Overview

Dataset statistics

Number of variables13
Number of observations158
Missing cells86
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.8 KiB
Average record size in memory108.8 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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-20395/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 3 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
우편번호 is highly overall correlated with 시설종류명(시설유형)High correlation
정원(수용인원) has 31 (19.6%) missing valuesMissing
현인원 has 55 (34.8%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 16 (10.1%) zerosZeros
현인원 has 2 (1.3%) zerosZeros

Reproduction

Analysis started2024-05-04 00:19:40.776018
Analysis finished2024-05-04 00:19:45.380067
Duration4.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct153
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-04T00:19:45.754603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length11.886076
Min length3

Characters and Unicode

Total characters1878
Distinct characters255
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

Unique148 ?
Unique (%)93.7%

Sample

1st row서울특별시립 남부노인전문요양원
2nd row중앙노인보호전문기관
3rd row서울성모원
4th row구립영등포노인케어센터
5th row구립영등포노인종합복지관
ValueCountFrequency (%)
우리동네키움센터 13
 
5.9%
아이랜드 6
 
2.7%
병설 5
 
2.3%
어버이사랑노인의료복지센터2 3
 
1.4%
영등포구 3
 
1.4%
데이케어센터 3
 
1.4%
노인요양공동생활가정 3
 
1.4%
디모데지역아동센터 2
 
0.9%
어버이사랑노인의료복지센터3 2
 
0.9%
어버이사랑노인의료실버타운 2
 
0.9%
Other values (172) 178
80.9%
2024-05-04T00:19:46.654594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 113
 
6.0%
센 111
 
5.9%
지 63
 
3.4%
62
 
3.3%
동 60
 
3.2%
영 46
 
2.4%
포 44
 
2.3%
등 44
 
2.3%
인 42
 
2.2%
이 40
 
2.1%
Other values (245) 1253
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1721
91.6%
Space Separator 62
 
3.3%
Decimal Number 50
 
2.7%
Close Punctuation 16
 
0.9%
Open Punctuation 16
 
0.9%
Lowercase Letter 8
 
0.4%
Uppercase Letter 4
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 113
 
6.6%
센 111
 
6.4%
지 63
 
3.7%
동 60
 
3.5%
영 46
 
2.7%
포 44
 
2.6%
등 44
 
2.6%
인 42
 
2.4%
이 40
 
2.3%
아 36
 
2.1%
Other values (222) 1122
65.2%
Decimal Number
ValueCountFrequency (%)
1 17
34.0%
2 13
26.0%
3 7
14.0%
5 4
 
8.0%
6 2
 
4.0%
7 2
 
4.0%
0 2
 
4.0%
4 1
 
2.0%
8 1
 
2.0%
9 1
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
37.5%
n 2
25.0%
r 1
 
12.5%
t 1
 
12.5%
i 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
C 1
25.0%
V 1
25.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1721
91.6%
Common 145
 
7.7%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 113
 
6.6%
센 111
 
6.4%
지 63
 
3.7%
동 60
 
3.5%
영 46
 
2.7%
포 44
 
2.6%
등 44
 
2.6%
인 42
 
2.4%
이 40
 
2.3%
아 36
 
2.1%
Other values (222) 1122
65.2%
Common
ValueCountFrequency (%)
62
42.8%
1 17
 
11.7%
) 16
 
11.0%
( 16
 
11.0%
2 13
 
9.0%
3 7
 
4.8%
5 4
 
2.8%
6 2
 
1.4%
7 2
 
1.4%
0 2
 
1.4%
Other values (4) 4
 
2.8%
Latin
ValueCountFrequency (%)
e 3
25.0%
n 2
16.7%
B 1
 
8.3%
A 1
 
8.3%
r 1
 
8.3%
t 1
 
8.3%
C 1
 
8.3%
i 1
 
8.3%
V 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1721
91.6%
ASCII 157
 
8.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 113
 
6.6%
센 111
 
6.4%
지 63
 
3.7%
동 60
 
3.5%
영 46
 
2.7%
포 44
 
2.6%
등 44
 
2.6%
인 42
 
2.4%
이 40
 
2.3%
아 36
 
2.1%
Other values (222) 1122
65.2%
ASCII
ValueCountFrequency (%)
62
39.5%
1 17
 
10.8%
) 16
 
10.2%
( 16
 
10.2%
2 13
 
8.3%
3 7
 
4.5%
5 4
 
2.5%
e 3
 
1.9%
6 2
 
1.3%
7 2
 
1.3%
Other values (13) 15
 
9.6%

시설코드
Text

UNIQUE 

Distinct158
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-04T00:19:47.321898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0316456
Min length5

Characters and Unicode

Total characters795
Distinct characters24
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

Unique158 ?
Unique (%)100.0%

Sample

1st rowA0016
2nd rowA1729
3rd rowA2156
4th rowA3121
5th rowA4035
ValueCountFrequency (%)
a0016 1
 
0.6%
j1290 1
 
0.6%
k0403 1
 
0.6%
g7467 1
 
0.6%
g7477 1
 
0.6%
g7485 1
 
0.6%
g8073 1
 
0.6%
i0413 1
 
0.6%
i0436 1
 
0.6%
g6142 1
 
0.6%
Other values (148) 148
93.7%
2024-05-04T00:19:48.476411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 101
12.7%
1 91
11.4%
4 67
8.4%
2 66
8.3%
3 64
8.1%
6 54
 
6.8%
7 54
 
6.8%
5 53
 
6.7%
9 44
 
5.5%
8 43
 
5.4%
Other values (14) 158
19.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 637
80.1%
Uppercase Letter 158
 
19.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 30
19.0%
B 22
13.9%
K 21
13.3%
A 19
12.0%
C 18
11.4%
P 16
10.1%
F 10
 
6.3%
Z 7
 
4.4%
E 5
 
3.2%
W 3
 
1.9%
Other values (4) 7
 
4.4%
Decimal Number
ValueCountFrequency (%)
0 101
15.9%
1 91
14.3%
4 67
10.5%
2 66
10.4%
3 64
10.0%
6 54
8.5%
7 54
8.5%
5 53
8.3%
9 44
6.9%
8 43
6.8%

Most occurring scripts

ValueCountFrequency (%)
Common 637
80.1%
Latin 158
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 30
19.0%
B 22
13.9%
K 21
13.3%
A 19
12.0%
C 18
11.4%
P 16
10.1%
F 10
 
6.3%
Z 7
 
4.4%
E 5
 
3.2%
W 3
 
1.9%
Other values (4) 7
 
4.4%
Common
ValueCountFrequency (%)
0 101
15.9%
1 91
14.3%
4 67
10.5%
2 66
10.4%
3 64
10.0%
6 54
8.5%
7 54
8.5%
5 53
8.3%
9 44
6.9%
8 43
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 795
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 101
12.7%
1 91
11.4%
4 67
8.4%
2 66
8.3%
3 64
8.1%
6 54
 
6.8%
7 54
 
6.8%
5 53
 
6.7%
9 44
 
5.5%
8 43
 
5.4%
Other values (14) 158
19.9%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
(노인) 재가노인복지시설
45 
(아동) 지역아동센터
24 
(노인) 노인요양공동생활가정
19 
(아동) 다함께돌봄센터
10 
(장애인) 장애인주간보호시설
 
5
Other values (36)
55 

Length

Max length27
Median length21
Mean length13.240506
Min length9

Unique

Unique23 ?
Unique (%)14.6%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 45
28.5%
(아동) 지역아동센터 24
15.2%
(노인) 노인요양공동생활가정 19
12.0%
(아동) 다함께돌봄센터 10
 
6.3%
(장애인) 장애인주간보호시설 5
 
3.2%
(장애인) 장애인공동생활가정 4
 
2.5%
(노인) 노인교실 3
 
1.9%
(아동) 아동보호치료시설 3
 
1.9%
(장애인) 장애인보호작업장 3
 
1.9%
(장애인) (기타)장애인복지시설 3
 
1.9%
Other values (31) 39
24.7%

Length

2024-05-04T00:19:48.861724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 74
23.4%
재가노인복지시설 45
14.2%
아동 43
13.6%
지역아동센터 24
 
7.6%
장애인 22
 
7.0%
노인요양공동생활가정 19
 
6.0%
다함께돌봄센터 10
 
3.2%
장애인주간보호시설 5
 
1.6%
정신보건 5
 
1.6%
노숙인등 5
 
1.6%
Other values (43) 64
20.3%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
재가노인복지시설
45 
아동복지시설
43 
노인의료복지시설
21 
장애인지역사회재활시설
7 
장애인거주시설
7 
Other values (18)
35 

Length

Max length11
Median length10
Mean length7.335443
Min length4

Unique

Unique11 ?
Unique (%)7.0%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 45
28.5%
아동복지시설 43
27.2%
노인의료복지시설 21
13.3%
장애인지역사회재활시설 7
 
4.4%
장애인거주시설 7
 
4.4%
장애인기타 5
 
3.2%
정신재활시설 4
 
2.5%
노숙인등이용시설 4
 
2.5%
노인여가복지시설 4
 
2.5%
장애인직업재활시설 3
 
1.9%
Other values (13) 15
 
9.5%

Length

2024-05-04T00:19:49.113589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재가노인복지시설 45
28.5%
아동복지시설 43
27.2%
노인의료복지시설 21
13.3%
장애인지역사회재활시설 7
 
4.4%
장애인거주시설 7
 
4.4%
장애인기타 5
 
3.2%
정신재활시설 4
 
2.5%
노숙인등이용시설 4
 
2.5%
노인여가복지시설 4
 
2.5%
장애인직업재활시설 3
 
1.9%
Other values (13) 15
 
9.5%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
자치구
158 

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 158
100.0%

Length

2024-05-04T00:19:49.339842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:19:49.620933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 158
100.0%

시설장명
Text

Distinct139
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-04T00:19:50.081053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters474
Distinct characters114
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

Unique122 ?
Unique (%)77.2%

Sample

1st row한철수
2nd row최영숙
3rd row오양식
4th row이지은
5th row박영숙
ValueCountFrequency (%)
김현주 3
 
1.9%
나택규 3
 
1.9%
유민혁 2
 
1.3%
이문노 2
 
1.3%
이의인 2
 
1.3%
이재훈 2
 
1.3%
박민자 2
 
1.3%
신승희 2
 
1.3%
조은선 2
 
1.3%
정혜선 2
 
1.3%
Other values (129) 136
86.1%
2024-05-04T00:19:50.903627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 33
 
7.0%
이 30
 
6.3%
정 18
 
3.8%
영 18
 
3.8%
희 15
 
3.2%
미 14
 
3.0%
박 14
 
3.0%
숙 13
 
2.7%
경 11
 
2.3%
선 11
 
2.3%
Other values (104) 297
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 474
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 33
 
7.0%
이 30
 
6.3%
정 18
 
3.8%
영 18
 
3.8%
희 15
 
3.2%
미 14
 
3.0%
박 14
 
3.0%
숙 13
 
2.7%
경 11
 
2.3%
선 11
 
2.3%
Other values (104) 297
62.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 474
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 33
 
7.0%
이 30
 
6.3%
정 18
 
3.8%
영 18
 
3.8%
희 15
 
3.2%
미 14
 
3.0%
박 14
 
3.0%
숙 13
 
2.7%
경 11
 
2.3%
선 11
 
2.3%
Other values (104) 297
62.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 474
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 33
 
7.0%
이 30
 
6.3%
정 18
 
3.8%
영 18
 
3.8%
희 15
 
3.2%
미 14
 
3.0%
박 14
 
3.0%
숙 13
 
2.7%
경 11
 
2.3%
선 11
 
2.3%
Other values (104) 297
62.7%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
1156000000
158 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1156000000
2nd row1156000000
3rd row1156000000
4th row1156000000
5th row1156000000

Common Values

ValueCountFrequency (%)
1156000000 158
100.0%

Length

2024-05-04T00:19:51.147461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:19:51.325552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1156000000 158
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
영등포구
158 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영등포구 158
100.0%

Length

2024-05-04T00:19:51.597323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T00:19:51.911017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영등포구 158
100.0%

시설주소
Text

Distinct151
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-04T00:19:52.555348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length43
Mean length30.753165
Min length15

Characters and Unicode

Total characters4859
Distinct characters157
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

Unique145 ?
Unique (%)91.8%

Sample

1st row경기도 군포시 고산로 589
2nd row서울특별시 마포구 마포대로 182-10성촌빌딩 2층공덕동
3rd row서울특별시 영등포구 대림로12가길 7-1
4th row서울특별시 영등포구 도림로 482
5th row서울특별시 영등포구 도림로 482
ValueCountFrequency (%)
서울특별시 151
 
17.4%
영등포구 151
 
17.4%
신길동 33
 
3.8%
대림동 23
 
2.6%
도림로 14
 
1.6%
2층 13
 
1.5%
1층 10
 
1.2%
도림동 7
 
0.8%
3층 7
 
0.8%
여의대방로 7
 
0.8%
Other values (318) 452
52.1%
2024-05-04T00:19:53.489970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
716
 
14.7%
영 196
 
4.0%
포 186
 
3.8%
등 183
 
3.8%
1 166
 
3.4%
시 159
 
3.3%
로 158
 
3.3%
서 155
 
3.2%
구 155
 
3.2%
울 153
 
3.1%
Other values (147) 2632
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2884
59.4%
Decimal Number 850
 
17.5%
Space Separator 716
 
14.7%
Open Punctuation 130
 
2.7%
Close Punctuation 130
 
2.7%
Other Punctuation 92
 
1.9%
Dash Punctuation 51
 
1.0%
Math Symbol 3
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 196
 
6.8%
포 186
 
6.4%
등 183
 
6.3%
시 159
 
5.5%
로 158
 
5.5%
서 155
 
5.4%
구 155
 
5.4%
울 153
 
5.3%
특 151
 
5.2%
별 151
 
5.2%
Other values (128) 1237
42.9%
Decimal Number
ValueCountFrequency (%)
1 166
19.5%
2 131
15.4%
3 125
14.7%
4 103
12.1%
0 72
8.5%
5 70
8.2%
8 57
 
6.7%
6 54
 
6.4%
9 44
 
5.2%
7 28
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 90
97.8%
. 2
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
716
100.0%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2884
59.4%
Common 1972
40.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 196
 
6.8%
포 186
 
6.4%
등 183
 
6.3%
시 159
 
5.5%
로 158
 
5.5%
서 155
 
5.4%
구 155
 
5.4%
울 153
 
5.3%
특 151
 
5.2%
별 151
 
5.2%
Other values (128) 1237
42.9%
Common
ValueCountFrequency (%)
716
36.3%
1 166
 
8.4%
2 131
 
6.6%
( 130
 
6.6%
) 130
 
6.6%
3 125
 
6.3%
4 103
 
5.2%
, 90
 
4.6%
0 72
 
3.7%
5 70
 
3.5%
Other values (7) 239
 
12.1%
Latin
ValueCountFrequency (%)
B 2
66.7%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2884
59.4%
ASCII 1975
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
716
36.3%
1 166
 
8.4%
2 131
 
6.6%
( 130
 
6.6%
) 130
 
6.6%
3 125
 
6.3%
4 103
 
5.2%
, 90
 
4.6%
0 72
 
3.6%
5 70
 
3.5%
Other values (9) 242
 
12.3%
Hangul
ValueCountFrequency (%)
영 196
 
6.8%
포 186
 
6.4%
등 183
 
6.3%
시 159
 
5.5%
로 158
 
5.5%
서 155
 
5.4%
구 155
 
5.4%
울 153
 
5.3%
특 151
 
5.2%
별 151
 
5.2%
Other values (128) 1237
42.9%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct44
Distinct (%)34.6%
Missing31
Missing (%)19.6%
Infinite0
Infinite (%)0.0%
Mean144.74803
Minimum0
Maximum13000
Zeros16
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-04T00:19:53.855882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median20
Q335
95-th percentile140.4
Maximum13000
Range13000
Interquartile range (IQR)26

Descriptive statistics

Standard deviation1154.1911
Coefficient of variation (CV)7.9737948
Kurtosis125.02106
Mean144.74803
Median Absolute Deviation (MAD)12
Skewness11.142535
Sum18383
Variance1332157.1
MonotonicityNot monotonic
2024-05-04T00:19:54.293048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 16
 
10.1%
9 11
 
7.0%
20 10
 
6.3%
35 7
 
4.4%
8 7
 
4.4%
15 6
 
3.8%
25 5
 
3.2%
43 4
 
2.5%
21 4
 
2.5%
28 3
 
1.9%
Other values (34) 54
34.2%
(Missing) 31
19.6%
ValueCountFrequency (%)
0 16
10.1%
4 3
 
1.9%
6 2
 
1.3%
7 2
 
1.3%
8 7
4.4%
9 11
7.0%
10 3
 
1.9%
11 1
 
0.6%
12 1
 
0.6%
15 6
 
3.8%
ValueCountFrequency (%)
13000 1
 
0.6%
820 1
 
0.6%
700 1
 
0.6%
300 1
 
0.6%
249 1
 
0.6%
190 1
 
0.6%
150 1
 
0.6%
118 1
 
0.6%
100 2
1.3%
80 3
1.9%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct57
Distinct (%)55.3%
Missing55
Missing (%)34.8%
Infinite0
Infinite (%)0.0%
Mean453.35922
Minimum0
Maximum18448
Zeros2
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-04T00:19:54.704364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median28
Q351
95-th percentile935.6
Maximum18448
Range18448
Interquartile range (IQR)42

Descriptive statistics

Standard deviation2257.45
Coefficient of variation (CV)4.9793848
Kurtosis47.732396
Mean453.35922
Median Absolute Deviation (MAD)19
Skewness6.7323683
Sum46696
Variance5096080.6
MonotonicityNot monotonic
2024-05-04T00:19:55.142823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 9
 
5.7%
8 7
 
4.4%
21 5
 
3.2%
29 3
 
1.9%
20 3
 
1.9%
40 3
 
1.9%
16 3
 
1.9%
31 3
 
1.9%
19 3
 
1.9%
30 3
 
1.9%
Other values (47) 61
38.6%
(Missing) 55
34.8%
ValueCountFrequency (%)
0 2
 
1.3%
2 2
 
1.3%
3 1
 
0.6%
4 2
 
1.3%
6 1
 
0.6%
7 3
 
1.9%
8 7
4.4%
9 9
5.7%
11 1
 
0.6%
14 1
 
0.6%
ValueCountFrequency (%)
18448 1
0.6%
12512 1
0.6%
5974 1
0.6%
2100 1
0.6%
1200 1
0.6%
962 1
0.6%
698 1
0.6%
650 1
0.6%
500 1
0.6%
416 1
0.6%

전화번호
Text

Distinct150
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-05-04T00:19:55.710608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.797468
Min length9

Characters and Unicode

Total characters1706
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

Unique144 ?
Unique (%)91.1%

Sample

1st row031-390-1003
2nd row02-3667-1389
3rd row02-831-9311
4th row02-2637-3960
5th row02-2068-5326
ValueCountFrequency (%)
028323355 4
 
2.5%
028480014 2
 
1.3%
02-833-2307 2
 
1.3%
02-2631-3212 2
 
1.3%
02-831-9311 2
 
1.3%
0269540004 2
 
1.3%
02-6677-0909 1
 
0.6%
02-842-7179 1
 
0.6%
0262676781 1
 
0.6%
02-831-3535 1
 
0.6%
Other values (140) 140
88.6%
2024-05-04T00:19:56.727804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 282
16.5%
2 279
16.4%
- 196
11.5%
8 181
10.6%
3 168
9.8%
6 130
7.6%
1 123
7.2%
7 101
 
5.9%
4 91
 
5.3%
5 84
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1510
88.5%
Dash Punctuation 196
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 282
18.7%
2 279
18.5%
8 181
12.0%
3 168
11.1%
6 130
8.6%
1 123
8.1%
7 101
 
6.7%
4 91
 
6.0%
5 84
 
5.6%
9 71
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1706
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 282
16.5%
2 279
16.4%
- 196
11.5%
8 181
10.6%
3 168
9.8%
6 130
7.6%
1 123
7.2%
7 101
 
5.9%
4 91
 
5.3%
5 84
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1706
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 282
16.5%
2 279
16.4%
- 196
11.5%
8 181
10.6%
3 168
9.8%
6 130
7.6%
1 123
7.2%
7 101
 
5.9%
4 91
 
5.3%
5 84
 
4.9%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct90
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14008.652
Minimum4207
Maximum150953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-05-04T00:19:57.033706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4207
5-th percentile7222
Q17278
median7358
Q37423.5
95-th percentile18171.4
Maximum150953
Range146746
Interquartile range (IQR)145.5

Descriptive statistics

Standard deviation29610.631
Coefficient of variation (CV)2.1137388
Kurtosis17.995109
Mean14008.652
Median Absolute Deviation (MAD)70
Skewness4.4349563
Sum2213367
Variance8.767895 × 108
MonotonicityNot monotonic
2024-05-04T00:19:57.407557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7438 12
 
7.6%
7382 9
 
5.7%
7296 5
 
3.2%
150650 5
 
3.2%
7356 4
 
2.5%
7261 4
 
2.5%
7348 4
 
2.5%
7255 3
 
1.9%
7369 3
 
1.9%
7434 3
 
1.9%
Other values (80) 106
67.1%
ValueCountFrequency (%)
4207 1
 
0.6%
7201 2
1.3%
7206 2
1.3%
7220 2
1.3%
7222 3
1.9%
7223 1
 
0.6%
7228 1
 
0.6%
7230 2
1.3%
7235 1
 
0.6%
7239 1
 
0.6%
ValueCountFrequency (%)
150953 1
 
0.6%
150851 1
 
0.6%
150650 5
3.2%
31496 1
 
0.6%
15820 1
 
0.6%
12729 2
 
1.3%
12583 1
 
0.6%
12024 1
 
0.6%
7442 2
 
1.3%
7440 1
 
0.6%

Interactions

2024-05-04T00:19:43.347420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:41.800263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:42.573839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:43.618244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:42.048394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:42.758620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:43.911456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:42.307859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T00:19:43.082728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T00:19:57.716296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0001.0000.9700.841
시설종류상세명(시설종류)1.0001.0000.5100.7850.497
정원(수용인원)1.0000.5101.0001.0000.000
현인원0.9700.7851.0001.0000.000
우편번호0.8410.4970.0000.0001.000
2024-05-04T00:19:57.914335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)
시설종류명(시설유형)1.0000.931
시설종류상세명(시설종류)0.9311.000
2024-05-04T00:19:58.115199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.561-0.1290.8530.413
현인원0.5611.000-0.2080.7410.495
우편번호-0.129-0.2081.0000.5520.270
시설종류명(시설유형)0.8530.7410.5521.0000.931
시설종류상세명(시설종류)0.4130.4950.2700.9311.000

Missing values

2024-05-04T00:19:44.358577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T00:19:44.904126image/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.
2024-05-04T00:19:45.244906image/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
0서울특별시립 남부노인전문요양원A0016(노인) 노인요양시설노인의료복지시설자치구한철수1156000000영등포구경기도 군포시 고산로 589190188031-390-100315820
1중앙노인보호전문기관A1729(노인) 노인보호전문기관노인보호전문기관자치구최영숙1156000000영등포구서울특별시 마포구 마포대로 182-10성촌빌딩 2층공덕동0<NA>02-3667-13894207
2서울성모원A2156(노인) 양로시설노인주거복지시설자치구오양식1156000000영등포구서울특별시 영등포구 대림로12가길 7-19902-831-93117438
3구립영등포노인케어센터A3121(노인) 노인요양시설노인의료복지시설자치구이지은1156000000영등포구서울특별시 영등포구 도림로 48211811802-2637-39607296
4구립영등포노인종합복지관A4035(노인) 노인복지관노인여가복지시설자치구박영숙1156000000영등포구서울특별시 영등포구 도림로 482130001844802-2068-53267296
5구립영등포노인종합복지관병설데이케어센터A4044(노인) 재가노인복지시설재가노인복지시설자치구박영숙1156000000영등포구서울특별시 영등포구 도림로 482353502-2068-53257296
6구립여의도원광데이케어센터A4344(노인) 재가노인복지시설재가노인복지시설자치구양귀자1156000000영등포구서울특별시 영등포구 여의대방로68길 15영창빌딩 3층282802-782-44387343
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