Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells10
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 = 29.32940495)Skewed

Reproduction

Analysis started2024-05-11 02:36:54.242065
Analysis finished2024-05-11 02:36:58.005057
Duration3.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2111
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:36:58.304119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.2403
Min length2

Characters and Unicode

Total characters72403
Distinct characters430
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

Unique208 ?
Unique (%)2.1%

Sample

1st row래미안서초유니빌
2nd row창동주공3단지
3rd row관악우방
4th row북아현두산
5th row대치아이파크
ValueCountFrequency (%)
아파트 147
 
1.4%
래미안 52
 
0.5%
입주자대표회의 31
 
0.3%
서초힐스 22
 
0.2%
은마 21
 
0.2%
강남한양수자인 20
 
0.2%
마포래미안푸르지오 20
 
0.2%
미아뉴타운두산위브트레지움 19
 
0.2%
금천롯데캐슬골드파크1차아파트 18
 
0.2%
남서울힐스테이트 18
 
0.2%
Other values (2172) 10278
96.5%
2024-05-11T02:36:59.467724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2360
 
3.3%
파 2196
 
3.0%
트 2137
 
3.0%
지 2018
 
2.8%
대 1690
 
2.3%
동 1609
 
2.2%
단 1568
 
2.2%
신 1429
 
2.0%
차 1419
 
2.0%
이 1360
 
1.9%
Other values (420) 54617
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66460
91.8%
Decimal Number 3730
 
5.2%
Uppercase Letter 730
 
1.0%
Space Separator 712
 
1.0%
Lowercase Letter 264
 
0.4%
Other Punctuation 141
 
0.2%
Close Punctuation 127
 
0.2%
Open Punctuation 127
 
0.2%
Dash Punctuation 102
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2360
 
3.6%
파 2196
 
3.3%
트 2137
 
3.2%
지 2018
 
3.0%
대 1690
 
2.5%
동 1609
 
2.4%
단 1568
 
2.4%
신 1429
 
2.2%
차 1419
 
2.1%
이 1360
 
2.0%
Other values (375) 48674
73.2%
Uppercase Letter
ValueCountFrequency (%)
S 129
17.7%
K 125
17.1%
C 86
11.8%
D 49
 
6.7%
M 49
 
6.7%
H 49
 
6.7%
L 47
 
6.4%
I 39
 
5.3%
E 35
 
4.8%
A 26
 
3.6%
Other values (6) 96
13.2%
Lowercase Letter
ValueCountFrequency (%)
e 160
60.6%
l 22
 
8.3%
i 20
 
7.6%
v 15
 
5.7%
k 12
 
4.5%
c 10
 
3.8%
s 10
 
3.8%
w 6
 
2.3%
h 3
 
1.1%
a 3
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 1099
29.5%
1 1072
28.7%
3 497
13.3%
4 278
 
7.5%
5 213
 
5.7%
6 164
 
4.4%
7 150
 
4.0%
9 103
 
2.8%
8 87
 
2.3%
0 67
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 122
86.5%
. 19
 
13.5%
Space Separator
ValueCountFrequency (%)
712
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66460
91.8%
Common 4943
 
6.8%
Latin 1000
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2360
 
3.6%
파 2196
 
3.3%
트 2137
 
3.2%
지 2018
 
3.0%
대 1690
 
2.5%
동 1609
 
2.4%
단 1568
 
2.4%
신 1429
 
2.2%
차 1419
 
2.1%
이 1360
 
2.0%
Other values (375) 48674
73.2%
Latin
ValueCountFrequency (%)
e 160
16.0%
S 129
12.9%
K 125
12.5%
C 86
 
8.6%
D 49
 
4.9%
M 49
 
4.9%
H 49
 
4.9%
L 47
 
4.7%
I 39
 
3.9%
E 35
 
3.5%
Other values (18) 232
23.2%
Common
ValueCountFrequency (%)
2 1099
22.2%
1 1072
21.7%
712
14.4%
3 497
10.1%
4 278
 
5.6%
5 213
 
4.3%
6 164
 
3.3%
7 150
 
3.0%
) 127
 
2.6%
( 127
 
2.6%
Other values (7) 504
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66460
91.8%
ASCII 5937
 
8.2%
Number Forms 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2360
 
3.6%
파 2196
 
3.3%
트 2137
 
3.2%
지 2018
 
3.0%
대 1690
 
2.5%
동 1609
 
2.4%
단 1568
 
2.4%
신 1429
 
2.2%
차 1419
 
2.1%
이 1360
 
2.0%
Other values (375) 48674
73.2%
ASCII
ValueCountFrequency (%)
2 1099
18.5%
1 1072
18.1%
712
12.0%
3 497
 
8.4%
4 278
 
4.7%
5 213
 
3.6%
6 164
 
2.8%
e 160
 
2.7%
7 150
 
2.5%
S 129
 
2.2%
Other values (34) 1463
24.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 6
100.0%

아파트코드
Text

Distinct2118
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:37:00.225059image/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

Unique209 ?
Unique (%)2.1%

Sample

1st rowA13707010
2nd rowA13204105
3rd rowA15303203
4th rowA12079501
5th rowA13528102
ValueCountFrequency (%)
a13778204 22
 
0.2%
a13583507 21
 
0.2%
a13520002 20
 
0.2%
a12175203 20
 
0.2%
a14272314 19
 
0.2%
a12179004 18
 
0.2%
a13880806 18
 
0.2%
a10027188 18
 
0.2%
a15370103 18
 
0.2%
a13822003 17
 
0.2%
Other values (2108) 9809
98.1%
2024-05-11T02:37:01.835031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18451
20.5%
1 17180
19.1%
A 9994
11.1%
3 9079
10.1%
2 8070
9.0%
5 6267
 
7.0%
8 5633
 
6.3%
7 5053
 
5.6%
4 3887
 
4.3%
6 3404
 
3.8%
Other values (2) 2982
 
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 18451
23.1%
1 17180
21.5%
3 9079
11.3%
2 8070
10.1%
5 6267
 
7.8%
8 5633
 
7.0%
7 5053
 
6.3%
4 3887
 
4.9%
6 3404
 
4.3%
9 2976
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9994
99.9%
B 6
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18451
23.1%
1 17180
21.5%
3 9079
11.3%
2 8070
10.1%
5 6267
 
7.8%
8 5633
 
7.0%
7 5053
 
6.3%
4 3887
 
4.9%
6 3404
 
4.3%
9 2976
 
3.7%
Latin
ValueCountFrequency (%)
A 9994
99.9%
B 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18451
20.5%
1 17180
19.1%
A 9994
11.1%
3 9079
10.1%
2 8070
9.0%
5 6267
 
7.0%
8 5633
 
6.3%
7 5053
 
5.6%
4 3887
 
4.3%
6 3404
 
3.8%
Other values (2) 2982
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3756 
승강기수익
1018 
잡수익
964 
광고료수익
837 
기타운영수익
836 
Other values (10)
2589 

Length

Max length9
Median length5
Mean length5.0139
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3756
37.6%
승강기수익 1018
 
10.2%
잡수익 964
 
9.6%
광고료수익 837
 
8.4%
기타운영수익 836
 
8.4%
주차장수익 829
 
8.3%
고용안정사업수익 409
 
4.1%
검침수익 288
 
2.9%
알뜰시장수익 246
 
2.5%
임대료수익 245
 
2.5%
Other values (5) 572
 
5.7%

Length

2024-05-11T02:37:02.589036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3756
37.6%
승강기수익 1018
 
10.2%
잡수익 964
 
9.6%
광고료수익 837
 
8.4%
기타운영수익 836
 
8.4%
주차장수익 829
 
8.3%
고용안정사업수익 409
 
4.1%
검침수익 288
 
2.9%
알뜰시장수익 246
 
2.5%
임대료수익 245
 
2.5%
Other values (5) 572
 
5.7%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200118
Minimum20200101
Maximum20200131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:37:03.127265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200101
5-th percentile20200102
Q120200109
median20200120
Q320200128
95-th percentile20200131
Maximum20200131
Range30
Interquartile range (IQR)19

Descriptive statistics

Standard deviation9.6877808
Coefficient of variation (CV)4.7959031 × 10-7
Kurtosis-1.288072
Mean20200118
Median Absolute Deviation (MAD)9
Skewness-0.16523428
Sum2.0200118 × 1011
Variance93.853096
MonotonicityNot monotonic
2024-05-11T02:37:03.747627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20200131 1088
 
10.9%
20200121 608
 
6.1%
20200130 547
 
5.5%
20200128 541
 
5.4%
20200110 503
 
5.0%
20200123 494
 
4.9%
20200129 466
 
4.7%
20200102 446
 
4.5%
20200120 433
 
4.3%
20200122 426
 
4.3%
Other values (21) 4448
44.5%
ValueCountFrequency (%)
20200101 216
2.2%
20200102 446
4.5%
20200103 387
3.9%
20200104 117
 
1.2%
20200105 89
 
0.9%
20200106 393
3.9%
20200107 327
3.3%
20200108 302
3.0%
20200109 307
3.1%
20200110 503
5.0%
ValueCountFrequency (%)
20200131 1088
10.9%
20200130 547
5.5%
20200129 466
4.7%
20200128 541
5.4%
20200127 185
 
1.8%
20200126 113
 
1.1%
20200125 74
 
0.7%
20200124 113
 
1.1%
20200123 494
4.9%
20200122 426
 
4.3%

금액
Real number (ℝ)

SKEWED 

Distinct3203
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265848.19
Minimum-5670000
Maximum90865380
Zeros7
Zeros (%)0.1%
Negative42
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:37:04.311916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5670000
5-th percentile120
Q12660
median30000
Q3100000
95-th percentile1072005.1
Maximum90865380
Range96535380
Interquartile range (IQR)97340

Descriptive statistics

Standard deviation1511460.4
Coefficient of variation (CV)5.6854267
Kurtosis1427.0958
Mean265848.19
Median Absolute Deviation (MAD)29270
Skewness29.329405
Sum2.6584819 × 109
Variance2.2845125 × 1012
MonotonicityNot monotonic
2024-05-11T02:37:04.855645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 515
 
5.1%
30000 512
 
5.1%
100000 482
 
4.8%
60000 154
 
1.5%
70000 151
 
1.5%
150000 138
 
1.4%
40000 129
 
1.3%
80000 115
 
1.1%
120000 113
 
1.1%
20000 106
 
1.1%
Other values (3193) 7585
75.8%
ValueCountFrequency (%)
-5670000 1
< 0.1%
-2280000 1
< 0.1%
-1900000 1
< 0.1%
-780000 1
< 0.1%
-575640 1
< 0.1%
-440000 1
< 0.1%
-330000 1
< 0.1%
-213600 1
< 0.1%
-200000 1
< 0.1%
-178610 1
< 0.1%
ValueCountFrequency (%)
90865380 1
< 0.1%
38275200 1
< 0.1%
34084170 1
< 0.1%
32616727 1
< 0.1%
26608040 1
< 0.1%
25734530 1
< 0.1%
25434000 1
< 0.1%
23987040 1
< 0.1%
22424430 1
< 0.1%
21200000 1
< 0.1%

내용
Text

Distinct5651
Distinct (%)56.6%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:37:05.624212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length70
Mean length13.908709
Min length2

Characters and Unicode

Total characters138948
Distinct characters742
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5431 ?
Unique (%)54.4%

Sample

1st row1015호 전입
2nd row일장야채(1/17)
3rd row수도계량기 1개(101-308)
4th row01월분 주차료수입
5th row108-1102호독서실사용료
ValueCountFrequency (%)
관리비 3889
 
14.8%
수납 3768
 
14.3%
연체료 3766
 
14.3%
1월분 318
 
1.2%
승강기 276
 
1.1%
12월분 276
 
1.1%
승강기사용료 220
 
0.8%
입금 197
 
0.7%
1월 192
 
0.7%
189
 
0.7%
Other values (7194) 13177
50.2%
2024-05-11T02:37:07.148910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16397
 
11.8%
1 6726
 
4.8%
료 5797
 
4.2%
0 5102
 
3.7%
수 5096
 
3.7%
리 4924
 
3.5%
비 4644
 
3.3%
관 4118
 
3.0%
체 3970
 
2.9%
납 3910
 
2.8%
Other values (732) 78264
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88601
63.8%
Decimal Number 21909
 
15.8%
Space Separator 16397
 
11.8%
Close Punctuation 2980
 
2.1%
Open Punctuation 2977
 
2.1%
Other Punctuation 2644
 
1.9%
Dash Punctuation 2190
 
1.6%
Uppercase Letter 701
 
0.5%
Math Symbol 334
 
0.2%
Lowercase Letter 148
 
0.1%
Other values (3) 67
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5797
 
6.5%
수 5096
 
5.8%
리 4924
 
5.6%
비 4644
 
5.2%
관 4118
 
4.6%
체 3970
 
4.5%
납 3910
 
4.4%
연 3825
 
4.3%
월 1826
 
2.1%
용 1581
 
1.8%
Other values (644) 48910
55.2%
Uppercase Letter
ValueCountFrequency (%)
N 84
 
12.0%
O 57
 
8.1%
T 52
 
7.4%
K 50
 
7.1%
A 49
 
7.0%
L 48
 
6.8%
G 42
 
6.0%
B 39
 
5.6%
E 35
 
5.0%
M 33
 
4.7%
Other values (14) 212
30.2%
Lowercase Letter
ValueCountFrequency (%)
o 51
34.5%
n 17
 
11.5%
x 13
 
8.8%
k 10
 
6.8%
c 10
 
6.8%
i 6
 
4.1%
r 5
 
3.4%
l 5
 
3.4%
t 5
 
3.4%
b 5
 
3.4%
Other values (9) 21
14.2%
Other Punctuation
ValueCountFrequency (%)
, 776
29.3%
/ 735
27.8%
. 733
27.7%
: 186
 
7.0%
* 130
 
4.9%
@ 35
 
1.3%
% 15
 
0.6%
? 14
 
0.5%
# 8
 
0.3%
' 4
 
0.2%
Other values (3) 8
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 6726
30.7%
0 5102
23.3%
2 3776
17.2%
3 1444
 
6.6%
4 1112
 
5.1%
9 927
 
4.2%
5 891
 
4.1%
6 733
 
3.3%
7 609
 
2.8%
8 589
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 281
84.1%
> 16
 
4.8%
+ 13
 
3.9%
< 7
 
2.1%
= 6
 
1.8%
× 4
 
1.2%
→ 4
 
1.2%
⇒ 2
 
0.6%
÷ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2909
97.6%
] 69
 
2.3%
} 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2908
97.7%
[ 67
 
2.3%
{ 2
 
0.1%
Other Number
ValueCountFrequency (%)
② 1
33.3%
① 1
33.3%
⑧ 1
33.3%
Space Separator
ValueCountFrequency (%)
16397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2190
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 63
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88599
63.8%
Common 49498
35.6%
Latin 849
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5797
 
6.5%
수 5096
 
5.8%
리 4924
 
5.6%
비 4644
 
5.2%
관 4118
 
4.6%
체 3970
 
4.5%
납 3910
 
4.4%
연 3825
 
4.3%
월 1826
 
2.1%
용 1581
 
1.8%
Other values (642) 48908
55.2%
Common
ValueCountFrequency (%)
16397
33.1%
1 6726
13.6%
0 5102
 
10.3%
2 3776
 
7.6%
) 2909
 
5.9%
( 2908
 
5.9%
- 2190
 
4.4%
3 1444
 
2.9%
4 1112
 
2.2%
9 927
 
1.9%
Other values (35) 6007
 
12.1%
Latin
ValueCountFrequency (%)
N 84
 
9.9%
O 57
 
6.7%
T 52
 
6.1%
o 51
 
6.0%
K 50
 
5.9%
A 49
 
5.8%
L 48
 
5.7%
G 42
 
4.9%
B 39
 
4.6%
E 35
 
4.1%
Other values (33) 342
40.3%
Han
ValueCountFrequency (%)
外 1
50.0%
人 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88599
63.8%
ASCII 50333
36.2%
Arrows 6
 
< 0.1%
None 5
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16397
32.6%
1 6726
13.4%
0 5102
 
10.1%
2 3776
 
7.5%
) 2909
 
5.8%
( 2908
 
5.8%
- 2190
 
4.4%
3 1444
 
2.9%
4 1112
 
2.2%
9 927
 
1.8%
Other values (71) 6842
13.6%
Hangul
ValueCountFrequency (%)
료 5797
 
6.5%
수 5096
 
5.8%
리 4924
 
5.6%
비 4644
 
5.2%
관 4118
 
4.6%
체 3970
 
4.5%
납 3910
 
4.4%
연 3825
 
4.3%
월 1826
 
2.1%
용 1581
 
1.8%
Other values (642) 48908
55.2%
None
ValueCountFrequency (%)
× 4
80.0%
÷ 1
 
20.0%
Arrows
ValueCountFrequency (%)
→ 4
66.7%
⇒ 2
33.3%
Enclosed Alphanum
ValueCountFrequency (%)
② 1
33.3%
① 1
33.3%
⑧ 1
33.3%
CJK
ValueCountFrequency (%)
外 1
50.0%
人 1
50.0%

Interactions

2024-05-11T02:36:56.680250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:36:56.113848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:36:56.971711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:36:56.402721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:37:07.505618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3680.188
년월일0.3681.0000.071
금액0.1880.0711.000
2024-05-11T02:37:07.760332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0720.147
금액0.0721.0000.089
비용명0.1470.0891.000

Missing values

2024-05-11T02:36:57.453676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:36:57.833758image/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
30801래미안서초유니빌A13707010승강기수익20200107700001015호 전입
17517창동주공3단지A13204105광고료수익2020011740000일장야채(1/17)
52659관악우방A15303203잡수익202001022400수도계량기 1개(101-308)
8543북아현두산A12079501주차장수익20200131167095001월분 주차료수입
25858대치아이파크A13528102기타운영수익2020013050000108-1102호독서실사용료
53749브라운스톤상도A15603002연체료수익20200103430관리비 연체료 수납
37016상계주공16단지A13920803잡수익20200131600000근로복지공단 일자리안정자금지원 미화원
17268쌍문한양1차A13203303고용안정사업수익2020010263000012/12일건 11월분 미화원(7명) 일자리 지원금(근로복지공단) (수협)
58664강서한숲대림A15785703잡수익202001083체크카드 포인트 입금
40388월계극동A13985201검침수익2020010685564검침수당청구
아파트명아파트코드비용명년월일금액내용
46635양평벽산A15010203잡수익20200115600000장애복지수당(한국장애인고용공단)
13550휘경동일스위트리버A13009206기타운영수익20200118200001월 휘트니스회비(101-503)
13685장안현대힐스테이트A13010004연체료수익2020013111800관리비 연체료 수납
13404휘경동양1.2차A13009001연체료수익202001145460관리비 연체료 수납
29155꿈의숲푸르지오A13613009알뜰시장수익20200129160000일일장 (곱창 4회)
31554서초네이처힐7단지A13778203연체료수익20200104230관리비 연체료 수납
57510우장산힐스테이트A15728009검침수익202001169451401월분 한전검침지원금
461항동하버라인2단지A10025387연체료수익202001214260관리비 연체료 수납
8025북가좌두산위브A12013201검침수익20200120111150한전검침수당
61013목동6단지A15875103연체료수익20200102140관리비 연체료 수납