Overview

Dataset statistics

Number of variables13
Number of observations184
Missing cells88
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.5 KiB
Average record size in memory108.7 B

Variable types

Text5
Categorical5
Numeric3

Dataset

Description시설명,시설코드,시설종류명(시설유형),시설종류상세명(시설종류),자치구(시)구분,시설장명,시군구코드,시군구명,시설주소,정원(수용인원),현인원,전화번호,우편번호
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20391/S/1/datasetView.do

Alerts

자치구(시)구분 has constant value ""Constant
시군구코드 has constant value ""Constant
시군구명 has constant value ""Constant
시설종류상세명(시설종류) is highly overall correlated with 정원(수용인원) and 2 other fieldsHigh correlation
시설종류명(시설유형) is highly overall correlated with 정원(수용인원) and 2 other fieldsHigh correlation
정원(수용인원) is highly overall correlated with 현인원 and 2 other fieldsHigh correlation
현인원 is highly overall correlated with 정원(수용인원) and 2 other fieldsHigh correlation
정원(수용인원) has 37 (20.1%) missing valuesMissing
현인원 has 50 (27.2%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 3 (1.6%) zerosZeros
현인원 has 2 (1.1%) zerosZeros

Reproduction

Analysis started2024-05-11 02:20:27.843647
Analysis finished2024-05-11 02:20:34.544162
Duration6.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct175
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T02:20:34.892214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length9.8695652
Min length3

Characters and Unicode

Total characters1816
Distinct characters242
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)90.2%

Sample

1st row목동종합사회복지관병설목동노인복지센터
2nd row두엄자리
3rd row어르신이행복한세상주야간보호센터
4th row어르신이행복한세상요양센터01호
5th row양천어르신종합복지관
ValueCountFrequency (%)
재가복지센터 5
 
2.2%
우리동네키움센터 5
 
2.2%
양천구 5
 
2.2%
요양원 3
 
1.3%
아름드리지역아동센터 2
 
0.9%
융합형 2
 
0.9%
공동생활가정 2
 
0.9%
새희망 2
 
0.9%
다니엘청소년지역아동센터 2
 
0.9%
사랑초 2
 
0.9%
Other values (189) 196
86.7%
2024-05-11T02:20:36.276374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 112
 
6.2%
센 109
 
6.0%
지 84
 
4.6%
동 64
 
3.5%
복 56
 
3.1%
양 50
 
2.8%
45
 
2.5%
어 44
 
2.4%
가 37
 
2.0%
아 36
 
2.0%
Other values (232) 1179
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1746
96.1%
Space Separator 45
 
2.5%
Decimal Number 9
 
0.5%
Uppercase Letter 6
 
0.3%
Close Punctuation 5
 
0.3%
Open Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 112
 
6.4%
센 109
 
6.2%
지 84
 
4.8%
동 64
 
3.7%
복 56
 
3.2%
양 50
 
2.9%
어 44
 
2.5%
가 37
 
2.1%
아 36
 
2.1%
이 33
 
1.9%
Other values (221) 1121
64.2%
Decimal Number
ValueCountFrequency (%)
1 2
22.2%
5 2
22.2%
3 2
22.2%
4 1
11.1%
2 1
11.1%
0 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
S 4
66.7%
O 2
33.3%
Space Separator
ValueCountFrequency (%)
45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1746
96.1%
Common 64
 
3.5%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 112
 
6.4%
센 109
 
6.2%
지 84
 
4.8%
동 64
 
3.7%
복 56
 
3.2%
양 50
 
2.9%
어 44
 
2.5%
가 37
 
2.1%
아 36
 
2.1%
이 33
 
1.9%
Other values (221) 1121
64.2%
Common
ValueCountFrequency (%)
45
70.3%
) 5
 
7.8%
( 5
 
7.8%
1 2
 
3.1%
5 2
 
3.1%
3 2
 
3.1%
4 1
 
1.6%
2 1
 
1.6%
0 1
 
1.6%
Latin
ValueCountFrequency (%)
S 4
66.7%
O 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1746
96.1%
ASCII 70
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 112
 
6.4%
센 109
 
6.2%
지 84
 
4.8%
동 64
 
3.7%
복 56
 
3.2%
양 50
 
2.9%
어 44
 
2.5%
가 37
 
2.1%
아 36
 
2.1%
이 33
 
1.9%
Other values (221) 1121
64.2%
ASCII
ValueCountFrequency (%)
45
64.3%
) 5
 
7.1%
( 5
 
7.1%
S 4
 
5.7%
1 2
 
2.9%
5 2
 
2.9%
O 2
 
2.9%
3 2
 
2.9%
4 1
 
1.4%
2 1
 
1.4%

시설코드
Text

UNIQUE 

Distinct184
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T02:20:37.512650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0163043
Min length5

Characters and Unicode

Total characters923
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

Unique184 ?
Unique (%)100.0%

Sample

1st rowA0707
2nd rowA0765
3rd rowA1294
4th rowA1328
5th rowA1732
ValueCountFrequency (%)
a0707 1
 
0.5%
j6871 1
 
0.5%
k0641 1
 
0.5%
g8537 1
 
0.5%
g8558 1
 
0.5%
g8620 1
 
0.5%
g8732 1
 
0.5%
g8775 1
 
0.5%
g8914 1
 
0.5%
g9798 1
 
0.5%
Other values (174) 174
94.6%
2024-05-11T02:20:39.067837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 108
11.7%
5 92
10.0%
0 90
9.8%
9 69
 
7.5%
3 67
 
7.3%
4 66
 
7.2%
8 65
 
7.0%
7 63
 
6.8%
2 60
 
6.5%
6 59
 
6.4%
Other values (13) 184
19.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 739
80.1%
Uppercase Letter 184
 
19.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
G 45
24.5%
B 25
13.6%
C 23
12.5%
K 22
12.0%
P 22
12.0%
A 18
 
9.8%
F 11
 
6.0%
Z 9
 
4.9%
J 4
 
2.2%
W 2
 
1.1%
Other values (3) 3
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 108
14.6%
5 92
12.4%
0 90
12.2%
9 69
9.3%
3 67
9.1%
4 66
8.9%
8 65
8.8%
7 63
8.5%
2 60
8.1%
6 59
8.0%

Most occurring scripts

ValueCountFrequency (%)
Common 739
80.1%
Latin 184
 
19.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 45
24.5%
B 25
13.6%
C 23
12.5%
K 22
12.0%
P 22
12.0%
A 18
 
9.8%
F 11
 
6.0%
Z 9
 
4.9%
J 4
 
2.2%
W 2
 
1.1%
Other values (3) 3
 
1.6%
Common
ValueCountFrequency (%)
1 108
14.6%
5 92
12.4%
0 90
12.2%
9 69
9.3%
3 67
9.1%
4 66
8.9%
8 65
8.8%
7 63
8.5%
2 60
8.1%
6 59
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 108
11.7%
5 92
10.0%
0 90
9.8%
9 69
 
7.5%
3 67
 
7.3%
4 66
 
7.2%
8 65
 
7.0%
7 63
 
6.8%
2 60
 
6.5%
6 59
 
6.4%
Other values (13) 184
19.9%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
(노인) 재가노인복지시설
61 
(아동) 지역아동센터
30 
(노인) 노인요양시설
14 
(아동) 공동생활가정
12 
(노인) 노인요양공동생활가정
9 
Other values (27)
58 

Length

Max length21
Median length20
Mean length12.673913
Min length10

Unique

Unique18 ?
Unique (%)9.8%

Sample

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

Common Values

ValueCountFrequency (%)
(노인) 재가노인복지시설 61
33.2%
(아동) 지역아동센터 30
16.3%
(노인) 노인요양시설 14
 
7.6%
(아동) 공동생활가정 12
 
6.5%
(노인) 노인요양공동생활가정 9
 
4.9%
(장애인) 장애인공동생활가정 8
 
4.3%
(정신보건) 생활시설 6
 
3.3%
(장애인) 장애인주간보호시설 6
 
3.3%
(일반) 사회복지관 5
 
2.7%
(아동) 다함께돌봄센터 5
 
2.7%
Other values (22) 28
15.2%

Length

2024-05-11T02:20:39.742053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노인 90
24.5%
재가노인복지시설 61
16.6%
아동 49
13.3%
지역아동센터 30
 
8.2%
장애인 24
 
6.5%
노인요양시설 14
 
3.8%
공동생활가정 12
 
3.3%
노인요양공동생활가정 9
 
2.4%
정신보건 9
 
2.4%
장애인공동생활가정 8
 
2.2%
Other values (33) 62
16.8%

시설종류상세명(시설종류)
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
재가노인복지시설
61 
아동복지시설
49 
노인의료복지시설
23 
장애인거주시설
11 
장애인지역사회재활시설
8 
Other values (15)
32 

Length

Max length11
Median length8
Mean length7.4021739
Min length4

Unique

Unique10 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 61
33.2%
아동복지시설 49
26.6%
노인의료복지시설 23
 
12.5%
장애인거주시설 11
 
6.0%
장애인지역사회재활시설 8
 
4.3%
정신재활시설 8
 
4.3%
일반사회복지시설 5
 
2.7%
노인여가복지시설 4
 
2.2%
장애인직업재활시설 3
 
1.6%
자활시설 2
 
1.1%
Other values (10) 10
 
5.4%

Length

2024-05-11T02:20:40.518651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재가노인복지시설 61
33.2%
아동복지시설 49
26.6%
노인의료복지시설 23
 
12.5%
장애인거주시설 11
 
6.0%
장애인지역사회재활시설 8
 
4.3%
정신재활시설 8
 
4.3%
일반사회복지시설 5
 
2.7%
노인여가복지시설 4
 
2.2%
장애인직업재활시설 3
 
1.6%
자활시설 2
 
1.1%
Other values (10) 10
 
5.4%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
자치구
184 

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 184
100.0%

Length

2024-05-11T02:20:40.963890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:41.298183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 184
100.0%

시설장명
Text

Distinct157
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T02:20:42.294406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9945652
Min length2

Characters and Unicode

Total characters551
Distinct characters122
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

Unique133 ?
Unique (%)72.3%

Sample

1st row유영덕
2nd row김명화
3rd row박병택
4th row박병택
5th row한승호
ValueCountFrequency (%)
김경환 3
 
1.6%
한승호 3
 
1.6%
장동국 3
 
1.6%
최경주 2
 
1.1%
김광제 2
 
1.1%
강신구 2
 
1.1%
이영애 2
 
1.1%
송민하 2
 
1.1%
이재근 2
 
1.1%
김원수 2
 
1.1%
Other values (146) 161
87.5%
2024-05-11T02:20:43.865884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 43
 
7.8%
경 21
 
3.8%
정 19
 
3.4%
이 19
 
3.4%
영 18
 
3.3%
미 15
 
2.7%
박 15
 
2.7%
숙 13
 
2.4%
현 11
 
2.0%
은 10
 
1.8%
Other values (112) 367
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 550
99.8%
Space Separator 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 43
 
7.8%
경 21
 
3.8%
정 19
 
3.5%
이 19
 
3.5%
영 18
 
3.3%
미 15
 
2.7%
박 15
 
2.7%
숙 13
 
2.4%
현 11
 
2.0%
은 10
 
1.8%
Other values (111) 366
66.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 550
99.8%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 43
 
7.8%
경 21
 
3.8%
정 19
 
3.5%
이 19
 
3.5%
영 18
 
3.3%
미 15
 
2.7%
박 15
 
2.7%
숙 13
 
2.4%
현 11
 
2.0%
은 10
 
1.8%
Other values (111) 366
66.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 550
99.8%
ASCII 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 43
 
7.8%
경 21
 
3.8%
정 19
 
3.5%
이 19
 
3.5%
영 18
 
3.3%
미 15
 
2.7%
박 15
 
2.7%
숙 13
 
2.4%
현 11
 
2.0%
은 10
 
1.8%
Other values (111) 366
66.5%
ASCII
ValueCountFrequency (%)
1
100.0%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
1147000000
184 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1147000000
2nd row1147000000
3rd row1147000000
4th row1147000000
5th row1147000000

Common Values

ValueCountFrequency (%)
1147000000 184
100.0%

Length

2024-05-11T02:20:44.414811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:44.789901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1147000000 184
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
양천구
184 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양천구 184
100.0%

Length

2024-05-11T02:20:45.266722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:20:45.703718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 184
100.0%

시설주소
Text

Distinct178
Distinct (%)97.3%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-05-11T02:20:46.246930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length30.196721
Min length14

Characters and Unicode

Total characters5526
Distinct characters178
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

Unique173 ?
Unique (%)94.5%

Sample

1st row서울특별시 양천구 목동중앙북로8길 104목동종합사회복지관 2층
2nd row서울특별시 양천구 목동중앙남로16다길 6-13 (목동)
3rd row서울특별시 양천구 신월로 338원빌딩 2층
4th row서울특별시 양천구 신월로 338원빌딩 2층
5th row서울특별시 양천구 목동로3길 106서울특별시 양천구 목동로3길106 (신정동)
ValueCountFrequency (%)
양천구 182
 
17.7%
서울특별시 181
 
17.6%
신월동 55
 
5.4%
신정동 52
 
5.1%
목동 25
 
2.4%
2층 17
 
1.7%
1층 15
 
1.5%
3층 15
 
1.5%
오목로 9
 
0.9%
신월로 9
 
0.9%
Other values (346) 468
45.5%
2024-05-11T02:20:47.450762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
851
 
15.4%
동 234
 
4.2%
양 197
 
3.6%
1 194
 
3.5%
로 189
 
3.4%
천 188
 
3.4%
서 187
 
3.4%
시 186
 
3.4%
구 184
 
3.3%
울 183
 
3.3%
Other values (168) 2933
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3324
60.2%
Decimal Number 893
 
16.2%
Space Separator 852
 
15.4%
Close Punctuation 150
 
2.7%
Open Punctuation 149
 
2.7%
Other Punctuation 125
 
2.3%
Dash Punctuation 23
 
0.4%
Uppercase Letter 9
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 234
 
7.0%
양 197
 
5.9%
로 189
 
5.7%
천 188
 
5.7%
서 187
 
5.6%
시 186
 
5.6%
구 184
 
5.5%
울 183
 
5.5%
별 183
 
5.5%
특 182
 
5.5%
Other values (143) 1411
42.4%
Decimal Number
ValueCountFrequency (%)
1 194
21.7%
2 154
17.2%
3 119
13.3%
0 102
11.4%
4 79
8.8%
5 75
 
8.4%
6 58
 
6.5%
7 39
 
4.4%
9 37
 
4.1%
8 36
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
W 1
 
11.1%
I 1
 
11.1%
V 1
 
11.1%
K 1
 
11.1%
S 1
 
11.1%
E 1
 
11.1%
Space Separator
ValueCountFrequency (%)
851
99.9%
　 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 121
96.8%
. 4
 
3.2%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3324
60.2%
Common 2193
39.7%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 234
 
7.0%
양 197
 
5.9%
로 189
 
5.7%
천 188
 
5.7%
서 187
 
5.6%
시 186
 
5.6%
구 184
 
5.5%
울 183
 
5.5%
별 183
 
5.5%
특 182
 
5.5%
Other values (143) 1411
42.4%
Common
ValueCountFrequency (%)
851
38.8%
1 194
 
8.8%
2 154
 
7.0%
) 150
 
6.8%
( 149
 
6.8%
, 121
 
5.5%
3 119
 
5.4%
0 102
 
4.7%
4 79
 
3.6%
5 75
 
3.4%
Other values (8) 199
 
9.1%
Latin
ValueCountFrequency (%)
B 3
33.3%
W 1
 
11.1%
I 1
 
11.1%
V 1
 
11.1%
K 1
 
11.1%
S 1
 
11.1%
E 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3324
60.2%
ASCII 2201
39.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
851
38.7%
1 194
 
8.8%
2 154
 
7.0%
) 150
 
6.8%
( 149
 
6.8%
, 121
 
5.5%
3 119
 
5.4%
0 102
 
4.6%
4 79
 
3.6%
5 75
 
3.4%
Other values (14) 207
 
9.4%
Hangul
ValueCountFrequency (%)
동 234
 
7.0%
양 197
 
5.9%
로 189
 
5.7%
천 188
 
5.7%
서 187
 
5.6%
시 186
 
5.6%
구 184
 
5.5%
울 183
 
5.5%
별 183
 
5.5%
특 182
 
5.5%
Other values (143) 1411
42.4%
None
ValueCountFrequency (%)
　 1
100.0%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct50
Distinct (%)34.0%
Missing37
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean53.367347
Minimum0
Maximum2500
Zeros3
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T02:20:47.860606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q19
median24
Q335.5
95-th percentile100
Maximum2500
Range2500
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation219.07533
Coefficient of variation (CV)4.1050445
Kurtosis109.58267
Mean53.367347
Median Absolute Deviation (MAD)15
Skewness10.095908
Sum7845
Variance47994.001
MonotonicityNot monotonic
2024-05-11T02:20:48.307269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 13
 
7.1%
9 11
 
6.0%
4 8
 
4.3%
35 8
 
4.3%
19 7
 
3.8%
25 7
 
3.8%
29 7
 
3.8%
24 7
 
3.8%
20 7
 
3.8%
50 6
 
3.3%
Other values (40) 66
35.9%
(Missing) 37
20.1%
ValueCountFrequency (%)
0 3
 
1.6%
3 1
 
0.5%
4 8
4.3%
5 1
 
0.5%
6 2
 
1.1%
7 13
7.1%
8 3
 
1.6%
9 11
6.0%
10 5
 
2.7%
12 1
 
0.5%
ValueCountFrequency (%)
2500 1
 
0.5%
898 1
 
0.5%
407 1
 
0.5%
120 1
 
0.5%
119 2
1.1%
106 1
 
0.5%
100 3
1.6%
80 1
 
0.5%
77 1
 
0.5%
75 1
 
0.5%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct58
Distinct (%)43.3%
Missing50
Missing (%)27.2%
Infinite0
Infinite (%)0.0%
Mean144.52239
Minimum0
Maximum6704
Zeros2
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T02:20:48.742504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q110
median23
Q335
95-th percentile402.5
Maximum6704
Range6704
Interquartile range (IQR)25

Descriptive statistics

Standard deviation771.94934
Coefficient of variation (CV)5.3413824
Kurtosis62.286333
Mean144.52239
Median Absolute Deviation (MAD)13
Skewness7.8563289
Sum19366
Variance595905.79
MonotonicityNot monotonic
2024-05-11T02:20:49.191021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 7
 
3.8%
21 6
 
3.3%
20 6
 
3.3%
6 5
 
2.7%
4 5
 
2.7%
24 5
 
2.7%
23 4
 
2.2%
27 4
 
2.2%
7 4
 
2.2%
18 4
 
2.2%
Other values (48) 84
45.7%
(Missing) 50
27.2%
ValueCountFrequency (%)
0 2
 
1.1%
1 1
 
0.5%
2 1
 
0.5%
3 4
2.2%
4 5
2.7%
5 2
 
1.1%
6 5
2.7%
7 4
2.2%
8 2
 
1.1%
9 7
3.8%
ValueCountFrequency (%)
6704 1
0.5%
5902 1
0.5%
710 2
1.1%
690 1
0.5%
520 1
0.5%
500 1
0.5%
350 1
0.5%
120 1
0.5%
114 1
0.5%
100 2
1.1%

전화번호
Text

Distinct170
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T02:20:49.781881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.070652
Min length9

Characters and Unicode

Total characters2037
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)85.9%

Sample

1st row02-2651-0809
2nd row02-2642-8267
3rd row02-2646-3898
4th row02-2646-3893
5th row02-2649-8815
ValueCountFrequency (%)
0226079560 4
 
2.2%
0226538678 2
 
1.1%
070-4306-6712 2
 
1.1%
02-2692-2448 2
 
1.1%
02-2690-8762 2
 
1.1%
0236623245 2
 
1.1%
0220657105 2
 
1.1%
02-2643-7222 2
 
1.1%
02-2651-2332 2
 
1.1%
0269566252 2
 
1.1%
Other values (160) 162
88.0%
2024-05-11T02:20:50.812457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 422
20.7%
0 372
18.3%
6 262
12.9%
- 181
8.9%
7 132
 
6.5%
9 130
 
6.4%
3 123
 
6.0%
1 116
 
5.7%
5 110
 
5.4%
4 105
 
5.2%
Other values (2) 84
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1855
91.1%
Dash Punctuation 181
 
8.9%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 422
22.7%
0 372
20.1%
6 262
14.1%
7 132
 
7.1%
9 130
 
7.0%
3 123
 
6.6%
1 116
 
6.3%
5 110
 
5.9%
4 105
 
5.7%
8 83
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2037
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 422
20.7%
0 372
18.3%
6 262
12.9%
- 181
8.9%
7 132
 
6.5%
9 130
 
6.4%
3 123
 
6.0%
1 116
 
5.7%
5 110
 
5.4%
4 105
 
5.2%
Other values (2) 84
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2037
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 422
20.7%
0 372
18.3%
6 262
12.9%
- 181
8.9%
7 132
 
6.5%
9 130
 
6.4%
3 123
 
6.0%
1 116
 
5.7%
5 110
 
5.4%
4 105
 
5.2%
Other values (2) 84
 
4.1%

우편번호
Real number (ℝ)

Distinct100
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21113.918
Minimum7901
Maximum158856
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-05-11T02:20:51.221084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7901
5-th percentile7911
Q17939.75
median8014.5
Q38061
95-th percentile158600
Maximum158856
Range150955
Interquartile range (IQR)121.25

Descriptive statistics

Standard deviation42564.554
Coefficient of variation (CV)2.0159476
Kurtosis6.8109154
Mean21113.918
Median Absolute Deviation (MAD)67
Skewness2.9557808
Sum3884961
Variance1.8117413 × 109
MonotonicityNot monotonic
2024-05-11T02:20:51.890987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
158600 8
 
4.3%
7944 5
 
2.7%
8015 5
 
2.7%
8028 5
 
2.7%
7950 4
 
2.2%
7923 4
 
2.2%
7925 4
 
2.2%
8061 4
 
2.2%
7930 3
 
1.6%
7914 3
 
1.6%
Other values (90) 139
75.5%
ValueCountFrequency (%)
7901 1
 
0.5%
7904 1
 
0.5%
7905 2
1.1%
7909 3
1.6%
7910 2
1.1%
7911 3
1.6%
7912 3
1.6%
7913 1
 
0.5%
7914 3
1.6%
7916 1
 
0.5%
ValueCountFrequency (%)
158856 1
 
0.5%
158846 1
 
0.5%
158828 1
 
0.5%
158827 1
 
0.5%
158822 1
 
0.5%
158765 1
 
0.5%
158764 1
 
0.5%
158600 8
4.3%
158077 1
 
0.5%
10040 2
 
1.1%

Interactions

2024-05-11T02:20:31.426804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:29.359671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:30.514824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:31.679401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:29.694544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:30.849982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:32.027382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:30.088860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:20:31.149492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:20:52.190538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시설종류상세명(시설종류)정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0001.0000.9570.9870.293
시설종류상세명(시설종류)1.0001.0000.9190.8980.295
정원(수용인원)0.9570.9191.0000.4820.000
현인원0.9870.8980.4821.0000.000
우편번호0.2930.2950.0000.0001.000
2024-05-11T02:20:52.483777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류상세명(시설종류)시설종류명(시설유형)
시설종류상세명(시설종류)1.0000.963
시설종류명(시설유형)0.9631.000
2024-05-11T02:20:52.741001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원(수용인원)현인원우편번호시설종류명(시설유형)시설종류상세명(시설종류)
정원(수용인원)1.0000.7310.0650.7000.753
현인원0.7311.0000.1020.8580.726
우편번호0.0650.1021.0000.2140.222
시설종류명(시설유형)0.7000.8580.2141.0000.963
시설종류상세명(시설종류)0.7530.7260.2220.9631.000

Missing values

2024-05-11T02:20:32.677799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:20:33.613479image/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.
2024-05-11T02:20:34.249993image/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
0목동종합사회복지관병설목동노인복지센터A0707(노인) 재가노인복지시설재가노인복지시설자치구유영덕1147000000양천구서울특별시 양천구 목동중앙북로8길 104목동종합사회복지관 2층242402-2651-08097949
1두엄자리A0765(노인) 노인요양시설노인의료복지시설자치구김명화1147000000양천구서울특별시 양천구 목동중앙남로16다길 6-13 (목동)222102-2642-82677952
2어르신이행복한세상주야간보호센터A1294(노인) 재가노인복지시설재가노인복지시설자치구박병택1147000000양천구서울특별시 양천구 신월로 338원빌딩 2층9702-2646-38988086
3어르신이행복한세상요양센터01호A1328(노인) 노인요양공동생활가정노인의료복지시설자치구박병택1147000000양천구서울특별시 양천구 신월로 338원빌딩 2층9802-2646-38938086
4양천어르신종합복지관A1732(노인) 노인복지관노인여가복지시설자치구한승호1147000000양천구서울특별시 양천구 목동로3길 106서울특별시 양천구 목동로3길106 (신정동)<NA><NA>02-2649-88158098
5한빛데이케어센터A1963(노인) 재가노인복지시설재가노인복지시설자치구권구택1147000000양천구서울특별시 양천구 신월로11길 16(신월4동)282702-2698-99778031
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