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 = 75.86852561)Skewed

Reproduction

Analysis started2024-05-11 02:39:51.425155
Analysis finished2024-05-11 02:39:55.621066
Duration4.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2060
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:39:56.036243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.2049
Min length2

Characters and Unicode

Total characters72049
Distinct characters429
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

Unique177 ?
Unique (%)1.8%

Sample

1st row잠실5단지아파트 입주자대표회의
2nd row목동부영그린타운3차
3rd row신도림동아1차
4th row공릉1단지
5th row마포중동청구
ValueCountFrequency (%)
아파트 134
 
1.3%
래미안 33
 
0.3%
입주자대표회의 27
 
0.3%
창동동아청솔 21
 
0.2%
잠실엘스 19
 
0.2%
전농sk 19
 
0.2%
독립문극동 18
 
0.2%
목동7단지 17
 
0.2%
상계보람 17
 
0.2%
힐스테이트 17
 
0.2%
Other values (2113) 10195
96.9%
2024-05-11T02:39:57.214791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2240
 
3.1%
파 2223
 
3.1%
지 2109
 
2.9%
트 2010
 
2.8%
대 1759
 
2.4%
단 1677
 
2.3%
동 1646
 
2.3%
신 1474
 
2.0%
차 1402
 
1.9%
성 1280
 
1.8%
Other values (419) 54229
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65870
91.4%
Decimal Number 3967
 
5.5%
Uppercase Letter 785
 
1.1%
Space Separator 574
 
0.8%
Lowercase Letter 275
 
0.4%
Close Punctuation 151
 
0.2%
Open Punctuation 151
 
0.2%
Other Punctuation 133
 
0.2%
Dash Punctuation 130
 
0.2%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2240
 
3.4%
파 2223
 
3.4%
지 2109
 
3.2%
트 2010
 
3.1%
대 1759
 
2.7%
단 1677
 
2.5%
동 1646
 
2.5%
신 1474
 
2.2%
차 1402
 
2.1%
성 1280
 
1.9%
Other values (373) 48050
72.9%
Uppercase Letter
ValueCountFrequency (%)
S 148
18.9%
K 115
14.6%
C 77
9.8%
L 66
8.4%
H 53
 
6.8%
D 50
 
6.4%
M 50
 
6.4%
E 43
 
5.5%
I 41
 
5.2%
A 33
 
4.2%
Other values (7) 109
13.9%
Lowercase Letter
ValueCountFrequency (%)
e 181
65.8%
l 24
 
8.7%
i 24
 
8.7%
v 13
 
4.7%
g 7
 
2.5%
a 7
 
2.5%
w 5
 
1.8%
s 4
 
1.5%
c 4
 
1.5%
k 3
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 1181
29.8%
2 1134
28.6%
3 499
12.6%
4 270
 
6.8%
5 235
 
5.9%
6 186
 
4.7%
7 139
 
3.5%
9 137
 
3.5%
8 102
 
2.6%
0 84
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 119
89.5%
. 14
 
10.5%
Space Separator
ValueCountFrequency (%)
574
100.0%
Close Punctuation
ValueCountFrequency (%)
) 151
100.0%
Open Punctuation
ValueCountFrequency (%)
( 151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65870
91.4%
Common 5112
 
7.1%
Latin 1067
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2240
 
3.4%
파 2223
 
3.4%
지 2109
 
3.2%
트 2010
 
3.1%
대 1759
 
2.7%
단 1677
 
2.5%
동 1646
 
2.5%
신 1474
 
2.2%
차 1402
 
2.1%
성 1280
 
1.9%
Other values (373) 48050
72.9%
Latin
ValueCountFrequency (%)
e 181
17.0%
S 148
13.9%
K 115
10.8%
C 77
 
7.2%
L 66
 
6.2%
H 53
 
5.0%
D 50
 
4.7%
M 50
 
4.7%
E 43
 
4.0%
I 41
 
3.8%
Other values (19) 243
22.8%
Common
ValueCountFrequency (%)
1 1181
23.1%
2 1134
22.2%
574
11.2%
3 499
9.8%
4 270
 
5.3%
5 235
 
4.6%
6 186
 
3.6%
) 151
 
3.0%
( 151
 
3.0%
7 139
 
2.7%
Other values (7) 592
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65870
91.4%
ASCII 6172
 
8.6%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2240
 
3.4%
파 2223
 
3.4%
지 2109
 
3.2%
트 2010
 
3.1%
대 1759
 
2.7%
단 1677
 
2.5%
동 1646
 
2.5%
신 1474
 
2.2%
차 1402
 
2.1%
성 1280
 
1.9%
Other values (373) 48050
72.9%
ASCII
ValueCountFrequency (%)
1 1181
19.1%
2 1134
18.4%
574
 
9.3%
3 499
 
8.1%
4 270
 
4.4%
5 235
 
3.8%
6 186
 
3.0%
e 181
 
2.9%
) 151
 
2.4%
( 151
 
2.4%
Other values (35) 1610
26.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2066
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:39:58.193575image/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 rowA13879102
2nd rowA15805301
3rd rowA15288813
4th rowA13980512
5th rowA12187904
ValueCountFrequency (%)
a13204409 21
 
0.2%
a13084804 19
 
0.2%
a13822004 19
 
0.2%
a12008003 18
 
0.2%
a15805115 17
 
0.2%
a13982604 17
 
0.2%
a15780704 16
 
0.2%
a13879102 16
 
0.2%
a10027346 16
 
0.2%
a15721006 16
 
0.2%
Other values (2056) 9825
98.2%
2024-05-11T02:39:59.635193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18416
20.5%
1 17329
19.3%
A 9991
11.1%
3 8897
9.9%
2 7983
8.9%
5 6208
 
6.9%
8 5785
 
6.4%
7 5066
 
5.6%
4 3892
 
4.3%
6 3351
 
3.7%
Other values (2) 3082
 
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 18416
23.0%
1 17329
21.7%
3 8897
11.1%
2 7983
10.0%
5 6208
 
7.8%
8 5785
 
7.2%
7 5066
 
6.3%
4 3892
 
4.9%
6 3351
 
4.2%
9 3073
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9991
99.9%
B 9
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18416
23.0%
1 17329
21.7%
3 8897
11.1%
2 7983
10.0%
5 6208
 
7.8%
8 5785
 
7.2%
7 5066
 
6.3%
4 3892
 
4.9%
6 3351
 
4.2%
9 3073
 
3.8%
Latin
ValueCountFrequency (%)
A 9991
99.9%
B 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18416
20.5%
1 17329
19.3%
A 9991
11.1%
3 8897
9.9%
2 7983
8.9%
5 6208
 
6.9%
8 5785
 
6.4%
7 5066
 
5.6%
4 3892
 
4.3%
6 3351
 
3.7%
Other values (2) 3082
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3665 
광고료수익
981 
잡수익
908 
승강기수익
883 
주차장수익
779 
Other values (10)
2784 

Length

Max length9
Median length5
Mean length4.9351
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3665
36.6%
광고료수익 981
 
9.8%
잡수익 908
 
9.1%
승강기수익 883
 
8.8%
주차장수익 779
 
7.8%
이자수익 680
 
6.8%
기타운영수익 656
 
6.6%
고용안정사업수익 336
 
3.4%
검침수익 246
 
2.5%
임대료수익 224
 
2.2%
Other values (5) 642
 
6.4%

Length

2024-05-11T02:40:00.259444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3665
36.6%
광고료수익 981
 
9.8%
잡수익 908
 
9.1%
승강기수익 883
 
8.8%
주차장수익 779
 
7.8%
이자수익 680
 
6.8%
기타운영수익 656
 
6.6%
고용안정사업수익 336
 
3.4%
검침수익 246
 
2.5%
임대료수익 224
 
2.2%
Other values (5) 642
 
6.4%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190318
Minimum20190301
Maximum20190331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:40:00.867844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190301
5-th percentile20190304
Q120190309
median20190318
Q320190326
95-th percentile20190331
Maximum20190331
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.1319507
Coefficient of variation (CV)4.5229356 × 10-7
Kurtosis-1.2727454
Mean20190318
Median Absolute Deviation (MAD)8
Skewness-0.14265359
Sum2.0190318 × 1011
Variance83.392523
MonotonicityNot monotonic
2024-05-11T02:40:01.507770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20190331 650
 
6.5%
20190329 594
 
5.9%
20190304 547
 
5.5%
20190325 544
 
5.4%
20190315 535
 
5.3%
20190311 474
 
4.7%
20190305 436
 
4.4%
20190328 420
 
4.2%
20190326 415
 
4.2%
20190327 405
 
4.0%
Other values (21) 4980
49.8%
ValueCountFrequency (%)
20190301 201
 
2.0%
20190302 129
 
1.3%
20190303 125
 
1.2%
20190304 547
5.5%
20190305 436
4.4%
20190306 311
3.1%
20190307 286
2.9%
20190308 323
3.2%
20190309 150
 
1.5%
20190310 81
 
0.8%
ValueCountFrequency (%)
20190331 650
6.5%
20190330 189
 
1.9%
20190329 594
5.9%
20190328 420
4.2%
20190327 405
4.0%
20190326 415
4.2%
20190325 544
5.4%
20190324 152
 
1.5%
20190323 200
 
2.0%
20190322 325
3.2%

금액
Real number (ℝ)

SKEWED 

Distinct3686
Distinct (%)36.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean293037.82
Minimum-10160545
Maximum3.30853 × 108
Zeros13
Zeros (%)0.1%
Negative51
Negative (%)0.5%
Memory size166.0 KiB
2024-05-11T02:40:02.166545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10160545
5-th percentile170
Q12710
median28325
Q3100000
95-th percentile1120822
Maximum3.30853 × 108
Range3.4101354 × 108
Interquartile range (IQR)97290

Descriptive statistics

Standard deviation3670172.7
Coefficient of variation (CV)12.52457
Kurtosis6650.0944
Mean293037.82
Median Absolute Deviation (MAD)27195
Skewness75.868526
Sum2.9303782 × 109
Variance1.3470168 × 1013
MonotonicityNot monotonic
2024-05-11T02:40:02.755564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 578
 
5.8%
50000 553
 
5.5%
100000 430
 
4.3%
60000 159
 
1.6%
40000 134
 
1.3%
70000 127
 
1.3%
200000 118
 
1.2%
20000 108
 
1.1%
150000 103
 
1.0%
80000 100
 
1.0%
Other values (3676) 7590
75.9%
ValueCountFrequency (%)
-10160545 1
< 0.1%
-6600000 1
< 0.1%
-3395010 1
< 0.1%
-2600000 1
< 0.1%
-2174860 1
< 0.1%
-1890000 1
< 0.1%
-1864640 1
< 0.1%
-1734830 1
< 0.1%
-1640000 1
< 0.1%
-1443600 1
< 0.1%
ValueCountFrequency (%)
330853000 1
< 0.1%
104263356 1
< 0.1%
32523660 1
< 0.1%
32212965 1
< 0.1%
32000000 1
< 0.1%
31445966 1
< 0.1%
31198470 1
< 0.1%
25320000 1
< 0.1%
25000000 1
< 0.1%
20100000 1
< 0.1%

내용
Text

Distinct5716
Distinct (%)57.2%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:40:03.694506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length75
Mean length13.597557
Min length2

Characters and Unicode

Total characters135826
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

Unique5481 ?
Unique (%)54.9%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row우편함광고-세계로 식자재마트(세계로마트)
4th row관리비 연체료 수납
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3803
 
14.9%
수납 3677
 
14.4%
연체료 3675
 
14.4%
3월분 312
 
1.2%
235
 
0.9%
승강기 217
 
0.9%
3월 211
 
0.8%
2월분 181
 
0.7%
게시판 171
 
0.7%
입금 165
 
0.6%
Other values (7144) 12845
50.4%
2024-05-11T02:40:05.181917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15615
 
11.5%
료 5477
 
4.0%
수 5207
 
3.8%
리 4926
 
3.6%
비 4672
 
3.4%
1 4451
 
3.3%
0 4284
 
3.2%
관 4093
 
3.0%
체 3871
 
2.8%
연 3752
 
2.8%
Other values (715) 79478
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88484
65.1%
Decimal Number 19524
 
14.4%
Space Separator 15615
 
11.5%
Close Punctuation 3039
 
2.2%
Open Punctuation 3038
 
2.2%
Other Punctuation 2598
 
1.9%
Dash Punctuation 2294
 
1.7%
Uppercase Letter 702
 
0.5%
Math Symbol 308
 
0.2%
Lowercase Letter 154
 
0.1%
Other values (2) 70
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5477
 
6.2%
수 5207
 
5.9%
리 4926
 
5.6%
비 4672
 
5.3%
관 4093
 
4.6%
체 3871
 
4.4%
연 3752
 
4.2%
납 3746
 
4.2%
자 1762
 
2.0%
월 1720
 
1.9%
Other values (628) 49258
55.7%
Uppercase Letter
ValueCountFrequency (%)
N 78
 
11.1%
K 57
 
8.1%
G 51
 
7.3%
L 50
 
7.1%
T 46
 
6.6%
C 41
 
5.8%
O 40
 
5.7%
D 40
 
5.7%
B 40
 
5.7%
S 37
 
5.3%
Other values (15) 222
31.6%
Lowercase Letter
ValueCountFrequency (%)
o 59
38.3%
n 21
 
13.6%
x 15
 
9.7%
e 11
 
7.1%
k 9
 
5.8%
s 7
 
4.5%
b 5
 
3.2%
c 4
 
2.6%
a 4
 
2.6%
t 3
 
1.9%
Other values (13) 16
 
10.4%
Other Punctuation
ValueCountFrequency (%)
/ 748
28.8%
. 727
28.0%
, 710
27.3%
: 209
 
8.0%
* 106
 
4.1%
@ 34
 
1.3%
? 20
 
0.8%
# 10
 
0.4%
% 10
 
0.4%
' 9
 
0.3%
Other values (4) 15
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 4451
22.8%
0 4284
21.9%
2 3029
15.5%
3 2657
13.6%
4 1193
 
6.1%
5 944
 
4.8%
9 901
 
4.6%
6 741
 
3.8%
8 687
 
3.5%
7 637
 
3.3%
Math Symbol
ValueCountFrequency (%)
~ 256
83.1%
+ 15
 
4.9%
= 14
 
4.5%
× 9
 
2.9%
> 9
 
2.9%
< 5
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 2956
97.3%
] 83
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 2954
97.2%
[ 84
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 2293
> 99.9%
－ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15615
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 69
100.0%
Other Number
ValueCountFrequency (%)
⑭ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88481
65.1%
Common 46486
34.2%
Latin 856
 
0.6%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5477
 
6.2%
수 5207
 
5.9%
리 4926
 
5.6%
비 4672
 
5.3%
관 4093
 
4.6%
체 3871
 
4.4%
연 3752
 
4.2%
납 3746
 
4.2%
자 1762
 
2.0%
월 1720
 
1.9%
Other values (626) 49255
55.7%
Latin
ValueCountFrequency (%)
N 78
 
9.1%
o 59
 
6.9%
K 57
 
6.7%
G 51
 
6.0%
L 50
 
5.8%
T 46
 
5.4%
C 41
 
4.8%
O 40
 
4.7%
D 40
 
4.7%
B 40
 
4.7%
Other values (38) 354
41.4%
Common
ValueCountFrequency (%)
15615
33.6%
1 4451
 
9.6%
0 4284
 
9.2%
2 3029
 
6.5%
) 2956
 
6.4%
( 2954
 
6.4%
3 2657
 
5.7%
- 2293
 
4.9%
4 1193
 
2.6%
5 944
 
2.0%
Other values (29) 6110
 
13.1%
Han
ValueCountFrequency (%)
人 2
66.7%
內 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88477
65.1%
ASCII 47330
34.8%
None 11
 
< 0.1%
Compat Jamo 4
 
< 0.1%
CJK 3
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15615
33.0%
1 4451
 
9.4%
0 4284
 
9.1%
2 3029
 
6.4%
) 2956
 
6.2%
( 2954
 
6.2%
3 2657
 
5.6%
- 2293
 
4.8%
4 1193
 
2.5%
5 944
 
2.0%
Other values (73) 6954
14.7%
Hangul
ValueCountFrequency (%)
료 5477
 
6.2%
수 5207
 
5.9%
리 4926
 
5.6%
비 4672
 
5.3%
관 4093
 
4.6%
체 3871
 
4.4%
연 3752
 
4.2%
납 3746
 
4.2%
자 1762
 
2.0%
월 1720
 
1.9%
Other values (622) 49251
55.7%
None
ValueCountFrequency (%)
× 9
81.8%
－ 1
 
9.1%
· 1
 
9.1%
CJK
ValueCountFrequency (%)
人 2
66.7%
內 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅍ 1
25.0%
ㄴ 1
25.0%
ㆍ 1
25.0%
ㅐ 1
25.0%
Enclosed Alphanum
ValueCountFrequency (%)
⑭ 1
100.0%

Interactions

2024-05-11T02:39:54.320254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:39:53.462308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:39:54.721130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:39:53.866140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:40:05.495015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4530.142
년월일0.4531.0000.015
금액0.1420.0151.000
2024-05-11T02:40:05.818916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0160.187
금액0.0161.0000.081
비용명0.1870.0811.000

Missing values

2024-05-11T02:39:55.133795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:39:55.463843image/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
37237잠실5단지아파트 입주자대표회의A13879102연체료수익2019032817040관리비 연체료 수납
63045목동부영그린타운3차A15805301연체료수익201903121260관리비 연체료 수납
55633신도림동아1차A15288813광고료수익20190321110000우편함광고-세계로 식자재마트(세계로마트)
40759공릉1단지A13980512연체료수익201903072310관리비 연체료 수납
10752마포중동청구A12187904연체료수익20190322120관리비 연체료 수납
21282금호자이1차A13380301연체료수익20190327100관리비 연체료 수납
55713신도림대림1,2차A15288814기타운영수익20190324600002/4분기 요가 1명
34992거여6단지A13811001연체료수익2019032620370관리비 연체료 수납
41762상계주공1단지A13983105검침수익20190331858240한전검침수당 입금 - 3/21농협
45322시티파크2단지A14088201연체료수익201903311860관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
61988방화11단지A15785005연체료수익201903318330관리비 연체료 수납
60738마곡수명산파크7단지A15728005연체료수익201903041620관리비 연체료 수납
23778길동우성2차A13481305이자수익20190324100272이자수입 3월
54452고척경남2차A15283603잡수익201903311415전산차익
24519역삼경남A13508002주차장수익20190306400000홈넘버주식회사 주차장 2면 임대료 입금
48786신길삼성A15005603광고료수익2019030730000대림할인마트(우편함광고)
63955목동우성2차A15807703연체료수익2019030411070관리비 연체료 수납
40252공릉우방4단지A13980012연체료수익201903251700관리비 연체료 수납
35458송파동부센트레빌A13816101연체료수익2019032910740관리비 연체료 수납
16293신내동성1차2차A13186708알뜰시장수익2019032850000제주은갈치 일일장