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 = 47.56623477)Skewed

Reproduction

Analysis started2024-05-11 02:31:27.962564
Analysis finished2024-05-11 02:31:32.912895
Duration4.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2168
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:31:33.439818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length7.3529
Min length2

Characters and Unicode

Total characters73529
Distinct characters429
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

Unique223 ?
Unique (%)2.2%

Sample

1st rowe편한세상화랑대아파트
2nd row장안한신
3rd row홍은벽산
4th row정릉풍림아이원임대
5th row송파파인타운10단지
ValueCountFrequency (%)
아파트 191
 
1.8%
래미안 39
 
0.4%
아이파크 38
 
0.4%
e편한세상 25
 
0.2%
힐스테이트 21
 
0.2%
sk뷰 21
 
0.2%
헬리오시티아파트 21
 
0.2%
도봉한신 21
 
0.2%
래미안트리베라1차 20
 
0.2%
고덕 19
 
0.2%
Other values (2235) 10364
96.1%
2024-05-11T02:31:34.585961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2602
 
3.5%
파 2528
 
3.4%
트 2422
 
3.3%
지 2005
 
2.7%
대 1694
 
2.3%
단 1589
 
2.2%
동 1517
 
2.1%
이 1422
 
1.9%
신 1333
 
1.8%
차 1290
 
1.8%
Other values (419) 55127
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67292
91.5%
Decimal Number 3634
 
4.9%
Space Separator 885
 
1.2%
Uppercase Letter 843
 
1.1%
Lowercase Letter 342
 
0.5%
Close Punctuation 149
 
0.2%
Open Punctuation 149
 
0.2%
Dash Punctuation 129
 
0.2%
Other Punctuation 102
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2602
 
3.9%
파 2528
 
3.8%
트 2422
 
3.6%
지 2005
 
3.0%
대 1694
 
2.5%
단 1589
 
2.4%
동 1517
 
2.3%
이 1422
 
2.1%
신 1333
 
2.0%
차 1290
 
1.9%
Other values (374) 48890
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 152
18.0%
K 115
13.6%
C 112
13.3%
D 79
9.4%
M 79
9.4%
H 59
 
7.0%
L 50
 
5.9%
E 37
 
4.4%
I 33
 
3.9%
A 31
 
3.7%
Other values (7) 96
11.4%
Lowercase Letter
ValueCountFrequency (%)
e 190
55.6%
l 34
 
9.9%
s 28
 
8.2%
i 23
 
6.7%
k 23
 
6.7%
v 18
 
5.3%
h 9
 
2.6%
c 8
 
2.3%
w 3
 
0.9%
a 3
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 1100
30.3%
2 1034
28.5%
3 447
12.3%
4 264
 
7.3%
5 220
 
6.1%
6 158
 
4.3%
7 125
 
3.4%
9 109
 
3.0%
8 105
 
2.9%
0 72
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 89
87.3%
. 13
 
12.7%
Space Separator
ValueCountFrequency (%)
885
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67292
91.5%
Common 5048
 
6.9%
Latin 1189
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2602
 
3.9%
파 2528
 
3.8%
트 2422
 
3.6%
지 2005
 
3.0%
대 1694
 
2.5%
단 1589
 
2.4%
동 1517
 
2.3%
이 1422
 
2.1%
신 1333
 
2.0%
차 1290
 
1.9%
Other values (374) 48890
72.7%
Latin
ValueCountFrequency (%)
e 190
16.0%
S 152
12.8%
K 115
9.7%
C 112
 
9.4%
D 79
 
6.6%
M 79
 
6.6%
H 59
 
5.0%
L 50
 
4.2%
E 37
 
3.1%
l 34
 
2.9%
Other values (19) 282
23.7%
Common
ValueCountFrequency (%)
1 1100
21.8%
2 1034
20.5%
885
17.5%
3 447
8.9%
4 264
 
5.2%
5 220
 
4.4%
6 158
 
3.1%
) 149
 
3.0%
( 149
 
3.0%
- 129
 
2.6%
Other values (6) 513
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67292
91.5%
ASCII 6233
 
8.5%
Number Forms 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2602
 
3.9%
파 2528
 
3.8%
트 2422
 
3.6%
지 2005
 
3.0%
대 1694
 
2.5%
단 1589
 
2.4%
동 1517
 
2.3%
이 1422
 
2.1%
신 1333
 
2.0%
차 1290
 
1.9%
Other values (374) 48890
72.7%
ASCII
ValueCountFrequency (%)
1 1100
17.6%
2 1034
16.6%
885
14.2%
3 447
 
7.2%
4 264
 
4.2%
5 220
 
3.5%
e 190
 
3.0%
6 158
 
2.5%
S 152
 
2.4%
) 149
 
2.4%
Other values (34) 1634
26.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%

아파트코드
Text

Distinct2173
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:31:35.355575image/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

Unique224 ?
Unique (%)2.2%

Sample

1st rowA10025855
2nd rowA13084701
3rd rowA12010104
4th rowA13676704
5th rowA13821005
ValueCountFrequency (%)
a13201209 21
 
0.2%
a10025850 21
 
0.2%
a14272309 20
 
0.2%
a12179004 19
 
0.2%
a13704104 19
 
0.2%
a13822004 18
 
0.2%
a12175203 17
 
0.2%
a15370103 17
 
0.2%
a13822003 17
 
0.2%
a13204104 16
 
0.2%
Other values (2163) 9815
98.2%
2024-05-11T02:31:36.938540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18573
20.6%
1 17157
19.1%
A 9993
11.1%
3 8836
9.8%
2 8279
9.2%
5 6379
 
7.1%
8 5520
 
6.1%
7 4812
 
5.3%
4 4040
 
4.5%
6 3381
 
3.8%
Other values (2) 3030
 
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 18573
23.2%
1 17157
21.4%
3 8836
11.0%
2 8279
10.3%
5 6379
 
8.0%
8 5520
 
6.9%
7 4812
 
6.0%
4 4040
 
5.1%
6 3381
 
4.2%
9 3023
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9993
99.9%
B 7
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18573
23.2%
1 17157
21.4%
3 8836
11.0%
2 8279
10.3%
5 6379
 
8.0%
8 5520
 
6.9%
7 4812
 
6.0%
4 4040
 
5.1%
6 3381
 
4.2%
9 3023
 
3.8%
Latin
ValueCountFrequency (%)
A 9993
99.9%
B 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18573
20.6%
1 17157
19.1%
A 9993
11.1%
3 8836
9.8%
2 8279
9.2%
5 6379
 
7.1%
8 5520
 
6.1%
7 4812
 
5.3%
4 4040
 
4.5%
6 3381
 
3.8%
Other values (2) 3030
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3506 
승강기수익
1121 
잡수익
1076 
주차장수익
915 
광고료수익
833 
Other values (10)
2549 

Length

Max length9
Median length5
Mean length5.0132
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3506
35.1%
승강기수익 1121
 
11.2%
잡수익 1076
 
10.8%
주차장수익 915
 
9.2%
광고료수익 833
 
8.3%
기타운영수익 645
 
6.5%
고용안정사업수익 497
 
5.0%
검침수익 313
 
3.1%
임대료수익 240
 
2.4%
알뜰시장수익 238
 
2.4%
Other values (5) 616
 
6.2%

Length

2024-05-11T02:31:37.485908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3506
35.1%
승강기수익 1121
 
11.2%
잡수익 1076
 
10.8%
주차장수익 915
 
9.2%
광고료수익 833
 
8.3%
기타운영수익 645
 
6.5%
고용안정사업수익 497
 
5.0%
검침수익 313
 
3.1%
임대료수익 240
 
2.4%
알뜰시장수익 238
 
2.4%
Other values (5) 616
 
6.2%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210717
Minimum20210701
Maximum20210731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:31:37.896154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210701
5-th percentile20210701
Q120210709
median20210719
Q320210726
95-th percentile20210731
Maximum20210731
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.54596
Coefficient of variation (CV)4.7232168 × 10-7
Kurtosis-1.2360005
Mean20210717
Median Absolute Deviation (MAD)8
Skewness-0.19683856
Sum2.0210717 × 1011
Variance91.125352
MonotonicityNot monotonic
2024-05-11T02:31:38.312322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210731 698
 
7.0%
20210730 565
 
5.7%
20210715 531
 
5.3%
20210701 528
 
5.3%
20210726 519
 
5.2%
20210719 485
 
4.9%
20210723 474
 
4.7%
20210705 460
 
4.6%
20210712 446
 
4.5%
20210720 401
 
4.0%
Other values (21) 4893
48.9%
ValueCountFrequency (%)
20210701 528
5.3%
20210702 368
3.7%
20210703 90
 
0.9%
20210704 76
 
0.8%
20210705 460
4.6%
20210706 342
3.4%
20210707 270
2.7%
20210708 294
2.9%
20210709 312
3.1%
20210710 85
 
0.9%
ValueCountFrequency (%)
20210731 698
7.0%
20210730 565
5.7%
20210729 335
3.4%
20210728 367
3.7%
20210727 391
3.9%
20210726 519
5.2%
20210725 169
 
1.7%
20210724 136
 
1.4%
20210723 474
4.7%
20210722 332
3.3%

금액
Real number (ℝ)

SKEWED 

Distinct3154
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean267550.72
Minimum-3280000
Maximum1.8144 × 108
Zeros14
Zeros (%)0.1%
Negative43
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:31:38.813014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3280000
5-th percentile90
Q12207.5
median30000
Q3100000
95-th percentile894372.2
Maximum1.8144 × 108
Range1.8472 × 108
Interquartile range (IQR)97792.5

Descriptive statistics

Standard deviation2559582.2
Coefficient of variation (CV)9.5667179
Kurtosis2910.8257
Mean267550.72
Median Absolute Deviation (MAD)29410
Skewness47.566235
Sum2.6755072 × 109
Variance6.5514611 × 1012
MonotonicityNot monotonic
2024-05-11T02:31:39.367620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 577
 
5.8%
30000 567
 
5.7%
100000 526
 
5.3%
200000 187
 
1.9%
60000 153
 
1.5%
150000 150
 
1.5%
70000 139
 
1.4%
40000 135
 
1.4%
80000 96
 
1.0%
20000 95
 
0.9%
Other values (3144) 7375
73.8%
ValueCountFrequency (%)
-3280000 1
< 0.1%
-1556050 1
< 0.1%
-1348600 1
< 0.1%
-820000 1
< 0.1%
-660000 1
< 0.1%
-390000 1
< 0.1%
-320000 1
< 0.1%
-300000 1
< 0.1%
-201673 1
< 0.1%
-200000 1
< 0.1%
ValueCountFrequency (%)
181440000 1
< 0.1%
97457861 1
< 0.1%
93000400 1
< 0.1%
37817150 1
< 0.1%
37240850 1
< 0.1%
37192000 1
< 0.1%
31520110 1
< 0.1%
27497180 1
< 0.1%
27024300 1
< 0.1%
26070000 1
< 0.1%

내용
Text

Distinct5787
Distinct (%)57.9%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:31:40.449457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length75
Mean length14.173691
Min length1

Characters and Unicode

Total characters141581
Distinct characters715
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

Unique5531 ?
Unique (%)55.4%

Sample

1st row7월 상가 주차장 이용 수입(탑차,1대)
2nd row관리비 연체료 수납
3rd row재활용수거비용-협성펄프(7월분)
4th row관리비 연체료 수납
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3651
 
13.8%
수납 3518
 
13.3%
연체료 3515
 
13.3%
7월분 363
 
1.4%
승강기 322
 
1.2%
6월분 288
 
1.1%
승강기사용료 254
 
1.0%
238
 
0.9%
입금 236
 
0.9%
7월 231
 
0.9%
Other values (7307) 13824
52.3%
2024-05-11T02:31:41.985675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16555
 
11.7%
료 5563
 
3.9%
0 5043
 
3.6%
수 4969
 
3.5%
리 4888
 
3.5%
1 4881
 
3.4%
비 4451
 
3.1%
관 3881
 
2.7%
체 3708
 
2.6%
납 3655
 
2.6%
Other values (705) 83987
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90563
64.0%
Decimal Number 22021
 
15.6%
Space Separator 16555
 
11.7%
Close Punctuation 3060
 
2.2%
Open Punctuation 3053
 
2.2%
Other Punctuation 2772
 
2.0%
Dash Punctuation 2328
 
1.6%
Uppercase Letter 662
 
0.5%
Math Symbol 339
 
0.2%
Lowercase Letter 132
 
0.1%
Other values (2) 96
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5563
 
6.1%
수 4969
 
5.5%
리 4888
 
5.4%
비 4451
 
4.9%
관 3881
 
4.3%
체 3708
 
4.1%
납 3655
 
4.0%
연 3585
 
4.0%
월 1899
 
2.1%
사 1825
 
2.0%
Other values (622) 52139
57.6%
Uppercase Letter
ValueCountFrequency (%)
N 69
 
10.4%
T 52
 
7.9%
K 45
 
6.8%
L 43
 
6.5%
A 42
 
6.3%
B 41
 
6.2%
D 39
 
5.9%
O 38
 
5.7%
C 38
 
5.7%
F 34
 
5.1%
Other values (15) 221
33.4%
Lowercase Letter
ValueCountFrequency (%)
o 41
31.1%
x 16
 
12.1%
n 12
 
9.1%
k 11
 
8.3%
s 9
 
6.8%
a 7
 
5.3%
e 7
 
5.3%
b 4
 
3.0%
t 4
 
3.0%
d 3
 
2.3%
Other values (10) 18
13.6%
Other Punctuation
ValueCountFrequency (%)
/ 788
28.4%
. 784
28.3%
, 747
26.9%
: 188
 
6.8%
* 143
 
5.2%
? 39
 
1.4%
@ 35
 
1.3%
% 24
 
0.9%
& 9
 
0.3%
' 7
 
0.3%
Other values (3) 8
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 5043
22.9%
1 4881
22.2%
2 3106
14.1%
7 2118
9.6%
6 1577
 
7.2%
3 1485
 
6.7%
4 1200
 
5.4%
5 1105
 
5.0%
8 835
 
3.8%
9 671
 
3.0%
Math Symbol
ValueCountFrequency (%)
~ 285
84.1%
+ 24
 
7.1%
> 12
 
3.5%
× 7
 
2.1%
= 6
 
1.8%
< 4
 
1.2%
⇒ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2987
97.6%
] 73
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 2979
97.6%
[ 74
 
2.4%
Space Separator
ValueCountFrequency (%)
16555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2328
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 95
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90554
64.0%
Common 50224
35.5%
Latin 794
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5563
 
6.1%
수 4969
 
5.5%
리 4888
 
5.4%
비 4451
 
4.9%
관 3881
 
4.3%
체 3708
 
4.1%
납 3655
 
4.0%
연 3585
 
4.0%
월 1899
 
2.1%
사 1825
 
2.0%
Other values (616) 52130
57.6%
Latin
ValueCountFrequency (%)
N 69
 
8.7%
T 52
 
6.5%
K 45
 
5.7%
L 43
 
5.4%
A 42
 
5.3%
o 41
 
5.2%
B 41
 
5.2%
D 39
 
4.9%
O 38
 
4.8%
C 38
 
4.8%
Other values (35) 346
43.6%
Common
ValueCountFrequency (%)
16555
33.0%
0 5043
 
10.0%
1 4881
 
9.7%
2 3106
 
6.2%
) 2987
 
5.9%
( 2979
 
5.9%
- 2328
 
4.6%
7 2118
 
4.2%
6 1577
 
3.1%
3 1485
 
3.0%
Other values (28) 7165
14.3%
Han
ValueCountFrequency (%)
入 4
44.4%
人 1
 
11.1%
內 1
 
11.1%
出 1
 
11.1%
不 1
 
11.1%
用 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90554
64.0%
ASCII 51010
36.0%
CJK 8
 
< 0.1%
None 7
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16555
32.5%
0 5043
 
9.9%
1 4881
 
9.6%
2 3106
 
6.1%
) 2987
 
5.9%
( 2979
 
5.8%
- 2328
 
4.6%
7 2118
 
4.2%
6 1577
 
3.1%
3 1485
 
2.9%
Other values (71) 7951
15.6%
Hangul
ValueCountFrequency (%)
료 5563
 
6.1%
수 4969
 
5.5%
리 4888
 
5.4%
비 4451
 
4.9%
관 3881
 
4.3%
체 3708
 
4.1%
납 3655
 
4.0%
연 3585
 
4.0%
월 1899
 
2.1%
사 1825
 
2.0%
Other values (616) 52130
57.6%
None
ValueCountFrequency (%)
× 7
100.0%
CJK
ValueCountFrequency (%)
入 4
50.0%
人 1
 
12.5%
內 1
 
12.5%
出 1
 
12.5%
用 1
 
12.5%
CJK Compat Ideographs
ValueCountFrequency (%)
不 1
100.0%
Arrows
ValueCountFrequency (%)
⇒ 1
100.0%

Interactions

2024-05-11T02:31:30.515252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:29.759429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:31.173538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:30.042463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:31:42.250054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4070.133
년월일0.4071.0000.000
금액0.1330.0001.000
2024-05-11T02:31:42.550834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0270.164
금액0.0271.0000.056
비용명0.1640.0561.000

Missing values

2024-05-11T02:31:31.883658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:31:32.592261image/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
3676e편한세상화랑대아파트A10025855주차장수익202107311000007월 상가 주차장 이용 수입(탑차,1대)
16342장안한신A13084701연체료수익202107214210관리비 연체료 수납
9692홍은벽산A12010104재활용품수익20210715905400재활용수거비용-협성펄프(7월분)
31458정릉풍림아이원임대A13676704연체료수익20210709310관리비 연체료 수납
35683송파파인타운10단지A13821005연체료수익202107282260관리비 연체료 수납
4506e편한세상신촌아파트A10026370승강기수익20210729130000401동 2604호 승강기 사용료
17445신내데시앙A13178101연체료수익20210726240관리비 연체료 수납
31847정릉푸른마을동아A13684605주차장수익20210731212450007월분 2주차이상세대 주차비(102세대)
11371상암월드컵파크3단지A12127003승강기수익2021071350000303-201 전출세대 승강기사용료
23514강변건영A13392307기타운영수익202107193300106동 504호 음식물카드 발급
아파트명아파트코드비용명년월일금액내용
57968화곡초록A15770801기타운영수익20210708230리모컨 건전지 판매수익(102-106)
23795프라이어팰리스A13405003연체료수익20210711780관리비 연체료 수납
21940텐즈힐2구역A13373301연체료수익202107273230관리비 연체료 수납
972이편한세상 송파파크센트럴A10024787연체료수익20210701510관리비 연체료 수납
17027묵동신안3차A13114106기타운영수익202107084000103동 110호 복사비 입금
60703목동11단지A15807705광고료수익20210712100000게시판광고-강성희 메싸홈스쿨, 매직셈 (주민)
7961롯데캐슬베네치아A10044002승강기수익202107231000004-1402 전출 추가사용 7/23
27279도곡렉슬A13527203광고료수익20210726200000게시판 광고(7/26~8/1.현대썬앤빌 신사.좋은광고기획)
5295래미안용산아파트A10026922기타운영수익2021071172730무인카페 판매(47잔)
57246마곡엠밸리6단지A15721006잡수익20210709-33340스포츠센터이용료 환불-김지훈(07/03) (기안:21-263)