Overview

Dataset statistics

Number of variables20
Number of observations155
Missing cells155
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory25.4 KiB
Average record size in memory167.9 B

Variable types

Text3
Categorical4
DateTime3
Numeric6
Boolean3
Unsupported1

Dataset

Description파일 다운로드
Author도봉구
URLhttps://data.seoul.go.kr/dataList/OA-13475/F/1/datasetView.do

Alerts

운영시작일자 has constant value ""Constant
운영종료일자 has constant value ""Constant
숙박가능여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리기관전화번호 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
주말운영여부 is highly overall correlated with 시설면적 and 4 other fieldsHigh correlation
법정동명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
야간연장운영여부 is highly overall correlated with 시설면적 and 4 other fieldsHigh correlation
시설면적 is highly overall correlated with 이용가능인원수 and 4 other fieldsHigh correlation
이용가능인원수 is highly overall correlated with 시설면적 and 3 other fieldsHigh correlation
선풍기보유대수 is highly overall correlated with 시설면적 and 3 other fieldsHigh correlation
에어컨보유대수 is highly overall correlated with 쉼터유형구분High correlation
위도 is highly overall correlated with 법정동명 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 법정동명 and 2 other fieldsHigh correlation
쉼터유형구분 is highly overall correlated with 시설면적 and 5 other fieldsHigh correlation
쉼터유형구분 is highly imbalanced (55.7%)Imbalance
특이사항 has 155 (100.0%) missing valuesMissing
특이사항 is an unsupported type, check if it needs cleaning or further analysisUnsupported
선풍기보유대수 has 3 (1.9%) zerosZeros

Reproduction

Analysis started2023-12-11 09:53:52.392341
Analysis finished2023-12-11 09:53:57.940888
Duration5.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

쉼터명
Text

Distinct149
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T18:53:58.142617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.5806452
Min length6

Characters and Unicode

Total characters1330
Distinct characters148
Distinct categories5 ?
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 (%)93.5%

Sample

1st row주공3단지A 경로당
2nd row창2동 주민센터
3rd row창동건영캐스빌A 경로당
4th row장수 경로당
5th row초안 경로당
ValueCountFrequency (%)
경로당 123
40.5%
주민센터 13
 
4.3%
노인복지센터 4
 
1.3%
한신a 3
 
1.0%
극동a 3
 
1.0%
제2경로당 3
 
1.0%
방학3동 2
 
0.7%
방학1동 2
 
0.7%
대상타운현대a 2
 
0.7%
창5동 2
 
0.7%
Other values (135) 147
48.4%
2023-12-11T18:53:58.528794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
 
11.2%
당 136
 
10.2%
경 135
 
10.2%
로 134
 
10.1%
A 93
 
7.0%
동 48
 
3.6%
차 22
 
1.7%
2 19
 
1.4%
주 19
 
1.4%
1 19
 
1.4%
Other values (138) 556
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1022
76.8%
Space Separator 149
 
11.2%
Uppercase Letter 95
 
7.1%
Decimal Number 62
 
4.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 136
 
13.3%
경 135
 
13.2%
로 134
 
13.1%
동 48
 
4.7%
차 22
 
2.2%
주 19
 
1.9%
지 18
 
1.8%
센 17
 
1.7%
터 17
 
1.7%
창 16
 
1.6%
Other values (125) 460
45.0%
Decimal Number
ValueCountFrequency (%)
2 19
30.6%
1 19
30.6%
3 11
17.7%
4 7
 
11.3%
5 3
 
4.8%
9 1
 
1.6%
7 1
 
1.6%
6 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
A 93
97.9%
E 1
 
1.1%
S 1
 
1.1%
Space Separator
ValueCountFrequency (%)
149
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1022
76.8%
Common 213
 
16.0%
Latin 95
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 136
 
13.3%
경 135
 
13.2%
로 134
 
13.1%
동 48
 
4.7%
차 22
 
2.2%
주 19
 
1.9%
지 18
 
1.8%
센 17
 
1.7%
터 17
 
1.7%
창 16
 
1.6%
Other values (125) 460
45.0%
Common
ValueCountFrequency (%)
149
70.0%
2 19
 
8.9%
1 19
 
8.9%
3 11
 
5.2%
4 7
 
3.3%
5 3
 
1.4%
, 2
 
0.9%
9 1
 
0.5%
7 1
 
0.5%
6 1
 
0.5%
Latin
ValueCountFrequency (%)
A 93
97.9%
E 1
 
1.1%
S 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1022
76.8%
ASCII 308
 
23.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
48.4%
A 93
30.2%
2 19
 
6.2%
1 19
 
6.2%
3 11
 
3.6%
4 7
 
2.3%
5 3
 
1.0%
, 2
 
0.6%
9 1
 
0.3%
E 1
 
0.3%
Other values (3) 3
 
1.0%
Hangul
ValueCountFrequency (%)
당 136
 
13.3%
경 135
 
13.2%
로 134
 
13.1%
동 48
 
4.7%
차 22
 
2.2%
주 19
 
1.9%
지 18
 
1.8%
센 17
 
1.7%
터 17
 
1.7%
창 16
 
1.6%
Other values (125) 460
45.0%

법정동명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
방학3동
17 
쌍문1동
15 
창5동
15 
도봉2동
14 
쌍문4동
12 
Other values (9)
82 

Length

Max length4
Median length4
Mean length3.6709677
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row창1동
2nd row창2동
3rd row창2동
4th row창2동
5th row창2동

Common Values

ValueCountFrequency (%)
방학3동 17
11.0%
쌍문1동 15
9.7%
창5동 15
9.7%
도봉2동 14
9.0%
쌍문4동 12
 
7.7%
방학1동 12
 
7.7%
도봉1동 11
 
7.1%
창4동 10
 
6.5%
창1동 9
 
5.8%
창2동 9
 
5.8%
Other values (4) 31
20.0%

Length

2023-12-11T18:53:58.675503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방학3동 17
11.0%
쌍문1동 15
9.7%
창5동 15
9.7%
도봉2동 14
9.0%
쌍문4동 12
 
7.7%
방학1동 12
 
7.7%
도봉1동 11
 
7.1%
창4동 10
 
6.5%
창1동 9
 
5.8%
창2동 9
 
5.8%
Other values (4) 31
20.0%

쉼터유형구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
노인시설
134 
주민센터
 
13
복지회관
 
8

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row노인시설
2nd row주민센터
3rd row노인시설
4th row노인시설
5th row노인시설

Common Values

ValueCountFrequency (%)
노인시설 134
86.5%
주민센터 13
 
8.4%
복지회관 8
 
5.2%

Length

2023-12-11T18:53:58.788519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:53:58.899812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인시설 134
86.5%
주민센터 13
 
8.4%
복지회관 8
 
5.2%

운영시작일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2016-05-01 00:00:00
Maximum2016-05-01 00:00:00
2023-12-11T18:53:58.981003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:59.073892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

운영종료일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2016-09-30 00:00:00
Maximum2016-09-30 00:00:00
2023-12-11T18:53:59.173551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:59.269916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct124
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268.56916
Minimum19
Maximum3582
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T18:53:59.396508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile32.7
Q162.5
median92
Q3185
95-th percentile1304.5
Maximum3582
Range3563
Interquartile range (IQR)122.5

Descriptive statistics

Standard deviation523.80989
Coefficient of variation (CV)1.9503724
Kurtosis19.385125
Mean268.56916
Median Absolute Deviation (MAD)46
Skewness4.1132287
Sum41628.22
Variance274376.8
MonotonicityNot monotonic
2023-12-11T18:53:59.791103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.0 4
 
2.6%
82.0 3
 
1.9%
80.0 3
 
1.9%
165.0 3
 
1.9%
83.0 3
 
1.9%
40.0 2
 
1.3%
470.16 2
 
1.3%
63.0 2
 
1.3%
99.0 2
 
1.3%
185.0 2
 
1.3%
Other values (114) 129
83.2%
ValueCountFrequency (%)
19.0 1
0.6%
20.0 2
1.3%
21.0 1
0.6%
22.68 1
0.6%
22.84 1
0.6%
28.49 1
0.6%
32.0 1
0.6%
33.0 1
0.6%
36.0 2
1.3%
37.0 2
1.3%
ValueCountFrequency (%)
3582.0 1
0.6%
3217.0 1
0.6%
2757.0 1
0.6%
1814.0 1
0.6%
1572.63 1
0.6%
1378.0 1
0.6%
1329.0 2
1.3%
1294.0 1
0.6%
1145.0 1
0.6%
1125.0 1
0.6%

이용가능인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.670968
Minimum9
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T18:53:59.949609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile19.4
Q130
median40
Q356.5
95-th percentile150
Maximum250
Range241
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation46.132659
Coefficient of variation (CV)0.78629449
Kurtosis4.0144342
Mean58.670968
Median Absolute Deviation (MAD)10
Skewness2.0190128
Sum9094
Variance2128.2222
MonotonicityNot monotonic
2023-12-11T18:54:00.134201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
40 38
24.5%
30 29
18.7%
50 27
17.4%
100 13
 
8.4%
150 12
 
7.7%
200 3
 
1.9%
60 3
 
1.9%
90 3
 
1.9%
21 3
 
1.9%
16 2
 
1.3%
Other values (19) 22
14.2%
ValueCountFrequency (%)
9 1
 
0.6%
11 1
 
0.6%
14 1
 
0.6%
15 1
 
0.6%
16 2
1.3%
17 1
 
0.6%
18 1
 
0.6%
20 1
 
0.6%
21 3
1.9%
22 2
1.3%
ValueCountFrequency (%)
250 1
 
0.6%
247 1
 
0.6%
200 3
 
1.9%
150 12
7.7%
100 13
8.4%
90 3
 
1.9%
80 1
 
0.6%
70 1
 
0.6%
60 3
 
1.9%
59 1
 
0.6%

선풍기보유대수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2258065
Minimum0
Maximum33
Zeros3
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T18:54:00.261859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile10.6
Maximum33
Range33
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.6031446
Coefficient of variation (CV)1.0892938
Kurtosis18.395509
Mean4.2258065
Median Absolute Deviation (MAD)1
Skewness3.8537744
Sum655
Variance21.18894
MonotonicityNot monotonic
2023-12-11T18:54:00.394690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2 47
30.3%
3 28
18.1%
4 25
16.1%
1 14
 
9.0%
5 11
 
7.1%
7 6
 
3.9%
10 5
 
3.2%
6 5
 
3.2%
0 3
 
1.9%
8 2
 
1.3%
Other values (9) 9
 
5.8%
ValueCountFrequency (%)
0 3
 
1.9%
1 14
 
9.0%
2 47
30.3%
3 28
18.1%
4 25
16.1%
5 11
 
7.1%
6 5
 
3.2%
7 6
 
3.9%
8 2
 
1.3%
9 1
 
0.6%
ValueCountFrequency (%)
33 1
 
0.6%
30 1
 
0.6%
26 1
 
0.6%
17 1
 
0.6%
16 1
 
0.6%
14 1
 
0.6%
13 1
 
0.6%
12 1
 
0.6%
10 5
3.2%
9 1
 
0.6%

에어컨보유대수
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7935484
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T18:54:00.518567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile6.3
Maximum27
Range26
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.7324425
Coefficient of variation (CV)1.3360937
Kurtosis25.440718
Mean2.7935484
Median Absolute Deviation (MAD)1
Skewness4.7825153
Sum433
Variance13.931127
MonotonicityNot monotonic
2023-12-11T18:54:00.651743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 75
48.4%
1 43
27.7%
3 16
 
10.3%
4 8
 
5.2%
5 3
 
1.9%
6 2
 
1.3%
27 2
 
1.3%
10 1
 
0.6%
15 1
 
0.6%
12 1
 
0.6%
Other values (3) 3
 
1.9%
ValueCountFrequency (%)
1 43
27.7%
2 75
48.4%
3 16
 
10.3%
4 8
 
5.2%
5 3
 
1.9%
6 2
 
1.3%
7 1
 
0.6%
10 1
 
0.6%
12 1
 
0.6%
15 1
 
0.6%
ValueCountFrequency (%)
27 2
 
1.3%
19 1
 
0.6%
16 1
 
0.6%
15 1
 
0.6%
12 1
 
0.6%
10 1
 
0.6%
7 1
 
0.6%
6 2
 
1.3%
5 3
 
1.9%
4 8
5.2%

야간연장운영여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size287.0 B
False
126 
True
29 
ValueCountFrequency (%)
False 126
81.3%
True 29
 
18.7%
2023-12-11T18:54:00.759286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주말운영여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size287.0 B
False
126 
True
29 
ValueCountFrequency (%)
False 126
81.3%
True 29
 
18.7%
2023-12-11T18:54:00.850162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

숙박가능여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size287.0 B
False
155 
ValueCountFrequency (%)
False 155
100.0%
2023-12-11T18:54:00.968363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

특이사항
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing155
Missing (%)100.0%
Memory size1.5 KiB

소재지도로명주소
Text

Distinct153
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T18:54:01.248531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length41
Mean length29.56129
Min length15

Characters and Unicode

Total characters4582
Distinct characters127
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

Unique151 ?
Unique (%)97.4%

Sample

1st row서울특별시 도봉구 해등로 50 (창동, 창동주공아파트)
2nd row서울특별시 도봉구 덕릉로59길 73-3 (창동)
3rd row서울특별시 도봉구 우이천로20길 7 (창동, 건영캐스빌아파트)
4th row서울특별시 도봉구 도봉로104길 101 (창동)
5th row서울특별시 도봉구 덕릉로59차길 14 (창동)
ValueCountFrequency (%)
서울특별시 155
17.9%
도봉구 155
17.9%
창동 55
 
6.4%
쌍문동 39
 
4.5%
방학동 37
 
4.3%
도봉동 24
 
2.8%
해등로 13
 
1.5%
마들로 13
 
1.5%
시루봉로 8
 
0.9%
경로당 7
 
0.8%
Other values (287) 359
41.5%
2023-12-11T18:54:01.713063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
710
 
15.5%
봉 231
 
5.0%
도 228
 
5.0%
동 185
 
4.0%
시 172
 
3.8%
서 159
 
3.5%
구 158
 
3.4%
울 157
 
3.4%
별 155
 
3.4%
특 155
 
3.4%
Other values (117) 2272
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2803
61.2%
Space Separator 710
 
15.5%
Decimal Number 649
 
14.2%
Close Punctuation 143
 
3.1%
Open Punctuation 143
 
3.1%
Other Punctuation 87
 
1.9%
Dash Punctuation 41
 
0.9%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
봉 231
 
8.2%
도 228
 
8.1%
동 185
 
6.6%
시 172
 
6.1%
서 159
 
5.7%
구 158
 
5.6%
울 157
 
5.6%
별 155
 
5.5%
특 155
 
5.5%
로 154
 
5.5%
Other values (101) 1049
37.4%
Decimal Number
ValueCountFrequency (%)
1 140
21.6%
6 88
13.6%
2 76
11.7%
3 73
11.2%
4 67
10.3%
0 52
 
8.0%
5 45
 
6.9%
8 37
 
5.7%
9 36
 
5.5%
7 35
 
5.4%
Space Separator
ValueCountFrequency (%)
710
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Other Punctuation
ValueCountFrequency (%)
, 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2803
61.2%
Common 1773
38.7%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
봉 231
 
8.2%
도 228
 
8.1%
동 185
 
6.6%
시 172
 
6.1%
서 159
 
5.7%
구 158
 
5.6%
울 157
 
5.6%
별 155
 
5.5%
특 155
 
5.5%
로 154
 
5.5%
Other values (101) 1049
37.4%
Common
ValueCountFrequency (%)
710
40.0%
) 143
 
8.1%
( 143
 
8.1%
1 140
 
7.9%
6 88
 
5.0%
, 87
 
4.9%
2 76
 
4.3%
3 73
 
4.1%
4 67
 
3.8%
0 52
 
2.9%
Other values (5) 194
 
10.9%
Latin
ValueCountFrequency (%)
A 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2803
61.2%
ASCII 1779
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
710
39.9%
) 143
 
8.0%
( 143
 
8.0%
1 140
 
7.9%
6 88
 
4.9%
, 87
 
4.9%
2 76
 
4.3%
3 73
 
4.1%
4 67
 
3.8%
0 52
 
2.9%
Other values (6) 200
 
11.2%
Hangul
ValueCountFrequency (%)
봉 231
 
8.2%
도 228
 
8.1%
동 185
 
6.6%
시 172
 
6.1%
서 159
 
5.7%
구 158
 
5.6%
울 157
 
5.6%
별 155
 
5.5%
특 155
 
5.5%
로 154
 
5.5%
Other values (101) 1049
37.4%

소재지지번주소
Text

Distinct154
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T18:54:02.077193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length34
Mean length23.206452
Min length15

Characters and Unicode

Total characters3597
Distinct characters66
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)98.7%

Sample

1st row서울특별시 도봉구 창제1동 해등로 50
2nd row서울특별시 도봉구 창제2동 창동 632-73
3rd row서울특별시 도봉구 창제2동 창동 635-42
4th row서울특별시 도봉구 창동 623-41
5th row서울특별시 도봉구 창제2동 창동 632-66
ValueCountFrequency (%)
서울특별시 155
20.4%
도봉구 155
20.4%
창동 39
 
5.1%
쌍문동 38
 
5.0%
방학동 27
 
3.6%
도봉동 19
 
2.5%
도봉제2동 13
 
1.7%
방학제3동 13
 
1.7%
창제5동 12
 
1.6%
방학제1동 11
 
1.4%
Other values (190) 278
36.6%
2023-12-11T18:54:02.667755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
605
16.8%
동 261
 
7.3%
도 205
 
5.7%
봉 202
 
5.6%
서 157
 
4.4%
구 157
 
4.4%
울 155
 
4.3%
시 155
 
4.3%
별 155
 
4.3%
특 155
 
4.3%
Other values (56) 1390
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2227
61.9%
Decimal Number 694
 
19.3%
Space Separator 605
 
16.8%
Dash Punctuation 65
 
1.8%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 261
11.7%
도 205
9.2%
봉 202
9.1%
서 157
 
7.0%
구 157
 
7.0%
울 155
 
7.0%
시 155
 
7.0%
별 155
 
7.0%
특 155
 
7.0%
제 130
 
5.8%
Other values (43) 495
22.2%
Decimal Number
ValueCountFrequency (%)
1 125
18.0%
3 94
13.5%
2 93
13.4%
4 73
10.5%
5 70
10.1%
6 66
9.5%
7 56
8.1%
8 45
 
6.5%
9 38
 
5.5%
0 34
 
4.9%
Space Separator
ValueCountFrequency (%)
605
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2227
61.9%
Common 1364
37.9%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 261
11.7%
도 205
9.2%
봉 202
9.1%
서 157
 
7.0%
구 157
 
7.0%
울 155
 
7.0%
시 155
 
7.0%
별 155
 
7.0%
특 155
 
7.0%
제 130
 
5.8%
Other values (43) 495
22.2%
Common
ValueCountFrequency (%)
605
44.4%
1 125
 
9.2%
3 94
 
6.9%
2 93
 
6.8%
4 73
 
5.4%
5 70
 
5.1%
6 66
 
4.8%
- 65
 
4.8%
7 56
 
4.1%
8 45
 
3.3%
Other values (2) 72
 
5.3%
Latin
ValueCountFrequency (%)
A 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2227
61.9%
ASCII 1370
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
605
44.2%
1 125
 
9.1%
3 94
 
6.9%
2 93
 
6.8%
4 73
 
5.3%
5 70
 
5.1%
6 66
 
4.8%
- 65
 
4.7%
7 56
 
4.1%
8 45
 
3.3%
Other values (3) 78
 
5.7%
Hangul
ValueCountFrequency (%)
동 261
11.7%
도 205
9.2%
봉 202
9.1%
서 157
 
7.0%
구 157
 
7.0%
울 155
 
7.0%
시 155
 
7.0%
별 155
 
7.0%
특 155
 
7.0%
제 130
 
5.8%
Other values (43) 495
22.2%

관리기관명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
방학3동
17 
쌍문1동
15 
창5동
15 
도봉2동
14 
쌍문4동
12 
Other values (9)
82 

Length

Max length4
Median length4
Mean length3.6709677
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row창1동
2nd row창2동
3rd row창2동
4th row창2동
5th row창2동

Common Values

ValueCountFrequency (%)
방학3동 17
11.0%
쌍문1동 15
9.7%
창5동 15
9.7%
도봉2동 14
9.0%
쌍문4동 12
 
7.7%
방학1동 12
 
7.7%
도봉1동 11
 
7.1%
창4동 10
 
6.5%
창1동 9
 
5.8%
창2동 9
 
5.8%
Other values (4) 31
20.0%

Length

2023-12-11T18:54:02.821965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방학3동 17
11.0%
쌍문1동 15
9.7%
창5동 15
9.7%
도봉2동 14
9.0%
쌍문4동 12
 
7.7%
방학1동 12
 
7.7%
도봉1동 11
 
7.1%
창4동 10
 
6.5%
창1동 9
 
5.8%
창2동 9
 
5.8%
Other values (4) 31
20.0%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
02-2091-5662
17 
02-2091-5507
15 
02-2091-5793
15 
02-2091-5844
14 
02-2091-5592
12 
Other values (9)
82 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02-2091-5403
2nd row02-2091-5714
3rd row02-2091-5714
4th row02-2091-5714
5th row02-2091-5714

Common Values

ValueCountFrequency (%)
02-2091-5662 17
11.0%
02-2091-5507 15
9.7%
02-2091-5793 15
9.7%
02-2091-5844 14
9.0%
02-2091-5592 12
 
7.7%
02-2091-5617 12
 
7.7%
02-2091-5813 11
 
7.1%
02-2091-5764 10
 
6.5%
02-2091-5403 9
 
5.8%
02-2091-5714 9
 
5.8%
Other values (4) 31
20.0%

Length

2023-12-11T18:54:02.977185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02-2091-5662 17
11.0%
02-2091-5507 15
9.7%
02-2091-5793 15
9.7%
02-2091-5844 14
9.0%
02-2091-5592 12
 
7.7%
02-2091-5617 12
 
7.7%
02-2091-5813 11
 
7.1%
02-2091-5764 10
 
6.5%
02-2091-5403 9
 
5.8%
02-2091-5714 9
 
5.8%
Other values (4) 31
20.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct151
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.658572
Minimum37.633053
Maximum37.68977
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T18:54:03.135078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.633053
5-th percentile37.640079
Q137.649983
median37.657179
Q337.664974
95-th percentile37.682617
Maximum37.68977
Range0.0567169
Interquartile range (IQR)0.01499095

Descriptive statistics

Standard deviation0.012483055
Coefficient of variation (CV)0.00033147977
Kurtosis-0.0444321
Mean37.658572
Median Absolute Deviation (MAD)0.0077946
Skewness0.50764872
Sum5837.0786
Variance0.00015582665
MonotonicityNot monotonic
2023-12-11T18:54:03.311172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6513004 2
 
1.3%
37.6713606 2
 
1.3%
37.6488798 2
 
1.3%
37.664974 2
 
1.3%
37.6500415 1
 
0.6%
37.6563305 1
 
0.6%
37.6527374 1
 
0.6%
37.6544747 1
 
0.6%
37.6616531 1
 
0.6%
37.6531585 1
 
0.6%
Other values (141) 141
91.0%
ValueCountFrequency (%)
37.6330531 1
0.6%
37.6333523 1
0.6%
37.6347893 1
0.6%
37.6366719 1
0.6%
37.6377532 1
0.6%
37.6381103 1
0.6%
37.6389718 1
0.6%
37.6392696 1
0.6%
37.6404265 1
0.6%
37.6408568 1
0.6%
ValueCountFrequency (%)
37.68977 1
0.6%
37.6888571 1
0.6%
37.6876359 1
0.6%
37.6864633 1
0.6%
37.6857879 1
0.6%
37.6846068 1
0.6%
37.6841853 1
0.6%
37.6829494 1
0.6%
37.6824746 1
0.6%
37.6820824 1
0.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct151
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.03742
Minimum127.01364
Maximum127.0539
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T18:54:03.464910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.01364
5-th percentile127.02289
Q1127.03007
median127.0381
Q3127.04521
95-th percentile127.04998
Maximum127.0539
Range0.0402561
Interquartile range (IQR)0.01513905

Descriptive statistics

Standard deviation0.0091294056
Coefficient of variation (CV)7.1863907 × 10-5
Kurtosis-0.69749248
Mean127.03742
Median Absolute Deviation (MAD)0.007256
Skewness-0.36694753
Sum19690.801
Variance8.3346047 × 10-5
MonotonicityNot monotonic
2023-12-11T18:54:03.654449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0247059 2
 
1.3%
127.047272 2
 
1.3%
127.0484783 2
 
1.3%
127.048155 2
 
1.3%
127.0436076 1
 
0.6%
127.0417 1
 
0.6%
127.0420601 1
 
0.6%
127.0464077 1
 
0.6%
127.0441715 1
 
0.6%
127.045654 1
 
0.6%
Other values (141) 141
91.0%
ValueCountFrequency (%)
127.0136444 1
0.6%
127.0144941 1
0.6%
127.0149044 1
0.6%
127.0186501 1
0.6%
127.0216044 1
0.6%
127.0219908 1
0.6%
127.0222484 1
0.6%
127.0227487 1
0.6%
127.0229441 1
0.6%
127.0232072 1
0.6%
ValueCountFrequency (%)
127.0539005 1
0.6%
127.0533207 1
0.6%
127.0515433 1
0.6%
127.0509338 1
0.6%
127.0507188 1
0.6%
127.0506781 1
0.6%
127.050345 1
0.6%
127.0502996 1
0.6%
127.0498458 1
0.6%
127.0497224 1
0.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2017-04-30 00:00:00
Maximum2017-04-30 00:00:00
2023-12-11T18:54:03.810995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:54:03.925188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T18:53:56.760490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:53.404933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.058510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.718724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.388362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.083328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.875802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:53.546490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.173713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.830371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.493680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.199355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.992883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:53.668017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.283920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.946525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.599692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.318388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:57.118857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:53.775185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.379264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.050831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.713838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.440125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:57.252186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:53.861597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.468670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.168684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.819409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.540479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:57.359966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:53.952405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:54.561501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.274394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:55.939375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:53:56.646961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:54:04.022274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명쉼터유형구분시설면적이용가능인원수선풍기보유대수에어컨보유대수야간연장운영여부주말운영여부관리기관명관리기관전화번호위도경도
법정동명1.0000.0000.2800.5210.3010.4580.0000.0001.0001.0000.8740.819
쉼터유형구분0.0001.0000.9730.8040.7160.6720.4270.4270.0000.0000.1810.000
시설면적0.2800.9731.0000.7780.8050.7900.5780.5780.2800.2800.0730.000
이용가능인원수0.5210.8040.7781.0000.6780.6030.7000.7000.5210.5210.3620.261
선풍기보유대수0.3010.7160.8050.6781.0000.9530.7640.7640.3010.3010.0000.000
에어컨보유대수0.4580.6720.7900.6030.9531.0000.5810.5810.4580.4580.2760.140
야간연장운영여부0.0000.4270.5780.7000.7640.5811.0000.9990.0000.0000.1270.000
주말운영여부0.0000.4270.5780.7000.7640.5810.9991.0000.0000.0000.1270.000
관리기관명1.0000.0000.2800.5210.3010.4580.0000.0001.0001.0000.8740.819
관리기관전화번호1.0000.0000.2800.5210.3010.4580.0000.0001.0001.0000.8740.819
위도0.8740.1810.0730.3620.0000.2760.1270.1270.8740.8741.0000.387
경도0.8190.0000.0000.2610.0000.1400.0000.0000.8190.8190.3871.000
2023-12-11T18:54:04.186793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관전화번호쉼터유형구분주말운영여부법정동명관리기관명야간연장운영여부
관리기관전화번호1.0000.0000.0001.0001.0000.000
쉼터유형구분0.0001.0000.6650.0000.0000.665
주말운영여부0.0000.6651.0000.0000.0000.979
법정동명1.0000.0000.0001.0001.0000.000
관리기관명1.0000.0000.0001.0001.0000.000
야간연장운영여부0.0000.6650.9790.0000.0001.000
2023-12-11T18:54:04.336550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설면적이용가능인원수선풍기보유대수에어컨보유대수위도경도법정동명쉼터유형구분야간연장운영여부주말운영여부관리기관명관리기관전화번호
시설면적1.0000.7460.5510.4830.0180.1100.1170.7880.5680.5680.1170.117
이용가능인원수0.7461.0000.3930.4420.0820.3260.2130.7480.7440.7440.2130.213
선풍기보유대수0.5510.3931.0000.420-0.127-0.1600.1320.5970.5770.5770.1320.132
에어컨보유대수0.4830.4420.4201.0000.2210.0010.2150.5420.4300.4300.2150.215
위도0.0180.082-0.1270.2211.0000.2420.5940.1050.0920.0920.5940.594
경도0.1100.326-0.1600.0010.2421.0000.5030.0000.0000.0000.5030.503
법정동명0.1170.2130.1320.2150.5940.5031.0000.0000.0000.0001.0001.000
쉼터유형구분0.7880.7480.5970.5420.1050.0000.0001.0000.6650.6650.0000.000
야간연장운영여부0.5680.7440.5770.4300.0920.0000.0000.6651.0000.9790.0000.000
주말운영여부0.5680.7440.5770.4300.0920.0000.0000.6650.9791.0000.0000.000
관리기관명0.1170.2130.1320.2150.5940.5031.0000.0000.0000.0001.0001.000
관리기관전화번호0.1170.2130.1320.2150.5940.5031.0000.0000.0000.0001.0001.000

Missing values

2023-12-11T18:53:57.535608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:53:57.843613image/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.

Sample

쉼터명법정동명쉼터유형구분운영시작일자운영종료일자시설면적이용가능인원수선풍기보유대수에어컨보유대수야간연장운영여부주말운영여부숙박가능여부특이사항소재지도로명주소소재지지번주소관리기관명관리기관전화번호위도경도데이터기준일자
0주공3단지A 경로당창1동노인시설2016-05-012016-09-30286.010072NNN<NA>서울특별시 도봉구 해등로 50 (창동, 창동주공아파트)서울특별시 도봉구 창제1동 해등로 50창1동02-2091-540337.650042127.0436082017-04-30
1창2동 주민센터창2동주민센터2016-05-012016-09-30988.024766YYN<NA>서울특별시 도봉구 덕릉로59길 73-3 (창동)서울특별시 도봉구 창제2동 창동 632-73창2동02-2091-571437.64139127.035642017-04-30
2창동건영캐스빌A 경로당창2동노인시설2016-05-012016-09-3086.42232NNN<NA>서울특별시 도봉구 우이천로20길 7 (창동, 건영캐스빌아파트)서울특별시 도봉구 창제2동 창동 635-42창2동02-2091-571437.641299127.0339962017-04-30
3장수 경로당창2동노인시설2016-05-012016-09-30234.05964YYN<NA>서울특별시 도봉구 도봉로104길 101 (창동)서울특별시 도봉구 창동 623-41창2동02-2091-571437.643983127.0374822017-04-30
4초안 경로당창2동노인시설2016-05-012016-09-30147.383082YYN<NA>서울특별시 도봉구 덕릉로59차길 14 (창동)서울특별시 도봉구 창제2동 창동 632-66창2동02-2091-571437.641236127.0356882017-04-30
5대우A 경로당창2동노인시설2016-05-012016-09-30143.05042NNN<NA>서울특별시 도봉구 덕릉로63가길 43, 대우A 경로당 (창동, 창동대우아파트)서울특별시 도봉구 창제2동 804 창동대우아파트 대우A 경로당창2동02-2091-571437.642356127.0375022017-04-30
6금용A 경로당창2동노인시설2016-05-012016-09-3038.03021NNN<NA>서울특별시 도봉구 우이천로 196-11 (창동, 창동금용아파트)서울특별시 도봉구 창제2동 창동 809창2동02-2091-571437.637753127.0357472017-04-30
7방학2동 경로당방학2동노인시설2016-05-012016-09-30188.03044YYN<NA>서울특별시 도봉구 시루봉로17길 64 (방학동)서울특별시 도봉구 방학제2동 방학동 398-15방학2동02-2091-564237.669332127.0313962017-04-30
8방학2동 주민센터방학2동주민센터2016-05-012016-09-301378.01501710YYN<NA>서울특별시 도봉구 시루봉로 226 (방학동)서울특별시 도봉구 방학제2동 방학동 621-3방학2동02-2091-564237.668177127.0350432017-04-30
9송학 경로당방학2동노인시설2016-05-012016-09-30142.03022NNN<NA>서울특별시 도봉구 도당로13라길 14-3 (방학동)서울특별시 도봉구 방학제2동 방학동 635-13방학2동02-2091-564237.66684127.0351272017-04-30
쉼터명법정동명쉼터유형구분운영시작일자운영종료일자시설면적이용가능인원수선풍기보유대수에어컨보유대수야간연장운영여부주말운영여부숙박가능여부특이사항소재지도로명주소소재지지번주소관리기관명관리기관전화번호위도경도데이터기준일자
145이수A 경로당방학1동노인시설2016-05-012016-09-3083.05022NNN<NA>서울특별시 도봉구 도봉로146길 36 (방학동, 브라운스톤방학아파트)서울특별시 도봉구 방학제1동 도봉로146길 36방학1동02-2091-561737.663477127.0450532017-04-30
146금광A 경로당방학1동노인시설2016-05-012016-09-3050.04022NNN<NA>서울특별시 도봉구 도봉로150바길 26 (방학동, 금광포란재아파트)서울특별시 도봉구 방학제1동 도봉로150바길 26방학1동02-2091-561737.664583127.0450672017-04-30
147ESA1단지A 경로당방학1동노인시설2016-05-012016-09-3037.03022NNN<NA>서울특별시 도봉구 마들로 657 (방학동, 이에스에이아파트)서울특별시 도봉구 방학제1동 마들로 657방학1동02-2091-561737.668562127.0454842017-04-30
148방학삼성래미안A2단지경로당방학1동노인시설2016-05-012016-09-3085.02241NNN<NA>서울특별시 도봉구 도봉로150길 42 (방학동, 방학동삼성래미안)서울특별시 도봉구 방학제1동 715-12 방학동삼성래미안방학1동02-2091-561737.665064127.0458052017-04-30
149신우 경로당방학2동노인시설2016-05-012016-09-30185.03032NNN<NA>서울특별시 도봉구 도당로13다길 39서울특별시 도봉구 방학제2동 방학동 317-10방학2동02-2091-564237.665238127.0326582017-04-30
150창동종합사회복지관창1동복지회관2016-05-012016-09-301814.015041YYN<NA>서울특별시 도봉구 덕릉로 329 (창동)서울특별시 도봉구 창제1동 창동 374창1동02-2091-540337.644837127.0454582017-04-30
151삼성A 제1경로당창1동노인시설2016-05-012016-09-30191.05432NNN<NA>서울특별시 도봉구 노해로66길 29 (창동)서울특별시 도봉구 창제1동 창동 45창1동02-2091-540337.64888127.0484782017-04-30
152현대타운A 경로당창1동노인시설2016-05-012016-09-3047.03031NNN<NA>서울특별시 도봉구 도봉로114길 22-8 (창동, 창동현대타운101동)서울특별시 도봉구 창제1동 창동 812창1동02-2091-540337.647098127.0352392017-04-30
153대우그린A 경로당창1동노인시설2016-05-012016-09-3072.01821NNN<NA>서울특별시 도봉구 덕릉로 371 (창동, 대우그린아파트)서울특별시 도봉구 창제1동 창동 814창1동02-2091-540337.646309127.0497222017-04-30
154삼성A 제2경로당창1동노인시설2016-05-012016-09-30123.03142NNN<NA>서울특별시 도봉구 노해로66길 29 (창동)서울특별시 도봉구 창제1동 쌍문동 45창1동02-2091-540337.64888127.0484782017-04-30