Overview

Dataset statistics

Number of variables13
Number of observations141
Missing cells74
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.0 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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-20389/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 정원(수용인원) and 2 other fieldsHigh correlation
시설종류상세명(시설종류) is highly overall correlated with 시설종류명(시설유형)High correlation
정원(수용인원) is highly overall correlated with 현인원 and 1 other fieldsHigh correlation
현인원 is highly overall correlated with 정원(수용인원) and 1 other fieldsHigh correlation
시설장명 has 3 (2.1%) missing valuesMissing
정원(수용인원) has 33 (23.4%) missing valuesMissing
현인원 has 38 (27.0%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 5 (3.5%) zerosZeros

Reproduction

Analysis started2024-05-18 00:31:39.577931
Analysis finished2024-05-18 00:31:46.027111
Duration6.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct139
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T09:31:46.345701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length19
Mean length10.432624
Min length2

Characters and Unicode

Total characters1471
Distinct characters226
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

Unique137 ?
Unique (%)97.2%

Sample

1st row효림재가노인지원센터
2nd row중앙소규모요양시설
3rd row북가좌노인복지관
4th row효림데이케어센터
5th row효림노인요양센터
ValueCountFrequency (%)
우리동네키움센터 9
 
4.9%
서대문구 8
 
4.4%
재가복지센터 3
 
1.6%
문화촌데이케어센터 2
 
1.1%
서대문 2
 
1.1%
성산100세노인요양공동생활가정 2
 
1.1%
노인요양시설 2
 
1.1%
신일지역아동센터 2
 
1.1%
시니어 1
 
0.5%
홍제천데이케어센터 1
 
0.5%
Other values (150) 150
82.4%
2024-05-18T09:31:47.364481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 79
 
5.4%
센 76
 
5.2%
지 46
 
3.1%
동 42
 
2.9%
서 42
 
2.9%
문 41
 
2.8%
41
 
2.8%
인 39
 
2.7%
가 35
 
2.4%
대 35
 
2.4%
Other values (216) 995
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1398
95.0%
Space Separator 41
 
2.8%
Decimal Number 23
 
1.6%
Uppercase Letter 3
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 79
 
5.7%
센 76
 
5.4%
지 46
 
3.3%
동 42
 
3.0%
서 42
 
3.0%
문 41
 
2.9%
인 39
 
2.8%
가 35
 
2.5%
대 35
 
2.5%
어 29
 
2.1%
Other values (198) 934
66.8%
Decimal Number
ValueCountFrequency (%)
1 6
26.1%
0 6
26.1%
2 2
 
8.7%
8 2
 
8.7%
3 2
 
8.7%
4 1
 
4.3%
7 1
 
4.3%
6 1
 
4.3%
5 1
 
4.3%
9 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
C 1
33.3%
D 1
33.3%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1398
95.0%
Common 70
 
4.8%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 79
 
5.7%
센 76
 
5.4%
지 46
 
3.3%
동 42
 
3.0%
서 42
 
3.0%
문 41
 
2.9%
인 39
 
2.8%
가 35
 
2.5%
대 35
 
2.5%
어 29
 
2.1%
Other values (198) 934
66.8%
Common
ValueCountFrequency (%)
41
58.6%
1 6
 
8.6%
0 6
 
8.6%
( 2
 
2.9%
2 2
 
2.9%
) 2
 
2.9%
8 2
 
2.9%
3 2
 
2.9%
< 1
 
1.4%
> 1
 
1.4%
Other values (5) 5
 
7.1%
Latin
ValueCountFrequency (%)
M 1
33.3%
C 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1398
95.0%
ASCII 73
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 79
 
5.7%
센 76
 
5.4%
지 46
 
3.3%
동 42
 
3.0%
서 42
 
3.0%
문 41
 
2.9%
인 39
 
2.8%
가 35
 
2.5%
대 35
 
2.5%
어 29
 
2.1%
Other values (198) 934
66.8%
ASCII
ValueCountFrequency (%)
41
56.2%
1 6
 
8.2%
0 6
 
8.2%
( 2
 
2.7%
2 2
 
2.7%
) 2
 
2.7%
8 2
 
2.7%
3 2
 
2.7%
M 1
 
1.4%
< 1
 
1.4%
Other values (8) 8
 
11.0%

시설코드
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T09:31:48.124566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0283688
Min length5

Characters and Unicode

Total characters709
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

Unique141 ?
Unique (%)100.0%

Sample

1st rowA0738
2nd rowA1302
3rd rowA1599
4th rowA1721
5th rowA1723
ValueCountFrequency (%)
a0738 1
 
0.7%
g4693 1
 
0.7%
g5178 1
 
0.7%
g5338 1
 
0.7%
g6445 1
 
0.7%
g6642 1
 
0.7%
g8409 1
 
0.7%
g8461 1
 
0.7%
g5171 1
 
0.7%
f14072 1
 
0.7%
Other values (131) 131
92.9%
2024-05-18T09:31:49.508950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 99
14.0%
3 65
9.2%
7 59
8.3%
2 58
8.2%
1 56
 
7.9%
6 54
 
7.6%
9 48
 
6.8%
8 45
 
6.3%
5 45
 
6.3%
4 39
 
5.5%
Other values (13) 141
19.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 568
80.1%
Uppercase Letter 141
 
19.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 27
19.1%
A 19
13.5%
B 18
12.8%
P 18
12.8%
C 17
12.1%
F 11
7.8%
K 10
 
7.1%
Z 7
 
5.0%
D 4
 
2.8%
E 4
 
2.8%
Other values (3) 6
 
4.3%
Decimal Number
ValueCountFrequency (%)
0 99
17.4%
3 65
11.4%
7 59
10.4%
2 58
10.2%
1 56
9.9%
6 54
9.5%
9 48
8.5%
8 45
7.9%
5 45
7.9%
4 39
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
Common 568
80.1%
Latin 141
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 27
19.1%
A 19
13.5%
B 18
12.8%
P 18
12.8%
C 17
12.1%
F 11
7.8%
K 10
 
7.1%
Z 7
 
5.0%
D 4
 
2.8%
E 4
 
2.8%
Other values (3) 6
 
4.3%
Common
ValueCountFrequency (%)
0 99
17.4%
3 65
11.4%
7 59
10.4%
2 58
10.2%
1 56
9.9%
6 54
9.5%
9 48
8.5%
8 45
7.9%
5 45
7.9%
4 39
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 99
14.0%
3 65
9.2%
7 59
8.3%
2 58
8.2%
1 56
 
7.9%
6 54
 
7.6%
9 48
 
6.8%
8 45
 
6.3%
5 45
 
6.3%
4 39
 
5.5%
Other values (13) 141
19.9%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
(노인) 재가노인복지시설
45 
(노인) 노인요양시설
11 
(아동) 지역아동센터
10 
(아동) 다함께돌봄센터
9 
(노인) 노인요양공동생활가정
8 
Other values (28)
58 

Length

Max length27
Median length20
Mean length13.524823
Min length9

Unique

Unique13 ?
Unique (%)9.2%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 45
31.9%
(노인) 노인요양시설 11
 
7.8%
(아동) 지역아동센터 10
 
7.1%
(아동) 다함께돌봄센터 9
 
6.4%
(노인) 노인요양공동생활가정 8
 
5.7%
(아동) 아동양육시설 6
 
4.3%
(장애인) 장애인공동생활가정 5
 
3.5%
(정신보건) 재활훈련시설-공동생활가정 5
 
3.5%
(아동) 공동생활가정 4
 
2.8%
(노인) 노인복지관(소규모) 3
 
2.1%
Other values (23) 35
24.8%

Length

2024-05-18T09:31:50.232234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 70
24.8%
재가노인복지시설 45
16.0%
아동 29
10.3%
장애인 19
 
6.7%
노인요양시설 11
 
3.9%
지역아동센터 10
 
3.5%
다함께돌봄센터 9
 
3.2%
노인요양공동생활가정 8
 
2.8%
정신보건 7
 
2.5%
아동양육시설 6
 
2.1%
Other values (35) 68
24.1%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
재가노인복지시설
45 
아동복지시설
29 
노인의료복지시설
19 
장애인거주시설
7 
정신재활시설
7 
Other values (15)
34 

Length

Max length11
Median length8
Mean length7.4964539
Min length4

Unique

Unique8 ?
Unique (%)5.7%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 45
31.9%
아동복지시설 29
20.6%
노인의료복지시설 19
13.5%
장애인거주시설 7
 
5.0%
정신재활시설 7
 
5.0%
장애인지역사회재활시설 7
 
5.0%
한부모가족복지시설 4
 
2.8%
노인여가복지시설 4
 
2.8%
노숙인등생활시설 3
 
2.1%
일반사회복지시설 3
 
2.1%
Other values (10) 13
 
9.2%

Length

2024-05-18T09:31:51.145646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재가노인복지시설 45
31.9%
아동복지시설 29
20.6%
노인의료복지시설 19
13.5%
장애인거주시설 7
 
5.0%
정신재활시설 7
 
5.0%
장애인지역사회재활시설 7
 
5.0%
한부모가족복지시설 4
 
2.8%
노인여가복지시설 4
 
2.8%
일반사회복지시설 3
 
2.1%
장애인직업재활시설 3
 
2.1%
Other values (10) 13
 
9.2%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
자치구
141 

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 141
100.0%

Length

2024-05-18T09:31:51.660878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:31:52.064359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 141
100.0%

시설장명
Text

MISSING 

Distinct119
Distinct (%)86.2%
Missing3
Missing (%)2.1%
Memory size1.2 KiB
2024-05-18T09:31:52.844358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9927536
Min length2

Characters and Unicode

Total characters413
Distinct characters102
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

Unique104 ?
Unique (%)75.4%

Sample

1st row김동숙
2nd row박형준
3rd row이은희
4th row김동금
5th row김동금
ValueCountFrequency (%)
정혜선 4
 
2.9%
박형준 3
 
2.2%
이은희 3
 
2.2%
전윤서 2
 
1.4%
김호규 2
 
1.4%
강주현 2
 
1.4%
권명심 2
 
1.4%
장미영 2
 
1.4%
추남숙 2
 
1.4%
백영수 2
 
1.4%
Other values (109) 114
82.6%
2024-05-18T09:31:54.023147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 30
 
7.3%
정 23
 
5.6%
영 18
 
4.4%
미 16
 
3.9%
이 15
 
3.6%
희 15
 
3.6%
혜 12
 
2.9%
성 10
 
2.4%
숙 9
 
2.2%
윤 9
 
2.2%
Other values (92) 256
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 413
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 30
 
7.3%
정 23
 
5.6%
영 18
 
4.4%
미 16
 
3.9%
이 15
 
3.6%
희 15
 
3.6%
혜 12
 
2.9%
성 10
 
2.4%
숙 9
 
2.2%
윤 9
 
2.2%
Other values (92) 256
62.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 413
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 30
 
7.3%
정 23
 
5.6%
영 18
 
4.4%
미 16
 
3.9%
이 15
 
3.6%
희 15
 
3.6%
혜 12
 
2.9%
성 10
 
2.4%
숙 9
 
2.2%
윤 9
 
2.2%
Other values (92) 256
62.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 413
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 30
 
7.3%
정 23
 
5.6%
영 18
 
4.4%
미 16
 
3.9%
이 15
 
3.6%
희 15
 
3.6%
혜 12
 
2.9%
성 10
 
2.4%
숙 9
 
2.2%
윤 9
 
2.2%
Other values (92) 256
62.0%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1141000000
141 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1141000000
2nd row1141000000
3rd row1141000000
4th row1141000000
5th row1141000000

Common Values

ValueCountFrequency (%)
1141000000 141
100.0%

Length

2024-05-18T09:31:54.495757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:31:54.795736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1141000000 141
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
서대문구
141 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서대문구 141
100.0%

Length

2024-05-18T09:31:55.247049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:31:55.717080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서대문구 141
100.0%

시설주소
Text

Distinct136
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T09:31:56.635922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length28.70922
Min length17

Characters and Unicode

Total characters4048
Distinct characters143
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)93.6%

Sample

1st row서울특별시 서대문구 경기대로9길 62-01-38
2nd row서울특별시 서대문구 서소문로 43-49 (합동)
3rd row서울특별시 서대문구 증가로20길 43북가좌2동노인복지센터
4th row서울특별시 서대문구 경기대로9길 624층
5th row서울특별시 서대문구 경기대로9길 62 (충정로3가)
ValueCountFrequency (%)
서대문구 140
19.3%
서울특별시 139
19.1%
홍은동 21
 
2.9%
2층 20
 
2.8%
홍제동 17
 
2.3%
북가좌동 16
 
2.2%
남가좌동 11
 
1.5%
연희로 10
 
1.4%
연희동 10
 
1.4%
1층 10
 
1.4%
Other values (238) 332
45.7%
2024-05-18T09:31:58.074562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
588
 
14.5%
서 288
 
7.1%
문 162
 
4.0%
대 160
 
4.0%
구 142
 
3.5%
시 141
 
3.5%
울 141
 
3.5%
특 139
 
3.4%
별 139
 
3.4%
1 131
 
3.2%
Other values (133) 2017
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2502
61.8%
Decimal Number 614
 
15.2%
Space Separator 588
 
14.5%
Close Punctuation 115
 
2.8%
Open Punctuation 115
 
2.8%
Other Punctuation 69
 
1.7%
Dash Punctuation 41
 
1.0%
Math Symbol 3
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 288
 
11.5%
문 162
 
6.5%
대 160
 
6.4%
구 142
 
5.7%
시 141
 
5.6%
울 141
 
5.6%
특 139
 
5.6%
별 139
 
5.6%
동 125
 
5.0%
로 119
 
4.8%
Other values (115) 946
37.8%
Decimal Number
ValueCountFrequency (%)
1 131
21.3%
2 107
17.4%
3 74
12.1%
4 67
10.9%
5 54
8.8%
0 52
 
8.5%
6 39
 
6.4%
7 32
 
5.2%
9 30
 
4.9%
8 28
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 67
97.1%
. 2
 
2.9%
Space Separator
ValueCountFrequency (%)
588
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2502
61.8%
Common 1545
38.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 288
 
11.5%
문 162
 
6.5%
대 160
 
6.4%
구 142
 
5.7%
시 141
 
5.6%
울 141
 
5.6%
특 139
 
5.6%
별 139
 
5.6%
동 125
 
5.0%
로 119
 
4.8%
Other values (115) 946
37.8%
Common
ValueCountFrequency (%)
588
38.1%
1 131
 
8.5%
) 115
 
7.4%
( 115
 
7.4%
2 107
 
6.9%
3 74
 
4.8%
, 67
 
4.3%
4 67
 
4.3%
5 54
 
3.5%
0 52
 
3.4%
Other values (7) 175
 
11.3%
Latin
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2502
61.8%
ASCII 1545
38.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
588
38.1%
1 131
 
8.5%
) 115
 
7.4%
( 115
 
7.4%
2 107
 
6.9%
3 74
 
4.8%
, 67
 
4.3%
4 67
 
4.3%
5 54
 
3.5%
0 52
 
3.4%
Other values (7) 175
 
11.3%
Hangul
ValueCountFrequency (%)
서 288
 
11.5%
문 162
 
6.5%
대 160
 
6.4%
구 142
 
5.7%
시 141
 
5.6%
울 141
 
5.6%
특 139
 
5.6%
별 139
 
5.6%
동 125
 
5.0%
로 119
 
4.8%
Other values (115) 946
37.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct46
Distinct (%)42.6%
Missing33
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean44.638889
Minimum0
Maximum1000
Zeros5
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-18T09:31:58.774407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19.75
median22.5
Q335.25
95-th percentile136
Maximum1000
Range1000
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation107.40007
Coefficient of variation (CV)2.4059754
Kurtosis60.344343
Mean44.638889
Median Absolute Deviation (MAD)13
Skewness7.2023988
Sum4821
Variance11534.775
MonotonicityNot monotonic
2024-05-18T09:31:59.260690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
21 8
 
5.7%
9 6
 
4.3%
4 6
 
4.3%
30 5
 
3.5%
25 5
 
3.5%
0 5
 
3.5%
28 4
 
2.8%
17 4
 
2.8%
10 4
 
2.8%
7 4
 
2.8%
Other values (36) 57
40.4%
(Missing) 33
23.4%
ValueCountFrequency (%)
0 5
3.5%
4 6
4.3%
5 2
 
1.4%
6 2
 
1.4%
7 4
2.8%
8 2
 
1.4%
9 6
4.3%
10 4
2.8%
15 2
 
1.4%
17 4
2.8%
ValueCountFrequency (%)
1000 1
0.7%
398 1
0.7%
300 1
0.7%
190 1
0.7%
160 1
0.7%
150 1
0.7%
110 1
0.7%
106 1
0.7%
100 1
0.7%
99 1
0.7%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct55
Distinct (%)53.4%
Missing38
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean84.786408
Minimum0
Maximum1666
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-18T09:31:59.842800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.1
Q19
median20
Q336.5
95-th percentile572.9
Maximum1666
Range1666
Interquartile range (IQR)27.5

Descriptive statistics

Standard deviation239.58975
Coefficient of variation (CV)2.8258038
Kurtosis25.179989
Mean84.786408
Median Absolute Deviation (MAD)12
Skewness4.7840833
Sum8733
Variance57403.248
MonotonicityNot monotonic
2024-05-18T09:32:00.725373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 6
 
4.3%
4 6
 
4.3%
21 5
 
3.5%
15 5
 
3.5%
3 4
 
2.8%
10 4
 
2.8%
24 4
 
2.8%
18 4
 
2.8%
6 4
 
2.8%
8 4
 
2.8%
Other values (45) 57
40.4%
(Missing) 38
27.0%
ValueCountFrequency (%)
0 1
 
0.7%
2 1
 
0.7%
3 4
2.8%
4 6
4.3%
5 2
 
1.4%
6 4
2.8%
7 3
2.1%
8 4
2.8%
9 2
 
1.4%
10 4
2.8%
ValueCountFrequency (%)
1666 1
0.7%
1300 1
0.7%
800 1
0.7%
671 1
0.7%
600 2
1.4%
329 1
0.7%
243 1
0.7%
170 1
0.7%
160 1
0.7%
130 1
0.7%

전화번호
Text

Distinct133
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-18T09:32:01.627951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.340426
Min length8

Characters and Unicode

Total characters1458
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 (%)90.1%

Sample

1st row02-313-5124
2nd row02-362-9262
3rd row02-376-5040
4th row02-313-5124
5th row02-313-5124
ValueCountFrequency (%)
02-313-5124 3
 
2.1%
0269569961 3
 
2.1%
02-362-9262 2
 
1.4%
02-391-1355 2
 
1.4%
02-392-3080 2
 
1.4%
023523520 2
 
1.4%
023918678 1
 
0.7%
01030062596 1
 
0.7%
02-396-2384 1
 
0.7%
01040536619 1
 
0.7%
Other values (123) 123
87.2%
2024-05-18T09:32:03.248013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 247
16.9%
2 242
16.6%
3 229
15.7%
- 146
10.0%
9 109
7.5%
1 100
6.9%
7 98
 
6.7%
6 86
 
5.9%
5 81
 
5.6%
4 62
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1312
90.0%
Dash Punctuation 146
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 247
18.8%
2 242
18.4%
3 229
17.5%
9 109
8.3%
1 100
7.6%
7 98
 
7.5%
6 86
 
6.6%
5 81
 
6.2%
4 62
 
4.7%
8 58
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 247
16.9%
2 242
16.6%
3 229
15.7%
- 146
10.0%
9 109
7.5%
1 100
6.9%
7 98
 
6.7%
6 86
 
5.9%
5 81
 
5.6%
4 62
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 247
16.9%
2 242
16.6%
3 229
15.7%
- 146
10.0%
9 109
7.5%
1 100
6.9%
7 98
 
6.7%
6 86
 
5.9%
5 81
 
5.6%
4 62
 
4.3%

우편번호
Real number (ℝ)

Distinct77
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12838.61
Minimum120
Maximum120861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-05-18T09:32:03.965055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120
5-th percentile3611
Q13656
median3696
Q33745
95-th percentile120650
Maximum120861
Range120741
Interquartile range (IQR)89

Descriptive statistics

Standard deviation31474.999
Coefficient of variation (CV)2.4515893
Kurtosis8.2240542
Mean12838.61
Median Absolute Deviation (MAD)46
Skewness3.178291
Sum1810244
Variance9.9067555 × 108
MonotonicityNot monotonic
2024-05-18T09:32:04.572982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120650 8
 
5.7%
3745 7
 
5.0%
3746 6
 
4.3%
3784 6
 
4.3%
3664 5
 
3.5%
3741 5
 
3.5%
3668 4
 
2.8%
3702 4
 
2.8%
3650 3
 
2.1%
3658 3
 
2.1%
Other values (67) 90
63.8%
ValueCountFrequency (%)
120 1
 
0.7%
3601 1
 
0.7%
3602 3
2.1%
3608 2
1.4%
3611 1
 
0.7%
3615 1
 
0.7%
3618 2
1.4%
3619 3
2.1%
3624 1
 
0.7%
3627 1
 
0.7%
ValueCountFrequency (%)
120861 1
 
0.7%
120818 1
 
0.7%
120650 8
5.7%
120080 1
 
0.7%
10833 1
 
0.7%
3784 6
4.3%
3783 1
 
0.7%
3769 1
 
0.7%
3762 1
 
0.7%
3760 1
 
0.7%

Interactions

2024-05-18T09:31:43.418570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:40.891826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:42.148808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:43.712801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:41.192108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:42.686309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:44.098069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:41.727343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:31:43.071233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:32:04.899143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0000.9750.9420.000
시설종류상세명(시설종류)1.0001.0000.5990.8090.000
정원(수용인원)0.9750.5991.0000.7200.000
현인원0.9420.8090.7201.0000.000
우편번호0.0000.0000.0000.0001.000
2024-05-18T09:32:05.297496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)
시설종류명(시설유형)1.0000.945
시설종류상세명(시설종류)0.9451.000
2024-05-18T09:32:05.620264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.8320.0800.7100.357
현인원0.8321.0000.0840.6080.436
우편번호0.0800.0841.0000.0000.000
시설종류명(시설유형)0.7100.6080.0001.0000.945
시설종류상세명(시설종류)0.3570.4360.0000.9451.000

Missing values

2024-05-18T09:31:44.589943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:31:45.284656image/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.
2024-05-18T09:31:45.842658image/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
0효림재가노인지원센터A0738(노인) 재가노인복지시설재가노인복지시설자치구김동숙1141000000서대문구서울특별시 서대문구 경기대로9길 62-01-38<NA>67102-313-51243746
1중앙소규모요양시설A1302(노인) 노인요양시설노인의료복지시설자치구박형준1141000000서대문구서울특별시 서대문구 서소문로 43-49 (합동)242402-362-92623741
2북가좌노인복지관A1599(노인) 노인복지관(소규모)노인여가복지시설자치구이은희1141000000서대문구서울특별시 서대문구 증가로20길 43북가좌2동노인복지센터11011002-376-50403668
3효림데이케어센터A1721(노인) 재가노인복지시설재가노인복지시설자치구김동금1141000000서대문구서울특별시 서대문구 경기대로9길 624층171702-313-51243746
4효림노인요양센터A1723(노인) 노인요양시설노인의료복지시설자치구김동금1141000000서대문구서울특별시 서대문구 경기대로9길 62 (충정로3가)212102-313-51243746
5연희노인복지관A1756(노인) 노인복지관(소규모)노인여가복지시설자치구조성준1141000000서대문구서울특별시 서대문구 홍제천로2길 111연희노인여가복지시설19016002-3143-77783700
6홍은데이케어센터A2069(노인) 재가노인복지시설재가노인복지시설자치구백영수1141000000서대문구서울특별시 서대문구 홍은중앙로9길 21홍은중앙로9길 21212102-391-13553602
7서대문노인종합복지관A2955(노인) 노인복지관노인여가복지시설자치구이대원1141000000서대문구서울특별시 서대문구 독립문로8길 57(천연동)1000130002-363-99883745
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