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 = 72.91557243)Skewed

Reproduction

Analysis started2024-05-11 02:37:28.611041
Analysis finished2024-05-11 02:37:32.493831
Duration3.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2059
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:37:32.930142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.2176
Min length2

Characters and Unicode

Total characters72176
Distinct characters423
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)2.0%

Sample

1st row양평한신
2nd row목동13단지
3rd row신수성원
4th row신천장미1차2차
5th row응봉리버그린동아
ValueCountFrequency (%)
아파트 108
 
1.0%
입주자대표회의 35
 
0.3%
래미안 31
 
0.3%
신내 28
 
0.3%
구로두산위브 20
 
0.2%
2단지 20
 
0.2%
도곡렉슬 19
 
0.2%
잠실5단지아파트 19
 
0.2%
월계그랑빌 18
 
0.2%
서초푸르지오써밋 18
 
0.2%
Other values (2114) 10258
97.0%
2024-05-11T02:37:34.244401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2296
 
3.2%
파 2257
 
3.1%
지 2061
 
2.9%
트 2045
 
2.8%
대 1713
 
2.4%
단 1650
 
2.3%
동 1604
 
2.2%
신 1475
 
2.0%
차 1419
 
2.0%
이 1300
 
1.8%
Other values (413) 54356
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65902
91.3%
Decimal Number 3978
 
5.5%
Uppercase Letter 764
 
1.1%
Space Separator 636
 
0.9%
Lowercase Letter 272
 
0.4%
Close Punctuation 165
 
0.2%
Open Punctuation 165
 
0.2%
Other Punctuation 146
 
0.2%
Dash Punctuation 130
 
0.2%
Letter Number 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2296
 
3.5%
파 2257
 
3.4%
지 2061
 
3.1%
트 2045
 
3.1%
대 1713
 
2.6%
단 1650
 
2.5%
동 1604
 
2.4%
신 1475
 
2.2%
차 1419
 
2.2%
이 1300
 
2.0%
Other values (367) 48082
73.0%
Uppercase Letter
ValueCountFrequency (%)
S 146
19.1%
K 112
14.7%
C 98
12.8%
D 62
8.1%
M 62
8.1%
H 48
 
6.3%
I 34
 
4.5%
E 31
 
4.1%
A 30
 
3.9%
L 29
 
3.8%
Other values (7) 112
14.7%
Lowercase Letter
ValueCountFrequency (%)
e 164
60.3%
l 34
 
12.5%
i 24
 
8.8%
v 18
 
6.6%
s 10
 
3.7%
h 6
 
2.2%
k 5
 
1.8%
w 5
 
1.8%
a 2
 
0.7%
g 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 1183
29.7%
2 1131
28.4%
3 492
12.4%
4 305
 
7.7%
5 248
 
6.2%
6 179
 
4.5%
9 118
 
3.0%
7 116
 
2.9%
8 105
 
2.6%
0 101
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 125
85.6%
. 21
 
14.4%
Space Separator
ValueCountFrequency (%)
636
100.0%
Close Punctuation
ValueCountFrequency (%)
) 165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 165
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65902
91.3%
Common 5227
 
7.2%
Latin 1047
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2296
 
3.5%
파 2257
 
3.4%
지 2061
 
3.1%
트 2045
 
3.1%
대 1713
 
2.6%
단 1650
 
2.5%
동 1604
 
2.4%
신 1475
 
2.2%
차 1419
 
2.2%
이 1300
 
2.0%
Other values (367) 48082
73.0%
Latin
ValueCountFrequency (%)
e 164
15.7%
S 146
13.9%
K 112
10.7%
C 98
 
9.4%
D 62
 
5.9%
M 62
 
5.9%
H 48
 
4.6%
l 34
 
3.2%
I 34
 
3.2%
E 31
 
3.0%
Other values (19) 256
24.5%
Common
ValueCountFrequency (%)
1 1183
22.6%
2 1131
21.6%
636
12.2%
3 492
9.4%
4 305
 
5.8%
5 248
 
4.7%
6 179
 
3.4%
) 165
 
3.2%
( 165
 
3.2%
- 130
 
2.5%
Other values (7) 593
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65902
91.3%
ASCII 6263
 
8.7%
Number Forms 11
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2296
 
3.5%
파 2257
 
3.4%
지 2061
 
3.1%
트 2045
 
3.1%
대 1713
 
2.6%
단 1650
 
2.5%
동 1604
 
2.4%
신 1475
 
2.2%
차 1419
 
2.2%
이 1300
 
2.0%
Other values (367) 48082
73.0%
ASCII
ValueCountFrequency (%)
1 1183
18.9%
2 1131
18.1%
636
 
10.2%
3 492
 
7.9%
4 305
 
4.9%
5 248
 
4.0%
6 179
 
2.9%
) 165
 
2.6%
( 165
 
2.6%
e 164
 
2.6%
Other values (35) 1595
25.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 11
100.0%

아파트코드
Text

Distinct2065
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:37:35.210505image/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

Unique200 ?
Unique (%)2.0%

Sample

1st rowA15010502
2nd rowA15807605
3rd rowA12185504
4th rowA13824005
5th rowA13385301
ValueCountFrequency (%)
a15205305 20
 
0.2%
a13527203 19
 
0.2%
a13879102 19
 
0.2%
a10026941 18
 
0.2%
a14272305 18
 
0.2%
a13984004 18
 
0.2%
a15884703 17
 
0.2%
a10027817 17
 
0.2%
a12175203 17
 
0.2%
a13583507 16
 
0.2%
Other values (2055) 9821
98.2%
2024-05-11T02:37:36.766071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18487
20.5%
1 17391
19.3%
A 9988
11.1%
3 8828
9.8%
2 8050
8.9%
5 6322
 
7.0%
8 5793
 
6.4%
7 4955
 
5.5%
4 3789
 
4.2%
6 3530
 
3.9%
Other values (2) 2867
 
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 18487
23.1%
1 17391
21.7%
3 8828
11.0%
2 8050
10.1%
5 6322
 
7.9%
8 5793
 
7.2%
7 4955
 
6.2%
4 3789
 
4.7%
6 3530
 
4.4%
9 2855
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9988
99.9%
B 12
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18487
23.1%
1 17391
21.7%
3 8828
11.0%
2 8050
10.1%
5 6322
 
7.9%
8 5793
 
7.2%
7 4955
 
6.2%
4 3789
 
4.7%
6 3530
 
4.4%
9 2855
 
3.6%
Latin
ValueCountFrequency (%)
A 9988
99.9%
B 12
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18487
20.5%
1 17391
19.3%
A 9988
11.1%
3 8828
9.8%
2 8050
8.9%
5 6322
 
7.0%
8 5793
 
6.4%
7 4955
 
5.5%
4 3789
 
4.2%
6 3530
 
3.9%
Other values (2) 2867
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3691 
광고료수익
1179 
승강기수익
1046 
잡수익
974 
주차장수익
872 
Other values (10)
2238 

Length

Max length9
Median length5
Mean length4.9205
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row검침수익
2nd row알뜰시장수익
3rd row잡수익
4th row연체료수익
5th row연체료수익

Common Values

ValueCountFrequency (%)
연체료수익 3691
36.9%
광고료수익 1179
 
11.8%
승강기수익 1046
 
10.5%
잡수익 974
 
9.7%
주차장수익 872
 
8.7%
기타운영수익 771
 
7.7%
검침수익 279
 
2.8%
알뜰시장수익 257
 
2.6%
임대료수익 225
 
2.2%
부과차익 205
 
2.1%
Other values (5) 501
 
5.0%

Length

2024-05-11T02:37:37.669800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3691
36.9%
광고료수익 1179
 
11.8%
승강기수익 1046
 
10.5%
잡수익 974
 
9.7%
주차장수익 872
 
8.7%
기타운영수익 771
 
7.7%
검침수익 279
 
2.8%
알뜰시장수익 257
 
2.6%
임대료수익 225
 
2.2%
부과차익 205
 
2.1%
Other values (5) 501
 
5.0%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20191117
Minimum20191101
Maximum20191130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:37:38.537135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20191101
5-th percentile20191101
Q120191108
median20191118
Q320191126
95-th percentile20191130
Maximum20191130
Range29
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.452718
Coefficient of variation (CV)4.6816221 × 10-7
Kurtosis-1.3471413
Mean20191117
Median Absolute Deviation (MAD)8
Skewness-0.18930683
Sum2.0191117 × 1011
Variance89.353877
MonotonicityNot monotonic
2024-05-11T02:37:39.208930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20191130 729
 
7.3%
20191129 673
 
6.7%
20191125 592
 
5.9%
20191111 534
 
5.3%
20191101 533
 
5.3%
20191126 476
 
4.8%
20191104 469
 
4.7%
20191105 464
 
4.6%
20191128 448
 
4.5%
20191120 415
 
4.2%
Other values (20) 4667
46.7%
ValueCountFrequency (%)
20191101 533
5.3%
20191102 120
 
1.2%
20191103 102
 
1.0%
20191104 469
4.7%
20191105 464
4.6%
20191106 351
3.5%
20191107 299
3.0%
20191108 333
3.3%
20191109 59
 
0.6%
20191110 70
 
0.7%
ValueCountFrequency (%)
20191130 729
7.3%
20191129 673
6.7%
20191128 448
4.5%
20191127 412
4.1%
20191126 476
4.8%
20191125 592
5.9%
20191124 125
 
1.2%
20191123 117
 
1.2%
20191122 337
3.4%
20191121 341
3.4%

금액
Real number (ℝ)

SKEWED 

Distinct3134
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317535.26
Minimum-11362000
Maximum5.816 × 108
Zeros9
Zeros (%)0.1%
Negative49
Negative (%)0.5%
Memory size166.0 KiB
2024-05-11T02:37:39.653944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-11362000
5-th percentile160
Q12830
median30000
Q3100000
95-th percentile871412.65
Maximum5.816 × 108
Range5.92962 × 108
Interquartile range (IQR)97170

Descriptive statistics

Standard deviation6717947.7
Coefficient of variation (CV)21.156541
Kurtosis5922.9355
Mean317535.26
Median Absolute Deviation (MAD)28890
Skewness72.915572
Sum3.1753526 × 109
Variance4.5130822 × 1013
MonotonicityNot monotonic
2024-05-11T02:37:40.139687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 675
 
6.8%
50000 645
 
6.5%
100000 521
 
5.2%
70000 181
 
1.8%
40000 178
 
1.8%
60000 170
 
1.7%
150000 160
 
1.6%
80000 123
 
1.2%
20000 120
 
1.2%
200000 111
 
1.1%
Other values (3124) 7116
71.2%
ValueCountFrequency (%)
-11362000 1
< 0.1%
-5511370 1
< 0.1%
-4605000 1
< 0.1%
-4359272 1
< 0.1%
-3090910 1
< 0.1%
-747000 1
< 0.1%
-481980 1
< 0.1%
-395000 1
< 0.1%
-199340 1
< 0.1%
-160000 1
< 0.1%
ValueCountFrequency (%)
581600000 1
< 0.1%
280631230 1
< 0.1%
124705659 1
< 0.1%
68200000 1
< 0.1%
42631800 1
< 0.1%
35896568 1
< 0.1%
35609014 1
< 0.1%
32395680 1
< 0.1%
30000000 1
< 0.1%
29400000 1
< 0.1%

내용
Text

Distinct5704
Distinct (%)57.1%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:37:40.876058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length80
Mean length13.784863
Min length2

Characters and Unicode

Total characters137697
Distinct characters775
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5469 ?
Unique (%)54.8%

Sample

1st row11월분 검침수당
2nd row우편함광고 (애플짐목동, 11-25)
3rd row101-1705 음식물카드 한쌍구입
4th row관리비 연체료 수납
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3828
 
14.9%
수납 3701
 
14.4%
연체료 3700
 
14.4%
11월분 358
 
1.4%
승강기 277
 
1.1%
11월 252
 
1.0%
승강기사용료 230
 
0.9%
222
 
0.9%
10월분 211
 
0.8%
게시판 200
 
0.8%
Other values (7348) 12771
49.6%
2024-05-11T02:37:42.391546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15862
 
11.5%
1 7825
 
5.7%
료 5811
 
4.2%
수 5093
 
3.7%
0 4825
 
3.5%
비 4513
 
3.3%
리 4467
 
3.2%
관 4021
 
2.9%
체 3890
 
2.8%
연 3781
 
2.7%
Other values (765) 77609
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87730
63.7%
Decimal Number 22074
 
16.0%
Space Separator 15862
 
11.5%
Close Punctuation 2921
 
2.1%
Open Punctuation 2915
 
2.1%
Other Punctuation 2503
 
1.8%
Dash Punctuation 2474
 
1.8%
Uppercase Letter 705
 
0.5%
Math Symbol 273
 
0.2%
Lowercase Letter 186
 
0.1%
Other values (2) 54
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5811
 
6.6%
수 5093
 
5.8%
비 4513
 
5.1%
리 4467
 
5.1%
관 4021
 
4.6%
체 3890
 
4.4%
연 3781
 
4.3%
납 3759
 
4.3%
용 1662
 
1.9%
사 1639
 
1.9%
Other values (681) 49094
56.0%
Lowercase Letter
ValueCountFrequency (%)
o 67
36.0%
n 27
14.5%
x 11
 
5.9%
s 9
 
4.8%
k 9
 
4.8%
t 9
 
4.8%
a 6
 
3.2%
b 6
 
3.2%
e 5
 
2.7%
g 5
 
2.7%
Other values (14) 32
17.2%
Uppercase Letter
ValueCountFrequency (%)
N 91
12.9%
A 57
 
8.1%
O 57
 
8.1%
T 49
 
7.0%
S 49
 
7.0%
K 44
 
6.2%
G 43
 
6.1%
B 39
 
5.5%
C 38
 
5.4%
L 36
 
5.1%
Other values (13) 202
28.7%
Other Punctuation
ValueCountFrequency (%)
/ 758
30.3%
. 668
26.7%
, 660
26.4%
: 216
 
8.6%
* 87
 
3.5%
@ 36
 
1.4%
% 24
 
1.0%
? 24
 
1.0%
# 14
 
0.6%
& 8
 
0.3%
Other values (2) 8
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 7825
35.4%
0 4825
21.9%
2 2640
 
12.0%
3 1487
 
6.7%
4 1175
 
5.3%
5 996
 
4.5%
9 963
 
4.4%
6 767
 
3.5%
7 710
 
3.2%
8 686
 
3.1%
Math Symbol
ValueCountFrequency (%)
~ 236
86.4%
> 14
 
5.1%
+ 11
 
4.0%
< 5
 
1.8%
→ 3
 
1.1%
= 2
 
0.7%
× 2
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 2848
97.5%
] 73
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 2837
97.3%
[ 78
 
2.7%
Space Separator
ValueCountFrequency (%)
15862
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2474
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 53
100.0%
Other Number
ValueCountFrequency (%)
② 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87726
63.7%
Common 49076
35.6%
Latin 891
 
0.6%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5811
 
6.6%
수 5093
 
5.8%
비 4513
 
5.1%
리 4467
 
5.1%
관 4021
 
4.6%
체 3890
 
4.4%
연 3781
 
4.3%
납 3759
 
4.3%
용 1662
 
1.9%
사 1639
 
1.9%
Other values (677) 49090
56.0%
Latin
ValueCountFrequency (%)
N 91
 
10.2%
o 67
 
7.5%
A 57
 
6.4%
O 57
 
6.4%
T 49
 
5.5%
S 49
 
5.5%
K 44
 
4.9%
G 43
 
4.8%
B 39
 
4.4%
C 38
 
4.3%
Other values (37) 357
40.1%
Common
ValueCountFrequency (%)
15862
32.3%
1 7825
15.9%
0 4825
 
9.8%
) 2848
 
5.8%
( 2837
 
5.8%
2 2640
 
5.4%
- 2474
 
5.0%
3 1487
 
3.0%
4 1175
 
2.4%
5 996
 
2.0%
Other values (27) 6107
 
12.4%
Han
ValueCountFrequency (%)
外 1
25.0%
入 1
25.0%
分 1
25.0%
不 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87726
63.7%
ASCII 49961
36.3%
Arrows 3
 
< 0.1%
CJK 3
 
< 0.1%
None 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15862
31.7%
1 7825
15.7%
0 4825
 
9.7%
) 2848
 
5.7%
( 2837
 
5.7%
2 2640
 
5.3%
- 2474
 
5.0%
3 1487
 
3.0%
4 1175
 
2.4%
5 996
 
2.0%
Other values (71) 6992
14.0%
Hangul
ValueCountFrequency (%)
료 5811
 
6.6%
수 5093
 
5.8%
비 4513
 
5.1%
리 4467
 
5.1%
관 4021
 
4.6%
체 3890
 
4.4%
연 3781
 
4.3%
납 3759
 
4.3%
용 1662
 
1.9%
사 1639
 
1.9%
Other values (677) 49090
56.0%
Arrows
ValueCountFrequency (%)
→ 3
100.0%
None
ValueCountFrequency (%)
× 2
100.0%
CJK
ValueCountFrequency (%)
外 1
33.3%
入 1
33.3%
分 1
33.3%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
不 1
100.0%

Interactions

2024-05-11T02:37:31.125621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:37:30.491980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:37:31.417518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:37:30.804466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:37:42.767300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3210.207
년월일0.3211.0000.000
금액0.2070.0001.000
2024-05-11T02:37:43.120693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0290.122
금액0.0291.0000.090
비용명0.1220.0901.000

Missing values

2024-05-11T02:37:31.775111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:37:32.208949image/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
43223양평한신A15010502검침수익2019111452245011월분 검침수당
55767목동13단지A15807605알뜰시장수익2019111870000우편함광고 (애플짐목동, 11-25)
9881신수성원A12185504잡수익201911053000101-1705 음식물카드 한쌍구입
32195신천장미1차2차A13824005연체료수익2019111831110관리비 연체료 수납
19867응봉리버그린동아A13385301연체료수익2019111410430관리비 연체료 수납
19672성수우방2차A13383301재활용품수익2019110610045010월 재활용수입 (9.13-10.12)
55216목동5단지A15805504연체료수익20191106190관리비 연체료 수납
4182DMC파크뷰자이아파트A10027817기타운영수익2019110750000011월분 헬스PT10 레슨비 입금 (124-502 강문정)
18149금호벽산(임대,501동)A13309103잡수익20191113124000KT 지하중계기 전기료(19.3.1~20.2.28)
30159잠원훼미리 아파트A13790612연체료수익2019112950관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
27139종암선경아파트A13671203승강기수익20191108100000102동 805호 승강기사용료(공사)
47896구로럭키A15284603광고료수익2019112541000전단지광고(11월)
15265신내10단지A13187306기타운영수익2019111150010월분 고용.산재보험료 납기내 완납에 따른 감액분
53028마곡수명산파크4단지A15728006연체료수익20191101800관리비 연체료 수납
26522길음래미안2차A13611201광고료수익2019112540000게시판광고 (배관청소)
28275방배래미안타워A13706302연체료수익2019112515130관리비 연체료 수납
51652상도동중앙하이츠빌아파트A15683402연체료수익2019112920250관리비 연체료 수납
11842답십리청솔우성A13003202알뜰시장수익2019111836364알뜰장 - 도넛
24489은마A13583507승강기수익2019110550000승강기사용료(10동 1403호)
10463응암금호A12201102광고료수익2019112230000알뜰장(타코야끼)