Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells9
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 = 96.97742338)Skewed

Reproduction

Analysis started2024-05-11 02:29:56.238570
Analysis finished2024-05-11 02:30:01.276610
Duration5.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2189
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:30:01.688697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.4352
Min length2

Characters and Unicode

Total characters74352
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

Unique222 ?
Unique (%)2.2%

Sample

1st row쌍문한양6차
2nd row롯데캐슬
3rd row신성둔촌미소지움2차
4th row양재리본타워1단지
5th row백련산 sk뷰 아이파크
ValueCountFrequency (%)
아파트 180
 
1.7%
래미안 45
 
0.4%
아이파크 39
 
0.4%
고덕 25
 
0.2%
e편한세상 25
 
0.2%
북한산 24
 
0.2%
마포래미안푸르지오 23
 
0.2%
sk뷰 22
 
0.2%
센트럴 21
 
0.2%
역삼아이파크 20
 
0.2%
Other values (2268) 10448
96.1%
2024-05-11T02:30:03.164356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2612
 
3.5%
파 2553
 
3.4%
트 2445
 
3.3%
지 2081
 
2.8%
대 1689
 
2.3%
단 1613
 
2.2%
이 1518
 
2.0%
동 1517
 
2.0%
차 1319
 
1.8%
신 1247
 
1.7%
Other values (424) 55758
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67885
91.3%
Decimal Number 3674
 
4.9%
Space Separator 972
 
1.3%
Uppercase Letter 908
 
1.2%
Lowercase Letter 357
 
0.5%
Close Punctuation 149
 
0.2%
Open Punctuation 149
 
0.2%
Dash Punctuation 137
 
0.2%
Other Punctuation 114
 
0.2%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2612
 
3.8%
파 2553
 
3.8%
트 2445
 
3.6%
지 2081
 
3.1%
대 1689
 
2.5%
단 1613
 
2.4%
이 1518
 
2.2%
동 1517
 
2.2%
차 1319
 
1.9%
신 1247
 
1.8%
Other values (379) 49291
72.6%
Uppercase Letter
ValueCountFrequency (%)
S 169
18.6%
K 109
12.0%
C 103
11.3%
D 86
9.5%
M 86
9.5%
L 77
8.5%
H 69
7.6%
E 41
 
4.5%
I 39
 
4.3%
V 33
 
3.6%
Other values (7) 96
10.6%
Lowercase Letter
ValueCountFrequency (%)
e 202
56.6%
l 36
 
10.1%
i 28
 
7.8%
s 27
 
7.6%
k 21
 
5.9%
v 20
 
5.6%
w 10
 
2.8%
h 9
 
2.5%
c 2
 
0.6%
g 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 1132
30.8%
2 1031
28.1%
3 453
12.3%
4 261
 
7.1%
5 241
 
6.6%
6 156
 
4.2%
7 146
 
4.0%
9 101
 
2.7%
8 79
 
2.2%
0 74
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 93
81.6%
. 21
 
18.4%
Space Separator
ValueCountFrequency (%)
972
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 137
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67885
91.3%
Common 5195
 
7.0%
Latin 1272
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2612
 
3.8%
파 2553
 
3.8%
트 2445
 
3.6%
지 2081
 
3.1%
대 1689
 
2.5%
단 1613
 
2.4%
이 1518
 
2.2%
동 1517
 
2.2%
차 1319
 
1.9%
신 1247
 
1.8%
Other values (379) 49291
72.6%
Latin
ValueCountFrequency (%)
e 202
15.9%
S 169
13.3%
K 109
 
8.6%
C 103
 
8.1%
D 86
 
6.8%
M 86
 
6.8%
L 77
 
6.1%
H 69
 
5.4%
E 41
 
3.2%
I 39
 
3.1%
Other values (19) 291
22.9%
Common
ValueCountFrequency (%)
1 1132
21.8%
2 1031
19.8%
972
18.7%
3 453
8.7%
4 261
 
5.0%
5 241
 
4.6%
6 156
 
3.0%
) 149
 
2.9%
( 149
 
2.9%
7 146
 
2.8%
Other values (6) 505
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67885
91.3%
ASCII 6460
 
8.7%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2612
 
3.8%
파 2553
 
3.8%
트 2445
 
3.6%
지 2081
 
3.1%
대 1689
 
2.5%
단 1613
 
2.4%
이 1518
 
2.2%
동 1517
 
2.2%
차 1319
 
1.9%
신 1247
 
1.8%
Other values (379) 49291
72.6%
ASCII
ValueCountFrequency (%)
1 1132
17.5%
2 1031
16.0%
972
15.0%
3 453
 
7.0%
4 261
 
4.0%
5 241
 
3.7%
e 202
 
3.1%
S 169
 
2.6%
6 156
 
2.4%
) 149
 
2.3%
Other values (34) 1694
26.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2195
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:30:04.134204image/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

Unique224 ?
Unique (%)2.2%

Sample

1st rowA13286107
2nd rowA15807205
3rd rowA13470502
4th rowA13713001
5th rowA10025310
ValueCountFrequency (%)
a12175203 23
 
0.2%
a13508009 20
 
0.2%
a15805115 18
 
0.2%
a12179004 17
 
0.2%
a10026232 17
 
0.2%
a15728009 17
 
0.2%
a15101504 17
 
0.2%
a10025614 16
 
0.2%
a13824006 16
 
0.2%
a13822003 16
 
0.2%
Other values (2185) 9823
98.2%
2024-05-11T02:30:05.550298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18838
20.9%
1 17239
19.2%
A 9995
11.1%
3 8786
9.8%
2 8219
9.1%
5 6354
 
7.1%
8 5443
 
6.0%
7 4727
 
5.3%
4 3977
 
4.4%
6 3503
 
3.9%
Other values (2) 2919
 
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 18838
23.5%
1 17239
21.5%
3 8786
11.0%
2 8219
10.3%
5 6354
 
7.9%
8 5443
 
6.8%
7 4727
 
5.9%
4 3977
 
5.0%
6 3503
 
4.4%
9 2914
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9995
> 99.9%
B 5
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18838
23.5%
1 17239
21.5%
3 8786
11.0%
2 8219
10.3%
5 6354
 
7.9%
8 5443
 
6.8%
7 4727
 
5.9%
4 3977
 
5.0%
6 3503
 
4.4%
9 2914
 
3.6%
Latin
ValueCountFrequency (%)
A 9995
> 99.9%
B 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18838
20.9%
1 17239
19.2%
A 9995
11.1%
3 8786
9.8%
2 8219
9.1%
5 6354
 
7.1%
8 5443
 
6.0%
7 4727
 
5.3%
4 3977
 
4.4%
6 3503
 
3.9%
Other values (2) 2919
 
3.2%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3389 
승강기수익
1007 
잡수익
983 
주차장수익
825 
광고료수익
816 
Other values (10)
2980 

Length

Max length9
Median length5
Mean length4.9588
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자산수증이익
2nd row연체료수익
3rd row연체료수익
4th row잡수익
5th row기타운영수익

Common Values

ValueCountFrequency (%)
연체료수익 3389
33.9%
승강기수익 1007
 
10.1%
잡수익 983
 
9.8%
주차장수익 825
 
8.2%
광고료수익 816
 
8.2%
기타운영수익 689
 
6.9%
이자수익 665
 
6.7%
고용안정사업수익 467
 
4.7%
검침수익 296
 
3.0%
알뜰시장수익 241
 
2.4%
Other values (5) 622
 
6.2%

Length

2024-05-11T02:30:06.080733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3389
33.9%
승강기수익 1007
 
10.1%
잡수익 983
 
9.8%
주차장수익 825
 
8.2%
광고료수익 816
 
8.2%
기타운영수익 689
 
6.9%
이자수익 665
 
6.7%
고용안정사업수익 467
 
4.7%
검침수익 296
 
3.0%
알뜰시장수익 241
 
2.4%
Other values (5) 622
 
6.2%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20220318
Minimum20220301
Maximum20220331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:30:06.470282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20220301
5-th percentile20220302
Q120220310
median20220318
Q320220326
95-th percentile20220331
Maximum20220331
Range30
Interquartile range (IQR)16

Descriptive statistics

Standard deviation9.5733702
Coefficient of variation (CV)4.73453 × 10-7
Kurtosis-1.2304845
Mean20220318
Median Absolute Deviation (MAD)8
Skewness-0.21461614
Sum2.0220318 × 1011
Variance91.649417
MonotonicityNot monotonic
2024-05-11T02:30:06.884380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20220331 928
 
9.3%
20220302 497
 
5.0%
20220325 479
 
4.8%
20220330 477
 
4.8%
20220310 463
 
4.6%
20220328 442
 
4.4%
20220315 442
 
4.4%
20220329 410
 
4.1%
20220324 395
 
4.0%
20220316 390
 
3.9%
Other values (21) 5077
50.8%
ValueCountFrequency (%)
20220301 204
2.0%
20220302 497
5.0%
20220303 390
3.9%
20220304 385
3.9%
20220305 98
 
1.0%
20220306 79
 
0.8%
20220307 345
3.5%
20220308 274
2.7%
20220309 63
 
0.6%
20220310 463
4.6%
ValueCountFrequency (%)
20220331 928
9.3%
20220330 477
4.8%
20220329 410
4.1%
20220328 442
4.4%
20220327 223
 
2.2%
20220326 164
 
1.6%
20220325 479
4.8%
20220324 395
4.0%
20220323 332
 
3.3%
20220322 303
 
3.0%

금액
Real number (ℝ)

SKEWED 

Distinct3518
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean295455.67
Minimum-4466430
Maximum7.92 × 108
Zeros8
Zeros (%)0.1%
Negative35
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:30:07.305505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4466430
5-th percentile160
Q12320
median28160
Q3100000
95-th percentile820142.5
Maximum7.92 × 108
Range7.9646643 × 108
Interquartile range (IQR)97680

Descriptive statistics

Standard deviation8000940.6
Coefficient of variation (CV)27.080003
Kurtosis9591.1205
Mean295455.67
Median Absolute Deviation (MAD)27210
Skewness96.977423
Sum2.9545567 × 109
Variance6.401505 × 1013
MonotonicityNot monotonic
2024-05-11T02:30:08.001483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 579
 
5.8%
50000 489
 
4.9%
100000 441
 
4.4%
60000 193
 
1.9%
150000 147
 
1.5%
70000 140
 
1.4%
200000 113
 
1.1%
20000 107
 
1.1%
40000 103
 
1.0%
120000 99
 
1.0%
Other values (3508) 7589
75.9%
ValueCountFrequency (%)
-4466430 1
 
< 0.1%
-2700000 1
 
< 0.1%
-1540000 1
 
< 0.1%
-460000 1
 
< 0.1%
-270000 1
 
< 0.1%
-166364 1
 
< 0.1%
-131810 1
 
< 0.1%
-100000 6
0.1%
-90000 1
 
< 0.1%
-73840 1
 
< 0.1%
ValueCountFrequency (%)
792000000 1
< 0.1%
50667610 1
< 0.1%
41707125 1
< 0.1%
28478500 1
< 0.1%
24750000 1
< 0.1%
23520000 1
< 0.1%
22000000 1
< 0.1%
18950000 1
< 0.1%
18945150 1
< 0.1%
17360000 1
< 0.1%

내용
Text

Distinct5916
Distinct (%)59.2%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:30:09.011654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length71
Mean length14.106996
Min length2

Characters and Unicode

Total characters140943
Distinct characters725
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5648 ?
Unique (%)56.5%

Sample

1st row음식물카드 재발급수수료:601-707
2nd row관리비 연체료 수납
3rd row관리비 연체료 수납
4th row2월분 고용,산재,국민연금,건강보험 자동이체할인
5th row커뮤니티 골프 개인 레슨비(주3회)/107동 2205호 신민환/최진호
ValueCountFrequency (%)
관리비 3521
 
13.6%
연체료 3399
 
13.1%
수납 3397
 
13.1%
333
 
1.3%
승강기 312
 
1.2%
3월분 279
 
1.1%
2월분 239
 
0.9%
승강기사용료 229
 
0.9%
3월 226
 
0.9%
입금 218
 
0.8%
Other values (7276) 13816
53.2%
2024-05-11T02:30:10.407570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16127
 
11.4%
료 5416
 
3.8%
수 4958
 
3.5%
0 4912
 
3.5%
리 4908
 
3.5%
비 4392
 
3.1%
1 4320
 
3.1%
2 4086
 
2.9%
관 3902
 
2.8%
체 3582
 
2.5%
Other values (715) 84340
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90347
64.1%
Decimal Number 21364
 
15.2%
Space Separator 16127
 
11.4%
Close Punctuation 3167
 
2.2%
Open Punctuation 3163
 
2.2%
Other Punctuation 3079
 
2.2%
Dash Punctuation 2460
 
1.7%
Uppercase Letter 667
 
0.5%
Math Symbol 331
 
0.2%
Lowercase Letter 128
 
0.1%
Other values (3) 110
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5416
 
6.0%
수 4958
 
5.5%
리 4908
 
5.4%
비 4392
 
4.9%
관 3902
 
4.3%
체 3582
 
4.0%
연 3470
 
3.8%
납 3444
 
3.8%
금 1925
 
2.1%
자 1881
 
2.1%
Other values (628) 52469
58.1%
Uppercase Letter
ValueCountFrequency (%)
N 82
12.3%
L 53
 
7.9%
K 53
 
7.9%
T 53
 
7.9%
C 50
 
7.5%
G 48
 
7.2%
O 35
 
5.2%
B 35
 
5.2%
S 34
 
5.1%
E 29
 
4.3%
Other values (15) 195
29.2%
Lowercase Letter
ValueCountFrequency (%)
o 36
28.1%
e 13
 
10.2%
x 13
 
10.2%
s 9
 
7.0%
t 9
 
7.0%
c 6
 
4.7%
k 6
 
4.7%
n 6
 
4.7%
l 5
 
3.9%
b 4
 
3.1%
Other values (10) 21
16.4%
Other Punctuation
ValueCountFrequency (%)
/ 807
26.2%
. 765
24.8%
, 683
22.2%
? 405
13.2%
: 184
 
6.0%
* 152
 
4.9%
@ 45
 
1.5%
% 15
 
0.5%
# 6
 
0.2%
& 6
 
0.2%
Other values (5) 11
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 4912
23.0%
1 4320
20.2%
2 4086
19.1%
3 2852
13.3%
4 1476
 
6.9%
5 1010
 
4.7%
6 772
 
3.6%
7 674
 
3.2%
8 662
 
3.1%
9 600
 
2.8%
Math Symbol
ValueCountFrequency (%)
~ 272
82.2%
+ 19
 
5.7%
= 14
 
4.2%
> 13
 
3.9%
× 8
 
2.4%
< 4
 
1.2%
∼ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3096
97.8%
] 71
 
2.2%
Open Punctuation
ValueCountFrequency (%)
( 3090
97.7%
[ 73
 
2.3%
Other Symbol
ValueCountFrequency (%)
★ 1
50.0%
㎡ 1
50.0%
Space Separator
ValueCountFrequency (%)
16127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2460
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 107
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90331
64.1%
Common 49801
35.3%
Latin 795
 
0.6%
Han 16
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5416
 
6.0%
수 4958
 
5.5%
리 4908
 
5.4%
비 4392
 
4.9%
관 3902
 
4.3%
체 3582
 
4.0%
연 3470
 
3.8%
납 3444
 
3.8%
금 1925
 
2.1%
자 1881
 
2.1%
Other values (621) 52453
58.1%
Latin
ValueCountFrequency (%)
N 82
 
10.3%
L 53
 
6.7%
K 53
 
6.7%
T 53
 
6.7%
C 50
 
6.3%
G 48
 
6.0%
o 36
 
4.5%
O 35
 
4.4%
B 35
 
4.4%
S 34
 
4.3%
Other values (35) 316
39.7%
Common
ValueCountFrequency (%)
16127
32.4%
0 4912
 
9.9%
1 4320
 
8.7%
2 4086
 
8.2%
) 3096
 
6.2%
( 3090
 
6.2%
3 2852
 
5.7%
- 2460
 
4.9%
4 1476
 
3.0%
5 1010
 
2.0%
Other values (32) 6372
 
12.8%
Han
ValueCountFrequency (%)
入 7
43.8%
人 3
18.8%
分 2
 
12.5%
中 1
 
6.2%
內 1
 
6.2%
月 1
 
6.2%
用 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90330
64.1%
ASCII 50583
35.9%
CJK 16
 
< 0.1%
None 10
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Math Operators 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16127
31.9%
0 4912
 
9.7%
1 4320
 
8.5%
2 4086
 
8.1%
) 3096
 
6.1%
( 3090
 
6.1%
3 2852
 
5.6%
- 2460
 
4.9%
4 1476
 
2.9%
5 1010
 
2.0%
Other values (71) 7154
14.1%
Hangul
ValueCountFrequency (%)
료 5416
 
6.0%
수 4958
 
5.5%
리 4908
 
5.4%
비 4392
 
4.9%
관 3902
 
4.3%
체 3582
 
4.0%
연 3470
 
3.8%
납 3444
 
3.8%
금 1925
 
2.1%
자 1881
 
2.1%
Other values (620) 52452
58.1%
None
ValueCountFrequency (%)
× 8
80.0%
＆ 1
 
10.0%
· 1
 
10.0%
CJK
ValueCountFrequency (%)
入 7
43.8%
人 3
18.8%
分 2
 
12.5%
中 1
 
6.2%
內 1
 
6.2%
月 1
 
6.2%
用 1
 
6.2%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄽ 1
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

Interactions

2024-05-11T02:29:59.471423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:58.716279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:59.910133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:29:59.077675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:30:10.730678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4640.145
년월일0.4641.0000.018
금액0.1450.0181.000
2024-05-11T02:30:10.985733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.000-0.0010.191
금액-0.0011.0000.132
비용명0.1910.1321.000

Missing values

2024-05-11T02:30:00.615444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:30:01.120092image/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
22994쌍문한양6차A13286107자산수증이익202203142000음식물카드 재발급수수료:601-707
65914롯데캐슬A15807205연체료수익202203316570관리비 연체료 수납
27367신성둔촌미소지움2차A13470502연체료수익20220324150관리비 연체료 수납
35868양재리본타워1단지A13713001잡수익202203107002월분 고용,산재,국민연금,건강보험 자동이체할인
3603백련산 sk뷰 아이파크A10025310기타운영수익20220318250000커뮤니티 골프 개인 레슨비(주3회)/107동 2205호 신민환/최진호
12722마포삼성A12104005광고료수익2022031150000게시판(KCC홈케어) 3/10~3/16
43960공릉2단지라이프A13980510연체료수익2022032860관리비 연체료 수납
16913답십리두산A13003201연체료수익202203083020관리비 연체료 수납
26686암사선사현대A13405201광고료수익2022032155000게시판광고[어문정]
15630갈현1단지e-편한세상A12205003이자수익202203271671농협(관리비통장)이자수익
아파트명아파트코드비용명년월일금액내용
24118신금호두산위브A13309101연체료수익202203105240관리비 연체료 수납
1796당산센트럴아이파크A10024789연체료수익2022031054510관리비 연체료 수납
47267LG한강자이A14003007연체료수익202203011450관리비 연체료 수납
26982고덕아이파크아파트A13408003승강기수익20220310150000109-1201 승강기사용료
33230정릉푸르지오A13610202잡수익202203223000관리소 팩스 사용료 (주민)입금건
27666명일동우성A13482505검침수익20220324237860한전검침수당(한전강동송파지점)
1649e편한세상 영등포 아델포레A10024725잡수익202203105004대보험 자동이체 수입
4787헬리오시티아파트A10025850승강기수익20220331100000213-1304호 전입 승강기사용료 입금
21886창동현대4차아이파크A13204402공동주택지원금수익202203036770일자리안정자금지원금 (경비실)
42036상계벽산A13920506연체료수익202203079190관리비 연체료 수납