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 = 77.19367971)Skewed

Reproduction

Analysis started2024-05-11 02:31:02.092562
Analysis finished2024-05-11 02:31:05.358395
Duration3.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2178
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:31:05.560375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.3671
Min length2

Characters and Unicode

Total characters73671
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

Unique220 ?
Unique (%)2.2%

Sample

1st row남가좌현대제2
2nd row상계주공7단지
3rd row길동삼익파크
4th row송파꿈에그린아파트
5th row불광미성
ValueCountFrequency (%)
아파트 182
 
1.7%
래미안 54
 
0.5%
아이파크 32
 
0.3%
e편한세상 28
 
0.3%
힐스테이트 26
 
0.2%
북한산 26
 
0.2%
잠실엘스아파트 24
 
0.2%
sk뷰 23
 
0.2%
고덕 22
 
0.2%
마포래미안푸르지오 20
 
0.2%
Other values (2247) 10366
96.0%
2024-05-11T02:31:06.444535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2636
 
3.6%
파 2570
 
3.5%
트 2436
 
3.3%
지 1944
 
2.6%
대 1620
 
2.2%
단 1562
 
2.1%
동 1546
 
2.1%
이 1419
 
1.9%
신 1413
 
1.9%
차 1332
 
1.8%
Other values (419) 55193
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67287
91.3%
Decimal Number 3656
 
5.0%
Space Separator 918
 
1.2%
Uppercase Letter 898
 
1.2%
Lowercase Letter 308
 
0.4%
Open Punctuation 164
 
0.2%
Close Punctuation 164
 
0.2%
Other Punctuation 140
 
0.2%
Dash Punctuation 125
 
0.2%
Letter Number 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2636
 
3.9%
파 2570
 
3.8%
트 2436
 
3.6%
지 1944
 
2.9%
대 1620
 
2.4%
단 1562
 
2.3%
동 1546
 
2.3%
이 1419
 
2.1%
신 1413
 
2.1%
차 1332
 
2.0%
Other values (374) 48809
72.5%
Uppercase Letter
ValueCountFrequency (%)
S 175
19.5%
K 121
13.5%
C 94
10.5%
D 77
8.6%
M 77
8.6%
H 67
 
7.5%
L 58
 
6.5%
E 45
 
5.0%
I 44
 
4.9%
A 30
 
3.3%
Other values (7) 110
12.2%
Lowercase Letter
ValueCountFrequency (%)
e 189
61.4%
k 24
 
7.8%
s 23
 
7.5%
l 20
 
6.5%
i 19
 
6.2%
v 13
 
4.2%
w 6
 
1.9%
c 6
 
1.9%
g 3
 
1.0%
a 3
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 1058
28.9%
2 1026
28.1%
3 475
13.0%
4 276
 
7.5%
5 252
 
6.9%
6 181
 
5.0%
7 132
 
3.6%
9 114
 
3.1%
8 74
 
2.0%
0 68
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 115
82.1%
. 25
 
17.9%
Space Separator
ValueCountFrequency (%)
918
100.0%
Open Punctuation
ValueCountFrequency (%)
( 164
100.0%
Close Punctuation
ValueCountFrequency (%)
) 164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 125
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67287
91.3%
Common 5167
 
7.0%
Latin 1217
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2636
 
3.9%
파 2570
 
3.8%
트 2436
 
3.6%
지 1944
 
2.9%
대 1620
 
2.4%
단 1562
 
2.3%
동 1546
 
2.3%
이 1419
 
2.1%
신 1413
 
2.1%
차 1332
 
2.0%
Other values (374) 48809
72.5%
Latin
ValueCountFrequency (%)
e 189
15.5%
S 175
14.4%
K 121
9.9%
C 94
 
7.7%
D 77
 
6.3%
M 77
 
6.3%
H 67
 
5.5%
L 58
 
4.8%
E 45
 
3.7%
I 44
 
3.6%
Other values (19) 270
22.2%
Common
ValueCountFrequency (%)
1 1058
20.5%
2 1026
19.9%
918
17.8%
3 475
9.2%
4 276
 
5.3%
5 252
 
4.9%
6 181
 
3.5%
( 164
 
3.2%
) 164
 
3.2%
7 132
 
2.6%
Other values (6) 521
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67287
91.3%
ASCII 6373
 
8.7%
Number Forms 11
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2636
 
3.9%
파 2570
 
3.8%
트 2436
 
3.6%
지 1944
 
2.9%
대 1620
 
2.4%
단 1562
 
2.3%
동 1546
 
2.3%
이 1419
 
2.1%
신 1413
 
2.1%
차 1332
 
2.0%
Other values (374) 48809
72.5%
ASCII
ValueCountFrequency (%)
1 1058
16.6%
2 1026
16.1%
918
14.4%
3 475
 
7.5%
4 276
 
4.3%
5 252
 
4.0%
e 189
 
3.0%
6 181
 
2.8%
S 175
 
2.7%
( 164
 
2.6%
Other values (34) 1659
26.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 11
100.0%

아파트코드
Text

Distinct2183
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:31:07.073291image/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

Unique220 ?
Unique (%)2.2%

Sample

1st rowA12072802
2nd rowA13982704
3rd rowA13470101
4th rowA13876114
5th rowA12285703
ValueCountFrequency (%)
a13822004 24
 
0.2%
a12175203 20
 
0.2%
a10026180 18
 
0.2%
a13003007 17
 
0.2%
a13920707 17
 
0.2%
a13879102 17
 
0.2%
a13824006 17
 
0.2%
a10078901 16
 
0.2%
a13987304 16
 
0.2%
a13982704 16
 
0.2%
Other values (2173) 9822
98.2%
2024-05-11T02:31:08.084718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18564
20.6%
1 17307
19.2%
A 9992
11.1%
3 8701
9.7%
2 8232
9.1%
5 6258
 
7.0%
8 5611
 
6.2%
7 4870
 
5.4%
4 4142
 
4.6%
6 3387
 
3.8%
Other values (2) 2936
 
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 18564
23.2%
1 17307
21.6%
3 8701
10.9%
2 8232
10.3%
5 6258
 
7.8%
8 5611
 
7.0%
7 4870
 
6.1%
4 4142
 
5.2%
6 3387
 
4.2%
9 2928
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9992
99.9%
B 8
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18564
23.2%
1 17307
21.6%
3 8701
10.9%
2 8232
10.3%
5 6258
 
7.8%
8 5611
 
7.0%
7 4870
 
6.1%
4 4142
 
5.2%
6 3387
 
4.2%
9 2928
 
3.7%
Latin
ValueCountFrequency (%)
A 9992
99.9%
B 8
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18564
20.6%
1 17307
19.2%
A 9992
11.1%
3 8701
9.7%
2 8232
9.1%
5 6258
 
7.0%
8 5611
 
6.2%
7 4870
 
5.4%
4 4142
 
4.6%
6 3387
 
3.8%
Other values (2) 2936
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3276 
승강기수익
1175 
잡수익
896 
주차장수익
848 
광고료수익
769 
Other values (10)
3036 

Length

Max length9
Median length5
Mean length5.0133
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고용안정사업수익
2nd row기타운영수익
3rd row연체료수익
4th row주차장수익
5th row연체료수익

Common Values

ValueCountFrequency (%)
연체료수익 3276
32.8%
승강기수익 1175
 
11.8%
잡수익 896
 
9.0%
주차장수익 848
 
8.5%
광고료수익 769
 
7.7%
이자수익 649
 
6.5%
기타운영수익 613
 
6.1%
고용안정사업수익 545
 
5.5%
검침수익 302
 
3.0%
임대료수익 230
 
2.3%
Other values (5) 697
 
7.0%

Length

2024-05-11T02:31:08.525236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3276
32.8%
승강기수익 1175
 
11.8%
잡수익 896
 
9.0%
주차장수익 848
 
8.5%
광고료수익 769
 
7.7%
이자수익 649
 
6.5%
기타운영수익 613
 
6.1%
고용안정사업수익 545
 
5.5%
검침수익 302
 
3.0%
임대료수익 230
 
2.3%
Other values (5) 697
 
7.0%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210917
Minimum20210901
Maximum20210930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:31:08.877907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210901
5-th percentile20210901
Q120210909
median20210917
Q320210927
95-th percentile20210930
Maximum20210930
Range29
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.5818357
Coefficient of variation (CV)4.7409208 × 10-7
Kurtosis-1.3144331
Mean20210917
Median Absolute Deviation (MAD)9
Skewness-0.1498402
Sum2.0210917 × 1011
Variance91.811575
MonotonicityNot monotonic
2024-05-11T02:31:09.116293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20210930 1065
 
10.7%
20210923 541
 
5.4%
20210924 521
 
5.2%
20210915 521
 
5.2%
20210927 519
 
5.2%
20210901 517
 
5.2%
20210929 499
 
5.0%
20210928 473
 
4.7%
20210910 436
 
4.4%
20210906 412
 
4.1%
Other values (20) 4496
45.0%
ValueCountFrequency (%)
20210901 517
5.2%
20210902 376
3.8%
20210903 373
3.7%
20210904 82
 
0.8%
20210905 62
 
0.6%
20210906 412
4.1%
20210907 306
3.1%
20210908 322
3.2%
20210909 305
3.0%
20210910 436
4.4%
ValueCountFrequency (%)
20210930 1065
10.7%
20210929 499
5.0%
20210928 473
4.7%
20210927 519
5.2%
20210926 244
 
2.4%
20210925 171
 
1.7%
20210924 521
5.2%
20210923 541
5.4%
20210922 66
 
0.7%
20210921 38
 
0.4%

금액
Real number (ℝ)

SKEWED 

Distinct3485
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean234086.31
Minimum-3062040
Maximum2.2580645 × 108
Zeros11
Zeros (%)0.1%
Negative31
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T02:31:09.391079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3062040
5-th percentile150
Q12500
median30000
Q3100000
95-th percentile800000
Maximum2.2580645 × 108
Range2.2886849 × 108
Interquartile range (IQR)97500

Descriptive statistics

Standard deviation2468959.7
Coefficient of variation (CV)10.547219
Kurtosis6977.0336
Mean234086.31
Median Absolute Deviation (MAD)29100
Skewness77.19368
Sum2.3408631 × 109
Variance6.095762 × 1012
MonotonicityNot monotonic
2024-05-11T02:31:09.802068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 640
 
6.4%
100000 542
 
5.4%
30000 486
 
4.9%
150000 184
 
1.8%
200000 165
 
1.7%
60000 159
 
1.6%
70000 144
 
1.4%
40000 118
 
1.2%
80000 102
 
1.0%
20000 86
 
0.9%
Other values (3475) 7374
73.7%
ValueCountFrequency (%)
-3062040 1
< 0.1%
-2885300 1
< 0.1%
-2400000 1
< 0.1%
-2000000 1
< 0.1%
-1983000 1
< 0.1%
-1148727 1
< 0.1%
-532400 1
< 0.1%
-505000 1
< 0.1%
-332080 1
< 0.1%
-150000 1
< 0.1%
ValueCountFrequency (%)
225806450 1
< 0.1%
33563809 1
< 0.1%
24358223 1
< 0.1%
21760670 1
< 0.1%
19942738 1
< 0.1%
18700000 1
< 0.1%
17936364 1
< 0.1%
17000000 1
< 0.1%
16000000 1
< 0.1%
15295000 1
< 0.1%

내용
Text

Distinct6004
Distinct (%)60.1%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:31:10.506275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length67
Mean length14.187269
Min length1

Characters and Unicode

Total characters141745
Distinct characters726
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5775 ?
Unique (%)57.8%

Sample

1st row일자리 지원금(경리)
2nd row체력단련실 수입(외부회원)
3rd row관리비 연체료 수납
4th row08월분주차료(우리부동산)
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3427
 
13.1%
연체료 3285
 
12.5%
수납 3284
 
12.5%
승강기 325
 
1.2%
9월분 308
 
1.2%
승강기사용료 302
 
1.2%
298
 
1.1%
8월분 291
 
1.1%
입금 256
 
1.0%
사용료 254
 
1.0%
Other values (7422) 14183
54.1%
2024-05-11T02:31:11.670702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16347
 
11.5%
료 5387
 
3.8%
0 5099
 
3.6%
리 4965
 
3.5%
수 4879
 
3.4%
1 4770
 
3.4%
비 4297
 
3.0%
관 3772
 
2.7%
체 3482
 
2.5%
연 3352
 
2.4%
Other values (716) 85395
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91070
64.2%
Decimal Number 21599
 
15.2%
Space Separator 16347
 
11.5%
Close Punctuation 3155
 
2.2%
Open Punctuation 3149
 
2.2%
Other Punctuation 2808
 
2.0%
Dash Punctuation 2410
 
1.7%
Uppercase Letter 678
 
0.5%
Math Symbol 306
 
0.2%
Lowercase Letter 143
 
0.1%
Other values (4) 80
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5387
 
5.9%
리 4965
 
5.5%
수 4879
 
5.4%
비 4297
 
4.7%
관 3772
 
4.1%
체 3482
 
3.8%
연 3352
 
3.7%
납 3337
 
3.7%
금 2128
 
2.3%
자 2109
 
2.3%
Other values (629) 53362
58.6%
Uppercase Letter
ValueCountFrequency (%)
N 93
13.7%
C 52
 
7.7%
O 45
 
6.6%
A 41
 
6.0%
S 41
 
6.0%
L 38
 
5.6%
B 36
 
5.3%
K 36
 
5.3%
E 36
 
5.3%
T 36
 
5.3%
Other values (15) 224
33.0%
Lowercase Letter
ValueCountFrequency (%)
o 39
27.3%
s 16
11.2%
t 13
 
9.1%
k 12
 
8.4%
n 9
 
6.3%
x 9
 
6.3%
e 8
 
5.6%
c 7
 
4.9%
l 6
 
4.2%
p 4
 
2.8%
Other values (11) 20
14.0%
Other Punctuation
ValueCountFrequency (%)
/ 786
28.0%
. 700
24.9%
, 666
23.7%
? 261
 
9.3%
: 163
 
5.8%
* 156
 
5.6%
@ 31
 
1.1%
% 20
 
0.7%
# 11
 
0.4%
& 6
 
0.2%
Other values (4) 8
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 5099
23.6%
1 4770
22.1%
2 2949
13.7%
9 1973
 
9.1%
3 1522
 
7.0%
8 1447
 
6.7%
4 1177
 
5.4%
5 1051
 
4.9%
6 819
 
3.8%
7 792
 
3.7%
Math Symbol
ValueCountFrequency (%)
~ 259
84.6%
+ 13
 
4.2%
> 13
 
4.2%
< 10
 
3.3%
= 5
 
1.6%
× 4
 
1.3%
→ 2
 
0.7%
Open Punctuation
ValueCountFrequency (%)
( 3078
97.7%
[ 71
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 3078
97.6%
] 77
 
2.4%
Space Separator
ValueCountFrequency (%)
16347
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2410
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 72
100.0%
Other Symbol
ValueCountFrequency (%)
☞ 5
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Letter Number
ValueCountFrequency (%)
ⅹ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91068
64.2%
Common 49853
35.2%
Latin 822
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5387
 
5.9%
리 4965
 
5.5%
수 4879
 
5.4%
비 4297
 
4.7%
관 3772
 
4.1%
체 3482
 
3.8%
연 3352
 
3.7%
납 3337
 
3.7%
금 2128
 
2.3%
자 2109
 
2.3%
Other values (627) 53360
58.6%
Latin
ValueCountFrequency (%)
N 93
 
11.3%
C 52
 
6.3%
O 45
 
5.5%
A 41
 
5.0%
S 41
 
5.0%
o 39
 
4.7%
L 38
 
4.6%
B 36
 
4.4%
K 36
 
4.4%
E 36
 
4.4%
Other values (37) 365
44.4%
Common
ValueCountFrequency (%)
16347
32.8%
0 5099
 
10.2%
1 4770
 
9.6%
( 3078
 
6.2%
) 3078
 
6.2%
2 2949
 
5.9%
- 2410
 
4.8%
9 1973
 
4.0%
3 1522
 
3.1%
8 1447
 
2.9%
Other values (30) 7180
14.4%
Han
ValueCountFrequency (%)
分 1
50.0%
入 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91068
64.2%
ASCII 50662
35.7%
Misc Symbols 5
 
< 0.1%
None 5
 
< 0.1%
Arrows 2
 
< 0.1%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16347
32.3%
0 5099
 
10.1%
1 4770
 
9.4%
( 3078
 
6.1%
) 3078
 
6.1%
2 2949
 
5.8%
- 2410
 
4.8%
9 1973
 
3.9%
3 1522
 
3.0%
8 1447
 
2.9%
Other values (72) 7989
15.8%
Hangul
ValueCountFrequency (%)
료 5387
 
5.9%
리 4965
 
5.5%
수 4879
 
5.4%
비 4297
 
4.7%
관 3772
 
4.1%
체 3482
 
3.8%
연 3352
 
3.7%
납 3337
 
3.7%
금 2128
 
2.3%
자 2109
 
2.3%
Other values (627) 53360
58.6%
Misc Symbols
ValueCountFrequency (%)
☞ 5
100.0%
None
ValueCountFrequency (%)
× 4
80.0%
· 1
 
20.0%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Number Forms
ValueCountFrequency (%)
ⅹ 1
100.0%
CJK
ValueCountFrequency (%)
分 1
50.0%
入 1
50.0%

Interactions

2024-05-11T02:31:04.227047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:03.682564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:04.501009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:03.961344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:31:11.947301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4610.138
년월일0.4611.0000.007
금액0.1380.0071.000
2024-05-11T02:31:12.107853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0230.189
금액0.0231.0000.062
비용명0.1890.0621.000

Missing values

2024-05-11T02:31:04.840125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:31:05.194593image/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
9938남가좌현대제2A12072802고용안정사업수익2021091550000일자리 지원금(경리)
38999상계주공7단지A13982704기타운영수익2021091781818체력단련실 수입(외부회원)
23505길동삼익파크A13470101연체료수익202109071110관리비 연체료 수납
35060송파꿈에그린아파트A13876114주차장수익202109173000008월분주차료(우리부동산)
13748불광미성A12285703연체료수익202109072310관리비 연체료 수납
9115인왕산벽산아파트A12009302주차장수익2021092570000주차료(2856)
29776삼선힐스테이트A13672102이자수익202109181645우리은행-헬스(1005-802-884523)이자수익
3550헬리오시티아파트A10025850승강기수익20210922100000313-2102호 전입 승강기사용료 입금
41907신동아아파트A14082601연체료수익202109021360관리비 연체료 수납
33564오금삼성A13813003연체료수익2021092410관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
60294은평뉴타운구파발10단지1관리A41279927고용안정사업수익2021092843540일자리지원금수익-고대흥50,000*27일(8월)
35168잠실5단지아파트A13879102기타운영수익2021092160000독서실 사용료 입금(10월,11월 2달 박희진)
42082시티파크2단지A14088201연체료수익2021090618690관리비 연체료 수납
59285목동진도1차A15882104재활용품수익20210927364009월 재활용 수입
17288신내영풍마드레빌A13186504기타운영수익20210908100000104동창고임대료
2130항동 한양수자인 에듀힐즈A10025193이자수익202109184275통장 이자수입 발생
9771충정리시온A12070201연체료수익202109281670관리비 연체료 수납
46867신길우성2차A15086007연체료수익202109273830관리비 연체료 수납
3069마포 보성 아파트A10025672잡수익2021091050008월분 4대보험 자동이체 할인등
52090남서울 무지개A15383905연체료수익20210925410관리비 연체료 수납