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 = 22.04975614)Skewed

Reproduction

Analysis started2024-05-11 02:24:32.788965
Analysis finished2024-05-11 02:24:36.136700
Duration3.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2199
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:36.416870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.5089
Min length2

Characters and Unicode

Total characters75089
Distinct characters435
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

Unique270 ?
Unique (%)2.7%

Sample

1st row답십리동답한신
2nd row신정이든채
3rd row우장산아이파크이편한세상
4th row송파 시그니처 롯데캐슬아파트
5th row우면코오롱
ValueCountFrequency (%)
아파트 219
 
2.0%
래미안 65
 
0.6%
아이파크 35
 
0.3%
e편한세상 34
 
0.3%
고덕 30
 
0.3%
마포래미안푸르지오 24
 
0.2%
센트럴 22
 
0.2%
롯데캐슬아파트 21
 
0.2%
이편한세상 20
 
0.2%
송파 20
 
0.2%
Other values (2283) 10559
95.6%
2024-05-11T02:24:37.057981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2727
 
3.6%
파 2659
 
3.5%
트 2606
 
3.5%
지 2004
 
2.7%
이 1609
 
2.1%
동 1581
 
2.1%
대 1551
 
2.1%
단 1533
 
2.0%
신 1331
 
1.8%
차 1254
 
1.7%
Other values (425) 56234
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68740
91.5%
Decimal Number 3457
 
4.6%
Space Separator 1140
 
1.5%
Uppercase Letter 928
 
1.2%
Lowercase Letter 305
 
0.4%
Close Punctuation 154
 
0.2%
Open Punctuation 154
 
0.2%
Other Punctuation 103
 
0.1%
Dash Punctuation 98
 
0.1%
Letter Number 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2727
 
4.0%
파 2659
 
3.9%
트 2606
 
3.8%
지 2004
 
2.9%
이 1609
 
2.3%
동 1581
 
2.3%
대 1551
 
2.3%
단 1533
 
2.2%
신 1331
 
1.9%
차 1254
 
1.8%
Other values (380) 49885
72.6%
Uppercase Letter
ValueCountFrequency (%)
S 155
16.7%
K 130
14.0%
C 130
14.0%
D 90
9.7%
M 90
9.7%
H 54
 
5.8%
I 49
 
5.3%
E 43
 
4.6%
L 42
 
4.5%
A 34
 
3.7%
Other values (7) 111
12.0%
Lowercase Letter
ValueCountFrequency (%)
e 190
62.3%
l 24
 
7.9%
s 22
 
7.2%
i 20
 
6.6%
k 16
 
5.2%
v 14
 
4.6%
h 7
 
2.3%
w 6
 
2.0%
c 2
 
0.7%
a 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
2 1041
30.1%
1 1033
29.9%
3 433
12.5%
4 228
 
6.6%
5 189
 
5.5%
6 162
 
4.7%
7 128
 
3.7%
9 105
 
3.0%
8 81
 
2.3%
0 57
 
1.6%
Other Punctuation
ValueCountFrequency (%)
, 80
77.7%
. 23
 
22.3%
Space Separator
ValueCountFrequency (%)
1140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 154
100.0%
Open Punctuation
ValueCountFrequency (%)
( 154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68740
91.5%
Common 5106
 
6.8%
Latin 1243
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2727
 
4.0%
파 2659
 
3.9%
트 2606
 
3.8%
지 2004
 
2.9%
이 1609
 
2.3%
동 1581
 
2.3%
대 1551
 
2.3%
단 1533
 
2.2%
신 1331
 
1.9%
차 1254
 
1.8%
Other values (380) 49885
72.6%
Latin
ValueCountFrequency (%)
e 190
15.3%
S 155
12.5%
K 130
10.5%
C 130
10.5%
D 90
 
7.2%
M 90
 
7.2%
H 54
 
4.3%
I 49
 
3.9%
E 43
 
3.5%
L 42
 
3.4%
Other values (19) 270
21.7%
Common
ValueCountFrequency (%)
1140
22.3%
2 1041
20.4%
1 1033
20.2%
3 433
 
8.5%
4 228
 
4.5%
5 189
 
3.7%
6 162
 
3.2%
) 154
 
3.0%
( 154
 
3.0%
7 128
 
2.5%
Other values (6) 444
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68740
91.5%
ASCII 6339
 
8.4%
Number Forms 10
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2727
 
4.0%
파 2659
 
3.9%
트 2606
 
3.8%
지 2004
 
2.9%
이 1609
 
2.3%
동 1581
 
2.3%
대 1551
 
2.3%
단 1533
 
2.2%
신 1331
 
1.9%
차 1254
 
1.8%
Other values (380) 49885
72.6%
ASCII
ValueCountFrequency (%)
1140
18.0%
2 1041
16.4%
1 1033
16.3%
3 433
 
6.8%
4 228
 
3.6%
e 190
 
3.0%
5 189
 
3.0%
6 162
 
2.6%
S 155
 
2.4%
) 154
 
2.4%
Other values (34) 1614
25.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 10
100.0%

아파트코드
Text

Distinct2203
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:24:37.635550image/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

Unique271 ?
Unique (%)2.7%

Sample

1st rowA13003405
2nd rowA10025649
3rd rowA15701003
4th rowA10023887
5th rowA13790002
ValueCountFrequency (%)
a12175203 24
 
0.2%
a12085303 17
 
0.2%
a10026180 17
 
0.2%
a13405201 17
 
0.2%
a13718001 17
 
0.2%
a14021001 17
 
0.2%
a15805115 17
 
0.2%
a10028021 17
 
0.2%
a10024872 16
 
0.2%
a10026104 16
 
0.2%
Other values (2193) 9825
98.2%
2024-05-11T02:24:38.631875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18920
21.0%
1 17025
18.9%
A 9986
11.1%
3 8595
9.6%
2 8351
9.3%
5 6174
 
6.9%
8 5431
 
6.0%
7 4834
 
5.4%
4 4131
 
4.6%
6 3505
 
3.9%
Other values (2) 3048
 
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 18920
23.6%
1 17025
21.3%
3 8595
10.7%
2 8351
10.4%
5 6174
 
7.7%
8 5431
 
6.8%
7 4834
 
6.0%
4 4131
 
5.2%
6 3505
 
4.4%
9 3034
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9986
99.9%
B 14
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18920
23.6%
1 17025
21.3%
3 8595
10.7%
2 8351
10.4%
5 6174
 
7.7%
8 5431
 
6.8%
7 4834
 
6.0%
4 4131
 
5.2%
6 3505
 
4.4%
9 3034
 
3.8%
Latin
ValueCountFrequency (%)
A 9986
99.9%
B 14
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18920
21.0%
1 17025
18.9%
A 9986
11.1%
3 8595
9.6%
2 8351
9.3%
5 6174
 
6.9%
8 5431
 
6.0%
7 4834
 
5.4%
4 4131
 
4.6%
6 3505
 
3.9%
Other values (2) 3048
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3778 
승강기수익
1136 
잡수익
991 
광고료수익
989 
기타운영수익
894 
Other values (10)
2212 

Length

Max length9
Median length5
Mean length4.8914
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3778
37.8%
승강기수익 1136
 
11.4%
잡수익 991
 
9.9%
광고료수익 989
 
9.9%
기타운영수익 894
 
8.9%
주차장수익 843
 
8.4%
검침수익 311
 
3.1%
부과차익 233
 
2.3%
임대료수익 216
 
2.2%
알뜰시장수익 208
 
2.1%
Other values (5) 401
 
4.0%

Length

2024-05-11T02:24:39.079970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3778
37.8%
승강기수익 1136
 
11.4%
잡수익 991
 
9.9%
광고료수익 989
 
9.9%
기타운영수익 894
 
8.9%
주차장수익 843
 
8.4%
검침수익 311
 
3.1%
부과차익 233
 
2.3%
임대료수익 216
 
2.2%
알뜰시장수익 208
 
2.1%
Other values (5) 401
 
4.0%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230517
Minimum20230501
Maximum20230531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:24:39.454792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230501
5-th percentile20230502
Q120230508
median20230517
Q320230526
95-th percentile20230531
Maximum20230531
Range30
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.07181
Coefficient of variation (CV)4.9785232 × 10-7
Kurtosis-1.366383
Mean20230517
Median Absolute Deviation (MAD)9
Skewness-0.095631963
Sum2.0230517 × 1011
Variance101.44135
MonotonicityNot monotonic
2024-05-11T02:24:39.869440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20230531 1110
 
11.1%
20230502 691
 
6.9%
20230530 622
 
6.2%
20230510 487
 
4.9%
20230525 473
 
4.7%
20230503 449
 
4.5%
20230508 432
 
4.3%
20230526 419
 
4.2%
20230504 418
 
4.2%
20230522 405
 
4.0%
Other values (21) 4494
44.9%
ValueCountFrequency (%)
20230501 306
3.1%
20230502 691
6.9%
20230503 449
4.5%
20230504 418
4.2%
20230505 110
 
1.1%
20230506 73
 
0.7%
20230507 79
 
0.8%
20230508 432
4.3%
20230509 353
3.5%
20230510 487
4.9%
ValueCountFrequency (%)
20230531 1110
11.1%
20230530 622
6.2%
20230529 183
 
1.8%
20230528 132
 
1.3%
20230527 129
 
1.3%
20230526 419
 
4.2%
20230525 473
4.7%
20230524 350
 
3.5%
20230523 389
 
3.9%
20230522 405
 
4.0%

금액
Real number (ℝ)

SKEWED 

Distinct3345
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307018.83
Minimum-2959000
Maximum94100000
Zeros24
Zeros (%)0.2%
Negative35
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:24:40.286877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2959000
5-th percentile160
Q12590
median28735
Q3100000
95-th percentile987446.5
Maximum94100000
Range97059000
Interquartile range (IQR)97410

Descriptive statistics

Standard deviation2084825.6
Coefficient of variation (CV)6.7905462
Kurtosis703.65437
Mean307018.83
Median Absolute Deviation (MAD)27635
Skewness22.049756
Sum3.0701883 × 109
Variance4.3464977 × 1012
MonotonicityNot monotonic
2024-05-11T02:24:40.970547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 574
 
5.7%
50000 555
 
5.5%
100000 533
 
5.3%
150000 156
 
1.6%
70000 148
 
1.5%
60000 135
 
1.4%
200000 134
 
1.3%
40000 132
 
1.3%
20000 109
 
1.1%
80000 109
 
1.1%
Other values (3335) 7415
74.2%
ValueCountFrequency (%)
-2959000 1
 
< 0.1%
-845160 1
 
< 0.1%
-480000 1
 
< 0.1%
-340000 1
 
< 0.1%
-334800 1
 
< 0.1%
-200000 2
< 0.1%
-136364 1
 
< 0.1%
-100000 3
< 0.1%
-99360 1
 
< 0.1%
-82320 1
 
< 0.1%
ValueCountFrequency (%)
94100000 1
< 0.1%
70000000 1
< 0.1%
60827050 1
< 0.1%
45000000 1
< 0.1%
40000000 1
< 0.1%
38800000 1
< 0.1%
36924930 1
< 0.1%
36608727 1
< 0.1%
33936980 1
< 0.1%
29491000 1
< 0.1%

내용
Text

Distinct5512
Distinct (%)55.2%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:24:41.558676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length67
Mean length14.308916
Min length2

Characters and Unicode

Total characters142989
Distinct characters736
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5233 ?
Unique (%)52.4%

Sample

1st row???????????(?????)
2nd row호두과자판매(103-406호 주민)
3rd row게시판광고/영어과외
4th row주차료 수입 [신용카드 매출]
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3905
 
14.2%
연체료 3781
 
13.8%
수납 3780
 
13.8%
2326
 
8.5%
승강기 292
 
1.1%
5월분 267
 
1.0%
사용료 210
 
0.8%
승강기사용료 204
 
0.7%
5월 188
 
0.7%
4월분 171
 
0.6%
Other values (6715) 12320
44.9%
2024-05-11T02:24:42.664521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17892
 
12.5%
? 12175
 
8.5%
료 5557
 
3.9%
수 4989
 
3.5%
0 4977
 
3.5%
1 4571
 
3.2%
비 4406
 
3.1%
리 4370
 
3.1%
관 4068
 
2.8%
체 3950
 
2.8%
Other values (726) 76034
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78165
54.7%
Decimal Number 22321
 
15.6%
Space Separator 17892
 
12.5%
Other Punctuation 14930
 
10.4%
Close Punctuation 2924
 
2.0%
Open Punctuation 2917
 
2.0%
Dash Punctuation 2446
 
1.7%
Uppercase Letter 779
 
0.5%
Math Symbol 375
 
0.3%
Lowercase Letter 132
 
0.1%
Other values (2) 108
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5557
 
7.1%
수 4989
 
6.4%
비 4406
 
5.6%
리 4370
 
5.6%
관 4068
 
5.2%
체 3950
 
5.1%
연 3861
 
4.9%
납 3823
 
4.9%
용 1507
 
1.9%
사 1452
 
1.9%
Other values (639) 40182
51.4%
Uppercase Letter
ValueCountFrequency (%)
N 87
 
11.2%
K 58
 
7.4%
C 58
 
7.4%
T 57
 
7.3%
O 53
 
6.8%
L 49
 
6.3%
A 48
 
6.2%
S 48
 
6.2%
G 41
 
5.3%
B 40
 
5.1%
Other values (15) 240
30.8%
Lowercase Letter
ValueCountFrequency (%)
o 39
29.5%
k 16
12.1%
n 14
 
10.6%
s 10
 
7.6%
t 9
 
6.8%
e 7
 
5.3%
i 5
 
3.8%
d 4
 
3.0%
b 4
 
3.0%
g 4
 
3.0%
Other values (11) 20
15.2%
Other Punctuation
ValueCountFrequency (%)
? 12175
81.5%
/ 944
 
6.3%
. 859
 
5.8%
, 581
 
3.9%
: 186
 
1.2%
* 103
 
0.7%
% 21
 
0.1%
@ 20
 
0.1%
& 14
 
0.1%
# 11
 
0.1%
Other values (4) 16
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 4977
22.3%
1 4571
20.5%
2 3225
14.4%
5 2501
11.2%
3 2078
9.3%
4 1816
 
8.1%
6 1080
 
4.8%
7 747
 
3.3%
8 713
 
3.2%
9 613
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 337
89.9%
+ 17
 
4.5%
> 9
 
2.4%
= 5
 
1.3%
× 3
 
0.8%
< 2
 
0.5%
⇒ 1
 
0.3%
→ 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 2825
96.8%
[ 91
 
3.1%
{ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2834
96.9%
] 90
 
3.1%
Space Separator
ValueCountFrequency (%)
17892
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2446
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 106
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78157
54.7%
Common 63913
44.7%
Latin 911
 
0.6%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5557
 
7.1%
수 4989
 
6.4%
비 4406
 
5.6%
리 4370
 
5.6%
관 4068
 
5.2%
체 3950
 
5.1%
연 3861
 
4.9%
납 3823
 
4.9%
용 1507
 
1.9%
사 1452
 
1.9%
Other values (635) 40174
51.4%
Latin
ValueCountFrequency (%)
N 87
 
9.5%
K 58
 
6.4%
C 58
 
6.4%
T 57
 
6.3%
O 53
 
5.8%
L 49
 
5.4%
A 48
 
5.3%
S 48
 
5.3%
G 41
 
4.5%
B 40
 
4.4%
Other values (36) 372
40.8%
Common
ValueCountFrequency (%)
17892
28.0%
? 12175
19.0%
0 4977
 
7.8%
1 4571
 
7.2%
2 3225
 
5.0%
) 2834
 
4.4%
( 2825
 
4.4%
5 2501
 
3.9%
- 2446
 
3.8%
3 2078
 
3.3%
Other values (31) 8389
13.1%
Han
ValueCountFrequency (%)
入 5
62.5%
金 1
 
12.5%
返 1
 
12.5%
內 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78156
54.7%
ASCII 64818
45.3%
CJK 7
 
< 0.1%
None 4
 
< 0.1%
Arrows 2
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17892
27.6%
? 12175
18.8%
0 4977
 
7.7%
1 4571
 
7.1%
2 3225
 
5.0%
) 2834
 
4.4%
( 2825
 
4.4%
5 2501
 
3.9%
- 2446
 
3.8%
3 2078
 
3.2%
Other values (73) 9294
14.3%
Hangul
ValueCountFrequency (%)
료 5557
 
7.1%
수 4989
 
6.4%
비 4406
 
5.6%
리 4370
 
5.6%
관 4068
 
5.2%
체 3950
 
5.1%
연 3861
 
4.9%
납 3823
 
4.9%
용 1507
 
1.9%
사 1452
 
1.9%
Other values (634) 40173
51.4%
CJK
ValueCountFrequency (%)
入 5
71.4%
返 1
 
14.3%
內 1
 
14.3%
None
ValueCountFrequency (%)
× 3
75.0%
？ 1
 
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
100.0%
Arrows
ValueCountFrequency (%)
⇒ 1
50.0%
→ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅊ 1
100.0%

Interactions

2024-05-11T02:24:34.967322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:34.492911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:35.240758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:24:34.772766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:24:42.849552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3500.158
년월일0.3501.0000.046
금액0.1580.0461.000
2024-05-11T02:24:43.017302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0630.138
금액0.0631.0000.068
비용명0.1380.0681.000

Missing values

2024-05-11T02:24:35.589606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:24:35.967968image/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
16640답십리동답한신A13003405공동주택지원금수익20230511353000???????????(?????)
4933신정이든채A10025649광고료수익2023052320000호두과자판매(103-406호 주민)
55883우장산아이파크이편한세상A15701003광고료수익20230521120000게시판광고/영어과외
713송파 시그니처 롯데캐슬아파트A10023887주차장수익2023052848182주차료 수입 [신용카드 매출]
34735우면코오롱A13790002연체료수익20230529150관리비 연체료 수납
35050신반포4차A13790828연체료수익20230525250관리비 연체료 수납
50427신도림롯데A15205511연체료수익202305122030관리비 연체료 수납
32906반포미도아파트A13704404연체료수익20230504200관리비 연체료 수납
9037신내의료안심주택A10027775연체료수익202305243980관리비 연체료 수납
50367구로두산A15205405잡수익202305021030101-808 ?? ???
아파트명아파트코드비용명년월일금액내용
49664성현동아A15176202승강기수익20230502170000104동 805호 전입세대 승강기 사용료
53611신대방현대A15601105알뜰시장수익2023052930000일일알뜰장(먹거리-떡볶이)
45175이튼타워리버3차A14319306연체료수익202305096090관리비 연체료 수납
52810관악벽산타운5단지A15303205주차장수익20230531116486005월 주차료 부과
3668e편한세상서울대입구아파트A10025092연체료수익202305294330관리비 연체료 수납
13778메세나폴리스A12174601기타운영수익20230520145818캡슐(4),냉동냉장(16),스크린골프(3)
58594화곡중앙하이츠A15788203부과차익2023051912074월분 관리비 부과시
13743메세나폴리스A12174601기타운영수익2023050167182캡슐(5),냉동냉장(7),스크린골프(2)
16177백련산힐스테이트3차A12290901연체료수익202305242280관리비 연체료 수납
1095양원역 금호어울림포레스트아파트A10024018연체료수익202305021430관리비 연체료 수납