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 = 39.39268542)Skewed

Reproduction

Analysis started2024-05-11 02:32:23.933959
Analysis finished2024-05-11 02:32:27.623173
Duration3.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2167
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:32:28.017515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length7.3085
Min length2

Characters and Unicode

Total characters73085
Distinct characters434
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

Unique229 ?
Unique (%)2.3%

Sample

1st row돈의문센트레빌
2nd row용산CJ나인파크
3rd row강남한양수자인
4th row광장동금호베스트빌
5th row삼성동센트럴아이파크
ValueCountFrequency (%)
아파트 174
 
1.6%
래미안 47
 
0.4%
아이파크 32
 
0.3%
은마 25
 
0.2%
힐스테이트 23
 
0.2%
마포래미안푸르지오 22
 
0.2%
e편한세상 22
 
0.2%
고덕 20
 
0.2%
월계그랑빌 19
 
0.2%
신동아아파트 18
 
0.2%
Other values (2229) 10322
96.3%
2024-05-11T02:32:29.466570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2666
 
3.6%
파 2538
 
3.5%
트 2412
 
3.3%
지 1929
 
2.6%
대 1728
 
2.4%
동 1631
 
2.2%
단 1539
 
2.1%
이 1425
 
1.9%
신 1423
 
1.9%
차 1319
 
1.8%
Other values (424) 54475
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66849
91.5%
Decimal Number 3699
 
5.1%
Space Separator 843
 
1.2%
Uppercase Letter 800
 
1.1%
Lowercase Letter 306
 
0.4%
Other Punctuation 163
 
0.2%
Open Punctuation 151
 
0.2%
Close Punctuation 151
 
0.2%
Dash Punctuation 111
 
0.2%
Letter Number 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2666
 
4.0%
파 2538
 
3.8%
트 2412
 
3.6%
지 1929
 
2.9%
대 1728
 
2.6%
동 1631
 
2.4%
단 1539
 
2.3%
이 1425
 
2.1%
신 1423
 
2.1%
차 1319
 
2.0%
Other values (379) 48239
72.2%
Uppercase Letter
ValueCountFrequency (%)
S 139
17.4%
K 114
14.2%
C 107
13.4%
M 75
9.4%
D 75
9.4%
H 52
 
6.5%
L 49
 
6.1%
I 33
 
4.1%
A 29
 
3.6%
E 27
 
3.4%
Other values (7) 100
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 180
58.8%
l 26
 
8.5%
i 22
 
7.2%
s 21
 
6.9%
k 16
 
5.2%
v 13
 
4.2%
h 8
 
2.6%
c 6
 
2.0%
a 5
 
1.6%
g 5
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 1142
30.9%
2 1051
28.4%
3 471
12.7%
4 256
 
6.9%
5 218
 
5.9%
6 165
 
4.5%
9 120
 
3.2%
7 106
 
2.9%
8 88
 
2.4%
0 82
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 148
90.8%
. 15
 
9.2%
Space Separator
ValueCountFrequency (%)
843
100.0%
Open Punctuation
ValueCountFrequency (%)
( 151
100.0%
Close Punctuation
ValueCountFrequency (%)
) 151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66849
91.5%
Common 5118
 
7.0%
Latin 1118
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2666
 
4.0%
파 2538
 
3.8%
트 2412
 
3.6%
지 1929
 
2.9%
대 1728
 
2.6%
동 1631
 
2.4%
단 1539
 
2.3%
이 1425
 
2.1%
신 1423
 
2.1%
차 1319
 
2.0%
Other values (379) 48239
72.2%
Latin
ValueCountFrequency (%)
e 180
16.1%
S 139
12.4%
K 114
10.2%
C 107
9.6%
M 75
 
6.7%
D 75
 
6.7%
H 52
 
4.7%
L 49
 
4.4%
I 33
 
3.0%
A 29
 
2.6%
Other values (19) 265
23.7%
Common
ValueCountFrequency (%)
1 1142
22.3%
2 1051
20.5%
843
16.5%
3 471
9.2%
4 256
 
5.0%
5 218
 
4.3%
6 165
 
3.2%
( 151
 
3.0%
) 151
 
3.0%
, 148
 
2.9%
Other values (6) 522
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66849
91.5%
ASCII 6224
 
8.5%
Number Forms 12
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2666
 
4.0%
파 2538
 
3.8%
트 2412
 
3.6%
지 1929
 
2.9%
대 1728
 
2.6%
동 1631
 
2.4%
단 1539
 
2.3%
이 1425
 
2.1%
신 1423
 
2.1%
차 1319
 
2.0%
Other values (379) 48239
72.2%
ASCII
ValueCountFrequency (%)
1 1142
18.3%
2 1051
16.9%
843
13.5%
3 471
 
7.6%
4 256
 
4.1%
5 218
 
3.5%
e 180
 
2.9%
6 165
 
2.7%
( 151
 
2.4%
) 151
 
2.4%
Other values (34) 1596
25.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 12
100.0%

아파트코드
Text

Distinct2173
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:32:30.950454image/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

Unique231 ?
Unique (%)2.3%

Sample

1st rowA12070101
2nd rowA14010003
3rd rowA13520002
4th rowA14381504
5th rowA10026350
ValueCountFrequency (%)
a13583507 25
 
0.2%
a12175203 22
 
0.2%
a13984004 19
 
0.2%
a13879102 18
 
0.2%
a13003007 18
 
0.2%
a14272304 18
 
0.2%
a12179004 18
 
0.2%
a14320304 16
 
0.2%
a14272305 16
 
0.2%
a10078901 16
 
0.2%
Other values (2163) 9814
98.1%
2024-05-11T02:32:32.673295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18635
20.7%
1 17110
19.0%
A 9992
11.1%
3 8835
9.8%
2 8170
9.1%
5 6438
 
7.2%
8 5564
 
6.2%
7 4932
 
5.5%
4 4018
 
4.5%
6 3386
 
3.8%
Other values (2) 2920
 
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 18635
23.3%
1 17110
21.4%
3 8835
11.0%
2 8170
10.2%
5 6438
 
8.0%
8 5564
 
7.0%
7 4932
 
6.2%
4 4018
 
5.0%
6 3386
 
4.2%
9 2912
 
3.6%
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 18635
23.3%
1 17110
21.4%
3 8835
11.0%
2 8170
10.2%
5 6438
 
8.0%
8 5564
 
7.0%
7 4932
 
6.2%
4 4018
 
5.0%
6 3386
 
4.2%
9 2912
 
3.6%
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 18635
20.7%
1 17110
19.0%
A 9992
11.1%
3 8835
9.8%
2 8170
9.1%
5 6438
 
7.2%
8 5564
 
6.2%
7 4932
 
5.5%
4 4018
 
4.5%
6 3386
 
3.8%
Other values (2) 2920
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3479 
승강기수익
1244 
잡수익
989 
광고료수익
885 
주차장수익
837 
Other values (10)
2566 

Length

Max length9
Median length5
Mean length5.033
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주차장수익
2nd row잡수익
3rd row승강기수익
4th row검침수익
5th row승강기수익

Common Values

ValueCountFrequency (%)
연체료수익 3479
34.8%
승강기수익 1244
 
12.4%
잡수익 989
 
9.9%
광고료수익 885
 
8.8%
주차장수익 837
 
8.4%
기타운영수익 641
 
6.4%
고용안정사업수익 513
 
5.1%
검침수익 320
 
3.2%
알뜰시장수익 283
 
2.8%
임대료수익 215
 
2.1%
Other values (5) 594
 
5.9%

Length

2024-05-11T02:32:33.363433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3479
34.8%
승강기수익 1244
 
12.4%
잡수익 989
 
9.9%
광고료수익 885
 
8.8%
주차장수익 837
 
8.4%
기타운영수익 641
 
6.4%
고용안정사업수익 513
 
5.1%
검침수익 320
 
3.2%
알뜰시장수익 283
 
2.8%
임대료수익 215
 
2.1%
Other values (5) 594
 
5.9%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210417
Minimum20210401
Maximum20210430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:32:33.885629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210401
5-th percentile20210402
Q120210409
median20210419
Q320210426
95-th percentile20210430
Maximum20210430
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.3774174
Coefficient of variation (CV)4.639893 × 10-7
Kurtosis-1.2359408
Mean20210417
Median Absolute Deviation (MAD)8
Skewness-0.24408072
Sum2.0210417 × 1011
Variance87.935957
MonotonicityNot monotonic
2024-05-11T02:32:34.388157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20210430 1083
 
10.8%
20210415 512
 
5.1%
20210429 492
 
4.9%
20210426 490
 
4.9%
20210401 489
 
4.9%
20210419 460
 
4.6%
20210412 452
 
4.5%
20210420 446
 
4.5%
20210405 436
 
4.4%
20210428 426
 
4.3%
Other values (20) 4714
47.1%
ValueCountFrequency (%)
20210401 489
4.9%
20210402 371
3.7%
20210403 91
 
0.9%
20210404 77
 
0.8%
20210405 436
4.4%
20210406 322
3.2%
20210407 292
2.9%
20210408 290
2.9%
20210409 346
3.5%
20210410 70
 
0.7%
ValueCountFrequency (%)
20210430 1083
10.8%
20210429 492
4.9%
20210428 426
 
4.3%
20210427 410
 
4.1%
20210426 490
4.9%
20210425 172
 
1.7%
20210424 148
 
1.5%
20210423 425
 
4.2%
20210422 358
 
3.6%
20210421 351
 
3.5%

금액
Real number (ℝ)

SKEWED 

Distinct3261
Distinct (%)32.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246090.17
Minimum-4485370
Maximum1.1305849 × 108
Zeros10
Zeros (%)0.1%
Negative43
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:32:34.968853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4485370
5-th percentile180
Q13260
median30000
Q3100000
95-th percentile881104.95
Maximum1.1305849 × 108
Range1.1754386 × 108
Interquartile range (IQR)96740

Descriptive statistics

Standard deviation1648306.8
Coefficient of variation (CV)6.697979
Kurtosis2348.7501
Mean246090.17
Median Absolute Deviation (MAD)29206
Skewness39.392685
Sum2.4609017 × 109
Variance2.7169153 × 1012
MonotonicityNot monotonic
2024-05-11T02:32:35.503314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 603
 
6.0%
30000 596
 
6.0%
100000 561
 
5.6%
150000 187
 
1.9%
200000 170
 
1.7%
60000 156
 
1.6%
70000 154
 
1.5%
40000 134
 
1.3%
80000 116
 
1.2%
120000 100
 
1.0%
Other values (3251) 7223
72.2%
ValueCountFrequency (%)
-4485370 1
< 0.1%
-3218770 1
< 0.1%
-1800000 1
< 0.1%
-1622516 1
< 0.1%
-1476000 1
< 0.1%
-1120000 1
< 0.1%
-620600 1
< 0.1%
-550000 1
< 0.1%
-534000 1
< 0.1%
-509545 1
< 0.1%
ValueCountFrequency (%)
113058490 1
< 0.1%
52000000 1
< 0.1%
31500000 1
< 0.1%
31000000 1
< 0.1%
27268000 1
< 0.1%
24862200 1
< 0.1%
24627900 1
< 0.1%
24265330 1
< 0.1%
21406070 1
< 0.1%
18710000 1
< 0.1%

내용
Text

Distinct5872
Distinct (%)58.8%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:32:36.369715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length64
Mean length14.207287
Min length1

Characters and Unicode

Total characters141945
Distinct characters719
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5618 ?
Unique (%)56.2%

Sample

1st row4월분 주차비 부과
2nd row게시판광고
3rd row418-402호 승강기사용료
4th row한전검침(한전광진성동지점)
5th row301-2002호 승강기 사용료/전출(04/26)
ValueCountFrequency (%)
관리비 3617
 
13.8%
수납 3485
 
13.3%
연체료 3483
 
13.2%
승강기 369
 
1.4%
4월분 332
 
1.3%
277
 
1.1%
3월분 272
 
1.0%
승강기사용료 261
 
1.0%
입금 248
 
0.9%
사용료 243
 
0.9%
Other values (7439) 13708
52.1%
2024-05-11T02:32:37.909698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16406
 
11.6%
료 5609
 
4.0%
0 5017
 
3.5%
수 4934
 
3.5%
리 4901
 
3.5%
1 4767
 
3.4%
비 4416
 
3.1%
관 3833
 
2.7%
체 3698
 
2.6%
납 3552
 
2.5%
Other values (709) 84812
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90854
64.0%
Decimal Number 21831
 
15.4%
Space Separator 16406
 
11.6%
Close Punctuation 3164
 
2.2%
Open Punctuation 3142
 
2.2%
Other Punctuation 2997
 
2.1%
Dash Punctuation 2415
 
1.7%
Uppercase Letter 613
 
0.4%
Math Symbol 308
 
0.2%
Lowercase Letter 145
 
0.1%
Other values (3) 70
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5609
 
6.2%
수 4934
 
5.4%
리 4901
 
5.4%
비 4416
 
4.9%
관 3833
 
4.2%
체 3698
 
4.1%
납 3552
 
3.9%
연 3541
 
3.9%
사 1945
 
2.1%
월 1845
 
2.0%
Other values (620) 52580
57.9%
Uppercase Letter
ValueCountFrequency (%)
N 83
13.5%
K 47
 
7.7%
O 44
 
7.2%
B 42
 
6.9%
L 41
 
6.7%
E 38
 
6.2%
T 38
 
6.2%
C 36
 
5.9%
A 33
 
5.4%
S 31
 
5.1%
Other values (16) 180
29.4%
Lowercase Letter
ValueCountFrequency (%)
o 37
25.5%
x 13
 
9.0%
s 13
 
9.0%
k 12
 
8.3%
e 12
 
8.3%
t 8
 
5.5%
c 7
 
4.8%
n 7
 
4.8%
b 5
 
3.4%
r 5
 
3.4%
Other values (11) 26
17.9%
Other Punctuation
ValueCountFrequency (%)
/ 827
27.6%
, 766
25.6%
. 742
24.8%
: 207
 
6.9%
* 184
 
6.1%
? 179
 
6.0%
@ 33
 
1.1%
% 24
 
0.8%
# 17
 
0.6%
& 7
 
0.2%
Other values (3) 11
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 5017
23.0%
1 4767
21.8%
2 3225
14.8%
4 2479
11.4%
3 2374
10.9%
5 1315
 
6.0%
6 778
 
3.6%
7 675
 
3.1%
8 634
 
2.9%
9 567
 
2.6%
Math Symbol
ValueCountFrequency (%)
~ 251
81.5%
+ 19
 
6.2%
> 12
 
3.9%
= 10
 
3.2%
× 9
 
2.9%
→ 3
 
1.0%
< 2
 
0.6%
⇒ 1
 
0.3%
÷ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3081
97.4%
] 83
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 3062
97.5%
[ 80
 
2.5%
Other Number
ValueCountFrequency (%)
⑦ 1
50.0%
③ 1
50.0%
Space Separator
ValueCountFrequency (%)
16406
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2415
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 67
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90850
64.0%
Common 50333
35.5%
Latin 758
 
0.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5609
 
6.2%
수 4934
 
5.4%
리 4901
 
5.4%
비 4416
 
4.9%
관 3833
 
4.2%
체 3698
 
4.1%
납 3552
 
3.9%
연 3541
 
3.9%
사 1945
 
2.1%
월 1845
 
2.0%
Other values (618) 52576
57.9%
Latin
ValueCountFrequency (%)
N 83
 
10.9%
K 47
 
6.2%
O 44
 
5.8%
B 42
 
5.5%
L 41
 
5.4%
E 38
 
5.0%
T 38
 
5.0%
o 37
 
4.9%
C 36
 
4.7%
A 33
 
4.4%
Other values (37) 319
42.1%
Common
ValueCountFrequency (%)
16406
32.6%
0 5017
 
10.0%
1 4767
 
9.5%
2 3225
 
6.4%
) 3081
 
6.1%
( 3062
 
6.1%
4 2479
 
4.9%
- 2415
 
4.8%
3 2374
 
4.7%
5 1315
 
2.6%
Other values (32) 6192
 
12.3%
Han
ValueCountFrequency (%)
入 3
75.0%
內 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90849
64.0%
ASCII 51075
36.0%
None 10
 
< 0.1%
Arrows 4
 
< 0.1%
CJK 4
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16406
32.1%
0 5017
 
9.8%
1 4767
 
9.3%
2 3225
 
6.3%
) 3081
 
6.0%
( 3062
 
6.0%
4 2479
 
4.9%
- 2415
 
4.7%
3 2374
 
4.6%
5 1315
 
2.6%
Other values (73) 6934
13.6%
Hangul
ValueCountFrequency (%)
료 5609
 
6.2%
수 4934
 
5.4%
리 4901
 
5.4%
비 4416
 
4.9%
관 3833
 
4.2%
체 3698
 
4.1%
납 3552
 
3.9%
연 3541
 
3.9%
사 1945
 
2.1%
월 1845
 
2.0%
Other values (617) 52575
57.9%
None
ValueCountFrequency (%)
× 9
90.0%
÷ 1
 
10.0%
Arrows
ValueCountFrequency (%)
→ 3
75.0%
⇒ 1
 
25.0%
CJK
ValueCountFrequency (%)
入 3
75.0%
內 1
 
25.0%
Enclosed Alphanum
ValueCountFrequency (%)
⑦ 1
50.0%
③ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㅋ 1
100.0%

Interactions

2024-05-11T02:32:26.319347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:25.736520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:26.618888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:26.044246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:32:38.167875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3860.137
년월일0.3861.0000.025
금액0.1370.0251.000
2024-05-11T02:32:38.491706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0390.152
금액0.0391.0000.064
비용명0.1520.0641.000

Missing values

2024-05-11T02:32:27.053197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:32:27.488643image/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
9679돈의문센트레빌A12070101주차장수익2021043027000004월분 주차비 부과
43232용산CJ나인파크A14010003잡수익2021042730000게시판광고
26125강남한양수자인A13520002승강기수익20210401110000418-402호 승강기사용료
45798광장동금호베스트빌A14381504검침수익20210420100630한전검침(한전광진성동지점)
4052삼성동센트럴아이파크A10026350승강기수익20210408100000301-2002호 승강기 사용료/전출(04/26)
3857롯데캐슬노블레스A10026180연체료수익202104291900관리비 연체료 수납
10049북아현두산A12079501승강기수익202104022000001-1706 공사
24437길동현대아파트A13480803검침수익20210422109780한전 검침비
37029송파현대1차A13885301잡수익20210427100000승강기사용료(101-1203공사)
53347신도림동아1차A15288813검침수익20210405470845한전검침수당
아파트명아파트코드비용명년월일금액내용
27571개포현대3차A13580001연체료수익202104282130관리비 연체료 수납
58272마곡엠밸리15단지A15728011잡수익2021041420001502-303 / 주차스티커 미반납 입금
26656역삼삼익A13527006연체료수익20210429840관리비 연체료 수납
47199신대림한솔솔파크A15007002기타운영수익20210413700팩스
23232대우한강베네시티A13402003고용안정사업수익2021041649030일자리안정지원금
60377목동부영그린타운2차A15805501검침수익20210423100220한전검침수당 입금
35195문정래미안A13820006검침수익20210422729280한전검침대행수수료
56526상도동중앙하이츠빌아파트A15683402연체료수익202104301250관리비 연체료 수납
25157역삼아이파크A13508009이자수익20210408843869장충금(국민-정기예금) 만기해약이자수입
8091중림삼성사이버빌리지A10085903승강기수익20210420120000승강기사용료(106-1801호,전입)