Overview

Dataset statistics

Number of variables19
Number of observations3745
Missing cells28517
Missing cells (%)40.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory610.9 KiB
Average record size in memory167.0 B

Variable types

Numeric8
Text2
Unsupported6
Categorical3

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15052/S/1/datasetView.do

Alerts

영업상태명 has constant value ""Constant
자격소유인원수 is highly overall correlated with 재개업일자 and 1 other fieldsHigh correlation
상세영업상태명 is highly overall correlated with 번호 and 8 other fieldsHigh correlation
번호 is highly overall correlated with 상세영업상태명High correlation
인허가일자 is highly overall correlated with 상세영업상태명High correlation
재개업일자 is highly overall correlated with 총인원수 and 3 other fieldsHigh correlation
입소정원 is highly overall correlated with 상세영업상태명High correlation
총인원수 is highly overall correlated with 재개업일자 and 1 other fieldsHigh correlation
위치정보(X) is highly overall correlated with 재개업일자 and 1 other fieldsHigh correlation
위치정보(Y) is highly overall correlated with 인허가번호 and 1 other fieldsHigh correlation
인허가번호 is highly overall correlated with 위치정보(Y) and 1 other fieldsHigh correlation
자격소유인원수 is highly imbalanced (71.8%)Imbalance
상세영업상태명 is highly imbalanced (93.6%)Imbalance
도로명전체주소 has 3745 (100.0%) missing valuesMissing
폐업일자 has 3745 (100.0%) missing valuesMissing
휴업시작일자 has 3745 (100.0%) missing valuesMissing
휴업종료일자 has 3745 (100.0%) missing valuesMissing
재개업일자 has 3725 (99.5%) missing valuesMissing
소재지면적 has 3745 (100.0%) missing valuesMissing
소재지우편번호 has 3745 (100.0%) missing valuesMissing
입소정원 has 58 (1.5%) missing valuesMissing
총인원수 has 450 (12.0%) missing valuesMissing
위치정보(X) has 907 (24.2%) missing valuesMissing
위치정보(Y) has 907 (24.2%) missing valuesMissing
입소정원 is highly skewed (γ1 = 45.9310573)Skewed
번호 has unique valuesUnique
도로명전체주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
입소정원 has 1317 (35.2%) zerosZeros
총인원수 has 2197 (58.7%) zerosZeros

Reproduction

Analysis started2024-03-13 12:57:09.658839
Analysis finished2024-03-13 12:57:20.768085
Duration11.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3745
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1873
Minimum1
Maximum3745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:20.859178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile188.2
Q1937
median1873
Q32809
95-th percentile3557.8
Maximum3745
Range3744
Interquartile range (IQR)1872

Descriptive statistics

Standard deviation1081.2327
Coefficient of variation (CV)0.5772732
Kurtosis-1.2
Mean1873
Median Absolute Deviation (MAD)936
Skewness0
Sum7014385
Variance1169064.2
MonotonicityStrictly increasing
2024-03-13T21:57:21.026166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2502 1
 
< 0.1%
2490 1
 
< 0.1%
2491 1
 
< 0.1%
2492 1
 
< 0.1%
2493 1
 
< 0.1%
2494 1
 
< 0.1%
2495 1
 
< 0.1%
2496 1
 
< 0.1%
2497 1
 
< 0.1%
Other values (3735) 3735
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3745 1
< 0.1%
3744 1
< 0.1%
3743 1
< 0.1%
3742 1
< 0.1%
3741 1
< 0.1%
3740 1
< 0.1%
3739 1
< 0.1%
3738 1
< 0.1%
3737 1
< 0.1%
3736 1
< 0.1%
Distinct3294
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size29.4 KiB
2024-03-13T21:57:21.339949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length9.0987984
Min length2

Characters and Unicode

Total characters34075
Distinct characters492
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3039 ?
Unique (%)81.1%

Sample

1st row백련산힐스테이트2차아파트경로당
2nd row백련산힐스테이트1차아파트경로당
3rd row구립양평3가경로당
4th row큰덕경로당
5th row마곡엠밸리6단지경로당
ValueCountFrequency (%)
경로당 591
 
12.8%
은평뉴타운 21
 
0.5%
현대아파트경로당 16
 
0.3%
장수경로당 15
 
0.3%
한신아파트경로당 14
 
0.3%
삼성아파트경로당 13
 
0.3%
구립 13
 
0.3%
아파트 12
 
0.3%
제2경로당 11
 
0.2%
중앙경로당 10
 
0.2%
Other values (3360) 3893
84.5%
2024-03-13T21:57:21.899104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3509
 
10.3%
3487
 
10.2%
3487
 
10.2%
2017
 
5.9%
1469
 
4.3%
1428
 
4.2%
865
 
2.5%
703
 
2.1%
) 547
 
1.6%
( 539
 
1.6%
Other values (482) 16024
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30452
89.4%
Decimal Number 1349
 
4.0%
Space Separator 865
 
2.5%
Close Punctuation 547
 
1.6%
Open Punctuation 539
 
1.6%
Uppercase Letter 196
 
0.6%
Lowercase Letter 66
 
0.2%
Other Punctuation 43
 
0.1%
Dash Punctuation 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3509
 
11.5%
3487
 
11.5%
3487
 
11.5%
2017
 
6.6%
1469
 
4.8%
1428
 
4.7%
703
 
2.3%
472
 
1.5%
419
 
1.4%
365
 
1.2%
Other values (431) 13096
43.0%
Uppercase Letter
ValueCountFrequency (%)
A 50
25.5%
S 23
11.7%
H 19
 
9.7%
L 16
 
8.2%
K 15
 
7.7%
C 14
 
7.1%
P 10
 
5.1%
D 8
 
4.1%
M 7
 
3.6%
I 7
 
3.6%
Other values (7) 27
13.8%
Lowercase Letter
ValueCountFrequency (%)
e 29
43.9%
l 8
 
12.1%
i 5
 
7.6%
s 4
 
6.1%
k 4
 
6.1%
v 3
 
4.5%
p 2
 
3.0%
r 2
 
3.0%
h 2
 
3.0%
a 1
 
1.5%
Other values (6) 6
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 412
30.5%
2 410
30.4%
3 178
13.2%
4 96
 
7.1%
5 72
 
5.3%
6 51
 
3.8%
7 37
 
2.7%
0 35
 
2.6%
9 30
 
2.2%
8 28
 
2.1%
Other Punctuation
ValueCountFrequency (%)
@ 30
69.8%
, 8
 
18.6%
. 4
 
9.3%
' 1
 
2.3%
Space Separator
ValueCountFrequency (%)
865
100.0%
Close Punctuation
ValueCountFrequency (%)
) 547
100.0%
Open Punctuation
ValueCountFrequency (%)
( 539
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30452
89.4%
Common 3361
 
9.9%
Latin 262
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3509
 
11.5%
3487
 
11.5%
3487
 
11.5%
2017
 
6.6%
1469
 
4.8%
1428
 
4.7%
703
 
2.3%
472
 
1.5%
419
 
1.4%
365
 
1.2%
Other values (431) 13096
43.0%
Latin
ValueCountFrequency (%)
A 50
19.1%
e 29
11.1%
S 23
 
8.8%
H 19
 
7.3%
L 16
 
6.1%
K 15
 
5.7%
C 14
 
5.3%
P 10
 
3.8%
l 8
 
3.1%
D 8
 
3.1%
Other values (23) 70
26.7%
Common
ValueCountFrequency (%)
865
25.7%
) 547
16.3%
( 539
16.0%
1 412
12.3%
2 410
12.2%
3 178
 
5.3%
4 96
 
2.9%
5 72
 
2.1%
6 51
 
1.5%
7 37
 
1.1%
Other values (8) 154
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30452
89.4%
ASCII 3623
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3509
 
11.5%
3487
 
11.5%
3487
 
11.5%
2017
 
6.6%
1469
 
4.8%
1428
 
4.7%
703
 
2.3%
472
 
1.5%
419
 
1.4%
365
 
1.2%
Other values (431) 13096
43.0%
ASCII
ValueCountFrequency (%)
865
23.9%
) 547
15.1%
( 539
14.9%
1 412
11.4%
2 410
11.3%
3 178
 
4.9%
4 96
 
2.6%
5 72
 
2.0%
6 51
 
1.4%
A 50
 
1.4%
Other values (41) 403
11.1%
Distinct3228
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Memory size29.4 KiB
2024-03-13T21:57:22.329659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length42
Mean length21.259012
Min length6

Characters and Unicode

Total characters79615
Distinct characters312
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2960 ?
Unique (%)79.0%

Sample

1st row서울특별시 은평구 응암동 백련산힐스테이트2차아파트
2nd row서울특별시 은평구 응암동
3rd row서울특별시 영등포구 양평동3가 36번지
4th row서울특별시 마포구 공덕동
5th row서울특별시 강서구 마곡동
ValueCountFrequency (%)
서울특별시 3744
 
24.9%
노원구 239
 
1.6%
강서구 238
 
1.6%
강남구 218
 
1.5%
구로구 194
 
1.3%
성북구 190
 
1.3%
영등포구 188
 
1.3%
서초구 178
 
1.2%
성동구 177
 
1.2%
마포구 175
 
1.2%
Other values (2964) 9466
63.1%
2024-03-13T21:57:22.965941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14939
18.8%
4520
 
5.7%
4355
 
5.5%
4044
 
5.1%
3789
 
4.8%
3744
 
4.7%
3744
 
4.7%
3744
 
4.7%
3228
 
4.1%
3177
 
4.0%
Other values (302) 30331
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50405
63.3%
Space Separator 14939
 
18.8%
Decimal Number 12644
 
15.9%
Dash Punctuation 1564
 
2.0%
Uppercase Letter 34
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Other Punctuation 9
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Lowercase Letter 3
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4520
 
9.0%
4355
 
8.6%
4044
 
8.0%
3789
 
7.5%
3744
 
7.4%
3744
 
7.4%
3744
 
7.4%
3228
 
6.4%
3177
 
6.3%
738
 
1.5%
Other values (270) 15322
30.4%
Uppercase Letter
ValueCountFrequency (%)
B 5
14.7%
L 5
14.7%
H 4
11.8%
C 4
11.8%
S 3
8.8%
K 3
8.8%
I 2
 
5.9%
D 2
 
5.9%
A 2
 
5.9%
V 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
1 2599
20.6%
2 1517
12.0%
3 1345
10.6%
4 1178
9.3%
0 1178
9.3%
5 1174
9.3%
7 1026
 
8.1%
6 999
 
7.9%
8 863
 
6.8%
9 765
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
. 1
 
11.1%
Lowercase Letter
ValueCountFrequency (%)
c 2
66.7%
e 1
33.3%
Space Separator
ValueCountFrequency (%)
14939
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1564
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50405
63.3%
Common 29173
36.6%
Latin 37
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4520
 
9.0%
4355
 
8.6%
4044
 
8.0%
3789
 
7.5%
3744
 
7.4%
3744
 
7.4%
3744
 
7.4%
3228
 
6.4%
3177
 
6.3%
738
 
1.5%
Other values (270) 15322
30.4%
Common
ValueCountFrequency (%)
14939
51.2%
1 2599
 
8.9%
- 1564
 
5.4%
2 1517
 
5.2%
3 1345
 
4.6%
4 1178
 
4.0%
0 1178
 
4.0%
5 1174
 
4.0%
7 1026
 
3.5%
6 999
 
3.4%
Other values (7) 1654
 
5.7%
Latin
ValueCountFrequency (%)
B 5
13.5%
L 5
13.5%
H 4
10.8%
C 4
10.8%
S 3
8.1%
K 3
8.1%
I 2
 
5.4%
D 2
 
5.4%
c 2
 
5.4%
A 2
 
5.4%
Other values (5) 5
13.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50405
63.3%
ASCII 29210
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14939
51.1%
1 2599
 
8.9%
- 1564
 
5.4%
2 1517
 
5.2%
3 1345
 
4.6%
4 1178
 
4.0%
0 1178
 
4.0%
5 1174
 
4.0%
7 1026
 
3.5%
6 999
 
3.4%
Other values (22) 1691
 
5.8%
Hangul
ValueCountFrequency (%)
4520
 
9.0%
4355
 
8.6%
4044
 
8.0%
3789
 
7.5%
3744
 
7.4%
3744
 
7.4%
3744
 
7.4%
3228
 
6.4%
3177
 
6.3%
738
 
1.5%
Other values (270) 15322
30.4%

도로명전체주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3745
Missing (%)100.0%
Memory size33.0 KiB

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2192
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19991198
Minimum18001021
Maximum20180410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:23.170584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18001021
5-th percentile19840138
Q119911125
median20001230
Q320070501
95-th percentile20130423
Maximum20180410
Range2179389
Interquartile range (IQR)159376

Descriptive statistics

Standard deviation100858.24
Coefficient of variation (CV)0.0050451325
Kurtosis40.186553
Mean19991198
Median Absolute Deviation (MAD)70619
Skewness-2.5358487
Sum7.4867037 × 1010
Variance1.0172385 × 1010
MonotonicityNot monotonic
2024-03-13T21:57:23.366820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19890601 104
 
2.8%
20080111 104
 
2.8%
19890630 76
 
2.0%
20080109 65
 
1.7%
20080110 64
 
1.7%
19890706 52
 
1.4%
20080108 40
 
1.1%
20071126 40
 
1.1%
19890701 38
 
1.0%
19890501 37
 
1.0%
Other values (2182) 3125
83.4%
ValueCountFrequency (%)
18001021 1
< 0.1%
19580101 1
< 0.1%
19600701 1
< 0.1%
19610531 1
< 0.1%
19611101 1
< 0.1%
19620701 1
< 0.1%
19630603 1
< 0.1%
19630613 1
< 0.1%
19640327 1
< 0.1%
19650101 1
< 0.1%
ValueCountFrequency (%)
20180410 1
< 0.1%
20180406 1
< 0.1%
20180404 1
< 0.1%
20180326 1
< 0.1%
20180313 1
< 0.1%
20180228 1
< 0.1%
20180219 1
< 0.1%
20180213 2
0.1%
20180119 2
0.1%
20180110 1
< 0.1%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size29.4 KiB
운영중
3745 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 3745
100.0%

Length

2024-03-13T21:57:23.525782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:57:23.662776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 3745
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3745
Missing (%)100.0%
Memory size33.0 KiB

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3745
Missing (%)100.0%
Memory size33.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3745
Missing (%)100.0%
Memory size33.0 KiB

재개업일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct20
Distinct (%)100.0%
Missing3725
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean20068143
Minimum19810315
Maximum20180405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:23.775911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19810315
5-th percentile19924992
Q120012953
median20106107
Q320150156
95-th percentile20171686
Maximum20180405
Range370090
Interquartile range (IQR)137203.75

Descriptive statistics

Standard deviation101129.28
Coefficient of variation (CV)0.0050392946
Kurtosis0.4796333
Mean20068143
Median Absolute Deviation (MAD)55069
Skewness-1.048947
Sum4.0136286 × 108
Variance1.0227132 × 1010
MonotonicityNot monotonic
2024-03-13T21:57:23.935969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20150601 1
 
< 0.1%
20150101 1
 
< 0.1%
20080115 1
 
< 0.1%
20150323 1
 
< 0.1%
20171227 1
 
< 0.1%
20140313 1
 
< 0.1%
20180405 1
 
< 0.1%
20040513 1
 
< 0.1%
19931028 1
 
< 0.1%
20120913 1
 
< 0.1%
Other values (10) 10
 
0.3%
(Missing) 3725
99.5%
ValueCountFrequency (%)
19810315 1
< 0.1%
19931028 1
< 0.1%
19950113 1
< 0.1%
19950513 1
< 0.1%
19960605 1
< 0.1%
20030402 1
< 0.1%
20040513 1
< 0.1%
20040923 1
< 0.1%
20080115 1
< 0.1%
20101103 1
< 0.1%
ValueCountFrequency (%)
20180405 1
< 0.1%
20171227 1
< 0.1%
20151125 1
< 0.1%
20150601 1
< 0.1%
20150323 1
< 0.1%
20150101 1
< 0.1%
20141112 1
< 0.1%
20140313 1
< 0.1%
20120913 1
< 0.1%
20111111 1
< 0.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3745
Missing (%)100.0%
Memory size33.0 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3745
Missing (%)100.0%
Memory size33.0 KiB

입소정원
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED  ZEROS 

Distinct140
Distinct (%)3.8%
Missing58
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean29.656903
Minimum0
Maximum4085
Zeros1317
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:24.176709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median25
Q343
95-th percentile84
Maximum4085
Range4085
Interquartile range (IQR)43

Descriptive statistics

Standard deviation73.383363
Coefficient of variation (CV)2.4744109
Kurtosis2531.6839
Mean29.656903
Median Absolute Deviation (MAD)25
Skewness45.931057
Sum109345
Variance5385.118
MonotonicityNot monotonic
2024-03-13T21:57:24.395645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1317
35.2%
30 146
 
3.9%
20 133
 
3.6%
25 108
 
2.9%
40 107
 
2.9%
50 104
 
2.8%
22 80
 
2.1%
23 65
 
1.7%
35 64
 
1.7%
21 62
 
1.7%
Other values (130) 1501
40.1%
ValueCountFrequency (%)
0 1317
35.2%
1 8
 
0.2%
2 1
 
< 0.1%
3 5
 
0.1%
5 1
 
< 0.1%
10 3
 
0.1%
14 1
 
< 0.1%
15 3
 
0.1%
16 1
 
< 0.1%
18 3
 
0.1%
ValueCountFrequency (%)
4085 1
< 0.1%
363 1
< 0.1%
275 1
< 0.1%
215 1
< 0.1%
214 1
< 0.1%
200 1
< 0.1%
195 1
< 0.1%
180 1
< 0.1%
165 2
0.1%
163 1
< 0.1%

자격소유인원수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.4 KiB
0
3271 
<NA>
466 
1
 
7
2
 
1

Length

Max length4
Median length1
Mean length1.3732977
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 3271
87.3%
<NA> 466
 
12.4%
1 7
 
0.2%
2 1
 
< 0.1%

Length

2024-03-13T21:57:24.580837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:57:25.222099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3271
87.3%
na 466
 
12.4%
1 7
 
0.2%
2 1
 
< 0.1%

총인원수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct97
Distinct (%)2.9%
Missing450
Missing (%)12.0%
Infinite0
Infinite (%)0.0%
Mean6.5314112
Minimum0
Maximum165
Zeros2197
Zeros (%)58.7%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:25.381226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile45
Maximum165
Range165
Interquartile range (IQR)1

Descriptive statistics

Standard deviation18.458214
Coefficient of variation (CV)2.8260683
Kurtosis17.078238
Mean6.5314112
Median Absolute Deviation (MAD)0
Skewness3.8227525
Sum21521
Variance340.70568
MonotonicityNot monotonic
2024-03-13T21:57:25.539927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2197
58.7%
1 416
 
11.1%
2 136
 
3.6%
3 68
 
1.8%
30 27
 
0.7%
60 23
 
0.6%
22 23
 
0.6%
24 21
 
0.6%
25 21
 
0.6%
20 21
 
0.6%
Other values (87) 342
 
9.1%
(Missing) 450
 
12.0%
ValueCountFrequency (%)
0 2197
58.7%
1 416
 
11.1%
2 136
 
3.6%
3 68
 
1.8%
4 5
 
0.1%
5 16
 
0.4%
6 2
 
0.1%
20 21
 
0.6%
21 21
 
0.6%
22 23
 
0.6%
ValueCountFrequency (%)
165 1
 
< 0.1%
145 1
 
< 0.1%
144 1
 
< 0.1%
139 1
 
< 0.1%
138 1
 
< 0.1%
135 2
0.1%
128 1
 
< 0.1%
126 1
 
< 0.1%
122 1
 
< 0.1%
120 4
0.1%

위치정보(X)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2621
Distinct (%)92.4%
Missing907
Missing (%)24.2%
Infinite0
Infinite (%)0.0%
Mean198846.38
Minimum182159.3
Maximum215422.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:25.704051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182159.3
5-th percentile185971.91
Q1191810.14
median200941.36
Q3205170.64
95-th percentile210587.12
Maximum215422.75
Range33263.442
Interquartile range (IQR)13360.509

Descriptive statistics

Standard deviation7840.8756
Coefficient of variation (CV)0.039431824
Kurtosis-1.0784102
Mean198846.38
Median Absolute Deviation (MAD)6032.5629
Skewness-0.2070571
Sum5.6432603 × 108
Variance61479330
MonotonicityNot monotonic
2024-03-13T21:57:25.900365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193998.104669 9
 
0.2%
192855.685644 5
 
0.1%
202240.553902 4
 
0.1%
200551.396284 4
 
0.1%
206101.913844 4
 
0.1%
204321.927324 3
 
0.1%
204418.836684 3
 
0.1%
195045.515108 3
 
0.1%
208851.688285 3
 
0.1%
209744.789378 3
 
0.1%
Other values (2611) 2797
74.7%
(Missing) 907
 
24.2%
ValueCountFrequency (%)
182159.304087 1
< 0.1%
182405.42605 1
< 0.1%
182742.537963 1
< 0.1%
182801.35478 1
< 0.1%
182859.059693 1
< 0.1%
182882.878688 1
< 0.1%
182929.561796 1
< 0.1%
182945.351625 1
< 0.1%
182977.186875 1
< 0.1%
182984.581165 1
< 0.1%
ValueCountFrequency (%)
215422.74612 1
< 0.1%
215223.60463 1
< 0.1%
215104.181061 1
< 0.1%
215097.641078 1
< 0.1%
214913.822718 1
< 0.1%
214912.807517 1
< 0.1%
213902.813009 1
< 0.1%
213749.143548 1
< 0.1%
213670.115208 1
< 0.1%
213646.900696 1
< 0.1%

위치정보(Y)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2621
Distinct (%)92.4%
Missing907
Missing (%)24.2%
Infinite0
Infinite (%)0.0%
Mean450240.4
Minimum436993.64
Maximum465314.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:26.097264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum436993.64
5-th percentile441565.79
Q1445125.99
median449559.8
Q3454843.95
95-th percentile461537.32
Maximum465314.41
Range28320.768
Interquartile range (IQR)9717.961

Descriptive statistics

Standard deviation6207.0626
Coefficient of variation (CV)0.013786107
Kurtosis-0.74309536
Mean450240.4
Median Absolute Deviation (MAD)4739.7757
Skewness0.348025
Sum1.2777823 × 109
Variance38527626
MonotonicityNot monotonic
2024-03-13T21:57:26.310517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453150.854122 9
 
0.2%
439663.585571 5
 
0.1%
447598.16242 4
 
0.1%
445806.025612 4
 
0.1%
452155.691149 4
 
0.1%
447244.33957 3
 
0.1%
439958.443579 3
 
0.1%
443011.455008 3
 
0.1%
448904.553298 3
 
0.1%
446601.107402 3
 
0.1%
Other values (2611) 2797
74.7%
(Missing) 907
 
24.2%
ValueCountFrequency (%)
436993.641744 1
< 0.1%
437488.324222 2
0.1%
437684.82988 1
< 0.1%
437926.789074 1
< 0.1%
438018.443263 1
< 0.1%
438423.909375 1
< 0.1%
438460.66732 2
0.1%
438525.414483 1
< 0.1%
438580.148239 2
0.1%
438583.251827 2
0.1%
ValueCountFrequency (%)
465314.409287 1
< 0.1%
465282.682615 1
< 0.1%
465165.043328 1
< 0.1%
465025.246647 1
< 0.1%
464905.033087 2
0.1%
464832.867314 1
< 0.1%
464814.717432 1
< 0.1%
464663.321565 1
< 0.1%
464588.079484 1
< 0.1%
464514.89393 1
< 0.1%

인허가번호
Real number (ℝ)

HIGH CORRELATION 

Distinct3744
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1252582 × 1015
Minimum1
Maximum3.2400002 × 1015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.0 KiB
2024-03-13T21:57:26.648308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.0200002 × 1015
Q13.0700002 × 1015
median3.1300002 × 1015
Q33.1900001 × 1015
95-th percentile3.2300002 × 1015
Maximum3.2400002 × 1015
Range3.2400002 × 1015
Interquartile range (IQR)1.1999991 × 1014

Descriptive statistics

Standard deviation1.3674335 × 1014
Coefficient of variation (CV)0.043754258
Kurtosis374.66682
Mean3.1252582 × 1015
Median Absolute Deviation (MAD)5.999991 × 1013
Skewness-16.792421
Sum-6.7426522 × 1018
Variance1.8698745 × 1028
MonotonicityNot monotonic
2024-03-13T21:57:26.871855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200100001 2
 
0.1%
3070000200600045 1
 
< 0.1%
3070000200700027 1
 
< 0.1%
3070000200700033 1
 
< 0.1%
3070000200500075 1
 
< 0.1%
3070000200600008 1
 
< 0.1%
3070000200600009 1
 
< 0.1%
3070000200600010 1
 
< 0.1%
3070000200600011 1
 
< 0.1%
3070000200600017 1
 
< 0.1%
Other values (3734) 3734
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
199900001 1
< 0.1%
200000001 1
< 0.1%
200100001 2
0.1%
1111111111111111 1
< 0.1%
3000000196000001 1
< 0.1%
3000000196200001 1
< 0.1%
3000000196400001 1
< 0.1%
3000000196600001 1
< 0.1%
3000000196700001 1
< 0.1%
ValueCountFrequency (%)
3240000201800004 1
< 0.1%
3240000201800003 1
< 0.1%
3240000201700012 1
< 0.1%
3240000201700011 1
< 0.1%
3240000201700010 1
< 0.1%
3240000201700002 1
< 0.1%
3240000201600008 1
< 0.1%
3240000201600002 1
< 0.1%
3240000201400005 1
< 0.1%
3240000201400001 1
< 0.1%

상세영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size29.4 KiB
운영
3717 
<NA>
 
28

Length

Max length4
Median length2
Mean length2.0149533
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영 3717
99.3%
<NA> 28
 
0.7%

Length

2024-03-13T21:57:27.065266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:57:27.219304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 3717
99.3%
na 28
 
0.7%

Interactions

2024-03-13T21:57:18.976330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:11.216994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.262454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.319238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.276242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.380673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:16.830194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.936058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.099330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:11.342718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.376282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.435919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.401344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.513595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:16.964967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.075409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.216457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:11.495616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.499657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.537166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.535577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.617265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.089737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.200021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.342148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:11.617080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.632018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.668699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.646281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.760828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.246384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.331808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.495774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:11.748755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.834705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.781111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.774520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.887788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.419947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.490374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.639168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:11.880522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.967602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.936568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.918260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:16.021710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.554788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.594916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.801477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.005119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.099907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.052164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.091288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:16.170194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.665541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.717211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:19.934027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:12.120268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:13.203157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:14.169850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:15.245753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:16.319481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:17.795187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:57:18.839824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:57:27.311258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호인허가일자재개업일자입소정원자격소유인원수총인원수위치정보(X)위치정보(Y)인허가번호
번호1.0000.2600.3830.0000.0000.3870.8090.7890.055
인허가일자0.2601.0000.5150.0000.0500.2010.1730.2300.000
재개업일자0.3830.5151.000NaNNaN0.0000.0000.350NaN
입소정원0.0000.000NaN1.0000.0000.0000.0000.0000.000
자격소유인원수0.0000.050NaN0.0001.0000.0000.0000.0550.000
총인원수0.3870.2010.0000.0000.0001.0000.3570.2930.000
위치정보(X)0.8090.1730.0000.0000.0000.3571.0000.6190.000
위치정보(Y)0.7890.2300.3500.0000.0550.2930.6191.0000.046
인허가번호0.0550.000NaN0.0000.0000.0000.0000.0461.000
2024-03-13T21:57:27.493242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자격소유인원수상세영업상태명
자격소유인원수1.0001.000
상세영업상태명1.0001.000
2024-03-13T21:57:27.624925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호인허가일자재개업일자입소정원총인원수위치정보(X)위치정보(Y)인허가번호자격소유인원수상세영업상태명
번호1.0000.1060.239-0.0020.1460.248-0.0530.0000.0001.000
인허가일자0.1061.0000.247-0.2580.092-0.090-0.0200.0450.0001.000
재개업일자0.2390.2471.0000.0210.5660.837-0.319-0.0051.0001.000
입소정원-0.002-0.2580.0211.0000.1330.1260.0260.0550.0001.000
총인원수0.1460.0920.5660.1331.0000.158-0.062-0.0910.0001.000
위치정보(X)0.248-0.0900.8370.1260.1581.0000.283-0.1460.0001.000
위치정보(Y)-0.053-0.020-0.3190.026-0.0620.2831.000-0.6450.0421.000
인허가번호0.0000.045-0.0050.055-0.091-0.146-0.6451.0000.0001.000
자격소유인원수0.0000.0001.0000.0000.0000.0000.0420.0001.0001.000
상세영업상태명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-03-13T21:57:20.115708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:57:20.410938image/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.
2024-03-13T21:57:20.658380image/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

번호사업장명소재지전체주소도로명전체주소인허가일자영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지면적소재지우편번호입소정원자격소유인원수총인원수위치정보(X)위치정보(Y)인허가번호상세영업상태명
01백련산힐스테이트2차아파트경로당서울특별시 은평구 응암동 백련산힐스테이트2차아파트<NA>20121009운영중<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3110000201600012운영
12백련산힐스테이트1차아파트경로당서울특별시 은평구 응암동<NA>20131121운영중<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA>3110000201500015운영
23구립양평3가경로당서울특별시 영등포구 양평동3가 36번지<NA>19890706운영중<NA><NA><NA><NA><NA><NA>0<NA><NA>189979.778775447187.5807253180000201500006운영
34큰덕경로당서울특별시 마포구 공덕동<NA>20111014운영중<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA>3130000201600006운영
45마곡엠밸리6단지경로당서울특별시 강서구 마곡동<NA>20160801운영중<NA><NA><NA><NA><NA><NA>58<NA><NA><NA><NA>3150000201600015운영
56흐능날 경로당서울특별시 서초구 내곡동 1-3026번지<NA>20160616운영중<NA><NA><NA><NA><NA><NA>25<NA><NA>207370.085715440099.0638393210000201600004운영
67공덕자이제2경로당서울특별시 마포구 아현동<NA>20160629운영중<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA>3130000201600009운영
78마곡엠밸리3단지 경로당서울특별시 강서구 마곡동<NA>20161028운영중<NA><NA><NA><NA><NA><NA>23<NA><NA><NA><NA>3150000201600021운영
89북한산푸르지오아파트경로당서울특별시 은평구 녹번동<NA>20160125운영중<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA>3110000201600001운영
910신대방벽산아파트경로당서울특별시 동작구 신대방동<NA>20130326운영중<NA><NA><NA><NA><NA><NA>0<NA><NA><NA><NA>3190000201300003<NA>
번호사업장명소재지전체주소도로명전체주소인허가일자영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지면적소재지우편번호입소정원자격소유인원수총인원수위치정보(X)위치정보(Y)인허가번호상세영업상태명
37353736SH공사공덕2차삼성아파트 경로당서울특별시 마포구 공덕동<NA>20150203운영중<NA><NA><NA><NA><NA><NA>36<NA><NA><NA><NA>3130000201800008운영
37363737창전삼성(아)경로당서울특별시 마포구 창전동 창전동삼성아파트<NA>20060117운영중<NA><NA><NA><NA><NA><NA>22<NA><NA><NA><NA>3130000201800009운영
37373738한강밤섬자이아파트 경로당서울특별시 마포구 하중동 한강밤섬자이<NA>20120709운영중<NA><NA><NA><NA><NA><NA>29<NA><NA><NA><NA>3130000201800010운영
37383739공덕5차래미안아파트A 경로당서울특별시 마포구 공덕동 래미안 공덕5차<NA>20120118운영중<NA><NA><NA><NA><NA><NA>28<NA><NA><NA><NA>3130000201800011운영
37393740월드컵아이파크106동 경로당서울특별시 마포구 성산동 월드컵아이파크<NA>20121126운영중<NA><NA><NA><NA><NA><NA>30<NA><NA><NA><NA>3130000201800012운영
37403741상암월드컵파크11단지 경로당서울특별시 마포구 상암동 상암월드컵파크11단지<NA>20121024운영중<NA><NA><NA><NA><NA><NA>36<NA><NA><NA><NA>3130000201800013운영
37413742상암월드컵파크12단지(아)경로당서울특별시 마포구 상암동 상암월드컵파크12단지<NA>20110414운영중<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3130000201800014운영
37423743아현 아이파크 경로당서울특별시 마포구 아현동 104동<NA>20180406운영중<NA><NA><NA><NA><NA><NA>23<NA><NA><NA><NA>3130000201800004운영
37433744구파발10단 제3경로당서울특별시 은평구 진관동 은평뉴타운구파발<NA>20121212운영중<NA><NA><NA><NA><NA><NA>22<NA><NA><NA><NA>3110000201800003운영
37443745정릉꿈에그린(아)경로당서울특별시 성북구 정릉동 정릉꿈에그린<NA>20170808운영중<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>3070000201800004운영