Overview

Dataset statistics

Number of variables22
Number of observations63
Missing cells125
Missing cells (%)9.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory189.1 B

Variable types

Categorical3
Text7
Numeric10
DateTime1
Unsupported1

Dataset

Description경기도_노인여가복지시설(노인복지관) 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=MGVBGBH0FKD48G8QQ4I827687767&infSeq=1

Alerts

설치주체-민간 has constant value ""Constant
설치주체-지자체 is highly imbalanced (85.2%)Imbalance
운영주체-구분 is highly imbalanced (51.2%)Imbalance
설치주체-민간 has 62 (98.4%) missing valuesMissing
비고 has 63 (100.0%) missing valuesMissing
시설명 has unique valuesUnique
도로명 주소 has unique valuesUnique
지번 주소 has unique valuesUnique
우편번호 has unique valuesUnique
전화번호 has unique valuesUnique
FAX번호 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported
이용회원수 has 1 (1.6%) zerosZeros
종사자현원-비정규직 has 3 (4.8%) zerosZeros

Reproduction

Analysis started2023-12-10 22:50:43.392232
Analysis finished2023-12-10 22:50:43.830321
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

Distinct30
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
성남시
6 
수원시
6 
평택시
 
4
화성시
 
3
안산시
 
3
Other values (25)
41 

Length

Max length4
Median length3
Mean length3.1111111
Min length3

Unique

Unique14 ?
Unique (%)22.2%

Sample

1st row가평군
2nd row가평군
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
성남시 6
 
9.5%
수원시 6
 
9.5%
평택시 4
 
6.3%
화성시 3
 
4.8%
안산시 3
 
4.8%
의정부시 3
 
4.8%
용인시 3
 
4.8%
남양주시 3
 
4.8%
고양시 3
 
4.8%
부천시 3
 
4.8%
Other values (20) 26
41.3%

Length

2023-12-11T07:50:43.905250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 6
 
9.5%
수원시 6
 
9.5%
평택시 4
 
6.3%
화성시 3
 
4.8%
안산시 3
 
4.8%
의정부시 3
 
4.8%
용인시 3
 
4.8%
남양주시 3
 
4.8%
고양시 3
 
4.8%
부천시 3
 
4.8%
Other values (20) 26
41.3%

시설명
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T07:50:44.117696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length9.1269841
Min length7

Characters and Unicode

Total characters575
Distinct characters104
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

Unique63 ?
Unique (%)100.0%

Sample

1st row가평군노인복지관
2nd row청평노인복지관
3rd row고양시대화노인종합복지관
4th row고양시덕양노인종합복지관
5th row고양시일산노인종합복지관
ValueCountFrequency (%)
가평군노인복지관 1
 
1.6%
시흥시노인종합복지관 1
 
1.6%
동산노인복지관 1
 
1.6%
상록구노인복지관 1
 
1.6%
안성시노인복지관 1
 
1.6%
안양시노인종합복지관 1
 
1.6%
회천노인복지관 1
 
1.6%
희망노인복지관 1
 
1.6%
양평군노인복지관 1
 
1.6%
여주시노인복지관 1
 
1.6%
Other values (53) 53
84.1%
2023-12-11T07:50:44.527025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 66
 
11.5%
복 64
 
11.1%
지 64
 
11.1%
인 63
 
11.0%
노 62
 
10.8%
시 28
 
4.9%
합 17
 
3.0%
종 17
 
3.0%
부 11
 
1.9%
천 9
 
1.6%
Other values (94) 174
30.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 567
98.6%
Other Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 66
 
11.6%
복 64
 
11.3%
지 64
 
11.3%
인 63
 
11.1%
노 62
 
10.9%
시 28
 
4.9%
합 17
 
3.0%
종 17
 
3.0%
부 11
 
1.9%
천 9
 
1.6%
Other values (87) 166
29.3%
Open Punctuation
ValueCountFrequency (%)
[ 1
50.0%
( 1
50.0%
Close Punctuation
ValueCountFrequency (%)
] 1
50.0%
) 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Other Punctuation
ValueCountFrequency (%)
: 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 567
98.6%
Common 6
 
1.0%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 66
 
11.6%
복 64
 
11.3%
지 64
 
11.3%
인 63
 
11.1%
노 62
 
10.9%
시 28
 
4.9%
합 17
 
3.0%
종 17
 
3.0%
부 11
 
1.9%
천 9
 
1.6%
Other values (87) 166
29.3%
Common
ValueCountFrequency (%)
: 2
33.3%
[ 1
16.7%
] 1
16.7%
( 1
16.7%
) 1
16.7%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 567
98.6%
ASCII 8
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 66
 
11.6%
복 64
 
11.3%
지 64
 
11.3%
인 63
 
11.1%
노 62
 
10.9%
시 28
 
4.9%
합 17
 
3.0%
종 17
 
3.0%
부 11
 
1.9%
천 9
 
1.6%
Other values (87) 166
29.3%
ASCII
ValueCountFrequency (%)
: 2
25.0%
[ 1
12.5%
] 1
12.5%
( 1
12.5%
) 1
12.5%
S 1
12.5%
K 1
12.5%

도로명 주소
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T07:50:44.802529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length18.809524
Min length14

Characters and Unicode

Total characters1185
Distinct characters131
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 가화로 161
2nd row경기도 가평군 청평면 은고개로 39
3rd row경기도 고양시 일산서구 일산로 778
4th row경기도 고양시 덕양구 어울림로 49
5th row경기도 고양시 일산동구 호수로 731
ValueCountFrequency (%)
경기도 63
 
22.0%
수원시 6
 
2.1%
성남시 6
 
2.1%
평택시 4
 
1.4%
안산시 3
 
1.0%
부천시 3
 
1.0%
고양시 3
 
1.0%
화성시 3
 
1.0%
남양주시 3
 
1.0%
용인시 3
 
1.0%
Other values (168) 189
66.1%
2023-12-11T07:50:45.274145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
18.8%
경 66
 
5.6%
기 65
 
5.5%
도 63
 
5.3%
로 61
 
5.1%
시 61
 
5.1%
1 36
 
3.0%
2 27
 
2.3%
4 23
 
1.9%
구 23
 
1.9%
Other values (121) 537
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 746
63.0%
Space Separator 223
 
18.8%
Decimal Number 210
 
17.7%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 66
 
8.8%
기 65
 
8.7%
도 63
 
8.4%
로 61
 
8.2%
시 61
 
8.2%
구 23
 
3.1%
길 19
 
2.5%
남 18
 
2.4%
성 16
 
2.1%
번 16
 
2.1%
Other values (109) 338
45.3%
Decimal Number
ValueCountFrequency (%)
1 36
17.1%
2 27
12.9%
4 23
11.0%
3 22
10.5%
5 20
9.5%
7 19
9.0%
8 17
8.1%
6 16
7.6%
9 15
7.1%
0 15
7.1%
Space Separator
ValueCountFrequency (%)
223
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 746
63.0%
Common 439
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 66
 
8.8%
기 65
 
8.7%
도 63
 
8.4%
로 61
 
8.2%
시 61
 
8.2%
구 23
 
3.1%
길 19
 
2.5%
남 18
 
2.4%
성 16
 
2.1%
번 16
 
2.1%
Other values (109) 338
45.3%
Common
ValueCountFrequency (%)
223
50.8%
1 36
 
8.2%
2 27
 
6.2%
4 23
 
5.2%
3 22
 
5.0%
5 20
 
4.6%
7 19
 
4.3%
8 17
 
3.9%
6 16
 
3.6%
9 15
 
3.4%
Other values (2) 21
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 746
63.0%
ASCII 439
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
50.8%
1 36
 
8.2%
2 27
 
6.2%
4 23
 
5.2%
3 22
 
5.0%
5 20
 
4.6%
7 19
 
4.3%
8 17
 
3.9%
6 16
 
3.6%
9 15
 
3.4%
Other values (2) 21
 
4.8%
Hangul
ValueCountFrequency (%)
경 66
 
8.8%
기 65
 
8.7%
도 63
 
8.4%
로 61
 
8.2%
시 61
 
8.2%
구 23
 
3.1%
길 19
 
2.5%
남 18
 
2.4%
성 16
 
2.1%
번 16
 
2.1%
Other values (109) 338
45.3%

지번 주소
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T07:50:45.576756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length26
Mean length21.412698
Min length16

Characters and Unicode

Total characters1349
Distinct characters137
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 가평읍 읍내리 625-8번지
2nd row경기도 가평군 청평면 청평리 333-13번지 2층
3rd row경기도 고양시 일산서구 대화동 2237번지
4th row경기도 고양시 덕양구 화정동 846번지
5th row경기도 고양시 일산동구 장항동 906번지
ValueCountFrequency (%)
경기도 63
 
20.9%
성남시 6
 
2.0%
수원시 6
 
2.0%
평택시 4
 
1.3%
남양주시 3
 
1.0%
고양시 3
 
1.0%
화성시 3
 
1.0%
용인시 3
 
1.0%
의정부시 3
 
1.0%
부천시 3
 
1.0%
Other values (185) 205
67.9%
2023-12-11T07:50:46.035884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
 
17.7%
지 67
 
5.0%
기 64
 
4.7%
경 63
 
4.7%
도 63
 
4.7%
번 63
 
4.7%
시 61
 
4.5%
동 55
 
4.1%
2 36
 
2.7%
1 33
 
2.4%
Other values (127) 605
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 855
63.4%
Space Separator 239
 
17.7%
Decimal Number 230
 
17.0%
Dash Punctuation 25
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 67
 
7.8%
기 64
 
7.5%
경 63
 
7.4%
도 63
 
7.4%
번 63
 
7.4%
시 61
 
7.1%
동 55
 
6.4%
구 23
 
2.7%
정 15
 
1.8%
성 15
 
1.8%
Other values (115) 366
42.8%
Decimal Number
ValueCountFrequency (%)
2 36
15.7%
1 33
14.3%
6 24
10.4%
3 23
10.0%
8 22
9.6%
7 22
9.6%
5 21
9.1%
4 18
7.8%
0 17
7.4%
9 14
 
6.1%
Space Separator
ValueCountFrequency (%)
239
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 855
63.4%
Common 494
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 67
 
7.8%
기 64
 
7.5%
경 63
 
7.4%
도 63
 
7.4%
번 63
 
7.4%
시 61
 
7.1%
동 55
 
6.4%
구 23
 
2.7%
정 15
 
1.8%
성 15
 
1.8%
Other values (115) 366
42.8%
Common
ValueCountFrequency (%)
239
48.4%
2 36
 
7.3%
1 33
 
6.7%
- 25
 
5.1%
6 24
 
4.9%
3 23
 
4.7%
8 22
 
4.5%
7 22
 
4.5%
5 21
 
4.3%
4 18
 
3.6%
Other values (2) 31
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 855
63.4%
ASCII 494
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
48.4%
2 36
 
7.3%
1 33
 
6.7%
- 25
 
5.1%
6 24
 
4.9%
3 23
 
4.7%
8 22
 
4.5%
7 22
 
4.5%
5 21
 
4.3%
4 18
 
3.6%
Other values (2) 31
 
6.3%
Hangul
ValueCountFrequency (%)
지 67
 
7.8%
기 64
 
7.5%
경 63
 
7.4%
도 63
 
7.4%
번 63
 
7.4%
시 61
 
7.1%
동 55
 
6.4%
구 23
 
2.7%
정 15
 
1.8%
성 15
 
1.8%
Other values (115) 366
42.8%

우편번호
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14291.302
Minimum10032
Maximum18590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:46.200234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10032
5-th percentile10407
Q112138.5
median14245
Q316380.5
95-th percentile18097.5
Maximum18590
Range8558
Interquartile range (IQR)4242

Descriptive statistics

Standard deviation2525.5811
Coefficient of variation (CV)0.17672156
Kurtosis-1.2333983
Mean14291.302
Median Absolute Deviation (MAD)2116
Skewness0.041095734
Sum900352
Variance6378559.8
MonotonicityNot monotonic
2023-12-11T07:50:46.374336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12413 1
 
1.6%
12452 1
 
1.6%
15585 1
 
1.6%
15300 1
 
1.6%
17591 1
 
1.6%
14081 1
 
1.6%
11451 1
 
1.6%
11486 1
 
1.6%
12555 1
 
1.6%
12629 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
10032 1
1.6%
10111 1
1.6%
10382 1
1.6%
10400 1
1.6%
10470 1
1.6%
10934 1
1.6%
11012 1
1.6%
11151 1
1.6%
11329 1
1.6%
11451 1
1.6%
ValueCountFrequency (%)
18590 1
1.6%
18501 1
1.6%
18274 1
1.6%
18109 1
1.6%
17994 1
1.6%
17882 1
1.6%
17816 1
1.6%
17730 1
1.6%
17591 1
1.6%
17375 1
1.6%

전화번호
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T07:50:46.644317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.047619
Min length11

Characters and Unicode

Total characters759
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

Unique63 ?
Unique (%)100.0%

Sample

1st row031-582-0763
2nd row031-582-8879
3rd row031-917-1352
4th row031-969-7781
5th row031-961-4300
ValueCountFrequency (%)
031-582-0763 1
 
1.6%
031-404-3100 1
 
1.6%
031-400-8701 1
 
1.6%
031-414-2271 1
 
1.6%
031-674-0794 1
 
1.6%
031-455-0551 1
 
1.6%
031-859-9081 1
 
1.6%
031-848-6500 1
 
1.6%
031-770-9751 1
 
1.6%
031-881-0050 1
 
1.6%
Other values (53) 53
84.1%
2023-12-11T07:50:47.071868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 142
18.7%
- 126
16.6%
3 94
12.4%
1 90
11.9%
8 56
 
7.4%
5 49
 
6.5%
7 47
 
6.2%
2 44
 
5.8%
9 42
 
5.5%
6 36
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 633
83.4%
Dash Punctuation 126
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142
22.4%
3 94
14.8%
1 90
14.2%
8 56
 
8.8%
5 49
 
7.7%
7 47
 
7.4%
2 44
 
7.0%
9 42
 
6.6%
6 36
 
5.7%
4 33
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 759
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 142
18.7%
- 126
16.6%
3 94
12.4%
1 90
11.9%
8 56
 
7.4%
5 49
 
6.5%
7 47
 
6.2%
2 44
 
5.8%
9 42
 
5.5%
6 36
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 759
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 142
18.7%
- 126
16.6%
3 94
12.4%
1 90
11.9%
8 56
 
7.4%
5 49
 
6.5%
7 47
 
6.2%
2 44
 
5.8%
9 42
 
5.5%
6 36
 
4.7%

FAX번호
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T07:50:47.634377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.095238
Min length11

Characters and Unicode

Total characters762
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

Unique63 ?
Unique (%)100.0%

Sample

1st row031-582-4181
2nd row031-584-8879
3rd row031-917-1351
4th row031-969-7784
5th row031-961-4399
ValueCountFrequency (%)
031-582-4181 1
 
1.6%
031-404-3122 1
 
1.6%
031-400-8724 1
 
1.6%
031-486-6600 1
 
1.6%
031-674-0797 1
 
1.6%
031-455-0553 1
 
1.6%
031-859-9084 1
 
1.6%
031-848-3200 1
 
1.6%
031-774-9750 1
 
1.6%
031-881-0041 1
 
1.6%
Other values (53) 53
84.1%
2023-12-11T07:50:48.097537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 126
16.5%
0 114
15.0%
3 91
11.9%
1 90
11.8%
9 57
7.5%
8 56
7.3%
5 50
 
6.6%
4 47
 
6.2%
2 45
 
5.9%
7 45
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 636
83.5%
Dash Punctuation 126
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 114
17.9%
3 91
14.3%
1 90
14.2%
9 57
9.0%
8 56
8.8%
5 50
7.9%
4 47
7.4%
2 45
 
7.1%
7 45
 
7.1%
6 41
 
6.4%
Dash Punctuation
ValueCountFrequency (%)
- 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 126
16.5%
0 114
15.0%
3 91
11.9%
1 90
11.8%
9 57
7.5%
8 56
7.3%
5 50
 
6.6%
4 47
 
6.2%
2 45
 
5.9%
7 45
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 126
16.5%
0 114
15.0%
3 91
11.9%
1 90
11.8%
9 57
7.5%
8 56
7.3%
5 50
 
6.6%
4 47
 
6.2%
2 45
 
5.9%
7 45
 
5.9%

이용회원수
Real number (ℝ)

ZEROS 

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11419.333
Minimum0
Maximum87988
Zeros1
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:48.286951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile446.9
Q13879.5
median8449
Q313479.5
95-th percentile38874.1
Maximum87988
Range87988
Interquartile range (IQR)9600

Descriptive statistics

Standard deviation13742.479
Coefficient of variation (CV)1.2034397
Kurtosis15.295349
Mean11419.333
Median Absolute Deviation (MAD)5027
Skewness3.3367657
Sum719418
Variance1.8885572 × 108
MonotonicityNot monotonic
2023-12-11T07:50:48.458148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000 2
 
3.2%
3914 1
 
1.6%
14662 1
 
1.6%
1789 1
 
1.6%
87988 1
 
1.6%
6621 1
 
1.6%
800 1
 
1.6%
2025 1
 
1.6%
0 1
 
1.6%
4208 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
0 1
1.6%
375 1
1.6%
420 1
1.6%
441 1
1.6%
500 1
1.6%
800 1
1.6%
918 1
1.6%
1000 2
3.2%
1405 1
1.6%
1576 1
1.6%
ValueCountFrequency (%)
87988 1
1.6%
41948 1
1.6%
40197 1
1.6%
39940 1
1.6%
29281 1
1.6%
28402 1
1.6%
25746 1
1.6%
22014 1
1.6%
17806 1
1.6%
17489 1
1.6%

종사자정원
Real number (ℝ)

Distinct43
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.269841
Minimum10
Maximum131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:48.612091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile14
Q125
median34
Q363.5
95-th percentile94.9
Maximum131
Range121
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation28.559619
Coefficient of variation (CV)0.61724047
Kurtosis-0.21824747
Mean46.269841
Median Absolute Deviation (MAD)16
Skewness0.80058521
Sum2915
Variance815.65182
MonotonicityNot monotonic
2023-12-11T07:50:48.757948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
14 4
 
6.3%
32 3
 
4.8%
25 3
 
4.8%
30 2
 
3.2%
40 2
 
3.2%
50 2
 
3.2%
10 2
 
3.2%
26 2
 
3.2%
23 2
 
3.2%
34 2
 
3.2%
Other values (33) 39
61.9%
ValueCountFrequency (%)
10 2
3.2%
14 4
6.3%
15 1
 
1.6%
17 1
 
1.6%
18 2
3.2%
19 1
 
1.6%
20 1
 
1.6%
22 1
 
1.6%
23 2
3.2%
25 3
4.8%
ValueCountFrequency (%)
131 1
1.6%
97 1
1.6%
96 1
1.6%
95 1
1.6%
94 1
1.6%
92 1
1.6%
90 1
1.6%
89 1
1.6%
83 2
3.2%
80 2
3.2%

종사자현원-계
Real number (ℝ)

Distinct50
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.126984
Minimum10
Maximum131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:48.906503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15.3
Q132
median60
Q382.5
95-th percentile102.3
Maximum131
Range121
Interquartile range (IQR)50.5

Descriptive statistics

Standard deviation29.673216
Coefficient of variation (CV)0.50185573
Kurtosis-0.87748769
Mean59.126984
Median Absolute Deviation (MAD)27
Skewness0.11495016
Sum3725
Variance880.49974
MonotonicityNot monotonic
2023-12-11T07:50:49.079602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96 3
 
4.8%
21 2
 
3.2%
27 2
 
3.2%
59 2
 
3.2%
55 2
 
3.2%
48 2
 
3.2%
42 2
 
3.2%
10 2
 
3.2%
60 2
 
3.2%
80 2
 
3.2%
Other values (40) 42
66.7%
ValueCountFrequency (%)
10 2
3.2%
14 1
1.6%
15 1
1.6%
18 1
1.6%
19 1
1.6%
21 2
3.2%
22 1
1.6%
23 1
1.6%
24 1
1.6%
27 2
3.2%
ValueCountFrequency (%)
131 1
 
1.6%
113 1
 
1.6%
106 1
 
1.6%
103 1
 
1.6%
96 3
4.8%
94 1
 
1.6%
93 1
 
1.6%
92 1
 
1.6%
91 2
3.2%
90 1
 
1.6%

종사자현원-남자
Real number (ℝ)

Distinct18
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.174603
Minimum3
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:49.195939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q16.5
median9
Q312.5
95-th percentile19
Maximum34
Range31
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.6384043
Coefficient of variation (CV)0.55416454
Kurtosis4.2538269
Mean10.174603
Median Absolute Deviation (MAD)3
Skewness1.6987568
Sum641
Variance31.791603
MonotonicityNot monotonic
2023-12-11T07:50:49.312651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
8 8
12.7%
9 7
11.1%
7 7
11.1%
6 5
7.9%
5 5
7.9%
4 5
7.9%
19 4
 
6.3%
12 4
 
6.3%
15 3
 
4.8%
10 3
 
4.8%
Other values (8) 12
19.0%
ValueCountFrequency (%)
3 1
 
1.6%
4 5
7.9%
5 5
7.9%
6 5
7.9%
7 7
11.1%
8 8
12.7%
9 7
11.1%
10 3
 
4.8%
11 2
 
3.2%
12 4
6.3%
ValueCountFrequency (%)
34 1
 
1.6%
25 1
 
1.6%
19 4
6.3%
18 1
 
1.6%
17 2
3.2%
15 3
4.8%
14 3
4.8%
13 1
 
1.6%
12 4
6.3%
11 2
3.2%

종사자현원-여자
Real number (ℝ)

Distinct46
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.952381
Minimum5
Maximum122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:49.497875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile11
Q122
median52
Q371
95-th percentile94.3
Maximum122
Range117
Interquartile range (IQR)49

Descriptive statistics

Standard deviation28.178823
Coefficient of variation (CV)0.57563744
Kurtosis-0.8013158
Mean48.952381
Median Absolute Deviation (MAD)25
Skewness0.22201899
Sum3084
Variance794.04608
MonotonicityNot monotonic
2023-12-11T07:50:49.673154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
77 3
 
4.8%
62 3
 
4.8%
15 2
 
3.2%
27 2
 
3.2%
11 2
 
3.2%
48 2
 
3.2%
72 2
 
3.2%
76 2
 
3.2%
47 2
 
3.2%
21 2
 
3.2%
Other values (36) 41
65.1%
ValueCountFrequency (%)
5 1
1.6%
6 1
1.6%
10 1
1.6%
11 2
3.2%
13 1
1.6%
14 2
3.2%
15 2
3.2%
17 1
1.6%
18 1
1.6%
19 1
1.6%
ValueCountFrequency (%)
122 1
 
1.6%
99 1
 
1.6%
97 1
 
1.6%
95 1
 
1.6%
88 1
 
1.6%
87 1
 
1.6%
81 1
 
1.6%
79 1
 
1.6%
77 3
4.8%
76 2
3.2%

종사자현원-정규직
Real number (ℝ)

Distinct28
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.412698
Minimum6
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:49.822072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9.1
Q114
median18
Q324.5
95-th percentile34.9
Maximum47
Range41
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation8.6948908
Coefficient of variation (CV)0.42595499
Kurtosis0.4892176
Mean20.412698
Median Absolute Deviation (MAD)5
Skewness0.79769651
Sum1286
Variance75.601126
MonotonicityNot monotonic
2023-12-11T07:50:49.935895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
18 6
 
9.5%
17 6
 
9.5%
14 6
 
9.5%
22 5
 
7.9%
13 3
 
4.8%
32 3
 
4.8%
24 3
 
4.8%
40 2
 
3.2%
23 2
 
3.2%
7 2
 
3.2%
Other values (18) 25
39.7%
ValueCountFrequency (%)
6 1
 
1.6%
7 2
 
3.2%
9 1
 
1.6%
10 2
 
3.2%
11 2
 
3.2%
12 2
 
3.2%
13 3
4.8%
14 6
9.5%
15 1
 
1.6%
16 1
 
1.6%
ValueCountFrequency (%)
47 1
 
1.6%
40 2
3.2%
35 1
 
1.6%
34 1
 
1.6%
32 3
4.8%
31 2
3.2%
30 2
3.2%
27 2
3.2%
26 1
 
1.6%
25 1
 
1.6%

종사자현원-비정규직
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.714286
Minimum0
Maximum114
Zeros3
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:50.051279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.3
Q111.5
median42
Q358
95-th percentile82.6
Maximum114
Range114
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation27.61044
Coefficient of variation (CV)0.7131848
Kurtosis-0.65186007
Mean38.714286
Median Absolute Deviation (MAD)25
Skewness0.36335181
Sum2439
Variance762.33641
MonotonicityNot monotonic
2023-12-11T07:50:50.195487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
11 5
 
7.9%
0 3
 
4.8%
57 3
 
4.8%
5 2
 
3.2%
53 2
 
3.2%
7 2
 
3.2%
14 2
 
3.2%
8 2
 
3.2%
65 2
 
3.2%
42 2
 
3.2%
Other values (36) 38
60.3%
ValueCountFrequency (%)
0 3
4.8%
2 1
 
1.6%
5 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%
9 1
 
1.6%
11 5
7.9%
12 1
 
1.6%
13 1
 
1.6%
14 2
 
3.2%
ValueCountFrequency (%)
114 1
1.6%
92 1
1.6%
89 1
1.6%
83 1
1.6%
79 1
1.6%
74 1
1.6%
70 1
1.6%
69 1
1.6%
67 1
1.6%
66 1
1.6%

설치일자
Date

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum1900-01-02 00:00:00
Maximum2022-11-01 00:00:00
2023-12-11T07:50:50.319017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:50:50.467895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

설치주체-지자체
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
지자체 위탁
61 
<NA>
 
1
지자체 직영
 
1

Length

Max length6
Median length6
Mean length5.968254
Min length4

Unique

Unique2 ?
Unique (%)3.2%

Sample

1st row지자체 위탁
2nd row지자체 위탁
3rd row지자체 위탁
4th row지자체 위탁
5th row지자체 위탁

Common Values

ValueCountFrequency (%)
지자체 위탁 61
96.8%
<NA> 1
 
1.6%
지자체 직영 1
 
1.6%

Length

2023-12-11T07:50:50.626410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:50:50.734929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지자체 62
49.6%
위탁 61
48.8%
na 1
 
0.8%
직영 1
 
0.8%

설치주체-민간
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing62
Missing (%)98.4%
Memory size636.0 B
2023-12-11T07:50:50.871857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
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

Unique1 ?
Unique (%)100.0%

Sample

1st row사회복지법인
ValueCountFrequency (%)
사회복지법인 1
100.0%
2023-12-11T07:50:51.127615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1
16.7%
회 1
16.7%
복 1
16.7%
지 1
16.7%
법 1
16.7%
인 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1
16.7%
회 1
16.7%
복 1
16.7%
지 1
16.7%
법 1
16.7%
인 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1
16.7%
회 1
16.7%
복 1
16.7%
지 1
16.7%
법 1
16.7%
인 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1
16.7%
회 1
16.7%
복 1
16.7%
지 1
16.7%
법 1
16.7%
인 1
16.7%

운영주체-구분
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
사회복지법인
49 
재단법인
8 
사단법인
 
2
학교법인
 
2
기타
 
2

Length

Max length6
Median length6
Mean length5.4920635
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재단법인
2nd row재단법인
3rd row사회복지법인
4th row사회복지법인
5th row사회복지법인

Common Values

ValueCountFrequency (%)
사회복지법인 49
77.8%
재단법인 8
 
12.7%
사단법인 2
 
3.2%
학교법인 2
 
3.2%
기타 2
 
3.2%

Length

2023-12-11T07:50:51.270703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:50:51.412682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사회복지법인 49
77.8%
재단법인 8
 
12.7%
사단법인 2
 
3.2%
학교법인 2
 
3.2%
기타 2
 
3.2%

운영주체-법인(단체)명
Text

Distinct45
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-11T07:50:51.615034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length13.365079
Min length4

Characters and Unicode

Total characters842
Distinct characters105
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)55.6%

Sample

1st row가평군복지재단
2nd row재단법인 가평군복지재단
3rd row사회복지법인 효샘
4th row사회복지법인 해피월드복지재단
5th row사회복지법인 연꽃마을
ValueCountFrequency (%)
사회복지법인 36
30.0%
대한불교조계종사회복지재단 9
 
7.5%
재단법인 6
 
5.0%
연꽃마을 5
 
4.2%
사회복지회 3
 
2.5%
사회복지재단 2
 
1.7%
가평군복지재단 2
 
1.7%
수원교구 2
 
1.7%
지구촌사회복지재단 2
 
1.7%
평택복지재단 2
 
1.7%
Other values (43) 51
42.5%
2023-12-11T07:50:51.988341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 83
 
9.9%
복 78
 
9.3%
회 75
 
8.9%
사 58
 
6.9%
57
 
6.8%
인 46
 
5.5%
법 45
 
5.3%
단 43
 
5.1%
재 42
 
5.0%
교 27
 
3.2%
Other values (95) 288
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 779
92.5%
Space Separator 57
 
6.8%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 83
 
10.7%
복 78
 
10.0%
회 75
 
9.6%
사 58
 
7.4%
인 46
 
5.9%
법 45
 
5.8%
단 43
 
5.5%
재 42
 
5.4%
교 27
 
3.5%
한 25
 
3.2%
Other values (92) 257
33.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 779
92.5%
Common 63
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 83
 
10.7%
복 78
 
10.0%
회 75
 
9.6%
사 58
 
7.4%
인 46
 
5.9%
법 45
 
5.8%
단 43
 
5.5%
재 42
 
5.4%
교 27
 
3.5%
한 25
 
3.2%
Other values (92) 257
33.0%
Common
ValueCountFrequency (%)
57
90.5%
) 3
 
4.8%
( 3
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 779
92.5%
ASCII 63
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 83
 
10.7%
복 78
 
10.0%
회 75
 
9.6%
사 58
 
7.4%
인 46
 
5.9%
법 45
 
5.8%
단 43
 
5.5%
재 42
 
5.4%
교 27
 
3.5%
한 25
 
3.2%
Other values (92) 257
33.0%
ASCII
ValueCountFrequency (%)
57
90.5%
) 3
 
4.8%
( 3
 
4.8%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing63
Missing (%)100.0%
Memory size699.0 B

WGS84위도
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.44791
Minimum36.957641
Maximum38.103506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:52.141593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.957641
5-th percentile37.010513
Q137.29152
median37.416897
Q337.661662
95-th percentile37.837693
Maximum38.103506
Range1.1458644
Interquartile range (IQR)0.37014221

Descriptive statistics

Standard deviation0.24832637
Coefficient of variation (CV)0.0066312477
Kurtosis-0.21576857
Mean37.44791
Median Absolute Deviation (MAD)0.13837438
Skewness0.27330937
Sum2359.2184
Variance0.061665986
MonotonicityNot monotonic
2023-12-11T07:50:52.302505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.8336279459 1
 
1.6%
37.739208662 1
 
1.6%
37.3014877519 1
 
1.6%
37.318021391 1
 
1.6%
37.004372045 1
 
1.6%
37.3799031031 1
 
1.6%
37.8381451088 1
 
1.6%
37.8014591158 1
 
1.6%
37.4879003818 1
 
1.6%
37.2936231233 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
36.9576412931 1
1.6%
36.989711369 1
1.6%
36.998843304 1
1.6%
37.004372045 1
1.6%
37.0657848904 1
1.6%
37.1282159918 1
1.6%
37.1704840136 1
1.6%
37.177749844 1
1.6%
37.1989145975 1
1.6%
37.2410143538 1
1.6%
ValueCountFrequency (%)
38.1035057227 1
1.6%
37.9051489094 1
1.6%
37.9050478228 1
1.6%
37.8381451088 1
1.6%
37.8336279459 1
1.6%
37.8014591158 1
1.6%
37.7538424164 1
1.6%
37.7431838577 1
1.6%
37.739208662 1
1.6%
37.7390199061 1
1.6%

WGS84경도
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.04293
Minimum126.6069
Maximum127.64064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-11T07:50:52.446916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6069
5-th percentile126.76239
Q1126.90356
median127.05619
Q3127.13101
95-th percentile127.43893
Maximum127.64064
Range1.0337346
Interquartile range (IQR)0.2274562

Descriptive statistics

Standard deviation0.20426488
Coefficient of variation (CV)0.0016078413
Kurtosis0.61694889
Mean127.04293
Median Absolute Deviation (MAD)0.11874024
Skewness0.57343256
Sum8003.7048
Variance0.041724141
MonotonicityNot monotonic
2023-12-11T07:50:52.593935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.5112051744 1
 
1.6%
127.4243423168 1
 
1.6%
126.8438689356 1
 
1.6%
126.8442895366 1
 
1.6%
127.2750841367 1
 
1.6%
126.9509318074 1
 
1.6%
127.0680539582 1
 
1.6%
127.1085702709 1
 
1.6%
127.4912334922 1
 
1.6%
127.6406364705 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
126.6069018961 1
1.6%
126.7226202082 1
1.6%
126.7481458171 1
1.6%
126.7604466371 1
1.6%
126.7798321687 1
1.6%
126.7875124505 1
1.6%
126.7960281955 1
1.6%
126.7999425034 1
1.6%
126.8105951315 1
1.6%
126.8133338254 1
1.6%
ValueCountFrequency (%)
127.6406364705 1
1.6%
127.5112051744 1
1.6%
127.4912334922 1
1.6%
127.4405533809 1
1.6%
127.4243423168 1
1.6%
127.3205402827 1
1.6%
127.2750841367 1
1.6%
127.2500113689 1
1.6%
127.2423884428 1
1.6%
127.212150464 1
1.6%

Sample

시군명시설명도로명 주소지번 주소우편번호전화번호FAX번호이용회원수종사자정원종사자현원-계종사자현원-남자종사자현원-여자종사자현원-정규직종사자현원-비정규직설치일자설치주체-지자체설치주체-민간운영주체-구분운영주체-법인(단체)명비고WGS84위도WGS84경도
0가평군가평군노인복지관경기도 가평군 가평읍 가화로 161경기도 가평군 가평읍 읍내리 625-8번지12413031-582-0763031-582-4181391422216159122012-01-19지자체 위탁<NA>재단법인가평군복지재단<NA>37.833628127.511205
1가평군청평노인복지관경기도 가평군 청평면 은고개로 39경기도 가평군 청평면 청평리 333-13번지 2층12452031-582-8879031-584-8879157655558476492019-12-26지자체 위탁<NA>재단법인재단법인 가평군복지재단<NA>37.739209127.424342
2고양시고양시대화노인종합복지관경기도 고양시 일산서구 일산로 778경기도 고양시 일산서구 대화동 2237번지10382031-917-1352031-917-13519665636245822402014-03-11지자체 위탁<NA>사회복지법인사회복지법인 효샘<NA>37.674473126.748146
3고양시고양시덕양노인종합복지관경기도 고양시 덕양구 어울림로 49경기도 고양시 덕양구 화정동 846번지10470031-969-7781031-969-7784284029592137935572000-10-04지자체 위탁<NA>사회복지법인사회복지법인 해피월드복지재단<NA>37.64847126.836884
4고양시고양시일산노인종합복지관경기도 고양시 일산동구 호수로 731경기도 고양시 일산동구 장항동 906번지10400031-961-4300031-961-4399399409494177732622000-04-20지자체 위탁<NA>사회복지법인사회복지법인 연꽃마을<NA>37.664465126.760447
5과천시과천시노인복지관경기도 과천시 문원로 57경기도 과천시 문원동 15-168번지1382802-502-850002-502-852242908383156827562001-02-08지자체 위탁<NA>사회복지법인사회복지법인 큰소망<NA>37.428064127.004199
6광명시광명시립소하노인복지관경기도 광명시 소하로 25경기도 광명시 소하동 1291번지1431502-2625-744402-2625-933011693969698726702009-07-01지자체 위탁<NA>사회복지법인사회복지법인 한기장복지재단<NA>37.452255126.884918
7광명시광명시립하안노인복지관경기도 광명시 철망산로 48경기도 광명시 하안동 683번지1424502-898-883002-898-19433938646475717472018-12-26지자체 위탁<NA>사단법인(사)함께하는사랑밭<NA>37.468009126.874227
8광주시광주시노인복지관경기도 광주시 파발로 202경기도 광주시 탄벌동 18-1번지12739031-766-9129031-766-926616907414163524172006-08-12지자체 위탁<NA>사회복지법인사회복지법인휴먼복지회<NA>37.416897127.250011
9군포시군포시노인복지관경기도 군포시 고산로 223경기도 군포시 당동 887번지15876031-399-2270031-399-22719931333392422111997-09-29지자체 위탁<NA>사회복지법인사회복지법인 기아대책<NA>37.345518126.947502
시군명시설명도로명 주소지번 주소우편번호전화번호FAX번호이용회원수종사자정원종사자현원-계종사자현원-남자종사자현원-여자종사자현원-정규직종사자현원-비정규직설치일자설치주체-지자체설치주체-민간운영주체-구분운영주체-법인(단체)명비고WGS84위도WGS84경도
53파주시파주시노인복지관경기도 파주시 가나무로 130경기도 파주시 금릉동 428번지10934031-943-0730031-943-07522574630113189530832005-03-04지자체 위탁<NA>사회복지법인사회복지법인 해피월드복지재단<NA>37.753842126.779832
54평택시팽성노인복지관경기도 평택시 팽성읍 팽성남산4길 6경기도 평택시 팽성읍 남산리 406-21번지17994031-660-7410031-618-864150017185131172009-05-20지자체 위탁<NA>재단법인재단법인 평택복지재단<NA>36.957641127.059543
55평택시평택남부노인복지관경기도 평택시 평택5로 220경기도 평택시 비전동 805번지17882031-8036-4910031-8036-49191000262742316112004-12-31지자체 위탁<NA>사회복지법인사회복지법인 연꽃마을<NA>36.998843127.102158
56평택시평택북부노인복지관경기도 평택시 서정로 295경기도 평택시 서정동 산12번지17730031-615-3918031-615-39921000252451911132006-03-10지자체 위탁<NA>재단법인재단법인 평택복지재단<NA>37.065785127.0665
57평택시평택서부노인복지관경기도 평택시 안중읍 서동대로 1557경기도 평택시 안중읍 학현리 501-2번지17816031-650-2637031-660-743944119214171292007-12-31지자체 위탁<NA>재단법인재단법인 대한성공회 유지재단<NA>36.989711126.922195
58포천시포천시노인복지관경기도 포천시 군내면 청성로 5경기도 포천시 군내면 하성북리 520-3번지 포천시노인복지관11151031-8083-7777031-8083-3336575218198111722010-05-13지자체 위탁<NA>사회복지법인사회복지법인 삼육재단<NA>37.905048127.21215
59하남시하남시노인복지관경기도 하남시 서하남로 488경기도 하남시 춘궁동 334-1번지13020031-790-6841031-790-621984491414311771998-12-24지자체 직영<NA>기타하남시청<NA>37.521982127.194051
60화성시화성시남부노인복지관경기도 화성시 향남읍 토성로 37-22경기도 화성시 향남읍 행정리 29-2번지18590031-366-5678031-8059-008610087797476718562008-11-08지자체 위탁<NA>사회복지법인평안밀알복지재단<NA>37.128216126.937445
61화성시화성시동탄노인복지관경기도 화성시 동탄대로8길 36경기도 화성시 산척동 726번지18501031-8077-1800031-8077-189945069090157521692011-01-07지자체 위탁<NA>학교법인일송학원<NA>37.170484127.110463
62화성시화성시서부노인복지관경기도 화성시 남양읍 시청로 155경기도 화성시 남양읍 남양리 2147번지 모두누림센터 4층18274031-8077-2605031-8077-26072899808047614662017-01-02지자체 위탁<NA>사회복지법인대한불교조계종사회복지재단<NA>37.198915126.828656