Overview

Dataset statistics

Number of variables13
Number of observations114
Missing cells22
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory109.2 B

Variable types

Text5
Categorical4
Numeric4

Dataset

Description시설명,시설코드,시설종류명(시설유형),시설종류상세명(시설종류),자치구(시)구분,시설장명,시군구코드,시군구명,시설주소,정원(수용인원),현인원,전화번호,우편번호
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20434/S/1/datasetView.do

Alerts

시설종류상세명(시설종류) has constant value ""Constant
자치구(시)구분 has constant value ""Constant
시군구코드 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
정원(수용인원) is highly overall correlated with 현인원 and 1 other fieldsHigh correlation
현인원 is highly overall correlated with 정원(수용인원)High correlation
우편번호 is highly overall correlated with 시군구코드High correlation
시설종류명(시설유형) is highly overall correlated with 정원(수용인원)High correlation
시군구명 is highly overall correlated with 시군구코드High correlation
정원(수용인원) has 5 (4.4%) missing valuesMissing
현인원 has 16 (14.0%) missing valuesMissing
시설코드 has unique valuesUnique
정원(수용인원) has 2 (1.8%) zerosZeros

Reproduction

Analysis started2024-05-11 06:18:22.430063
Analysis finished2024-05-11 06:18:27.164075
Duration4.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-11T15:18:27.508907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length5.7017544
Min length2

Characters and Unicode

Total characters650
Distinct characters200
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

Unique110 ?
Unique (%)96.5%

Sample

1st row한마음의집
2nd row여울목
3rd row관악좋은집
4th row꿈꾸는집
5th row새로돋는집
ValueCountFrequency (%)
서초아이존 2
 
1.6%
돌봄사랑채 2
 
1.6%
행복한하루 2
 
1.6%
금천구정신건강복지센터 1
 
0.8%
맑은샘 1
 
0.8%
위드유사회복귀시설 1
 
0.8%
센터 1
 
0.8%
회복 1
 
0.8%
알코올 1
 
0.8%
까리따스 1
 
0.8%
Other values (109) 109
89.3%
2024-05-11T15:18:28.238932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 15
 
2.3%
터 15
 
2.3%
집 14
 
2.2%
이 13
 
2.0%
서 11
 
1.7%
정 11
 
1.7%
하 11
 
1.7%
센 11
 
1.7%
아 11
 
1.7%
스 10
 
1.5%
Other values (190) 528
81.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
96.5%
Space Separator 8
 
1.2%
Decimal Number 7
 
1.1%
Open Punctuation 4
 
0.6%
Close Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 15
 
2.4%
터 15
 
2.4%
집 14
 
2.2%
이 13
 
2.1%
서 11
 
1.8%
정 11
 
1.8%
하 11
 
1.8%
센 11
 
1.8%
아 11
 
1.8%
스 10
 
1.6%
Other values (183) 505
80.5%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
2 2
28.6%
3 2
28.6%
4 1
14.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
96.5%
Common 23
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 15
 
2.4%
터 15
 
2.4%
집 14
 
2.2%
이 13
 
2.1%
서 11
 
1.8%
정 11
 
1.8%
하 11
 
1.8%
센 11
 
1.8%
아 11
 
1.8%
스 10
 
1.6%
Other values (183) 505
80.5%
Common
ValueCountFrequency (%)
8
34.8%
( 4
17.4%
) 4
17.4%
1 2
 
8.7%
2 2
 
8.7%
3 2
 
8.7%
4 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
96.5%
ASCII 23
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 15
 
2.4%
터 15
 
2.4%
집 14
 
2.2%
이 13
 
2.1%
서 11
 
1.8%
정 11
 
1.8%
하 11
 
1.8%
센 11
 
1.8%
아 11
 
1.8%
스 10
 
1.6%
Other values (183) 505
80.5%
ASCII
ValueCountFrequency (%)
8
34.8%
( 4
17.4%
) 4
17.4%
1 2
 
8.7%
2 2
 
8.7%
3 2
 
8.7%
4 1
 
4.3%

시설코드
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-11T15:18:28.797757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.0175439
Min length5

Characters and Unicode

Total characters572
Distinct characters12
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

Unique114 ?
Unique (%)100.0%

Sample

1st rowF0040
2nd rowF0045
3rd rowF0046
4th rowF0091
5th rowF0092
ValueCountFrequency (%)
f0040 1
 
0.9%
f0568 1
 
0.9%
f0563 1
 
0.9%
f0560 1
 
0.9%
f0556 1
 
0.9%
f0554 1
 
0.9%
f0551 1
 
0.9%
f0546 1
 
0.9%
f0540 1
 
0.9%
f0532 1
 
0.9%
Other values (104) 104
91.2%
2024-05-11T15:18:29.741833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 154
26.9%
F 112
19.6%
5 51
 
8.9%
4 44
 
7.7%
2 41
 
7.2%
6 39
 
6.8%
3 38
 
6.6%
9 31
 
5.4%
1 30
 
5.2%
7 17
 
3.0%
Other values (2) 15
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 458
80.1%
Uppercase Letter 114
 
19.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 154
33.6%
5 51
 
11.1%
4 44
 
9.6%
2 41
 
9.0%
6 39
 
8.5%
3 38
 
8.3%
9 31
 
6.8%
1 30
 
6.6%
7 17
 
3.7%
8 13
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
F 112
98.2%
Z 2
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 458
80.1%
Latin 114
 
19.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 154
33.6%
5 51
 
11.1%
4 44
 
9.6%
2 41
 
9.0%
6 39
 
8.5%
3 38
 
8.3%
9 31
 
6.8%
1 30
 
6.6%
7 17
 
3.7%
8 13
 
2.8%
Latin
ValueCountFrequency (%)
F 112
98.2%
Z 2
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 154
26.9%
F 112
19.6%
5 51
 
8.9%
4 44
 
7.7%
2 41
 
7.2%
6 39
 
6.8%
3 38
 
6.6%
9 31
 
5.4%
1 30
 
5.2%
7 17
 
3.0%
Other values (2) 15
 
2.6%

시설종류명(시설유형)
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
(정신보건) 재활훈련시설-공동생활가정
46 
(정신보건) 재활훈련시설-주간재활시설
30 
(정신보건) 생활시설
14 
(정신보건) 재활훈련시설-직업재활시설
7 
(정신보건) 재활훈련시설-아동?청소년정신건강지원시설
5 
Other values (5)
12 

Length

Max length28
Median length20
Mean length18.964912
Min length11

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row(정신보건) 재활훈련시설-공동생활가정
2nd row(정신보건) 재활훈련시설-공동생활가정
3rd row(정신보건) 생활시설
4th row(정신보건) 재활훈련시설-공동생활가정
5th row(정신보건) 생활시설

Common Values

ValueCountFrequency (%)
(정신보건) 재활훈련시설-공동생활가정 46
40.4%
(정신보건) 재활훈련시설-주간재활시설 30
26.3%
(정신보건) 생활시설 14
 
12.3%
(정신보건) 재활훈련시설-직업재활시설 7
 
6.1%
(정신보건) 재활훈련시설-아동?청소년정신건강지원시설 5
 
4.4%
(정신보건) 중독자재활시설 4
 
3.5%
(정신보건) 재활훈련시설-지역사회전환시설 4
 
3.5%
(정신보건) 종합시설 2
 
1.8%
(정신보건) 정신질환자주거시설(구) 1
 
0.9%
(정신보건) 정신질환자지역사회재활시설(구) 1
 
0.9%

Length

2024-05-11T15:18:30.072859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:30.324904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정신보건 114
50.0%
재활훈련시설-공동생활가정 46
20.2%
재활훈련시설-주간재활시설 30
 
13.2%
생활시설 14
 
6.1%
재활훈련시설-직업재활시설 7
 
3.1%
재활훈련시설-아동?청소년정신건강지원시설 5
 
2.2%
중독자재활시설 4
 
1.8%
재활훈련시설-지역사회전환시설 4
 
1.8%
종합시설 2
 
0.9%
정신질환자주거시설(구 1
 
0.4%

시설종류상세명(시설종류)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
정신재활시설
114 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정신재활시설 114
100.0%

Length

2024-05-11T15:18:30.598228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:30.761362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정신재활시설 114
100.0%

자치구(시)구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
자치구
114 

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 114
100.0%

Length

2024-05-11T15:18:30.957815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:18:31.144093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자치구 114
100.0%

시설장명
Text

Distinct107
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-11T15:18:31.612772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3
Min length2

Characters and Unicode

Total characters342
Distinct characters100
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

Unique101 ?
Unique (%)88.6%

Sample

1st row최동표
2nd row김시현
3rd row임영희
4th row정명희
5th row김범곤
ValueCountFrequency (%)
이송자 3
 
2.6%
우명숙 2
 
1.8%
최성남 2
 
1.8%
김미희 2
 
1.8%
심종온 2
 
1.8%
이현주 2
 
1.8%
원유수 1
 
0.9%
박정현 1
 
0.9%
옥정 1
 
0.9%
박부진 1
 
0.9%
Other values (97) 97
85.1%
2024-05-11T15:18:32.458654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 28
 
8.2%
이 21
 
6.1%
정 18
 
5.3%
현 13
 
3.8%
숙 11
 
3.2%
미 11
 
3.2%
영 9
 
2.6%
박 9
 
2.6%
은 8
 
2.3%
수 8
 
2.3%
Other values (90) 206
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 28
 
8.2%
이 21
 
6.1%
정 18
 
5.3%
현 13
 
3.8%
숙 11
 
3.2%
미 11
 
3.2%
영 9
 
2.6%
박 9
 
2.6%
은 8
 
2.3%
수 8
 
2.3%
Other values (90) 206
60.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 28
 
8.2%
이 21
 
6.1%
정 18
 
5.3%
현 13
 
3.8%
숙 11
 
3.2%
미 11
 
3.2%
영 9
 
2.6%
박 9
 
2.6%
은 8
 
2.3%
수 8
 
2.3%
Other values (90) 206
60.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 28
 
8.2%
이 21
 
6.1%
정 18
 
5.3%
현 13
 
3.8%
숙 11
 
3.2%
미 11
 
3.2%
영 9
 
2.6%
박 9
 
2.6%
은 8
 
2.3%
수 8
 
2.3%
Other values (90) 206
60.2%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1412456 × 109
Minimum1.1 × 109
Maximum1.174 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T15:18:32.687824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1 × 109
5-th percentile1.117 × 109
Q11.129 × 109
median1.141 × 109
Q31.153 × 109
95-th percentile1.171 × 109
Maximum1.174 × 109
Range74000000
Interquartile range (IQR)24000000

Descriptive statistics

Standard deviation16858763
Coefficient of variation (CV)0.014772248
Kurtosis-0.70658604
Mean1.1412456 × 109
Median Absolute Deviation (MAD)12000000
Skewness0.11277322
Sum1.30102 × 1011
Variance2.842179 × 1014
MonotonicityNot monotonic
2024-05-11T15:18:32.945776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1132000000 11
 
9.6%
1121500000 9
 
7.9%
1147000000 8
 
7.0%
1141000000 7
 
6.1%
1150000000 7
 
6.1%
1138000000 7
 
6.1%
1153000000 6
 
5.3%
1126000000 6
 
5.3%
1162000000 6
 
5.3%
1171000000 4
 
3.5%
Other values (16) 43
37.7%
ValueCountFrequency (%)
1100000000 1
 
0.9%
1111000000 3
 
2.6%
1114000000 1
 
0.9%
1117000000 2
 
1.8%
1120000000 2
 
1.8%
1121500000 9
7.9%
1123000000 4
3.5%
1126000000 6
5.3%
1129000000 3
 
2.6%
1130500000 2
 
1.8%
ValueCountFrequency (%)
1174000000 4
3.5%
1171000000 4
3.5%
1168000000 1
 
0.9%
1165000000 4
3.5%
1162000000 6
5.3%
1159000000 1
 
0.9%
1156000000 4
3.5%
1154500000 3
2.6%
1153000000 6
5.3%
1150000000 7
6.1%

시군구명
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
도봉구
11 
광진구
9 
양천구
8 
서대문구
 
7
강서구
 
7
Other values (21)
72 

Length

Max length5
Median length3
Mean length3.1403509
Min length2

Unique

Unique4 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
도봉구 11
 
9.6%
광진구 9
 
7.9%
양천구 8
 
7.0%
서대문구 7
 
6.1%
강서구 7
 
6.1%
은평구 7
 
6.1%
구로구 6
 
5.3%
중랑구 6
 
5.3%
관악구 6
 
5.3%
서초구 4
 
3.5%
Other values (16) 43
37.7%

Length

2024-05-11T15:18:33.625830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도봉구 11
 
9.6%
광진구 9
 
7.9%
양천구 8
 
7.0%
서대문구 7
 
6.1%
강서구 7
 
6.1%
은평구 7
 
6.1%
구로구 6
 
5.3%
중랑구 6
 
5.3%
관악구 6
 
5.3%
영등포구 4
 
3.5%
Other values (16) 43
37.7%

시설주소
Text

Distinct112
Distinct (%)99.1%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
2024-05-11T15:18:34.082723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length40
Mean length29.59292
Min length14

Characters and Unicode

Total characters3344
Distinct characters209
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

Unique111 ?
Unique (%)98.2%

Sample

1st row서울특별시 서대문구 연희로39다길 201층
2nd row서울특별시 강서구 화곡로13길 66-28301호 (화곡동)
3rd row서울특별시 관악구 법원단지32길 5-0신림동, 201호
4th row서울특별시 관악구 당곡6길 65201호
5th row서울특별시 관악구 대학18길 41401호 (신림동, 현산푸른숲빌)
ValueCountFrequency (%)
서울특별시 113
 
19.8%
도봉구 11
 
1.9%
광진구 9
 
1.6%
4층 8
 
1.4%
은평구 7
 
1.2%
양천구 7
 
1.2%
서대문구 7
 
1.2%
강서구 7
 
1.2%
중랑구 6
 
1.1%
관악구 6
 
1.1%
Other values (311) 390
68.3%
2024-05-11T15:18:34.918408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
459
 
13.7%
1 149
 
4.5%
서 137
 
4.1%
구 124
 
3.7%
시 122
 
3.6%
2 121
 
3.6%
로 114
 
3.4%
특 114
 
3.4%
별 114
 
3.4%
울 114
 
3.4%
Other values (199) 1776
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1925
57.6%
Decimal Number 714
 
21.4%
Space Separator 459
 
13.7%
Close Punctuation 70
 
2.1%
Open Punctuation 70
 
2.1%
Dash Punctuation 51
 
1.5%
Other Punctuation 48
 
1.4%
Uppercase Letter 6
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 137
 
7.1%
구 124
 
6.4%
시 122
 
6.3%
로 114
 
5.9%
특 114
 
5.9%
별 114
 
5.9%
울 114
 
5.9%
동 100
 
5.2%
길 90
 
4.7%
호 52
 
2.7%
Other values (179) 844
43.8%
Decimal Number
ValueCountFrequency (%)
1 149
20.9%
2 121
16.9%
3 100
14.0%
0 92
12.9%
4 70
9.8%
5 48
 
6.7%
6 45
 
6.3%
8 33
 
4.6%
9 29
 
4.1%
7 27
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
B 2
33.3%
G 2
33.3%
Other Punctuation
ValueCountFrequency (%)
, 39
81.2%
/ 9
 
18.8%
Space Separator
ValueCountFrequency (%)
459
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1925
57.6%
Common 1412
42.2%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 137
 
7.1%
구 124
 
6.4%
시 122
 
6.3%
로 114
 
5.9%
특 114
 
5.9%
별 114
 
5.9%
울 114
 
5.9%
동 100
 
5.2%
길 90
 
4.7%
호 52
 
2.7%
Other values (179) 844
43.8%
Common
ValueCountFrequency (%)
459
32.5%
1 149
 
10.6%
2 121
 
8.6%
3 100
 
7.1%
0 92
 
6.5%
) 70
 
5.0%
( 70
 
5.0%
4 70
 
5.0%
- 51
 
3.6%
5 48
 
3.4%
Other values (6) 182
 
12.9%
Latin
ValueCountFrequency (%)
L 2
28.6%
B 2
28.6%
G 2
28.6%
Ⅰ 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1925
57.6%
ASCII 1418
42.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
459
32.4%
1 149
 
10.5%
2 121
 
8.5%
3 100
 
7.1%
0 92
 
6.5%
) 70
 
4.9%
( 70
 
4.9%
4 70
 
4.9%
- 51
 
3.6%
5 48
 
3.4%
Other values (9) 188
13.3%
Hangul
ValueCountFrequency (%)
서 137
 
7.1%
구 124
 
6.4%
시 122
 
6.3%
로 114
 
5.9%
특 114
 
5.9%
별 114
 
5.9%
울 114
 
5.9%
동 100
 
5.2%
길 90
 
4.7%
호 52
 
2.7%
Other values (179) 844
43.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

정원(수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct25
Distinct (%)22.9%
Missing5
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean18.614679
Minimum0
Maximum150
Zeros2
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T15:18:35.140316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q16
median8
Q325
95-th percentile50
Maximum150
Range150
Interquartile range (IQR)19

Descriptive statistics

Standard deviation19.819981
Coefficient of variation (CV)1.0647501
Kurtosis16.782875
Mean18.614679
Median Absolute Deviation (MAD)4
Skewness3.1094885
Sum2029
Variance392.83163
MonotonicityNot monotonic
2024-05-11T15:18:35.375827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
8 15
13.2%
5 12
10.5%
7 11
9.6%
25 11
9.6%
6 10
8.8%
4 7
 
6.1%
50 6
 
5.3%
30 5
 
4.4%
40 5
 
4.4%
23 3
 
2.6%
Other values (15) 24
21.1%
(Missing) 5
 
4.4%
ValueCountFrequency (%)
0 2
 
1.8%
2 1
 
0.9%
3 1
 
0.9%
4 7
6.1%
5 12
10.5%
6 10
8.8%
7 11
9.6%
8 15
13.2%
9 2
 
1.8%
10 1
 
0.9%
ValueCountFrequency (%)
150 1
 
0.9%
60 1
 
0.9%
55 1
 
0.9%
53 1
 
0.9%
50 6
5.3%
40 5
4.4%
39 1
 
0.9%
35 2
 
1.8%
32 1
 
0.9%
31 3
2.6%

현인원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct31
Distinct (%)31.6%
Missing16
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean19.142857
Minimum0
Maximum168
Zeros1
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T15:18:35.585716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q15
median7
Q330
95-th percentile53
Maximum168
Range168
Interquartile range (IQR)25

Descriptive statistics

Standard deviation22.42973
Coefficient of variation (CV)1.1717023
Kurtosis18.975591
Mean19.142857
Median Absolute Deviation (MAD)4
Skewness3.3826646
Sum1876
Variance503.09278
MonotonicityNot monotonic
2024-05-11T15:18:35.877779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5 16
14.0%
7 14
12.3%
4 8
 
7.0%
3 7
 
6.1%
6 5
 
4.4%
25 5
 
4.4%
23 4
 
3.5%
8 4
 
3.5%
30 4
 
3.5%
31 3
 
2.6%
Other values (21) 28
24.6%
(Missing) 16
14.0%
ValueCountFrequency (%)
0 1
 
0.9%
3 7
6.1%
4 8
7.0%
5 16
14.0%
6 5
 
4.4%
7 14
12.3%
8 4
 
3.5%
9 1
 
0.9%
11 1
 
0.9%
18 1
 
0.9%
ValueCountFrequency (%)
168 1
 
0.9%
64 1
 
0.9%
57 1
 
0.9%
55 1
 
0.9%
53 3
2.6%
51 1
 
0.9%
50 2
1.8%
43 1
 
0.9%
41 2
1.8%
40 2
1.8%

전화번호
Text

Distinct110
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-05-11T15:18:36.264790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.219298
Min length9

Characters and Unicode

Total characters1279
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

Unique106 ?
Unique (%)93.0%

Sample

1st row02-391-2504
2nd row02-2605-2176
3rd row02-858-1019
4th row02-877-9974
5th row02-872-9961
ValueCountFrequency (%)
0234099444 2
 
1.8%
02-926-2172 2
 
1.8%
07086707026 2
 
1.8%
025352940 2
 
1.8%
02-6012-7963 1
 
0.9%
029394200 1
 
0.9%
02-3663-2035 1
 
0.9%
02-997-0444 1
 
0.9%
02-6739-3500 1
 
0.9%
028779984 1
 
0.9%
Other values (100) 100
87.7%
2024-05-11T15:18:36.918331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 210
16.4%
2 206
16.1%
- 180
14.1%
4 108
8.4%
9 100
7.8%
7 99
7.7%
3 98
7.7%
6 76
 
5.9%
1 73
 
5.7%
5 70
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1099
85.9%
Dash Punctuation 180
 
14.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 210
19.1%
2 206
18.7%
4 108
9.8%
9 100
9.1%
7 99
9.0%
3 98
8.9%
6 76
 
6.9%
1 73
 
6.6%
5 70
 
6.4%
8 59
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1279
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 210
16.4%
2 206
16.1%
- 180
14.1%
4 108
8.4%
9 100
7.8%
7 99
7.7%
3 98
7.7%
6 76
 
5.9%
1 73
 
5.7%
5 70
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1279
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 210
16.4%
2 206
16.1%
- 180
14.1%
4 108
8.4%
9 100
7.8%
7 99
7.7%
3 98
7.7%
6 76
 
5.9%
1 73
 
5.7%
5 70
 
5.5%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17087.474
Minimum1047
Maximum158828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T15:18:37.206960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1047
5-th percentile1302
Q12887.5
median4961.5
Q37862
95-th percentile143885.4
Maximum158828
Range157781
Interquartile range (IQR)4974.5

Descriptive statistics

Standard deviation40047.452
Coefficient of variation (CV)2.3436731
Kurtosis7.2379568
Mean17087.474
Median Absolute Deviation (MAD)2684
Skewness2.991899
Sum1947972
Variance1.6037984 × 109
MonotonicityNot monotonic
2024-05-11T15:18:37.477966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1302 5
 
4.4%
5072 3
 
2.6%
3668 2
 
1.8%
6572 2
 
1.8%
1314 2
 
1.8%
3337 1
 
0.9%
1047 1
 
0.9%
8303 1
 
0.9%
8837 1
 
0.9%
158600 1
 
0.9%
Other values (95) 95
83.3%
ValueCountFrequency (%)
1047 1
 
0.9%
1132 1
 
0.9%
1302 5
4.4%
1310 1
 
0.9%
1314 2
 
1.8%
1352 1
 
0.9%
1377 1
 
0.9%
1391 1
 
0.9%
1609 1
 
0.9%
1668 1
 
0.9%
ValueCountFrequency (%)
158828 1
0.9%
158822 1
0.9%
158600 1
0.9%
152650 1
0.9%
150650 1
0.9%
143888 1
0.9%
143884 1
0.9%
138600 1
0.9%
130851 1
0.9%
110032 1
0.9%

Interactions

2024-05-11T15:18:25.699229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:23.378242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:24.160858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:24.948259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:25.862313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:23.564878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:24.371121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:25.147986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:26.027702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:23.754231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:24.564759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:25.384998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:26.199601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:23.945682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:24.753559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:18:25.531838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:18:37.659466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류명(시설유형)시군구코드시군구명정원(수용인원)현인원우편번호
시설종류명(시설유형)1.0000.3440.6790.7050.6710.324
시군구코드0.3441.0001.0000.2150.0000.418
시군구명0.6791.0001.0000.5860.3670.431
정원(수용인원)0.7050.2150.5861.0000.8840.102
현인원0.6710.0000.3670.8841.0000.000
우편번호0.3240.4180.4310.1020.0001.000
2024-05-11T15:18:37.846277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명시설종류명(시설유형)
시군구명1.0000.292
시설종류명(시설유형)0.2921.000
2024-05-11T15:18:38.004992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드정원(수용인원)현인원우편번호시설종류명(시설유형)시군구명
시군구코드1.0000.0780.1430.5250.1310.920
정원(수용인원)0.0781.0000.8830.0580.5070.192
현인원0.1430.8831.0000.0940.4870.164
우편번호0.5250.0580.0941.0000.1940.214
시설종류명(시설유형)0.1310.5070.4870.1941.0000.292
시군구명0.9200.1920.1640.2140.2921.000

Missing values

2024-05-11T15:18:26.463552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:18:26.806409image/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.
2024-05-11T15:18:27.047632image/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
0한마음의집F0040(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구최동표1141000000서대문구서울특별시 서대문구 연희로39다길 201층9802-391-25043651
1여울목F0045(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구김시현1150000000강서구서울특별시 강서구 화곡로13길 66-28301호 (화곡동)4402-2605-21767710
2관악좋은집F0046(정신보건) 생활시설정신재활시설자치구임영희1162000000관악구서울특별시 관악구 법원단지32길 5-0신림동, 201호5402-858-10198853
3꿈꾸는집F0091(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구정명희1162000000관악구서울특별시 관악구 당곡6길 65201호5502-877-99748709
4새로돋는집F0092(정신보건) 생활시설정신재활시설자치구김범곤1162000000관악구서울특별시 관악구 대학18길 41401호 (신림동, 현산푸른숲빌)4302-872-99618824
5아름드리(여성주거시설)F0098(정신보건) 생활시설정신재활시설자치구황미리1147000000양천구서울특별시 양천구 남부순환로59길 16-1 201호7702-2696-7725158828
6대길푸른초장F0112(정신보건) 재활훈련시설-주간재활시설정신재활시설자치구우상원1156000000영등포구서울특별시 영등포구 영등포로84길 24-1463702-835-80117356
7한마음세상F0135(정신보건) 종합시설정신재활시설자치구이현주1150000000강서구서울특별시 강서구 초록마을로32길 33-18505302-2699-73247730
8열린세상(남성주거시설)F0137(정신보건) 생활시설정신재활시설자치구우성필1147000000양천구서울특별시 양천구 남부순환로 450301호10702-2693-73287916
9강서그룹홈F0138(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구장재선1150000000강서구서울특별시 강서구 초록마을로16길 20201호 (화곡동)9902-2699-73287723
시설명시설코드시설종류명(시설유형)시설종류상세명(시설종류)자치구(시)구분시설장명시군구코드시군구명시설주소정원(수용인원)현인원전화번호우편번호
104그라따F0650(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구박정숙1132000000도봉구서울특별시 도봉구 도봉로139길 42-6302호 (쌍문동, 삼성쉐르빌)4402-6369-17161391
105나눔터F0665(정신보건) 재활훈련시설-주간재활시설정신재활시설자치구김대겸1129000000성북구서울특별시 성북구 한천로76다길 46, 5층 (석관동)20302-926-21722781
106한울림F0670(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구황현각1129000000성북구서울특별시 성북구 보국문로6길 5-10, 제B동 2층 202호 (정릉동, 정릉하우드 B동)4302-942-10372718
107중구아이존F0692(정신보건) 재활훈련시설-아동?청소년정신건강지원시설정신재활시설자치구권윤정1114000000중구서울특별시 중구 서소문로6길16 (중림동, 중림종합복지센터 3층)<NA><NA>02203876504506
108새빛F0699(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구우명숙1138000000은평구서울특별시 은평구 증산로3길 8-24 (증산동)<NA><NA>0271933693500
109서초아이존F0710(정신보건) 재활훈련시설-아동?청소년정신건강지원시설정신재활시설자치구심종온1165000000서초구서울특별시 서초구 방배로 173 (방배동) 방배열린문화센터 지하1층<NA><NA>0253529406572
110서울시 정신건강통합센터F0712(정신보건) 종합시설정신재활시설자치구손주영1171000000송파구서울특별시 송파구 백제고분로 449, 1,3,4층 (방이동)<NA><NA>0242322305550
111행복한하루F0722(정신보건) 재활훈련시설-공동생활가정정신재활시설자치구최기복1132000000도봉구서울특별시 도봉구 시루봉로15라길 7-7 (방학동) 301호6<NA>02349231591314
112금천구정신건강복지센터Z5497(정신보건) 정신질환자지역사회재활시설(구)정신재활시설자치구김수완1154500000금천구서울특별시 금천구 시흥대로123길 115층0<NA>02-3281-93148523
113서울시정신보건센터Z5500(정신보건) 재활훈련시설-주간재활시설정신재활시설자치구이명수1100000000서울특별시서울특별시 강남구 봉은사로 21길 6(논현동) 5-7층<NA><NA>02-3444-99346122