Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells10
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

Alerts

금액 is highly skewed (γ1 = 49.18722553)Skewed

Reproduction

Analysis started2024-05-11 02:29:03.651596
Analysis finished2024-05-11 02:29:08.240833
Duration4.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2178
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:29:08.540013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.416
Min length2

Characters and Unicode

Total characters74160
Distinct characters431
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)1.9%

Sample

1st row상계불암대림
2nd rowDMC센트레빌
3rd row봉천건영6차아파트
4th row서초포레스타2단지아파트
5th row남서울건영아파트
ValueCountFrequency (%)
아파트 163
 
1.5%
래미안 41
 
0.4%
e편한세상 32
 
0.3%
고덕 29
 
0.3%
아이파크 28
 
0.3%
sk뷰 26
 
0.2%
트리마제 17
 
0.2%
경남아너스빌 17
 
0.2%
목동7단지 17
 
0.2%
가락쌍용1차 17
 
0.2%
Other values (2255) 10443
96.4%
2024-05-11T02:29:09.494750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2615
 
3.5%
파 2585
 
3.5%
트 2525
 
3.4%
지 2021
 
2.7%
대 1618
 
2.2%
단 1588
 
2.1%
동 1552
 
2.1%
이 1550
 
2.1%
신 1380
 
1.9%
차 1313
 
1.8%
Other values (421) 55413
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67815
91.4%
Decimal Number 3582
 
4.8%
Uppercase Letter 980
 
1.3%
Space Separator 943
 
1.3%
Lowercase Letter 333
 
0.4%
Open Punctuation 149
 
0.2%
Close Punctuation 149
 
0.2%
Dash Punctuation 103
 
0.1%
Other Punctuation 99
 
0.1%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2615
 
3.9%
파 2585
 
3.8%
트 2525
 
3.7%
지 2021
 
3.0%
대 1618
 
2.4%
단 1588
 
2.3%
동 1552
 
2.3%
이 1550
 
2.3%
신 1380
 
2.0%
차 1313
 
1.9%
Other values (376) 49068
72.4%
Uppercase Letter
ValueCountFrequency (%)
S 158
16.1%
C 128
13.1%
K 112
11.4%
M 103
10.5%
D 103
10.5%
L 69
7.0%
H 66
6.7%
I 49
 
5.0%
E 43
 
4.4%
V 33
 
3.4%
Other values (7) 116
11.8%
Lowercase Letter
ValueCountFrequency (%)
e 194
58.3%
k 28
 
8.4%
s 26
 
7.8%
l 22
 
6.6%
i 18
 
5.4%
c 14
 
4.2%
v 9
 
2.7%
h 9
 
2.7%
w 5
 
1.5%
g 4
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 1084
30.3%
2 1010
28.2%
3 455
12.7%
4 252
 
7.0%
5 215
 
6.0%
6 152
 
4.2%
7 137
 
3.8%
9 103
 
2.9%
8 98
 
2.7%
0 76
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 70
70.7%
. 29
29.3%
Space Separator
ValueCountFrequency (%)
943
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67815
91.4%
Common 5025
 
6.8%
Latin 1320
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2615
 
3.9%
파 2585
 
3.8%
트 2525
 
3.7%
지 2021
 
3.0%
대 1618
 
2.4%
단 1588
 
2.3%
동 1552
 
2.3%
이 1550
 
2.3%
신 1380
 
2.0%
차 1313
 
1.9%
Other values (376) 49068
72.4%
Latin
ValueCountFrequency (%)
e 194
14.7%
S 158
12.0%
C 128
9.7%
K 112
 
8.5%
M 103
 
7.8%
D 103
 
7.8%
L 69
 
5.2%
H 66
 
5.0%
I 49
 
3.7%
E 43
 
3.3%
Other values (19) 295
22.3%
Common
ValueCountFrequency (%)
1 1084
21.6%
2 1010
20.1%
943
18.8%
3 455
9.1%
4 252
 
5.0%
5 215
 
4.3%
6 152
 
3.0%
( 149
 
3.0%
) 149
 
3.0%
7 137
 
2.7%
Other values (6) 479
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67815
91.4%
ASCII 6338
 
8.5%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2615
 
3.9%
파 2585
 
3.8%
트 2525
 
3.7%
지 2021
 
3.0%
대 1618
 
2.4%
단 1588
 
2.3%
동 1552
 
2.3%
이 1550
 
2.3%
신 1380
 
2.0%
차 1313
 
1.9%
Other values (376) 49068
72.4%
ASCII
ValueCountFrequency (%)
1 1084
17.1%
2 1010
15.9%
943
14.9%
3 455
 
7.2%
4 252
 
4.0%
5 215
 
3.4%
e 194
 
3.1%
S 158
 
2.5%
6 152
 
2.4%
( 149
 
2.4%
Other values (34) 1726
27.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2184
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:29:10.220924image/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

Unique193 ?
Unique (%)1.9%

Sample

1st rowA13981006
2nd rowA12072801
3rd rowA15176602
4th rowA10028021
5th rowA15386404
ValueCountFrequency (%)
a13880806 17
 
0.2%
a13201209 17
 
0.2%
a15805115 17
 
0.2%
a10026988 17
 
0.2%
a13879102 16
 
0.2%
a11054101 15
 
0.1%
a10026180 15
 
0.1%
a13824006 15
 
0.1%
a13982704 15
 
0.1%
a10044002 15
 
0.1%
Other values (2174) 9841
98.4%
2024-05-11T02:29:11.361291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18778
20.9%
1 17090
19.0%
A 9996
11.1%
3 8595
9.6%
2 8410
9.3%
5 6296
 
7.0%
8 5589
 
6.2%
7 4761
 
5.3%
4 4141
 
4.6%
6 3340
 
3.7%
Other values (2) 3004
 
3.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18778
23.5%
1 17090
21.4%
3 8595
10.7%
2 8410
10.5%
5 6296
 
7.9%
8 5589
 
7.0%
7 4761
 
6.0%
4 4141
 
5.2%
6 3340
 
4.2%
9 3000
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9996
> 99.9%
B 4
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18778
23.5%
1 17090
21.4%
3 8595
10.7%
2 8410
10.5%
5 6296
 
7.9%
8 5589
 
7.0%
7 4761
 
6.0%
4 4141
 
5.2%
6 3340
 
4.2%
9 3000
 
3.8%
Latin
ValueCountFrequency (%)
A 9996
> 99.9%
B 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18778
20.9%
1 17090
19.0%
A 9996
11.1%
3 8595
9.6%
2 8410
9.3%
5 6296
 
7.0%
8 5589
 
6.2%
7 4761
 
5.3%
4 4141
 
4.6%
6 3340
 
3.7%
Other values (2) 3004
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3191 
이자수익
931 
잡수익
917 
승강기수익
891 
광고료수익
868 
Other values (10)
3202 

Length

Max length9
Median length5
Mean length4.9601
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연체료수익
2nd row연체료수익
3rd row주차장수익
4th row연체료수익
5th row주차장수익

Common Values

ValueCountFrequency (%)
연체료수익 3191
31.9%
이자수익 931
 
9.3%
잡수익 917
 
9.2%
승강기수익 891
 
8.9%
광고료수익 868
 
8.7%
기타운영수익 783
 
7.8%
주차장수익 770
 
7.7%
고용안정사업수익 464
 
4.6%
검침수익 300
 
3.0%
부과차익 216
 
2.2%
Other values (5) 669
 
6.7%

Length

2024-05-11T02:29:11.810671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3191
31.9%
이자수익 931
 
9.3%
잡수익 917
 
9.2%
승강기수익 891
 
8.9%
광고료수익 868
 
8.7%
기타운영수익 783
 
7.8%
주차장수익 770
 
7.7%
고용안정사업수익 464
 
4.6%
검침수익 300
 
3.0%
부과차익 216
 
2.2%
Other values (5) 669
 
6.7%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220617
Minimum20220601
Maximum20220630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:29:12.291867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220601
5-th percentile20220602
Q120220610
median20220618
Q320220626
95-th percentile20220630
Maximum20220630
Range29
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.9652436
Coefficient of variation (CV)4.433714 × 10-7
Kurtosis-1.1561387
Mean20220617
Median Absolute Deviation (MAD)8
Skewness-0.20413659
Sum2.0220617 × 1011
Variance80.375592
MonotonicityNot monotonic
2024-05-11T02:29:12.758285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20220630 957
 
9.6%
20220629 510
 
5.1%
20220602 501
 
5.0%
20220615 463
 
4.6%
20220627 452
 
4.5%
20220610 448
 
4.5%
20220620 441
 
4.4%
20220624 435
 
4.3%
20220617 427
 
4.3%
20220628 391
 
3.9%
Other values (20) 4975
49.8%
ValueCountFrequency (%)
20220601 175
 
1.8%
20220602 501
5.0%
20220603 361
3.6%
20220604 95
 
0.9%
20220605 59
 
0.6%
20220606 97
 
1.0%
20220607 389
3.9%
20220608 312
3.1%
20220609 270
2.7%
20220610 448
4.5%
ValueCountFrequency (%)
20220630 957
9.6%
20220629 510
5.1%
20220628 391
3.9%
20220627 452
4.5%
20220626 313
 
3.1%
20220625 150
 
1.5%
20220624 435
4.3%
20220623 300
 
3.0%
20220622 329
 
3.3%
20220621 341
 
3.4%

금액
Real number (ℝ)

SKEWED 

Distinct3835
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean276989.16
Minimum-13000000
Maximum2.1337327 × 108
Zeros14
Zeros (%)0.1%
Negative47
Negative (%)0.5%
Memory size166.0 KiB
2024-05-11T02:29:13.169199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-13000000
5-th percentile150
Q12750
median28030
Q3100000
95-th percentile753850.5
Maximum2.1337327 × 108
Range2.2637327 × 108
Interquartile range (IQR)97250

Descriptive statistics

Standard deviation2997231.3
Coefficient of variation (CV)10.820753
Kurtosis3063.2777
Mean276989.16
Median Absolute Deviation (MAD)26967.5
Skewness49.187226
Sum2.7698916 × 109
Variance8.9833952 × 1012
MonotonicityNot monotonic
2024-05-11T02:29:13.579845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 559
 
5.6%
50000 501
 
5.0%
100000 417
 
4.2%
60000 147
 
1.5%
150000 141
 
1.4%
40000 122
 
1.2%
200000 118
 
1.2%
70000 110
 
1.1%
80000 108
 
1.1%
120000 98
 
1.0%
Other values (3825) 7679
76.8%
ValueCountFrequency (%)
-13000000 1
< 0.1%
-2900000 1
< 0.1%
-1800000 1
< 0.1%
-600000 1
< 0.1%
-515510 1
< 0.1%
-360000 1
< 0.1%
-200000 1
< 0.1%
-180000 1
< 0.1%
-130000 1
< 0.1%
-124000 1
< 0.1%
ValueCountFrequency (%)
213373274 1
< 0.1%
137448220 1
< 0.1%
78120000 1
< 0.1%
56094990 1
< 0.1%
47520000 1
< 0.1%
34000000 1
< 0.1%
28759390 1
< 0.1%
26454200 1
< 0.1%
25158000 1
< 0.1%
24371680 1
< 0.1%

내용
Text

Distinct5991
Distinct (%)60.0%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:29:14.314456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length66
Mean length14.267968
Min length2

Characters and Unicode

Total characters142537
Distinct characters720
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5725 ?
Unique (%)57.3%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row외부주차-조윤서(3769)
4th row관리비 연체료 수납
5th row조규상 외부주차료 입금
ValueCountFrequency (%)
관리비 3358
 
12.8%
수납 3199
 
12.2%
연체료 3198
 
12.2%
369
 
1.4%
6월분 290
 
1.1%
5월분 280
 
1.1%
승강기 257
 
1.0%
입금 242
 
0.9%
6월 218
 
0.8%
승강기사용료 211
 
0.8%
Other values (7578) 14539
55.6%
2024-05-11T02:29:15.567484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16525
 
11.6%
료 5078
 
3.6%
0 4966
 
3.5%
수 4826
 
3.4%
리 4723
 
3.3%
비 4297
 
3.0%
1 3977
 
2.8%
관 3824
 
2.7%
2 3499
 
2.5%
체 3409
 
2.4%
Other values (710) 87413
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91513
64.2%
Decimal Number 21287
 
14.9%
Space Separator 16525
 
11.6%
Close Punctuation 3323
 
2.3%
Open Punctuation 3306
 
2.3%
Other Punctuation 2939
 
2.1%
Dash Punctuation 2477
 
1.7%
Uppercase Letter 605
 
0.4%
Math Symbol 339
 
0.2%
Lowercase Letter 124
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5078
 
5.5%
수 4826
 
5.3%
리 4723
 
5.2%
비 4297
 
4.7%
관 3824
 
4.2%
체 3409
 
3.7%
연 3275
 
3.6%
납 3246
 
3.5%
자 2207
 
2.4%
금 2079
 
2.3%
Other values (627) 54549
59.6%
Uppercase Letter
ValueCountFrequency (%)
N 79
13.1%
K 49
 
8.1%
T 48
 
7.9%
A 46
 
7.6%
B 42
 
6.9%
C 40
 
6.6%
O 39
 
6.4%
L 36
 
6.0%
D 33
 
5.5%
G 32
 
5.3%
Other values (15) 161
26.6%
Lowercase Letter
ValueCountFrequency (%)
o 41
33.1%
n 12
 
9.7%
x 12
 
9.7%
k 11
 
8.9%
t 10
 
8.1%
c 8
 
6.5%
e 6
 
4.8%
g 5
 
4.0%
s 5
 
4.0%
a 3
 
2.4%
Other values (9) 11
 
8.9%
Other Punctuation
ValueCountFrequency (%)
/ 840
28.6%
. 743
25.3%
, 698
23.7%
: 223
 
7.6%
? 179
 
6.1%
* 152
 
5.2%
@ 60
 
2.0%
% 13
 
0.4%
# 11
 
0.4%
& 8
 
0.3%
Other values (4) 12
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 4966
23.3%
1 3977
18.7%
2 3499
16.4%
6 2106
9.9%
5 1728
 
8.1%
3 1567
 
7.4%
4 1237
 
5.8%
7 896
 
4.2%
8 699
 
3.3%
9 612
 
2.9%
Math Symbol
ValueCountFrequency (%)
~ 277
81.7%
+ 19
 
5.6%
> 13
 
3.8%
× 11
 
3.2%
< 8
 
2.4%
= 8
 
2.4%
→ 2
 
0.6%
÷ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3235
97.4%
] 88
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 3221
97.4%
[ 85
 
2.6%
Space Separator
ValueCountFrequency (%)
16525
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2477
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91509
64.2%
Common 50295
35.3%
Latin 729
 
0.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5078
 
5.5%
수 4826
 
5.3%
리 4723
 
5.2%
비 4297
 
4.7%
관 3824
 
4.2%
체 3409
 
3.7%
연 3275
 
3.6%
납 3246
 
3.5%
자 2207
 
2.4%
금 2079
 
2.3%
Other values (625) 54545
59.6%
Latin
ValueCountFrequency (%)
N 79
 
10.8%
K 49
 
6.7%
T 48
 
6.6%
A 46
 
6.3%
B 42
 
5.8%
o 41
 
5.6%
C 40
 
5.5%
O 39
 
5.3%
L 36
 
4.9%
D 33
 
4.5%
Other values (34) 276
37.9%
Common
ValueCountFrequency (%)
16525
32.9%
0 4966
 
9.9%
1 3977
 
7.9%
2 3499
 
7.0%
) 3235
 
6.4%
( 3221
 
6.4%
- 2477
 
4.9%
6 2106
 
4.2%
5 1728
 
3.4%
3 1567
 
3.1%
Other values (29) 6994
13.9%
Han
ValueCountFrequency (%)
入 3
75.0%
名 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91507
64.2%
ASCII 51009
35.8%
None 13
 
< 0.1%
CJK 4
 
< 0.1%
Arrows 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16525
32.4%
0 4966
 
9.7%
1 3977
 
7.8%
2 3499
 
6.9%
) 3235
 
6.3%
( 3221
 
6.3%
- 2477
 
4.9%
6 2106
 
4.1%
5 1728
 
3.4%
3 1567
 
3.1%
Other values (69) 7708
15.1%
Hangul
ValueCountFrequency (%)
료 5078
 
5.5%
수 4826
 
5.3%
리 4723
 
5.2%
비 4297
 
4.7%
관 3824
 
4.2%
체 3409
 
3.7%
연 3275
 
3.6%
납 3246
 
3.5%
자 2207
 
2.4%
금 2079
 
2.3%
Other values (623) 54543
59.6%
None
ValueCountFrequency (%)
× 11
84.6%
？ 1
 
7.7%
÷ 1
 
7.7%
CJK
ValueCountFrequency (%)
入 3
75.0%
名 1
 
25.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
50.0%
ㅡ 1
50.0%

Interactions

2024-05-11T02:29:06.704488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:05.998808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:07.113276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:06.306543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:29:15.836126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4840.213
년월일0.4841.0000.030
금액0.2130.0301.000
2024-05-11T02:29:16.089363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0190.203
금액0.0191.0000.098
비용명0.2030.0981.000

Missing values

2024-05-11T02:29:07.645805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:29:08.074632image/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
43997상계불암대림A13981006연체료수익202206308900관리비 연체료 수납
12186DMC센트레빌A12072801연체료수익2022063070400관리비 연체료 수납
54810봉천건영6차아파트A15176602주차장수익2022061963636외부주차-조윤서(3769)
9205서초포레스타2단지아파트A10028021연체료수익20220603270관리비 연체료 수납
59034남서울건영아파트A15386404주차장수익2022061760000조규상 외부주차료 입금
20652신내8단지두산화성A13187201고용안정사업수익202206171540002022년 05월분 청소 일자리지원금
13258상암월드컵파크3단지A12127003승강기수익20220606400000305-703 공사 승강기 사용료
32405돈암동한신한진아파트A13606004연체료수익202206106480관리비 연체료 수납
19285묵동금호어울림A13114103고용안정사업수익2022061666000일자리지원금(미화) 김정래,최복순,최봉순 각22,000원
8318인왕산2차아이파크아파트A10027708이자수익202206189657관리비(새마을금고) 결산 이자
아파트명아파트코드비용명년월일금액내용
57975신도림대림5차e-편한세상A15288805광고료수익2022062730000게시판광고
65426목동롯데캐슬위너A15805303이자수익2022061892604장기수선충당금 이자수입
26924강일리버파크8단지A13410002승강기수익20220610100000809-303 승강기사용료
696위례포레샤인17단지A10024152연체료수익2022062813640관리비 연체료 수납
42193상계주공10단지A13920804승강기수익2022060345455승강기사용료(1006-1406호 )
30728삼성동힐스테이트2단지A13570501재활용품수익202206262600006월 재활용수거비
12651공덕한화꿈에그린A12102002기타운영수익20220630505000104동@20,000*14세대,@5,000*세대,@90,000*1세대,@60,000*2세대,@15,000*1세대
12725신공덕3차삼성래미안A12103002광고료수익2022061360000게시판광고료-페이스피부과2주*
39142문정시영A13820007이자수익202206263705예금이자 수입(수협-잡수입)
45641중계현대2차(4동)A13985904고용안정사업수익2022061530000일자리안정자금지원금-경리주임(5월분 )