Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells8
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 = 44.507867)Skewed

Reproduction

Analysis started2024-05-11 02:29:38.963511
Analysis finished2024-05-11 02:29:44.199013
Duration5.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2188
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:29:44.630983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.4338
Min length2

Characters and Unicode

Total characters74338
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

Unique236 ?
Unique (%)2.4%

Sample

1st row마곡푸르지오
2nd row쌍문현대2차
3rd row구의현대프라임
4th row충정리시온
5th row성산시영아파트
ValueCountFrequency (%)
아파트 199
 
1.8%
래미안 65
 
0.6%
e편한세상 39
 
0.4%
아이파크 34
 
0.3%
고덕 25
 
0.2%
sk북한산시티아파트 23
 
0.2%
래미안위브 19
 
0.2%
항동하버라인3단지 18
 
0.2%
sk뷰 18
 
0.2%
올림픽선수기자촌아파트 17
 
0.2%
Other values (2265) 10401
95.8%
2024-05-11T02:29:46.149972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2704
 
3.6%
파 2673
 
3.6%
트 2547
 
3.4%
지 1977
 
2.7%
대 1635
 
2.2%
동 1578
 
2.1%
단 1530
 
2.1%
이 1446
 
1.9%
차 1357
 
1.8%
신 1272
 
1.7%
Other values (423) 55619
74.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67936
91.4%
Decimal Number 3634
 
4.9%
Space Separator 944
 
1.3%
Uppercase Letter 912
 
1.2%
Lowercase Letter 347
 
0.5%
Close Punctuation 155
 
0.2%
Open Punctuation 155
 
0.2%
Dash Punctuation 141
 
0.2%
Other Punctuation 110
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2704
 
4.0%
파 2673
 
3.9%
트 2547
 
3.7%
지 1977
 
2.9%
대 1635
 
2.4%
동 1578
 
2.3%
단 1530
 
2.3%
이 1446
 
2.1%
차 1357
 
2.0%
신 1272
 
1.9%
Other values (378) 49217
72.4%
Uppercase Letter
ValueCountFrequency (%)
S 169
18.5%
C 126
13.8%
K 125
13.7%
D 90
9.9%
M 90
9.9%
H 62
 
6.8%
L 49
 
5.4%
I 35
 
3.8%
E 34
 
3.7%
A 31
 
3.4%
Other values (7) 101
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 222
64.0%
l 32
 
9.2%
s 21
 
6.1%
i 19
 
5.5%
v 16
 
4.6%
k 16
 
4.6%
h 10
 
2.9%
c 6
 
1.7%
w 3
 
0.9%
a 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 1136
31.3%
2 983
27.1%
3 473
13.0%
4 254
 
7.0%
5 218
 
6.0%
6 165
 
4.5%
7 126
 
3.5%
9 118
 
3.2%
8 86
 
2.4%
0 75
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 92
83.6%
. 18
 
16.4%
Space Separator
ValueCountFrequency (%)
944
100.0%
Close Punctuation
ValueCountFrequency (%)
) 155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 141
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67936
91.4%
Common 5139
 
6.9%
Latin 1263
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2704
 
4.0%
파 2673
 
3.9%
트 2547
 
3.7%
지 1977
 
2.9%
대 1635
 
2.4%
동 1578
 
2.3%
단 1530
 
2.3%
이 1446
 
2.1%
차 1357
 
2.0%
신 1272
 
1.9%
Other values (378) 49217
72.4%
Latin
ValueCountFrequency (%)
e 222
17.6%
S 169
13.4%
C 126
10.0%
K 125
9.9%
D 90
 
7.1%
M 90
 
7.1%
H 62
 
4.9%
L 49
 
3.9%
I 35
 
2.8%
E 34
 
2.7%
Other values (19) 261
20.7%
Common
ValueCountFrequency (%)
1 1136
22.1%
2 983
19.1%
944
18.4%
3 473
9.2%
4 254
 
4.9%
5 218
 
4.2%
6 165
 
3.2%
) 155
 
3.0%
( 155
 
3.0%
- 141
 
2.7%
Other values (6) 515
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67936
91.4%
ASCII 6398
 
8.6%
Number Forms 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2704
 
4.0%
파 2673
 
3.9%
트 2547
 
3.7%
지 1977
 
2.9%
대 1635
 
2.4%
동 1578
 
2.3%
단 1530
 
2.3%
이 1446
 
2.1%
차 1357
 
2.0%
신 1272
 
1.9%
Other values (378) 49217
72.4%
ASCII
ValueCountFrequency (%)
1 1136
17.8%
2 983
15.4%
944
14.8%
3 473
 
7.4%
4 254
 
4.0%
e 222
 
3.5%
5 218
 
3.4%
S 169
 
2.6%
6 165
 
2.6%
) 155
 
2.4%
Other values (34) 1679
26.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%

아파트코드
Text

Distinct2194
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:29:47.122159image/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

Unique239 ?
Unique (%)2.4%

Sample

1st rowA15722004
2nd rowA13286002
3rd rowA14320304
4th rowA12070201
5th rowA12185004
ValueCountFrequency (%)
a14272304 23
 
0.2%
a13003007 19
 
0.2%
a10025614 18
 
0.2%
a13805002 17
 
0.2%
a14272309 16
 
0.2%
a15721006 16
 
0.2%
a10026988 16
 
0.2%
a14272305 16
 
0.2%
a12175203 16
 
0.2%
a15101508 16
 
0.2%
Other values (2184) 9827
98.3%
2024-05-11T02:29:48.556141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18812
20.9%
1 17219
19.1%
A 9998
11.1%
3 8670
9.6%
2 8362
9.3%
5 6285
 
7.0%
8 5331
 
5.9%
7 4867
 
5.4%
4 4116
 
4.6%
6 3435
 
3.8%
Other values (2) 2905
 
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 18812
23.5%
1 17219
21.5%
3 8670
10.8%
2 8362
10.5%
5 6285
 
7.9%
8 5331
 
6.7%
7 4867
 
6.1%
4 4116
 
5.1%
6 3435
 
4.3%
9 2903
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9998
> 99.9%
B 2
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18812
23.5%
1 17219
21.5%
3 8670
10.8%
2 8362
10.5%
5 6285
 
7.9%
8 5331
 
6.7%
7 4867
 
6.1%
4 4116
 
5.1%
6 3435
 
4.3%
9 2903
 
3.6%
Latin
ValueCountFrequency (%)
A 9998
> 99.9%
B 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18812
20.9%
1 17219
19.1%
A 9998
11.1%
3 8670
9.6%
2 8362
9.3%
5 6285
 
7.0%
8 5331
 
5.9%
7 4867
 
5.4%
4 4116
 
4.6%
6 3435
 
3.8%
Other values (2) 2905
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3393 
잡수익
967 
승강기수익
955 
주차장수익
925 
광고료수익
917 
Other values (10)
2843 

Length

Max length9
Median length5
Mean length5.0626
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연체료수익
2nd row주차장수익
3rd row이자수익
4th row연체료수익
5th row연체료수익

Common Values

ValueCountFrequency (%)
연체료수익 3393
33.9%
잡수익 967
 
9.7%
승강기수익 955
 
9.6%
주차장수익 925
 
9.2%
광고료수익 917
 
9.2%
기타운영수익 871
 
8.7%
고용안정사업수익 504
 
5.0%
검침수익 317
 
3.2%
알뜰시장수익 262
 
2.6%
재활용품수익 235
 
2.4%
Other values (5) 654
 
6.5%

Length

2024-05-11T02:29:49.012311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3393
33.9%
잡수익 967
 
9.7%
승강기수익 955
 
9.6%
주차장수익 925
 
9.2%
광고료수익 917
 
9.2%
기타운영수익 871
 
8.7%
고용안정사업수익 504
 
5.0%
검침수익 317
 
3.2%
알뜰시장수익 262
 
2.6%
재활용품수익 235
 
2.4%
Other values (5) 654
 
6.5%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220417
Minimum20220401
Maximum20220430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:29:49.394729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220401
5-th percentile20220401
Q120220409
median20220418
Q320220426
95-th percentile20220430
Maximum20220430
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.208858
Coefficient of variation (CV)4.5542374 × 10-7
Kurtosis-1.2451901
Mean20220417
Median Absolute Deviation (MAD)8
Skewness-0.22287933
Sum2.0220417 × 1011
Variance84.803065
MonotonicityNot monotonic
2024-05-11T02:29:49.806057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20220430 694
 
6.9%
20220429 630
 
6.3%
20220425 575
 
5.8%
20220415 554
 
5.5%
20220401 527
 
5.3%
20220411 482
 
4.8%
20220418 455
 
4.5%
20220420 441
 
4.4%
20220426 428
 
4.3%
20220428 422
 
4.2%
Other values (20) 4792
47.9%
ValueCountFrequency (%)
20220401 527
5.3%
20220402 127
 
1.3%
20220403 114
 
1.1%
20220404 381
3.8%
20220405 409
4.1%
20220406 336
3.4%
20220407 300
3.0%
20220408 305
3.0%
20220409 77
 
0.8%
20220410 62
 
0.6%
ValueCountFrequency (%)
20220430 694
6.9%
20220429 630
6.3%
20220428 422
4.2%
20220427 406
4.1%
20220426 428
4.3%
20220425 575
5.8%
20220424 135
 
1.4%
20220423 128
 
1.3%
20220422 349
3.5%
20220421 363
3.6%

금액
Real number (ℝ)

SKEWED 

Distinct3267
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean286017.53
Minimum-5928000
Maximum1.6938054 × 108
Zeros11
Zeros (%)0.1%
Negative26
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T02:29:50.321228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5928000
5-th percentile160
Q12680
median30000
Q3100000
95-th percentile896130
Maximum1.6938054 × 108
Range1.7530854 × 108
Interquartile range (IQR)97320

Descriptive statistics

Standard deviation2705147.1
Coefficient of variation (CV)9.4579766
Kurtosis2456.4576
Mean286017.53
Median Absolute Deviation (MAD)29280
Skewness44.507867
Sum2.8601753 × 109
Variance7.3178207 × 1012
MonotonicityNot monotonic
2024-05-11T02:29:50.770004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 658
 
6.6%
50000 517
 
5.2%
100000 424
 
4.2%
60000 172
 
1.7%
70000 171
 
1.7%
150000 163
 
1.6%
200000 138
 
1.4%
120000 121
 
1.2%
40000 119
 
1.2%
80000 115
 
1.1%
Other values (3257) 7402
74.0%
ValueCountFrequency (%)
-5928000 1
< 0.1%
-5850000 1
< 0.1%
-1800000 1
< 0.1%
-1450000 1
< 0.1%
-360000 1
< 0.1%
-329050 1
< 0.1%
-300000 1
< 0.1%
-200000 1
< 0.1%
-180000 1
< 0.1%
-125000 1
< 0.1%
ValueCountFrequency (%)
169380540 1
< 0.1%
145600000 1
< 0.1%
74360000 1
< 0.1%
63904448 1
< 0.1%
37802040 1
< 0.1%
32073800 1
< 0.1%
29200000 1
< 0.1%
27840000 1
< 0.1%
27500000 1
< 0.1%
24700000 1
< 0.1%

내용
Text

Distinct5864
Distinct (%)58.7%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:29:51.426224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length64
Mean length14.148018
Min length1

Characters and Unicode

Total characters141367
Distinct characters757
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

Unique5576 ?
Unique (%)55.8%

Sample

1st row관리비 연체료 수납
2nd row04월분 주차비 (25대*20,000)
3rd row장충금 예치만기시 이자(2021.4.28~2022.4.28)
4th row관리비 연체료 수납
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3545
 
13.5%
수납 3401
 
13.0%
연체료 3394
 
12.9%
4월분 323
 
1.2%
299
 
1.1%
승강기 287
 
1.1%
3월분 273
 
1.0%
4월 239
 
0.9%
입금 227
 
0.9%
승강기사용료 218
 
0.8%
Other values (7509) 14024
53.5%
2024-05-11T02:29:52.515182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16417
 
11.6%
료 5430
 
3.8%
수 4928
 
3.5%
0 4817
 
3.4%
리 4780
 
3.4%
비 4399
 
3.1%
1 4071
 
2.9%
관 3806
 
2.7%
2 3664
 
2.6%
체 3619
 
2.6%
Other values (747) 85436
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90722
64.2%
Decimal Number 21275
 
15.0%
Space Separator 16417
 
11.6%
Close Punctuation 3220
 
2.3%
Open Punctuation 3209
 
2.3%
Other Punctuation 2922
 
2.1%
Dash Punctuation 2357
 
1.7%
Uppercase Letter 646
 
0.5%
Math Symbol 337
 
0.2%
Lowercase Letter 136
 
0.1%
Other values (2) 126
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5430
 
6.0%
수 4928
 
5.4%
리 4780
 
5.3%
비 4399
 
4.8%
관 3806
 
4.2%
체 3619
 
4.0%
연 3476
 
3.8%
납 3456
 
3.8%
월 1908
 
2.1%
금 1725
 
1.9%
Other values (661) 53195
58.6%
Uppercase Letter
ValueCountFrequency (%)
N 84
13.0%
B 58
 
9.0%
K 55
 
8.5%
L 52
 
8.0%
O 51
 
7.9%
C 48
 
7.4%
G 41
 
6.3%
T 40
 
6.2%
A 35
 
5.4%
D 27
 
4.2%
Other values (14) 155
24.0%
Lowercase Letter
ValueCountFrequency (%)
o 36
26.5%
e 12
 
8.8%
t 11
 
8.1%
x 10
 
7.4%
g 9
 
6.6%
n 9
 
6.6%
k 9
 
6.6%
p 6
 
4.4%
a 5
 
3.7%
c 5
 
3.7%
Other values (12) 24
17.6%
Other Punctuation
ValueCountFrequency (%)
. 845
28.9%
/ 766
26.2%
, 689
23.6%
: 199
 
6.8%
* 167
 
5.7%
? 157
 
5.4%
@ 46
 
1.6%
% 24
 
0.8%
& 14
 
0.5%
' 6
 
0.2%
Other values (4) 9
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 4817
22.6%
1 4071
19.1%
2 3664
17.2%
4 2561
12.0%
3 2318
10.9%
5 1254
 
5.9%
6 800
 
3.8%
7 647
 
3.0%
8 599
 
2.8%
9 544
 
2.6%
Math Symbol
ValueCountFrequency (%)
~ 289
85.8%
+ 14
 
4.2%
> 13
 
3.9%
× 12
 
3.6%
< 4
 
1.2%
= 3
 
0.9%
→ 1
 
0.3%
÷ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3132
97.3%
] 88
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 3124
97.4%
[ 85
 
2.6%
Space Separator
ValueCountFrequency (%)
16417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2357
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 123
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90716
64.2%
Common 49860
35.3%
Latin 782
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5430
 
6.0%
수 4928
 
5.4%
리 4780
 
5.3%
비 4399
 
4.8%
관 3806
 
4.2%
체 3619
 
4.0%
연 3476
 
3.8%
납 3456
 
3.8%
월 1908
 
2.1%
금 1725
 
1.9%
Other values (657) 53189
58.6%
Latin
ValueCountFrequency (%)
N 84
 
10.7%
B 58
 
7.4%
K 55
 
7.0%
L 52
 
6.6%
O 51
 
6.5%
C 48
 
6.1%
G 41
 
5.2%
T 40
 
5.1%
o 36
 
4.6%
A 35
 
4.5%
Other values (36) 282
36.1%
Common
ValueCountFrequency (%)
16417
32.9%
0 4817
 
9.7%
1 4071
 
8.2%
2 3664
 
7.3%
) 3132
 
6.3%
( 3124
 
6.3%
4 2561
 
5.1%
- 2357
 
4.7%
3 2318
 
4.6%
5 1254
 
2.5%
Other values (29) 6145
 
12.3%
Han
ValueCountFrequency (%)
入 4
44.4%
名 2
22.2%
人 1
 
11.1%
不 1
 
11.1%
中 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90713
64.2%
ASCII 50627
35.8%
None 17
 
< 0.1%
CJK 8
 
< 0.1%
Arrows 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16417
32.4%
0 4817
 
9.5%
1 4071
 
8.0%
2 3664
 
7.2%
) 3132
 
6.2%
( 3124
 
6.2%
4 2561
 
5.1%
- 2357
 
4.7%
3 2318
 
4.6%
5 1254
 
2.5%
Other values (71) 6912
13.7%
Hangul
ValueCountFrequency (%)
료 5430
 
6.0%
수 4928
 
5.4%
리 4780
 
5.3%
비 4399
 
4.8%
관 3806
 
4.2%
체 3619
 
4.0%
연 3476
 
3.8%
납 3456
 
3.8%
월 1908
 
2.1%
금 1725
 
1.9%
Other values (656) 53186
58.6%
None
ValueCountFrequency (%)
× 12
70.6%
㈜ 3
 
17.6%
· 1
 
5.9%
÷ 1
 
5.9%
CJK
ValueCountFrequency (%)
入 4
50.0%
名 2
25.0%
人 1
 
12.5%
中 1
 
12.5%
Arrows
ValueCountFrequency (%)
→ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
不 1
100.0%

Interactions

2024-05-11T02:29:42.695421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:42.057276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:43.180623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:42.393121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:29:52.776268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3970.133
년월일0.3971.0000.000
금액0.1330.0001.000
2024-05-11T02:29:53.031264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0560.158
금액0.0561.0000.060
비용명0.1580.0601.000

Missing values

2024-05-11T02:29:43.594512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:29:43.970789image/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
56315마곡푸르지오A15722004연체료수익202204275010관리비 연체료 수납
20692쌍문현대2차A13286002주차장수익2022043050000004월분 주차비 (25대*20,000)
44769구의현대프라임A14320304이자수익202204281395984장충금 예치만기시 이자(2021.4.28~2022.4.28)
10801충정리시온A12070201연체료수익202204126080관리비 연체료 수납
13380성산시영아파트A12185004연체료수익202204218860관리비 연체료 수납
12696신공덕삼성임대A12179002주차장수익2022040170000외부주차료(9-501)
47249영등포아트자이A15076702연체료수익202204287240관리비 연체료 수납
26829수서신동아A13522006승강기수익20220419150000(no-39)703동 1310호 승강기사용료(전입)
20442도봉서울가든A13281201승강기수익20220428200000세대공사 승강기이용료(3-1201)
2072이편한세상서울대입구2차(5단지)A10024894기타운영수익2022040450004월 헬스장(4-1401 강대희)
아파트명아파트코드비용명년월일금액내용
44785광장11현대홈타운A14321001잡수익2022041220지방소득세 환급(광진구청)
26687래미안강남힐즈A13520003연체료수익2022042949530관리비 연체료 수납
46303신길우성5차A15005301기타운영수익202204135000알뜰시장사용시 전기료-엘제라
47007양평동보아파트A15010501잡수익202204054전기료 체크카드 할인(사사오입 부과차)
36405송파삼성래미안A13877501연체료수익202204304850관리비 연체료 수납
41744하계학여울청구A13987305연체료수익202204187800관리비 연체료 수납
50912개봉건영A15275101승강기수익2022042550000102-903 승강기수입
9457현대뜨레비앙A11034001연체료수익202204268360관리비 연체료 수납
49994구로두산A15205405알뜰시장수익2022040130000된장,고추장 알뜰시장(4/1)금요일
1428위례포레샤인18단지A10024577연체료수익202204298690관리비 연체료 수납