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

Reproduction

Analysis started2024-05-11 02:26:33.161550
Analysis finished2024-05-11 02:26:38.146988
Duration4.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2171
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:26:38.615712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length7.4882
Min length2

Characters and Unicode

Total characters74882
Distinct characters434
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

Unique254 ?
Unique (%)2.5%

Sample

1st row신반포자이아파트
2nd row쌍문금호1차아파트
3rd row송파레이크파크 호반 써밋2
4th row가락쌍용1차
5th row중계주공7단지
ValueCountFrequency (%)
아파트 213
 
1.9%
래미안 58
 
0.5%
e편한세상 33
 
0.3%
아이파크 32
 
0.3%
마포래미안푸르지오 31
 
0.3%
잠실파크리오 27
 
0.2%
마포펜트라우스 23
 
0.2%
고덕 21
 
0.2%
센트럴 21
 
0.2%
영등포 20
 
0.2%
Other values (2250) 10461
95.6%
2024-05-11T02:26:40.027196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2647
 
3.5%
파 2602
 
3.5%
트 2528
 
3.4%
지 2068
 
2.8%
단 1583
 
2.1%
대 1560
 
2.1%
이 1530
 
2.0%
동 1529
 
2.0%
신 1328
 
1.8%
차 1314
 
1.8%
Other values (424) 56193
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68354
91.3%
Decimal Number 3706
 
4.9%
Space Separator 1041
 
1.4%
Uppercase Letter 840
 
1.1%
Lowercase Letter 342
 
0.5%
Close Punctuation 159
 
0.2%
Open Punctuation 159
 
0.2%
Dash Punctuation 142
 
0.2%
Other Punctuation 132
 
0.2%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2647
 
3.9%
파 2602
 
3.8%
트 2528
 
3.7%
지 2068
 
3.0%
단 1583
 
2.3%
대 1560
 
2.3%
이 1530
 
2.2%
동 1529
 
2.2%
신 1328
 
1.9%
차 1314
 
1.9%
Other values (379) 49665
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 157
18.7%
K 119
14.2%
C 116
13.8%
M 75
8.9%
D 75
8.9%
H 60
 
7.1%
L 51
 
6.1%
I 37
 
4.4%
E 33
 
3.9%
A 28
 
3.3%
Other values (7) 89
10.6%
Lowercase Letter
ValueCountFrequency (%)
e 197
57.6%
l 36
 
10.5%
i 24
 
7.0%
k 21
 
6.1%
s 19
 
5.6%
v 19
 
5.6%
c 12
 
3.5%
h 4
 
1.2%
g 4
 
1.2%
a 4
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 1081
29.2%
2 1033
27.9%
3 488
13.2%
4 266
 
7.2%
5 235
 
6.3%
6 174
 
4.7%
7 128
 
3.5%
9 127
 
3.4%
8 101
 
2.7%
0 73
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 108
81.8%
. 24
 
18.2%
Space Separator
ValueCountFrequency (%)
1041
100.0%
Close Punctuation
ValueCountFrequency (%)
) 159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68354
91.3%
Common 5339
 
7.1%
Latin 1189
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2647
 
3.9%
파 2602
 
3.8%
트 2528
 
3.7%
지 2068
 
3.0%
단 1583
 
2.3%
대 1560
 
2.3%
이 1530
 
2.2%
동 1529
 
2.2%
신 1328
 
1.9%
차 1314
 
1.9%
Other values (379) 49665
72.7%
Latin
ValueCountFrequency (%)
e 197
16.6%
S 157
13.2%
K 119
10.0%
C 116
9.8%
M 75
 
6.3%
D 75
 
6.3%
H 60
 
5.0%
L 51
 
4.3%
I 37
 
3.1%
l 36
 
3.0%
Other values (19) 266
22.4%
Common
ValueCountFrequency (%)
1 1081
20.2%
1041
19.5%
2 1033
19.3%
3 488
9.1%
4 266
 
5.0%
5 235
 
4.4%
6 174
 
3.3%
) 159
 
3.0%
( 159
 
3.0%
- 142
 
2.7%
Other values (6) 561
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68354
91.3%
ASCII 6521
 
8.7%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2647
 
3.9%
파 2602
 
3.8%
트 2528
 
3.7%
지 2068
 
3.0%
단 1583
 
2.3%
대 1560
 
2.3%
이 1530
 
2.2%
동 1529
 
2.2%
신 1328
 
1.9%
차 1314
 
1.9%
Other values (379) 49665
72.7%
ASCII
ValueCountFrequency (%)
1 1081
16.6%
1041
16.0%
2 1033
15.8%
3 488
 
7.5%
4 266
 
4.1%
5 235
 
3.6%
e 197
 
3.0%
6 174
 
2.7%
) 159
 
2.4%
( 159
 
2.4%
Other values (34) 1688
25.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2176
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:26:40.977118image/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

Unique258 ?
Unique (%)2.6%

Sample

1st rowA10026004
2nd rowA13203408
3rd rowA10023922
4th rowA13880806
5th rowA13922910
ValueCountFrequency (%)
a12175203 31
 
0.3%
a13824006 27
 
0.3%
a12179004 23
 
0.2%
a10025614 20
 
0.2%
a13987306 19
 
0.2%
a13822004 19
 
0.2%
a13805002 17
 
0.2%
a10026941 17
 
0.2%
a15780905 17
 
0.2%
a10028021 17
 
0.2%
Other values (2166) 9793
97.9%
2024-05-11T02:26:42.393895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18795
20.9%
1 16921
18.8%
A 9996
11.1%
3 8576
9.5%
2 8405
9.3%
5 6267
 
7.0%
8 5494
 
6.1%
7 4865
 
5.4%
4 4195
 
4.7%
6 3453
 
3.8%
Other values (2) 3033
 
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 18795
23.5%
1 16921
21.2%
3 8576
10.7%
2 8405
10.5%
5 6267
 
7.8%
8 5494
 
6.9%
7 4865
 
6.1%
4 4195
 
5.2%
6 3453
 
4.3%
9 3029
 
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 18795
23.5%
1 16921
21.2%
3 8576
10.7%
2 8405
10.5%
5 6267
 
7.8%
8 5494
 
6.9%
7 4865
 
6.1%
4 4195
 
5.2%
6 3453
 
4.3%
9 3029
 
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 18795
20.9%
1 16921
18.8%
A 9996
11.1%
3 8576
9.5%
2 8405
9.3%
5 6267
 
7.0%
8 5494
 
6.1%
7 4865
 
5.4%
4 4195
 
4.7%
6 3453
 
3.8%
Other values (2) 3033
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3643 
광고료수익
1062 
잡수익
1018 
승강기수익
963 
주차장수익
940 
Other values (10)
2374 

Length

Max length9
Median length5
Mean length4.8749
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3643
36.4%
광고료수익 1062
 
10.6%
잡수익 1018
 
10.2%
승강기수익 963
 
9.6%
주차장수익 940
 
9.4%
기타운영수익 902
 
9.0%
검침수익 319
 
3.2%
부과차익 257
 
2.6%
임대료수익 255
 
2.5%
알뜰시장수익 230
 
2.3%
Other values (5) 411
 
4.1%

Length

2024-05-11T02:26:42.895162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3643
36.4%
광고료수익 1062
 
10.6%
잡수익 1018
 
10.2%
승강기수익 963
 
9.6%
주차장수익 940
 
9.4%
기타운영수익 902
 
9.0%
검침수익 319
 
3.2%
부과차익 257
 
2.6%
임대료수익 255
 
2.5%
알뜰시장수익 230
 
2.3%
Other values (5) 411
 
4.1%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20221117
Minimum20221101
Maximum20221130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:26:43.429427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20221101
5-th percentile20221101
Q120221108
median20221118
Q320221126
95-th percentile20221130
Maximum20221130
Range29
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.7810954
Coefficient of variation (CV)4.8370698 × 10-7
Kurtosis-1.3515736
Mean20221117
Median Absolute Deviation (MAD)9
Skewness-0.18561475
Sum2.0221117 × 1011
Variance95.669827
MonotonicityNot monotonic
2024-05-11T02:26:44.158214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20221130 1137
 
11.4%
20221129 599
 
6.0%
20221101 564
 
5.6%
20221128 493
 
4.9%
20221125 488
 
4.9%
20221110 464
 
4.6%
20221121 426
 
4.3%
20221107 412
 
4.1%
20221102 393
 
3.9%
20221124 373
 
3.7%
Other values (20) 4651
46.5%
ValueCountFrequency (%)
20221101 564
5.6%
20221102 393
3.9%
20221103 325
3.2%
20221104 361
3.6%
20221105 92
 
0.9%
20221106 70
 
0.7%
20221107 412
4.1%
20221108 326
3.3%
20221109 305
3.0%
20221110 464
4.6%
ValueCountFrequency (%)
20221130 1137
11.4%
20221129 599
6.0%
20221128 493
4.9%
20221127 195
 
1.9%
20221126 167
 
1.7%
20221125 488
4.9%
20221124 373
 
3.7%
20221123 358
 
3.6%
20221122 338
 
3.4%
20221121 426
 
4.3%

금액
Real number (ℝ)

Distinct3241
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean260048.75
Minimum-7168000
Maximum40368450
Zeros18
Zeros (%)0.2%
Negative56
Negative (%)0.6%
Memory size166.0 KiB
2024-05-11T02:26:44.832826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7168000
5-th percentile160
Q12330
median29907
Q3100000
95-th percentile997672.5
Maximum40368450
Range47536450
Interquartile range (IQR)97670

Descriptive statistics

Standard deviation1353847.3
Coefficient of variation (CV)5.206129
Kurtosis242.98265
Mean260048.75
Median Absolute Deviation (MAD)28810.5
Skewness13.23055
Sum2.6004875 × 109
Variance1.8329026 × 1012
MonotonicityNot monotonic
2024-05-11T02:26:45.335753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 603
 
6.0%
30000 561
 
5.6%
100000 466
 
4.7%
60000 179
 
1.8%
70000 162
 
1.6%
150000 153
 
1.5%
40000 149
 
1.5%
200000 132
 
1.3%
80000 116
 
1.2%
20000 116
 
1.2%
Other values (3231) 7363
73.6%
ValueCountFrequency (%)
-7168000 1
< 0.1%
-4477730 1
< 0.1%
-2800000 1
< 0.1%
-1980000 1
< 0.1%
-1062369 1
< 0.1%
-775000 1
< 0.1%
-613640 1
< 0.1%
-435000 1
< 0.1%
-339100 1
< 0.1%
-300000 1
< 0.1%
ValueCountFrequency (%)
40368450 1
< 0.1%
29970000 1
< 0.1%
29804928 1
< 0.1%
29677840 1
< 0.1%
26257000 1
< 0.1%
26018810 1
< 0.1%
23520000 1
< 0.1%
23010000 1
< 0.1%
22019820 1
< 0.1%
21600000 1
< 0.1%

내용
Text

Distinct5639
Distinct (%)56.4%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:26:46.188796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length67
Mean length14.368832
Min length2

Characters and Unicode

Total characters143559
Distinct characters751
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5375 ?
Unique (%)53.8%

Sample

1st row입주민 카페 운영수입
2nd row게시판 광고료(크린토피아방학점)
3rd row관리비 연체료 수납
4th row하나카드 헬스장이용료
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3800
 
14.1%
수납 3661
 
13.6%
연체료 3652
 
13.6%
596
 
2.2%
11월분 406
 
1.5%
승강기 269
 
1.0%
11월 266
 
1.0%
10월분 244
 
0.9%
승강기사용료 219
 
0.8%
사용료 216
 
0.8%
Other values (7329) 13580
50.5%
2024-05-11T02:26:47.973629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17311
 
12.1%
1 8338
 
5.8%
료 5853
 
4.1%
수 5186
 
3.6%
0 4924
 
3.4%
비 4439
 
3.1%
리 4290
 
3.0%
관 4005
 
2.8%
체 3873
 
2.7%
연 3742
 
2.6%
Other values (741) 81598
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88489
61.6%
Decimal Number 23706
 
16.5%
Space Separator 17311
 
12.1%
Other Punctuation 4411
 
3.1%
Close Punctuation 2948
 
2.1%
Open Punctuation 2929
 
2.0%
Dash Punctuation 2445
 
1.7%
Uppercase Letter 693
 
0.5%
Math Symbol 349
 
0.2%
Lowercase Letter 142
 
0.1%
Other values (2) 136
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5853
 
6.6%
수 5186
 
5.9%
비 4439
 
5.0%
리 4290
 
4.8%
관 4005
 
4.5%
체 3873
 
4.4%
연 3742
 
4.2%
납 3730
 
4.2%
용 1744
 
2.0%
사 1623
 
1.8%
Other values (654) 50004
56.5%
Uppercase Letter
ValueCountFrequency (%)
T 66
 
9.5%
N 65
 
9.4%
C 63
 
9.1%
K 59
 
8.5%
A 55
 
7.9%
B 53
 
7.6%
O 48
 
6.9%
S 42
 
6.1%
D 29
 
4.2%
G 29
 
4.2%
Other values (16) 184
26.6%
Lowercase Letter
ValueCountFrequency (%)
o 23
16.2%
k 18
12.7%
e 15
10.6%
s 15
10.6%
t 11
7.7%
n 11
7.7%
a 8
 
5.6%
c 6
 
4.2%
p 4
 
2.8%
h 4
 
2.8%
Other values (12) 27
19.0%
Other Punctuation
ValueCountFrequency (%)
? 1668
37.8%
/ 945
21.4%
. 818
18.5%
, 612
 
13.9%
: 174
 
3.9%
* 93
 
2.1%
@ 33
 
0.7%
% 33
 
0.7%
' 14
 
0.3%
# 11
 
0.2%
Other values (4) 10
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 8338
35.2%
0 4924
20.8%
2 3694
15.6%
3 1598
 
6.7%
4 1250
 
5.3%
5 1102
 
4.6%
6 805
 
3.4%
8 674
 
2.8%
7 666
 
2.8%
9 655
 
2.8%
Math Symbol
ValueCountFrequency (%)
~ 302
86.5%
+ 17
 
4.9%
> 11
 
3.2%
× 8
 
2.3%
= 6
 
1.7%
< 4
 
1.1%
→ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2857
96.9%
] 91
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 2839
96.9%
[ 90
 
3.1%
Space Separator
ValueCountFrequency (%)
17311
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2445
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 135
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88479
61.6%
Common 54235
37.8%
Latin 835
 
0.6%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5853
 
6.6%
수 5186
 
5.9%
비 4439
 
5.0%
리 4290
 
4.8%
관 4005
 
4.5%
체 3873
 
4.4%
연 3742
 
4.2%
납 3730
 
4.2%
용 1744
 
2.0%
사 1623
 
1.8%
Other values (651) 49994
56.5%
Latin
ValueCountFrequency (%)
T 66
 
7.9%
N 65
 
7.8%
C 63
 
7.5%
K 59
 
7.1%
A 55
 
6.6%
B 53
 
6.3%
O 48
 
5.7%
S 42
 
5.0%
D 29
 
3.5%
G 29
 
3.5%
Other values (38) 326
39.0%
Common
ValueCountFrequency (%)
17311
31.9%
1 8338
15.4%
0 4924
 
9.1%
2 3694
 
6.8%
) 2857
 
5.3%
( 2839
 
5.2%
- 2445
 
4.5%
? 1668
 
3.1%
3 1598
 
2.9%
4 1250
 
2.3%
Other values (29) 7311
13.5%
Han
ValueCountFrequency (%)
入 7
70.0%
內 2
 
20.0%
多 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88478
61.6%
ASCII 55060
38.4%
CJK 10
 
< 0.1%
None 9
 
< 0.1%
Arrows 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17311
31.4%
1 8338
15.1%
0 4924
 
8.9%
2 3694
 
6.7%
) 2857
 
5.2%
( 2839
 
5.2%
- 2445
 
4.4%
? 1668
 
3.0%
3 1598
 
2.9%
4 1250
 
2.3%
Other values (74) 8136
14.8%
Hangul
ValueCountFrequency (%)
료 5853
 
6.6%
수 5186
 
5.9%
비 4439
 
5.0%
리 4290
 
4.8%
관 4005
 
4.5%
체 3873
 
4.4%
연 3742
 
4.2%
납 3730
 
4.2%
용 1744
 
2.0%
사 1623
 
1.8%
Other values (650) 49993
56.5%
None
ValueCountFrequency (%)
× 8
88.9%
· 1
 
11.1%
CJK
ValueCountFrequency (%)
入 7
70.0%
內 2
 
20.0%
多 1
 
10.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅂ 1
100.0%

Interactions

2024-05-11T02:26:36.392250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:35.662633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:36.776715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:36.010672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:26:48.345084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3430.310
년월일0.3431.0000.113
금액0.3100.1131.000
2024-05-11T02:26:48.671763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0370.135
금액0.0371.0000.131
비용명0.1350.1311.000

Missing values

2024-05-11T02:26:37.256520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:26:37.922741image/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
4882신반포자이아파트A10026004기타운영수익2022111945100입주민 카페 운영수입
18544쌍문금호1차아파트A13203408주차장수익2022111430000게시판 광고료(크린토피아방학점)
308송파레이크파크 호반 써밋2A10023922연체료수익202211254080관리비 연체료 수납
34386가락쌍용1차A13880806기타운영수익2022111488000하나카드 헬스장이용료
36007중계주공7단지A13922910연체료수익202211293350관리비 연체료 수납
23528명일한양A13482603재활용품수익2022111690909재활용수입11월(12개월분1.090.909선납/12=90.909
28822월곡두산위브아파트A13613008잡수익202211301000011월 탁구장 사용료
39353상계한양A13994302광고료수익2022110730000게시판 / 영어전문교실
17520신내건영2차아파트A13185607잡수익20221129363640이루니유치원 텃밭사용료(11월분)
35256상계벽산A13920506승강기수익2022110810000109동 919호 승강기 ( 부분 1회) 사용료
아파트명아파트코드비용명년월일금액내용
7059파크하비오푸르지오아파트A10027346기타운영수익202211306798002022.11월 독서실 이용료 부과수입
51789등촌IPARKA15703204연체료수익202211074900관리비 연체료 수납
55467수명산롯데캐슬A15809502연체료수익202211292990관리비 연체료 수납
31339래미안방배아트힐A13785008광고료수익20221122100000게시판광고료
24045역삼아이파크A13508009기타운영수익2022110313000골프이용료입주민(김민수외)
29841정릉푸른마을동아A13684605광고료수익2022112850000우편함 광고료
8135래미안첼리투스A10027908승강기수익20221122100000NO116 103-403호 전출 승강기사용료
53694방화3차우림필유A15785002주차장수익20221130134333011월분 주차료수입
20465서울숲삼부아파트A13307101주차장수익202211301000002022-12월분 외부차량 주차료/7127
22974강일리버파크1단지A13410001연체료수익2022111415490관리비 연체료 수납