Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells9
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 = 20.86658731)Skewed

Reproduction

Analysis started2024-05-11 02:24:02.822938
Analysis finished2024-05-11 02:24:06.884716
Duration4.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2193
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:07.338762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.5271
Min length2

Characters and Unicode

Total characters75271
Distinct characters435
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

Unique260 ?
Unique (%)2.6%

Sample

1st row꿈의숲 해링턴 플레이스 아파트
2nd row약수하이츠아파트(임대)
3rd row광장청구
4th row도곡삼성래미안
5th row래미안수유(임대)
ValueCountFrequency (%)
아파트 236
 
2.1%
래미안 84
 
0.8%
아이파크 39
 
0.4%
고덕 34
 
0.3%
sk뷰 32
 
0.3%
e편한세상 31
 
0.3%
마포래미안푸르지오 25
 
0.2%
래미안위브 24
 
0.2%
센트럴 23
 
0.2%
서초포레스타2단지아파트 21
 
0.2%
Other values (2275) 10494
95.0%
2024-05-11T02:24:08.583985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2715
 
3.6%
파 2680
 
3.6%
트 2581
 
3.4%
지 2046
 
2.7%
단 1581
 
2.1%
대 1572
 
2.1%
동 1543
 
2.0%
이 1513
 
2.0%
신 1321
 
1.8%
스 1217
 
1.6%
Other values (425) 56502
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68692
91.3%
Decimal Number 3524
 
4.7%
Space Separator 1148
 
1.5%
Uppercase Letter 960
 
1.3%
Lowercase Letter 403
 
0.5%
Open Punctuation 154
 
0.2%
Close Punctuation 154
 
0.2%
Other Punctuation 117
 
0.2%
Dash Punctuation 114
 
0.2%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2715
 
4.0%
파 2680
 
3.9%
트 2581
 
3.8%
지 2046
 
3.0%
단 1581
 
2.3%
대 1572
 
2.3%
동 1543
 
2.2%
이 1513
 
2.2%
신 1321
 
1.9%
스 1217
 
1.8%
Other values (380) 49923
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 160
16.7%
C 134
14.0%
K 120
12.5%
D 101
10.5%
M 101
10.5%
I 51
 
5.3%
H 47
 
4.9%
E 47
 
4.9%
A 33
 
3.4%
V 33
 
3.4%
Other values (7) 133
13.9%
Lowercase Letter
ValueCountFrequency (%)
e 192
47.6%
l 46
 
11.4%
s 37
 
9.2%
k 33
 
8.2%
i 31
 
7.7%
v 24
 
6.0%
c 18
 
4.5%
h 13
 
3.2%
w 7
 
1.7%
a 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 1023
29.0%
1 1019
28.9%
3 468
13.3%
4 253
 
7.2%
5 204
 
5.8%
6 157
 
4.5%
7 133
 
3.8%
9 113
 
3.2%
8 81
 
2.3%
0 73
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 96
82.1%
. 21
 
17.9%
Space Separator
ValueCountFrequency (%)
1148
100.0%
Open Punctuation
ValueCountFrequency (%)
( 154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68692
91.3%
Common 5211
 
6.9%
Latin 1368
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2715
 
4.0%
파 2680
 
3.9%
트 2581
 
3.8%
지 2046
 
3.0%
단 1581
 
2.3%
대 1572
 
2.3%
동 1543
 
2.2%
이 1513
 
2.2%
신 1321
 
1.9%
스 1217
 
1.8%
Other values (380) 49923
72.7%
Latin
ValueCountFrequency (%)
e 192
14.0%
S 160
11.7%
C 134
 
9.8%
K 120
 
8.8%
D 101
 
7.4%
M 101
 
7.4%
I 51
 
3.7%
H 47
 
3.4%
E 47
 
3.4%
l 46
 
3.4%
Other values (19) 369
27.0%
Common
ValueCountFrequency (%)
1148
22.0%
2 1023
19.6%
1 1019
19.6%
3 468
9.0%
4 253
 
4.9%
5 204
 
3.9%
6 157
 
3.0%
( 154
 
3.0%
) 154
 
3.0%
7 133
 
2.6%
Other values (6) 498
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68692
91.3%
ASCII 6574
 
8.7%
Number Forms 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2715
 
4.0%
파 2680
 
3.9%
트 2581
 
3.8%
지 2046
 
3.0%
단 1581
 
2.3%
대 1572
 
2.3%
동 1543
 
2.2%
이 1513
 
2.2%
신 1321
 
1.9%
스 1217
 
1.8%
Other values (380) 49923
72.7%
ASCII
ValueCountFrequency (%)
1148
17.5%
2 1023
15.6%
1 1019
15.5%
3 468
 
7.1%
4 253
 
3.8%
5 204
 
3.1%
e 192
 
2.9%
S 160
 
2.4%
6 157
 
2.4%
( 154
 
2.3%
Other values (34) 1796
27.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 5
100.0%

아파트코드
Text

Distinct2198
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:09.475837image/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

Unique260 ?
Unique (%)2.6%

Sample

1st rowA10025241
2nd rowA10045402
3rd rowA14381513
4th rowA13550502
5th rowA14207201
ValueCountFrequency (%)
a12175203 25
 
0.2%
a13003007 24
 
0.2%
a10028021 21
 
0.2%
a10025850 19
 
0.2%
a13822004 18
 
0.2%
a10026180 18
 
0.2%
a15728009 18
 
0.2%
a13778204 17
 
0.2%
a10024872 17
 
0.2%
a13592604 17
 
0.2%
Other values (2188) 9806
98.1%
2024-05-11T02:24:10.807046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18969
21.1%
1 17077
19.0%
A 9990
11.1%
3 8522
9.5%
2 8372
9.3%
5 6289
 
7.0%
8 5443
 
6.0%
7 4770
 
5.3%
4 4184
 
4.6%
6 3427
 
3.8%
Other values (2) 2957
 
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 18969
23.7%
1 17077
21.3%
3 8522
10.7%
2 8372
10.5%
5 6289
 
7.9%
8 5443
 
6.8%
7 4770
 
6.0%
4 4184
 
5.2%
6 3427
 
4.3%
9 2947
 
3.7%
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 18969
23.7%
1 17077
21.3%
3 8522
10.7%
2 8372
10.5%
5 6289
 
7.9%
8 5443
 
6.8%
7 4770
 
6.0%
4 4184
 
5.2%
6 3427
 
4.3%
9 2947
 
3.7%
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 18969
21.1%
1 17077
19.0%
A 9990
11.1%
3 8522
9.5%
2 8372
9.3%
5 6289
 
7.0%
8 5443
 
6.0%
7 4770
 
5.3%
4 4184
 
4.6%
6 3427
 
3.8%
Other values (2) 2957
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3855 
잡수익
1093 
주차장수익
973 
승강기수익
949 
기타운영수익
888 
Other values (10)
2242 

Length

Max length9
Median length5
Mean length4.8529
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재활용품수익
2nd row연체료수익
3rd row연체료수익
4th row알뜰시장수익
5th row연체료수익

Common Values

ValueCountFrequency (%)
연체료수익 3855
38.6%
잡수익 1093
 
10.9%
주차장수익 973
 
9.7%
승강기수익 949
 
9.5%
기타운영수익 888
 
8.9%
광고료수익 779
 
7.8%
검침수익 357
 
3.6%
임대료수익 268
 
2.7%
부과차익 231
 
2.3%
재활용품수익 215
 
2.1%
Other values (5) 392
 
3.9%

Length

2024-05-11T02:24:11.435474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3855
38.6%
잡수익 1093
 
10.9%
주차장수익 973
 
9.7%
승강기수익 949
 
9.5%
기타운영수익 888
 
8.9%
광고료수익 779
 
7.8%
검침수익 357
 
3.6%
임대료수익 268
 
2.7%
부과차익 231
 
2.3%
재활용품수익 215
 
2.1%
Other values (5) 392
 
3.9%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230117
Minimum20230101
Maximum20230131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:24:11.872079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230101
5-th percentile20230102
Q120230107
median20230117
Q320230127
95-th percentile20230131
Maximum20230131
Range30
Interquartile range (IQR)20

Descriptive statistics

Standard deviation10.210588
Coefficient of variation (CV)5.0472213 × 10-7
Kurtosis-1.4249811
Mean20230117
Median Absolute Deviation (MAD)10
Skewness-0.042767526
Sum2.0230117 × 1011
Variance104.2561
MonotonicityNot monotonic
2024-05-11T02:24:12.268864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20230131 1169
 
11.7%
20230102 656
 
6.6%
20230125 575
 
5.8%
20230130 575
 
5.8%
20230110 502
 
5.0%
20230127 470
 
4.7%
20230120 417
 
4.2%
20230103 412
 
4.1%
20230105 407
 
4.1%
20230126 406
 
4.1%
Other values (21) 4411
44.1%
ValueCountFrequency (%)
20230101 262
 
2.6%
20230102 656
6.6%
20230103 412
4.1%
20230104 345
3.5%
20230105 407
4.1%
20230106 342
3.4%
20230107 98
 
1.0%
20230108 60
 
0.6%
20230109 360
3.6%
20230110 502
5.0%
ValueCountFrequency (%)
20230131 1169
11.7%
20230130 575
5.8%
20230129 164
 
1.6%
20230128 160
 
1.6%
20230127 470
4.7%
20230126 406
 
4.1%
20230125 575
5.8%
20230124 124
 
1.2%
20230123 64
 
0.6%
20230122 56
 
0.6%

금액
Real number (ℝ)

SKEWED 

Distinct3356
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean273813.33
Minimum-7508700
Maximum70845660
Zeros18
Zeros (%)0.2%
Negative38
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:24:12.701816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7508700
5-th percentile90
Q12000
median20000
Q3100000
95-th percentile1000000
Maximum70845660
Range78354360
Interquartile range (IQR)98000

Descriptive statistics

Standard deviation1624939.3
Coefficient of variation (CV)5.9344785
Kurtosis648.56335
Mean273813.33
Median Absolute Deviation (MAD)19750
Skewness20.866587
Sum2.7381333 × 109
Variance2.6404278 × 1012
MonotonicityNot monotonic
2024-05-11T02:24:13.301238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 501
 
5.0%
50000 480
 
4.8%
30000 477
 
4.8%
60000 166
 
1.7%
150000 157
 
1.6%
70000 133
 
1.3%
40000 119
 
1.2%
20000 108
 
1.1%
200000 102
 
1.0%
80000 88
 
0.9%
Other values (3346) 7669
76.7%
ValueCountFrequency (%)
-7508700 1
< 0.1%
-2000000 1
< 0.1%
-600000 1
< 0.1%
-431200 1
< 0.1%
-420000 1
< 0.1%
-374230 1
< 0.1%
-350000 1
< 0.1%
-330000 1
< 0.1%
-188000 1
< 0.1%
-150000 1
< 0.1%
ValueCountFrequency (%)
70845660 1
< 0.1%
50847380 1
< 0.1%
47739752 1
< 0.1%
46145560 1
< 0.1%
32314400 1
< 0.1%
31818182 1
< 0.1%
27000000 1
< 0.1%
25490243 1
< 0.1%
23548920 1
< 0.1%
21272727 1
< 0.1%

내용
Text

Distinct5468
Distinct (%)54.7%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:24:14.277910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length74
Mean length14.125113
Min length2

Characters and Unicode

Total characters141124
Distinct characters722
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5212 ?
Unique (%)52.2%

Sample

1st row재활용품(23.02.01-02.28)
2nd row관리비 연체료 수납
3rd row관리비 연체료 수납
4th row알뜰장이용료입금
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3985
 
14.5%
연체료 3863
 
14.1%
수납 3862
 
14.1%
577
 
2.1%
1월분 347
 
1.3%
승강기 307
 
1.1%
1월 226
 
0.8%
사용료 221
 
0.8%
12월분 216
 
0.8%
입금 200
 
0.7%
Other values (7073) 13674
49.8%
2024-05-11T02:24:15.807385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17850
 
12.6%
1 6432
 
4.6%
료 5947
 
4.2%
수 5325
 
3.8%
0 4824
 
3.4%
비 4613
 
3.3%
2 4574
 
3.2%
리 4406
 
3.1%
관 4171
 
3.0%
체 4099
 
2.9%
Other values (712) 78883
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86891
61.6%
Decimal Number 22739
 
16.1%
Space Separator 17850
 
12.6%
Other Punctuation 4585
 
3.2%
Close Punctuation 2739
 
1.9%
Open Punctuation 2728
 
1.9%
Dash Punctuation 2267
 
1.6%
Uppercase Letter 739
 
0.5%
Math Symbol 349
 
0.2%
Lowercase Letter 141
 
0.1%
Other values (2) 96
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5947
 
6.8%
수 5325
 
6.1%
비 4613
 
5.3%
리 4406
 
5.1%
관 4171
 
4.8%
체 4099
 
4.7%
납 3989
 
4.6%
연 3938
 
4.5%
용 1710
 
2.0%
기 1625
 
1.9%
Other values (630) 47068
54.2%
Uppercase Letter
ValueCountFrequency (%)
K 75
 
10.1%
T 71
 
9.6%
B 65
 
8.8%
N 65
 
8.8%
A 57
 
7.7%
L 51
 
6.9%
C 45
 
6.1%
G 44
 
6.0%
O 34
 
4.6%
D 31
 
4.2%
Other values (15) 201
27.2%
Lowercase Letter
ValueCountFrequency (%)
o 35
24.8%
k 14
 
9.9%
e 13
 
9.2%
n 10
 
7.1%
s 10
 
7.1%
c 9
 
6.4%
a 8
 
5.7%
t 8
 
5.7%
d 6
 
4.3%
l 4
 
2.8%
Other values (9) 24
17.0%
Other Punctuation
ValueCountFrequency (%)
? 1902
41.5%
. 888
19.4%
/ 835
18.2%
, 609
 
13.3%
: 173
 
3.8%
* 94
 
2.1%
@ 32
 
0.7%
% 21
 
0.5%
# 12
 
0.3%
' 8
 
0.2%
Other values (3) 11
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 6432
28.3%
0 4824
21.2%
2 4574
20.1%
3 1981
 
8.7%
4 1185
 
5.2%
5 974
 
4.3%
6 832
 
3.7%
7 705
 
3.1%
9 636
 
2.8%
8 596
 
2.6%
Math Symbol
ValueCountFrequency (%)
~ 278
79.7%
+ 29
 
8.3%
> 13
 
3.7%
× 10
 
2.9%
= 10
 
2.9%
< 6
 
1.7%
→ 3
 
0.9%
Close Punctuation
ValueCountFrequency (%)
) 2634
96.2%
] 105
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 2622
96.1%
[ 106
 
3.9%
Space Separator
ValueCountFrequency (%)
17850
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2267
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 95
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86884
61.6%
Common 53353
37.8%
Latin 880
 
0.6%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5947
 
6.8%
수 5325
 
6.1%
비 4613
 
5.3%
리 4406
 
5.1%
관 4171
 
4.8%
체 4099
 
4.7%
납 3989
 
4.6%
연 3938
 
4.5%
용 1710
 
2.0%
기 1625
 
1.9%
Other values (628) 47061
54.2%
Latin
ValueCountFrequency (%)
K 75
 
8.5%
T 71
 
8.1%
B 65
 
7.4%
N 65
 
7.4%
A 57
 
6.5%
L 51
 
5.8%
C 45
 
5.1%
G 44
 
5.0%
o 35
 
4.0%
O 34
 
3.9%
Other values (34) 338
38.4%
Common
ValueCountFrequency (%)
17850
33.5%
1 6432
 
12.1%
0 4824
 
9.0%
2 4574
 
8.6%
) 2634
 
4.9%
( 2622
 
4.9%
- 2267
 
4.2%
3 1981
 
3.7%
? 1902
 
3.6%
4 1185
 
2.2%
Other values (28) 7082
 
13.3%
Han
ValueCountFrequency (%)
入 6
85.7%
用 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86884
61.6%
ASCII 54219
38.4%
None 11
 
< 0.1%
CJK 7
 
< 0.1%
Arrows 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17850
32.9%
1 6432
 
11.9%
0 4824
 
8.9%
2 4574
 
8.4%
) 2634
 
4.9%
( 2622
 
4.8%
- 2267
 
4.2%
3 1981
 
3.7%
? 1902
 
3.5%
4 1185
 
2.2%
Other values (69) 7948
14.7%
Hangul
ValueCountFrequency (%)
료 5947
 
6.8%
수 5325
 
6.1%
비 4613
 
5.3%
리 4406
 
5.1%
관 4171
 
4.8%
체 4099
 
4.7%
납 3989
 
4.6%
연 3938
 
4.5%
용 1710
 
2.0%
기 1625
 
1.9%
Other values (628) 47061
54.2%
None
ValueCountFrequency (%)
× 10
90.9%
？ 1
 
9.1%
CJK
ValueCountFrequency (%)
入 6
85.7%
用 1
 
14.3%
Arrows
ValueCountFrequency (%)
→ 3
100.0%

Interactions

2024-05-11T02:24:05.599949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:04.726649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:05.901980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:05.145453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:24:16.072043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3410.400
년월일0.3411.0000.163
금액0.4000.1631.000
2024-05-11T02:24:16.326690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0470.135
금액0.0471.0000.175
비용명0.1350.1751.000

Missing values

2024-05-11T02:24:06.299003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:24:06.720800image/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
3850꿈의숲 해링턴 플레이스 아파트A10025241재활용품수익20230101616800재활용품(23.02.01-02.28)
9711약수하이츠아파트(임대)A10045402연체료수익202301251500관리비 연체료 수납
43100광장청구A14381513연체료수익20230105480관리비 연체료 수납
26623도곡삼성래미안A13550502알뜰시장수익20230109460000알뜰장이용료입금
41478래미안수유(임대)A14207201연체료수익202301191280관리비 연체료 수납
23032천호태영A13402002이자수익20230125-100공동주택지원금 통장 이자 반납-강동구청
25924수서까치마을A13522007주차장수익2023011810007-807 주차스티커비 입금
31573서초힐스A13778204주차장수익202301215455주차료수익-국민카드외
29994래미안석관A13676101기타운영수익20230109836368휘트니스 이용료
18922도봉한신A13201209기타운영수익20230117159200주민운동시설수입-주미형,임혜린(비씨카드160,000)
아파트명아파트코드비용명년월일금액내용
46697봉천두산1,2단지A15106901임대료수익20230126770000행복한어린이집 임대료 1월분
29000길음뉴타운푸르지오아파트2,3단지A13611007기타운영수익20230114321000스포츠센터 이용(카드결재)(1월 17일) 입금예정)
26030개포우성3차A13524004연체료수익2023011631980관리비 연체료 수납
23668강일리버파크10단지A13410005잡수익2023011222022년 2기확정 부가세신고
50892신동아리버파크A15605103연체료수익202301222610관리비 연체료 수납
43542여의도삼부A15001020연체료수익202301161490관리비 연체료 수납
54246등촌임광A15783701잡수익2023011810000102-1202호 차량리모컨 구입(1ea)
43296자양우성3차A14386110부과차익202301311440부과차익 발생
4987아크로 리버하임A10025770승강기수익20230123200000111동 7301호 동간이사 승강기사용료(105동 1801호로~)
36128상계주공6단지A13920707연체료수익2023010431310관리비 연체료 수납