Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells11
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 = 35.36472978)Skewed

Reproduction

Analysis started2024-05-11 02:24:19.181794
Analysis finished2024-05-11 02:24:22.582835
Duration3.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2053
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:22.859364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.5238
Min length2

Characters and Unicode

Total characters75238
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

Unique219 ?
Unique (%)2.2%

Sample

1st row등촌대림아파트
2nd row상계주공6단지
3rd row우장산힐스테이트
4th row길동삼익파크
5th row래미안솔베뉴
ValueCountFrequency (%)
아파트 214
 
1.9%
래미안 58
 
0.5%
e편한세상 47
 
0.4%
아이파크 37
 
0.3%
센트럴 27
 
0.2%
마포래미안푸르지오 24
 
0.2%
송파 23
 
0.2%
창동북한산아이파크 22
 
0.2%
이편한세상 22
 
0.2%
롯데캐슬아파트 21
 
0.2%
Other values (2132) 10578
95.5%
2024-05-11T02:24:23.881246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2662
 
3.5%
파 2655
 
3.5%
트 2606
 
3.5%
지 1964
 
2.6%
대 1611
 
2.1%
이 1563
 
2.1%
단 1532
 
2.0%
동 1504
 
2.0%
차 1295
 
1.7%
신 1290
 
1.7%
Other values (421) 56556
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68908
91.6%
Decimal Number 3486
 
4.6%
Space Separator 1176
 
1.6%
Uppercase Letter 820
 
1.1%
Lowercase Letter 293
 
0.4%
Open Punctuation 158
 
0.2%
Close Punctuation 158
 
0.2%
Other Punctuation 118
 
0.2%
Dash Punctuation 114
 
0.2%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2662
 
3.9%
파 2655
 
3.9%
트 2606
 
3.8%
지 1964
 
2.9%
대 1611
 
2.3%
이 1563
 
2.3%
단 1532
 
2.2%
동 1504
 
2.2%
차 1295
 
1.9%
신 1290
 
1.9%
Other values (376) 50226
72.9%
Uppercase Letter
ValueCountFrequency (%)
S 148
18.0%
K 115
14.0%
C 110
13.4%
D 81
9.9%
M 81
9.9%
H 53
 
6.5%
L 42
 
5.1%
I 36
 
4.4%
E 34
 
4.1%
V 21
 
2.6%
Other values (7) 99
12.1%
Lowercase Letter
ValueCountFrequency (%)
e 209
71.3%
s 20
 
6.8%
k 18
 
6.1%
i 12
 
4.1%
l 8
 
2.7%
v 7
 
2.4%
w 5
 
1.7%
c 4
 
1.4%
h 4
 
1.4%
a 3
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 991
28.4%
2 963
27.6%
3 524
15.0%
4 237
 
6.8%
5 212
 
6.1%
6 164
 
4.7%
7 124
 
3.6%
9 120
 
3.4%
8 91
 
2.6%
0 60
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 89
75.4%
. 29
 
24.6%
Space Separator
ValueCountFrequency (%)
1176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68908
91.6%
Common 5210
 
6.9%
Latin 1120
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2662
 
3.9%
파 2655
 
3.9%
트 2606
 
3.8%
지 1964
 
2.9%
대 1611
 
2.3%
이 1563
 
2.3%
단 1532
 
2.2%
동 1504
 
2.2%
차 1295
 
1.9%
신 1290
 
1.9%
Other values (376) 50226
72.9%
Latin
ValueCountFrequency (%)
e 209
18.7%
S 148
13.2%
K 115
10.3%
C 110
9.8%
D 81
 
7.2%
M 81
 
7.2%
H 53
 
4.7%
L 42
 
3.8%
I 36
 
3.2%
E 34
 
3.0%
Other values (19) 211
18.8%
Common
ValueCountFrequency (%)
1176
22.6%
1 991
19.0%
2 963
18.5%
3 524
10.1%
4 237
 
4.5%
5 212
 
4.1%
6 164
 
3.1%
( 158
 
3.0%
) 158
 
3.0%
7 124
 
2.4%
Other values (6) 503
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68908
91.6%
ASCII 6323
 
8.4%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2662
 
3.9%
파 2655
 
3.9%
트 2606
 
3.8%
지 1964
 
2.9%
대 1611
 
2.3%
이 1563
 
2.3%
단 1532
 
2.2%
동 1504
 
2.2%
차 1295
 
1.9%
신 1290
 
1.9%
Other values (376) 50226
72.9%
ASCII
ValueCountFrequency (%)
1176
18.6%
1 991
15.7%
2 963
15.2%
3 524
 
8.3%
4 237
 
3.7%
5 212
 
3.4%
e 209
 
3.3%
6 164
 
2.6%
( 158
 
2.5%
) 158
 
2.5%
Other values (34) 1531
24.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2057
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:24.733638image/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

Unique219 ?
Unique (%)2.2%

Sample

1st rowA15703307
2nd rowA13920707
3rd rowA15728009
4th rowA13470101
5th rowA10025415
ValueCountFrequency (%)
a12175203 24
 
0.2%
a13204510 22
 
0.2%
a13552002 20
 
0.2%
a13527203 20
 
0.2%
a10025614 20
 
0.2%
a13373301 20
 
0.2%
a14021001 20
 
0.2%
a13003007 20
 
0.2%
a13822004 19
 
0.2%
a10024473 18
 
0.2%
Other values (2047) 9797
98.0%
2024-05-11T02:24:25.830615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18835
20.9%
1 17126
19.0%
A 9991
11.1%
3 8691
9.7%
2 8351
9.3%
5 6283
 
7.0%
8 5396
 
6.0%
7 4702
 
5.2%
4 4304
 
4.8%
6 3396
 
3.8%
Other values (2) 2925
 
3.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18835
23.5%
1 17126
21.4%
3 8691
10.9%
2 8351
10.4%
5 6283
 
7.9%
8 5396
 
6.7%
7 4702
 
5.9%
4 4304
 
5.4%
6 3396
 
4.2%
9 2916
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9991
99.9%
B 9
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18835
23.5%
1 17126
21.4%
3 8691
10.9%
2 8351
10.4%
5 6283
 
7.9%
8 5396
 
6.7%
7 4702
 
5.9%
4 4304
 
5.4%
6 3396
 
4.2%
9 2916
 
3.6%
Latin
ValueCountFrequency (%)
A 9991
99.9%
B 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18835
20.9%
1 17126
19.0%
A 9991
11.1%
3 8691
9.7%
2 8351
9.3%
5 6283
 
7.0%
8 5396
 
6.0%
7 4702
 
5.2%
4 4304
 
4.8%
6 3396
 
3.8%
Other values (2) 2925
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3555 
승강기수익
1143 
잡수익
1010 
광고료수익
971 
기타운영수익
949 
Other values (10)
2372 

Length

Max length9
Median length5
Mean length4.8733
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3555
35.5%
승강기수익 1143
 
11.4%
잡수익 1010
 
10.1%
광고료수익 971
 
9.7%
기타운영수익 949
 
9.5%
주차장수익 905
 
9.0%
검침수익 392
 
3.9%
부과차익 237
 
2.4%
임대료수익 237
 
2.4%
알뜰시장수익 223
 
2.2%
Other values (5) 378
 
3.8%

Length

2024-05-11T02:24:26.316137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3555
35.5%
승강기수익 1143
 
11.4%
잡수익 1010
 
10.1%
광고료수익 971
 
9.7%
기타운영수익 949
 
9.5%
주차장수익 905
 
9.0%
검침수익 392
 
3.9%
부과차익 237
 
2.4%
임대료수익 237
 
2.4%
알뜰시장수익 223
 
2.2%
Other values (5) 378
 
3.8%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230417
Minimum20230401
Maximum20230430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:24:26.691037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230401
5-th percentile20230403
Q120230409
median20230418
Q320230426
95-th percentile20230430
Maximum20230430
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.2967388
Coefficient of variation (CV)4.5954262 × 10-7
Kurtosis-1.3731054
Mean20230417
Median Absolute Deviation (MAD)8
Skewness-0.15677813
Sum2.0230417 × 1011
Variance86.429353
MonotonicityNot monotonic
2024-05-11T02:24:27.076760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20230430 744
 
7.4%
20230428 672
 
6.7%
20230403 630
 
6.3%
20230410 595
 
5.9%
20230425 555
 
5.5%
20230427 481
 
4.8%
20230426 442
 
4.4%
20230424 422
 
4.2%
20230404 396
 
4.0%
20230405 391
 
3.9%
Other values (20) 4672
46.7%
ValueCountFrequency (%)
20230401 217
 
2.2%
20230402 130
 
1.3%
20230403 630
6.3%
20230404 396
4.0%
20230405 391
3.9%
20230406 334
3.3%
20230407 291
2.9%
20230408 75
 
0.8%
20230409 56
 
0.6%
20230410 595
5.9%
ValueCountFrequency (%)
20230430 744
7.4%
20230429 221
 
2.2%
20230428 672
6.7%
20230427 481
4.8%
20230426 442
4.4%
20230425 555
5.5%
20230424 422
4.2%
20230423 125
 
1.2%
20230422 107
 
1.1%
20230421 381
3.8%

금액
Real number (ℝ)

SKEWED 

Distinct3274
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317213.03
Minimum-1700000
Maximum1.6938 × 108
Zeros17
Zeros (%)0.2%
Negative38
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:24:27.480048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1700000
5-th percentile150
Q12427.5
median30000
Q3100000
95-th percentile1000000
Maximum1.6938 × 108
Range1.7108 × 108
Interquartile range (IQR)97572.5

Descriptive statistics

Standard deviation2720340.8
Coefficient of variation (CV)8.5757537
Kurtosis1772.5541
Mean317213.03
Median Absolute Deviation (MAD)29170
Skewness35.36473
Sum3.1721303 × 109
Variance7.4002541 × 1012
MonotonicityNot monotonic
2024-05-11T02:24:27.856402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 584
 
5.8%
100000 563
 
5.6%
50000 523
 
5.2%
40000 164
 
1.6%
150000 155
 
1.6%
70000 151
 
1.5%
200000 146
 
1.5%
60000 139
 
1.4%
500 103
 
1.0%
80000 102
 
1.0%
Other values (3264) 7370
73.7%
ValueCountFrequency (%)
-1700000 1
< 0.1%
-1467540 1
< 0.1%
-600000 1
< 0.1%
-273472 1
< 0.1%
-200000 1
< 0.1%
-140000 1
< 0.1%
-130000 1
< 0.1%
-100000 1
< 0.1%
-88000 1
< 0.1%
-87330 1
< 0.1%
ValueCountFrequency (%)
169380000 1
< 0.1%
93366000 1
< 0.1%
69538200 1
< 0.1%
65037230 1
< 0.1%
61010900 1
< 0.1%
57109091 1
< 0.1%
48387290 1
< 0.1%
43695360 1
< 0.1%
36316000 1
< 0.1%
30638806 1
< 0.1%

내용
Text

Distinct5724
Distinct (%)57.3%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:24:28.427450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length68
Mean length14.440284
Min length2

Characters and Unicode

Total characters144244
Distinct characters738
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

Unique5450 ?
Unique (%)54.6%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row주차료 수입
4th row관리비 연체료 수납
5th row113-3202 이사 공사 승강기 사용료-전출
ValueCountFrequency (%)
관리비 3689
 
13.6%
연체료 3558
 
13.2%
수납 3557
 
13.2%
1360
 
5.0%
승강기 347
 
1.3%
4월분 325
 
1.2%
사용료 246
 
0.9%
승강기사용료 237
 
0.9%
4월 227
 
0.8%
입금 190
 
0.7%
Other values (7291) 13311
49.2%
2024-05-11T02:24:29.549621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17465
 
12.1%
? 6533
 
4.5%
료 5640
 
3.9%
0 5353
 
3.7%
수 4948
 
3.4%
1 4882
 
3.4%
비 4294
 
3.0%
리 4156
 
2.9%
관 3879
 
2.7%
체 3769
 
2.6%
Other values (728) 83325
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83793
58.1%
Decimal Number 23487
 
16.3%
Space Separator 17465
 
12.1%
Other Punctuation 9431
 
6.5%
Close Punctuation 3109
 
2.2%
Open Punctuation 3085
 
2.1%
Dash Punctuation 2572
 
1.8%
Uppercase Letter 721
 
0.5%
Math Symbol 376
 
0.3%
Lowercase Letter 106
 
0.1%
Other values (2) 99
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5640
 
6.7%
수 4948
 
5.9%
비 4294
 
5.1%
리 4156
 
5.0%
관 3879
 
4.6%
체 3769
 
4.5%
연 3652
 
4.4%
납 3638
 
4.3%
용 1769
 
2.1%
사 1682
 
2.0%
Other values (646) 46366
55.3%
Uppercase Letter
ValueCountFrequency (%)
N 90
12.5%
B 58
 
8.0%
O 55
 
7.6%
K 55
 
7.6%
T 53
 
7.4%
C 51
 
7.1%
L 48
 
6.7%
A 42
 
5.8%
G 41
 
5.7%
S 34
 
4.7%
Other values (13) 194
26.9%
Lowercase Letter
ValueCountFrequency (%)
o 33
31.1%
k 10
 
9.4%
n 9
 
8.5%
a 6
 
5.7%
e 6
 
5.7%
t 6
 
5.7%
s 5
 
4.7%
g 4
 
3.8%
l 4
 
3.8%
x 4
 
3.8%
Other values (8) 19
17.9%
Other Punctuation
ValueCountFrequency (%)
? 6533
69.3%
/ 961
 
10.2%
. 846
 
9.0%
, 686
 
7.3%
: 192
 
2.0%
* 109
 
1.2%
@ 39
 
0.4%
% 30
 
0.3%
& 9
 
0.1%
# 9
 
0.1%
Other values (3) 17
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 5353
22.8%
1 4882
20.8%
2 3560
15.2%
4 2845
12.1%
3 2543
10.8%
5 1352
 
5.8%
6 892
 
3.8%
7 761
 
3.2%
8 668
 
2.8%
9 631
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 313
83.2%
+ 27
 
7.2%
> 14
 
3.7%
× 9
 
2.4%
= 5
 
1.3%
< 5
 
1.3%
→ 1
 
0.3%
⇒ 1
 
0.3%
÷ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3008
96.8%
] 100
 
3.2%
］ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 2983
96.7%
[ 102
 
3.3%
Space Separator
ValueCountFrequency (%)
17465
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2572
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 98
100.0%
Other Symbol
ValueCountFrequency (%)
☞ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83784
58.1%
Common 59624
41.3%
Latin 827
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5640
 
6.7%
수 4948
 
5.9%
비 4294
 
5.1%
리 4156
 
5.0%
관 3879
 
4.6%
체 3769
 
4.5%
연 3652
 
4.4%
납 3638
 
4.3%
용 1769
 
2.1%
사 1682
 
2.0%
Other values (643) 46357
55.3%
Common
ValueCountFrequency (%)
17465
29.3%
? 6533
 
11.0%
0 5353
 
9.0%
1 4882
 
8.2%
2 3560
 
6.0%
) 3008
 
5.0%
( 2983
 
5.0%
4 2845
 
4.8%
- 2572
 
4.3%
3 2543
 
4.3%
Other values (31) 7880
13.2%
Latin
ValueCountFrequency (%)
N 90
 
10.9%
B 58
 
7.0%
O 55
 
6.7%
K 55
 
6.7%
T 53
 
6.4%
C 51
 
6.2%
L 48
 
5.8%
A 42
 
5.1%
G 41
 
5.0%
S 34
 
4.1%
Other values (31) 300
36.3%
Han
ValueCountFrequency (%)
入 5
55.6%
內 3
33.3%
人 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83784
58.1%
ASCII 60437
41.9%
None 11
 
< 0.1%
CJK 9
 
< 0.1%
Arrows 2
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17465
28.9%
? 6533
 
10.8%
0 5353
 
8.9%
1 4882
 
8.1%
2 3560
 
5.9%
) 3008
 
5.0%
( 2983
 
4.9%
4 2845
 
4.7%
- 2572
 
4.3%
3 2543
 
4.2%
Other values (66) 8693
14.4%
Hangul
ValueCountFrequency (%)
료 5640
 
6.7%
수 4948
 
5.9%
비 4294
 
5.1%
리 4156
 
5.0%
관 3879
 
4.6%
체 3769
 
4.5%
연 3652
 
4.4%
납 3638
 
4.3%
용 1769
 
2.1%
사 1682
 
2.0%
Other values (643) 46357
55.3%
None
ValueCountFrequency (%)
× 9
81.8%
］ 1
 
9.1%
÷ 1
 
9.1%
CJK
ValueCountFrequency (%)
入 5
55.6%
內 3
33.3%
人 1
 
11.1%
Arrows
ValueCountFrequency (%)
→ 1
50.0%
⇒ 1
50.0%
Misc Symbols
ValueCountFrequency (%)
☞ 1
100.0%

Interactions

2024-05-11T02:24:21.428060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:20.901999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:21.782938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:21.150870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:24:29.804455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3410.212
년월일0.3411.0000.016
금액0.2120.0161.000
2024-05-11T02:24:30.017102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0500.134
금액0.0501.0000.097
비용명0.1340.0971.000

Missing values

2024-05-11T02:24:22.060437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:24:22.426022image/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
49045등촌대림아파트A15703307연체료수익202304139760관리비 연체료 수납
34016상계주공6단지A13920707연체료수익202304162940관리비 연체료 수납
49936우장산힐스테이트A15728009주차장수익202304193618주차료 수입
22734길동삼익파크A13470101연체료수익20230406260관리비 연체료 수납
4184래미안솔베뉴A10025415승강기수익20230410100000113-3202 이사 공사 승강기 사용료-전출
10739DMC래미안e편한세상A12013003광고료수익20230426400000?????(????) 4/27~5/3
36123두산아파트A13983713연체료수익202304251480관리비 연체료 수납
27917장월SH-VILLE1단지A13614301연체료수익20230427940관리비 연체료 수납
28293삼선푸르지오아파트A13672101주차장수익2023043024625504월분 세대 주차비
8343공덕자이 아파트A10027906기타운영수익202304281505000신해정 PT수업 강습비외 수입 16건
아파트명아파트코드비용명년월일금액내용
7773송파 와이즈더샵A10027632광고료수익20230424200000게시판광고[버디톡 23.4.24~5.8]
15252장안현대힐스테이트A13010004기타운영수익202304261070000윤수용 외 3인 수익금
28721돈암현대A13681304승강기수익2023041330000승강기사용료:101동 909호(4.15일전출승강기사용료)
31995잠실레이크팰리스A13822001잡수익2023042183월 관리비 잡수입
41770양평현대2차A15010305알뜰시장수익20230418300001일 수산물 판매 / 알뜰장수입
24972도곡렉슬A13527203승강기수익2023042877272승강기보양재 사용료(103-603 공사)
2984e편한세상 강동에코포레 아파트A10024932승강기수익20230421100000104-1002 승강기사용료(4/21 전입)
29249양재리본타워2단지A13713002주차장수익2023043013096604? ??????(23.04.01~23.04.30)
15765답십리대림A13080801연체료수익2023042620관리비 연체료 수납
31737문정래미안A13820006임대료수익202304252080000SK텔레콤 지하 중계기 임대료 수입(22.0101~22.12.31)