Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells7
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 = 28.28827102)Skewed

Reproduction

Analysis started2024-05-11 02:32:06.711783
Analysis finished2024-05-11 02:32:11.070925
Duration4.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2179
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:32:11.418929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length7.3268
Min length2

Characters and Unicode

Total characters73268
Distinct characters430
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

Unique226 ?
Unique (%)2.3%

Sample

1st row둔촌현대2차
2nd row이편한세상 송파파크센트럴
3rd row아크로리버뷰 신반포
4th row마포자이3차아파트
5th row송파파인타운6단지
ValueCountFrequency (%)
아파트 202
 
1.9%
래미안 35
 
0.3%
아이파크 24
 
0.2%
목동7단지 22
 
0.2%
e편한세상 22
 
0.2%
고덕 20
 
0.2%
북한산 19
 
0.2%
힐스테이트 18
 
0.2%
서초힐스 17
 
0.2%
역삼푸르지오 16
 
0.1%
Other values (2243) 10340
96.3%
2024-05-11T02:32:12.511893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2653
 
3.6%
파 2582
 
3.5%
트 2413
 
3.3%
지 1980
 
2.7%
대 1595
 
2.2%
단 1566
 
2.1%
동 1548
 
2.1%
이 1450
 
2.0%
신 1395
 
1.9%
차 1299
 
1.8%
Other values (420) 54787
74.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67180
91.7%
Decimal Number 3605
 
4.9%
Space Separator 823
 
1.1%
Uppercase Letter 802
 
1.1%
Lowercase Letter 295
 
0.4%
Open Punctuation 156
 
0.2%
Close Punctuation 156
 
0.2%
Other Punctuation 127
 
0.2%
Dash Punctuation 119
 
0.2%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2653
 
3.9%
파 2582
 
3.8%
트 2413
 
3.6%
지 1980
 
2.9%
대 1595
 
2.4%
단 1566
 
2.3%
동 1548
 
2.3%
이 1450
 
2.2%
신 1395
 
2.1%
차 1299
 
1.9%
Other values (375) 48699
72.5%
Uppercase Letter
ValueCountFrequency (%)
S 134
16.7%
K 121
15.1%
C 117
14.6%
D 81
10.1%
M 81
10.1%
H 36
 
4.5%
I 35
 
4.4%
L 34
 
4.2%
E 32
 
4.0%
A 31
 
3.9%
Other values (7) 100
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 182
61.7%
i 21
 
7.1%
l 18
 
6.1%
k 17
 
5.8%
s 15
 
5.1%
v 14
 
4.7%
c 10
 
3.4%
w 9
 
3.1%
a 3
 
1.0%
h 3
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 1129
31.3%
2 1033
28.7%
3 442
 
12.3%
4 259
 
7.2%
5 225
 
6.2%
6 159
 
4.4%
7 117
 
3.2%
9 115
 
3.2%
8 75
 
2.1%
0 51
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 109
85.8%
. 18
 
14.2%
Space Separator
ValueCountFrequency (%)
823
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67180
91.7%
Common 4986
 
6.8%
Latin 1102
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2653
 
3.9%
파 2582
 
3.8%
트 2413
 
3.6%
지 1980
 
2.9%
대 1595
 
2.4%
단 1566
 
2.3%
동 1548
 
2.3%
이 1450
 
2.2%
신 1395
 
2.1%
차 1299
 
1.9%
Other values (375) 48699
72.5%
Latin
ValueCountFrequency (%)
e 182
16.5%
S 134
12.2%
K 121
11.0%
C 117
10.6%
D 81
 
7.4%
M 81
 
7.4%
H 36
 
3.3%
I 35
 
3.2%
L 34
 
3.1%
E 32
 
2.9%
Other values (19) 249
22.6%
Common
ValueCountFrequency (%)
1 1129
22.6%
2 1033
20.7%
823
16.5%
3 442
 
8.9%
4 259
 
5.2%
5 225
 
4.5%
6 159
 
3.2%
( 156
 
3.1%
) 156
 
3.1%
- 119
 
2.4%
Other values (6) 485
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67180
91.7%
ASCII 6083
 
8.3%
Number Forms 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2653
 
3.9%
파 2582
 
3.8%
트 2413
 
3.6%
지 1980
 
2.9%
대 1595
 
2.4%
단 1566
 
2.3%
동 1548
 
2.3%
이 1450
 
2.2%
신 1395
 
2.1%
차 1299
 
1.9%
Other values (375) 48699
72.5%
ASCII
ValueCountFrequency (%)
1 1129
18.6%
2 1033
17.0%
823
13.5%
3 442
 
7.3%
4 259
 
4.3%
5 225
 
3.7%
e 182
 
3.0%
6 159
 
2.6%
( 156
 
2.6%
) 156
 
2.6%
Other values (34) 1519
25.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 5
100.0%

아파트코드
Text

Distinct2184
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:32:13.550635image/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

Unique227 ?
Unique (%)2.3%

Sample

1st rowA13406201
2nd rowA10024787
3rd rowA10026227
4th rowA10026036
5th rowA13876108
ValueCountFrequency (%)
a15805115 22
 
0.2%
a13778204 17
 
0.2%
a13881005 16
 
0.2%
a10026370 16
 
0.2%
a13084804 16
 
0.2%
a13592604 16
 
0.2%
a10025675 16
 
0.2%
a10025850 15
 
0.1%
a15701003 15
 
0.1%
a13010004 15
 
0.1%
Other values (2174) 9836
98.4%
2024-05-11T02:32:15.194146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18675
20.8%
1 17184
19.1%
A 9993
11.1%
3 8651
9.6%
2 8133
9.0%
5 6393
 
7.1%
8 5738
 
6.4%
7 4803
 
5.3%
4 4008
 
4.5%
6 3501
 
3.9%
Other values (2) 2921
 
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 18675
23.3%
1 17184
21.5%
3 8651
10.8%
2 8133
10.2%
5 6393
 
8.0%
8 5738
 
7.2%
7 4803
 
6.0%
4 4008
 
5.0%
6 3501
 
4.4%
9 2914
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9993
99.9%
B 7
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18675
23.3%
1 17184
21.5%
3 8651
10.8%
2 8133
10.2%
5 6393
 
8.0%
8 5738
 
7.2%
7 4803
 
6.0%
4 4008
 
5.0%
6 3501
 
4.4%
9 2914
 
3.6%
Latin
ValueCountFrequency (%)
A 9993
99.9%
B 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18675
20.8%
1 17184
19.1%
A 9993
11.1%
3 8651
9.6%
2 8133
9.0%
5 6393
 
7.1%
8 5738
 
6.4%
7 4803
 
5.3%
4 4008
 
4.5%
6 3501
 
3.9%
Other values (2) 2921
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3636 
승강기수익
1135 
잡수익
946 
광고료수익
905 
주차장수익
887 
Other values (10)
2491 

Length

Max length9
Median length5
Mean length5.042
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3636
36.4%
승강기수익 1135
 
11.3%
잡수익 946
 
9.5%
광고료수익 905
 
9.0%
주차장수익 887
 
8.9%
기타운영수익 634
 
6.3%
고용안정사업수익 525
 
5.2%
검침수익 304
 
3.0%
부과차익 211
 
2.1%
알뜰시장수익 210
 
2.1%
Other values (5) 607
 
6.1%

Length

2024-05-11T02:32:15.779934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3636
36.4%
승강기수익 1135
 
11.3%
잡수익 946
 
9.5%
광고료수익 905
 
9.0%
주차장수익 887
 
8.9%
기타운영수익 634
 
6.3%
고용안정사업수익 525
 
5.2%
검침수익 304
 
3.0%
부과차익 211
 
2.1%
알뜰시장수익 210
 
2.1%
Other values (5) 607
 
6.1%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210518
Minimum20210501
Maximum20210531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:32:16.256157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210501
5-th percentile20210503
Q120210510
median20210518
Q320210526
95-th percentile20210531
Maximum20210531
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.445211
Coefficient of variation (CV)4.6734137 × 10-7
Kurtosis-1.2900262
Mean20210518
Median Absolute Deviation (MAD)8
Skewness-0.17945801
Sum2.0210518 × 1011
Variance89.212011
MonotonicityNot monotonic
2024-05-11T02:32:16.920799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210531 1103
 
11.0%
20210525 608
 
6.1%
20210510 550
 
5.5%
20210503 535
 
5.3%
20210514 488
 
4.9%
20210520 468
 
4.7%
20210528 450
 
4.5%
20210524 445
 
4.5%
20210526 442
 
4.4%
20210518 436
 
4.4%
Other values (21) 4475
44.8%
ValueCountFrequency (%)
20210501 190
 
1.9%
20210502 142
 
1.4%
20210503 535
5.3%
20210504 408
4.1%
20210505 108
 
1.1%
20210506 425
4.2%
20210507 336
3.4%
20210508 83
 
0.8%
20210509 61
 
0.6%
20210510 550
5.5%
ValueCountFrequency (%)
20210531 1103
11.0%
20210530 178
 
1.8%
20210529 140
 
1.4%
20210528 450
4.5%
20210527 429
 
4.3%
20210526 442
4.4%
20210525 608
6.1%
20210524 445
4.5%
20210523 111
 
1.1%
20210522 97
 
1.0%

금액
Real number (ℝ)

SKEWED 

Distinct3181
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226162.37
Minimum-10182840
Maximum64237000
Zeros14
Zeros (%)0.1%
Negative40
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:32:17.497706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10182840
5-th percentile140
Q12530
median30000
Q3100000
95-th percentile817016.5
Maximum64237000
Range74419840
Interquartile range (IQR)97470

Descriptive statistics

Standard deviation1354408.4
Coefficient of variation (CV)5.9886549
Kurtosis1146.228
Mean226162.37
Median Absolute Deviation (MAD)29290
Skewness28.288271
Sum2.2616237 × 109
Variance1.8344221 × 1012
MonotonicityNot monotonic
2024-05-11T02:32:17.945532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 618
 
6.2%
30000 604
 
6.0%
100000 559
 
5.6%
150000 181
 
1.8%
60000 175
 
1.8%
200000 155
 
1.6%
70000 147
 
1.5%
40000 139
 
1.4%
120000 108
 
1.1%
80000 95
 
0.9%
Other values (3171) 7219
72.2%
ValueCountFrequency (%)
-10182840 1
 
< 0.1%
-2500000 1
 
< 0.1%
-990000 1
 
< 0.1%
-710780 1
 
< 0.1%
-693870 1
 
< 0.1%
-551420 1
 
< 0.1%
-360000 1
 
< 0.1%
-300000 3
< 0.1%
-290000 1
 
< 0.1%
-162500 1
 
< 0.1%
ValueCountFrequency (%)
64237000 1
< 0.1%
59950590 1
< 0.1%
53045911 1
< 0.1%
27252040 1
< 0.1%
23683090 1
< 0.1%
17056150 1
< 0.1%
15990000 1
< 0.1%
14000000 1
< 0.1%
13400000 1
< 0.1%
13100000 1
< 0.1%

내용
Text

Distinct5691
Distinct (%)56.9%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:32:18.772392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length67
Mean length13.939257
Min length2

Characters and Unicode

Total characters139295
Distinct characters739
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

Unique5450 ?
Unique (%)54.5%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row관리비 연체료 수납
4th row104-802 승강기사용료:에어컨
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3763
 
14.2%
연체료 3645
 
13.8%
수납 3643
 
13.8%
승강기 338
 
1.3%
5월분 335
 
1.3%
4월분 286
 
1.1%
274
 
1.0%
승강기사용료 242
 
0.9%
사용료 228
 
0.9%
입금 224
 
0.8%
Other values (7219) 13472
50.9%
2024-05-11T02:32:20.175172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16561
 
11.9%
료 5660
 
4.1%
리 5049
 
3.6%
수 5041
 
3.6%
0 4717
 
3.4%
비 4588
 
3.3%
1 4505
 
3.2%
관 3958
 
2.8%
체 3845
 
2.8%
연 3715
 
2.7%
Other values (729) 81656
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90365
64.9%
Decimal Number 20404
 
14.6%
Space Separator 16561
 
11.9%
Close Punctuation 3005
 
2.2%
Open Punctuation 2987
 
2.1%
Other Punctuation 2609
 
1.9%
Dash Punctuation 2215
 
1.6%
Uppercase Letter 671
 
0.5%
Math Symbol 301
 
0.2%
Lowercase Letter 95
 
0.1%
Other values (4) 82
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5660
 
6.3%
리 5049
 
5.6%
수 5041
 
5.6%
비 4588
 
5.1%
관 3958
 
4.4%
체 3845
 
4.3%
연 3715
 
4.1%
납 3688
 
4.1%
월 1854
 
2.1%
사 1780
 
2.0%
Other values (645) 51187
56.6%
Uppercase Letter
ValueCountFrequency (%)
N 78
 
11.6%
C 56
 
8.3%
A 52
 
7.7%
T 51
 
7.6%
D 43
 
6.4%
E 41
 
6.1%
O 40
 
6.0%
L 39
 
5.8%
K 36
 
5.4%
M 34
 
5.1%
Other values (15) 201
30.0%
Lowercase Letter
ValueCountFrequency (%)
o 28
29.5%
x 13
13.7%
e 11
 
11.6%
n 8
 
8.4%
l 7
 
7.4%
t 6
 
6.3%
k 4
 
4.2%
a 4
 
4.2%
b 2
 
2.1%
h 2
 
2.1%
Other values (7) 10
 
10.5%
Other Punctuation
ValueCountFrequency (%)
/ 772
29.6%
, 672
25.8%
. 638
24.5%
: 185
 
7.1%
? 132
 
5.1%
* 126
 
4.8%
@ 33
 
1.3%
% 19
 
0.7%
# 10
 
0.4%
& 8
 
0.3%
Other values (4) 14
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 4717
23.1%
1 4505
22.1%
2 2698
13.2%
5 2308
11.3%
4 1935
9.5%
3 1557
 
7.6%
6 918
 
4.5%
7 652
 
3.2%
8 624
 
3.1%
9 490
 
2.4%
Math Symbol
ValueCountFrequency (%)
~ 227
75.4%
× 18
 
6.0%
+ 17
 
5.6%
> 16
 
5.3%
= 13
 
4.3%
< 8
 
2.7%
→ 2
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 2930
97.5%
] 75
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 2915
97.6%
[ 72
 
2.4%
Other Number
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%
Space Separator
ValueCountFrequency (%)
16561
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2215
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 78
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
ⅹ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90363
64.9%
Common 48163
34.6%
Latin 767
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5660
 
6.3%
리 5049
 
5.6%
수 5041
 
5.6%
비 4588
 
5.1%
관 3958
 
4.4%
체 3845
 
4.3%
연 3715
 
4.1%
납 3688
 
4.1%
월 1854
 
2.1%
사 1780
 
2.0%
Other values (643) 51185
56.6%
Latin
ValueCountFrequency (%)
N 78
 
10.2%
C 56
 
7.3%
A 52
 
6.8%
T 51
 
6.6%
D 43
 
5.6%
E 41
 
5.3%
O 40
 
5.2%
L 39
 
5.1%
K 36
 
4.7%
M 34
 
4.4%
Other values (33) 297
38.7%
Common
ValueCountFrequency (%)
16561
34.4%
0 4717
 
9.8%
1 4505
 
9.4%
) 2930
 
6.1%
( 2915
 
6.1%
2 2698
 
5.6%
5 2308
 
4.8%
- 2215
 
4.6%
4 1935
 
4.0%
3 1557
 
3.2%
Other values (31) 5822
 
12.1%
Han
ValueCountFrequency (%)
用 1
50.0%
人 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90363
64.9%
ASCII 48906
35.1%
None 19
 
< 0.1%
Arrows 2
 
< 0.1%
CJK 2
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16561
33.9%
0 4717
 
9.6%
1 4505
 
9.2%
) 2930
 
6.0%
( 2915
 
6.0%
2 2698
 
5.5%
5 2308
 
4.7%
- 2215
 
4.5%
4 1935
 
4.0%
3 1557
 
3.2%
Other values (68) 6565
 
13.4%
Hangul
ValueCountFrequency (%)
료 5660
 
6.3%
리 5049
 
5.6%
수 5041
 
5.6%
비 4588
 
5.1%
관 3958
 
4.4%
체 3845
 
4.3%
연 3715
 
4.1%
납 3688
 
4.1%
월 1854
 
2.1%
사 1780
 
2.0%
Other values (643) 51185
56.6%
None
ValueCountFrequency (%)
× 18
94.7%
？ 1
 
5.3%
Arrows
ValueCountFrequency (%)
→ 2
100.0%
Number Forms
ValueCountFrequency (%)
ⅹ 1
100.0%
CJK
ValueCountFrequency (%)
用 1
50.0%
人 1
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
50.0%
② 1
50.0%

Interactions

2024-05-11T02:32:09.682402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:08.869661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:09.992655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:09.249912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:32:20.439874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4270.162
년월일0.4271.0000.083
금액0.1620.0831.000
2024-05-11T02:32:20.820584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0660.174
금액0.0661.0000.068
비용명0.1740.0681.000

Missing values

2024-05-11T02:32:10.405330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:32:10.827085image/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
23679둔촌현대2차A13406201연체료수익202105282670관리비 연체료 수납
829이편한세상 송파파크센트럴A10024787연체료수익20210525630관리비 연체료 수납
4012아크로리버뷰 신반포A10026227연체료수익202105293110관리비 연체료 수납
3691마포자이3차아파트A10026036승강기수익20210503100000104-802 승강기사용료:에어컨
35925송파파인타운6단지A13876108연체료수익20210503610관리비 연체료 수납
1835잠실올림픽공원아이파크A10025185기타운영수익202105187000주민회의실이용 104-2702
54363상도래미안1차제2A15603007주차장수익2021051770000외부주차료(강문화)
59979목동롯데캐슬위너A15805303임대료수익202105314563505월 임대료
12598신수성원A12185504부과차익202105216804월 부과차익
40048상계주공12단지A13982202승강기수익20210507500001213-0708 승강기 이용료 - 신한(잡)
아파트명아파트코드비용명년월일금액내용
40334상계주공2단지A13983004광고료수익2021052050000게시판광고 와우필라테스
19353창동동아청솔A13204409광고료수익2021052550000게시판광고, 학원~5/31
23542암사선사현대A13405201기타운영수익202105073400음식물 카드판매[116-1906,106-2605]
42609이촌한강맨션A14003008이자수익202105317219신한 5월 잡수익 MMF계좌 평가이자(세전)
7489용두 롯데 캐슬리치 아파트A10028080기타운영수익2021052840000독서실 이용료(최성아)
53677독산진도2차A15383601검침수익2021052464050한전검침지원금 입금
31773반포본동아파트A13704901광고료수익20210524100000정원공인중개사
471개포래미안포레스트A10024564승강기수익2021050680000승강기 사용료 입금 - 104동 1002호 전출
51403경남아너스빌A15210207주차장수익2021053150000외부주차료수입(알파전자)
7845신당남산타운(분양)A10045302연체료수익2021051718690관리비 연체료 수납