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 = 47.19292806)Skewed

Reproduction

Analysis started2024-05-11 02:23:48.600316
Analysis finished2024-05-11 02:23:52.556723
Duration3.96 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
2024-05-11T02:23:52.883493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length19
Mean length7.5255
Min length2

Characters and Unicode

Total characters75255
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

Unique252 ?
Unique (%)2.5%

Sample

1st row중계센트럴파크아파트
2nd row경희궁자이4단지주상복합
3rd row장안현대홈타운
4th row래미안그레이튼
5th row상봉듀오트리스
ValueCountFrequency (%)
아파트 211
 
1.9%
래미안 69
 
0.6%
아이파크 41
 
0.4%
e편한세상 33
 
0.3%
고덕 26
 
0.2%
마포래미안푸르지오 25
 
0.2%
백련산 23
 
0.2%
푸르지오 23
 
0.2%
힐스테이트 22
 
0.2%
sk뷰 22
 
0.2%
Other values (2270) 10508
95.5%
2024-05-11T02:23:53.848808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 2626
 
3.5%
아 2586
 
3.4%
트 2537
 
3.4%
지 2121
 
2.8%
단 1668
 
2.2%
대 1562
 
2.1%
이 1499
 
2.0%
동 1493
 
2.0%
신 1311
 
1.7%
차 1230
 
1.6%
Other values (423) 56622
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68762
91.4%
Decimal Number 3630
 
4.8%
Space Separator 1131
 
1.5%
Uppercase Letter 889
 
1.2%
Lowercase Letter 293
 
0.4%
Close Punctuation 164
 
0.2%
Open Punctuation 164
 
0.2%
Dash Punctuation 112
 
0.1%
Other Punctuation 95
 
0.1%
Letter Number 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2626
 
3.8%
아 2586
 
3.8%
트 2537
 
3.7%
지 2121
 
3.1%
단 1668
 
2.4%
대 1562
 
2.3%
이 1499
 
2.2%
동 1493
 
2.2%
신 1311
 
1.9%
차 1230
 
1.8%
Other values (378) 50129
72.9%
Uppercase Letter
ValueCountFrequency (%)
C 139
15.6%
S 138
15.5%
K 103
11.6%
M 102
11.5%
D 102
11.5%
H 51
 
5.7%
L 47
 
5.3%
I 39
 
4.4%
E 37
 
4.2%
A 32
 
3.6%
Other values (7) 99
11.1%
Lowercase Letter
ValueCountFrequency (%)
e 181
61.8%
s 24
 
8.2%
k 23
 
7.8%
i 19
 
6.5%
l 16
 
5.5%
v 11
 
3.8%
w 7
 
2.4%
a 4
 
1.4%
g 4
 
1.4%
c 2
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 1059
29.2%
2 1004
27.7%
3 511
14.1%
4 250
 
6.9%
5 207
 
5.7%
6 174
 
4.8%
7 136
 
3.7%
9 131
 
3.6%
8 85
 
2.3%
0 73
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 76
80.0%
. 19
 
20.0%
Space Separator
ValueCountFrequency (%)
1131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 164
100.0%
Open Punctuation
ValueCountFrequency (%)
( 164
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68762
91.4%
Common 5296
 
7.0%
Latin 1197
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2626
 
3.8%
아 2586
 
3.8%
트 2537
 
3.7%
지 2121
 
3.1%
단 1668
 
2.4%
대 1562
 
2.3%
이 1499
 
2.2%
동 1493
 
2.2%
신 1311
 
1.9%
차 1230
 
1.8%
Other values (378) 50129
72.9%
Latin
ValueCountFrequency (%)
e 181
15.1%
C 139
11.6%
S 138
11.5%
K 103
 
8.6%
M 102
 
8.5%
D 102
 
8.5%
H 51
 
4.3%
L 47
 
3.9%
I 39
 
3.3%
E 37
 
3.1%
Other values (19) 258
21.6%
Common
ValueCountFrequency (%)
1131
21.4%
1 1059
20.0%
2 1004
19.0%
3 511
9.6%
4 250
 
4.7%
5 207
 
3.9%
6 174
 
3.3%
) 164
 
3.1%
( 164
 
3.1%
7 136
 
2.6%
Other values (6) 496
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68762
91.4%
ASCII 6478
 
8.6%
Number Forms 15
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 2626
 
3.8%
아 2586
 
3.8%
트 2537
 
3.7%
지 2121
 
3.1%
단 1668
 
2.4%
대 1562
 
2.3%
이 1499
 
2.2%
동 1493
 
2.2%
신 1311
 
1.9%
차 1230
 
1.8%
Other values (378) 50129
72.9%
ASCII
ValueCountFrequency (%)
1131
17.5%
1 1059
16.3%
2 1004
15.5%
3 511
 
7.9%
4 250
 
3.9%
5 207
 
3.2%
e 181
 
2.8%
6 174
 
2.7%
) 164
 
2.5%
( 164
 
2.5%
Other values (34) 1633
25.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 15
100.0%

아파트코드
Text

Distinct2194
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:23:54.428870image/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

Unique252 ?
Unique (%)2.5%

Sample

1st rowA10027601
2nd rowA10026940
3rd rowA13010006
4th rowA13508011
5th rowA10027670
ValueCountFrequency (%)
a12175203 25
 
0.2%
a10025614 18
 
0.2%
a10045002 17
 
0.2%
a12179004 17
 
0.2%
a13204510 17
 
0.2%
a13805002 17
 
0.2%
a10027817 16
 
0.2%
a10027188 16
 
0.2%
a13982704 16
 
0.2%
a10028021 15
 
0.1%
Other values (2184) 9826
98.3%
2024-05-11T02:23:55.335453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18957
21.1%
1 17279
19.2%
A 9984
11.1%
3 8594
9.5%
2 8322
9.2%
5 6308
 
7.0%
8 5431
 
6.0%
7 4833
 
5.4%
4 3988
 
4.4%
6 3357
 
3.7%
Other values (2) 2947
 
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 18957
23.7%
1 17279
21.6%
3 8594
10.7%
2 8322
10.4%
5 6308
 
7.9%
8 5431
 
6.8%
7 4833
 
6.0%
4 3988
 
5.0%
6 3357
 
4.2%
9 2931
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9984
99.8%
B 16
 
0.2%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18957
23.7%
1 17279
21.6%
3 8594
10.7%
2 8322
10.4%
5 6308
 
7.9%
8 5431
 
6.8%
7 4833
 
6.0%
4 3988
 
5.0%
6 3357
 
4.2%
9 2931
 
3.7%
Latin
ValueCountFrequency (%)
A 9984
99.8%
B 16
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18957
21.1%
1 17279
19.2%
A 9984
11.1%
3 8594
9.5%
2 8322
9.2%
5 6308
 
7.0%
8 5431
 
6.0%
7 4833
 
5.4%
4 3988
 
4.4%
6 3357
 
3.7%
Other values (2) 2947
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3510 
승강기수익
1141 
광고료수익
932 
잡수익
914 
주차장수익
836 
Other values (10)
2667 

Length

Max length9
Median length5
Mean length4.8212
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3510
35.1%
승강기수익 1141
 
11.4%
광고료수익 932
 
9.3%
잡수익 914
 
9.1%
주차장수익 836
 
8.4%
기타운영수익 795
 
8.0%
이자수익 682
 
6.8%
검침수익 316
 
3.2%
임대료수익 244
 
2.4%
부과차익 218
 
2.2%
Other values (5) 412
 
4.1%

Length

2024-05-11T02:23:55.606042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3510
35.1%
승강기수익 1141
 
11.4%
광고료수익 932
 
9.3%
잡수익 914
 
9.1%
주차장수익 836
 
8.4%
기타운영수익 795
 
8.0%
이자수익 682
 
6.8%
검침수익 316
 
3.2%
임대료수익 244
 
2.4%
부과차익 218
 
2.2%
Other values (5) 412
 
4.1%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230318
Minimum20230301
Maximum20230331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:23:55.898582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230301
5-th percentile20230302
Q120230309
median20230318
Q320230327
95-th percentile20230331
Maximum20230331
Range30
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.7175917
Coefficient of variation (CV)4.8034795 × 10-7
Kurtosis-1.2889535
Mean20230318
Median Absolute Deviation (MAD)9
Skewness-0.19247158
Sum2.0230318 × 1011
Variance94.431589
MonotonicityNot monotonic
2024-05-11T02:23:56.305333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20230331 1020
 
10.2%
20230302 552
 
5.5%
20230330 530
 
5.3%
20230327 487
 
4.9%
20230306 450
 
4.5%
20230310 432
 
4.3%
20230320 401
 
4.0%
20230324 399
 
4.0%
20230328 381
 
3.8%
20230318 375
 
3.8%
Other values (21) 4973
49.7%
ValueCountFrequency (%)
20230301 221
2.2%
20230302 552
5.5%
20230303 375
3.8%
20230304 94
 
0.9%
20230305 81
 
0.8%
20230306 450
4.5%
20230307 297
3.0%
20230308 275
2.8%
20230309 261
2.6%
20230310 432
4.3%
ValueCountFrequency (%)
20230331 1020
10.2%
20230330 530
5.3%
20230329 329
 
3.3%
20230328 381
 
3.8%
20230327 487
4.9%
20230326 247
 
2.5%
20230325 162
 
1.6%
20230324 399
 
4.0%
20230323 297
 
3.0%
20230322 290
 
2.9%

금액
Real number (ℝ)

SKEWED 

Distinct3571
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277822.03
Minimum-878000
Maximum1.6938 × 108
Zeros14
Zeros (%)0.1%
Negative33
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T02:23:56.606175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-878000
5-th percentile130
Q12340
median23430
Q399000
95-th percentile1000000
Maximum1.6938 × 108
Range1.70258 × 108
Interquartile range (IQR)96660

Descriptive statistics

Standard deviation2246089.3
Coefficient of variation (CV)8.0846333
Kurtosis3274.8662
Mean277822.03
Median Absolute Deviation (MAD)22930
Skewness47.192928
Sum2.7782203 × 109
Variance5.0449169 × 1012
MonotonicityNot monotonic
2024-05-11T02:23:57.051234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 557
 
5.6%
50000 523
 
5.2%
100000 522
 
5.2%
40000 155
 
1.6%
150000 153
 
1.5%
60000 149
 
1.5%
70000 135
 
1.4%
80000 107
 
1.1%
200000 107
 
1.1%
20000 99
 
1.0%
Other values (3561) 7493
74.9%
ValueCountFrequency (%)
-878000 1
< 0.1%
-600000 1
< 0.1%
-374230 1
< 0.1%
-247745 1
< 0.1%
-150000 1
< 0.1%
-132000 1
< 0.1%
-110000 1
< 0.1%
-100000 1
< 0.1%
-90000 2
< 0.1%
-80000 1
< 0.1%
ValueCountFrequency (%)
169380000 1
< 0.1%
46572470 1
< 0.1%
37446340 1
< 0.1%
35675040 1
< 0.1%
34090909 1
< 0.1%
33800247 1
< 0.1%
32990400 1
< 0.1%
28823050 1
< 0.1%
26625282 1
< 0.1%
26297900 1
< 0.1%

내용
Text

Distinct5907
Distinct (%)59.1%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:23:57.687939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length58
Mean length14.525073
Min length2

Characters and Unicode

Total characters145120
Distinct characters760
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

Unique5682 ?
Unique (%)56.9%

Sample

1st row관리비 연체료 수납
2nd row관리비 연체료 수납
3rd row관리비 연체료 수납
4th row게시판광고/정우재학원
5th row게시판광고[3/21~4/4] 바디톡 휘트니스
ValueCountFrequency (%)
관리비 3651
 
13.5%
연체료 3516
 
13.0%
수납 3513
 
13.0%
539
 
2.0%
승강기 365
 
1.4%
3월분 295
 
1.1%
사용료 257
 
1.0%
승강기사용료 244
 
0.9%
3월 197
 
0.7%
2월분 185
 
0.7%
Other values (7722) 14236
52.7%
2024-05-11T02:23:58.778854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17384
 
12.0%
료 5686
 
3.9%
0 5349
 
3.7%
수 5166
 
3.6%
1 4844
 
3.3%
비 4371
 
3.0%
리 4321
 
3.0%
2 3988
 
2.7%
관 3979
 
2.7%
체 3711
 
2.6%
Other values (750) 86321
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89504
61.7%
Decimal Number 23764
 
16.4%
Space Separator 17384
 
12.0%
Other Punctuation 4139
 
2.9%
Close Punctuation 3182
 
2.2%
Open Punctuation 3155
 
2.2%
Dash Punctuation 2676
 
1.8%
Uppercase Letter 630
 
0.4%
Math Symbol 379
 
0.3%
Lowercase Letter 195
 
0.1%
Other values (3) 112
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5686
 
6.4%
수 5166
 
5.8%
비 4371
 
4.9%
리 4321
 
4.8%
관 3979
 
4.4%
체 3711
 
4.1%
연 3614
 
4.0%
납 3605
 
4.0%
기 1805
 
2.0%
용 1797
 
2.0%
Other values (664) 51449
57.5%
Uppercase Letter
ValueCountFrequency (%)
N 90
14.3%
B 55
 
8.7%
O 45
 
7.1%
L 44
 
7.0%
G 43
 
6.8%
T 41
 
6.5%
K 40
 
6.3%
C 38
 
6.0%
A 35
 
5.6%
S 26
 
4.1%
Other values (13) 173
27.5%
Lowercase Letter
ValueCountFrequency (%)
o 49
25.1%
n 24
12.3%
e 18
 
9.2%
a 14
 
7.2%
k 12
 
6.2%
c 11
 
5.6%
t 9
 
4.6%
s 8
 
4.1%
i 7
 
3.6%
b 7
 
3.6%
Other values (13) 36
18.5%
Other Punctuation
ValueCountFrequency (%)
? 1241
30.0%
/ 965
23.3%
. 924
22.3%
, 643
15.5%
: 185
 
4.5%
* 105
 
2.5%
% 25
 
0.6%
@ 24
 
0.6%
# 13
 
0.3%
& 5
 
0.1%
Other values (4) 9
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 5349
22.5%
1 4844
20.4%
2 3988
16.8%
3 3592
15.1%
4 1603
 
6.7%
5 1184
 
5.0%
6 910
 
3.8%
7 843
 
3.5%
8 795
 
3.3%
9 656
 
2.8%
Math Symbol
ValueCountFrequency (%)
~ 320
84.4%
+ 28
 
7.4%
× 13
 
3.4%
> 9
 
2.4%
= 7
 
1.8%
< 2
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 3088
97.0%
] 94
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 3062
97.1%
[ 93
 
2.9%
Other Number
ValueCountFrequency (%)
⑤ 1
50.0%
④ 1
50.0%
Space Separator
ValueCountFrequency (%)
17384
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2676
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 109
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89492
61.7%
Common 54791
37.8%
Latin 825
 
0.6%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5686
 
6.4%
수 5166
 
5.8%
비 4371
 
4.9%
리 4321
 
4.8%
관 3979
 
4.4%
체 3711
 
4.1%
연 3614
 
4.0%
납 3605
 
4.0%
기 1805
 
2.0%
용 1797
 
2.0%
Other values (661) 51437
57.5%
Latin
ValueCountFrequency (%)
N 90
 
10.9%
B 55
 
6.7%
o 49
 
5.9%
O 45
 
5.5%
L 44
 
5.3%
G 43
 
5.2%
T 41
 
5.0%
K 40
 
4.8%
C 38
 
4.6%
A 35
 
4.2%
Other values (36) 345
41.8%
Common
ValueCountFrequency (%)
17384
31.7%
0 5349
 
9.8%
1 4844
 
8.8%
2 3988
 
7.3%
3 3592
 
6.6%
) 3088
 
5.6%
( 3062
 
5.6%
- 2676
 
4.9%
4 1603
 
2.9%
? 1241
 
2.3%
Other values (30) 7964
14.5%
Han
ValueCountFrequency (%)
入 10
83.3%
內 1
 
8.3%
出 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89491
61.7%
ASCII 55598
38.3%
None 15
 
< 0.1%
CJK 12
 
< 0.1%
Enclosed Alphanum 2
 
< 0.1%
CJK Compat 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17384
31.3%
0 5349
 
9.6%
1 4844
 
8.7%
2 3988
 
7.2%
3 3592
 
6.5%
) 3088
 
5.6%
( 3062
 
5.5%
- 2676
 
4.8%
4 1603
 
2.9%
? 1241
 
2.2%
Other values (70) 8771
15.8%
Hangul
ValueCountFrequency (%)
료 5686
 
6.4%
수 5166
 
5.8%
비 4371
 
4.9%
리 4321
 
4.8%
관 3979
 
4.4%
체 3711
 
4.1%
연 3614
 
4.0%
납 3605
 
4.0%
기 1805
 
2.0%
용 1797
 
2.0%
Other values (660) 51436
57.5%
None
ValueCountFrequency (%)
× 13
86.7%
· 1
 
6.7%
？ 1
 
6.7%
CJK
ValueCountFrequency (%)
入 10
83.3%
內 1
 
8.3%
出 1
 
8.3%
Enclosed Alphanum
ValueCountFrequency (%)
⑤ 1
50.0%
④ 1
50.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅏ 1
100.0%

Interactions

2024-05-11T02:23:51.356131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:23:50.598479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:23:51.655713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:23:51.043252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:23:59.039634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4720.273
년월일0.4721.0000.058
금액0.2730.0581.000
2024-05-11T02:23:59.281600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0440.196
금액0.0441.0000.158
비용명0.1960.1581.000

Missing values

2024-05-11T02:23:52.045241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:23:52.425276image/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
9146중계센트럴파크아파트A10027601연체료수익20230308930관리비 연체료 수납
7761경희궁자이4단지주상복합A10026940연체료수익20230328110관리비 연체료 수납
18249장안현대홈타운A13010006연체료수익202303251400관리비 연체료 수납
28170래미안그레이튼A13508011광고료수익20230306100000게시판광고/정우재학원
9311상봉듀오트리스A10027670광고료수익20230321100000게시판광고[3/21~4/4] 바디톡 휘트니스
54186개봉현대홈타운2단지A15209206승강기수익20230306100000205동 701호 승강기사용료(전입)
44790중계경남아너스빌A13986703승강기수익202303071000001-504인테리어e/l
25124행당대림제2A13377902임대료수익2023032740000텃밭임대료수입
64060신월대방샤인힐A15809001광고료수익2023033030000게시판광고(제이엠)박경화
3540백련산 해모로 아파트A10024947연체료수익202303305730관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
65449은평뉴타운우물골7단지A41279918연체료수익202303306270관리비 연체료 수납
42142공릉비선A13980018연체료수익202303105410관리비 연체료 수납
28827압구정신현대A13511004연체료수익2023032076610관리비 연체료 수납
46124동부센트레빌아스테리움서울A14070901연체료수익202303043940관리비 연체료 수납
13133남가좌현대제2A12072802연체료수익20230329710관리비 연체료 수납
64363목동2단지A15875102연체료수익202303222000관리비 연체료 수납
65758행당두산위브임대B13307001기타운영수익2023033140513??????????????
47220미아현대A14272307연체료수익202303221000관리비 연체료 수납
49701당산삼성래미안A15004507기타운영수익20230317800000헬스레슨비(2명)
5395래미안블레스티지A10025675승강기수익20230328200000204동 2102호 승강기사용료-전출