Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells1
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 = 52.93191185)Skewed

Reproduction

Analysis started2024-05-11 02:37:11.494798
Analysis finished2024-05-11 02:37:16.162274
Duration4.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2064
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:37:16.415535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.2206
Min length2

Characters and Unicode

Total characters72206
Distinct characters431
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

Unique178 ?
Unique (%)1.8%

Sample

1st row등촌동성
2nd row창동북한산아이파크
3rd row신정대림
4th row정릉우성
5th row휘경주공1단지
ValueCountFrequency (%)
아파트 130
 
1.2%
입주자대표회의 33
 
0.3%
신내 24
 
0.2%
신림현대 22
 
0.2%
잠실리센츠 22
 
0.2%
래미안 20
 
0.2%
힐스테이트 20
 
0.2%
남가좌현대아파트 19
 
0.2%
구의현대2단지 19
 
0.2%
아이파크 18
 
0.2%
Other values (2125) 10245
96.9%
2024-05-11T02:37:17.447812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 2317
 
3.2%
아 2296
 
3.2%
트 2135
 
3.0%
지 2100
 
2.9%
단 1691
 
2.3%
대 1681
 
2.3%
동 1505
 
2.1%
신 1469
 
2.0%
차 1412
 
2.0%
이 1329
 
1.8%
Other values (421) 54271
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66007
91.4%
Decimal Number 3988
 
5.5%
Uppercase Letter 761
 
1.1%
Space Separator 631
 
0.9%
Lowercase Letter 277
 
0.4%
Other Punctuation 139
 
0.2%
Open Punctuation 136
 
0.2%
Close Punctuation 136
 
0.2%
Dash Punctuation 116
 
0.2%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2317
 
3.5%
아 2296
 
3.5%
트 2135
 
3.2%
지 2100
 
3.2%
단 1691
 
2.6%
대 1681
 
2.5%
동 1505
 
2.3%
신 1469
 
2.2%
차 1412
 
2.1%
이 1329
 
2.0%
Other values (375) 48072
72.8%
Uppercase Letter
ValueCountFrequency (%)
S 155
20.4%
K 114
15.0%
C 80
10.5%
H 59
 
7.8%
L 50
 
6.6%
D 50
 
6.6%
M 50
 
6.6%
E 37
 
4.9%
I 37
 
4.9%
A 29
 
3.8%
Other values (7) 100
13.1%
Lowercase Letter
ValueCountFrequency (%)
e 153
55.2%
l 40
 
14.4%
i 25
 
9.0%
v 22
 
7.9%
s 11
 
4.0%
k 8
 
2.9%
c 6
 
2.2%
h 6
 
2.2%
w 4
 
1.4%
g 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 1219
30.6%
2 1053
26.4%
3 514
12.9%
4 304
 
7.6%
5 263
 
6.6%
6 185
 
4.6%
7 150
 
3.8%
9 105
 
2.6%
0 104
 
2.6%
8 91
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 120
86.3%
. 19
 
13.7%
Space Separator
ValueCountFrequency (%)
631
100.0%
Open Punctuation
ValueCountFrequency (%)
( 136
100.0%
Close Punctuation
ValueCountFrequency (%)
) 136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66007
91.4%
Common 5155
 
7.1%
Latin 1044
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2317
 
3.5%
아 2296
 
3.5%
트 2135
 
3.2%
지 2100
 
3.2%
단 1691
 
2.6%
대 1681
 
2.5%
동 1505
 
2.3%
신 1469
 
2.2%
차 1412
 
2.1%
이 1329
 
2.0%
Other values (375) 48072
72.8%
Latin
ValueCountFrequency (%)
S 155
14.8%
e 153
14.7%
K 114
10.9%
C 80
 
7.7%
H 59
 
5.7%
L 50
 
4.8%
D 50
 
4.8%
M 50
 
4.8%
l 40
 
3.8%
E 37
 
3.5%
Other values (19) 256
24.5%
Common
ValueCountFrequency (%)
1 1219
23.6%
2 1053
20.4%
631
12.2%
3 514
10.0%
4 304
 
5.9%
5 263
 
5.1%
6 185
 
3.6%
7 150
 
2.9%
( 136
 
2.6%
) 136
 
2.6%
Other values (7) 564
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66007
91.4%
ASCII 6193
 
8.6%
Number Forms 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 2317
 
3.5%
아 2296
 
3.5%
트 2135
 
3.2%
지 2100
 
3.2%
단 1691
 
2.6%
대 1681
 
2.5%
동 1505
 
2.3%
신 1469
 
2.2%
차 1412
 
2.1%
이 1329
 
2.0%
Other values (375) 48072
72.8%
ASCII
ValueCountFrequency (%)
1 1219
19.7%
2 1053
17.0%
631
10.2%
3 514
 
8.3%
4 304
 
4.9%
5 263
 
4.2%
6 185
 
3.0%
S 155
 
2.5%
e 153
 
2.5%
7 150
 
2.4%
Other values (35) 1566
25.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 6
100.0%

아파트코드
Text

Distinct2070
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:37:18.437968image/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

Unique179 ?
Unique (%)1.8%

Sample

1st rowA15703302
2nd rowA13204510
3rd rowA15885303
4th rowA13677206
5th rowA13009002
ValueCountFrequency (%)
a13822003 22
 
0.2%
a15101508 22
 
0.2%
a12012203 19
 
0.2%
a14383205 19
 
0.2%
a13879102 18
 
0.2%
a12179004 18
 
0.2%
a15805115 17
 
0.2%
a12104005 16
 
0.2%
a14272304 16
 
0.2%
a15728011 16
 
0.2%
Other values (2060) 9817
98.2%
2024-05-11T02:37:20.088420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18350
20.4%
1 17385
19.3%
A 9995
11.1%
3 8908
9.9%
2 8131
9.0%
5 6412
 
7.1%
8 5681
 
6.3%
7 4975
 
5.5%
4 3772
 
4.2%
6 3399
 
3.8%
Other values (2) 2992
 
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 18350
22.9%
1 17385
21.7%
3 8908
11.1%
2 8131
10.2%
5 6412
 
8.0%
8 5681
 
7.1%
7 4975
 
6.2%
4 3772
 
4.7%
6 3399
 
4.2%
9 2987
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9995
> 99.9%
B 5
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18350
22.9%
1 17385
21.7%
3 8908
11.1%
2 8131
10.2%
5 6412
 
8.0%
8 5681
 
7.1%
7 4975
 
6.2%
4 3772
 
4.7%
6 3399
 
4.2%
9 2987
 
3.7%
Latin
ValueCountFrequency (%)
A 9995
> 99.9%
B 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18350
20.4%
1 17385
19.3%
A 9995
11.1%
3 8908
9.9%
2 8131
9.0%
5 6412
 
7.1%
8 5681
 
6.3%
7 4975
 
5.5%
4 3772
 
4.2%
6 3399
 
3.8%
Other values (2) 2992
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3508 
광고료수익
1023 
잡수익
929 
이자수익
889 
승강기수익
886 
Other values (10)
2765 

Length

Max length9
Median length5
Mean length4.8849
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row이자수익
2nd row부과차익
3rd row연체료수익
4th row연체료수익
5th row광고료수익

Common Values

ValueCountFrequency (%)
연체료수익 3508
35.1%
광고료수익 1023
 
10.2%
잡수익 929
 
9.3%
이자수익 889
 
8.9%
승강기수익 886
 
8.9%
주차장수익 726
 
7.3%
기타운영수익 709
 
7.1%
검침수익 281
 
2.8%
고용안정사업수익 237
 
2.4%
임대료수익 224
 
2.2%
Other values (5) 588
 
5.9%

Length

2024-05-11T02:37:20.750347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3508
35.1%
광고료수익 1023
 
10.2%
잡수익 929
 
9.3%
이자수익 889
 
8.9%
승강기수익 886
 
8.9%
주차장수익 726
 
7.3%
기타운영수익 709
 
7.1%
검침수익 281
 
2.8%
고용안정사업수익 237
 
2.4%
임대료수익 224
 
2.2%
Other values (5) 588
 
5.9%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20191217
Minimum20191201
Maximum20191231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:37:21.193449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20191201
5-th percentile20191202
Q120191210
median20191218
Q320191226
95-th percentile20191231
Maximum20191231
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.5945917
Coefficient of variation (CV)4.7518639 × 10-7
Kurtosis-1.2457408
Mean20191217
Median Absolute Deviation (MAD)8
Skewness-0.10627312
Sum2.0191217 × 1011
Variance92.05619
MonotonicityNot monotonic
2024-05-11T02:37:21.632156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20191231 978
 
9.8%
20191202 590
 
5.9%
20191230 553
 
5.5%
20191212 476
 
4.8%
20191210 454
 
4.5%
20191224 424
 
4.2%
20191221 416
 
4.2%
20191216 396
 
4.0%
20191226 383
 
3.8%
20191223 360
 
3.6%
Other values (21) 4970
49.7%
ValueCountFrequency (%)
20191201 204
 
2.0%
20191202 590
5.9%
20191203 337
3.4%
20191204 311
3.1%
20191205 344
3.4%
20191206 230
 
2.3%
20191207 75
 
0.8%
20191208 52
 
0.5%
20191209 288
2.9%
20191210 454
4.5%
ValueCountFrequency (%)
20191231 978
9.8%
20191230 553
5.5%
20191229 239
 
2.4%
20191228 116
 
1.2%
20191227 355
 
3.5%
20191226 383
 
3.8%
20191225 170
 
1.7%
20191224 424
4.2%
20191223 360
 
3.6%
20191222 103
 
1.0%

금액
Real number (ℝ)

SKEWED 

Distinct3836
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean342164.89
Minimum-20578890
Maximum3.644 × 108
Zeros20
Zeros (%)0.2%
Negative57
Negative (%)0.6%
Memory size166.0 KiB
2024-05-11T02:37:22.071219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-20578890
5-th percentile170
Q13190
median28505
Q3100000
95-th percentile1036790.2
Maximum3.644 × 108
Range3.8497889 × 108
Interquartile range (IQR)96810

Descriptive statistics

Standard deviation5253243.5
Coefficient of variation (CV)15.352959
Kurtosis3202.9219
Mean342164.89
Median Absolute Deviation (MAD)26995
Skewness52.931912
Sum3.4216489 × 109
Variance2.7596568 × 1013
MonotonicityNot monotonic
2024-05-11T02:37:22.776203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 576
 
5.8%
50000 526
 
5.3%
100000 437
 
4.4%
40000 149
 
1.5%
70000 147
 
1.5%
60000 144
 
1.4%
150000 134
 
1.3%
200000 105
 
1.1%
20000 101
 
1.0%
80000 98
 
1.0%
Other values (3826) 7583
75.8%
ValueCountFrequency (%)
-20578890 1
< 0.1%
-8119350 1
< 0.1%
-3857600 1
< 0.1%
-3749000 1
< 0.1%
-3384000 1
< 0.1%
-2500000 1
< 0.1%
-1894640 1
< 0.1%
-1660043 1
< 0.1%
-945000 1
< 0.1%
-828680 1
< 0.1%
ValueCountFrequency (%)
364400000 1
< 0.1%
274000000 1
< 0.1%
179096433 1
< 0.1%
111836449 1
< 0.1%
68500000 1
< 0.1%
64316724 1
< 0.1%
45454545 1
< 0.1%
37169400 1
< 0.1%
32459100 1
< 0.1%
31000000 1
< 0.1%

내용
Text

Distinct5831
Distinct (%)58.3%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T02:37:23.712488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length70
Mean length13.849885
Min length2

Characters and Unicode

Total characters138485
Distinct characters725
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5567 ?
Unique (%)55.7%

Sample

1st row새마을금고 하자보수충당금(보통) 예금이자
2nd row19.11월분 부과차익
3rd row관리비 연체료 수납
4th row관리비 연체료 수납
5th row광고(47)게시판-농협대출(제이에스모기지) 김도형
ValueCountFrequency (%)
관리비 3648
 
14.3%
연체료 3516
 
13.8%
수납 3514
 
13.8%
12월분 312
 
1.2%
승강기 257
 
1.0%
209
 
0.8%
12월 203
 
0.8%
11월분 195
 
0.8%
입금 179
 
0.7%
게시판 175
 
0.7%
Other values (7337) 13254
52.1%
2024-05-11T02:37:25.141516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15578
 
11.2%
1 6705
 
4.8%
료 5404
 
3.9%
수 5192
 
3.7%
리 4722
 
3.4%
비 4507
 
3.3%
0 4363
 
3.2%
관 4009
 
2.9%
체 3714
 
2.7%
2 3652
 
2.6%
Other values (715) 80639
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89503
64.6%
Decimal Number 21026
 
15.2%
Space Separator 15578
 
11.2%
Close Punctuation 3140
 
2.3%
Open Punctuation 3126
 
2.3%
Other Punctuation 2572
 
1.9%
Dash Punctuation 2351
 
1.7%
Uppercase Letter 711
 
0.5%
Math Symbol 267
 
0.2%
Lowercase Letter 139
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5404
 
6.0%
수 5192
 
5.8%
리 4722
 
5.3%
비 4507
 
5.0%
관 4009
 
4.5%
체 3714
 
4.1%
연 3588
 
4.0%
납 3575
 
4.0%
자 1751
 
2.0%
금 1641
 
1.8%
Other values (631) 51400
57.4%
Uppercase Letter
ValueCountFrequency (%)
N 88
12.4%
O 68
 
9.6%
T 51
 
7.2%
C 48
 
6.8%
S 46
 
6.5%
G 45
 
6.3%
L 44
 
6.2%
A 40
 
5.6%
K 38
 
5.3%
D 36
 
5.1%
Other values (16) 207
29.1%
Lowercase Letter
ValueCountFrequency (%)
o 43
30.9%
n 17
 
12.2%
x 14
 
10.1%
k 9
 
6.5%
e 9
 
6.5%
s 7
 
5.0%
h 6
 
4.3%
b 6
 
4.3%
t 5
 
3.6%
a 5
 
3.6%
Other values (10) 18
12.9%
Other Punctuation
ValueCountFrequency (%)
/ 769
29.9%
. 740
28.8%
, 682
26.5%
: 211
 
8.2%
* 91
 
3.5%
@ 26
 
1.0%
% 22
 
0.9%
' 11
 
0.4%
# 10
 
0.4%
& 4
 
0.2%
Other values (4) 6
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 6705
31.9%
0 4363
20.8%
2 3652
17.4%
3 1397
 
6.6%
4 1064
 
5.1%
9 911
 
4.3%
5 909
 
4.3%
6 744
 
3.5%
7 646
 
3.1%
8 635
 
3.0%
Math Symbol
ValueCountFrequency (%)
~ 236
88.4%
+ 14
 
5.2%
× 4
 
1.5%
= 4
 
1.5%
> 4
 
1.5%
< 3
 
1.1%
→ 2
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 3060
97.5%
] 80
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 3046
97.4%
[ 80
 
2.6%
Space Separator
ValueCountFrequency (%)
15578
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2351
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89501
64.6%
Common 48132
34.8%
Latin 850
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5404
 
6.0%
수 5192
 
5.8%
리 4722
 
5.3%
비 4507
 
5.0%
관 4009
 
4.5%
체 3714
 
4.1%
연 3588
 
4.0%
납 3575
 
4.0%
자 1751
 
2.0%
금 1641
 
1.8%
Other values (629) 51398
57.4%
Latin
ValueCountFrequency (%)
N 88
 
10.4%
O 68
 
8.0%
T 51
 
6.0%
C 48
 
5.6%
S 46
 
5.4%
G 45
 
5.3%
L 44
 
5.2%
o 43
 
5.1%
A 40
 
4.7%
K 38
 
4.5%
Other values (36) 339
39.9%
Common
ValueCountFrequency (%)
15578
32.4%
1 6705
13.9%
0 4363
 
9.1%
2 3652
 
7.6%
) 3060
 
6.4%
( 3046
 
6.3%
- 2351
 
4.9%
3 1397
 
2.9%
4 1064
 
2.2%
9 911
 
1.9%
Other values (28) 6005
 
12.5%
Han
ValueCountFrequency (%)
入 1
50.0%
用 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89499
64.6%
ASCII 48975
35.4%
None 5
 
< 0.1%
Arrows 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15578
31.8%
1 6705
13.7%
0 4363
 
8.9%
2 3652
 
7.5%
) 3060
 
6.2%
( 3046
 
6.2%
- 2351
 
4.8%
3 1397
 
2.9%
4 1064
 
2.2%
9 911
 
1.9%
Other values (71) 6848
14.0%
Hangul
ValueCountFrequency (%)
료 5404
 
6.0%
수 5192
 
5.8%
리 4722
 
5.3%
비 4507
 
5.0%
관 4009
 
4.5%
체 3714
 
4.1%
연 3588
 
4.0%
납 3575
 
4.0%
자 1751
 
2.0%
금 1641
 
1.8%
Other values (627) 51396
57.4%
None
ValueCountFrequency (%)
× 4
80.0%
· 1
 
20.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1
50.0%
ㅣ 1
50.0%
CJK
ValueCountFrequency (%)
入 1
50.0%
用 1
50.0%

Interactions

2024-05-11T02:37:14.706283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:37:14.117600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:37:15.080513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:37:14.406444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:37:25.504710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.5150.195
년월일0.5151.0000.000
금액0.1950.0001.000
2024-05-11T02:37:25.800738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.000-0.0020.220
금액-0.0021.0000.089
비용명0.2200.0891.000

Missing values

2024-05-11T02:37:15.536250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:37:15.921252image/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
62096등촌동성A15703302이자수익20191221141새마을금고 하자보수충당금(보통) 예금이자
19850창동북한산아이파크A13204510부과차익201912231864419.11월분 부과차익
67970신정대림A15885303연체료수익201912251760관리비 연체료 수납
33174정릉우성A13677206연체료수익2019123011090관리비 연체료 수납
14555휘경주공1단지A13009002광고료수익2019120570000광고(47)게시판-농협대출(제이에스모기지) 김도형
11716성산시영아파트A12185004연체료수익2019122412570관리비 연체료 수납
66412신트리2단지A15807313고용안정사업수익2019121236000010,11월분 청소용역비 일자리안정자금 수입
53497건영3차아파트A15101903연체료수익201912213080관리비 연체료 수납
24454명일삼익그린2차A13407104잡수익201912021347011월 상가오물처리비
44755중계주공2단지A13985909연체료수익20191206130관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
3553포레스트힐시티A10027162주차장수익20191231117420012월 주차비
53791관악드림타운제2A15105503잡수익20191211130000012/2일 주말알뜰시장 입찰보증료 계약금으로 대체 (초록물산)
45586월계역신도브래뉴A13987502광고료수익2019121830000게시판광고수입
23777행당한신아파트A13386702연체료수익201912115150관리비 연체료 수납
31445길음삼부A13611004연체료수익201912166450관리비 연체료 수납
39960잠실현대A13886701광고료수익2019120960000게시판광고(토즈) 2주
47955벽산라이브파크A14272305연체료수익2019122429720관리비 연체료 수납
28024역삼삼익A13527006연체료수익2019122014700관리비 연체료 수납
24591명일신동아A13407204연체료수익201912274050관리비 연체료 수납
28221도곡개포한신아파트A13527016알뜰시장수익2019123150000012월분 알뜰시장수익 - 정주상회