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 = 35.39944147)Skewed

Reproduction

Analysis started2024-05-11 02:24:45.951774
Analysis finished2024-05-11 02:24:49.347631
Duration3.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2211
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:49.653067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.5357
Min length2

Characters and Unicode

Total characters75357
Distinct characters433
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

Unique248 ?
Unique (%)2.5%

Sample

1st row서초한빛삼성
2nd row잠실푸르지오월드마크
3rd row목동롯데캐슬 마에스트로
4th row하계청솔
5th row송파파인타운9단지
ValueCountFrequency (%)
아파트 207
 
1.9%
래미안 52
 
0.5%
아이파크 37
 
0.3%
고덕 31
 
0.3%
힐스테이트 30
 
0.3%
e편한세상 28
 
0.3%
마포래미안푸르지오 26
 
0.2%
sk뷰 25
 
0.2%
롯데캐슬아파트 23
 
0.2%
센트럴 23
 
0.2%
Other values (2295) 10520
95.6%
2024-05-11T02:24:50.522262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2745
 
3.6%
파 2716
 
3.6%
트 2586
 
3.4%
지 2106
 
2.8%
단 1681
 
2.2%
대 1555
 
2.1%
동 1523
 
2.0%
이 1521
 
2.0%
신 1311
 
1.7%
차 1212
 
1.6%
Other values (423) 56401
74.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68892
91.4%
Decimal Number 3656
 
4.9%
Space Separator 1101
 
1.5%
Uppercase Letter 910
 
1.2%
Lowercase Letter 310
 
0.4%
Open Punctuation 131
 
0.2%
Close Punctuation 131
 
0.2%
Other Punctuation 113
 
0.1%
Dash Punctuation 107
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2745
 
4.0%
파 2716
 
3.9%
트 2586
 
3.8%
지 2106
 
3.1%
단 1681
 
2.4%
대 1555
 
2.3%
동 1523
 
2.2%
이 1521
 
2.2%
신 1311
 
1.9%
차 1212
 
1.8%
Other values (378) 49936
72.5%
Uppercase Letter
ValueCountFrequency (%)
S 161
17.7%
C 118
13.0%
K 117
12.9%
M 90
9.9%
D 90
9.9%
H 61
 
6.7%
I 47
 
5.2%
E 45
 
4.9%
L 41
 
4.5%
A 34
 
3.7%
Other values (7) 106
11.6%
Lowercase Letter
ValueCountFrequency (%)
e 180
58.1%
s 29
 
9.4%
k 28
 
9.0%
i 20
 
6.5%
l 18
 
5.8%
v 15
 
4.8%
w 9
 
2.9%
c 4
 
1.3%
h 3
 
1.0%
a 2
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 1067
29.2%
2 1040
28.4%
3 455
12.4%
4 302
 
8.3%
5 234
 
6.4%
6 144
 
3.9%
7 131
 
3.6%
9 129
 
3.5%
8 98
 
2.7%
0 56
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 97
85.8%
. 16
 
14.2%
Space Separator
ValueCountFrequency (%)
1101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68892
91.4%
Common 5239
 
7.0%
Latin 1226
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2745
 
4.0%
파 2716
 
3.9%
트 2586
 
3.8%
지 2106
 
3.1%
단 1681
 
2.4%
대 1555
 
2.3%
동 1523
 
2.2%
이 1521
 
2.2%
신 1311
 
1.9%
차 1212
 
1.8%
Other values (378) 49936
72.5%
Latin
ValueCountFrequency (%)
e 180
14.7%
S 161
13.1%
C 118
9.6%
K 117
9.5%
M 90
 
7.3%
D 90
 
7.3%
H 61
 
5.0%
I 47
 
3.8%
E 45
 
3.7%
L 41
 
3.3%
Other values (19) 276
22.5%
Common
ValueCountFrequency (%)
1101
21.0%
1 1067
20.4%
2 1040
19.9%
3 455
8.7%
4 302
 
5.8%
5 234
 
4.5%
6 144
 
2.7%
7 131
 
2.5%
( 131
 
2.5%
) 131
 
2.5%
Other values (6) 503
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68892
91.4%
ASCII 6459
 
8.6%
Number Forms 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2745
 
4.0%
파 2716
 
3.9%
트 2586
 
3.8%
지 2106
 
3.1%
단 1681
 
2.4%
대 1555
 
2.3%
동 1523
 
2.2%
이 1521
 
2.2%
신 1311
 
1.9%
차 1212
 
1.8%
Other values (378) 49936
72.5%
ASCII
ValueCountFrequency (%)
1101
17.0%
1 1067
16.5%
2 1040
16.1%
3 455
 
7.0%
4 302
 
4.7%
5 234
 
3.6%
e 180
 
2.8%
S 161
 
2.5%
6 144
 
2.2%
7 131
 
2.0%
Other values (34) 1644
25.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 6
100.0%

아파트코드
Text

Distinct2215
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:51.093477image/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

Unique248 ?
Unique (%)2.5%

Sample

1st rowA13787105
2nd rowA13872503
3rd rowA10026023
4th rowA13923108
5th rowA13821007
ValueCountFrequency (%)
a12175203 26
 
0.3%
a10044002 19
 
0.2%
a13676101 17
 
0.2%
a13508009 17
 
0.2%
a13707010 16
 
0.2%
a13879102 16
 
0.2%
a13527203 16
 
0.2%
a14272309 16
 
0.2%
a14072701 15
 
0.1%
a13611008 15
 
0.1%
Other values (2205) 9827
98.3%
2024-05-11T02:24:51.912910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18864
21.0%
1 17320
19.2%
A 9989
11.1%
3 8694
9.7%
2 8528
9.5%
5 6096
 
6.8%
8 5341
 
5.9%
7 4690
 
5.2%
4 4112
 
4.6%
6 3373
 
3.7%
Other values (2) 2993
 
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 18864
23.6%
1 17320
21.6%
3 8694
10.9%
2 8528
10.7%
5 6096
 
7.6%
8 5341
 
6.7%
7 4690
 
5.9%
4 4112
 
5.1%
6 3373
 
4.2%
9 2982
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9989
99.9%
B 11
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18864
23.6%
1 17320
21.6%
3 8694
10.9%
2 8528
10.7%
5 6096
 
7.6%
8 5341
 
6.7%
7 4690
 
5.9%
4 4112
 
5.1%
6 3373
 
4.2%
9 2982
 
3.7%
Latin
ValueCountFrequency (%)
A 9989
99.9%
B 11
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18864
21.0%
1 17320
19.2%
A 9989
11.1%
3 8694
9.7%
2 8528
9.5%
5 6096
 
6.8%
8 5341
 
5.9%
7 4690
 
5.2%
4 4112
 
4.6%
6 3373
 
3.7%
Other values (2) 2993
 
3.3%

비용명
Categorical

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3277 
승강기수익
1054 
이자수익
1023 
잡수익
921 
광고료수익
899 
Other values (9)
2826 

Length

Max length9
Median length5
Mean length4.8064
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3277
32.8%
승강기수익 1054
 
10.5%
이자수익 1023
 
10.2%
잡수익 921
 
9.2%
광고료수익 899
 
9.0%
기타운영수익 836
 
8.4%
주차장수익 807
 
8.1%
검침수익 302
 
3.0%
임대료수익 247
 
2.5%
부과차익 199
 
2.0%
Other values (4) 435
 
4.3%

Length

2024-05-11T02:24:52.353129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3277
32.8%
승강기수익 1054
 
10.5%
이자수익 1023
 
10.2%
잡수익 921
 
9.2%
광고료수익 899
 
9.0%
기타운영수익 836
 
8.4%
주차장수익 807
 
8.1%
검침수익 302
 
3.0%
임대료수익 247
 
2.5%
부과차익 199
 
2.0%
Other values (4) 435
 
4.3%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230617
Minimum20230601
Maximum20230630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:24:52.715317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230601
5-th percentile20230601
Q120230609
median20230617
Q320230626
95-th percentile20230630
Maximum20230630
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.2582632
Coefficient of variation (CV)4.5763622 × 10-7
Kurtosis-1.2204549
Mean20230617
Median Absolute Deviation (MAD)8
Skewness-0.19229696
Sum2.0230617 × 1011
Variance85.715438
MonotonicityNot monotonic
2024-05-11T02:24:53.107457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20230630 1010
 
10.1%
20230601 513
 
5.1%
20230626 474
 
4.7%
20230612 454
 
4.5%
20230629 441
 
4.4%
20230617 435
 
4.3%
20230627 421
 
4.2%
20230623 415
 
4.2%
20230605 402
 
4.0%
20230607 385
 
3.9%
Other values (20) 5050
50.5%
ValueCountFrequency (%)
20230601 513
5.1%
20230602 376
3.8%
20230603 96
 
1.0%
20230604 77
 
0.8%
20230605 402
4.0%
20230606 97
 
1.0%
20230607 385
3.9%
20230608 328
3.3%
20230609 279
2.8%
20230610 367
3.7%
ValueCountFrequency (%)
20230630 1010
10.1%
20230629 441
4.4%
20230628 357
 
3.6%
20230627 421
4.2%
20230626 474
4.7%
20230625 284
 
2.8%
20230624 161
 
1.6%
20230623 415
4.2%
20230622 292
 
2.9%
20230621 274
 
2.7%

금액
Real number (ℝ)

SKEWED 

Distinct3891
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277541.89
Minimum-13000000
Maximum1.342044 × 108
Zeros20
Zeros (%)0.2%
Negative29
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T02:24:53.446827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-13000000
5-th percentile170
Q12570
median22565
Q392281.75
95-th percentile990500
Maximum1.342044 × 108
Range1.472044 × 108
Interquartile range (IQR)89711.75

Descriptive statistics

Standard deviation2054088.9
Coefficient of variation (CV)7.4010048
Kurtosis1967.4936
Mean277541.89
Median Absolute Deviation (MAD)22000.5
Skewness35.399441
Sum2.7754189 × 109
Variance4.2192811 × 1012
MonotonicityNot monotonic
2024-05-11T02:24:53.894988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 534
 
5.3%
30000 501
 
5.0%
100000 459
 
4.6%
60000 156
 
1.6%
150000 142
 
1.4%
200000 137
 
1.4%
40000 130
 
1.3%
70000 117
 
1.2%
20000 113
 
1.1%
80000 94
 
0.9%
Other values (3881) 7617
76.2%
ValueCountFrequency (%)
-13000000 1
< 0.1%
-10901280 1
< 0.1%
-5517035 1
< 0.1%
-4207500 1
< 0.1%
-1375000 1
< 0.1%
-280000 1
< 0.1%
-166670 1
< 0.1%
-160000 1
< 0.1%
-152728 1
< 0.1%
-130000 1
< 0.1%
ValueCountFrequency (%)
134204400 1
< 0.1%
64980000 1
< 0.1%
38858170 1
< 0.1%
37090684 1
< 0.1%
36279990 1
< 0.1%
34000000 1
< 0.1%
31400727 1
< 0.1%
30310000 1
< 0.1%
27007320 1
< 0.1%
25440000 1
< 0.1%

내용
Text

Distinct5985
Distinct (%)59.9%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:24:54.548810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length64
Mean length14.467421
Min length1

Characters and Unicode

Total characters144544
Distinct characters725
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

Unique5734 ?
Unique (%)57.4%

Sample

1st row101동 408호 승강기사용료(인테리어)
2nd row관리비 연체료 수납
3rd row관리비 연체료 수납
4th row관리비 연체료 수납
5th row임대수익
ValueCountFrequency (%)
관리비 3458
 
12.9%
수납 3286
 
12.3%
연체료 3282
 
12.3%
402
 
1.5%
승강기 383
 
1.4%
6월분 282
 
1.1%
사용료 244
 
0.9%
승강기사용료 239
 
0.9%
6월 212
 
0.8%
입금 210
 
0.8%
Other values (7658) 14708
55.1%
2024-05-11T02:24:55.696915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17094
 
11.8%
료 5370
 
3.7%
0 5283
 
3.7%
수 4997
 
3.5%
1 4612
 
3.2%
비 4277
 
3.0%
리 4262
 
2.9%
관 3866
 
2.7%
체 3517
 
2.4%
연 3378
 
2.3%
Other values (715) 87888
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90872
62.9%
Decimal Number 23091
 
16.0%
Space Separator 17094
 
11.8%
Close Punctuation 3307
 
2.3%
Open Punctuation 3299
 
2.3%
Other Punctuation 2928
 
2.0%
Dash Punctuation 2655
 
1.8%
Uppercase Letter 676
 
0.5%
Math Symbol 387
 
0.3%
Lowercase Letter 124
 
0.1%
Other values (2) 111
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5370
 
5.9%
수 4997
 
5.5%
비 4277
 
4.7%
리 4262
 
4.7%
관 3866
 
4.3%
체 3517
 
3.9%
연 3378
 
3.7%
납 3343
 
3.7%
이 1919
 
2.1%
용 1770
 
1.9%
Other values (629) 54173
59.6%
Uppercase Letter
ValueCountFrequency (%)
N 75
 
11.1%
B 71
 
10.5%
C 57
 
8.4%
T 54
 
8.0%
K 46
 
6.8%
O 45
 
6.7%
L 42
 
6.2%
G 37
 
5.5%
A 31
 
4.6%
S 28
 
4.1%
Other values (16) 190
28.1%
Lowercase Letter
ValueCountFrequency (%)
o 26
21.0%
e 12
9.7%
k 11
 
8.9%
s 10
 
8.1%
t 8
 
6.5%
n 8
 
6.5%
a 7
 
5.6%
p 5
 
4.0%
d 5
 
4.0%
c 4
 
3.2%
Other values (13) 28
22.6%
Other Punctuation
ValueCountFrequency (%)
/ 915
31.2%
. 873
29.8%
, 589
20.1%
? 182
 
6.2%
: 170
 
5.8%
* 97
 
3.3%
@ 48
 
1.6%
% 24
 
0.8%
# 16
 
0.5%
& 7
 
0.2%
Other values (3) 7
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 5283
22.9%
1 4612
20.0%
2 3208
13.9%
6 2303
10.0%
3 2153
9.3%
5 1630
 
7.1%
4 1419
 
6.1%
7 1032
 
4.5%
8 727
 
3.1%
9 724
 
3.1%
Math Symbol
ValueCountFrequency (%)
~ 328
84.8%
+ 21
 
5.4%
> 16
 
4.1%
× 9
 
2.3%
< 8
 
2.1%
= 5
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 3197
96.7%
] 110
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 3194
96.8%
[ 105
 
3.2%
Space Separator
ValueCountFrequency (%)
17094
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2655
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 110
100.0%
Other Number
ValueCountFrequency (%)
③ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90866
62.9%
Common 52872
36.6%
Latin 800
 
0.6%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5370
 
5.9%
수 4997
 
5.5%
비 4277
 
4.7%
리 4262
 
4.7%
관 3866
 
4.3%
체 3517
 
3.9%
연 3378
 
3.7%
납 3343
 
3.7%
이 1919
 
2.1%
용 1770
 
1.9%
Other values (626) 54167
59.6%
Latin
ValueCountFrequency (%)
N 75
 
9.4%
B 71
 
8.9%
C 57
 
7.1%
T 54
 
6.8%
K 46
 
5.8%
O 45
 
5.6%
L 42
 
5.2%
G 37
 
4.6%
A 31
 
3.9%
S 28
 
3.5%
Other values (39) 314
39.2%
Common
ValueCountFrequency (%)
17094
32.3%
0 5283
 
10.0%
1 4612
 
8.7%
2 3208
 
6.1%
) 3197
 
6.0%
( 3194
 
6.0%
- 2655
 
5.0%
6 2303
 
4.4%
3 2153
 
4.1%
5 1630
 
3.1%
Other values (27) 7543
14.3%
Han
ValueCountFrequency (%)
入 4
66.7%
大 1
 
16.7%
小 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90865
62.9%
ASCII 53662
37.1%
None 9
 
< 0.1%
CJK 6
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17094
31.9%
0 5283
 
9.8%
1 4612
 
8.6%
2 3208
 
6.0%
) 3197
 
6.0%
( 3194
 
6.0%
- 2655
 
4.9%
6 2303
 
4.3%
3 2153
 
4.0%
5 1630
 
3.0%
Other values (74) 8333
15.5%
Hangul
ValueCountFrequency (%)
료 5370
 
5.9%
수 4997
 
5.5%
비 4277
 
4.7%
리 4262
 
4.7%
관 3866
 
4.3%
체 3517
 
3.9%
연 3378
 
3.7%
납 3343
 
3.7%
이 1919
 
2.1%
용 1770
 
1.9%
Other values (625) 54166
59.6%
None
ValueCountFrequency (%)
× 9
100.0%
CJK
ValueCountFrequency (%)
入 4
66.7%
大 1
 
16.7%
小 1
 
16.7%
Enclosed Alphanum
ValueCountFrequency (%)
③ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
100.0%

Interactions

2024-05-11T02:24:48.135868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:47.530334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:48.451784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:47.804454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:24:55.932509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4710.288
년월일0.4711.0000.147
금액0.2880.1471.000
2024-05-11T02:24:56.085326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0390.214
금액0.0391.0000.146
비용명0.2140.1461.000

Missing values

2024-05-11T02:24:48.836498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:24:49.194669image/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
36474서초한빛삼성A13787105승강기수익2023061380000101동 408호 승강기사용료(인테리어)
39034잠실푸르지오월드마크A13872503연체료수익20230630310관리비 연체료 수납
6362목동롯데캐슬 마에스트로A10026023연체료수익20230602150관리비 연체료 수납
41585하계청솔A13923108연체료수익20230613950관리비 연체료 수납
38299송파파인타운9단지A13821007임대료수익20230601800000임대수익
16164북한산힐스테이트3차A12204004승강기수익20230620120000승강기료 (3306-1503)
7388옥수파크힐스아파트A10026748연체료수익202306071580관리비 연체료 수납
2154마곡엠밸리9단지A10024426연체료수익202306079660관리비 연체료 수납
7011래미안서초에스티지에스아파트A10026411승강기수익20230608200000승강기수입(203-1002)6/10전출
45213상계한양A13994302연체료수익202306278350관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
40986상계주공9단지A13921005이자수익202306116363결산이자(기업)
55128구로보광A15285503주차장수익20230624210000외부주차(3건)
16992이편한세상 수색 에코포레A12287204연체료수익202306295030관리비 연체료 수납
5025래미안장위포레카운티아파트A10025461기타운영수익2023061367679커뮤니티센터 커피머신 이용료
56407독산진도3차A15383604이자수익202306171140이자수입 - 장기수선예금[새마을,2696-1]
39265송파꿈에그린아파트A13876114승강기수익202306212000002-2002 인테리어 승강기사용료
22804도봉서울가든A13281201연체료수익202306093670관리비 연체료 수납
17629답십리동아A13003406이자수익2023062558442수협(잡수입)통장 이자수익 (2010-0812-3840)
44915하계극동건영벽산A13987306연체료수익202306068030관리비 연체료 수납
20233면목두산4,5단지A13184107검침수익20230627238650검침수당(2023년5월분)