Overview

Dataset statistics

Number of variables13
Number of observations115
Missing cells90
Missing cells (%)6.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.3 KiB
Average record size in memory109.1 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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-20398/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 정원(수용인원) and 3 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
우편번호 is highly overall correlated with 시설종류상세명(시설종류)High correlation
시설주소 has 4 (3.5%) missing valuesMissing
정원(수용인원) has 35 (30.4%) missing valuesMissing
현인원 has 47 (40.9%) missing valuesMissing
전화번호 has 4 (3.5%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 9 (7.8%) zerosZeros

Reproduction

Analysis started2024-05-10 22:28:05.330963
Analysis finished2024-05-10 22:28:10.314409
Duration4.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct110
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-10T22:28:10.642414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length9.4173913
Min length3

Characters and Unicode

Total characters1083
Distinct characters197
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)91.3%

Sample

1st row구립서초노인요양센터
2nd row구립서초노인요양센터
3rd row서울특별시남부노인보호전문기관
4th row서초구립양재노인종합복지관
5th row노인주간보호센터은빛마을
ValueCountFrequency (%)
서초구립 5
 
3.4%
케어링 4
 
2.8%
구립서초노인요양센터 2
 
1.4%
초등키움센터 2
 
1.4%
재가복지센터 2
 
1.4%
사랑의복지관 2
 
1.4%
지역아동센터 2
 
1.4%
구립 2
 
1.4%
서초 2
 
1.4%
하나복지지역아동센터 2
 
1.4%
Other values (116) 120
82.8%
2024-05-10T22:28:11.565806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 72
 
6.6%
센 69
 
6.4%
서 46
 
4.2%
초 46
 
4.2%
지 41
 
3.8%
30
 
2.8%
복 26
 
2.4%
구 24
 
2.2%
인 20
 
1.8%
동 20
 
1.8%
Other values (187) 689
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1028
94.9%
Space Separator 30
 
2.8%
Decimal Number 11
 
1.0%
Uppercase Letter 4
 
0.4%
Close Punctuation 3
 
0.3%
Math Symbol 3
 
0.3%
Open Punctuation 3
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 72
 
7.0%
센 69
 
6.7%
서 46
 
4.5%
초 46
 
4.5%
지 41
 
4.0%
복 26
 
2.5%
구 24
 
2.3%
인 20
 
1.9%
동 20
 
1.9%
립 19
 
1.8%
Other values (173) 645
62.7%
Decimal Number
ValueCountFrequency (%)
9 2
18.2%
5 2
18.2%
1 2
18.2%
2 2
18.2%
3 2
18.2%
0 1
9.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
B 1
25.0%
K 1
25.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1028
94.9%
Common 50
 
4.6%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 72
 
7.0%
센 69
 
6.7%
서 46
 
4.5%
초 46
 
4.5%
지 41
 
4.0%
복 26
 
2.5%
구 24
 
2.3%
인 20
 
1.9%
동 20
 
1.9%
립 19
 
1.8%
Other values (173) 645
62.7%
Common
ValueCountFrequency (%)
30
60.0%
) 3
 
6.0%
+ 3
 
6.0%
( 3
 
6.0%
9 2
 
4.0%
5 2
 
4.0%
1 2
 
4.0%
2 2
 
4.0%
3 2
 
4.0%
0 1
 
2.0%
Latin
ValueCountFrequency (%)
A 2
40.0%
B 1
20.0%
K 1
20.0%
e 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1028
94.9%
ASCII 55
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 72
 
7.0%
센 69
 
6.7%
서 46
 
4.5%
초 46
 
4.5%
지 41
 
4.0%
복 26
 
2.5%
구 24
 
2.3%
인 20
 
1.9%
동 20
 
1.9%
립 19
 
1.8%
Other values (173) 645
62.7%
ASCII
ValueCountFrequency (%)
30
54.5%
) 3
 
5.5%
+ 3
 
5.5%
( 3
 
5.5%
9 2
 
3.6%
A 2
 
3.6%
5 2
 
3.6%
1 2
 
3.6%
2 2
 
3.6%
3 2
 
3.6%
Other values (4) 4
 
7.3%

시설코드
Text

UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-10T22:28:12.208651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0521739
Min length5

Characters and Unicode

Total characters581
Distinct characters20
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

Unique115 ?
Unique (%)100.0%

Sample

1st rowA0368
2nd rowA0386
3rd rowA0533
4th rowA0724
5th rowA2075
ValueCountFrequency (%)
a0368 1
 
0.9%
f0568 1
 
0.9%
k0554 1
 
0.9%
k0479 1
 
0.9%
k0478 1
 
0.9%
k0211 1
 
0.9%
k0162 1
 
0.9%
k0067 1
 
0.9%
j9447 1
 
0.9%
j8681 1
 
0.9%
Other values (105) 105
91.3%
2024-05-10T22:28:13.274128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80
13.8%
6 52
9.0%
3 49
8.4%
1 47
8.1%
5 46
 
7.9%
7 46
 
7.9%
4 40
 
6.9%
8 37
 
6.4%
9 35
 
6.0%
2 34
 
5.9%
Other values (10) 115
19.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 466
80.2%
Uppercase Letter 115
 
19.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80
17.2%
6 52
11.2%
3 49
10.5%
1 47
10.1%
5 46
9.9%
7 46
9.9%
4 40
8.6%
8 37
7.9%
9 35
7.5%
2 34
7.3%
Uppercase Letter
ValueCountFrequency (%)
C 28
24.3%
G 16
13.9%
K 15
13.0%
A 15
13.0%
F 10
 
8.7%
P 10
 
8.7%
Z 10
 
8.7%
B 7
 
6.1%
J 3
 
2.6%
W 1
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 466
80.2%
Latin 115
 
19.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80
17.2%
6 52
11.2%
3 49
10.5%
1 47
10.1%
5 46
9.9%
7 46
9.9%
4 40
8.6%
8 37
7.9%
9 35
7.5%
2 34
7.3%
Latin
ValueCountFrequency (%)
C 28
24.3%
G 16
13.9%
K 15
13.0%
A 15
13.0%
F 10
 
8.7%
P 10
 
8.7%
Z 10
 
8.7%
B 7
 
6.1%
J 3
 
2.6%
W 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 581
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80
13.8%
6 52
9.0%
3 49
8.4%
1 47
8.1%
5 46
 
7.9%
7 46
 
7.9%
4 40
 
6.9%
8 37
 
6.4%
9 35
 
6.0%
2 34
 
5.9%
Other values (10) 115
19.8%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
(노인) 재가노인복지시설
31 
(아동) 지역아동센터
12 
(장애인) 장애인주간보호시설
8 
(장애인) 장애인공동생활가정
7 
(노인) 노인요양시설
6 
Other values (25)
51 

Length

Max length28
Median length20
Mean length12.991304
Min length9

Unique

Unique12 ?
Unique (%)10.4%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 31
27.0%
(아동) 지역아동센터 12
 
10.4%
(장애인) 장애인주간보호시설 8
 
7.0%
(장애인) 장애인공동생활가정 7
 
6.1%
(노인) 노인요양시설 6
 
5.2%
(아동) 다함께돌봄센터 6
 
5.2%
(아동) 아동양육시설 4
 
3.5%
(일반) 사회복지관 4
 
3.5%
(장애인) 장애인복지관 3
 
2.6%
(정신보건) 재활훈련시설-주간재활시설 3
 
2.6%
Other values (20) 31
27.0%

Length

2024-05-10T22:28:13.640602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 47
20.4%
재가노인복지시설 31
13.5%
장애인 30
13.0%
아동 23
10.0%
지역아동센터 12
 
5.2%
장애인주간보호시설 8
 
3.5%
장애인공동생활가정 7
 
3.0%
노인요양시설 6
 
2.6%
다함께돌봄센터 6
 
2.6%
정신보건 5
 
2.2%
Other values (30) 55
23.9%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
재가노인복지시설
31 
아동복지시설
23 
장애인지역사회재활시설
13 
장애인거주시설
11 
노인의료복지시설
7 
Other values (12)
30 

Length

Max length11
Median length9
Mean length7.6434783
Min length4

Unique

Unique6 ?
Unique (%)5.2%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 31
27.0%
아동복지시설 23
20.0%
장애인지역사회재활시설 13
11.3%
장애인거주시설 11
 
9.6%
노인의료복지시설 7
 
6.1%
노인여가복지시설 6
 
5.2%
장애인직업재활시설 6
 
5.2%
정신재활시설 4
 
3.5%
일반사회복지시설 4
 
3.5%
보육시설 2
 
1.7%
Other values (7) 8
 
7.0%

Length

2024-05-10T22:28:14.070002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재가노인복지시설 31
27.0%
아동복지시설 23
20.0%
장애인지역사회재활시설 13
11.3%
장애인거주시설 11
 
9.6%
노인의료복지시설 7
 
6.1%
노인여가복지시설 6
 
5.2%
장애인직업재활시설 6
 
5.2%
일반사회복지시설 4
 
3.5%
정신재활시설 4
 
3.5%
보육시설 2
 
1.7%
Other values (7) 8
 
7.0%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
자치구
115 

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 115
100.0%

Length

2024-05-10T22:28:14.539091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:28:14.775232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 115
100.0%

시설장명
Text

Distinct99
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-10T22:28:15.394620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters345
Distinct characters99
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

Unique87 ?
Unique (%)75.7%

Sample

1st row나종선
2nd row이민정
3rd row나경희
4th row전경아
5th row이은주
ValueCountFrequency (%)
김상호 4
 
3.5%
남동우 3
 
2.6%
위수경 3
 
2.6%
심종온 2
 
1.7%
전경아 2
 
1.7%
오명숙 2
 
1.7%
이은주 2
 
1.7%
이정욱 2
 
1.7%
강명희 2
 
1.7%
최은경 2
 
1.7%
Other values (88) 91
79.1%
2024-05-10T22:28:16.478612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 25
 
7.2%
정 17
 
4.9%
김 15
 
4.3%
경 14
 
4.1%
박 14
 
4.1%
영 12
 
3.5%
숙 11
 
3.2%
희 9
 
2.6%
상 8
 
2.3%
한 8
 
2.3%
Other values (89) 212
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 344
99.7%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 25
 
7.3%
정 17
 
4.9%
김 15
 
4.4%
경 14
 
4.1%
박 14
 
4.1%
영 12
 
3.5%
숙 11
 
3.2%
희 9
 
2.6%
상 8
 
2.3%
한 8
 
2.3%
Other values (88) 211
61.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 344
99.7%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 25
 
7.3%
정 17
 
4.9%
김 15
 
4.4%
경 14
 
4.1%
박 14
 
4.1%
영 12
 
3.5%
숙 11
 
3.2%
희 9
 
2.6%
상 8
 
2.3%
한 8
 
2.3%
Other values (88) 211
61.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 344
99.7%
ASCII 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 25
 
7.3%
정 17
 
4.9%
김 15
 
4.4%
경 14
 
4.1%
박 14
 
4.1%
영 12
 
3.5%
숙 11
 
3.2%
희 9
 
2.6%
상 8
 
2.3%
한 8
 
2.3%
Other values (88) 211
61.3%
ASCII
ValueCountFrequency (%)
1
100.0%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1165000000
115 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1165000000
2nd row1165000000
3rd row1165000000
4th row1165000000
5th row1165000000

Common Values

ValueCountFrequency (%)
1165000000 115
100.0%

Length

2024-05-10T22:28:16.956657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:28:17.275136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1165000000 115
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
서초구
115 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 115
100.0%

Length

2024-05-10T22:28:17.577712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:28:17.948429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서초구 115
100.0%

시설주소
Text

MISSING 

Distinct109
Distinct (%)98.2%
Missing4
Missing (%)3.5%
Memory size1.0 KiB
2024-05-10T22:28:18.672142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length30.243243
Min length17

Characters and Unicode

Total characters3357
Distinct characters157
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)96.4%

Sample

1st row서울특별시 서초구 남부순환로340길 21 (서초동 380-4)
2nd row서울특별시 서초구 남부순환로340길21
3rd row서울특별시 서초구 남부순환로 2124까리따스종합복지관 (방배동)(방배동)
4th row서울특별시 서초구 강남대로30길 73-7양재노인종합복지관 (양재동)
5th row서울특별시 서초구 신반포로 33길 22(잠원동)반포종합사회복지관 2층
ValueCountFrequency (%)
서울특별시 110
 
18.3%
서초구 110
 
18.3%
방배동 21
 
3.5%
서초동 15
 
2.5%
2층 10
 
1.7%
반포동 9
 
1.5%
양재동 8
 
1.3%
우면동 7
 
1.2%
헌릉로468길 6
 
1.0%
15 6
 
1.0%
Other values (230) 299
49.8%
2024-05-10T22:28:19.761913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
502
 
15.0%
서 250
 
7.4%
초 139
 
4.1%
1 121
 
3.6%
구 113
 
3.4%
시 111
 
3.3%
특 110
 
3.3%
울 110
 
3.3%
동 110
 
3.3%
별 110
 
3.3%
Other values (147) 1681
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1945
57.9%
Decimal Number 620
 
18.5%
Space Separator 502
 
15.0%
Close Punctuation 94
 
2.8%
Open Punctuation 94
 
2.8%
Other Punctuation 54
 
1.6%
Dash Punctuation 41
 
1.2%
Uppercase Letter 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 250
 
12.9%
초 139
 
7.1%
구 113
 
5.8%
시 111
 
5.7%
특 110
 
5.7%
울 110
 
5.7%
동 110
 
5.7%
별 110
 
5.7%
로 101
 
5.2%
길 82
 
4.2%
Other values (125) 709
36.5%
Decimal Number
ValueCountFrequency (%)
1 121
19.5%
2 104
16.8%
3 77
12.4%
4 68
11.0%
0 58
9.4%
5 57
9.2%
6 43
 
6.9%
8 37
 
6.0%
9 28
 
4.5%
7 27
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
28.6%
B 1
14.3%
I 1
14.3%
P 1
14.3%
R 1
14.3%
K 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 53
98.1%
. 1
 
1.9%
Space Separator
ValueCountFrequency (%)
502
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1945
57.9%
Common 1405
41.9%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 250
 
12.9%
초 139
 
7.1%
구 113
 
5.8%
시 111
 
5.7%
특 110
 
5.7%
울 110
 
5.7%
동 110
 
5.7%
별 110
 
5.7%
로 101
 
5.2%
길 82
 
4.2%
Other values (125) 709
36.5%
Common
ValueCountFrequency (%)
502
35.7%
1 121
 
8.6%
2 104
 
7.4%
) 94
 
6.7%
( 94
 
6.7%
3 77
 
5.5%
4 68
 
4.8%
0 58
 
4.1%
5 57
 
4.1%
, 53
 
3.8%
Other values (6) 177
 
12.6%
Latin
ValueCountFrequency (%)
A 2
28.6%
B 1
14.3%
I 1
14.3%
P 1
14.3%
R 1
14.3%
K 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1945
57.9%
ASCII 1412
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
502
35.6%
1 121
 
8.6%
2 104
 
7.4%
) 94
 
6.7%
( 94
 
6.7%
3 77
 
5.5%
4 68
 
4.8%
0 58
 
4.1%
5 57
 
4.0%
, 53
 
3.8%
Other values (12) 184
 
13.0%
Hangul
ValueCountFrequency (%)
서 250
 
12.9%
초 139
 
7.1%
구 113
 
5.8%
시 111
 
5.7%
특 110
 
5.7%
울 110
 
5.7%
동 110
 
5.7%
별 110
 
5.7%
로 101
 
5.2%
길 82
 
4.2%
Other values (125) 709
36.5%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct38
Distinct (%)47.5%
Missing35
Missing (%)30.4%
Infinite0
Infinite (%)0.0%
Mean51.5375
Minimum0
Maximum1000
Zeros9
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-10T22:28:20.159103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.75
median20.5
Q336
95-th percentile200
Maximum1000
Range1000
Interquartile range (IQR)26.25

Descriptive statistics

Standard deviation128.0944
Coefficient of variation (CV)2.4854601
Kurtosis39.651368
Mean51.5375
Median Absolute Deviation (MAD)14
Skewness5.8546548
Sum4123
Variance16408.176
MonotonicityNot monotonic
2024-05-10T22:28:20.506611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 9
 
7.8%
4 7
 
6.1%
30 5
 
4.3%
19 5
 
4.3%
10 5
 
4.3%
12 4
 
3.5%
24 4
 
3.5%
17 3
 
2.6%
25 3
 
2.6%
35 3
 
2.6%
Other values (28) 32
27.8%
(Missing) 35
30.4%
ValueCountFrequency (%)
0 9
7.8%
4 7
6.1%
5 1
 
0.9%
7 2
 
1.7%
9 1
 
0.9%
10 5
4.3%
12 4
3.5%
13 1
 
0.9%
17 3
 
2.6%
19 5
4.3%
ValueCountFrequency (%)
1000 1
0.9%
427 1
0.9%
388 1
0.9%
200 2
1.7%
126 1
0.9%
107 1
0.9%
85 1
0.9%
80 2
1.7%
71 1
0.9%
60 1
0.9%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)61.8%
Missing47
Missing (%)40.9%
Infinite0
Infinite (%)0.0%
Mean202.22059
Minimum0
Maximum5647
Zeros1
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-10T22:28:20.805724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q110
median24
Q353.75
95-th percentile897.5
Maximum5647
Range5647
Interquartile range (IQR)43.75

Descriptive statistics

Standard deviation732.17967
Coefficient of variation (CV)3.620698
Kurtosis47.166349
Mean202.22059
Median Absolute Deviation (MAD)15
Skewness6.5144795
Sum13751
Variance536087.07
MonotonicityNot monotonic
2024-05-10T22:28:21.196586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
4 7
 
6.1%
10 7
 
6.1%
24 4
 
3.5%
17 4
 
3.5%
31 2
 
1.7%
42 2
 
1.7%
30 2
 
1.7%
20 2
 
1.7%
12 2
 
1.7%
23 2
 
1.7%
Other values (32) 34
29.6%
(Missing) 47
40.9%
ValueCountFrequency (%)
0 1
 
0.9%
3 1
 
0.9%
4 7
6.1%
5 1
 
0.9%
9 2
 
1.7%
10 7
6.1%
11 1
 
0.9%
12 2
 
1.7%
17 4
3.5%
18 1
 
0.9%
ValueCountFrequency (%)
5647 1
0.9%
1711 1
0.9%
1220 1
0.9%
950 1
0.9%
800 1
0.9%
600 1
0.9%
400 1
0.9%
376 1
0.9%
237 1
0.9%
200 1
0.9%

전화번호
Text

MISSING 

Distinct107
Distinct (%)96.4%
Missing4
Missing (%)3.5%
Memory size1.0 KiB
2024-05-10T22:28:21.794534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.558559
Min length8

Characters and Unicode

Total characters1172
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

Unique103 ?
Unique (%)92.8%

Sample

1st row02-597-5008
2nd row02-597-5008
3rd row02-3472-1389
4th row02-578-1515
5th row02-3477-1011
ValueCountFrequency (%)
02-582-6004 2
 
1.8%
02-2055-0909 2
 
1.8%
02-597-5008 2
 
1.8%
025352940 2
 
1.8%
01062249879 1
 
0.9%
025777943 1
 
0.9%
025717942 1
 
0.9%
0234781027 1
 
0.9%
025739811 1
 
0.9%
02537-9871 1
 
0.9%
Other values (97) 97
87.4%
2024-05-10T22:28:22.846568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 195
16.6%
0 190
16.2%
5 135
11.5%
- 126
10.8%
7 110
9.4%
9 82
7.0%
3 81
6.9%
4 71
 
6.1%
8 70
 
6.0%
1 68
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1046
89.2%
Dash Punctuation 126
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 195
18.6%
0 190
18.2%
5 135
12.9%
7 110
10.5%
9 82
7.8%
3 81
7.7%
4 71
 
6.8%
8 70
 
6.7%
1 68
 
6.5%
6 44
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 195
16.6%
0 190
16.2%
5 135
11.5%
- 126
10.8%
7 110
9.4%
9 82
7.0%
3 81
6.9%
4 71
 
6.1%
8 70
 
6.0%
1 68
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 195
16.6%
0 190
16.2%
5 135
11.5%
- 126
10.8%
7 110
9.4%
9 82
7.0%
3 81
6.9%
4 71
 
6.1%
8 70
 
6.0%
1 68
 
5.8%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17944.139
Minimum6504
Maximum137900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-10T22:28:23.266563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6504
5-th percentile6529
Q16632.5
median6710
Q36784
95-th percentile137307.2
Maximum137900
Range131396
Interquartile range (IQR)151.5

Descriptive statistics

Standard deviation35230.916
Coefficient of variation (CV)1.9633662
Kurtosis7.3234492
Mean17944.139
Median Absolute Deviation (MAD)77
Skewness2.9973337
Sum2063576
Variance1.2412174 × 109
MonotonicityNot monotonic
2024-05-10T22:28:23.736390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6677 8
 
7.0%
6756 5
 
4.3%
6760 5
 
4.3%
6534 5
 
4.3%
6796 5
 
4.3%
6793 5
 
4.3%
6522 4
 
3.5%
6570 3
 
2.6%
6572 3
 
2.6%
6784 3
 
2.6%
Other values (56) 69
60.0%
ValueCountFrequency (%)
6504 1
 
0.9%
6509 1
 
0.9%
6522 4
3.5%
6532 1
 
0.9%
6534 5
4.3%
6535 1
 
0.9%
6544 1
 
0.9%
6558 1
 
0.9%
6568 1
 
0.9%
6569 1
 
0.9%
ValueCountFrequency (%)
137900 1
0.9%
137892 1
0.9%
137856 1
0.9%
137846 1
0.9%
137604 2
1.7%
137180 1
0.9%
137070 1
0.9%
99999 2
1.7%
39848 1
0.9%
24241 1
0.9%

Interactions

2024-05-10T22:28:08.023176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:06.595512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:07.349741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:08.375759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:06.839992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:07.600423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:08.635639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:07.083584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:28:07.788295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T22:28:24.039003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)시설장명정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0000.9870.9760.9180.859
시설종류상세명(시설종류)1.0001.0000.9910.9070.7960.779
시설장명0.9870.9911.0000.0000.9730.972
정원(수용인원)0.9760.9070.0001.0000.8800.000
현인원0.9180.7960.9730.8801.0000.000
우편번호0.8590.7790.9720.0000.0001.000
2024-05-10T22:28:24.306074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)
시설종류명(시설유형)1.0000.931
시설종류상세명(시설종류)0.9311.000
2024-05-10T22:28:24.657044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.580-0.1020.7950.711
현인원0.5801.000-0.1210.6650.567
우편번호-0.102-0.1211.0000.4960.515
시설종류명(시설유형)0.7950.6650.4961.0000.931
시설종류상세명(시설종류)0.7110.5670.5150.9311.000

Missing values

2024-05-10T22:28:09.236948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T22:28:09.761571image/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.
2024-05-10T22:28:10.136842image/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
0구립서초노인요양센터A0368(노인) 노인요양시설노인의료복지시설자치구나종선1165000000서초구서울특별시 서초구 남부순환로340길 21 (서초동 380-4)20020002-597-50086756
1구립서초노인요양센터A0386(노인) 노인요양시설노인의료복지시설자치구이민정1165000000서초구서울특별시 서초구 남부순환로340길2120018402-597-50086756
2서울특별시남부노인보호전문기관A0533(노인) 노인보호전문기관노인보호전문기관자치구나경희1165000000서초구서울특별시 서초구 남부순환로 2124까리따스종합복지관 (방배동)(방배동)13<NA>02-3472-13896760
3서초구립양재노인종합복지관A0724(노인) 노인복지관노인여가복지시설자치구전경아1165000000서초구서울특별시 서초구 강남대로30길 73-7양재노인종합복지관 (양재동)<NA>122002-578-15156741
4노인주간보호센터은빛마을A2075(노인) 재가노인복지시설재가노인복지시설자치구이은주1165000000서초구서울특별시 서초구 신반포로 33길 22(잠원동)반포종합사회복지관 2층212102-3477-10116522
5서초성심노인복지센터(주야간보호)A2360(노인) 재가노인복지시설재가노인복지시설자치구오명숙1165000000서초구서울특별시 서초구 반포대로22길 61(서초동 1558-15)242402-582-60046646
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