 7
 
8.9%
1 7
 
8.9%
0 2
 
2.5%
' 2
 
2.5%
? 1
 
1.3%
3 1
 
1.3%
Latin
ValueCountFrequency (%)
C 6
26.1%
S 5
21.7%
R 5
21.7%
I 2
 
8.7%
Y 1
 
4.3%
G 1
 
4.3%
W 1
 
4.3%
Ⅱ 1
 
4.3%
A 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1708
94.4%
ASCII 101
 
5.6%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 116
 
6.8%
센 113
 
6.6%
지 78
 
4.6%
동 52
 
3.0%
양 52
 
3.0%
요 50
 
2.9%
원 46
 
2.7%
관 45
 
2.6%
아 42
 
2.5%
역 39
 
2.3%
Other values (213) 1075
62.9%
ASCII
ValueCountFrequency (%)
43
42.6%
2 9
 
8.9%
) 7
 
6.9%
( 7
 
6.9%
1 7
 
6.9%
C 6
 
5.9%
S 5
 
5.0%
R 5
 
5.0%
0 2
 
2.0%
' 2
 
2.0%
Other values (7) 8
 
7.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

시설코드
Text

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-18T11:33:24.554588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0150754
Min length5

Characters and Unicode

Total characters998
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

Unique199 ?
Unique (%)100.0%

Sample

1st rowA0100
2nd rowA1082
3rd rowA2055
4th rowA2773
5th rowA2776
ValueCountFrequency (%)
a0100 1
 
0.5%
k1579 1
 
0.5%
g5883 1
 
0.5%
g6034 1
 
0.5%
g6090 1
 
0.5%
g6409 1
 
0.5%
g6420 1
 
0.5%
g6476 1
 
0.5%
g6593 1
 
0.5%
g6877 1
 
0.5%
Other values (189) 189
95.0%
2024-05-18T11:33:26.163177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 108
10.8%
0 106
10.6%
2 96
9.6%
3 85
8.5%
5 79
7.9%
9 74
 
7.4%
6 67
 
6.7%
4 66
 
6.6%
8 65
 
6.5%
G 58
 
5.8%
Other values (12) 194
19.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 799
80.1%
Uppercase Letter 199
 
19.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 58
29.1%
B 38
19.1%
C 24
12.1%
P 22
 
11.1%
K 18
 
9.0%
A 15
 
7.5%
F 9
 
4.5%
Z 7
 
3.5%
W 3
 
1.5%
J 2
 
1.0%
Other values (2) 3
 
1.5%
Decimal Number
ValueCountFrequency (%)
1 108
13.5%
0 106
13.3%
2 96
12.0%
3 85
10.6%
5 79
9.9%
9 74
9.3%
6 67
8.4%
4 66
8.3%
8 65
8.1%
7 53
6.6%

Most occurring scripts

ValueCountFrequency (%)
Common 799
80.1%
Latin 199
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 58
29.1%
B 38
19.1%
C 24
12.1%
P 22
 
11.1%
K 18
 
9.0%
A 15
 
7.5%
F 9
 
4.5%
Z 7
 
3.5%
W 3
 
1.5%
J 2
 
1.0%
Other values (2) 3
 
1.5%
Common
ValueCountFrequency (%)
1 108
13.5%
0 106
13.3%
2 96
12.0%
3 85
10.6%
5 79
9.9%
9 74
9.3%
6 67
8.4%
4 66
8.3%
8 65
8.1%
7 53
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 108
10.8%
0 106
10.6%
2 96
9.6%
3 85
8.5%
5 79
7.9%
9 74
 
7.4%
6 67
 
6.7%
4 66
 
6.6%
8 65
 
6.5%
G 58
 
5.8%
Other values (12) 194
19.4%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
(노인) 재가노인복지시설
54 
(아동) 지역아동센터
38 
(노인) 노인요양공동생활가정
32 
(노인) 노인요양시설
11 
(아동) 공동생활가정
9 
Other values (29)
55 

Length

Max length21
Median length20
Mean length12.979899
Min length10

Unique

Unique17 ?
Unique (%)8.5%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 54
27.1%
(아동) 지역아동센터 38
19.1%
(노인) 노인요양공동생활가정 32
16.1%
(노인) 노인요양시설 11
 
5.5%
(아동) 공동생활가정 9
 
4.5%
(장애인) 장애인공동생활가정 6
 
3.0%
(장애인) 장애인주간보호시설 5
 
2.5%
(일반) 사회복지관 5
 
2.5%
(장애인) 장애인보호작업장 4
 
2.0%
(아동) 다함께돌봄센터 3
 
1.5%
Other values (24) 32
16.1%

Length

2024-05-18T11:33:26.806503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 101
25.4%
아동 56
14.1%
재가노인복지시설 54
13.6%
지역아동센터 38
 
9.5%
노인요양공동생활가정 32
 
8.0%
장애인 25
 
6.3%
노인요양시설 11
 
2.8%
공동생활가정 9
 
2.3%
정신보건 7
 
1.8%
장애인공동생활가정 6
 
1.5%
Other values (33) 59
14.8%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
아동복지시설
56 
재가노인복지시설
54 
노인의료복지시설
43 
장애인지역사회재활시설
9 
장애인거주시설
8 
Other values (13)
29 

Length

Max length11
Median length8
Mean length7.3919598
Min length4

Unique

Unique7 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
아동복지시설 56
28.1%
재가노인복지시설 54
27.1%
노인의료복지시설 43
21.6%
장애인지역사회재활시설 9
 
4.5%
장애인거주시설 8
 
4.0%
정신재활시설 6
 
3.0%
장애인직업재활시설 5
 
2.5%
일반사회복지시설 5
 
2.5%
자활시설 2
 
1.0%
노인기타 2
 
1.0%
Other values (8) 9
 
4.5%

Length

2024-05-18T11:33:27.400894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동복지시설 56
28.1%
재가노인복지시설 54
27.1%
노인의료복지시설 43
21.6%
장애인지역사회재활시설 9
 
4.5%
장애인거주시설 8
 
4.0%
정신재활시설 6
 
3.0%
장애인직업재활시설 5
 
2.5%
일반사회복지시설 5
 
2.5%
장애인의료재활시설 2
 
1.0%
노인기타 2
 
1.0%
Other values (8) 9
 
4.5%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
자치구
199 

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 199
100.0%

Length

2024-05-18T11:33:27.935586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:33:28.309578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 199
100.0%

시설장명
Text

Distinct171
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-18T11:33:29.134276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9899497
Min length2

Characters and Unicode

Total characters595
Distinct characters124
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

Unique144 ?
Unique (%)72.4%

Sample

1st row김병한
2nd row최성숙
3rd row한정옥
4th row김동호
5th row김동호
ValueCountFrequency (%)
부청하 3
 
1.5%
김광빈 2
 
1.0%
김정희 2
 
1.0%
김미혜 2
 
1.0%
이재영 2
 
1.0%
정여정 2
 
1.0%
곽지연 2
 
1.0%
최보경 2
 
1.0%
박병요 2
 
1.0%
이경아 2
 
1.0%
Other values (161) 178
89.4%
2024-05-18T11:33:30.475703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 45
 
7.6%
박 30
 
5.0%
이 30
 
5.0%
정 26
 
4.4%
영 21
 
3.5%
희 20
 
3.4%
미 19
 
3.2%
경 15
 
2.5%
성 13
 
2.2%
숙 12
 
2.0%
Other values (114) 364
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 595
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 45
 
7.6%
박 30
 
5.0%
이 30
 
5.0%
정 26
 
4.4%
영 21
 
3.5%
희 20
 
3.4%
미 19
 
3.2%
경 15
 
2.5%
성 13
 
2.2%
숙 12
 
2.0%
Other values (114) 364
61.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 595
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 45
 
7.6%
박 30
 
5.0%
이 30
 
5.0%
정 26
 
4.4%
영 21
 
3.5%
희 20
 
3.4%
미 19
 
3.2%
경 15
 
2.5%
성 13
 
2.2%
숙 12
 
2.0%
Other values (114) 364
61.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 595
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 45
 
7.6%
박 30
 
5.0%
이 30
 
5.0%
정 26
 
4.4%
영 21
 
3.5%
희 20
 
3.4%
미 19
 
3.2%
경 15
 
2.5%
성 13
 
2.2%
숙 12
 
2.0%
Other values (114) 364
61.2%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1162000000
199 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1162000000
2nd row1162000000
3rd row1162000000
4th row1162000000
5th row1162000000

Common Values

ValueCountFrequency (%)
1162000000 199
100.0%

Length

2024-05-18T11:33:30.924198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:33:31.248836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1162000000 199
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
관악구
199 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관악구 199
100.0%

Length

2024-05-18T11:33:31.638165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T11:33:31.956755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관악구 199
100.0%

시설주소
Text

MISSING 

Distinct187
Distinct (%)94.9%
Missing2
Missing (%)1.0%
Memory size1.7 KiB
2024-05-18T11:33:32.866487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length39
Mean length27.766497
Min length16

Characters and Unicode

Total characters5470
Distinct characters159
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

Unique178 ?
Unique (%)90.4%

Sample

1st row서울특별시 관악구 봉천로23라길 15(봉천동)
2nd row서울특별시 관악구 난곡로 110(난항동)
3rd row서울특별시 관악구 은천로 83-1
4th row서울특별시 관악구 보라매로 35(봉천동)
5th row서울특별시 관악구 보라매로 35(봉천동)
ValueCountFrequency (%)
서울특별시 192
18.0%
관악구 192
18.0%
신림동 81
 
7.6%
봉천동 53
 
5.0%
2층 21
 
2.0%
3층 21
 
2.0%
남부순환로 20
 
1.9%
4층 18
 
1.7%
난곡로 14
 
1.3%
관악로 11
 
1.0%
Other values (306) 444
41.6%
2024-05-18T11:33:34.369492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
871
 
15.9%
관 218
 
4.0%
악 211
 
3.9%
시 198
 
3.6%
구 197
 
3.6%
1 196
 
3.6%
별 193
 
3.5%
서 192
 
3.5%
특 192
 
3.5%
울 192
 
3.5%
Other values (149) 2810
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3210
58.7%
Decimal Number 893
 
16.3%
Space Separator 871
 
15.9%
Open Punctuation 162
 
3.0%
Close Punctuation 162
 
3.0%
Other Punctuation 133
 
2.4%
Dash Punctuation 30
 
0.5%
Math Symbol 6
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 218
 
6.8%
악 211
 
6.6%
시 198
 
6.2%
구 197
 
6.1%
별 193
 
6.0%
서 192
 
6.0%
특 192
 
6.0%
울 192
 
6.0%
동 172
 
5.4%
로 143
 
4.5%
Other values (127) 1302
40.6%
Decimal Number
ValueCountFrequency (%)
1 196
21.9%
2 137
15.3%
3 118
13.2%
4 106
11.9%
0 82
9.2%
6 73
 
8.2%
5 63
 
7.1%
7 56
 
6.3%
9 31
 
3.5%
8 31
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 129
97.0%
. 2
 
1.5%
@ 1
 
0.8%
/ 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
R 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
871
100.0%
Open Punctuation
ValueCountFrequency (%)
( 162
100.0%
Close Punctuation
ValueCountFrequency (%)
) 162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3210
58.7%
Common 2257
41.3%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 218
 
6.8%
악 211
 
6.6%
시 198
 
6.2%
구 197
 
6.1%
별 193
 
6.0%
서 192
 
6.0%
특 192
 
6.0%
울 192
 
6.0%
동 172
 
5.4%
로 143
 
4.5%
Other values (127) 1302
40.6%
Common
ValueCountFrequency (%)
871
38.6%
1 196
 
8.7%
( 162
 
7.2%
) 162
 
7.2%
2 137
 
6.1%
, 129
 
5.7%
3 118
 
5.2%
4 106
 
4.7%
0 82
 
3.6%
6 73
 
3.2%
Other values (9) 221
 
9.8%
Latin
ValueCountFrequency (%)
C 1
33.3%
R 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3210
58.7%
ASCII 2260
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
871
38.5%
1 196
 
8.7%
( 162
 
7.2%
) 162
 
7.2%
2 137
 
6.1%
, 129
 
5.7%
3 118
 
5.2%
4 106
 
4.7%
0 82
 
3.6%
6 73
 
3.2%
Other values (12) 224
 
9.9%
Hangul
ValueCountFrequency (%)
관 218
 
6.8%
악 211
 
6.6%
시 198
 
6.2%
구 197
 
6.1%
별 193
 
6.0%
서 192
 
6.0%
특 192
 
6.0%
울 192
 
6.0%
동 172
 
5.4%
로 143
 
4.5%
Other values (127) 1302
40.6%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct47
Distinct (%)28.0%
Missing31
Missing (%)15.6%
Infinite0
Infinite (%)0.0%
Mean40.952381
Minimum0
Maximum1000
Zeros11
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-18T11:33:35.055400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median19
Q337
95-th percentile99
Maximum1000
Range1000
Interquartile range (IQR)28

Descriptive statistics

Standard deviation106.47227
Coefficient of variation (CV)2.5999044
Kurtosis55.141647
Mean40.952381
Median Absolute Deviation (MAD)11
Skewness7.0360825
Sum6880
Variance11336.345
MonotonicityNot monotonic
2024-05-18T11:33:35.611950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
9 32
16.1%
7 11
 
5.5%
0 11
 
5.5%
49 10
 
5.0%
19 8
 
4.0%
35 7
 
3.5%
20 7
 
3.5%
4 6
 
3.0%
29 6
 
3.0%
21 4
 
2.0%
Other values (37) 66
33.2%
(Missing) 31
15.6%
ValueCountFrequency (%)
0 11
 
5.5%
4 6
 
3.0%
5 2
 
1.0%
6 2
 
1.0%
7 11
 
5.5%
9 32
16.1%
10 2
 
1.0%
13 3
 
1.5%
15 2
 
1.0%
16 1
 
0.5%
ValueCountFrequency (%)
1000 1
 
0.5%
800 1
 
0.5%
406 1
 
0.5%
300 2
1.0%
114 1
 
0.5%
105 1
 
0.5%
100 1
 
0.5%
99 3
1.5%
90 1
 
0.5%
80 1
 
0.5%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct64
Distinct (%)48.1%
Missing66
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean152.10526
Minimum0
Maximum8000
Zeros7
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-18T11:33:36.216694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q19
median20
Q341
95-th percentile771.4
Maximum8000
Range8000
Interquartile range (IQR)32

Descriptive statistics

Standard deviation730.2482
Coefficient of variation (CV)4.8009397
Kurtosis102.95988
Mean152.10526
Median Absolute Deviation (MAD)15
Skewness9.6904518
Sum20230
Variance533262.43
MonotonicityNot monotonic
2024-05-18T11:33:37.035463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 17
 
8.5%
0 7
 
3.5%
5 6
 
3.0%
17 6
 
3.0%
4 6
 
3.0%
28 5
 
2.5%
10 4
 
2.0%
3 4
 
2.0%
21 4
 
2.0%
100 3
 
1.5%
Other values (54) 71
35.7%
(Missing) 66
33.2%
ValueCountFrequency (%)
0 7
3.5%
1 1
 
0.5%
2 1
 
0.5%
3 4
 
2.0%
4 6
 
3.0%
5 6
 
3.0%
6 1
 
0.5%
7 1
 
0.5%
9 17
8.5%
10 4
 
2.0%
ValueCountFrequency (%)
8000 1
0.5%
1800 1
0.5%
1100 1
0.5%
1000 2
1.0%
816 1
0.5%
790 1
0.5%
759 1
0.5%
700 1
0.5%
497 1
0.5%
432 1
0.5%

전화번호
Text

Distinct181
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-05-18T11:33:38.102955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.115578
Min length8

Characters and Unicode

Total characters2013
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

Unique171 ?
Unique (%)85.9%

Sample

1st row02-875-2770
2nd row02-851-2833
3rd row02-3285-8969
4th row02-888-9978
5th row02-888-6144
ValueCountFrequency (%)
028666028 4
 
2.0%
028575882 4
 
2.0%
028888833 4
 
2.0%
028564382 3
 
1.5%
028821592 3
 
1.5%
028623090 2
 
1.0%
028877783 2
 
1.0%
028761117 2
 
1.0%
028554382 2
 
1.0%
028586690 2
 
1.0%
Other values (171) 171
85.9%
2024-05-18T11:33:39.699843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 348
17.3%
0 320
15.9%
2 286
14.2%
- 185
9.2%
7 165
8.2%
5 164
8.1%
6 125
 
6.2%
1 124
 
6.2%
3 112
 
5.6%
9 104
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1828
90.8%
Dash Punctuation 185
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 348
19.0%
0 320
17.5%
2 286
15.6%
7 165
9.0%
5 164
9.0%
6 125
 
6.8%
1 124
 
6.8%
3 112
 
6.1%
9 104
 
5.7%
4 80
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2013
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 348
17.3%
0 320
15.9%
2 286
14.2%
- 185
9.2%
7 165
8.2%
5 164
8.1%
6 125
 
6.2%
1 124
 
6.2%
3 112
 
5.6%
9 104
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2013
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 348
17.3%
0 320
15.9%
2 286
14.2%
- 185
9.2%
7 165
8.2%
5 164
8.1%
6 125
 
6.2%
1 124
 
6.2%
3 112
 
5.6%
9 104
 
5.2%

우편번호
Real number (ℝ)

Distinct101
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30344.126
Minimum8703
Maximum482845
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-05-18T11:33:40.330247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8703
5-th percentile8710.9
Q18754.5
median8797
Q38853.5
95-th percentile151802.9
Maximum482845
Range474142
Interquartile range (IQR)99

Descriptive statistics

Standard deviation64108.236
Coefficient of variation (CV)2.1127067
Kurtosis22.41275
Mean30344.126
Median Absolute Deviation (MAD)52
Skewness4.1466622
Sum6038481
Variance4.109866 × 109
MonotonicityNot monotonic
2024-05-18T11:33:41.008672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
151600 13
 
6.5%
8771 10
 
5.0%
8864 6
 
3.0%
8859 5
 
2.5%
8785 4
 
2.0%
8832 4
 
2.0%
8708 4
 
2.0%
8726 4
 
2.0%
8850 4
 
2.0%
8772 4
 
2.0%
Other values (91) 141
70.9%
ValueCountFrequency (%)
8703 2
1.0%
8705 1
 
0.5%
8708 4
2.0%
8709 2
1.0%
8710 1
 
0.5%
8711 1
 
0.5%
8713 3
1.5%
8715 2
1.0%
8716 1
 
0.5%
8717 3
1.5%
ValueCountFrequency (%)
482845 1
0.5%
464863 1
0.5%
151906 1
0.5%
151901 1
0.5%
151894 1
0.5%
151888 1
0.5%
151873 1
0.5%
151866 1
0.5%
151829 2
1.0%
151800 2
1.0%

Interactions

2024-05-18T11:33:18.015297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:15.855390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:16.853784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:18.370041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:16.155099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:17.291006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:18.792627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:16.479502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T11:33:17.635826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T11:33:41.388302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0000.9530.9570.662
시설종류상세명(시설종류)1.0001.0000.8970.8730.401
정원(수용인원)0.9530.8971.0000.4820.000
현인원0.9570.8730.4821.0000.000
우편번호0.6620.4010.0000.0001.000
2024-05-18T11:33:41.792556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류상세명(시설종류)시설종류명(시설유형)
시설종류상세명(시설종류)1.0000.955
시설종류명(시설유형)0.9551.000
2024-05-18T11:33:42.040896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.6730.0620.7850.721
현인원0.6731.0000.0300.7490.682
우편번호0.0620.0301.0000.3720.222
시설종류명(시설유형)0.7850.7490.3721.0000.955
시설종류상세명(시설종류)0.7210.6820.2220.9551.000

Missing values

2024-05-18T11:33:19.844623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T11:33:21.161103image/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.
2024-05-18T11:33:21.723065image/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
0동명노인복지센타A0100(노인) 노인요양시설노인의료복지시설자치구김병한1162000000관악구서울특별시 관악구 봉천로23라길 15(봉천동)909002-875-2770151829
1푸른햇살데이케어센터A1082(노인) 재가노인복지시설재가노인복지시설자치구최성숙1162000000관악구서울특별시 관악구 난곡로 110(난항동)222202-851-28338860
2한사랑복지센터A2055(노인) 재가노인복지시설재가노인복지시설자치구한정옥1162000000관악구서울특별시 관악구 은천로 83-10002-3285-89698715
3관악노인종합사회복지관병설관악데이케어센터A2773(노인) 재가노인복지시설재가노인복지시설자치구김동호1162000000관악구서울특별시 관악구 보라매로 35(봉천동)<NA><NA>02-888-99788708
4관악노인종합복지관A2776(노인) 노인복지관노인여가복지시설자치구김동호1162000000관악구서울특별시 관악구 보라매로 35(봉천동)1000100002-888-61448708
5관악실버케어A5072(노인) 노인요양시설노인의료복지시설자치구정윤성1162000000관악구서울특별시 관악구 대학18길 34-7 (신림동)171702-875-31148820
6상록재가노인지원센터A5801(노인) 재가노인복지시설재가노인복지시설자치구김선옥1162000000관악구서울특별시 관악구 남현길 63(남현동)8011302-521-7097151800
7수호데이케어센터A5914(노인) 재가노인복지시설재가노인복지시설자치구박홍래1162000000관악구서울특별시 관악구 인헌길 161-9(인헌동)201902-888-10888800
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