Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells12
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 = 32.67655264)Skewed

Reproduction

Analysis started2024-05-11 02:23:36.537221
Analysis finished2024-05-11 02:23:39.838094
Duration3.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2177
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:23:40.040835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.5347
Min length2

Characters and Unicode

Total characters75347
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

Unique255 ?
Unique (%)2.5%

Sample

1st row반포써밋
2nd row래미안하이리버
3rd row가락프라자
4th row양평한신
5th row목동12단지
ValueCountFrequency (%)
아파트 228
 
2.1%
래미안 63
 
0.6%
e편한세상 45
 
0.4%
아이파크 41
 
0.4%
고덕 27
 
0.2%
금천롯데캐슬골드파크1차아파트 26
 
0.2%
힐스테이트 24
 
0.2%
마포래미안푸르지오 23
 
0.2%
텐즈힐2구역 21
 
0.2%
송파 21
 
0.2%
Other values (2260) 10515
95.3%
2024-05-11T02:23:40.890993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 2807
 
3.7%
아 2756
 
3.7%
트 2653
 
3.5%
지 2076
 
2.8%
단 1611
 
2.1%
대 1591
 
2.1%
이 1577
 
2.1%
동 1509
 
2.0%
신 1369
 
1.8%
차 1295
 
1.7%
Other values (419) 56103
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68828
91.3%
Decimal Number 3693
 
4.9%
Space Separator 1149
 
1.5%
Uppercase Letter 815
 
1.1%
Lowercase Letter 326
 
0.4%
Close Punctuation 140
 
0.2%
Open Punctuation 140
 
0.2%
Other Punctuation 128
 
0.2%
Dash Punctuation 123
 
0.2%
Letter Number 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2807
 
4.1%
아 2756
 
4.0%
트 2653
 
3.9%
지 2076
 
3.0%
단 1611
 
2.3%
대 1591
 
2.3%
이 1577
 
2.3%
동 1509
 
2.2%
신 1369
 
2.0%
차 1295
 
1.9%
Other values (374) 49584
72.0%
Uppercase Letter
ValueCountFrequency (%)
S 140
17.2%
C 122
15.0%
K 102
12.5%
M 87
10.7%
D 87
10.7%
H 52
 
6.4%
L 41
 
5.0%
E 35
 
4.3%
I 33
 
4.0%
A 32
 
3.9%
Other values (7) 84
10.3%
Lowercase Letter
ValueCountFrequency (%)
e 212
65.0%
k 26
 
8.0%
s 26
 
8.0%
l 16
 
4.9%
i 13
 
4.0%
c 12
 
3.7%
v 9
 
2.8%
h 6
 
1.8%
w 4
 
1.2%
g 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 1110
30.1%
2 1075
29.1%
3 435
 
11.8%
4 275
 
7.4%
5 212
 
5.7%
6 181
 
4.9%
7 130
 
3.5%
9 118
 
3.2%
8 94
 
2.5%
0 63
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 111
86.7%
. 17
 
13.3%
Space Separator
ValueCountFrequency (%)
1149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 140
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68828
91.3%
Common 5373
 
7.1%
Latin 1146
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2807
 
4.1%
아 2756
 
4.0%
트 2653
 
3.9%
지 2076
 
3.0%
단 1611
 
2.3%
대 1591
 
2.3%
이 1577
 
2.3%
동 1509
 
2.2%
신 1369
 
2.0%
차 1295
 
1.9%
Other values (374) 49584
72.0%
Latin
ValueCountFrequency (%)
e 212
18.5%
S 140
12.2%
C 122
10.6%
K 102
8.9%
M 87
 
7.6%
D 87
 
7.6%
H 52
 
4.5%
L 41
 
3.6%
E 35
 
3.1%
I 33
 
2.9%
Other values (19) 235
20.5%
Common
ValueCountFrequency (%)
1149
21.4%
1 1110
20.7%
2 1075
20.0%
3 435
 
8.1%
4 275
 
5.1%
5 212
 
3.9%
6 181
 
3.4%
) 140
 
2.6%
( 140
 
2.6%
7 130
 
2.4%
Other values (6) 526
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68828
91.3%
ASCII 6514
 
8.6%
Number Forms 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 2807
 
4.1%
아 2756
 
4.0%
트 2653
 
3.9%
지 2076
 
3.0%
단 1611
 
2.3%
대 1591
 
2.3%
이 1577
 
2.3%
동 1509
 
2.2%
신 1369
 
2.0%
차 1295
 
1.9%
Other values (374) 49584
72.0%
ASCII
ValueCountFrequency (%)
1149
17.6%
1 1110
17.0%
2 1075
16.5%
3 435
 
6.7%
4 275
 
4.2%
e 212
 
3.3%
5 212
 
3.3%
6 181
 
2.8%
) 140
 
2.1%
S 140
 
2.1%
Other values (34) 1585
24.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 5
100.0%

아파트코드
Text

Distinct2182
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:23:41.568191image/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

Unique257 ?
Unique (%)2.6%

Sample

1st rowA10026015
2nd rowA13380302
3rd rowA13881204
4th rowA15010502
5th rowA15807706
ValueCountFrequency (%)
a10027188 26
 
0.3%
a12175203 23
 
0.2%
a13373301 21
 
0.2%
a13380803 18
 
0.2%
a10028021 18
 
0.2%
a13805002 18
 
0.2%
a13822003 17
 
0.2%
a15728009 17
 
0.2%
a15205305 17
 
0.2%
a13822004 16
 
0.2%
Other values (2172) 9809
98.1%
2024-05-11T02:23:42.507556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18834
20.9%
1 16983
18.9%
A 9996
11.1%
3 8711
9.7%
2 8446
9.4%
5 6269
 
7.0%
8 5570
 
6.2%
7 4761
 
5.3%
4 4137
 
4.6%
6 3353
 
3.7%
Other values (2) 2940
 
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 18834
23.5%
1 16983
21.2%
3 8711
10.9%
2 8446
10.6%
5 6269
 
7.8%
8 5570
 
7.0%
7 4761
 
6.0%
4 4137
 
5.2%
6 3353
 
4.2%
9 2936
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9996
> 99.9%
B 4
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18834
23.5%
1 16983
21.2%
3 8711
10.9%
2 8446
10.6%
5 6269
 
7.8%
8 5570
 
7.0%
7 4761
 
6.0%
4 4137
 
5.2%
6 3353
 
4.2%
9 2936
 
3.7%
Latin
ValueCountFrequency (%)
A 9996
> 99.9%
B 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18834
20.9%
1 16983
18.9%
A 9996
11.1%
3 8711
9.7%
2 8446
9.4%
5 6269
 
7.0%
8 5570
 
6.2%
7 4761
 
5.3%
4 4137
 
4.6%
6 3353
 
3.7%
Other values (2) 2940
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3454 
승강기수익
1289 
잡수익
1028 
광고료수익
1026 
주차장수익
925 
Other values (10)
2278 

Length

Max length9
Median length5
Mean length4.8538
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3454
34.5%
승강기수익 1289
 
12.9%
잡수익 1028
 
10.3%
광고료수익 1026
 
10.3%
주차장수익 925
 
9.2%
기타운영수익 812
 
8.1%
검침수익 365
 
3.6%
임대료수익 252
 
2.5%
재활용품수익 240
 
2.4%
부과차익 238
 
2.4%
Other values (5) 371
 
3.7%

Length

2024-05-11T02:23:42.782852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3454
34.5%
승강기수익 1289
 
12.9%
잡수익 1028
 
10.3%
광고료수익 1026
 
10.3%
주차장수익 925
 
9.2%
기타운영수익 812
 
8.1%
검침수익 365
 
3.6%
임대료수익 252
 
2.5%
재활용품수익 240
 
2.4%
부과차익 238
 
2.4%
Other values (5) 371
 
3.7%

년월일
Real number (ℝ)

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230216
Minimum20230201
Maximum20230228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:23:43.069561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230201
5-th percentile20230201
Q120230208
median20230217
Q320230224
95-th percentile20230228
Maximum20230228
Range27
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.1138699
Coefficient of variation (CV)4.5050779 × 10-7
Kurtosis-1.3342818
Mean20230216
Median Absolute Deviation (MAD)8
Skewness-0.21095971
Sum2.0230216 × 1011
Variance83.062624
MonotonicityNot monotonic
2024-05-11T02:23:43.479873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20230228 1321
 
13.2%
20230227 686
 
6.9%
20230201 592
 
5.9%
20230224 541
 
5.4%
20230206 502
 
5.0%
20230220 494
 
4.9%
20230210 488
 
4.9%
20230202 421
 
4.2%
20230221 406
 
4.1%
20230223 384
 
3.8%
Other values (18) 4165
41.6%
ValueCountFrequency (%)
20230201 592
5.9%
20230202 421
4.2%
20230203 364
3.6%
20230204 94
 
0.9%
20230205 80
 
0.8%
20230206 502
5.0%
20230207 320
3.2%
20230208 306
3.1%
20230209 311
3.1%
20230210 488
4.9%
ValueCountFrequency (%)
20230228 1321
13.2%
20230227 686
6.9%
20230226 188
 
1.9%
20230225 195
 
1.9%
20230224 541
5.4%
20230223 384
 
3.8%
20230222 374
 
3.7%
20230221 406
 
4.1%
20230220 494
 
4.9%
20230219 70
 
0.7%

금액
Real number (ℝ)

SKEWED 

Distinct3252
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean311056.87
Minimum-29271270
Maximum1.3608 × 108
Zeros20
Zeros (%)0.2%
Negative42
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:23:43.820827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-29271270
5-th percentile183.9
Q12720
median30000
Q3100000
95-th percentile1031680.8
Maximum1.3608 × 108
Range1.6535127 × 108
Interquartile range (IQR)97280

Descriptive statistics

Standard deviation2671187.1
Coefficient of variation (CV)8.5874557
Kurtosis1403.7922
Mean311056.87
Median Absolute Deviation (MAD)29080
Skewness32.676553
Sum3.1105687 × 109
Variance7.1352406 × 1012
MonotonicityNot monotonic
2024-05-11T02:23:44.112069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 607
 
6.1%
50000 569
 
5.7%
30000 553
 
5.5%
60000 176
 
1.8%
70000 165
 
1.7%
150000 161
 
1.6%
40000 149
 
1.5%
200000 137
 
1.4%
20000 131
 
1.3%
80000 131
 
1.3%
Other values (3242) 7221
72.2%
ValueCountFrequency (%)
-29271270 1
< 0.1%
-1180000 1
< 0.1%
-924200 1
< 0.1%
-450000 1
< 0.1%
-363636 1
< 0.1%
-350000 1
< 0.1%
-322560 1
< 0.1%
-302615 1
< 0.1%
-275800 1
< 0.1%
-218182 1
< 0.1%
ValueCountFrequency (%)
136080000 1
< 0.1%
115402350 1
< 0.1%
114922175 1
< 0.1%
54123077 1
< 0.1%
43217820 1
< 0.1%
41934000 1
< 0.1%
38148330 1
< 0.1%
38120000 1
< 0.1%
35751970 1
< 0.1%
35153455 1
< 0.1%

내용
Text

Distinct5914
Distinct (%)59.2%
Missing12
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:23:44.651088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length69
Mean length14.570985
Min length2

Characters and Unicode

Total characters145535
Distinct characters739
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5659 ?
Unique (%)56.7%

Sample

1st row관리비 연체료 수납
2nd row음식물키(105-1003)
3rd row12-503 음식물 카드
4th row상가유료주차비(8351 1/26~2/25)
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3605
 
13.2%
연체료 3460
 
12.7%
수납 3457
 
12.7%
승강기 421
 
1.5%
401
 
1.5%
2월분 382
 
1.4%
사용료 281
 
1.0%
승강기사용료 279
 
1.0%
2월 237
 
0.9%
1월분 210
 
0.8%
Other values (7735) 14548
53.3%
2024-05-11T02:23:45.694328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17729
 
12.2%
료 5867
 
4.0%
0 5502
 
3.8%
1 5394
 
3.7%
2 5309
 
3.6%
수 5000
 
3.4%
비 4280
 
2.9%
리 4130
 
2.8%
관 3803
 
2.6%
체 3684
 
2.5%
Other values (729) 84837
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89726
61.7%
Decimal Number 24311
 
16.7%
Space Separator 17729
 
12.2%
Other Punctuation 3620
 
2.5%
Close Punctuation 3100
 
2.1%
Open Punctuation 3086
 
2.1%
Dash Punctuation 2642
 
1.8%
Uppercase Letter 721
 
0.5%
Math Symbol 368
 
0.3%
Lowercase Letter 126
 
0.1%
Other values (4) 106
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5867
 
6.5%
수 5000
 
5.6%
비 4280
 
4.8%
리 4130
 
4.6%
관 3803
 
4.2%
체 3684
 
4.1%
연 3530
 
3.9%
납 3520
 
3.9%
용 2059
 
2.3%
사 1877
 
2.1%
Other values (638) 51976
57.9%
Uppercase Letter
ValueCountFrequency (%)
N 80
 
11.1%
T 62
 
8.6%
K 54
 
7.5%
B 49
 
6.8%
G 48
 
6.7%
A 46
 
6.4%
C 45
 
6.2%
L 45
 
6.2%
O 44
 
6.1%
D 35
 
4.9%
Other values (15) 213
29.5%
Lowercase Letter
ValueCountFrequency (%)
o 40
31.7%
n 12
 
9.5%
t 11
 
8.7%
k 10
 
7.9%
x 8
 
6.3%
c 5
 
4.0%
s 5
 
4.0%
e 5
 
4.0%
p 4
 
3.2%
b 4
 
3.2%
Other values (13) 22
17.5%
Other Punctuation
ValueCountFrequency (%)
/ 932
25.7%
. 906
25.0%
? 720
19.9%
, 647
17.9%
: 203
 
5.6%
* 95
 
2.6%
@ 45
 
1.2%
% 36
 
1.0%
# 13
 
0.4%
' 10
 
0.3%
Other values (5) 13
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 5502
22.6%
1 5394
22.2%
2 5309
21.8%
3 2489
10.2%
4 1406
 
5.8%
5 1114
 
4.6%
6 937
 
3.9%
7 827
 
3.4%
8 731
 
3.0%
9 602
 
2.5%
Math Symbol
ValueCountFrequency (%)
~ 299
81.2%
+ 27
 
7.3%
> 16
 
4.3%
< 9
 
2.4%
× 8
 
2.2%
= 7
 
1.9%
⇒ 1
 
0.3%
→ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3006
97.0%
] 94
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 2993
97.0%
[ 93
 
3.0%
Space Separator
ValueCountFrequency (%)
17729
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2642
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 101
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Number
ValueCountFrequency (%)
① 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89715
61.6%
Common 54961
37.8%
Latin 847
 
0.6%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5867
 
6.5%
수 5000
 
5.6%
비 4280
 
4.8%
리 4130
 
4.6%
관 3803
 
4.2%
체 3684
 
4.1%
연 3530
 
3.9%
납 3520
 
3.9%
용 2059
 
2.3%
사 1877
 
2.1%
Other values (636) 51965
57.9%
Latin
ValueCountFrequency (%)
N 80
 
9.4%
T 62
 
7.3%
K 54
 
6.4%
B 49
 
5.8%
G 48
 
5.7%
A 46
 
5.4%
C 45
 
5.3%
L 45
 
5.3%
O 44
 
5.2%
o 40
 
4.7%
Other values (38) 334
39.4%
Common
ValueCountFrequency (%)
17729
32.3%
0 5502
 
10.0%
1 5394
 
9.8%
2 5309
 
9.7%
) 3006
 
5.5%
( 2993
 
5.4%
- 2642
 
4.8%
3 2489
 
4.5%
4 1406
 
2.6%
5 1114
 
2.0%
Other values (32) 7377
13.4%
Han
ValueCountFrequency (%)
入 8
66.7%
人 2
 
16.7%
大 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89714
61.6%
ASCII 55796
38.3%
CJK 12
 
< 0.1%
None 10
 
< 0.1%
Arrows 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17729
31.8%
0 5502
 
9.9%
1 5394
 
9.7%
2 5309
 
9.5%
) 3006
 
5.4%
( 2993
 
5.4%
- 2642
 
4.7%
3 2489
 
4.5%
4 1406
 
2.5%
5 1114
 
2.0%
Other values (75) 8212
14.7%
Hangul
ValueCountFrequency (%)
료 5867
 
6.5%
수 5000
 
5.6%
비 4280
 
4.8%
리 4130
 
4.6%
관 3803
 
4.2%
체 3684
 
4.1%
연 3530
 
3.9%
납 3520
 
3.9%
용 2059
 
2.3%
사 1877
 
2.1%
Other values (635) 51964
57.9%
None
ValueCountFrequency (%)
× 8
80.0%
㈜ 1
 
10.0%
· 1
 
10.0%
CJK
ValueCountFrequency (%)
入 8
66.7%
人 2
 
16.7%
大 2
 
16.7%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
100.0%
Arrows
ValueCountFrequency (%)
⇒ 1
50.0%
→ 1
50.0%

Interactions

2024-05-11T02:23:38.640690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:23:38.103119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:23:38.907121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:23:38.365598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:23:45.859821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3400.301
년월일0.3401.0000.095
금액0.3010.0951.000
2024-05-11T02:23:46.111296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0470.134
금액0.0471.0000.132
비용명0.1340.1321.000

Missing values

2024-05-11T02:23:39.234702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:23:39.597789image/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
5349반포써밋A10026015연체료수익202302086310관리비 연체료 수납
21394래미안하이리버A13380302잡수익202302153300음식물키(105-1003)
33691가락프라자A13881204잡수익20230202200012-503 음식물 카드
42773양평한신A15010502주차장수익2023021420000상가유료주차비(8351 1/26~2/25)
53729목동12단지A15807706연체료수익202302141880관리비 연체료 수납
17896중화한신아파트A13187702연체료수익202302275580관리비 연체료 수납
37258월계대우아파트A13985103잡수익2023020330000게시물(윌쌤영어)
46457구로대성스카이렉스A15284302임대료수익20230201250000태양상사 창고임대료
6612래미안용산아파트A10026922잡수익20230227350000세차수입(2월)
54937은평뉴타운우물골6단지A41279917잡수익2023021025001월 관리실 산재보험 할인
아파트명아파트코드비용명년월일금액내용
26289압구정현대아파트A13589802승강기수익2023022420000승강기 사용료(81-1208)
45968천왕이펜하우스1단지A15213006연체료수익20230226160관리비 연체료 수납
19949왕십리풍림아이원A13302206기타운영수익2023021760000운동시설이용료(조규진) : 골프 1개월, 락카룸이용료
26144래미안도곡카운티A13585404주차장수익2023021316745외부주차수입11건
33456가락우성1차A13880406이자수익202302092895527장기수선충당예치금만기이자발생
33721거여현대3차A13881302광고료수익2023022830000게시판 광고 (1주)
37697중계그린A13986306승강기수익2023022745455인테리어공사 승강기 사용료(108동 306호 대동인테리어)
7393센트라스A10027289잡수익20230215280신한은행 체크카드 법인포인트 입금
53736목동12단지A15807706기타운영수익20230217240000독서실 월권(40,000*6건)
31948오금현대아파트A13813010연체료수익202302121140관리비 연체료 수납