Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells7
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 = 27.66813537)Skewed

Reproduction

Analysis started2024-05-11 02:33:01.624249
Analysis finished2024-05-11 02:33:05.744846
Duration4.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2187
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:33:06.138913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length7.324
Min length2

Characters and Unicode

Total characters73240
Distinct characters435
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

Unique241 ?
Unique (%)2.4%

Sample

1st row은평뉴타운상림마을제3단지
2nd row묵동금호어울림
3rd row창신쌍용아파트 2단지
4th row힐스테이트녹번
5th row흑석한강센트레빌
ValueCountFrequency (%)
아파트 173
 
1.6%
래미안 45
 
0.4%
아이파크 29
 
0.3%
고덕 24
 
0.2%
e편한세상 22
 
0.2%
마포펜트라우스 22
 
0.2%
마포래미안푸르지오 19
 
0.2%
북한산 19
 
0.2%
힐스테이트 18
 
0.2%
은마 18
 
0.2%
Other values (2253) 10354
96.4%
2024-05-11T02:33:07.113853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2605
 
3.6%
파 2466
 
3.4%
트 2342
 
3.2%
지 1968
 
2.7%
대 1677
 
2.3%
단 1534
 
2.1%
동 1496
 
2.0%
이 1462
 
2.0%
신 1397
 
1.9%
차 1352
 
1.8%
Other values (425) 54941
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66936
91.4%
Decimal Number 3755
 
5.1%
Space Separator 832
 
1.1%
Uppercase Letter 730
 
1.0%
Lowercase Letter 338
 
0.5%
Open Punctuation 172
 
0.2%
Close Punctuation 172
 
0.2%
Other Punctuation 160
 
0.2%
Dash Punctuation 136
 
0.2%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2605
 
3.9%
파 2466
 
3.7%
트 2342
 
3.5%
지 1968
 
2.9%
대 1677
 
2.5%
단 1534
 
2.3%
동 1496
 
2.2%
이 1462
 
2.2%
신 1397
 
2.1%
차 1352
 
2.0%
Other values (380) 48637
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 127
17.4%
K 102
14.0%
C 82
11.2%
L 56
7.7%
H 55
7.5%
M 55
7.5%
D 55
7.5%
I 37
 
5.1%
E 32
 
4.4%
A 24
 
3.3%
Other values (7) 105
14.4%
Lowercase Letter
ValueCountFrequency (%)
e 187
55.3%
l 34
 
10.1%
i 26
 
7.7%
s 24
 
7.1%
k 19
 
5.6%
v 18
 
5.3%
h 9
 
2.7%
c 8
 
2.4%
w 5
 
1.5%
a 4
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 1118
29.8%
2 1062
28.3%
3 506
13.5%
4 282
 
7.5%
5 228
 
6.1%
6 182
 
4.8%
7 123
 
3.3%
9 103
 
2.7%
8 80
 
2.1%
0 71
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 133
83.1%
. 27
 
16.9%
Space Separator
ValueCountFrequency (%)
832
100.0%
Open Punctuation
ValueCountFrequency (%)
( 172
100.0%
Close Punctuation
ValueCountFrequency (%)
) 172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66936
91.4%
Common 5227
 
7.1%
Latin 1077
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2605
 
3.9%
파 2466
 
3.7%
트 2342
 
3.5%
지 1968
 
2.9%
대 1677
 
2.5%
단 1534
 
2.3%
동 1496
 
2.2%
이 1462
 
2.2%
신 1397
 
2.1%
차 1352
 
2.0%
Other values (380) 48637
72.7%
Latin
ValueCountFrequency (%)
e 187
17.4%
S 127
11.8%
K 102
 
9.5%
C 82
 
7.6%
L 56
 
5.2%
H 55
 
5.1%
M 55
 
5.1%
D 55
 
5.1%
I 37
 
3.4%
l 34
 
3.2%
Other values (19) 287
26.6%
Common
ValueCountFrequency (%)
1 1118
21.4%
2 1062
20.3%
832
15.9%
3 506
9.7%
4 282
 
5.4%
5 228
 
4.4%
6 182
 
3.5%
( 172
 
3.3%
) 172
 
3.3%
- 136
 
2.6%
Other values (6) 537
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66936
91.4%
ASCII 6295
 
8.6%
Number Forms 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2605
 
3.9%
파 2466
 
3.7%
트 2342
 
3.5%
지 1968
 
2.9%
대 1677
 
2.5%
단 1534
 
2.3%
동 1496
 
2.2%
이 1462
 
2.2%
신 1397
 
2.1%
차 1352
 
2.0%
Other values (380) 48637
72.7%
ASCII
ValueCountFrequency (%)
1 1118
17.8%
2 1062
16.9%
832
13.2%
3 506
 
8.0%
4 282
 
4.5%
5 228
 
3.6%
e 187
 
3.0%
6 182
 
2.9%
( 172
 
2.7%
) 172
 
2.7%
Other values (34) 1554
24.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

아파트코드
Text

Distinct2194
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:33:08.000505image/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

Unique241 ?
Unique (%)2.4%

Sample

1st rowA41279908
2nd rowA13114103
3rd rowA11077101
4th rowA10025836
5th rowA15679107
ValueCountFrequency (%)
a12179004 22
 
0.2%
a12175203 19
 
0.2%
a13583507 18
 
0.2%
a15383702 17
 
0.2%
a10027205 17
 
0.2%
a10025614 17
 
0.2%
a13822003 17
 
0.2%
a10025850 15
 
0.1%
a10026180 15
 
0.1%
a15101504 15
 
0.1%
Other values (2184) 9828
98.3%
2024-05-11T02:33:09.330254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18800
20.9%
1 17217
19.1%
A 9990
11.1%
3 8738
9.7%
2 8192
9.1%
5 6433
 
7.1%
8 5537
 
6.2%
7 4958
 
5.5%
4 3844
 
4.3%
6 3371
 
3.7%
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 18800
23.5%
1 17217
21.5%
3 8738
10.9%
2 8192
10.2%
5 6433
 
8.0%
8 5537
 
6.9%
7 4958
 
6.2%
4 3844
 
4.8%
6 3371
 
4.2%
9 2910
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9990
99.9%
B 10
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18800
23.5%
1 17217
21.5%
3 8738
10.9%
2 8192
10.2%
5 6433
 
8.0%
8 5537
 
6.9%
7 4958
 
6.2%
4 3844
 
4.8%
6 3371
 
4.2%
9 2910
 
3.6%
Latin
ValueCountFrequency (%)
A 9990
99.9%
B 10
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18800
20.9%
1 17217
19.1%
A 9990
11.1%
3 8738
9.7%
2 8192
9.1%
5 6433
 
7.1%
8 5537
 
6.2%
7 4958
 
5.5%
4 3844
 
4.3%
6 3371
 
3.7%
Other values (2) 2920
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3532 
승강기수익
1300 
잡수익
1029 
주차장수익
946 
광고료수익
910 
Other values (10)
2283 

Length

Max length9
Median length5
Mean length4.9174
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3532
35.3%
승강기수익 1300
 
13.0%
잡수익 1029
 
10.3%
주차장수익 946
 
9.5%
광고료수익 910
 
9.1%
기타운영수익 528
 
5.3%
검침수익 329
 
3.3%
고용안정사업수익 283
 
2.8%
부과차익 257
 
2.6%
임대료수익 249
 
2.5%
Other values (5) 637
 
6.4%

Length

2024-05-11T02:33:09.808826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3532
35.3%
승강기수익 1300
 
13.0%
잡수익 1029
 
10.3%
주차장수익 946
 
9.5%
광고료수익 910
 
9.1%
기타운영수익 528
 
5.3%
검침수익 329
 
3.3%
고용안정사업수익 283
 
2.8%
부과차익 257
 
2.6%
임대료수익 249
 
2.5%
Other values (5) 637
 
6.4%

년월일
Real number (ℝ)

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210216
Minimum20210201
Maximum20210228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:33:10.298503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210201
5-th percentile20210201
Q120210208
median20210217
Q320210225
95-th percentile20210228
Maximum20210228
Range27
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.2623907
Coefficient of variation (CV)4.5830241 × 10-7
Kurtosis-1.3814947
Mean20210216
Median Absolute Deviation (MAD)8
Skewness-0.28904288
Sum2.0210216 × 1011
Variance85.791881
MonotonicityNot monotonic
2024-05-11T02:33:10.700495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
20210228 830
 
8.3%
20210226 781
 
7.8%
20210201 763
 
7.6%
20210225 683
 
6.8%
20210210 552
 
5.5%
20210222 522
 
5.2%
20210224 505
 
5.1%
20210223 495
 
5.0%
20210202 484
 
4.8%
20210215 448
 
4.5%
Other values (18) 3937
39.4%
ValueCountFrequency (%)
20210201 763
7.6%
20210202 484
4.8%
20210203 375
3.8%
20210204 308
3.1%
20210205 369
3.7%
20210206 85
 
0.9%
20210207 72
 
0.7%
20210208 374
3.7%
20210209 297
 
3.0%
20210210 552
5.5%
ValueCountFrequency (%)
20210228 830
8.3%
20210227 220
 
2.2%
20210226 781
7.8%
20210225 683
6.8%
20210224 505
5.1%
20210223 495
5.0%
20210222 522
5.2%
20210221 84
 
0.8%
20210220 97
 
1.0%
20210219 373
3.7%

금액
Real number (ℝ)

SKEWED 

Distinct3291
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245995.83
Minimum-1500000
Maximum79965600
Zeros18
Zeros (%)0.2%
Negative32
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T02:33:11.141840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1500000
5-th percentile200
Q12727
median30000
Q3100000
95-th percentile1000000
Maximum79965600
Range81465600
Interquartile range (IQR)97273

Descriptive statistics

Standard deviation1408279.9
Coefficient of variation (CV)5.724812
Kurtosis1219.3582
Mean245995.83
Median Absolute Deviation (MAD)29260
Skewness27.668135
Sum2.4599583 × 109
Variance1.9832522 × 1012
MonotonicityNot monotonic
2024-05-11T02:33:11.731142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 631
 
6.3%
100000 611
 
6.1%
30000 551
 
5.5%
200000 179
 
1.8%
70000 176
 
1.8%
150000 169
 
1.7%
60000 129
 
1.3%
80000 110
 
1.1%
40000 106
 
1.1%
20000 91
 
0.9%
Other values (3281) 7247
72.5%
ValueCountFrequency (%)
-1500000 1
 
< 0.1%
-401500 1
 
< 0.1%
-274180 1
 
< 0.1%
-200000 1
 
< 0.1%
-123933 1
 
< 0.1%
-110970 1
 
< 0.1%
-100000 3
< 0.1%
-85250 1
 
< 0.1%
-82600 1
 
< 0.1%
-80000 3
< 0.1%
ValueCountFrequency (%)
79965600 1
< 0.1%
38430740 1
< 0.1%
36294070 1
< 0.1%
35095100 1
< 0.1%
28340160 1
< 0.1%
27272727 1
< 0.1%
26120000 1
< 0.1%
18818180 1
< 0.1%
18281950 1
< 0.1%
17800000 1
< 0.1%

내용
Text

Distinct5799
Distinct (%)58.0%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:33:12.772327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length73
Mean length14.041729
Min length2

Characters and Unicode

Total characters140319
Distinct characters722
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

Unique5550 ?
Unique (%)55.5%

Sample

1st row관리비 연체료 수납
2nd row차단기 리모콘(1동 1406호)
3rd row2월분 주차장수익
4th row관리비 연체료 수납
5th row승강기사용료(104-101인테리어)
ValueCountFrequency (%)
관리비 3712
 
14.0%
수납 3538
 
13.4%
연체료 3536
 
13.4%
2월분 372
 
1.4%
승강기 364
 
1.4%
승강기사용료 320
 
1.2%
296
 
1.1%
1월분 292
 
1.1%
2월 262
 
1.0%
사용료 242
 
0.9%
Other values (7176) 13537
51.1%
2024-05-11T02:33:14.468703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16595
 
11.8%
료 5800
 
4.1%
1 5631
 
4.0%
0 5134
 
3.7%
수 5037
 
3.6%
2 4758
 
3.4%
리 4660
 
3.3%
비 4502
 
3.2%
관 3944
 
2.8%
체 3755
 
2.7%
Other values (712) 80503
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89583
63.8%
Decimal Number 22063
 
15.7%
Space Separator 16595
 
11.8%
Close Punctuation 2993
 
2.1%
Open Punctuation 2979
 
2.1%
Other Punctuation 2738
 
2.0%
Dash Punctuation 2266
 
1.6%
Uppercase Letter 624
 
0.4%
Math Symbol 293
 
0.2%
Lowercase Letter 116
 
0.1%
Other values (3) 69
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5800
 
6.5%
수 5037
 
5.6%
리 4660
 
5.2%
비 4502
 
5.0%
관 3944
 
4.4%
체 3755
 
4.2%
연 3601
 
4.0%
납 3589
 
4.0%
사 1908
 
2.1%
월 1899
 
2.1%
Other values (626) 50888
56.8%
Uppercase Letter
ValueCountFrequency (%)
N 68
 
10.9%
T 53
 
8.5%
A 48
 
7.7%
K 43
 
6.9%
O 42
 
6.7%
M 38
 
6.1%
C 38
 
6.1%
L 37
 
5.9%
D 35
 
5.6%
B 34
 
5.4%
Other values (14) 188
30.1%
Lowercase Letter
ValueCountFrequency (%)
o 41
35.3%
n 15
 
12.9%
x 10
 
8.6%
k 10
 
8.6%
e 8
 
6.9%
t 7
 
6.0%
s 5
 
4.3%
l 4
 
3.4%
b 3
 
2.6%
r 2
 
1.7%
Other values (9) 11
 
9.5%
Other Punctuation
ValueCountFrequency (%)
. 816
29.8%
/ 726
26.5%
, 639
23.3%
: 185
 
6.8%
? 178
 
6.5%
* 125
 
4.6%
@ 27
 
1.0%
% 21
 
0.8%
' 7
 
0.3%
; 4
 
0.1%
Other values (4) 10
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 5631
25.5%
0 5134
23.3%
2 4758
21.6%
3 1662
 
7.5%
4 1188
 
5.4%
5 1080
 
4.9%
6 749
 
3.4%
8 652
 
3.0%
7 637
 
2.9%
9 572
 
2.6%
Math Symbol
ValueCountFrequency (%)
~ 253
86.3%
> 12
 
4.1%
+ 10
 
3.4%
< 7
 
2.4%
× 6
 
2.0%
= 3
 
1.0%
→ 1
 
0.3%
⇒ 1
 
0.3%
Other Number
ValueCountFrequency (%)
⑧ 1
33.3%
② 1
33.3%
⑨ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2890
96.6%
] 103
 
3.4%
Open Punctuation
ValueCountFrequency (%)
( 2877
96.6%
[ 102
 
3.4%
Space Separator
ValueCountFrequency (%)
16595
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2266
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 65
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89578
63.8%
Common 49996
35.6%
Latin 740
 
0.5%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5800
 
6.5%
수 5037
 
5.6%
리 4660
 
5.2%
비 4502
 
5.0%
관 3944
 
4.4%
체 3755
 
4.2%
연 3601
 
4.0%
납 3589
 
4.0%
사 1908
 
2.1%
월 1899
 
2.1%
Other values (624) 50883
56.8%
Common
ValueCountFrequency (%)
16595
33.2%
1 5631
 
11.3%
0 5134
 
10.3%
2 4758
 
9.5%
) 2890
 
5.8%
( 2877
 
5.8%
- 2266
 
4.5%
3 1662
 
3.3%
4 1188
 
2.4%
5 1080
 
2.2%
Other values (33) 5915
 
11.8%
Latin
ValueCountFrequency (%)
N 68
 
9.2%
T 53
 
7.2%
A 48
 
6.5%
K 43
 
5.8%
O 42
 
5.7%
o 41
 
5.5%
M 38
 
5.1%
C 38
 
5.1%
L 37
 
5.0%
D 35
 
4.7%
Other values (33) 297
40.1%
Han
ValueCountFrequency (%)
入 4
80.0%
出 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89576
63.8%
ASCII 50724
36.1%
None 7
 
< 0.1%
CJK 5
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Arrows 2
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16595
32.7%
1 5631
 
11.1%
0 5134
 
10.1%
2 4758
 
9.4%
) 2890
 
5.7%
( 2877
 
5.7%
- 2266
 
4.5%
3 1662
 
3.3%
4 1188
 
2.3%
5 1080
 
2.1%
Other values (69) 6643
13.1%
Hangul
ValueCountFrequency (%)
료 5800
 
6.5%
수 5037
 
5.6%
리 4660
 
5.2%
비 4502
 
5.0%
관 3944
 
4.4%
체 3755
 
4.2%
연 3601
 
4.0%
납 3589
 
4.0%
사 1908
 
2.1%
월 1899
 
2.1%
Other values (622) 50881
56.8%
None
ValueCountFrequency (%)
× 6
85.7%
· 1
 
14.3%
CJK
ValueCountFrequency (%)
入 4
80.0%
出 1
 
20.0%
Enclosed Alphanum
ValueCountFrequency (%)
⑧ 1
33.3%
② 1
33.3%
⑨ 1
33.3%
Arrows
ValueCountFrequency (%)
→ 1
50.0%
⇒ 1
50.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
50.0%
ㅛ 1
50.0%

Interactions

2024-05-11T02:33:04.259438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:03.628974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:04.560754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:33:03.933530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:33:14.814485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3650.149
년월일0.3651.0000.060
금액0.1490.0601.000
2024-05-11T02:33:15.209155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0880.143
금액0.0881.0000.070
비용명0.1430.0701.000

Missing values

2024-05-11T02:33:05.103214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:33:05.598756image/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
53484은평뉴타운상림마을제3단지A41279908연체료수익202102226120관리비 연체료 수납
14233묵동금호어울림A13114103잡수익2021021610000차단기 리모콘(1동 1406호)
7299창신쌍용아파트 2단지A11077101주차장수익2021022834957202월분 주차장수익
2379힐스테이트녹번A10025836연체료수익202102019400관리비 연체료 수납
48203흑석한강센트레빌A15679107승강기수익2021021850000승강기사용료(104-101인테리어)
32497상계중앙하이츠2차A13920209연체료수익2021022342680관리비 연체료 수납
48538사당극동A15681503연체료수익2021022622660관리비 연체료 수납
5149역삼자이아파트A10027474승강기수익20210219150000102동 2504호 전출시 승강기 사용료
10724대원칸타빌A12185605고용안정사업수익2021022890000일자리안정자금(미화3명 1월분)
22393강남한양수자인A13520002광고료수익20210204100000광고료[시립수서청소년센터]
아파트명아파트코드비용명년월일금액내용
48316대방2차현대A15681104주차장수익202102288942802월분 주차비
34510상계주공14단지A13981903연체료수익20210223204770관리비 연체료 수납
32361성원(사슴4)A13905302잡수익20210210100000상가지하 스포츠센터
41180양평동양A15010602임대료수익20210202100000디자인바이조은 1월분 창고임대료
11836녹번현대2차A12283601잡수익20210228768002월분 재활용 기금(모아자원)
40695문래진주A15009501연체료수익2021020310관리비 연체료 수납
24483역삼래미안A13592706검침수익202102174515001월 검침수당
21506역삼한스빌아파트A13508005연체료수익202102104650관리비 연체료 수납
31990가락삼익맨션A13885306재활용품수익202102162275002월 재활용품 판매(현대자원)
25950성북힐스테이트A13613004연체료수익20210201440관리비 연체료 수납