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 = 28.0742699)Skewed

Reproduction

Analysis started2024-05-11 02:26:18.520260
Analysis finished2024-05-11 02:26:22.134548
Duration3.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2157
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:26:22.368830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.4714
Min length2

Characters and Unicode

Total characters74714
Distinct characters433
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

Unique239 ?
Unique (%)2.4%

Sample

1st rowSK허브진주상복합아파트
2nd row공덕자이 아파트
3rd row프라이어팰리스
4th row풍납시티극동
5th row힐스테이트상도센트럴파크
ValueCountFrequency (%)
아파트 180
 
1.7%
래미안 55
 
0.5%
e편한세상 39
 
0.4%
아이파크 31
 
0.3%
sk뷰 30
 
0.3%
고덕 25
 
0.2%
백련산 22
 
0.2%
트리마제 21
 
0.2%
헬리오시티아파트 20
 
0.2%
해모로 20
 
0.2%
Other values (2236) 10434
95.9%
2024-05-11T02:26:23.225624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2626
 
3.5%
파 2594
 
3.5%
트 2461
 
3.3%
지 2082
 
2.8%
대 1687
 
2.3%
단 1636
 
2.2%
이 1512
 
2.0%
동 1504
 
2.0%
차 1345
 
1.8%
신 1310
 
1.8%
Other values (423) 55957
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68226
91.3%
Decimal Number 3716
 
5.0%
Space Separator 980
 
1.3%
Uppercase Letter 883
 
1.2%
Lowercase Letter 350
 
0.5%
Open Punctuation 157
 
0.2%
Close Punctuation 157
 
0.2%
Dash Punctuation 124
 
0.2%
Other Punctuation 112
 
0.1%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2626
 
3.8%
파 2594
 
3.8%
트 2461
 
3.6%
지 2082
 
3.1%
대 1687
 
2.5%
단 1636
 
2.4%
이 1512
 
2.2%
동 1504
 
2.2%
차 1345
 
2.0%
신 1310
 
1.9%
Other values (378) 49469
72.5%
Uppercase Letter
ValueCountFrequency (%)
S 143
16.2%
C 120
13.6%
K 111
12.6%
M 96
10.9%
D 96
10.9%
L 64
7.2%
H 53
 
6.0%
I 41
 
4.6%
E 30
 
3.4%
A 29
 
3.3%
Other values (7) 100
11.3%
Lowercase Letter
ValueCountFrequency (%)
e 214
61.1%
s 28
 
8.0%
l 26
 
7.4%
k 24
 
6.9%
i 21
 
6.0%
v 14
 
4.0%
h 6
 
1.7%
g 5
 
1.4%
a 5
 
1.4%
c 4
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 1065
28.7%
2 1012
27.2%
3 517
13.9%
4 313
 
8.4%
5 246
 
6.6%
6 157
 
4.2%
7 132
 
3.6%
9 118
 
3.2%
8 99
 
2.7%
0 57
 
1.5%
Other Punctuation
ValueCountFrequency (%)
, 92
82.1%
. 20
 
17.9%
Space Separator
ValueCountFrequency (%)
980
100.0%
Open Punctuation
ValueCountFrequency (%)
( 157
100.0%
Close Punctuation
ValueCountFrequency (%)
) 157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68226
91.3%
Common 5246
 
7.0%
Latin 1242
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2626
 
3.8%
파 2594
 
3.8%
트 2461
 
3.6%
지 2082
 
3.1%
대 1687
 
2.5%
단 1636
 
2.4%
이 1512
 
2.2%
동 1504
 
2.2%
차 1345
 
2.0%
신 1310
 
1.9%
Other values (378) 49469
72.5%
Latin
ValueCountFrequency (%)
e 214
17.2%
S 143
11.5%
C 120
9.7%
K 111
8.9%
M 96
 
7.7%
D 96
 
7.7%
L 64
 
5.2%
H 53
 
4.3%
I 41
 
3.3%
E 30
 
2.4%
Other values (19) 274
22.1%
Common
ValueCountFrequency (%)
1 1065
20.3%
2 1012
19.3%
980
18.7%
3 517
9.9%
4 313
 
6.0%
5 246
 
4.7%
( 157
 
3.0%
) 157
 
3.0%
6 157
 
3.0%
7 132
 
2.5%
Other values (6) 510
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68226
91.3%
ASCII 6479
 
8.7%
Number Forms 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2626
 
3.8%
파 2594
 
3.8%
트 2461
 
3.6%
지 2082
 
3.1%
대 1687
 
2.5%
단 1636
 
2.4%
이 1512
 
2.2%
동 1504
 
2.2%
차 1345
 
2.0%
신 1310
 
1.9%
Other values (378) 49469
72.5%
ASCII
ValueCountFrequency (%)
1 1065
16.4%
2 1012
15.6%
980
15.1%
3 517
 
8.0%
4 313
 
4.8%
5 246
 
3.8%
e 214
 
3.3%
( 157
 
2.4%
) 157
 
2.4%
6 157
 
2.4%
Other values (34) 1661
25.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

아파트코드
Text

Distinct2164
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:26:23.961405image/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

Unique240 ?
Unique (%)2.4%

Sample

1st rowA13484004
2nd rowA10027906
3rd rowA13405003
4th rowA13804003
5th rowA15678103
ValueCountFrequency (%)
a10026988 21
 
0.2%
a10025850 20
 
0.2%
a15101508 19
 
0.2%
a10026180 18
 
0.2%
a10026370 17
 
0.2%
a10027817 17
 
0.2%
a14383205 17
 
0.2%
a13204409 17
 
0.2%
a13707010 16
 
0.2%
a13822004 16
 
0.2%
Other values (2154) 9822
98.2%
2024-05-11T02:26:25.143496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18780
20.9%
1 17183
19.1%
A 9993
11.1%
3 8742
9.7%
2 8238
9.2%
5 6327
 
7.0%
8 5490
 
6.1%
7 4951
 
5.5%
4 4076
 
4.5%
6 3410
 
3.8%
Other values (2) 2810
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
88.9%
Uppercase Letter 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18780
23.5%
1 17183
21.5%
3 8742
10.9%
2 8238
10.3%
5 6327
 
7.9%
8 5490
 
6.9%
7 4951
 
6.2%
4 4076
 
5.1%
6 3410
 
4.3%
9 2803
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
A 9993
99.9%
B 7
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18780
23.5%
1 17183
21.5%
3 8742
10.9%
2 8238
10.3%
5 6327
 
7.9%
8 5490
 
6.9%
7 4951
 
6.2%
4 4076
 
5.1%
6 3410
 
4.3%
9 2803
 
3.5%
Latin
ValueCountFrequency (%)
A 9993
99.9%
B 7
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18780
20.9%
1 17183
19.1%
A 9993
11.1%
3 8742
9.7%
2 8238
9.2%
5 6327
 
7.0%
8 5490
 
6.1%
7 4951
 
5.5%
4 4076
 
4.5%
6 3410
 
3.8%
Other values (2) 2810
 
3.1%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3473 
잡수익
1038 
승강기수익
1026 
주차장수익
941 
광고료수익
804 
Other values (10)
2718 

Length

Max length9
Median length5
Mean length5.0306
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3473
34.7%
잡수익 1038
 
10.4%
승강기수익 1026
 
10.3%
주차장수익 941
 
9.4%
광고료수익 804
 
8.0%
기타운영수익 780
 
7.8%
고용안정사업수익 517
 
5.2%
검침수익 332
 
3.3%
임대료수익 227
 
2.3%
재활용품수익 223
 
2.2%
Other values (5) 639
 
6.4%

Length

2024-05-11T02:26:25.551306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3473
34.7%
잡수익 1038
 
10.4%
승강기수익 1026
 
10.3%
주차장수익 941
 
9.4%
광고료수익 804
 
8.0%
기타운영수익 780
 
7.8%
고용안정사업수익 517
 
5.2%
검침수익 332
 
3.3%
임대료수익 227
 
2.3%
재활용품수익 223
 
2.2%
Other values (5) 639
 
6.4%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220117
Minimum20220101
Maximum20220131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:26:25.874729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220101
5-th percentile20220103
Q120220110
median20220118
Q320220126
95-th percentile20220131
Maximum20220131
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.3401317
Coefficient of variation (CV)4.6192273 × 10-7
Kurtosis-1.2974393
Mean20220117
Median Absolute Deviation (MAD)8
Skewness-0.18271243
Sum2.0220117 × 1011
Variance87.23806
MonotonicityNot monotonic
2024-05-11T02:26:26.254257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20220131 743
 
7.4%
20220128 599
 
6.0%
20220125 555
 
5.5%
20220103 538
 
5.4%
20220127 494
 
4.9%
20220110 493
 
4.9%
20220124 487
 
4.9%
20220120 473
 
4.7%
20220126 461
 
4.6%
20220114 460
 
4.6%
Other values (21) 4697
47.0%
ValueCountFrequency (%)
20220101 231
2.3%
20220102 145
 
1.5%
20220103 538
5.4%
20220104 387
3.9%
20220105 388
3.9%
20220106 320
3.2%
20220107 293
2.9%
20220108 81
 
0.8%
20220109 65
 
0.7%
20220110 493
4.9%
ValueCountFrequency (%)
20220131 743
7.4%
20220130 122
 
1.2%
20220129 160
 
1.6%
20220128 599
6.0%
20220127 494
4.9%
20220126 461
4.6%
20220125 555
5.5%
20220124 487
4.9%
20220123 102
 
1.0%
20220122 103
 
1.0%

금액
Real number (ℝ)

SKEWED 

Distinct3212
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean259556.64
Minimum-4536000
Maximum91460050
Zeros19
Zeros (%)0.2%
Negative44
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:26:26.609774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4536000
5-th percentile110
Q12017.75
median30000
Q3100000
95-th percentile969905
Maximum91460050
Range95996050
Interquartile range (IQR)97982.25

Descriptive statistics

Standard deviation1583182.4
Coefficient of variation (CV)6.0995642
Kurtosis1275.5661
Mean259556.64
Median Absolute Deviation (MAD)29500
Skewness28.07427
Sum2.5955664 × 109
Variance2.5064664 × 1012
MonotonicityNot monotonic
2024-05-11T02:26:26.966841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 550
 
5.5%
100000 522
 
5.2%
50000 473
 
4.7%
60000 182
 
1.8%
150000 179
 
1.8%
70000 143
 
1.4%
200000 124
 
1.2%
40000 106
 
1.1%
80000 100
 
1.0%
20000 87
 
0.9%
Other values (3202) 7534
75.3%
ValueCountFrequency (%)
-4536000 1
 
< 0.1%
-450000 1
 
< 0.1%
-374230 1
 
< 0.1%
-298460 1
 
< 0.1%
-260000 1
 
< 0.1%
-250000 1
 
< 0.1%
-167000 1
 
< 0.1%
-163715 1
 
< 0.1%
-100000 3
< 0.1%
-90000 1
 
< 0.1%
ValueCountFrequency (%)
91460050 1
< 0.1%
47488320 1
< 0.1%
33775500 1
< 0.1%
33758296 1
< 0.1%
30000000 1
< 0.1%
27370400 1
< 0.1%
27249600 1
< 0.1%
25228720 1
< 0.1%
23873420 1
< 0.1%
23461818 1
< 0.1%

내용
Text

Distinct5823
Distinct (%)58.3%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:26:27.504594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length69
Mean length14.380881
Min length2

Characters and Unicode

Total characters143665
Distinct characters731
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

Unique5565 ?
Unique (%)55.7%

Sample

1st row관리비 연체료 수납
2nd row116동 1104호 외5건 강습비외수입
3rd row일자리 안정자금 -경비
4th row01월 주차료 수익(입주민)
5th row게시판광고-홍건축디자인
ValueCountFrequency (%)
관리비 3606
 
13.5%
연체료 3481
 
13.0%
수납 3479
 
13.0%
355
 
1.3%
1월분 337
 
1.3%
12월분 310
 
1.2%
승강기 281
 
1.0%
1월 252
 
0.9%
승강기사용료 249
 
0.9%
입금 236
 
0.9%
Other values (7428) 14180
53.0%
2024-05-11T02:26:28.690904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16917
 
11.8%
1 6900
 
4.8%
료 5570
 
3.9%
0 5115
 
3.6%
수 4890
 
3.4%
2 4889
 
3.4%
리 4880
 
3.4%
비 4441
 
3.1%
관 3861
 
2.7%
체 3692
 
2.6%
Other values (721) 82510
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90471
63.0%
Decimal Number 23340
 
16.2%
Space Separator 16917
 
11.8%
Other Punctuation 3272
 
2.3%
Open Punctuation 3114
 
2.2%
Close Punctuation 3111
 
2.2%
Dash Punctuation 2252
 
1.6%
Uppercase Letter 638
 
0.4%
Math Symbol 330
 
0.2%
Lowercase Letter 121
 
0.1%
Other values (3) 99
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5570
 
6.2%
수 4890
 
5.4%
리 4880
 
5.4%
비 4441
 
4.9%
관 3861
 
4.3%
체 3692
 
4.1%
납 3600
 
4.0%
연 3555
 
3.9%
월 1998
 
2.2%
용 1739
 
1.9%
Other values (631) 52245
57.7%
Uppercase Letter
ValueCountFrequency (%)
N 85
13.3%
K 59
 
9.2%
T 48
 
7.5%
O 44
 
6.9%
B 43
 
6.7%
A 42
 
6.6%
L 42
 
6.6%
C 35
 
5.5%
S 34
 
5.3%
M 32
 
5.0%
Other values (15) 174
27.3%
Lowercase Letter
ValueCountFrequency (%)
o 46
38.0%
n 15
 
12.4%
t 11
 
9.1%
x 10
 
8.3%
k 6
 
5.0%
c 4
 
3.3%
p 4
 
3.3%
v 4
 
3.3%
s 4
 
3.3%
e 3
 
2.5%
Other values (10) 14
 
11.6%
Other Punctuation
ValueCountFrequency (%)
/ 839
25.6%
. 793
24.2%
, 742
22.7%
? 406
12.4%
* 198
 
6.1%
: 185
 
5.7%
@ 58
 
1.8%
% 17
 
0.5%
' 9
 
0.3%
& 8
 
0.2%
Other values (5) 17
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 6900
29.6%
0 5115
21.9%
2 4889
20.9%
3 1585
 
6.8%
4 1181
 
5.1%
5 1010
 
4.3%
6 826
 
3.5%
7 670
 
2.9%
8 626
 
2.7%
9 538
 
2.3%
Math Symbol
ValueCountFrequency (%)
~ 276
83.6%
+ 17
 
5.2%
> 13
 
3.9%
= 11
 
3.3%
× 5
 
1.5%
< 4
 
1.2%
→ 2
 
0.6%
⇒ 1
 
0.3%
÷ 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 3043
97.7%
[ 70
 
2.2%
{ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 3039
97.7%
] 72
 
2.3%
Other Symbol
ValueCountFrequency (%)
★ 2
66.7%
☞ 1
33.3%
Space Separator
ValueCountFrequency (%)
16917
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2252
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 95
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90459
63.0%
Common 52435
36.5%
Latin 759
 
0.5%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5570
 
6.2%
수 4890
 
5.4%
리 4880
 
5.4%
비 4441
 
4.9%
관 3861
 
4.3%
체 3692
 
4.1%
납 3600
 
4.0%
연 3555
 
3.9%
월 1998
 
2.2%
용 1739
 
1.9%
Other values (623) 52233
57.7%
Common
ValueCountFrequency (%)
16917
32.3%
1 6900
13.2%
0 5115
 
9.8%
2 4889
 
9.3%
( 3043
 
5.8%
) 3039
 
5.8%
- 2252
 
4.3%
3 1585
 
3.0%
4 1181
 
2.3%
5 1010
 
1.9%
Other values (35) 6504
 
12.4%
Latin
ValueCountFrequency (%)
N 85
 
11.2%
K 59
 
7.8%
T 48
 
6.3%
o 46
 
6.1%
O 44
 
5.8%
B 43
 
5.7%
A 42
 
5.5%
L 42
 
5.5%
C 35
 
4.6%
S 34
 
4.5%
Other values (35) 281
37.0%
Han
ValueCountFrequency (%)
入 4
33.3%
人 2
16.7%
名 1
 
8.3%
出 1
 
8.3%
用 1
 
8.3%
分 1
 
8.3%
外 1
 
8.3%
月 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90458
63.0%
ASCII 53175
37.0%
None 13
 
< 0.1%
CJK 12
 
< 0.1%
Misc Symbols 3
 
< 0.1%
Arrows 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16917
31.8%
1 6900
13.0%
0 5115
 
9.6%
2 4889
 
9.2%
( 3043
 
5.7%
) 3039
 
5.7%
- 2252
 
4.2%
3 1585
 
3.0%
4 1181
 
2.2%
5 1010
 
1.9%
Other values (72) 7244
13.6%
Hangul
ValueCountFrequency (%)
료 5570
 
6.2%
수 4890
 
5.4%
리 4880
 
5.4%
비 4441
 
4.9%
관 3861
 
4.3%
체 3692
 
4.1%
납 3600
 
4.0%
연 3555
 
3.9%
월 1998
 
2.2%
용 1739
 
1.9%
Other values (622) 52232
57.7%
None
ValueCountFrequency (%)
× 5
38.5%
？ 5
38.5%
· 2
 
15.4%
÷ 1
 
7.7%
CJK
ValueCountFrequency (%)
入 4
33.3%
人 2
16.7%
名 1
 
8.3%
出 1
 
8.3%
用 1
 
8.3%
分 1
 
8.3%
外 1
 
8.3%
月 1
 
8.3%
Misc Symbols
ValueCountFrequency (%)
★ 2
66.7%
☞ 1
33.3%
Arrows
ValueCountFrequency (%)
→ 2
66.7%
⇒ 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㅊ 1
100.0%

Interactions

2024-05-11T02:26:20.847810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:20.352447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:21.137114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:20.637645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:26:28.960046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4390.153
년월일0.4391.0000.103
금액0.1530.1031.000
2024-05-11T02:26:29.237989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0450.180
금액0.0451.0000.072
비용명0.1800.0721.000

Missing values

2024-05-11T02:26:21.474618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:26:21.845144image/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
24518SK허브진주상복합아파트A13484004연체료수익20220124940관리비 연체료 수납
7808공덕자이 아파트A10027906기타운영수익20220112923130116동 1104호 외5건 강습비외수입
23448프라이어팰리스A13405003고용안정사업수익20220126240000일자리 안정자금 -경비
33617풍납시티극동A13804003주차장수익20220131297806001월 주차료 수익(입주민)
53167힐스테이트상도센트럴파크A15678103승강기수익20220126100000게시판광고-홍건축디자인
41965한가람아파트A14072701승강기수익20220103150000216동 1104호 승강기사용료(인테리어_00098)
33229잠원훼미리 아파트A13790612검침수익20220125119760한전 검침수당 입금
49620신도림디큐브시티A15277302재활용품수익202201031000001월분 재활용수거료(삼양글로벌)6/24 차감
34235래미안송파파인탑A13817001임대료수익202201249600000SK중계기임대료(2022.02.01~2023.01.31)
6446보문파크뷰자이아파트A10027189임대료수익2022012716500001월분 어린이집임대료(아뜰리에어린이집)
아파트명아파트코드비용명년월일금액내용
38406화랑해링턴플레이스A13980413잡수익2022010350000명가인테리어
23378성내삼성A13403101연체료수익2022012815380관리비 연체료 수납
49506오류동 영풍마드레빌A15210212연체료수익2022012823700관리비 연체료 수납
58710신월시영아파트A15884703연체료수익202201126310관리비 연체료 수납
53038신동아리버파크제2관리사무소A15676701재활용품수익20220131650000재활용수익금(21년도 이월금액)
14843답십리두산위브A13003003광고료수익20220117120000(오상현)경송한의원 광고 4주(게시판)
50612궁동우신빌라A15288301연체료수익20220122380관리비 연체료 수납
24230고덕리엔파크3단지A13472701연체료수익20220131164220관리비 연체료 수납
54397염창1차보람더하임아파트A15704007주차장수익202201035000012월 외부차량 주차료(윤나경 42두0725)
49606서울수목원현대홈타운스위트A15271601연체료수익202201287590관리비 연체료 수납