Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells7
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory566.4 KiB
Average record size in memory58.0 B

Variable types

Text3
Categorical1
Numeric2

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15819/S/1/datasetView.do

Reproduction

Analysis started2024-05-11 02:40:09.930417
Analysis finished2024-05-11 02:40:15.199049
Duration5.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2052
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:40:15.600006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.221
Min length2

Characters and Unicode

Total characters72210
Distinct characters429
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)2.0%

Sample

1st row상계한신
2nd row장안현대힐스테이트
3rd row상계은빛2단지
4th row신사두산위브
5th row개봉현대홈타운2단지
ValueCountFrequency (%)
아파트 109
 
1.0%
래미안 32
 
0.3%
목동7단지 27
 
0.3%
마포래미안푸르지오 22
 
0.2%
상계주공7단지 22
 
0.2%
입주자대표회의 22
 
0.2%
마곡엠밸리6단지 21
 
0.2%
힐스테이트 20
 
0.2%
금천롯데캐슬골드파크1차아파트 20
 
0.2%
공덕래미안5차 20
 
0.2%
Other values (2108) 10192
97.0%
2024-05-11T02:40:17.181491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2265
 
3.1%
파 2214
 
3.1%
지 2072
 
2.9%
트 2011
 
2.8%
대 1766
 
2.4%
단 1683
 
2.3%
동 1560
 
2.2%
차 1444
 
2.0%
신 1419
 
2.0%
성 1319
 
1.8%
Other values (419) 54457
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66009
91.4%
Decimal Number 4023
 
5.6%
Uppercase Letter 790
 
1.1%
Space Separator 554
 
0.8%
Lowercase Letter 241
 
0.3%
Open Punctuation 163
 
0.2%
Close Punctuation 163
 
0.2%
Other Punctuation 161
 
0.2%
Dash Punctuation 89
 
0.1%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2265
 
3.4%
파 2214
 
3.4%
지 2072
 
3.1%
트 2011
 
3.0%
대 1766
 
2.7%
단 1683
 
2.5%
동 1560
 
2.4%
차 1444
 
2.2%
신 1419
 
2.1%
성 1319
 
2.0%
Other values (373) 48256
73.1%
Uppercase Letter
ValueCountFrequency (%)
S 157
19.9%
K 127
16.1%
C 92
11.6%
H 59
 
7.5%
L 56
 
7.1%
M 50
 
6.3%
D 50
 
6.3%
I 35
 
4.4%
E 35
 
4.4%
G 29
 
3.7%
Other values (7) 100
12.7%
Lowercase Letter
ValueCountFrequency (%)
e 167
69.3%
i 16
 
6.6%
l 16
 
6.6%
v 11
 
4.6%
s 7
 
2.9%
k 5
 
2.1%
w 5
 
2.1%
c 4
 
1.7%
h 4
 
1.7%
g 3
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 1188
29.5%
2 1071
26.6%
3 535
13.3%
4 268
 
6.7%
5 245
 
6.1%
6 223
 
5.5%
7 171
 
4.3%
9 127
 
3.2%
8 105
 
2.6%
0 90
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 149
92.5%
. 12
 
7.5%
Space Separator
ValueCountFrequency (%)
554
100.0%
Open Punctuation
ValueCountFrequency (%)
( 163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66009
91.4%
Common 5161
 
7.1%
Latin 1040
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2265
 
3.4%
파 2214
 
3.4%
지 2072
 
3.1%
트 2011
 
3.0%
대 1766
 
2.7%
단 1683
 
2.5%
동 1560
 
2.4%
차 1444
 
2.2%
신 1419
 
2.1%
성 1319
 
2.0%
Other values (373) 48256
73.1%
Latin
ValueCountFrequency (%)
e 167
16.1%
S 157
15.1%
K 127
12.2%
C 92
8.8%
H 59
 
5.7%
L 56
 
5.4%
M 50
 
4.8%
D 50
 
4.8%
I 35
 
3.4%
E 35
 
3.4%
Other values (19) 212
20.4%
Common
ValueCountFrequency (%)
1 1188
23.0%
2 1071
20.8%
554
10.7%
3 535
10.4%
4 268
 
5.2%
5 245
 
4.7%
6 223
 
4.3%
7 171
 
3.3%
( 163
 
3.2%
) 163
 
3.2%
Other values (7) 580
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66009
91.4%
ASCII 6192
 
8.6%
Number Forms 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2265
 
3.4%
파 2214
 
3.4%
지 2072
 
3.1%
트 2011
 
3.0%
대 1766
 
2.7%
단 1683
 
2.5%
동 1560
 
2.4%
차 1444
 
2.2%
신 1419
 
2.1%
성 1319
 
2.0%
Other values (373) 48256
73.1%
ASCII
ValueCountFrequency (%)
1 1188
19.2%
2 1071
17.3%
554
 
8.9%
3 535
 
8.6%
4 268
 
4.3%
5 245
 
4.0%
6 223
 
3.6%
7 171
 
2.8%
e 167
 
2.7%
( 163
 
2.6%
Other values (35) 1607
26.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

아파트코드
Text

Distinct2058
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:40:17.963023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters90000
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique199 ?
Unique (%)2.0%

Sample

1st rowA13983608
2nd rowA13010004
3rd rowA13983815
4th rowA12208001
5th rowA15209206
ValueCountFrequency (%)
a15805115 27
 
0.3%
a12175203 22
 
0.2%
a13982704 22
 
0.2%
a15721006 21
 
0.2%
a12170603 20
 
0.2%
a10027188 20
 
0.2%
a10026748 18
 
0.2%
a13084804 18
 
0.2%
a13822004 18
 
0.2%
a13527203 17
 
0.2%
Other values (2048) 9797
98.0%
2024-05-11T02:40:19.041686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18345
20.4%
1 17511
19.5%
A 9990
11.1%
3 8854
9.8%
2 8168
9.1%
5 6079
 
6.8%
8 5684
 
6.3%
7 5134
 
5.7%
4 3855
 
4.3%
6 3353
 
3.7%
Other values (2) 3027
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
88.9%
Uppercase Letter 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18345
22.9%
1 17511
21.9%
3 8854
11.1%
2 8168
10.2%
5 6079
 
7.6%
8 5684
 
7.1%
7 5134
 
6.4%
4 3855
 
4.8%
6 3353
 
4.2%
9 3017
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9990
99.9%
B 10
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 80000
88.9%
Latin 10000
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18345
22.9%
1 17511
21.9%
3 8854
11.1%
2 8168
10.2%
5 6079
 
7.6%
8 5684
 
7.1%
7 5134
 
6.4%
4 3855
 
4.8%
6 3353
 
4.2%
9 3017
 
3.8%
Latin
ValueCountFrequency (%)
A 9990
99.9%
B 10
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18345
20.4%
1 17511
19.5%
A 9990
11.1%
3 8854
9.8%
2 8168
9.1%
5 6079
 
6.8%
8 5684
 
6.3%
7 5134
 
5.7%
4 3855
 
4.3%
6 3353
 
3.7%
Other values (2) 3027
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3898 
광고료수익
1100 
승강기수익
1000 
잡수익
979 
주차장수익
798 
Other values (10)
2225 

Length

Max length9
Median length5
Mean length4.8913
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고용안정사업수익
2nd row연체료수익
3rd row승강기수익
4th row잡수익
5th row승강기수익

Common Values

ValueCountFrequency (%)
연체료수익 3898
39.0%
광고료수익 1100
 
11.0%
승강기수익 1000
 
10.0%
잡수익 979
 
9.8%
주차장수익 798
 
8.0%
기타운영수익 683
 
6.8%
검침수익 310
 
3.1%
임대료수익 239
 
2.4%
재활용품수익 234
 
2.3%
알뜰시장수익 216
 
2.2%
Other values (5) 543
 
5.4%

Length

2024-05-11T02:40:19.502062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3898
39.0%
광고료수익 1100
 
11.0%
승강기수익 1000
 
10.0%
잡수익 979
 
9.8%
주차장수익 798
 
8.0%
기타운영수익 683
 
6.8%
검침수익 310
 
3.1%
임대료수익 239
 
2.4%
재활용품수익 234
 
2.3%
알뜰시장수익 216
 
2.2%
Other values (5) 543
 
5.4%

년월일
Real number (ℝ)

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190217
Minimum20190201
Maximum20190228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:40:20.101316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190201
5-th percentile20190201
Q120190211
median20190219
Q320190225
95-th percentile20190228
Maximum20190228
Range27
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.4994522
Coefficient of variation (CV)4.2096883 × 10-7
Kurtosis-1.043263
Mean20190217
Median Absolute Deviation (MAD)7
Skewness-0.3967599
Sum2.0190217 × 1011
Variance72.240687
MonotonicityNot monotonic
2024-05-11T02:40:20.517633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20190228 1289
 
12.9%
20190225 701
 
7.0%
20190227 641
 
6.4%
20190201 632
 
6.3%
20190211 599
 
6.0%
20190226 564
 
5.6%
20190207 526
 
5.3%
20190220 455
 
4.5%
20190218 447
 
4.5%
20190208 414
 
4.1%
Other values (18) 3732
37.3%
ValueCountFrequency (%)
20190201 632
6.3%
20190202 150
 
1.5%
20190203 74
 
0.7%
20190204 71
 
0.7%
20190205 37
 
0.4%
20190206 84
 
0.8%
20190207 526
5.3%
20190208 414
4.1%
20190209 94
 
0.9%
20190210 88
 
0.9%
ValueCountFrequency (%)
20190228 1289
12.9%
20190227 641
6.4%
20190226 564
5.6%
20190225 701
7.0%
20190224 181
 
1.8%
20190223 172
 
1.7%
20190222 408
 
4.1%
20190221 385
 
3.9%
20190220 455
 
4.5%
20190219 344
 
3.4%

금액
Real number (ℝ)

Distinct3430
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean221244.97
Minimum-4309260
Maximum50255760
Zeros12
Zeros (%)0.1%
Negative43
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:40:20.956336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4309260
5-th percentile210
Q13220
median30000
Q3100000
95-th percentile900000
Maximum50255760
Range54565020
Interquartile range (IQR)96780

Descriptive statistics

Standard deviation1165926.7
Coefficient of variation (CV)5.2698449
Kurtosis610.02915
Mean221244.97
Median Absolute Deviation (MAD)28695
Skewness19.781826
Sum2.2124497 × 109
Variance1.3593851 × 1012
MonotonicityNot monotonic
2024-05-11T02:40:21.403909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 629
 
6.3%
50000 618
 
6.2%
100000 486
 
4.9%
70000 173
 
1.7%
60000 155
 
1.6%
80000 131
 
1.3%
150000 130
 
1.3%
20000 129
 
1.3%
40000 127
 
1.3%
200000 113
 
1.1%
Other values (3420) 7309
73.1%
ValueCountFrequency (%)
-4309260 1
< 0.1%
-1890000 1
< 0.1%
-1505000 1
< 0.1%
-900000 1
< 0.1%
-300000 2
< 0.1%
-290600 1
< 0.1%
-275000 1
< 0.1%
-240000 1
< 0.1%
-215000 1
< 0.1%
-210000 1
< 0.1%
ValueCountFrequency (%)
50255760 1
< 0.1%
41561460 1
< 0.1%
27078260 1
< 0.1%
24921464 1
< 0.1%
22821576 1
< 0.1%
22127511 1
< 0.1%
20000000 1
< 0.1%
17785000 1
< 0.1%
16696917 1
< 0.1%
15544290 1
< 0.1%

내용
Text

Distinct5548
Distinct (%)55.5%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:40:22.204361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length74
Mean length13.308716
Min length2

Characters and Unicode

Total characters132994
Distinct characters731
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5333 ?
Unique (%)53.4%

Sample

1st row일자리안정자금
2nd row관리비 연체료 수납
3rd row승강기 사용료208-708공사
4th row산재,고용보험료 자동이체할인액
5th row211-2302호 승강기사용료(세대전출)
ValueCountFrequency (%)
관리비 4035
 
15.7%
수납 3908
 
15.2%
연체료 3908
 
15.2%
2월분 363
 
1.4%
승강기사용료 243
 
0.9%
승강기 242
 
0.9%
2월 229
 
0.9%
1월분 221
 
0.9%
사용료 194
 
0.8%
190
 
0.7%
Other values (6881) 12241
47.5%
2024-05-11T02:40:23.614666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15906
 
12.0%
료 6034
 
4.5%
수 5309
 
4.0%
1 4717
 
3.5%
비 4693
 
3.5%
리 4642
 
3.5%
관 4189
 
3.1%
0 4183
 
3.1%
체 4114
 
3.1%
연 3977
 
3.0%
Other values (721) 75230
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87235
65.6%
Decimal Number 18982
 
14.3%
Space Separator 15906
 
12.0%
Open Punctuation 2698
 
2.0%
Close Punctuation 2698
 
2.0%
Other Punctuation 2294
 
1.7%
Dash Punctuation 2133
 
1.6%
Uppercase Letter 584
 
0.4%
Math Symbol 257
 
0.2%
Lowercase Letter 160
 
0.1%
Other values (2) 47
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 6034
 
6.9%
수 5309
 
6.1%
비 4693
 
5.4%
리 4642
 
5.3%
관 4189
 
4.8%
체 4114
 
4.7%
연 3977
 
4.6%
납 3950
 
4.5%
용 1726
 
2.0%
월 1647
 
1.9%
Other values (639) 46954
53.8%
Uppercase Letter
ValueCountFrequency (%)
N 91
15.6%
O 53
 
9.1%
T 43
 
7.4%
K 41
 
7.0%
A 36
 
6.2%
B 36
 
6.2%
D 32
 
5.5%
G 30
 
5.1%
M 30
 
5.1%
S 28
 
4.8%
Other values (15) 164
28.1%
Lowercase Letter
ValueCountFrequency (%)
o 62
38.8%
n 29
18.1%
x 16
 
10.0%
s 12
 
7.5%
g 8
 
5.0%
k 8
 
5.0%
t 4
 
2.5%
l 3
 
1.9%
b 3
 
1.9%
p 2
 
1.2%
Other values (9) 13
 
8.1%
Other Punctuation
ValueCountFrequency (%)
/ 686
29.9%
. 651
28.4%
, 602
26.2%
: 201
 
8.8%
* 75
 
3.3%
? 21
 
0.9%
% 16
 
0.7%
# 13
 
0.6%
@ 11
 
0.5%
' 9
 
0.4%
Other values (3) 9
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 4717
24.8%
0 4183
22.0%
2 3809
20.1%
3 1467
 
7.7%
4 966
 
5.1%
5 951
 
5.0%
9 859
 
4.5%
8 717
 
3.8%
6 710
 
3.7%
7 603
 
3.2%
Math Symbol
ValueCountFrequency (%)
~ 224
87.2%
> 12
 
4.7%
+ 8
 
3.1%
< 7
 
2.7%
× 4
 
1.6%
÷ 1
 
0.4%
= 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 2649
98.2%
[ 49
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 2649
98.2%
] 49
 
1.8%
Space Separator
ValueCountFrequency (%)
15906
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2133
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 46
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87234
65.6%
Common 45014
33.8%
Latin 744
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 6034
 
6.9%
수 5309
 
6.1%
비 4693
 
5.4%
리 4642
 
5.3%
관 4189
 
4.8%
체 4114
 
4.7%
연 3977
 
4.6%
납 3950
 
4.5%
용 1726
 
2.0%
월 1647
 
1.9%
Other values (638) 46953
53.8%
Latin
ValueCountFrequency (%)
N 91
 
12.2%
o 62
 
8.3%
O 53
 
7.1%
T 43
 
5.8%
K 41
 
5.5%
A 36
 
4.8%
B 36
 
4.8%
D 32
 
4.3%
G 30
 
4.0%
M 30
 
4.0%
Other values (34) 290
39.0%
Common
ValueCountFrequency (%)
15906
35.3%
1 4717
 
10.5%
0 4183
 
9.3%
2 3809
 
8.5%
( 2649
 
5.9%
) 2649
 
5.9%
- 2133
 
4.7%
3 1467
 
3.3%
4 966
 
2.1%
5 951
 
2.1%
Other values (27) 5584
 
12.4%
Han
ValueCountFrequency (%)
入 1
50.0%
分 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87233
65.6%
ASCII 45753
34.4%
None 6
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15906
34.8%
1 4717
 
10.3%
0 4183
 
9.1%
2 3809
 
8.3%
( 2649
 
5.8%
) 2649
 
5.8%
- 2133
 
4.7%
3 1467
 
3.2%
4 966
 
2.1%
5 951
 
2.1%
Other values (69) 6323
 
13.8%
Hangul
ValueCountFrequency (%)
료 6034
 
6.9%
수 5309
 
6.1%
비 4693
 
5.4%
리 4642
 
5.3%
관 4189
 
4.8%
체 4114
 
4.7%
연 3977
 
4.6%
납 3950
 
4.5%
용 1726
 
2.0%
월 1647
 
1.9%
Other values (637) 46952
53.8%
None
ValueCountFrequency (%)
× 4
66.7%
÷ 1
 
16.7%
㈜ 1
 
16.7%
CJK
ValueCountFrequency (%)
入 1
50.0%
分 1
50.0%

Interactions

2024-05-11T02:40:13.184597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:12.348639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:13.662656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:40:12.743143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:40:23.956715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3150.324
년월일0.3151.0000.130
금액0.3240.1301.000
2024-05-11T02:40:24.209881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0790.128
금액0.0791.0000.145
비용명0.1280.1451.000

Missing values

2024-05-11T02:40:14.295239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:40:14.896219image/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

아파트명아파트코드비용명년월일금액내용
33053상계한신A13983608고용안정사업수익20190201130000일자리안정자금
10746장안현대힐스테이트A13010004연체료수익20190221670관리비 연체료 수납
33226상계은빛2단지A13983815승강기수익2019022150000승강기 사용료208-708공사
9213신사두산위브A12208001잡수익20190211500산재,고용보험료 자동이체할인액
42327개봉현대홈타운2단지A15209206승강기수익20190212100000211-2302호 승강기사용료(세대전출)
30127상아2차아파트A13886009연체료수익201902197790관리비 연체료 수납
15521마장신성미소지움A13305003광고료수익2019022630000광고료/전문과외
42209개봉한마을A15209002임대료수익201902282000002월헬스장 임대료
18242고덕아이파크아파트A13408003광고료수익20190226120000게시판광고비
17887성내삼성A13403101광고료수익20190215146364부과명세서 광고료(2월분)
아파트명아파트코드비용명년월일금액내용
46952우장산한화꿈에그린A15701004주차장수익2019020760000외부주차료(전태훈 0484, 2월분)아덴하임
19675삼성롯데캐슬프레미어A13509010연체료수익201902137110관리비 연체료 수납
46123신동아리버파크제2관리사무소A15676701연체료수익201902272970관리비 연체료 수납
5718대현럭키A12017001광고료수익20190214100000우편함 광고(진로 식자재마트)
28568송파파인타운10단지A13821005연체료수익2019022739540관리비 연체료 수납
41560서울대입구아이원 (1560-61)A15184101임대료수익201902262000002019년 2월분 현대엘리베이터 임대료
33513월계동신A13984604광고료수익2019020830000일일장입점비(닭강정)
11989신내우디안1단지A13113008기타운영수익201902283680002월분 커뮤니티 락카이용료(82세대/골프:5,000원,헬스:3,000원)
32330공릉풍림아이원A13980513연체료수익20190226970관리비 연체료 수납
3706래미안밤섬리베뉴 ⅠA10028177잡수익2019021415000회의실 사용료(2/14.2/21,2/28)1시간5,000*3일