Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells14
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 = 39.41946437)Skewed

Reproduction

Analysis started2024-05-11 02:28:42.962862
Analysis finished2024-05-11 02:28:47.604636
Duration4.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2195
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:28:47.897434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.4731
Min length2

Characters and Unicode

Total characters74731
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

Unique254 ?
Unique (%)2.5%

Sample

1st row천왕연지타운2단지
2nd row홍제청구3차
3rd row천호동아코아
4th row신구로자이
5th row방학명품ESA2단지
ValueCountFrequency (%)
아파트 211
 
1.9%
래미안 55
 
0.5%
e편한세상 40
 
0.4%
아이파크 29
 
0.3%
고덕 23
 
0.2%
백련산 23
 
0.2%
해모로 22
 
0.2%
영등포 21
 
0.2%
sk뷰 20
 
0.2%
잠실엘스아파트 20
 
0.2%
Other values (2275) 10461
95.8%
2024-05-11T02:28:49.112962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2636
 
3.5%
파 2565
 
3.4%
트 2559
 
3.4%
지 2106
 
2.8%
단 1636
 
2.2%
대 1593
 
2.1%
이 1535
 
2.1%
동 1518
 
2.0%
신 1329
 
1.8%
차 1264
 
1.7%
Other values (424) 55990
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68347
91.5%
Decimal Number 3621
 
4.8%
Space Separator 1042
 
1.4%
Uppercase Letter 909
 
1.2%
Lowercase Letter 317
 
0.4%
Open Punctuation 132
 
0.2%
Close Punctuation 132
 
0.2%
Dash Punctuation 110
 
0.1%
Other Punctuation 109
 
0.1%
Letter Number 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2636
 
3.9%
파 2565
 
3.8%
트 2559
 
3.7%
지 2106
 
3.1%
단 1636
 
2.4%
대 1593
 
2.3%
이 1535
 
2.2%
동 1518
 
2.2%
신 1329
 
1.9%
차 1264
 
1.8%
Other values (379) 49606
72.6%
Uppercase Letter
ValueCountFrequency (%)
S 152
16.7%
K 117
12.9%
C 113
12.4%
M 94
10.3%
D 94
10.3%
H 64
7.0%
L 56
 
6.2%
I 39
 
4.3%
E 38
 
4.2%
A 36
 
4.0%
Other values (7) 106
11.7%
Lowercase Letter
ValueCountFrequency (%)
e 202
63.7%
l 27
 
8.5%
i 22
 
6.9%
k 15
 
4.7%
s 13
 
4.1%
v 11
 
3.5%
g 7
 
2.2%
a 7
 
2.2%
h 5
 
1.6%
c 4
 
1.3%
Decimal Number
ValueCountFrequency (%)
1 1042
28.8%
2 974
26.9%
3 494
13.6%
4 305
 
8.4%
5 237
 
6.5%
6 176
 
4.9%
7 147
 
4.1%
9 107
 
3.0%
8 79
 
2.2%
0 60
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 89
81.7%
. 20
 
18.3%
Space Separator
ValueCountFrequency (%)
1042
100.0%
Open Punctuation
ValueCountFrequency (%)
( 132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68347
91.5%
Common 5146
 
6.9%
Latin 1238
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2636
 
3.9%
파 2565
 
3.8%
트 2559
 
3.7%
지 2106
 
3.1%
단 1636
 
2.4%
대 1593
 
2.3%
이 1535
 
2.2%
동 1518
 
2.2%
신 1329
 
1.9%
차 1264
 
1.8%
Other values (379) 49606
72.6%
Latin
ValueCountFrequency (%)
e 202
16.3%
S 152
12.3%
K 117
9.5%
C 113
9.1%
M 94
 
7.6%
D 94
 
7.6%
H 64
 
5.2%
L 56
 
4.5%
I 39
 
3.2%
E 38
 
3.1%
Other values (19) 269
21.7%
Common
ValueCountFrequency (%)
1 1042
20.2%
1042
20.2%
2 974
18.9%
3 494
9.6%
4 305
 
5.9%
5 237
 
4.6%
6 176
 
3.4%
7 147
 
2.9%
( 132
 
2.6%
) 132
 
2.6%
Other values (6) 465
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68347
91.5%
ASCII 6372
 
8.5%
Number Forms 12
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2636
 
3.9%
파 2565
 
3.8%
트 2559
 
3.7%
지 2106
 
3.1%
단 1636
 
2.4%
대 1593
 
2.3%
이 1535
 
2.2%
동 1518
 
2.2%
신 1329
 
1.9%
차 1264
 
1.8%
Other values (379) 49606
72.6%
ASCII
ValueCountFrequency (%)
1 1042
16.4%
1042
16.4%
2 974
15.3%
3 494
 
7.8%
4 305
 
4.8%
5 237
 
3.7%
e 202
 
3.2%
6 176
 
2.8%
S 152
 
2.4%
7 147
 
2.3%
Other values (34) 1601
25.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 12
100.0%

아파트코드
Text

Distinct2200
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:28:50.271279image/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

Unique255 ?
Unique (%)2.5%

Sample

1st rowA15213007
2nd rowA12078706
3rd rowA13475001
4th rowA15205508
5th rowA13272101
ValueCountFrequency (%)
a13822004 20
 
0.2%
a12175203 19
 
0.2%
a14272304 18
 
0.2%
a15678103 18
 
0.2%
a13570501 18
 
0.2%
a13606004 18
 
0.2%
a13527203 17
 
0.2%
a13822002 17
 
0.2%
a10025614 17
 
0.2%
a13509010 16
 
0.2%
Other values (2190) 9822
98.2%
2024-05-11T02:28:51.906320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18926
21.0%
1 17010
18.9%
A 9993
11.1%
3 8585
9.5%
2 8408
9.3%
5 6335
 
7.0%
8 5358
 
6.0%
7 4887
 
5.4%
4 4140
 
4.6%
6 3343
 
3.7%
Other values (2) 3015
 
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 18926
23.7%
1 17010
21.3%
3 8585
10.7%
2 8408
10.5%
5 6335
 
7.9%
8 5358
 
6.7%
7 4887
 
6.1%
4 4140
 
5.2%
6 3343
 
4.2%
9 3008
 
3.8%
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 18926
23.7%
1 17010
21.3%
3 8585
10.7%
2 8408
10.5%
5 6335
 
7.9%
8 5358
 
6.7%
7 4887
 
6.1%
4 4140
 
5.2%
6 3343
 
4.2%
9 3008
 
3.8%
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 18926
21.0%
1 17010
18.9%
A 9993
11.1%
3 8585
9.5%
2 8408
9.3%
5 6335
 
7.0%
8 5358
 
6.0%
7 4887
 
5.4%
4 4140
 
4.6%
6 3343
 
3.7%
Other values (2) 3015
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3664 
잡수익
1148 
승강기수익
1012 
주차장수익
934 
광고료수익
901 
Other values (10)
2341 

Length

Max length9
Median length5
Mean length4.8619
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연체료수익
2nd row연체료수익
3rd row연체료수익
4th row연체료수익
5th row재활용품수익

Common Values

ValueCountFrequency (%)
연체료수익 3664
36.6%
잡수익 1148
 
11.5%
승강기수익 1012
 
10.1%
주차장수익 934
 
9.3%
광고료수익 901
 
9.0%
기타운영수익 893
 
8.9%
검침수익 324
 
3.2%
부과차익 242
 
2.4%
임대료수익 240
 
2.4%
재활용품수익 227
 
2.3%
Other values (5) 415
 
4.2%

Length

2024-05-11T02:28:52.470515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3664
36.6%
잡수익 1148
 
11.5%
승강기수익 1012
 
10.1%
주차장수익 934
 
9.3%
광고료수익 901
 
9.0%
기타운영수익 893
 
8.9%
검침수익 324
 
3.2%
부과차익 242
 
2.4%
임대료수익 240
 
2.4%
재활용품수익 227
 
2.3%
Other values (5) 415
 
4.2%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220717
Minimum20220701
Maximum20220731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:28:53.101433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220701
5-th percentile20220701
Q120220708
median20220719
Q320220726
95-th percentile20220731
Maximum20220731
Range30
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.6686591
Coefficient of variation (CV)4.7815609 × 10-7
Kurtosis-1.3345118
Mean20220717
Median Absolute Deviation (MAD)8
Skewness-0.18237323
Sum2.0220717 × 1011
Variance93.482968
MonotonicityNot monotonic
2024-05-11T02:28:53.551542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20220731 745
 
7.4%
20220725 633
 
6.3%
20220729 572
 
5.7%
20220701 556
 
5.6%
20220711 556
 
5.6%
20220704 504
 
5.0%
20220726 432
 
4.3%
20220705 431
 
4.3%
20220727 423
 
4.2%
20220728 394
 
3.9%
Other values (21) 4754
47.5%
ValueCountFrequency (%)
20220701 556
5.6%
20220702 122
 
1.2%
20220703 123
 
1.2%
20220704 504
5.0%
20220705 431
4.3%
20220706 337
3.4%
20220707 276
2.8%
20220708 312
3.1%
20220709 82
 
0.8%
20220710 68
 
0.7%
ValueCountFrequency (%)
20220731 745
7.4%
20220730 191
 
1.9%
20220729 572
5.7%
20220728 394
3.9%
20220727 423
4.2%
20220726 432
4.3%
20220725 633
6.3%
20220724 153
 
1.5%
20220723 127
 
1.3%
20220722 373
3.7%

금액
Real number (ℝ)

SKEWED 

Distinct3157
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296157.53
Minimum-400000
Maximum1.6938 × 108
Zeros20
Zeros (%)0.2%
Negative37
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:28:54.291033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-400000
5-th percentile80
Q11840
median25000
Q3100000
95-th percentile983692.7
Maximum1.6938 × 108
Range1.6978 × 108
Interquartile range (IQR)98160

Descriptive statistics

Standard deviation2555686.8
Coefficient of variation (CV)8.6294846
Kurtosis2186.8245
Mean296157.53
Median Absolute Deviation (MAD)24695
Skewness39.419464
Sum2.9615753 × 109
Variance6.5315351 × 1012
MonotonicityNot monotonic
2024-05-11T02:28:55.034299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 599
 
6.0%
30000 505
 
5.1%
100000 480
 
4.8%
40000 155
 
1.6%
70000 147
 
1.5%
60000 137
 
1.4%
150000 131
 
1.3%
20000 117
 
1.2%
200000 110
 
1.1%
80000 103
 
1.0%
Other values (3147) 7516
75.2%
ValueCountFrequency (%)
-400000 1
 
< 0.1%
-275000 1
 
< 0.1%
-241610 1
 
< 0.1%
-125000 1
 
< 0.1%
-110000 1
 
< 0.1%
-100000 2
< 0.1%
-75270 1
 
< 0.1%
-50000 3
< 0.1%
-38780 1
 
< 0.1%
-37560 1
 
< 0.1%
ValueCountFrequency (%)
169380000 1
< 0.1%
81903750 1
< 0.1%
76847935 1
< 0.1%
73174000 1
< 0.1%
35052000 1
< 0.1%
33624800 1
< 0.1%
31575500 1
< 0.1%
30005730 1
< 0.1%
30000000 1
< 0.1%
27885131 1
< 0.1%

내용
Text

Distinct5679
Distinct (%)56.9%
Missing14
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:28:56.423761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length69
Mean length14.206189
Min length2

Characters and Unicode

Total characters141863
Distinct characters758
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

Unique5427 ?
Unique (%)54.3%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row관리비 연체료 수납
4th row관리비 연체료 수납
5th row재활용품 판매수입- 5월분 차액 추가분 110000-92730
ValueCountFrequency (%)
관리비 3819
 
14.0%
수납 3671
 
13.5%
연체료 3669
 
13.5%
7월분 346
 
1.3%
326
 
1.2%
승강기 312
 
1.1%
7월 281
 
1.0%
사용료 226
 
0.8%
6월분 223
 
0.8%
승강기사용료 217
 
0.8%
Other values (7445) 14100
51.9%
2024-05-11T02:28:58.385023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17551
 
12.4%
료 5860
 
4.1%
수 5208
 
3.7%
0 4875
 
3.4%
1 4544
 
3.2%
비 4459
 
3.1%
리 4327
 
3.1%
관 4026
 
2.8%
체 3890
 
2.7%
납 3804
 
2.7%
Other values (748) 83319
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89662
63.2%
Decimal Number 22066
 
15.6%
Space Separator 17551
 
12.4%
Close Punctuation 2958
 
2.1%
Open Punctuation 2946
 
2.1%
Other Punctuation 2938
 
2.1%
Dash Punctuation 2427
 
1.7%
Uppercase Letter 716
 
0.5%
Math Symbol 371
 
0.3%
Lowercase Letter 134
 
0.1%
Other values (2) 94
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5860
 
6.5%
수 5208
 
5.8%
비 4459
 
5.0%
리 4327
 
4.8%
관 4026
 
4.5%
체 3890
 
4.3%
납 3804
 
4.2%
연 3754
 
4.2%
용 1790
 
2.0%
사 1731
 
1.9%
Other values (656) 50813
56.7%
Uppercase Letter
ValueCountFrequency (%)
N 73
 
10.2%
B 59
 
8.2%
K 56
 
7.8%
C 54
 
7.5%
T 52
 
7.3%
A 46
 
6.4%
L 44
 
6.1%
O 42
 
5.9%
G 41
 
5.7%
D 38
 
5.3%
Other values (15) 211
29.5%
Lowercase Letter
ValueCountFrequency (%)
o 34
25.4%
n 14
10.4%
k 12
 
9.0%
s 10
 
7.5%
e 10
 
7.5%
t 8
 
6.0%
b 6
 
4.5%
x 5
 
3.7%
c 5
 
3.7%
f 4
 
3.0%
Other values (13) 26
19.4%
Other Punctuation
ValueCountFrequency (%)
/ 873
29.7%
. 821
27.9%
, 601
20.5%
? 272
 
9.3%
: 188
 
6.4%
* 92
 
3.1%
@ 32
 
1.1%
% 27
 
0.9%
& 13
 
0.4%
# 7
 
0.2%
Other values (6) 12
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 4875
22.1%
1 4544
20.6%
2 3733
16.9%
7 2164
9.8%
3 1602
 
7.3%
6 1338
 
6.1%
4 1211
 
5.5%
5 1117
 
5.1%
8 892
 
4.0%
9 590
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 303
81.7%
+ 28
 
7.5%
× 13
 
3.5%
> 10
 
2.7%
= 8
 
2.2%
< 6
 
1.6%
∼ 1
 
0.3%
⇒ 1
 
0.3%
→ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2889
97.7%
] 69
 
2.3%
Open Punctuation
ValueCountFrequency (%)
( 2876
97.6%
[ 70
 
2.4%
Other Symbol
ValueCountFrequency (%)
㎏ 1
50.0%
㈜ 1
50.0%
Space Separator
ValueCountFrequency (%)
17551
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2427
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89654
63.2%
Common 51350
36.2%
Latin 850
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5860
 
6.5%
수 5208
 
5.8%
비 4459
 
5.0%
리 4327
 
4.8%
관 4026
 
4.5%
체 3890
 
4.3%
납 3804
 
4.2%
연 3754
 
4.2%
용 1790
 
2.0%
사 1731
 
1.9%
Other values (650) 50805
56.7%
Latin
ValueCountFrequency (%)
N 73
 
8.6%
B 59
 
6.9%
K 56
 
6.6%
C 54
 
6.4%
T 52
 
6.1%
A 46
 
5.4%
L 44
 
5.2%
O 42
 
4.9%
G 41
 
4.8%
D 38
 
4.5%
Other values (38) 345
40.6%
Common
ValueCountFrequency (%)
17551
34.2%
0 4875
 
9.5%
1 4544
 
8.8%
2 3733
 
7.3%
) 2889
 
5.6%
( 2876
 
5.6%
- 2427
 
4.7%
7 2164
 
4.2%
3 1602
 
3.1%
6 1338
 
2.6%
Other values (33) 7351
14.3%
Han
ValueCountFrequency (%)
入 3
33.3%
人 1
 
11.1%
內 1
 
11.1%
大 1
 
11.1%
用 1
 
11.1%
女 1
 
11.1%
出 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89653
63.2%
ASCII 52181
36.8%
None 16
 
< 0.1%
CJK 8
 
< 0.1%
Arrows 2
 
< 0.1%
Math Operators 1
 
< 0.1%
CJK Compat 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17551
33.6%
0 4875
 
9.3%
1 4544
 
8.7%
2 3733
 
7.2%
) 2889
 
5.5%
( 2876
 
5.5%
- 2427
 
4.7%
7 2164
 
4.1%
3 1602
 
3.1%
6 1338
 
2.6%
Other values (75) 8182
15.7%
Hangul
ValueCountFrequency (%)
료 5860
 
6.5%
수 5208
 
5.8%
비 4459
 
5.0%
리 4327
 
4.8%
관 4026
 
4.5%
체 3890
 
4.3%
납 3804
 
4.2%
연 3754
 
4.2%
용 1790
 
2.0%
사 1731
 
1.9%
Other values (649) 50804
56.7%
None
ValueCountFrequency (%)
× 13
81.2%
· 2
 
12.5%
㈜ 1
 
6.2%
CJK
ValueCountFrequency (%)
入 3
37.5%
人 1
 
12.5%
內 1
 
12.5%
大 1
 
12.5%
用 1
 
12.5%
出 1
 
12.5%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
Arrows
ValueCountFrequency (%)
⇒ 1
50.0%
→ 1
50.0%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
女 1
100.0%

Interactions

2024-05-11T02:28:46.080921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:28:45.336606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:28:46.374091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:28:45.734655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:28:58.659007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3440.213
년월일0.3441.0000.041
금액0.2130.0411.000
2024-05-11T02:28:58.905247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0140.135
금액0.0141.0000.092
비용명0.1350.0921.000

Missing values

2024-05-11T02:28:46.800658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:28:47.417113image/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
50216천왕연지타운2단지A15213007연체료수익202207072010관리비 연체료 수납
11372홍제청구3차A12078706연체료수익2022070140관리비 연체료 수납
24657천호동아코아A13475001연체료수익202207041420관리비 연체료 수납
49409신구로자이A15205508연체료수익20220727100관리비 연체료 수납
20314방학명품ESA2단지A13272101재활용품수익2022070115700재활용품 판매수입- 5월분 차액 추가분 110000-92730
12674월드컵아이파크1단지A12171101연체료수익20220726260관리비 연체료 수납
32712서초호반써밋A13778211연체료수익202207302210관리비 연체료 수납
42379한가람아파트A14072701임대료수익20220715200000독서실-4명(4명*50,000원)
47084대림한신2차A15081802부과차익202207212306월분부과차익
7647강남효성해링턴코트A10027558승강기수익20220726150000승강기사용료 수입 (109-203 공사)
아파트명아파트코드비용명년월일금액내용
48452관악우성아파트A15105603연체료수익202207061270관리비 연체료 수납
8489텐즈힐1단지A10027920기타운영수익2022072080006월분 어린이집 휴카페이용요금
55171마곡엠밸리6단지A15721006승강기수익20220708-110000602동308호(유승우) 승강기이용료 환불 (기안:22-259)
6244래미안강동팰리스A10026852연체료수익20220702150관리비 연체료 수납
47870신길자이A15096001이자수익2022071845기업(관리비)통장 예금결산이자
56053가양강나루현대A15780401임대료수익202207083360007월 필라테스 임대료
13239상암월드컵파크9단지A12179504연체료수익20220707760관리비 연체료 수납
52237남서울건영아파트A15386404주차장수익2022070460000홍규택 외부주차료 입금
12159서강쌍용예가A12119006기타운영수익2022072710000110-801 헬스키 반납대금
52632래미안상도3차A15603006임대료수익202207111300007월분 우리은행 CD기 임대료