Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells12
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 = 69.44071971)Skewed

Reproduction

Analysis started2024-05-11 02:35:59.885742
Analysis finished2024-05-11 02:36:04.871842
Duration4.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2129
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:36:05.313493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length7.2387
Min length2

Characters and Unicode

Total characters72387
Distinct characters429
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

Unique187 ?
Unique (%)1.9%

Sample

1st row중계현대1차
2nd row신길센트럴아이파크
3rd row구로한일유엔아이
4th row고척경남2차
5th row한신무학
ValueCountFrequency (%)
아파트 150
 
1.4%
래미안 52
 
0.5%
고덕 31
 
0.3%
힐스테이트 28
 
0.3%
아이파크 20
 
0.2%
미아뉴타운두산위브트레지움 20
 
0.2%
상계주공7단지 18
 
0.2%
잠실엘스아파트 17
 
0.2%
도봉한신 17
 
0.2%
sk북한산시티아파트 17
 
0.2%
Other values (2190) 10323
96.5%
2024-05-11T02:36:06.631371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2431
 
3.4%
파 2276
 
3.1%
트 2140
 
3.0%
지 1947
 
2.7%
대 1752
 
2.4%
동 1563
 
2.2%
단 1541
 
2.1%
신 1535
 
2.1%
차 1391
 
1.9%
이 1321
 
1.8%
Other values (419) 54490
75.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66048
91.2%
Decimal Number 3748
 
5.2%
Uppercase Letter 900
 
1.2%
Space Separator 788
 
1.1%
Lowercase Letter 279
 
0.4%
Open Punctuation 171
 
0.2%
Close Punctuation 171
 
0.2%
Dash Punctuation 138
 
0.2%
Other Punctuation 133
 
0.2%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2431
 
3.7%
파 2276
 
3.4%
트 2140
 
3.2%
지 1947
 
2.9%
대 1752
 
2.7%
동 1563
 
2.4%
단 1541
 
2.3%
신 1535
 
2.3%
차 1391
 
2.1%
이 1321
 
2.0%
Other values (373) 48151
72.9%
Uppercase Letter
ValueCountFrequency (%)
S 153
17.0%
K 136
15.1%
C 112
12.4%
M 70
7.8%
D 70
7.8%
L 60
 
6.7%
I 51
 
5.7%
H 51
 
5.7%
E 36
 
4.0%
A 32
 
3.6%
Other values (7) 129
14.3%
Lowercase Letter
ValueCountFrequency (%)
e 171
61.3%
l 28
 
10.0%
i 22
 
7.9%
v 15
 
5.4%
s 13
 
4.7%
k 9
 
3.2%
h 6
 
2.2%
w 5
 
1.8%
c 4
 
1.4%
g 3
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 1074
28.7%
1 1068
28.5%
3 482
12.9%
4 295
 
7.9%
5 229
 
6.1%
6 186
 
5.0%
9 125
 
3.3%
7 118
 
3.1%
8 106
 
2.8%
0 65
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 106
79.7%
. 27
 
20.3%
Space Separator
ValueCountFrequency (%)
788
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66048
91.2%
Common 5156
 
7.1%
Latin 1183
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2431
 
3.7%
파 2276
 
3.4%
트 2140
 
3.2%
지 1947
 
2.9%
대 1752
 
2.7%
동 1563
 
2.4%
단 1541
 
2.3%
신 1535
 
2.3%
차 1391
 
2.1%
이 1321
 
2.0%
Other values (373) 48151
72.9%
Latin
ValueCountFrequency (%)
e 171
14.5%
S 153
12.9%
K 136
11.5%
C 112
9.5%
M 70
 
5.9%
D 70
 
5.9%
L 60
 
5.1%
I 51
 
4.3%
H 51
 
4.3%
E 36
 
3.0%
Other values (19) 273
23.1%
Common
ValueCountFrequency (%)
2 1074
20.8%
1 1068
20.7%
788
15.3%
3 482
9.3%
4 295
 
5.7%
5 229
 
4.4%
6 186
 
3.6%
( 171
 
3.3%
) 171
 
3.3%
- 138
 
2.7%
Other values (7) 554
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66048
91.2%
ASCII 6335
 
8.8%
Number Forms 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2431
 
3.7%
파 2276
 
3.4%
트 2140
 
3.2%
지 1947
 
2.9%
대 1752
 
2.7%
동 1563
 
2.4%
단 1541
 
2.3%
신 1535
 
2.3%
차 1391
 
2.1%
이 1321
 
2.0%
Other values (373) 48151
72.9%
ASCII
ValueCountFrequency (%)
2 1074
17.0%
1 1068
16.9%
788
12.4%
3 482
 
7.6%
4 295
 
4.7%
5 229
 
3.6%
6 186
 
2.9%
( 171
 
2.7%
e 171
 
2.7%
) 171
 
2.7%
Other values (35) 1700
26.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%

아파트코드
Text

Distinct2136
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:36:07.462747image/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

Unique187 ?
Unique (%)1.9%

Sample

1st rowA13922901
2nd rowA10025562
3rd rowA15205104
4th rowA15283603
5th rowA13385705
ValueCountFrequency (%)
a14272314 20
 
0.2%
a13982704 18
 
0.2%
a14272304 17
 
0.2%
a13201209 17
 
0.2%
a13822004 17
 
0.2%
a13527203 16
 
0.2%
a13922114 16
 
0.2%
a12179004 16
 
0.2%
a13407104 15
 
0.1%
a13606004 15
 
0.1%
Other values (2126) 9833
98.3%
2024-05-11T02:36:08.991934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18540
20.6%
1 17340
19.3%
A 9995
11.1%
3 8929
9.9%
2 8232
9.1%
5 6217
 
6.9%
8 5546
 
6.2%
7 4845
 
5.4%
4 3949
 
4.4%
6 3411
 
3.8%
Other values (2) 2996
 
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 18540
23.2%
1 17340
21.7%
3 8929
11.2%
2 8232
10.3%
5 6217
 
7.8%
8 5546
 
6.9%
7 4845
 
6.1%
4 3949
 
4.9%
6 3411
 
4.3%
9 2991
 
3.7%
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 18540
23.2%
1 17340
21.7%
3 8929
11.2%
2 8232
10.3%
5 6217
 
7.8%
8 5546
 
6.9%
7 4845
 
6.1%
4 3949
 
4.9%
6 3411
 
4.3%
9 2991
 
3.7%
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 18540
20.6%
1 17340
19.3%
A 9995
11.1%
3 8929
9.9%
2 8232
9.1%
5 6217
 
6.9%
8 5546
 
6.2%
7 4845
 
5.4%
4 3949
 
4.4%
6 3411
 
3.8%
Other values (2) 2996
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3648 
승강기수익
1084 
잡수익
1065 
주차장수익
874 
광고료수익
838 
Other values (10)
2491 

Length

Max length9
Median length5
Mean length5.0387
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3648
36.5%
승강기수익 1084
 
10.8%
잡수익 1065
 
10.7%
주차장수익 874
 
8.7%
광고료수익 838
 
8.4%
고용안정사업수익 624
 
6.2%
기타운영수익 472
 
4.7%
검침수익 306
 
3.1%
알뜰시장수익 254
 
2.5%
임대료수익 238
 
2.4%
Other values (5) 597
 
6.0%

Length

2024-05-11T02:36:09.556744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3648
36.5%
승강기수익 1084
 
10.8%
잡수익 1065
 
10.7%
주차장수익 874
 
8.7%
광고료수익 838
 
8.4%
고용안정사업수익 624
 
6.2%
기타운영수익 472
 
4.7%
검침수익 306
 
3.1%
알뜰시장수익 254
 
2.5%
임대료수익 238
 
2.4%
Other values (5) 597
 
6.0%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200417
Minimum20200401
Maximum20200430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:36:10.204697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200401
5-th percentile20200401
Q120200408
median20200417
Q320200426
95-th percentile20200430
Maximum20200430
Range29
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.5157334
Coefficient of variation (CV)4.7106619 × 10-7
Kurtosis-1.3115151
Mean20200417
Median Absolute Deviation (MAD)9
Skewness-0.1905646
Sum2.0200417 × 1011
Variance90.549183
MonotonicityNot monotonic
2024-05-11T02:36:10.652148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20200430 761
 
7.6%
20200429 699
 
7.0%
20200401 538
 
5.4%
20200414 528
 
5.3%
20200424 521
 
5.2%
20200427 506
 
5.1%
20200428 464
 
4.6%
20200410 462
 
4.6%
20200420 446
 
4.5%
20200417 445
 
4.5%
Other values (20) 4630
46.3%
ValueCountFrequency (%)
20200401 538
5.4%
20200402 388
3.9%
20200403 351
3.5%
20200404 80
 
0.8%
20200405 89
 
0.9%
20200406 434
4.3%
20200407 346
3.5%
20200408 335
3.4%
20200409 293
2.9%
20200410 462
4.6%
ValueCountFrequency (%)
20200430 761
7.6%
20200429 699
7.0%
20200428 464
4.6%
20200427 506
5.1%
20200426 137
 
1.4%
20200425 167
 
1.7%
20200424 521
5.2%
20200423 387
3.9%
20200422 366
3.7%
20200421 328
3.3%

금액
Real number (ℝ)

SKEWED 

Distinct3346
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean312190.54
Minimum-3620640
Maximum2.268 × 108
Zeros20
Zeros (%)0.2%
Negative41
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:36:11.077139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3620640
5-th percentile100
Q12770
median30000
Q3120000
95-th percentile1360000
Maximum2.268 × 108
Range2.3042064 × 108
Interquartile range (IQR)117230

Descriptive statistics

Standard deviation2576869.2
Coefficient of variation (CV)8.2541553
Kurtosis5984.7075
Mean312190.54
Median Absolute Deviation (MAD)29440
Skewness69.44072
Sum3.1219054 × 109
Variance6.640255 × 1012
MonotonicityNot monotonic
2024-05-11T02:36:11.628279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 563
 
5.6%
100000 525
 
5.2%
50000 493
 
4.9%
70000 153
 
1.5%
150000 117
 
1.2%
60000 115
 
1.1%
40000 111
 
1.1%
200000 110
 
1.1%
80000 104
 
1.0%
20000 86
 
0.9%
Other values (3336) 7623
76.2%
ValueCountFrequency (%)
-3620640 1
< 0.1%
-2777250 1
< 0.1%
-1900000 1
< 0.1%
-993600 1
< 0.1%
-911930 1
< 0.1%
-540000 1
< 0.1%
-440000 1
< 0.1%
-270000 1
< 0.1%
-230000 1
< 0.1%
-181818 1
< 0.1%
ValueCountFrequency (%)
226800000 1
< 0.1%
39398410 1
< 0.1%
33078000 1
< 0.1%
32528110 1
< 0.1%
30396000 1
< 0.1%
23244000 1
< 0.1%
21937305 1
< 0.1%
20958220 1
< 0.1%
20389000 1
< 0.1%
20170940 1
< 0.1%

내용
Text

Distinct5691
Distinct (%)57.0%
Missing12
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:36:12.408371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length67
Mean length14.281638
Min length2

Characters and Unicode

Total characters142645
Distinct characters721
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

Unique5444 ?
Unique (%)54.5%

Sample

1st row관리비 연체료 수납
2nd row승강기사용료-104동2603호 전출
3rd row관리비 연체료 수납
4th row전산차익
5th rowMMF 평가이자
ValueCountFrequency (%)
관리비 3754
 
14.2%
연체료 3656
 
13.8%
수납 3651
 
13.8%
4월분 339
 
1.3%
승강기 283
 
1.1%
승강기사용료 267
 
1.0%
3월분 235
 
0.9%
입금 230
 
0.9%
4월 211
 
0.8%
사용료 210
 
0.8%
Other values (7192) 13633
51.5%
2024-05-11T02:36:13.824815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16584
 
11.6%
료 5624
 
3.9%
0 5366
 
3.8%
리 5183
 
3.6%
수 5053
 
3.5%
비 4588
 
3.2%
1 4301
 
3.0%
관 4022
 
2.8%
체 3836
 
2.7%
납 3786
 
2.7%
Other values (711) 84302
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92100
64.6%
Decimal Number 21445
 
15.0%
Space Separator 16584
 
11.6%
Open Punctuation 3103
 
2.2%
Close Punctuation 3100
 
2.2%
Other Punctuation 2986
 
2.1%
Dash Punctuation 2178
 
1.5%
Uppercase Letter 562
 
0.4%
Math Symbol 411
 
0.3%
Lowercase Letter 116
 
0.1%
Other values (3) 60
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5624
 
6.1%
리 5183
 
5.6%
수 5053
 
5.5%
비 4588
 
5.0%
관 4022
 
4.4%
체 3836
 
4.2%
납 3786
 
4.1%
연 3702
 
4.0%
월 2145
 
2.3%
금 2015
 
2.2%
Other values (625) 52146
56.6%
Uppercase Letter
ValueCountFrequency (%)
N 82
14.6%
O 59
10.5%
K 44
 
7.8%
A 38
 
6.8%
L 38
 
6.8%
B 37
 
6.6%
C 36
 
6.4%
S 30
 
5.3%
M 29
 
5.2%
T 28
 
5.0%
Other values (14) 141
25.1%
Lowercase Letter
ValueCountFrequency (%)
o 35
30.2%
x 21
18.1%
n 12
 
10.3%
k 8
 
6.9%
t 5
 
4.3%
e 5
 
4.3%
c 5
 
4.3%
s 4
 
3.4%
f 3
 
2.6%
m 3
 
2.6%
Other values (10) 15
12.9%
Other Punctuation
ValueCountFrequency (%)
, 956
32.0%
/ 802
26.9%
. 713
23.9%
: 215
 
7.2%
* 170
 
5.7%
@ 49
 
1.6%
? 29
 
1.0%
% 23
 
0.8%
& 9
 
0.3%
' 8
 
0.3%
Other values (4) 12
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 5366
25.0%
1 4301
20.1%
2 3365
15.7%
4 2475
11.5%
3 2255
10.5%
5 1032
 
4.8%
6 784
 
3.7%
7 635
 
3.0%
9 628
 
2.9%
8 604
 
2.8%
Math Symbol
ValueCountFrequency (%)
~ 312
75.9%
+ 55
 
13.4%
> 16
 
3.9%
= 10
 
2.4%
< 10
 
2.4%
× 5
 
1.2%
→ 3
 
0.7%
Other Number
ValueCountFrequency (%)
① 1
33.3%
② 1
33.3%
⑪ 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 3027
97.6%
[ 76
 
2.4%
Close Punctuation
ValueCountFrequency (%)
) 3024
97.5%
] 76
 
2.5%
Space Separator
ValueCountFrequency (%)
16584
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2178
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 56
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92094
64.6%
Common 49867
35.0%
Latin 678
 
0.5%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5624
 
6.1%
리 5183
 
5.6%
수 5053
 
5.5%
비 4588
 
5.0%
관 4022
 
4.4%
체 3836
 
4.2%
납 3786
 
4.1%
연 3702
 
4.0%
월 2145
 
2.3%
금 2015
 
2.2%
Other values (622) 52140
56.6%
Latin
ValueCountFrequency (%)
N 82
 
12.1%
O 59
 
8.7%
K 44
 
6.5%
A 38
 
5.6%
L 38
 
5.6%
B 37
 
5.5%
C 36
 
5.3%
o 35
 
5.2%
S 30
 
4.4%
M 29
 
4.3%
Other values (34) 250
36.9%
Common
ValueCountFrequency (%)
16584
33.3%
0 5366
 
10.8%
1 4301
 
8.6%
2 3365
 
6.7%
( 3027
 
6.1%
) 3024
 
6.1%
4 2475
 
5.0%
3 2255
 
4.5%
- 2178
 
4.4%
5 1032
 
2.1%
Other values (32) 6260
 
12.6%
Han
ValueCountFrequency (%)
分 4
66.7%
入 1
 
16.7%
內 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92093
64.6%
ASCII 50532
35.4%
None 6
 
< 0.1%
CJK 6
 
< 0.1%
Arrows 3
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16584
32.8%
0 5366
 
10.6%
1 4301
 
8.5%
2 3365
 
6.7%
( 3027
 
6.0%
) 3024
 
6.0%
4 2475
 
4.9%
3 2255
 
4.5%
- 2178
 
4.3%
5 1032
 
2.0%
Other values (69) 6925
13.7%
Hangul
ValueCountFrequency (%)
료 5624
 
6.1%
리 5183
 
5.6%
수 5053
 
5.5%
비 4588
 
5.0%
관 4022
 
4.4%
체 3836
 
4.2%
납 3786
 
4.1%
연 3702
 
4.0%
월 2145
 
2.3%
금 2015
 
2.2%
Other values (621) 52139
56.6%
None
ValueCountFrequency (%)
× 5
83.3%
？ 1
 
16.7%
CJK
ValueCountFrequency (%)
分 4
66.7%
入 1
 
16.7%
內 1
 
16.7%
Arrows
ValueCountFrequency (%)
→ 3
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
33.3%
② 1
33.3%
⑪ 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

Interactions

2024-05-11T02:36:03.172627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:36:02.245221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:36:03.588977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:36:02.751596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:36:14.129863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.3590.265
년월일0.3591.0000.033
금액0.2650.0331.000
2024-05-11T02:36:14.502349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0010.141
금액0.0011.0000.124
비용명0.1410.1241.000

Missing values

2024-05-11T02:36:04.081324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:36:04.608936image/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
35148중계현대1차A13922901연체료수익20200430190관리비 연체료 수납
882신길센트럴아이파크A10025562승강기수익20200414100000승강기사용료-104동2603호 전출
47010구로한일유엔아이A15205104연체료수익2020042211640관리비 연체료 수납
48535고척경남2차A15283603잡수익202004306157전산차익
20836한신무학A13385705이자수익20200430-64531MMF 평가이자
23021테헤란 IPARKA13508012기타운영수익20200414230000일자리안정자금[관리사무소]코로나지원금[2~5월한시적]3월
20860무학현대A13385802잡수익202004303390부과차익
35482하계청솔A13923108잡수익2020041021500삼성자판기에이에스
40567번동신원A14206306기타운영수익20200410134190일자리안정자금지원금 입금
53591염창동아1차A15704028검침수익20200410622400수도검침수당
아파트명아파트코드비용명년월일금액내용
7253연희대우A12011002승강기수익20200414100000102동904호 전출 승강기사용료(4/15일)
3641래미안힐스테이트 고덕A10027207연체료수익202004308540관리비 연체료 수납
41477자양현대A14319003고용안정사업수익202004141240000일자리안정자금
49513신도림대림7차e-편한세상A15288807주차장수익202004307250004월분 주차수입
20720응봉대림2차A13385202연체료수익202004228620관리비 연체료 수납
43693문래두산위브A15009505광고료수익2020042727273게시판 광고료(영어과외 김성은)
38021중계현대2차(4동)A13985904연체료수익202004272250관리비 연체료 수납
31423풍납시티극동A13804003이자수익2020042014예금결산이자(264-048309-04-062)
2282e편한세상신촌아파트A10026370승강기수익20200429130000401동 3005호 승강기사용료
56626신정이펜하우스4단지A15807004연체료수익20200422217200관리비 연체료 수납