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 = 73.90748552)Skewed

Reproduction

Analysis started2024-05-11 02:28:04.100583
Analysis finished2024-05-11 02:28:08.717892
Duration4.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2182
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:28:09.154918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.5055
Min length2

Characters and Unicode

Total characters75055
Distinct characters432
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

Unique272 ?
Unique (%)2.7%

Sample

1st row성수금호3차
2nd row돈암동일하이빌
3rd row동양엔파트
4th row가산두산위브
5th row신정양천
ValueCountFrequency (%)
아파트 205
 
1.9%
래미안 60
 
0.5%
e편한세상 39
 
0.4%
아이파크 25
 
0.2%
고덕 23
 
0.2%
롯데캐슬노블레스 21
 
0.2%
백련산 19
 
0.2%
푸르지오 19
 
0.2%
영등포 18
 
0.2%
sk뷰 18
 
0.2%
Other values (2262) 10526
95.9%
2024-05-11T02:28:10.335185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 2612
 
3.5%
아 2607
 
3.5%
트 2553
 
3.4%
지 2066
 
2.8%
단 1622
 
2.2%
대 1575
 
2.1%
동 1565
 
2.1%
이 1504
 
2.0%
신 1327
 
1.8%
차 1282
 
1.7%
Other values (422) 56342
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68573
91.4%
Decimal Number 3661
 
4.9%
Space Separator 1082
 
1.4%
Uppercase Letter 917
 
1.2%
Lowercase Letter 287
 
0.4%
Open Punctuation 153
 
0.2%
Close Punctuation 153
 
0.2%
Other Punctuation 114
 
0.2%
Dash Punctuation 111
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2612
 
3.8%
아 2607
 
3.8%
트 2553
 
3.7%
지 2066
 
3.0%
단 1622
 
2.4%
대 1575
 
2.3%
동 1565
 
2.3%
이 1504
 
2.2%
신 1327
 
1.9%
차 1282
 
1.9%
Other values (377) 49860
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 158
17.2%
C 122
13.3%
K 114
12.4%
D 100
10.9%
M 100
10.9%
L 51
 
5.6%
H 50
 
5.5%
I 45
 
4.9%
E 42
 
4.6%
A 29
 
3.2%
Other values (7) 106
11.6%
Lowercase Letter
ValueCountFrequency (%)
e 180
62.7%
k 21
 
7.3%
s 21
 
7.3%
l 18
 
6.3%
i 15
 
5.2%
v 10
 
3.5%
c 8
 
2.8%
a 4
 
1.4%
g 4
 
1.4%
h 4
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 1073
29.3%
2 1011
27.6%
3 468
12.8%
4 295
 
8.1%
5 221
 
6.0%
6 158
 
4.3%
7 147
 
4.0%
9 129
 
3.5%
8 89
 
2.4%
0 70
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 90
78.9%
. 24
 
21.1%
Space Separator
ValueCountFrequency (%)
1082
100.0%
Open Punctuation
ValueCountFrequency (%)
( 153
100.0%
Close Punctuation
ValueCountFrequency (%)
) 153
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68573
91.4%
Common 5274
 
7.0%
Latin 1208
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2612
 
3.8%
아 2607
 
3.8%
트 2553
 
3.7%
지 2066
 
3.0%
단 1622
 
2.4%
대 1575
 
2.3%
동 1565
 
2.3%
이 1504
 
2.2%
신 1327
 
1.9%
차 1282
 
1.9%
Other values (377) 49860
72.7%
Latin
ValueCountFrequency (%)
e 180
14.9%
S 158
13.1%
C 122
10.1%
K 114
9.4%
D 100
8.3%
M 100
8.3%
L 51
 
4.2%
H 50
 
4.1%
I 45
 
3.7%
E 42
 
3.5%
Other values (19) 246
20.4%
Common
ValueCountFrequency (%)
1082
20.5%
1 1073
20.3%
2 1011
19.2%
3 468
8.9%
4 295
 
5.6%
5 221
 
4.2%
6 158
 
3.0%
( 153
 
2.9%
) 153
 
2.9%
7 147
 
2.8%
Other values (6) 513
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68573
91.4%
ASCII 6478
 
8.6%
Number Forms 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 2612
 
3.8%
아 2607
 
3.8%
트 2553
 
3.7%
지 2066
 
3.0%
단 1622
 
2.4%
대 1575
 
2.3%
동 1565
 
2.3%
이 1504
 
2.2%
신 1327
 
1.9%
차 1282
 
1.9%
Other values (377) 49860
72.7%
ASCII
ValueCountFrequency (%)
1082
16.7%
1 1073
16.6%
2 1011
15.6%
3 468
 
7.2%
4 295
 
4.6%
5 221
 
3.4%
e 180
 
2.8%
6 158
 
2.4%
S 158
 
2.4%
( 153
 
2.4%
Other values (34) 1679
25.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%

아파트코드
Text

Distinct2187
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:28:11.491901image/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

Unique273 ?
Unique (%)2.7%

Sample

1st rowA13311101
2nd rowA13603501
3rd rowA12181101
4th rowA15380403
5th rowA15807707
ValueCountFrequency (%)
a10026180 21
 
0.2%
a12179004 18
 
0.2%
a10026988 18
 
0.2%
a12175203 18
 
0.2%
a13201209 17
 
0.2%
a10028021 17
 
0.2%
a13822004 17
 
0.2%
a13822003 17
 
0.2%
a10025985 17
 
0.2%
a13611008 16
 
0.2%
Other values (2177) 9824
98.2%
2024-05-11T02:28:13.478461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18639
20.7%
1 17187
19.1%
A 9999
11.1%
3 8596
9.6%
2 8416
9.4%
5 6213
 
6.9%
8 5483
 
6.1%
7 4835
 
5.4%
4 4194
 
4.7%
6 3383
 
3.8%
Other values (2) 3055
 
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 18639
23.3%
1 17187
21.5%
3 8596
10.7%
2 8416
10.5%
5 6213
 
7.8%
8 5483
 
6.9%
7 4835
 
6.0%
4 4194
 
5.2%
6 3383
 
4.2%
9 3054
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9999
> 99.9%
B 1
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18639
23.3%
1 17187
21.5%
3 8596
10.7%
2 8416
10.5%
5 6213
 
7.8%
8 5483
 
6.9%
7 4835
 
6.0%
4 4194
 
5.2%
6 3383
 
4.2%
9 3054
 
3.8%
Latin
ValueCountFrequency (%)
A 9999
> 99.9%
B 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18639
20.7%
1 17187
19.1%
A 9999
11.1%
3 8596
9.6%
2 8416
9.4%
5 6213
 
6.9%
8 5483
 
6.1%
7 4835
 
5.4%
4 4194
 
4.7%
6 3383
 
3.8%
Other values (2) 3055
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3686 
잡수익
1055 
승강기수익
1002 
광고료수익
998 
주차장수익
962 
Other values (10)
2297 

Length

Max length9
Median length5
Mean length4.8754
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광고료수익
2nd row연체료수익
3rd row검침수익
4th row연체료수익
5th row연체료수익

Common Values

ValueCountFrequency (%)
연체료수익 3686
36.9%
잡수익 1055
 
10.5%
승강기수익 1002
 
10.0%
광고료수익 998
 
10.0%
주차장수익 962
 
9.6%
기타운영수익 877
 
8.8%
검침수익 338
 
3.4%
임대료수익 236
 
2.4%
알뜰시장수익 234
 
2.3%
부과차익 218
 
2.2%
Other values (5) 394
 
3.9%

Length

2024-05-11T02:28:14.105311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3686
36.9%
잡수익 1055
 
10.5%
승강기수익 1002
 
10.0%
광고료수익 998
 
10.0%
주차장수익 962
 
9.6%
기타운영수익 877
 
8.8%
검침수익 338
 
3.4%
임대료수익 236
 
2.4%
알뜰시장수익 234
 
2.3%
부과차익 218
 
2.2%
Other values (5) 394
 
3.9%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20221018
Minimum20221001
Maximum20221031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:28:14.537470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20221001
5-th percentile20221004
Q120221011
median20221019
Q320221027
95-th percentile20221031
Maximum20221031
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.4487599
Coefficient of variation (CV)4.6727419 × 10-7
Kurtosis-1.2919095
Mean20221018
Median Absolute Deviation (MAD)8
Skewness-0.22155101
Sum2.0221018 × 1011
Variance89.279065
MonotonicityNot monotonic
2024-05-11T02:28:14.934131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20221031 1194
 
11.9%
20221025 600
 
6.0%
20221004 574
 
5.7%
20221028 515
 
5.1%
20221011 483
 
4.8%
20221005 479
 
4.8%
20221027 443
 
4.4%
20221026 437
 
4.4%
20221024 406
 
4.1%
20221017 400
 
4.0%
Other values (21) 4469
44.7%
ValueCountFrequency (%)
20221001 197
 
2.0%
20221002 104
 
1.0%
20221003 151
 
1.5%
20221004 574
5.7%
20221005 479
4.8%
20221006 360
3.6%
20221007 356
3.6%
20221008 68
 
0.7%
20221009 50
 
0.5%
20221010 95
 
0.9%
ValueCountFrequency (%)
20221031 1194
11.9%
20221030 192
 
1.9%
20221029 176
 
1.8%
20221028 515
5.1%
20221027 443
 
4.4%
20221026 437
 
4.4%
20221025 600
6.0%
20221024 406
 
4.1%
20221023 97
 
1.0%
20221022 100
 
1.0%

금액
Real number (ℝ)

SKEWED 

Distinct3187
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean354122.13
Minimum-17470226
Maximum4.44 × 108
Zeros19
Zeros (%)0.2%
Negative37
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:28:15.367685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-17470226
5-th percentile150
Q12177.75
median30000
Q3100000
95-th percentile1080000
Maximum4.44 × 108
Range4.6147023 × 108
Interquartile range (IQR)97822.25

Descriptive statistics

Standard deviation4970905.6
Coefficient of variation (CV)14.037263
Kurtosis6408.0429
Mean354122.13
Median Absolute Deviation (MAD)29005
Skewness73.907486
Sum3.5412213 × 109
Variance2.4709903 × 1013
MonotonicityNot monotonic
2024-05-11T02:28:15.922016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 593
 
5.9%
50000 585
 
5.9%
100000 436
 
4.4%
60000 157
 
1.6%
40000 152
 
1.5%
200000 146
 
1.5%
70000 140
 
1.4%
150000 137
 
1.4%
20000 130
 
1.3%
500 98
 
1.0%
Other values (3177) 7426
74.3%
ValueCountFrequency (%)
-17470226 1
 
< 0.1%
-3845000 1
 
< 0.1%
-772380 1
 
< 0.1%
-330000 1
 
< 0.1%
-270000 1
 
< 0.1%
-230000 1
 
< 0.1%
-225000 1
 
< 0.1%
-200000 1
 
< 0.1%
-156330 1
 
< 0.1%
-150000 3
< 0.1%
ValueCountFrequency (%)
444000000 1
< 0.1%
136080000 1
< 0.1%
57270000 1
< 0.1%
56215250 1
< 0.1%
50976396 1
< 0.1%
40000000 1
< 0.1%
38691000 1
< 0.1%
30750000 1
< 0.1%
30000000 1
< 0.1%
28350000 1
< 0.1%

내용
Text

Distinct5669
Distinct (%)56.7%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:28:16.955983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length68
Mean length14.239616
Min length2

Characters and Unicode

Total characters142268
Distinct characters725
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5438 ?
Unique (%)54.4%

Sample

1st row게시판 광고료
2nd row관리비 연체료 수납
3rd row10월분 한전검침수당
4th row관리비 연체료 수납
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3822
 
14.2%
수납 3700
 
13.7%
연체료 3690
 
13.7%
10월분 452
 
1.7%
357
 
1.3%
승강기 293
 
1.1%
10월 289
 
1.1%
승강기사용료 243
 
0.9%
사용료 218
 
0.8%
9월분 206
 
0.8%
Other values (7334) 13644
50.7%
2024-05-11T02:28:18.723023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17245
 
12.1%
1 6597
 
4.6%
0 5990
 
4.2%
료 5897
 
4.1%
수 5296
 
3.7%
비 4526
 
3.2%
리 4360
 
3.1%
관 4018
 
2.8%
체 3913
 
2.8%
연 3770
 
2.6%
Other values (715) 80656
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89106
62.6%
Decimal Number 23089
 
16.2%
Space Separator 17245
 
12.1%
Other Punctuation 3255
 
2.3%
Close Punctuation 2916
 
2.0%
Open Punctuation 2907
 
2.0%
Dash Punctuation 2434
 
1.7%
Uppercase Letter 703
 
0.5%
Math Symbol 344
 
0.2%
Lowercase Letter 150
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5897
 
6.6%
수 5296
 
5.9%
비 4526
 
5.1%
리 4360
 
4.9%
관 4018
 
4.5%
체 3913
 
4.4%
연 3770
 
4.2%
납 3760
 
4.2%
용 1817
 
2.0%
사 1733
 
1.9%
Other values (628) 50016
56.1%
Uppercase Letter
ValueCountFrequency (%)
N 70
 
10.0%
T 68
 
9.7%
K 67
 
9.5%
B 59
 
8.4%
A 43
 
6.1%
C 43
 
6.1%
O 41
 
5.8%
L 39
 
5.5%
G 38
 
5.4%
S 30
 
4.3%
Other values (14) 205
29.2%
Lowercase Letter
ValueCountFrequency (%)
o 39
26.0%
n 17
11.3%
k 15
 
10.0%
a 10
 
6.7%
t 10
 
6.7%
e 9
 
6.0%
b 8
 
5.3%
s 5
 
3.3%
m 5
 
3.3%
c 5
 
3.3%
Other values (14) 27
18.0%
Other Punctuation
ValueCountFrequency (%)
/ 895
27.5%
. 785
24.1%
, 622
19.1%
? 591
18.2%
: 184
 
5.7%
* 93
 
2.9%
@ 37
 
1.1%
% 22
 
0.7%
# 11
 
0.3%
' 5
 
0.2%
Other values (4) 10
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 6597
28.6%
0 5990
25.9%
2 3391
14.7%
3 1540
 
6.7%
4 1190
 
5.2%
9 1086
 
4.7%
5 1062
 
4.6%
6 844
 
3.7%
7 716
 
3.1%
8 673
 
2.9%
Math Symbol
ValueCountFrequency (%)
~ 271
78.8%
> 20
 
5.8%
= 16
 
4.7%
+ 15
 
4.4%
× 12
 
3.5%
< 8
 
2.3%
→ 1
 
0.3%
÷ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2826
96.9%
] 90
 
3.1%
Open Punctuation
ValueCountFrequency (%)
( 2819
97.0%
[ 88
 
3.0%
Space Separator
ValueCountFrequency (%)
17245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2434
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89099
62.6%
Common 52309
36.8%
Latin 853
 
0.6%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5897
 
6.6%
수 5296
 
5.9%
비 4526
 
5.1%
리 4360
 
4.9%
관 4018
 
4.5%
체 3913
 
4.4%
연 3770
 
4.2%
납 3760
 
4.2%
용 1817
 
2.0%
사 1733
 
1.9%
Other values (625) 50009
56.1%
Latin
ValueCountFrequency (%)
N 70
 
8.2%
T 68
 
8.0%
K 67
 
7.9%
B 59
 
6.9%
A 43
 
5.0%
C 43
 
5.0%
O 41
 
4.8%
o 39
 
4.6%
L 39
 
4.6%
G 38
 
4.5%
Other values (38) 346
40.6%
Common
ValueCountFrequency (%)
17245
33.0%
1 6597
 
12.6%
0 5990
 
11.5%
2 3391
 
6.5%
) 2826
 
5.4%
( 2819
 
5.4%
- 2434
 
4.7%
3 1540
 
2.9%
4 1190
 
2.3%
9 1086
 
2.1%
Other values (29) 7191
13.7%
Han
ValueCountFrequency (%)
入 5
71.4%
中 1
 
14.3%
外 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89099
62.6%
ASCII 53147
37.4%
None 14
 
< 0.1%
CJK 7
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17245
32.4%
1 6597
 
12.4%
0 5990
 
11.3%
2 3391
 
6.4%
) 2826
 
5.3%
( 2819
 
5.3%
- 2434
 
4.6%
3 1540
 
2.9%
4 1190
 
2.2%
9 1086
 
2.0%
Other values (73) 8029
15.1%
Hangul
ValueCountFrequency (%)
료 5897
 
6.6%
수 5296
 
5.9%
비 4526
 
5.1%
리 4360
 
4.9%
관 4018
 
4.5%
체 3913
 
4.4%
연 3770
 
4.2%
납 3760
 
4.2%
용 1817
 
2.0%
사 1733
 
1.9%
Other values (625) 50009
56.1%
None
ValueCountFrequency (%)
× 12
85.7%
÷ 1
 
7.1%
· 1
 
7.1%
CJK
ValueCountFrequency (%)
入 5
71.4%
中 1
 
14.3%
外 1
 
14.3%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

Interactions

2024-05-11T02:28:07.066866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:28:06.273817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:28:07.476113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:28:06.714806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:28:19.069683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3480.284
년월일0.3481.0000.000
금액0.2840.0001.000
2024-05-11T02:28:19.519845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0460.137
금액0.0461.0000.165
비용명0.1370.1651.000

Missing values

2024-05-11T02:28:07.967149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:28:08.508816image/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
20942성수금호3차A13311101광고료수익2022101830000게시판 광고료
27521돈암동일하이빌A13603501연체료수익202210254450관리비 연체료 수납
12810동양엔파트A12181101검침수익202210136862010월분 한전검침수당
49280가산두산위브A15380403연체료수익2022102515980관리비 연체료 수납
55734신정양천A15807707연체료수익202210115460관리비 연체료 수납
38196월계시영고층A13984005연체료수익20221015400관리비 연체료 수납
7024올림픽파크한양수자인A10027354이자수익202210052619796정기예금 해약만기이자-우리은행1020-444-785290
32182신반포4차A13790828연체료수익20221022100관리비 연체료 수납
46626구로한일유엔아이A15205104기타운영수익2022101250000헬스장이용료(강경희 - 3개월)
13650응암신동아A12201101연체료수익20221006150관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
38370월계동신A13984604연체료수익2022102616280관리비 연체료 수납
43791문래현대1차A15009604연체료수익20221025130관리비 연체료 수납
5119힐스테이트청계A10026104기타운영수익20221006419890골프연습장/헬스강습/공용락카/골프락카 사용수입
15979이문현대A13082703알뜰시장수익2022100630000일일장 (두부)-김영환
54571화곡푸르지오A15792602승강기수익20221024100000113동701호 내부수리승강기사용료
56336신정뉴타운두산위브A15883401잡수익202210257전기요금(주택용)체크카드 할인요금
44613대림3동현대아파트A15081604광고료수익2022101150000?????-?????
28412길음뉴타운푸르지오아파트2,3단지A13611007광고료수익20221027100000우편함광고-동북쇼핑 식자재마트
48730신도림우성1,2차A15288806광고료수익2022102510416010월분 시설물광고료-동양기획(5/24회)
3933항동하버라인3단지A10025614기타운영수익2022101650000304동 306호 게스트하우스 이용료