Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells11
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 = 64.19779349)Skewed

Reproduction

Analysis started2024-05-11 02:31:14.702722
Analysis finished2024-05-11 02:31:17.711343
Duration3.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2152
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:31:17.951465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.3629
Min length2

Characters and Unicode

Total characters73629
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

Unique215 ?
Unique (%)2.1%

Sample

1st row효창파크푸르지오
2nd row강변아파트
3rd row상암월드컵파크7단지
4th row방화2단지
5th row관악동부센트레빌
ValueCountFrequency (%)
아파트 177
 
1.6%
래미안 52
 
0.5%
아이파크 38
 
0.4%
sk뷰 23
 
0.2%
고덕 23
 
0.2%
상계주공7단지 23
 
0.2%
e편한세상 21
 
0.2%
힐스테이트 21
 
0.2%
잠실리센츠 19
 
0.2%
마포래미안푸르지오 19
 
0.2%
Other values (2222) 10367
96.1%
2024-05-11T02:31:18.758601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2513
 
3.4%
파 2450
 
3.3%
트 2394
 
3.3%
지 2028
 
2.8%
대 1638
 
2.2%
단 1625
 
2.2%
동 1574
 
2.1%
이 1431
 
1.9%
신 1386
 
1.9%
차 1293
 
1.8%
Other values (424) 55297
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67192
91.3%
Decimal Number 3705
 
5.0%
Space Separator 913
 
1.2%
Uppercase Letter 849
 
1.2%
Lowercase Letter 347
 
0.5%
Close Punctuation 166
 
0.2%
Open Punctuation 166
 
0.2%
Other Punctuation 153
 
0.2%
Dash Punctuation 129
 
0.2%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2513
 
3.7%
파 2450
 
3.6%
트 2394
 
3.6%
지 2028
 
3.0%
대 1638
 
2.4%
단 1625
 
2.4%
동 1574
 
2.3%
이 1431
 
2.1%
신 1386
 
2.1%
차 1293
 
1.9%
Other values (379) 48860
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 153
18.0%
K 123
14.5%
C 107
12.6%
H 60
 
7.1%
M 60
 
7.1%
D 60
 
7.1%
L 54
 
6.4%
I 43
 
5.1%
E 40
 
4.7%
A 37
 
4.4%
Other values (7) 112
13.2%
Lowercase Letter
ValueCountFrequency (%)
e 193
55.6%
l 30
 
8.6%
s 28
 
8.1%
k 25
 
7.2%
i 22
 
6.3%
v 17
 
4.9%
c 14
 
4.0%
h 10
 
2.9%
w 6
 
1.7%
g 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 1122
30.3%
2 1010
27.3%
3 493
13.3%
4 280
 
7.6%
5 239
 
6.5%
6 164
 
4.4%
7 143
 
3.9%
9 106
 
2.9%
8 76
 
2.1%
0 72
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 130
85.0%
. 23
 
15.0%
Space Separator
ValueCountFrequency (%)
913
100.0%
Close Punctuation
ValueCountFrequency (%)
) 166
100.0%
Open Punctuation
ValueCountFrequency (%)
( 166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67192
91.3%
Common 5232
 
7.1%
Latin 1205
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2513
 
3.7%
파 2450
 
3.6%
트 2394
 
3.6%
지 2028
 
3.0%
대 1638
 
2.4%
단 1625
 
2.4%
동 1574
 
2.3%
이 1431
 
2.1%
신 1386
 
2.1%
차 1293
 
1.9%
Other values (379) 48860
72.7%
Latin
ValueCountFrequency (%)
e 193
16.0%
S 153
12.7%
K 123
 
10.2%
C 107
 
8.9%
H 60
 
5.0%
M 60
 
5.0%
D 60
 
5.0%
L 54
 
4.5%
I 43
 
3.6%
E 40
 
3.3%
Other values (19) 312
25.9%
Common
ValueCountFrequency (%)
1 1122
21.4%
2 1010
19.3%
913
17.5%
3 493
9.4%
4 280
 
5.4%
5 239
 
4.6%
) 166
 
3.2%
( 166
 
3.2%
6 164
 
3.1%
7 143
 
2.7%
Other values (6) 536
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67192
91.3%
ASCII 6428
 
8.7%
Number Forms 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2513
 
3.7%
파 2450
 
3.6%
트 2394
 
3.6%
지 2028
 
3.0%
대 1638
 
2.4%
단 1625
 
2.4%
동 1574
 
2.3%
이 1431
 
2.1%
신 1386
 
2.1%
차 1293
 
1.9%
Other values (379) 48860
72.7%
ASCII
ValueCountFrequency (%)
1 1122
17.5%
2 1010
15.7%
913
14.2%
3 493
 
7.7%
4 280
 
4.4%
5 239
 
3.7%
e 193
 
3.0%
) 166
 
2.6%
( 166
 
2.6%
6 164
 
2.6%
Other values (34) 1682
26.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

아파트코드
Text

Distinct2157
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:31:19.315717image/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

Unique216 ?
Unique (%)2.2%

Sample

1st rowA14074101
2nd rowA13790714
3rd rowA12127005
4th rowA15722314
5th rowA15192201
ValueCountFrequency (%)
a13982704 23
 
0.2%
a12179004 19
 
0.2%
a12175203 19
 
0.2%
a10025461 19
 
0.2%
a13822003 19
 
0.2%
a13583507 18
 
0.2%
a13822004 16
 
0.2%
a13704104 16
 
0.2%
a14272304 15
 
0.1%
a10026988 15
 
0.1%
Other values (2147) 9821
98.2%
2024-05-11T02:31:20.373107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18651
20.7%
1 17224
19.1%
A 9992
11.1%
3 8811
9.8%
2 8204
9.1%
5 6340
 
7.0%
8 5495
 
6.1%
7 4925
 
5.5%
4 4036
 
4.5%
6 3317
 
3.7%
Other values (2) 3005
 
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 18651
23.3%
1 17224
21.5%
3 8811
11.0%
2 8204
10.3%
5 6340
 
7.9%
8 5495
 
6.9%
7 4925
 
6.2%
4 4036
 
5.0%
6 3317
 
4.1%
9 2997
 
3.7%
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 18651
23.3%
1 17224
21.5%
3 8811
11.0%
2 8204
10.3%
5 6340
 
7.9%
8 5495
 
6.9%
7 4925
 
6.2%
4 4036
 
5.0%
6 3317
 
4.1%
9 2997
 
3.7%
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 18651
20.7%
1 17224
19.1%
A 9992
11.1%
3 8811
9.8%
2 8204
9.1%
5 6340
 
7.0%
8 5495
 
6.1%
7 4925
 
5.5%
4 4036
 
4.5%
6 3317
 
3.7%
Other values (2) 3005
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3552 
승강기수익
1179 
잡수익
1008 
주차장수익
924 
광고료수익
806 
Other values (10)
2531 

Length

Max length9
Median length5
Mean length5.0285
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row잡수익
2nd row광고료수익
3rd row연체료수익
4th row알뜰시장수익
5th row연체료수익

Common Values

ValueCountFrequency (%)
연체료수익 3552
35.5%
승강기수익 1179
 
11.8%
잡수익 1008
 
10.1%
주차장수익 924
 
9.2%
광고료수익 806
 
8.1%
기타운영수익 676
 
6.8%
고용안정사업수익 522
 
5.2%
검침수익 328
 
3.3%
임대료수익 238
 
2.4%
재활용품수익 209
 
2.1%
Other values (5) 558
 
5.6%

Length

2024-05-11T02:31:20.884375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3552
35.5%
승강기수익 1179
 
11.8%
잡수익 1008
 
10.1%
주차장수익 924
 
9.2%
광고료수익 806
 
8.1%
기타운영수익 676
 
6.8%
고용안정사업수익 522
 
5.2%
검침수익 328
 
3.3%
임대료수익 238
 
2.4%
재활용품수익 209
 
2.1%
Other values (5) 558
 
5.6%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210817
Minimum20210801
Maximum20210831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:31:21.212316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210801
5-th percentile20210802
Q120210809
median20210818
Q320210826
95-th percentile20210831
Maximum20210831
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.7941289
Coefficient of variation (CV)4.8459836 × 10-7
Kurtosis-1.3181549
Mean20210817
Median Absolute Deviation (MAD)8
Skewness-0.15237704
Sum2.0210817 × 1011
Variance95.92496
MonotonicityNot monotonic
2024-05-11T02:31:21.615380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210831 1074
 
10.7%
20210802 588
 
5.9%
20210830 554
 
5.5%
20210825 547
 
5.5%
20210810 480
 
4.8%
20210818 459
 
4.6%
20210813 437
 
4.4%
20210817 428
 
4.3%
20210826 404
 
4.0%
20210823 403
 
4.0%
Other values (21) 4626
46.3%
ValueCountFrequency (%)
20210801 177
 
1.8%
20210802 588
5.9%
20210803 400
4.0%
20210804 310
3.1%
20210805 371
3.7%
20210806 266
2.7%
20210807 79
 
0.8%
20210808 54
 
0.5%
20210809 352
3.5%
20210810 480
4.8%
ValueCountFrequency (%)
20210831 1074
10.7%
20210830 554
5.5%
20210829 142
 
1.4%
20210828 127
 
1.3%
20210827 350
 
3.5%
20210826 404
 
4.0%
20210825 547
5.5%
20210824 395
 
4.0%
20210823 403
 
4.0%
20210822 60
 
0.6%

금액
Real number (ℝ)

SKEWED 

Distinct3181
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245725.95
Minimum-10692000
Maximum1.878 × 108
Zeros15
Zeros (%)0.1%
Negative43
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:31:22.061444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10692000
5-th percentile170.95
Q12727
median30000
Q3100000
95-th percentile870000
Maximum1.878 × 108
Range1.98492 × 108
Interquartile range (IQR)97273

Descriptive statistics

Standard deviation2207747.9
Coefficient of variation (CV)8.984594
Kurtosis5257.4771
Mean245725.95
Median Absolute Deviation (MAD)29300
Skewness64.197793
Sum2.4572595 × 109
Variance4.8741509 × 1012
MonotonicityNot monotonic
2024-05-11T02:31:22.720258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 567
 
5.7%
100000 546
 
5.5%
30000 496
 
5.0%
150000 192
 
1.9%
200000 183
 
1.8%
70000 162
 
1.6%
60000 148
 
1.5%
40000 139
 
1.4%
80000 130
 
1.3%
20000 100
 
1.0%
Other values (3171) 7337
73.4%
ValueCountFrequency (%)
-10692000 1
< 0.1%
-6200000 1
< 0.1%
-3224100 1
< 0.1%
-1514182 1
< 0.1%
-1000000 1
< 0.1%
-862400 1
< 0.1%
-793800 1
< 0.1%
-491940 1
< 0.1%
-450000 1
< 0.1%
-390000 1
< 0.1%
ValueCountFrequency (%)
187800000 1
< 0.1%
52500000 1
< 0.1%
36180600 1
< 0.1%
27872000 1
< 0.1%
27215000 1
< 0.1%
23980000 1
< 0.1%
23295424 1
< 0.1%
18833790 1
< 0.1%
16960000 1
< 0.1%
14870000 1
< 0.1%

내용
Text

Distinct5775
Distinct (%)57.8%
Missing11
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:31:23.415649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length62
Mean length14.121133
Min length2

Characters and Unicode

Total characters141056
Distinct characters705
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5523 ?
Unique (%)55.3%

Sample

1st row성실종합자원미수금 차액분 잡수입 전환
2nd row제니스 잉글리쉬 광고게시 2주
3rd row관리비 연체료 수납
4th row8월분 알뜰장사용료 입금
5th row관리비 연체료 수납
ValueCountFrequency (%)
관리비 3668
 
13.8%
수납 3559
 
13.4%
연체료 3557
 
13.4%
승강기 402
 
1.5%
8월분 378
 
1.4%
7월분 301
 
1.1%
승강기사용료 278
 
1.0%
사용료 275
 
1.0%
입금 262
 
1.0%
251
 
0.9%
Other values (7219) 13629
51.3%
2024-05-11T02:31:24.437881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16679
 
11.8%
료 5756
 
4.1%
0 4996
 
3.5%
리 4973
 
3.5%
수 4950
 
3.5%
1 4688
 
3.3%
비 4557
 
3.2%
관 3933
 
2.8%
체 3748
 
2.7%
연 3634
 
2.6%
Other values (695) 83142
58.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90509
64.2%
Decimal Number 21623
 
15.3%
Space Separator 16679
 
11.8%
Close Punctuation 3017
 
2.1%
Open Punctuation 3006
 
2.1%
Other Punctuation 2690
 
1.9%
Dash Punctuation 2338
 
1.7%
Uppercase Letter 674
 
0.5%
Math Symbol 294
 
0.2%
Lowercase Letter 131
 
0.1%
Other values (2) 95
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5756
 
6.4%
리 4973
 
5.5%
수 4950
 
5.5%
비 4557
 
5.0%
관 3933
 
4.3%
체 3748
 
4.1%
연 3634
 
4.0%
납 3614
 
4.0%
월 1874
 
2.1%
사 1853
 
2.0%
Other values (612) 51617
57.0%
Uppercase Letter
ValueCountFrequency (%)
N 77
11.4%
B 59
 
8.8%
C 55
 
8.2%
T 50
 
7.4%
O 46
 
6.8%
K 44
 
6.5%
A 42
 
6.2%
L 39
 
5.8%
M 36
 
5.3%
S 34
 
5.0%
Other values (15) 192
28.5%
Lowercase Letter
ValueCountFrequency (%)
o 40
30.5%
x 15
 
11.5%
k 13
 
9.9%
t 10
 
7.6%
n 9
 
6.9%
e 8
 
6.1%
s 6
 
4.6%
l 5
 
3.8%
c 5
 
3.8%
p 3
 
2.3%
Other values (8) 17
13.0%
Other Punctuation
ValueCountFrequency (%)
. 780
29.0%
, 726
27.0%
/ 697
25.9%
: 182
 
6.8%
* 161
 
6.0%
? 47
 
1.7%
@ 39
 
1.4%
% 20
 
0.7%
& 10
 
0.4%
' 9
 
0.3%
Other values (4) 19
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 4996
23.1%
1 4688
21.7%
2 3061
14.2%
8 2052
9.5%
3 1552
 
7.2%
7 1413
 
6.5%
4 1199
 
5.5%
5 1036
 
4.8%
6 855
 
4.0%
9 771
 
3.6%
Math Symbol
ValueCountFrequency (%)
~ 255
86.7%
+ 13
 
4.4%
× 10
 
3.4%
> 6
 
2.0%
= 5
 
1.7%
< 4
 
1.4%
→ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2938
97.4%
] 79
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 2929
97.4%
[ 77
 
2.6%
Other Symbol
ValueCountFrequency (%)
☞ 1
50.0%
㎡ 1
50.0%
Space Separator
ValueCountFrequency (%)
16679
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2338
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90504
64.2%
Common 49742
35.3%
Latin 805
 
0.6%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5756
 
6.4%
리 4973
 
5.5%
수 4950
 
5.5%
비 4557
 
5.0%
관 3933
 
4.3%
체 3748
 
4.1%
연 3634
 
4.0%
납 3614
 
4.0%
월 1874
 
2.1%
사 1853
 
2.0%
Other values (610) 51612
57.0%
Latin
ValueCountFrequency (%)
N 77
 
9.6%
B 59
 
7.3%
C 55
 
6.8%
T 50
 
6.2%
O 46
 
5.7%
K 44
 
5.5%
A 42
 
5.2%
o 40
 
5.0%
L 39
 
4.8%
M 36
 
4.5%
Other values (33) 317
39.4%
Common
ValueCountFrequency (%)
16679
33.5%
0 4996
 
10.0%
1 4688
 
9.4%
2 3061
 
6.2%
) 2938
 
5.9%
( 2929
 
5.9%
- 2338
 
4.7%
8 2052
 
4.1%
3 1552
 
3.1%
7 1413
 
2.8%
Other values (30) 7096
14.3%
Han
ValueCountFrequency (%)
入 4
80.0%
內 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90503
64.2%
ASCII 50532
35.8%
None 12
 
< 0.1%
CJK 5
 
< 0.1%
Arrows 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%
CJK Compat 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16679
33.0%
0 4996
 
9.9%
1 4688
 
9.3%
2 3061
 
6.1%
) 2938
 
5.8%
( 2929
 
5.8%
- 2338
 
4.6%
8 2052
 
4.1%
3 1552
 
3.1%
7 1413
 
2.8%
Other values (68) 7886
15.6%
Hangul
ValueCountFrequency (%)
료 5756
 
6.4%
리 4973
 
5.5%
수 4950
 
5.5%
비 4557
 
5.0%
관 3933
 
4.3%
체 3748
 
4.1%
연 3634
 
4.0%
납 3614
 
4.0%
월 1874
 
2.1%
사 1853
 
2.0%
Other values (609) 51611
57.0%
None
ValueCountFrequency (%)
× 10
83.3%
？ 2
 
16.7%
CJK
ValueCountFrequency (%)
入 4
80.0%
內 1
 
20.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%
Misc Symbols
ValueCountFrequency (%)
☞ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄴ 1
100.0%

Interactions

2024-05-11T02:31:16.791142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:16.315628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:17.002700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:31:16.564658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:31:24.718942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3970.188
년월일0.3971.0000.000
금액0.1880.0001.000
2024-05-11T02:31:24.944343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0770.160
금액0.0771.0000.081
비용명0.1600.0811.000

Missing values

2024-05-11T02:31:17.297147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:31:17.623946image/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
42722효창파크푸르지오A14074101잡수익20210825371647성실종합자원미수금 차액분 잡수입 전환
33604강변아파트A13790714광고료수익2021082060000제니스 잉글리쉬 광고게시 2주
11346상암월드컵파크7단지A12127005연체료수익202108246730관리비 연체료 수납
56470방화2단지A15722314알뜰시장수익20210802300008월분 알뜰장사용료 입금
49529관악동부센트레빌A15192201연체료수익202108302850관리비 연체료 수납
59381목동우성2차A15807703연체료수익20210806490관리비 연체료 수납
56715우장산힐스테이트A15728009광고료수익20210805150000우편투입- 애드랩
47988롯데캐슬아이비A15088915잡수익2021080310000102-502 보안카드 분실 재발급비
45497여의도대교A15001016연체료수익202108253620관리비 연체료 수납
27660대치포스코더샵A13584101주차장수익2021083116950008월 주차비 부과
아파트명아파트코드비용명년월일금액내용
53983사당유니드A15609001임대료수익20210803960000권혁일 창고 임대료
44868광장현대3단지아파트A14381415연체료수익202108033720관리비 연체료 수납
53143신대방현대A15601105승강기수익20210826100000승강기사용료(103-1402 유지연 입주민납부)
1366서교동 효성해링턴타워A10024891재활용품수익202108101818188월분 재활용품대금(동광자원)
47590문래힐스테이트A15083603잡수익202108021700음식물카드 판매
41281하계시영5단지A13987302연체료수익20210803940관리비 연체료 수납
52921남서울건영2차A15384603잡수익2021080920002-807 음식물
20423창동동아A13290003연체료수익2021083117250관리비 연체료 수납
49689구로신성미소지움A15205301연체료수익202108241470관리비 연체료 수납
7503공덕자이(임대)A10027951연체료수익202108311730관리비 연체료 수납