Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells5
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 = 20.39506625)Skewed

Reproduction

Analysis started2024-05-11 02:39:13.965515
Analysis finished2024-05-11 02:39:19.066433
Duration5.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2065
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:39:19.434028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.1577
Min length2

Characters and Unicode

Total characters71577
Distinct characters427
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)1.9%

Sample

1st row삼성래미안공덕4차
2nd row북가좌삼호제2
3rd row신월시영아파트
4th row개봉삼환
5th row응봉신동아
ValueCountFrequency (%)
아파트 101
 
1.0%
래미안 41
 
0.4%
서초힐스 22
 
0.2%
입주자대표회의 22
 
0.2%
방학신동아1단지 19
 
0.2%
힐스테이트 19
 
0.2%
잠실엘스 18
 
0.2%
영등포푸르지오 18
 
0.2%
래미안아름숲 18
 
0.2%
sk북한산시티아파트 17
 
0.2%
Other values (2118) 10216
97.2%
2024-05-11T02:39:20.774287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2263
 
3.2%
파 2162
 
3.0%
지 2033
 
2.8%
트 2011
 
2.8%
대 1790
 
2.5%
단 1634
 
2.3%
동 1591
 
2.2%
신 1409
 
2.0%
차 1358
 
1.9%
성 1318
 
1.8%
Other values (417) 54008
75.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65452
91.4%
Decimal Number 3971
 
5.5%
Uppercase Letter 754
 
1.1%
Space Separator 559
 
0.8%
Lowercase Letter 267
 
0.4%
Other Punctuation 142
 
0.2%
Close Punctuation 139
 
0.2%
Open Punctuation 139
 
0.2%
Dash Punctuation 138
 
0.2%
Letter Number 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2263
 
3.5%
파 2162
 
3.3%
지 2033
 
3.1%
트 2011
 
3.1%
대 1790
 
2.7%
단 1634
 
2.5%
동 1591
 
2.4%
신 1409
 
2.2%
차 1358
 
2.1%
성 1318
 
2.0%
Other values (371) 47883
73.2%
Uppercase Letter
ValueCountFrequency (%)
S 133
17.6%
K 108
14.3%
C 90
11.9%
M 62
8.2%
D 62
8.2%
H 49
 
6.5%
L 47
 
6.2%
I 37
 
4.9%
G 32
 
4.2%
A 29
 
3.8%
Other values (7) 105
13.9%
Lowercase Letter
ValueCountFrequency (%)
e 166
62.2%
l 34
 
12.7%
i 22
 
8.2%
v 18
 
6.7%
s 7
 
2.6%
h 6
 
2.2%
c 4
 
1.5%
w 3
 
1.1%
k 3
 
1.1%
g 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 1266
31.9%
2 1087
27.4%
3 457
 
11.5%
4 287
 
7.2%
5 236
 
5.9%
6 192
 
4.8%
9 134
 
3.4%
7 129
 
3.2%
0 92
 
2.3%
8 91
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 130
91.5%
. 12
 
8.5%
Space Separator
ValueCountFrequency (%)
559
100.0%
Close Punctuation
ValueCountFrequency (%)
) 139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65452
91.4%
Common 5093
 
7.1%
Latin 1032
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2263
 
3.5%
파 2162
 
3.3%
지 2033
 
3.1%
트 2011
 
3.1%
대 1790
 
2.7%
단 1634
 
2.5%
동 1591
 
2.4%
신 1409
 
2.2%
차 1358
 
2.1%
성 1318
 
2.0%
Other values (371) 47883
73.2%
Latin
ValueCountFrequency (%)
e 166
16.1%
S 133
12.9%
K 108
10.5%
C 90
 
8.7%
M 62
 
6.0%
D 62
 
6.0%
H 49
 
4.7%
L 47
 
4.6%
I 37
 
3.6%
l 34
 
3.3%
Other values (19) 244
23.6%
Common
ValueCountFrequency (%)
1 1266
24.9%
2 1087
21.3%
559
11.0%
3 457
 
9.0%
4 287
 
5.6%
5 236
 
4.6%
6 192
 
3.8%
) 139
 
2.7%
( 139
 
2.7%
- 138
 
2.7%
Other values (7) 593
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65452
91.4%
ASCII 6114
 
8.5%
Number Forms 11
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2263
 
3.5%
파 2162
 
3.3%
지 2033
 
3.1%
트 2011
 
3.1%
대 1790
 
2.7%
단 1634
 
2.5%
동 1591
 
2.4%
신 1409
 
2.2%
차 1358
 
2.1%
성 1318
 
2.0%
Other values (371) 47883
73.2%
ASCII
ValueCountFrequency (%)
1 1266
20.7%
2 1087
17.8%
559
 
9.1%
3 457
 
7.5%
4 287
 
4.7%
5 236
 
3.9%
6 192
 
3.1%
e 166
 
2.7%
) 139
 
2.3%
( 139
 
2.3%
Other values (35) 1586
25.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 11
100.0%

아파트코드
Text

Distinct2071
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:39:21.759405image/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

Unique193 ?
Unique (%)1.9%

Sample

1st rowA12170601
2nd rowA12076601
3rd rowA15884703
4th rowA15209205
5th rowA13385303
ValueCountFrequency (%)
a13778204 22
 
0.2%
a13202312 19
 
0.2%
a15003002 18
 
0.2%
a13002002 18
 
0.2%
a13822004 18
 
0.2%
a14272304 17
 
0.2%
a10027817 17
 
0.2%
a13788208 16
 
0.2%
a13718001 16
 
0.2%
a12012202 15
 
0.1%
Other values (2061) 9824
98.2%
2024-05-11T02:39:23.505632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18384
20.4%
1 17423
19.4%
A 9991
11.1%
3 9059
10.1%
2 7948
8.8%
5 6138
 
6.8%
8 5748
 
6.4%
7 5051
 
5.6%
4 3810
 
4.2%
6 3397
 
3.8%
Other values (2) 3051
 
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 18384
23.0%
1 17423
21.8%
3 9059
11.3%
2 7948
9.9%
5 6138
 
7.7%
8 5748
 
7.2%
7 5051
 
6.3%
4 3810
 
4.8%
6 3397
 
4.2%
9 3042
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9991
99.9%
B 9
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18384
23.0%
1 17423
21.8%
3 9059
11.3%
2 7948
9.9%
5 6138
 
7.7%
8 5748
 
7.2%
7 5051
 
6.3%
4 3810
 
4.8%
6 3397
 
4.2%
9 3042
 
3.8%
Latin
ValueCountFrequency (%)
A 9991
99.9%
B 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18384
20.4%
1 17423
19.4%
A 9991
11.1%
3 9059
10.1%
2 7948
8.8%
5 6138
 
6.8%
8 5748
 
6.4%
7 5051
 
5.6%
4 3810
 
4.2%
6 3397
 
3.8%
Other values (2) 3051
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3768 
광고료수익
1218 
잡수익
948 
승강기수익
781 
주차장수익
750 
Other values (10)
2535 

Length

Max length9
Median length5
Mean length5.0459
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3768
37.7%
광고료수익 1218
 
12.2%
잡수익 948
 
9.5%
승강기수익 781
 
7.8%
주차장수익 750
 
7.5%
기타운영수익 697
 
7.0%
고용안정사업수익 480
 
4.8%
검침수익 266
 
2.7%
알뜰시장수익 248
 
2.5%
임대료수익 231
 
2.3%
Other values (5) 613
 
6.1%

Length

2024-05-11T02:39:24.034739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3768
37.7%
광고료수익 1218
 
12.2%
잡수익 948
 
9.5%
승강기수익 781
 
7.8%
주차장수익 750
 
7.5%
기타운영수익 697
 
7.0%
고용안정사업수익 480
 
4.8%
검침수익 266
 
2.7%
알뜰시장수익 248
 
2.5%
임대료수익 231
 
2.3%
Other values (5) 613
 
6.1%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190518
Minimum20190501
Maximum20190531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:39:24.609060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190501
5-th percentile20190502
Q120190510
median20190520
Q320190527
95-th percentile20190531
Maximum20190531
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.4620816
Coefficient of variation (CV)4.6863986 × 10-7
Kurtosis-1.2041811
Mean20190518
Median Absolute Deviation (MAD)8
Skewness-0.23146323
Sum2.0190518 × 1011
Variance89.530989
MonotonicityNot monotonic
2024-05-11T02:39:25.122788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20190531 969
 
9.7%
20190515 527
 
5.3%
20190520 524
 
5.2%
20190530 505
 
5.1%
20190527 482
 
4.8%
20190502 455
 
4.5%
20190510 442
 
4.4%
20190524 436
 
4.4%
20190507 431
 
4.3%
20190529 394
 
3.9%
Other values (21) 4835
48.4%
ValueCountFrequency (%)
20190501 238
2.4%
20190502 455
4.5%
20190503 385
3.9%
20190504 88
 
0.9%
20190505 60
 
0.6%
20190506 99
 
1.0%
20190507 431
4.3%
20190508 333
3.3%
20190509 327
3.3%
20190510 442
4.4%
ValueCountFrequency (%)
20190531 969
9.7%
20190530 505
5.1%
20190529 394
3.9%
20190528 386
 
3.9%
20190527 482
4.8%
20190526 164
 
1.6%
20190525 157
 
1.6%
20190524 436
4.4%
20190523 372
 
3.7%
20190522 354
 
3.5%

금액
Real number (ℝ)

SKEWED 

Distinct3326
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean250229.79
Minimum-7736770
Maximum50000000
Zeros13
Zeros (%)0.1%
Negative42
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:39:25.639217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7736770
5-th percentile210
Q13550
median30000
Q3100000
95-th percentile1052835
Maximum50000000
Range57736770
Interquartile range (IQR)96450

Descriptive statistics

Standard deviation1284459.8
Coefficient of variation (CV)5.133121
Kurtosis630.53972
Mean250229.79
Median Absolute Deviation (MAD)28700
Skewness20.395066
Sum2.5022979 × 109
Variance1.6498369 × 1012
MonotonicityNot monotonic
2024-05-11T02:39:26.216445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 768
 
7.7%
50000 622
 
6.2%
100000 409
 
4.1%
60000 152
 
1.5%
40000 146
 
1.5%
70000 132
 
1.3%
80000 116
 
1.2%
150000 109
 
1.1%
20000 99
 
1.0%
200000 89
 
0.9%
Other values (3316) 7358
73.6%
ValueCountFrequency (%)
-7736770 1
< 0.1%
-4360000 1
< 0.1%
-1879670 1
< 0.1%
-910000 1
< 0.1%
-890000 1
< 0.1%
-557150 1
< 0.1%
-432500 1
< 0.1%
-350000 1
< 0.1%
-300000 1
< 0.1%
-272727 1
< 0.1%
ValueCountFrequency (%)
50000000 1
< 0.1%
47973481 1
< 0.1%
45022000 1
< 0.1%
27300000 1
< 0.1%
23720400 1
< 0.1%
23302033 1
< 0.1%
17325000 1
< 0.1%
16800000 2
< 0.1%
15272727 1
< 0.1%
15000000 1
< 0.1%

내용
Text

Distinct5664
Distinct (%)56.7%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T02:39:26.960882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length92
Median length69
Mean length13.491746
Min length2

Characters and Unicode

Total characters134850
Distinct characters752
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5428 ?
Unique (%)54.3%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row김지원
4th row게시판-블루라군
5th row호떡장사
ValueCountFrequency (%)
관리비 3904
 
15.1%
연체료 3774
 
14.6%
수납 3771
 
14.6%
5월분 320
 
1.2%
4월분 307
 
1.2%
238
 
0.9%
5월 221
 
0.9%
승강기 213
 
0.8%
입금 209
 
0.8%
게시판 208
 
0.8%
Other values (7096) 12644
49.0%
2024-05-11T02:39:28.291639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15937
 
11.8%
료 5561
 
4.1%
수 5105
 
3.8%
리 5043
 
3.7%
비 4765
 
3.5%
관 4131
 
3.1%
체 3945
 
2.9%
0 3892
 
2.9%
연 3858
 
2.9%
1 3833
 
2.8%
Other values (742) 78780
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89196
66.1%
Decimal Number 17897
 
13.3%
Space Separator 15937
 
11.8%
Close Punctuation 2975
 
2.2%
Open Punctuation 2971
 
2.2%
Other Punctuation 2600
 
1.9%
Dash Punctuation 2074
 
1.5%
Uppercase Letter 720
 
0.5%
Math Symbol 282
 
0.2%
Lowercase Letter 145
 
0.1%
Other values (3) 53
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5561
 
6.2%
수 5105
 
5.7%
리 5043
 
5.7%
비 4765
 
5.3%
관 4131
 
4.6%
체 3945
 
4.4%
연 3858
 
4.3%
납 3828
 
4.3%
월 1862
 
2.1%
금 1566
 
1.8%
Other values (657) 49532
55.5%
Uppercase Letter
ValueCountFrequency (%)
N 82
 
11.4%
L 56
 
7.8%
C 53
 
7.4%
T 53
 
7.4%
K 52
 
7.2%
O 45
 
6.2%
E 45
 
6.2%
G 44
 
6.1%
A 44
 
6.1%
D 40
 
5.6%
Other values (15) 206
28.6%
Lowercase Letter
ValueCountFrequency (%)
o 54
37.2%
x 18
 
12.4%
n 18
 
12.4%
k 14
 
9.7%
c 9
 
6.2%
s 8
 
5.5%
b 8
 
5.5%
t 5
 
3.4%
e 2
 
1.4%
g 2
 
1.4%
Other values (6) 7
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 732
28.2%
/ 722
27.8%
. 669
25.7%
: 212
 
8.2%
* 126
 
4.8%
? 50
 
1.9%
@ 35
 
1.3%
& 16
 
0.6%
# 12
 
0.5%
% 12
 
0.5%
Other values (4) 14
 
0.5%
Decimal Number
ValueCountFrequency (%)
0 3892
21.7%
1 3833
21.4%
2 2204
12.3%
5 2115
11.8%
4 1775
9.9%
3 1352
 
7.6%
9 807
 
4.5%
6 795
 
4.4%
8 573
 
3.2%
7 551
 
3.1%
Math Symbol
ValueCountFrequency (%)
~ 226
80.1%
+ 22
 
7.8%
× 11
 
3.9%
> 10
 
3.5%
< 7
 
2.5%
= 3
 
1.1%
⇒ 1
 
0.4%
→ 1
 
0.4%
÷ 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 2894
97.3%
] 79
 
2.7%
} 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2888
97.2%
[ 82
 
2.8%
{ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
15937
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2074
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 51
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89188
66.1%
Common 44788
33.2%
Latin 865
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5561
 
6.2%
수 5105
 
5.7%
리 5043
 
5.7%
비 4765
 
5.3%
관 4131
 
4.6%
체 3945
 
4.4%
연 3858
 
4.3%
납 3828
 
4.3%
월 1862
 
2.1%
금 1566
 
1.8%
Other values (651) 49524
55.5%
Common
ValueCountFrequency (%)
15937
35.6%
0 3892
 
8.7%
1 3833
 
8.6%
) 2894
 
6.5%
( 2888
 
6.4%
2 2204
 
4.9%
5 2115
 
4.7%
- 2074
 
4.6%
4 1775
 
4.0%
3 1352
 
3.0%
Other values (33) 5824
 
13.0%
Latin
ValueCountFrequency (%)
N 82
 
9.5%
L 56
 
6.5%
o 54
 
6.2%
C 53
 
6.1%
T 53
 
6.1%
K 52
 
6.0%
O 45
 
5.2%
E 45
 
5.2%
G 44
 
5.1%
A 44
 
5.1%
Other values (31) 337
39.0%
Han
ValueCountFrequency (%)
分 2
22.2%
人 2
22.2%
月 1
11.1%
名 1
11.1%
氏 1
11.1%
入 1
11.1%
萬 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89187
66.1%
ASCII 45639
33.8%
None 13
 
< 0.1%
CJK 9
 
< 0.1%
Arrows 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15937
34.9%
0 3892
 
8.5%
1 3833
 
8.4%
) 2894
 
6.3%
( 2888
 
6.3%
2 2204
 
4.8%
5 2115
 
4.6%
- 2074
 
4.5%
4 1775
 
3.9%
3 1352
 
3.0%
Other values (70) 6675
14.6%
Hangul
ValueCountFrequency (%)
료 5561
 
6.2%
수 5105
 
5.7%
리 5043
 
5.7%
비 4765
 
5.3%
관 4131
 
4.6%
체 3945
 
4.4%
연 3858
 
4.3%
납 3828
 
4.3%
월 1862
 
2.1%
금 1566
 
1.8%
Other values (650) 49523
55.5%
None
ValueCountFrequency (%)
× 11
84.6%
㈜ 1
 
7.7%
÷ 1
 
7.7%
CJK
ValueCountFrequency (%)
分 2
22.2%
人 2
22.2%
月 1
11.1%
名 1
11.1%
氏 1
11.1%
入 1
11.1%
萬 1
11.1%
Arrows
ValueCountFrequency (%)
⇒ 1
50.0%
→ 1
50.0%

Interactions

2024-05-11T02:39:17.648023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:39:17.022540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:39:18.027692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:39:17.338946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:39:28.641966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3570.241
년월일0.3571.0000.050
금액0.2410.0501.000
2024-05-11T02:39:28.998862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0210.141
금액0.0211.0000.146
비용명0.1410.1461.000

Missing values

2024-05-11T02:39:18.408007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:39:18.860745image/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
8794삼성래미안공덕4차A12170601연체료수익201905039150관리비 연체료 수납
7288북가좌삼호제2A12076601연체료수익20190514350관리비 연체료 수납
62372신월시영아파트A15884703알뜰시장수익2019051730000김지원
51103개봉삼환A15209205광고료수익2019050730000게시판-블루라군
21516응봉신동아A13385303알뜰시장수익2019051330000호떡장사
63231은평뉴타운구파발9단지1관리A41279921광고료수익2019052050000게시판광고/한의원
37643중계금호A13922904연체료수익201905318610관리비 연체료 수납
54791상도래미안1차A15603204광고료수익2019052030000초미세방충망 게시판광고-현대시스템창호
60161목동현대아이파크A15805102주차장수익201905201363602019년 1~4월 주차비(교촌치킨)
42298이촌강촌A14003106연체료수익2019052811630관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
47229양평현대2차A15010305연체료수익201905295710관리비 연체료 수납
28743길음뉴타운8단지A13611008승강기수익2019050360000804-304 전출.전입
20764금호자이1차A13380301연체료수익201905231710관리비 연체료 수납
53024신도림현대A15288803연체료수익201905167670관리비 연체료 수납
20518행당대림제2A13377902연체료수익201905071390관리비 연체료 수납
26172동화히스토리A13572601연체료수익201905315850관리비 연체료 수납
20447행당한진타운A13377703잡수익20190503300005월 탁구장 전기 사용료
36163한양아파트A13885102연체료수익20190502170관리비 연체료 수납
858힐스테이트청계A10026104잡수익201905143300103동 1804호 현관마스터키 1개 구입비
56746흑석한강현대A15685702잡수익201905105004월분 산재보험료 자동이체 할인