Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells8
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 = 29.51795672)Skewed

Reproduction

Analysis started2024-05-11 02:32:42.154848
Analysis finished2024-05-11 02:32:46.993144
Duration4.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2170
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:32:47.427582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length7.2571
Min length2

Characters and Unicode

Total characters72571
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

Unique206 ?
Unique (%)2.1%

Sample

1st rowe편한세상마포리버파크
2nd row관악푸르지오아파트
3rd row역삼아이파크
4th row군자일성파크
5th row신트리1단지
ValueCountFrequency (%)
아파트 150
 
1.4%
래미안 58
 
0.5%
힐스테이트 29
 
0.3%
아이파크 24
 
0.2%
미아뉴타운두산위브트레지움 20
 
0.2%
도봉한신 19
 
0.2%
e편한세상 19
 
0.2%
고덕 18
 
0.2%
잠실동트리지움 17
 
0.2%
sk뷰 17
 
0.2%
Other values (2237) 10347
96.5%
2024-05-11T02:32:48.688689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2512
 
3.5%
파 2456
 
3.4%
트 2343
 
3.2%
지 1958
 
2.7%
대 1720
 
2.4%
동 1628
 
2.2%
단 1548
 
2.1%
신 1381
 
1.9%
이 1360
 
1.9%
차 1330
 
1.8%
Other values (423) 54335
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66484
91.6%
Decimal Number 3658
 
5.0%
Space Separator 825
 
1.1%
Uppercase Letter 802
 
1.1%
Lowercase Letter 307
 
0.4%
Dash Punctuation 125
 
0.2%
Open Punctuation 121
 
0.2%
Close Punctuation 121
 
0.2%
Other Punctuation 121
 
0.2%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2512
 
3.8%
파 2456
 
3.7%
트 2343
 
3.5%
지 1958
 
2.9%
대 1720
 
2.6%
동 1628
 
2.4%
단 1548
 
2.3%
신 1381
 
2.1%
이 1360
 
2.0%
차 1330
 
2.0%
Other values (378) 48248
72.6%
Uppercase Letter
ValueCountFrequency (%)
S 128
16.0%
K 114
14.2%
C 106
13.2%
D 65
8.1%
M 65
8.1%
L 57
7.1%
H 50
 
6.2%
I 45
 
5.6%
A 32
 
4.0%
E 32
 
4.0%
Other values (7) 108
13.5%
Lowercase Letter
ValueCountFrequency (%)
e 170
55.4%
l 32
 
10.4%
i 23
 
7.5%
s 23
 
7.5%
k 18
 
5.9%
v 17
 
5.5%
h 8
 
2.6%
c 6
 
2.0%
w 4
 
1.3%
g 3
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 1051
28.7%
2 1037
28.3%
3 494
13.5%
4 271
 
7.4%
5 239
 
6.5%
6 164
 
4.5%
7 132
 
3.6%
9 103
 
2.8%
8 91
 
2.5%
0 76
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 102
84.3%
. 19
 
15.7%
Space Separator
ValueCountFrequency (%)
825
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 125
100.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66484
91.6%
Common 4971
 
6.8%
Latin 1116
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2512
 
3.8%
파 2456
 
3.7%
트 2343
 
3.5%
지 1958
 
2.9%
대 1720
 
2.6%
동 1628
 
2.4%
단 1548
 
2.3%
신 1381
 
2.1%
이 1360
 
2.0%
차 1330
 
2.0%
Other values (378) 48248
72.6%
Latin
ValueCountFrequency (%)
e 170
15.2%
S 128
11.5%
K 114
10.2%
C 106
 
9.5%
D 65
 
5.8%
M 65
 
5.8%
L 57
 
5.1%
H 50
 
4.5%
I 45
 
4.0%
A 32
 
2.9%
Other values (19) 284
25.4%
Common
ValueCountFrequency (%)
1 1051
21.1%
2 1037
20.9%
825
16.6%
3 494
9.9%
4 271
 
5.5%
5 239
 
4.8%
6 164
 
3.3%
7 132
 
2.7%
- 125
 
2.5%
( 121
 
2.4%
Other values (6) 512
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66484
91.6%
ASCII 6080
 
8.4%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2512
 
3.8%
파 2456
 
3.7%
트 2343
 
3.5%
지 1958
 
2.9%
대 1720
 
2.6%
동 1628
 
2.4%
단 1548
 
2.3%
신 1381
 
2.1%
이 1360
 
2.0%
차 1330
 
2.0%
Other values (378) 48248
72.6%
ASCII
ValueCountFrequency (%)
1 1051
17.3%
2 1037
17.1%
825
13.6%
3 494
 
8.1%
4 271
 
4.5%
5 239
 
3.9%
e 170
 
2.8%
6 164
 
2.7%
7 132
 
2.2%
S 128
 
2.1%
Other values (34) 1569
25.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2176
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:32:49.784922image/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

Unique210 ?
Unique (%)2.1%

Sample

1st rowA10028006
2nd rowA15105302
3rd rowA13508009
4th rowA14383901
5th rowA15807002
ValueCountFrequency (%)
a14272314 20
 
0.2%
a13201209 19
 
0.2%
a13822002 17
 
0.2%
a10025614 16
 
0.2%
a10027714 16
 
0.2%
a13972603 16
 
0.2%
a13003007 16
 
0.2%
a13386702 15
 
0.1%
a13822003 15
 
0.1%
a12179004 15
 
0.1%
Other values (2166) 9835
98.4%
2024-05-11T02:32:51.692481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18499
20.6%
1 17185
19.1%
A 9992
11.1%
3 8843
9.8%
2 8298
9.2%
5 6415
 
7.1%
8 5490
 
6.1%
7 4919
 
5.5%
4 3932
 
4.4%
6 3418
 
3.8%
Other values (2) 3009
 
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 18499
23.1%
1 17185
21.5%
3 8843
11.1%
2 8298
10.4%
5 6415
 
8.0%
8 5490
 
6.9%
7 4919
 
6.1%
4 3932
 
4.9%
6 3418
 
4.3%
9 3001
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9992
99.9%
B 8
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18499
23.1%
1 17185
21.5%
3 8843
11.1%
2 8298
10.4%
5 6415
 
8.0%
8 5490
 
6.9%
7 4919
 
6.1%
4 3932
 
4.9%
6 3418
 
4.3%
9 3001
 
3.8%
Latin
ValueCountFrequency (%)
A 9992
99.9%
B 8
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18499
20.6%
1 17185
19.1%
A 9992
11.1%
3 8843
9.8%
2 8298
9.2%
5 6415
 
7.1%
8 5490
 
6.1%
7 4919
 
5.5%
4 3932
 
4.4%
6 3418
 
3.8%
Other values (2) 3009
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3389 
승강기수익
1203 
잡수익
927 
광고료수익
823 
주차장수익
795 
Other values (10)
2863 

Length

Max length9
Median length5
Mean length4.9811
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3389
33.9%
승강기수익 1203
 
12.0%
잡수익 927
 
9.3%
광고료수익 823
 
8.2%
주차장수익 795
 
8.0%
이자수익 604
 
6.0%
기타운영수익 580
 
5.8%
고용안정사업수익 503
 
5.0%
검침수익 293
 
2.9%
알뜰시장수익 235
 
2.4%
Other values (5) 648
 
6.5%

Length

2024-05-11T02:32:52.721722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3389
33.9%
승강기수익 1203
 
12.0%
잡수익 927
 
9.3%
광고료수익 823
 
8.2%
주차장수익 795
 
8.0%
이자수익 604
 
6.0%
기타운영수익 580
 
5.8%
고용안정사업수익 503
 
5.0%
검침수익 293
 
2.9%
알뜰시장수익 235
 
2.4%
Other values (5) 648
 
6.5%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210317
Minimum20210301
Maximum20210331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:32:53.385972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210301
5-th percentile20210302
Q120210309
median20210317
Q320210326
95-th percentile20210331
Maximum20210331
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.7449933
Coefficient of variation (CV)4.8217914 × 10-7
Kurtosis-1.297999
Mean20210317
Median Absolute Deviation (MAD)8
Skewness-0.11381719
Sum2.0210317 × 1011
Variance94.964894
MonotonicityNot monotonic
2024-05-11T02:32:53.914296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20210331 966
 
9.7%
20210302 587
 
5.9%
20210315 528
 
5.3%
20210330 481
 
4.8%
20210325 439
 
4.4%
20210310 437
 
4.4%
20210303 399
 
4.0%
20210322 392
 
3.9%
20210329 386
 
3.9%
20210305 365
 
3.6%
Other values (21) 5020
50.2%
ValueCountFrequency (%)
20210301 220
 
2.2%
20210302 587
5.9%
20210303 399
4.0%
20210304 365
3.6%
20210305 365
3.6%
20210306 85
 
0.9%
20210307 66
 
0.7%
20210308 354
3.5%
20210309 278
2.8%
20210310 437
4.4%
ValueCountFrequency (%)
20210331 966
9.7%
20210330 481
4.8%
20210329 386
 
3.9%
20210328 199
 
2.0%
20210327 124
 
1.2%
20210326 351
 
3.5%
20210325 439
4.4%
20210324 357
 
3.6%
20210323 305
 
3.0%
20210322 392
3.9%

금액
Real number (ℝ)

SKEWED 

Distinct3491
Distinct (%)34.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean223554.32
Minimum-3317010
Maximum69969490
Zeros14
Zeros (%)0.1%
Negative32
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T02:32:54.613135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3317010
5-th percentile190
Q13000
median30000
Q3100000
95-th percentile800000
Maximum69969490
Range73286500
Interquartile range (IQR)97000

Descriptive statistics

Standard deviation1338633.7
Coefficient of variation (CV)5.9879573
Kurtosis1255.1694
Mean223554.32
Median Absolute Deviation (MAD)28940
Skewness29.517957
Sum2.2355432 × 109
Variance1.7919403 × 1012
MonotonicityNot monotonic
2024-05-11T02:32:55.602355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 558
 
5.6%
100000 529
 
5.3%
50000 522
 
5.2%
150000 181
 
1.8%
70000 171
 
1.7%
60000 157
 
1.6%
200000 152
 
1.5%
40000 130
 
1.3%
120000 111
 
1.1%
80000 107
 
1.1%
Other values (3481) 7382
73.8%
ValueCountFrequency (%)
-3317010 1
< 0.1%
-3097600 1
< 0.1%
-1650000 1
< 0.1%
-1051630 1
< 0.1%
-586890 1
< 0.1%
-556820 1
< 0.1%
-462150 1
< 0.1%
-330000 1
< 0.1%
-315000 1
< 0.1%
-310910 1
< 0.1%
ValueCountFrequency (%)
69969490 1
< 0.1%
58599100 1
< 0.1%
39300000 1
< 0.1%
38280000 1
< 0.1%
19063636 1
< 0.1%
19030000 1
< 0.1%
18037000 1
< 0.1%
14274396 1
< 0.1%
14160000 1
< 0.1%
12682372 1
< 0.1%

내용
Text

Distinct5972
Distinct (%)59.8%
Missing8
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:32:56.549634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length69
Mean length14.091273
Min length1

Characters and Unicode

Total characters140800
Distinct characters740
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5730 ?
Unique (%)57.3%

Sample

1st row102동304호 전출 승강기 사용료
2nd row관리비 연체료 수납
3rd row201/606외 2건 승강기사용료 (전출입)
4th row장충금(하나)결산이자
5th row108-206호 확장공사시 승강기사용료 입금(24번)
ValueCountFrequency (%)
관리비 3526
 
13.6%
수납 3397
 
13.1%
연체료 3393
 
13.1%
승강기 315
 
1.2%
승강기사용료 289
 
1.1%
3월분 287
 
1.1%
279
 
1.1%
2월분 247
 
1.0%
입금 228
 
0.9%
사용료 214
 
0.8%
Other values (7366) 13718
53.0%
2024-05-11T02:32:58.287826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16014
 
11.4%
료 5420
 
3.8%
0 5055
 
3.6%
리 4982
 
3.5%
수 4967
 
3.5%
1 4847
 
3.4%
비 4361
 
3.1%
관 3847
 
2.7%
2 3804
 
2.7%
체 3558
 
2.5%
Other values (730) 83945
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90360
64.2%
Decimal Number 21629
 
15.4%
Space Separator 16014
 
11.4%
Close Punctuation 3175
 
2.3%
Open Punctuation 3166
 
2.2%
Other Punctuation 2826
 
2.0%
Dash Punctuation 2411
 
1.7%
Uppercase Letter 682
 
0.5%
Math Symbol 321
 
0.2%
Lowercase Letter 129
 
0.1%
Other values (4) 87
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5420
 
6.0%
리 4982
 
5.5%
수 4967
 
5.5%
비 4361
 
4.8%
관 3847
 
4.3%
체 3558
 
3.9%
연 3449
 
3.8%
납 3442
 
3.8%
자 1942
 
2.1%
금 1904
 
2.1%
Other values (639) 52488
58.1%
Uppercase Letter
ValueCountFrequency (%)
N 97
14.2%
C 64
 
9.4%
O 47
 
6.9%
R 42
 
6.2%
L 41
 
6.0%
K 40
 
5.9%
T 38
 
5.6%
A 38
 
5.6%
S 37
 
5.4%
E 36
 
5.3%
Other values (14) 202
29.6%
Lowercase Letter
ValueCountFrequency (%)
o 37
28.7%
x 12
 
9.3%
e 11
 
8.5%
s 11
 
8.5%
k 11
 
8.5%
c 9
 
7.0%
t 8
 
6.2%
n 7
 
5.4%
a 5
 
3.9%
l 5
 
3.9%
Other values (10) 13
 
10.1%
Other Punctuation
ValueCountFrequency (%)
/ 746
26.4%
, 724
25.6%
. 717
25.4%
: 201
 
7.1%
* 177
 
6.3%
? 165
 
5.8%
@ 40
 
1.4%
% 21
 
0.7%
# 12
 
0.4%
& 7
 
0.2%
Other values (6) 16
 
0.6%
Decimal Number
ValueCountFrequency (%)
0 5055
23.4%
1 4847
22.4%
2 3804
17.6%
3 2761
12.8%
4 1323
 
6.1%
5 1117
 
5.2%
6 821
 
3.8%
8 649
 
3.0%
7 635
 
2.9%
9 617
 
2.9%
Math Symbol
ValueCountFrequency (%)
~ 262
81.6%
> 16
 
5.0%
+ 16
 
5.0%
× 9
 
2.8%
< 8
 
2.5%
= 8
 
2.5%
→ 1
 
0.3%
∼ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3101
97.7%
] 73
 
2.3%
］ 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3092
97.7%
[ 73
 
2.3%
［ 1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
☞ 1
50.0%
㎡ 1
50.0%
Space Separator
ValueCountFrequency (%)
16014
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2411
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 83
100.0%
Other Number
ValueCountFrequency (%)
③ 1
100.0%
Letter Number
ValueCountFrequency (%)
ⅹ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90351
64.2%
Common 49628
35.2%
Latin 812
 
0.6%
Han 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5420
 
6.0%
리 4982
 
5.5%
수 4967
 
5.5%
비 4361
 
4.8%
관 3847
 
4.3%
체 3558
 
3.9%
연 3449
 
3.8%
납 3442
 
3.8%
자 1942
 
2.1%
금 1904
 
2.1%
Other values (632) 52479
58.1%
Common
ValueCountFrequency (%)
16014
32.3%
0 5055
 
10.2%
1 4847
 
9.8%
2 3804
 
7.7%
) 3101
 
6.2%
( 3092
 
6.2%
3 2761
 
5.6%
- 2411
 
4.9%
4 1323
 
2.7%
5 1117
 
2.3%
Other values (36) 6103
 
12.3%
Latin
ValueCountFrequency (%)
N 97
 
11.9%
C 64
 
7.9%
O 47
 
5.8%
R 42
 
5.2%
L 41
 
5.0%
K 40
 
4.9%
T 38
 
4.7%
A 38
 
4.7%
o 37
 
4.6%
S 37
 
4.6%
Other values (35) 331
40.8%
Han
ValueCountFrequency (%)
中 2
22.2%
入 2
22.2%
不 1
11.1%
人 1
11.1%
月 1
11.1%
分 1
11.1%
外 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90350
64.2%
ASCII 50422
35.8%
None 12
 
< 0.1%
CJK 8
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Misc Symbols 1
 
< 0.1%
Number Forms 1
 
< 0.1%
Arrows 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16014
31.8%
0 5055
 
10.0%
1 4847
 
9.6%
2 3804
 
7.5%
) 3101
 
6.2%
( 3092
 
6.1%
3 2761
 
5.5%
- 2411
 
4.8%
4 1323
 
2.6%
5 1117
 
2.2%
Other values (71) 6897
13.7%
Hangul
ValueCountFrequency (%)
료 5420
 
6.0%
리 4982
 
5.5%
수 4967
 
5.5%
비 4361
 
4.8%
관 3847
 
4.3%
체 3558
 
3.9%
연 3449
 
3.8%
납 3442
 
3.8%
자 1942
 
2.1%
금 1904
 
2.1%
Other values (631) 52478
58.1%
None
ValueCountFrequency (%)
× 9
75.0%
· 1
 
8.3%
］ 1
 
8.3%
［ 1
 
8.3%
CJK
ValueCountFrequency (%)
中 2
25.0%
入 2
25.0%
人 1
12.5%
月 1
12.5%
分 1
12.5%
外 1
12.5%
CJK Compat Ideographs
ValueCountFrequency (%)
不 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
③ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%
Misc Symbols
ValueCountFrequency (%)
☞ 1
100.0%
Number Forms
ValueCountFrequency (%)
ⅹ 1
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

Interactions

2024-05-11T02:32:45.472869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:44.574750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:45.884162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:32:44.986940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:32:58.627432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4890.148
년월일0.4891.0000.073
금액0.1480.0731.000
2024-05-11T02:32:58.878947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0230.205
금액0.0231.0000.067
비용명0.2050.0671.000

Missing values

2024-05-11T02:32:46.420704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:32:46.842007image/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
7770e편한세상마포리버파크A10028006승강기수익20210327100000102동304호 전출 승강기 사용료
55994관악푸르지오아파트A15105302연체료수익2021030440관리비 연체료 수납
28036역삼아이파크A13508009승강기수익2021032260000201/606외 2건 승강기사용료 (전출입)
51714군자일성파크A14383901이자수익202103208873장충금(하나)결산이자
68094신트리1단지A15807002승강기수익20210321100000108-206호 확장공사시 승강기사용료 입금(24번)
41977월계동현대A13905105승강기수익2021031650000107-301호 승강기사용료(인테리어)
45444상계주공7단지A13982704고용안정사업수익2021032332140일자리 안정자금 지원금(경비원 2월분 )
21187창동아이파크(창동2.3차현대)A13204404잡수익202103311050음식물카드 3장 *350원 잡수익 처리
11188홍제한양A12085303주차장수익202103193610외부인 주차료(신한카드)
43811중계4단지목화A13972603연체료수익202103222050관리비 연체료 수납
아파트명아파트코드비용명년월일금액내용
9796홍제성원아파트A12009201잡수익20210331200000공용부지 사용료(3월 현대홍익유치원)
2848백련산파크자이아파트A10025683기타운영수익2021033127168003월 락커, 골프, 음료 개별이용료
57448고척삼환로즈빌A15208003광고료수익20210325100000우편함광고(이마트신도림)
42089월계6-2초안A13905208알뜰시장수익2021030630000일일장 - 금
17766제기안암골벽산A13086101잡수익20210310700고용,산재 이체 할인
50089벽산라이브파크2차A14272310연체료수익202103306130관리비 연체료 수납
51909여의도금호리첸시아A15001005연체료수익202103305430관리비 연체료 수납
29165엘에이치강남브리즈힐A13520004승강기수익20210315110000409동302호세대공사 승강기사용료
56753해태보라매타워A15183001임대료수익20210310210000b5-1 바시코리아-3월
11727한강밤섬자이아파트A12115001재활용품수익20210325244000재활용수익(488-500,신성리사이클링) 3월