Overview

Dataset statistics

Number of variables13
Number of observations81
Missing cells35
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory109.6 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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-20377/S/1/datasetView.do

Alerts

자치구(시)구분 has constant value ""Constant
시군구코드 has constant value ""Constant
시군구명 has constant value ""Constant
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
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) has 15 (18.5%) missing valuesMissing
현인원 has 20 (24.7%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 8 (9.9%) zerosZeros
현인원 has 4 (4.9%) zerosZeros

Reproduction

Analysis started2024-05-18 00:37:31.105487
Analysis finished2024-05-18 00:37:39.002991
Duration7.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct80
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-05-18T09:37:39.583464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length9.8765432
Min length3

Characters and Unicode

Total characters800
Distinct characters183
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)97.5%

Sample

1st row청운양로원
2nd row청운노인요양원
3rd row청운실버센터
4th row서울노인복지센터
5th row아름다운실버홈
ValueCountFrequency (%)
종로구 6
 
5.7%
우리동네키움센터 5
 
4.7%
친구네지역아동센터 2
 
1.9%
서울특별시립 2
 
1.9%
요양원 2
 
1.9%
종로노인종합복지관 1
 
0.9%
어르신상담센터 1
 
0.9%
3호점 1
 
0.9%
다정이네 1
 
0.9%
시립양평쉼터 1
 
0.9%
Other values (84) 84
79.2%
2024-05-18T09:37:40.961472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 54
 
6.8%
센 51
 
6.4%
지 30
 
3.8%
로 29
 
3.6%
종 28
 
3.5%
25
 
3.1%
동 23
 
2.9%
복 17
 
2.1%
가 16
 
2.0%
인 16
 
2.0%
Other values (173) 511
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 761
95.1%
Space Separator 25
 
3.1%
Decimal Number 6
 
0.8%
Close Punctuation 4
 
0.5%
Open Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 54
 
7.1%
센 51
 
6.7%
지 30
 
3.9%
로 29
 
3.8%
종 28
 
3.7%
동 23
 
3.0%
복 17
 
2.2%
가 16
 
2.1%
인 16
 
2.1%
구 14
 
1.8%
Other values (165) 483
63.5%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
4 1
16.7%
2 1
16.7%
5 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 761
95.1%
Common 39
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 54
 
7.1%
센 51
 
6.7%
지 30
 
3.9%
로 29
 
3.8%
종 28
 
3.7%
동 23
 
3.0%
복 17
 
2.2%
가 16
 
2.1%
인 16
 
2.1%
구 14
 
1.8%
Other values (165) 483
63.5%
Common
ValueCountFrequency (%)
25
64.1%
) 4
 
10.3%
( 4
 
10.3%
3 2
 
5.1%
4 1
 
2.6%
2 1
 
2.6%
5 1
 
2.6%
1 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 761
95.1%
ASCII 39
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 54
 
7.1%
센 51
 
6.7%
지 30
 
3.9%
로 29
 
3.8%
종 28
 
3.7%
동 23
 
3.0%
복 17
 
2.2%
가 16
 
2.1%
인 16
 
2.1%
구 14
 
1.8%
Other values (165) 483
63.5%
ASCII
ValueCountFrequency (%)
25
64.1%
) 4
 
10.3%
( 4
 
10.3%
3 2
 
5.1%
4 1
 
2.6%
2 1
 
2.6%
5 1
 
2.6%
1 1
 
2.6%

시설코드
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-05-18T09:37:41.938920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0246914
Min length5

Characters and Unicode

Total characters407
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

Unique81 ?
Unique (%)100.0%

Sample

1st rowA0002
2nd rowA0003
3rd rowA0937
4th rowA2947
5th rowA3469
ValueCountFrequency (%)
a0002 1
 
1.2%
e0405 1
 
1.2%
k1290 1
 
1.2%
k1220 1
 
1.2%
k1183 1
 
1.2%
k0502 1
 
1.2%
j4119 1
 
1.2%
j0767 1
 
1.2%
g9104 1
 
1.2%
g9059 1
 
1.2%
Other values (71) 71
87.7%
2024-05-18T09:37:43.109845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
15.0%
1 45
11.1%
2 34
8.4%
4 32
 
7.9%
9 31
 
7.6%
3 30
 
7.4%
7 30
 
7.4%
5 23
 
5.7%
6 21
 
5.2%
8 19
 
4.7%
Other values (13) 81
19.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 326
80.1%
Uppercase Letter 81
 
19.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 15
18.5%
C 12
14.8%
B 11
13.6%
K 8
9.9%
P 7
8.6%
Z 7
8.6%
F 6
 
7.4%
G 6
 
7.4%
E 3
 
3.7%
J 2
 
2.5%
Other values (3) 4
 
4.9%
Decimal Number
ValueCountFrequency (%)
0 61
18.7%
1 45
13.8%
2 34
10.4%
4 32
9.8%
9 31
9.5%
3 30
9.2%
7 30
9.2%
5 23
 
7.1%
6 21
 
6.4%
8 19
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 326
80.1%
Latin 81
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 15
18.5%
C 12
14.8%
B 11
13.6%
K 8
9.9%
P 7
8.6%
Z 7
8.6%
F 6
 
7.4%
G 6
 
7.4%
E 3
 
3.7%
J 2
 
2.5%
Other values (3) 4
 
4.9%
Common
ValueCountFrequency (%)
0 61
18.7%
1 45
13.8%
2 34
10.4%
4 32
9.8%
9 31
9.5%
3 30
9.2%
7 30
9.2%
5 23
 
7.1%
6 21
 
6.4%
8 19
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
15.0%
1 45
11.1%
2 34
8.4%
4 32
 
7.9%
9 31
 
7.6%
3 30
 
7.4%
7 30
 
7.4%
5 23
 
5.7%
6 21
 
5.2%
8 19
 
4.7%
Other values (13) 81
19.9%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size780.0 B
(노인) 재가노인복지시설
16 
(아동) 지역아동센터
12 
(노인) 노인요양시설
8 
(아동) 다함께돌봄센터
5 
(노인) 노인요양공동생활가정
 
3
Other values (31)
37 

Length

Max length28
Median length27
Mean length13.185185
Min length9

Unique

Unique25 ?
Unique (%)30.9%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 16
19.8%
(아동) 지역아동센터 12
14.8%
(노인) 노인요양시설 8
 
9.9%
(아동) 다함께돌봄센터 5
 
6.2%
(노인) 노인요양공동생활가정 3
 
3.7%
(노인) 노인복지관 2
 
2.5%
(장애인) 중증장애인거주시설 2
 
2.5%
(장애인) 장애인주간보호시설 2
 
2.5%
(노인) 장기요양기관 2
 
2.5%
(장애인) 장애인단기거주시설 2
 
2.5%
Other values (26) 27
33.3%

Length

2024-05-18T09:37:43.907201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 34
21.0%
아동 18
11.1%
재가노인복지시설 16
 
9.9%
장애인 13
 
8.0%
지역아동센터 12
 
7.4%
노인요양시설 8
 
4.9%
다함께돌봄센터 7
 
4.3%
정신보건 5
 
3.1%
노인요양공동생활가정 3
 
1.9%
노숙인등 3
 
1.9%
Other values (37) 43
26.5%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Memory size780.0 B
아동복지시설
18 
재가노인복지시설
16 
노인의료복지시설
11 
장애인거주시설
5 
장애인지역사회재활시설
4 
Other values (19)
27 

Length

Max length11
Median length9
Mean length7.2469136
Min length4

Unique

Unique14 ?
Unique (%)17.3%

Sample

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

Common Values

ValueCountFrequency (%)
아동복지시설 18
22.2%
재가노인복지시설 16
19.8%
노인의료복지시설 11
13.6%
장애인거주시설 5
 
6.2%
장애인지역사회재활시설 4
 
4.9%
정신재활시설 3
 
3.7%
장애인직업재활시설 3
 
3.7%
노인기타 3
 
3.7%
노인여가복지시설 2
 
2.5%
노숙인등이용시설 2
 
2.5%
Other values (14) 14
17.3%

Length

2024-05-18T09:37:44.550380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
아동복지시설 18
22.2%
재가노인복지시설 16
19.8%
노인의료복지시설 11
13.6%
장애인거주시설 5
 
6.2%
장애인지역사회재활시설 4
 
4.9%
정신재활시설 3
 
3.7%
장애인직업재활시설 3
 
3.7%
노인기타 3
 
3.7%
노인여가복지시설 2
 
2.5%
노숙인등이용시설 2
 
2.5%
Other values (14) 14
17.3%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
자치구
81 

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 81
100.0%

Length

2024-05-18T09:37:45.041101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:37:45.473932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 81
100.0%

시설장명
Text

Distinct72
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-05-18T09:37:46.167012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters243
Distinct characters82
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

Unique63 ?
Unique (%)77.8%

Sample

1st row이종명
2nd row이종후
3rd row이지원
4th row김경미
5th row박은영
ValueCountFrequency (%)
박지선 2
 
2.5%
이재원 2
 
2.5%
김종민 2
 
2.5%
조성재 2
 
2.5%
장유진 2
 
2.5%
이정연 2
 
2.5%
김영기 2
 
2.5%
이지원 2
 
2.5%
김경미 2
 
2.5%
이은혜 1
 
1.2%
Other values (62) 62
76.5%
2024-05-18T09:37:47.474999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 18
 
7.4%
김 17
 
7.0%
경 10
 
4.1%
박 8
 
3.3%
영 8
 
3.3%
지 8
 
3.3%
유 8
 
3.3%
은 7
 
2.9%
미 7
 
2.9%
명 6
 
2.5%
Other values (72) 146
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 18
 
7.4%
김 17
 
7.0%
경 10
 
4.1%
박 8
 
3.3%
영 8
 
3.3%
지 8
 
3.3%
유 8
 
3.3%
은 7
 
2.9%
미 7
 
2.9%
명 6
 
2.5%
Other values (72) 146
60.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 18
 
7.4%
김 17
 
7.0%
경 10
 
4.1%
박 8
 
3.3%
영 8
 
3.3%
지 8
 
3.3%
유 8
 
3.3%
은 7
 
2.9%
미 7
 
2.9%
명 6
 
2.5%
Other values (72) 146
60.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 18
 
7.4%
김 17
 
7.0%
경 10
 
4.1%
박 8
 
3.3%
영 8
 
3.3%
지 8
 
3.3%
유 8
 
3.3%
은 7
 
2.9%
미 7
 
2.9%
명 6
 
2.5%
Other values (72) 146
60.1%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
1111000000
81 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1111000000
2nd row1111000000
3rd row1111000000
4th row1111000000
5th row1111000000

Common Values

ValueCountFrequency (%)
1111000000 81
100.0%

Length

2024-05-18T09:37:47.942455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:37:48.266396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111000000 81
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
종로구
81 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 81
100.0%

Length

2024-05-18T09:37:48.725330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T09:37:49.221121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 81
100.0%

시설주소
Text

Distinct79
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-05-18T09:37:49.914015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length38
Mean length27.197531
Min length17

Characters and Unicode

Total characters2203
Distinct characters151
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

Unique77 ?
Unique (%)95.1%

Sample

1st row서울특별시 종로구 비봉길 76 (구기동)
2nd row서울특별시 종로구 비봉길 76 (구기동)
3rd row서울특별시 종로구 자하문로28길 29 (청운동)
4th row서울특별시 종로구 삼일대로 467(경운동)
5th row서울특별시 종로구 평창길 123 (평창동)
ValueCountFrequency (%)
서울특별시 77
 
18.1%
종로구 77
 
18.1%
창신동 9
 
2.1%
평창동 8
 
1.9%
2층 5
 
1.2%
창신길 4
 
0.9%
신영동 4
 
0.9%
이화동 3
 
0.7%
텃골1길 3
 
0.7%
철원군 3
 
0.7%
Other values (189) 232
54.6%
2024-05-18T09:37:51.264055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
346
 
15.7%
로 138
 
6.3%
종 94
 
4.3%
1 80
 
3.6%
구 80
 
3.6%
시 78
 
3.5%
서 77
 
3.5%
울 77
 
3.5%
별 77
 
3.5%
특 77
 
3.5%
Other values (141) 1079
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1305
59.2%
Decimal Number 370
 
16.8%
Space Separator 346
 
15.7%
Open Punctuation 64
 
2.9%
Close Punctuation 64
 
2.9%
Dash Punctuation 27
 
1.2%
Other Punctuation 24
 
1.1%
Math Symbol 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 138
 
10.6%
종 94
 
7.2%
구 80
 
6.1%
시 78
 
6.0%
서 77
 
5.9%
울 77
 
5.9%
별 77
 
5.9%
특 77
 
5.9%
동 70
 
5.4%
길 62
 
4.8%
Other values (124) 475
36.4%
Decimal Number
ValueCountFrequency (%)
1 80
21.6%
2 72
19.5%
3 35
9.5%
0 34
9.2%
8 28
 
7.6%
4 28
 
7.6%
9 26
 
7.0%
5 24
 
6.5%
6 22
 
5.9%
7 21
 
5.7%
Space Separator
ValueCountFrequency (%)
346
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1305
59.2%
Common 897
40.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 138
 
10.6%
종 94
 
7.2%
구 80
 
6.1%
시 78
 
6.0%
서 77
 
5.9%
울 77
 
5.9%
별 77
 
5.9%
특 77
 
5.9%
동 70
 
5.4%
길 62
 
4.8%
Other values (124) 475
36.4%
Common
ValueCountFrequency (%)
346
38.6%
1 80
 
8.9%
2 72
 
8.0%
( 64
 
7.1%
) 64
 
7.1%
3 35
 
3.9%
0 34
 
3.8%
8 28
 
3.1%
4 28
 
3.1%
- 27
 
3.0%
Other values (6) 119
 
13.3%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1305
59.2%
ASCII 898
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
346
38.5%
1 80
 
8.9%
2 72
 
8.0%
( 64
 
7.1%
) 64
 
7.1%
3 35
 
3.9%
0 34
 
3.8%
8 28
 
3.1%
4 28
 
3.1%
- 27
 
3.0%
Other values (7) 120
 
13.4%
Hangul
ValueCountFrequency (%)
로 138
 
10.6%
종 94
 
7.2%
구 80
 
6.1%
시 78
 
6.0%
서 77
 
5.9%
울 77
 
5.9%
별 77
 
5.9%
특 77
 
5.9%
동 70
 
5.4%
길 62
 
4.8%
Other values (124) 475
36.4%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct38
Distinct (%)57.6%
Missing15
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean95.272727
Minimum0
Maximum2000
Zeros8
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size861.0 B
2024-05-18T09:37:51.776499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median22
Q342
95-th percentile304.5
Maximum2000
Range2000
Interquartile range (IQR)30

Descriptive statistics

Standard deviation302.34614
Coefficient of variation (CV)3.1734804
Kurtosis30.239988
Mean95.272727
Median Absolute Deviation (MAD)13.5
Skewness5.400715
Sum6288
Variance91413.186
MonotonicityNot monotonic
2024-05-18T09:37:52.286547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 8
 
9.9%
20 6
 
7.4%
19 5
 
6.2%
10 3
 
3.7%
29 3
 
3.7%
30 3
 
3.7%
35 3
 
3.7%
100 2
 
2.5%
17 2
 
2.5%
38 2
 
2.5%
Other values (28) 29
35.8%
(Missing) 15
18.5%
ValueCountFrequency (%)
0 8
9.9%
4 1
 
1.2%
5 1
 
1.2%
7 1
 
1.2%
8 1
 
1.2%
9 1
 
1.2%
10 3
 
3.7%
11 1
 
1.2%
15 1
 
1.2%
16 1
 
1.2%
ValueCountFrequency (%)
2000 1
1.2%
1449 1
1.2%
389 1
1.2%
330 1
1.2%
228 1
1.2%
200 1
1.2%
131 1
1.2%
100 2
2.5%
77 1
1.2%
76 1
1.2%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct41
Distinct (%)67.2%
Missing20
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean193.36066
Minimum0
Maximum3200
Zeros4
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size861.0 B
2024-05-18T09:37:52.905108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113
median29
Q377
95-th percentile1345
Maximum3200
Range3200
Interquartile range (IQR)64

Descriptive statistics

Standard deviation553.23386
Coefficient of variation (CV)2.8611501
Kurtosis17.215506
Mean193.36066
Median Absolute Deviation (MAD)19
Skewness4.0527221
Sum11795
Variance306067.7
MonotonicityNot monotonic
2024-05-18T09:37:53.491533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
6 5
 
6.2%
0 4
 
4.9%
19 4
 
4.9%
10 3
 
3.7%
38 2
 
2.5%
77 2
 
2.5%
31 2
 
2.5%
35 2
 
2.5%
23 2
 
2.5%
44 2
 
2.5%
Other values (31) 33
40.7%
(Missing) 20
24.7%
ValueCountFrequency (%)
0 4
4.9%
3 1
 
1.2%
6 5
6.2%
7 1
 
1.2%
9 1
 
1.2%
10 3
3.7%
13 1
 
1.2%
16 1
 
1.2%
17 2
 
2.5%
19 4
4.9%
ValueCountFrequency (%)
3200 1
1.2%
2000 1
1.2%
1944 1
1.2%
1345 1
1.2%
598 1
1.2%
503 1
1.2%
211 1
1.2%
189 1
1.2%
160 1
1.2%
146 1
1.2%

전화번호
Text

Distinct75
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size780.0 B
2024-05-18T09:37:54.298852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.777778
Min length9

Characters and Unicode

Total characters873
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)87.7%

Sample

1st row02-379-9232
2nd row02-3217-0057
3rd row02-730-4966
4th row02-739-9501
5th row02-394-0461
ValueCountFrequency (%)
027450794 3
 
3.7%
02-391-7936 3
 
3.7%
02-766-8282 2
 
2.5%
02-3676-5509 2
 
2.5%
027435515 1
 
1.2%
0263957045 1
 
1.2%
02-6220-8500 1
 
1.2%
027449707 1
 
1.2%
02-742-0515 1
 
1.2%
02-1877-5255 1
 
1.2%
Other values (65) 65
80.2%
2024-05-18T09:37:55.725714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 144
16.5%
2 117
13.4%
- 108
12.4%
7 99
11.3%
4 78
8.9%
3 76
8.7%
5 63
7.2%
9 63
7.2%
6 60
6.9%
1 42
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 765
87.6%
Dash Punctuation 108
 
12.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144
18.8%
2 117
15.3%
7 99
12.9%
4 78
10.2%
3 76
9.9%
5 63
8.2%
9 63
8.2%
6 60
7.8%
1 42
 
5.5%
8 23
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 144
16.5%
2 117
13.4%
- 108
12.4%
7 99
11.3%
4 78
8.9%
3 76
8.7%
5 63
7.2%
9 63
7.2%
6 60
6.9%
1 42
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 144
16.5%
2 117
13.4%
- 108
12.4%
7 99
11.3%
4 78
8.9%
3 76
8.7%
5 63
7.2%
9 63
7.2%
6 60
6.9%
1 42
 
4.8%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8428.6296
Minimum3001
Maximum269804
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2024-05-18T09:37:56.582138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3001
5-th percentile3004
Q13033
median3091
Q33120
95-th percentile12524
Maximum269804
Range266803
Interquartile range (IQR)87

Descriptive statistics

Standard deviation31878.992
Coefficient of variation (CV)3.7822271
Kurtosis59.164173
Mean8428.6296
Median Absolute Deviation (MAD)44
Skewness7.4773878
Sum682719
Variance1.0162701 × 109
MonotonicityNot monotonic
2024-05-18T09:37:57.178444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3100 4
 
4.9%
3015 3
 
3.7%
3091 3
 
3.7%
3097 3
 
3.7%
3001 2
 
2.5%
3089 2
 
2.5%
3139 2
 
2.5%
3047 2
 
2.5%
3140 2
 
2.5%
3067 2
 
2.5%
Other values (44) 56
69.1%
ValueCountFrequency (%)
3001 2
2.5%
3002 2
2.5%
3004 1
1.2%
3005 1
1.2%
3006 2
2.5%
3007 1
1.2%
3008 1
1.2%
3009 1
1.2%
3011 1
1.2%
3014 1
1.2%
ValueCountFrequency (%)
269804 1
1.2%
110032 1
1.2%
24030 2
2.5%
12524 1
1.2%
11521 1
1.2%
3180 1
1.2%
3169 1
1.2%
3165 1
1.2%
3147 2
2.5%
3140 2
2.5%

Interactions

2024-05-18T09:37:36.263774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:34.646574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:35.489364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:36.545043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:34.932849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:35.758440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:36.809882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:35.240134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T09:37:36.017995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T09:37:57.542655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)시설장명시설주소정원(수용인원)현인원전화번호우편번호
시설명1.0001.0001.0001.0001.0000.9961.0001.0001.0001.000
시설코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시설종류명(시설유형)1.0001.0001.0001.0000.0000.9840.9300.9430.9931.000
시설종류상세명(시설종류)1.0001.0001.0001.0000.5490.9440.7930.7440.9930.436
시설장명1.0001.0000.0000.5491.0000.9980.0000.0000.9920.000
시설주소0.9961.0000.9840.9440.9981.0001.0001.0000.9851.000
정원(수용인원)1.0001.0000.9300.7930.0001.0001.0000.6071.0000.000
현인원1.0001.0000.9430.7440.0001.0000.6071.0000.7510.000
전화번호1.0001.0000.9930.9930.9920.9851.0000.7511.0001.000
우편번호1.0001.0001.0000.4360.0001.0000.0000.0001.0001.000
2024-05-18T09:37:57.924194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)
시설종류명(시설유형)1.0000.889
시설종류상세명(시설종류)0.8891.000
2024-05-18T09:37:58.216541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.5190.0420.5850.496
현인원0.5191.0000.1470.5320.417
우편번호0.0420.1471.0000.7600.196
시설종류명(시설유형)0.5850.5320.7601.0000.889
시설종류상세명(시설종류)0.4960.4170.1960.8891.000

Missing values

2024-05-18T09:37:37.321085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T09:37:37.886555image/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.
2024-05-18T09:37:38.586448image/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
0청운양로원A0002(노인) 양로시설노인주거복지시설자치구이종명1111000000종로구서울특별시 종로구 비봉길 76 (구기동)575002-379-92323001
1청운노인요양원A0003(노인) 노인요양시설노인의료복지시설자치구이종후1111000000종로구서울특별시 종로구 비봉길 76 (구기동)454502-3217-00573001
2청운실버센터A0937(노인) 노인요양공동생활가정노인의료복지시설자치구이지원1111000000종로구서울특별시 종로구 자하문로28길 29 (청운동)9902-730-49663047
3서울노인복지센터A2947(노인) 노인복지관노인여가복지시설자치구김경미1111000000종로구서울특별시 종로구 삼일대로 467(경운동)0320002-739-95013147
4아름다운실버홈A3469(노인) 노인요양시설노인의료복지시설자치구박은영1111000000종로구서울특별시 종로구 평창길 123 (평창동)161602-394-04613002
5종로노인종합복지관A3971(노인) 노인복지관노인여가복지시설자치구정영순1111000000종로구서울특별시 종로구 율곡로19길 17-8(이화동)2000200002-742-95003100
6북악실버홈 (휴지중)A3980(노인) 노인요양공동생활가정노인의료복지시설자치구손양순1111000000종로구서울특별시 종로구 진흥로 493-6 (신영동)5002-391-79363007
7우리모두재가노인지원센터A5003(노인) 재가노인복지시설재가노인복지시설자치구권양희1111000000종로구서울특별시 종로구 지봉로12나길 1-0B0210011002-744-85733108
8종로데이케어센터A5081(노인) 재가노인복지시설재가노인복지시설자치구이재원1111000000종로구서울특별시 종로구 지봉로13길 82 (창신동)171702-741-49043091
9보현데이케어센터A5868(노인) 재가노인복지시설재가노인복지시설자치구양유진1111000000종로구서울특별시 종로구 평창4길 21-22(평창동)202002-394-55113002
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
71미래다움재가복지센터P3189(노인) 재가노인복지시설재가노인복지시설자치구천세현1111000000종로구서울특별시 종로구 대학로 144, 507호 (혜화동)<NA><NA>070426734993084
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74종로지역자활센터Z0314(저소득) 지역자활센터자활시설자치구한재경1111000000종로구서울특별시 종로구 종로63가길 59-3(숭인동)768202-3673-39633110
75종로종합사회복지관Z5326(일반) 사회복지관일반사회복지시설자치구오성택1111000000종로구서울특별시 종로구 지봉로13길 82종로종합사회복지관 (창신동)<NA>194402-766-82823091
76종로시니어클럽Z5442(노인) 노인일자리지원기관노인일자리지원기관자치구전석달1111000000종로구서울특별시 종로구 숭인동2길 28(숭인동)<NA>602-762-33743110
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78종로구정신건강복지센터Z5496(정신보건) 정신건강증진센터정신보건기타자치구서화연1111000000종로구서울특별시 종로구 성균관로15길 10 (명륜1가)389<NA>02-745-01993066
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