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 = 27.12069923)Skewed

Reproduction

Analysis started2024-05-11 02:25:23.790106
Analysis finished2024-05-11 02:25:27.144234
Duration3.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2180
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:25:27.442864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.596
Min length2

Characters and Unicode

Total characters75960
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

Unique229 ?
Unique (%)2.3%

Sample

1st row홍제태영으뜸
2nd row한남하이츠
3rd row광장현대5단지
4th row고덕센트럴 아이파크
5th row목동금호어울림
ValueCountFrequency (%)
아파트 248
 
2.2%
래미안 71
 
0.6%
e편한세상 46
 
0.4%
아이파크 42
 
0.4%
sk뷰 29
 
0.3%
송파 29
 
0.3%
롯데캐슬아파트 27
 
0.2%
고덕 27
 
0.2%
센트럴 24
 
0.2%
디에이치 24
 
0.2%
Other values (2266) 10619
94.9%
2024-05-11T02:25:28.287627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2694
 
3.5%
파 2658
 
3.5%
트 2650
 
3.5%
지 2119
 
2.8%
단 1645
 
2.2%
대 1553
 
2.0%
이 1546
 
2.0%
동 1476
 
1.9%
1301
 
1.7%
신 1274
 
1.7%
Other values (423) 57044
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69280
91.2%
Decimal Number 3572
 
4.7%
Space Separator 1301
 
1.7%
Uppercase Letter 939
 
1.2%
Lowercase Letter 328
 
0.4%
Close Punctuation 163
 
0.2%
Open Punctuation 163
 
0.2%
Dash Punctuation 111
 
0.1%
Other Punctuation 95
 
0.1%
Letter Number 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2694
 
3.9%
파 2658
 
3.8%
트 2650
 
3.8%
지 2119
 
3.1%
단 1645
 
2.4%
대 1553
 
2.2%
이 1546
 
2.2%
동 1476
 
2.1%
신 1274
 
1.8%
차 1232
 
1.8%
Other values (378) 50433
72.8%
Uppercase Letter
ValueCountFrequency (%)
S 150
16.0%
C 137
14.6%
K 131
14.0%
M 92
9.8%
D 92
9.8%
I 49
 
5.2%
E 46
 
4.9%
L 41
 
4.4%
H 40
 
4.3%
A 34
 
3.6%
Other values (7) 127
13.5%
Lowercase Letter
ValueCountFrequency (%)
e 209
63.7%
s 26
 
7.9%
l 24
 
7.3%
k 23
 
7.0%
i 17
 
5.2%
v 13
 
4.0%
h 5
 
1.5%
c 4
 
1.2%
w 3
 
0.9%
a 2
 
0.6%
Decimal Number
ValueCountFrequency (%)
2 1034
28.9%
1 1028
28.8%
3 467
13.1%
4 245
 
6.9%
5 205
 
5.7%
6 168
 
4.7%
7 134
 
3.8%
8 116
 
3.2%
9 99
 
2.8%
0 76
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 75
78.9%
. 20
 
21.1%
Space Separator
ValueCountFrequency (%)
1301
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Open Punctuation
ValueCountFrequency (%)
( 163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69280
91.2%
Common 5405
 
7.1%
Latin 1275
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2694
 
3.9%
파 2658
 
3.8%
트 2650
 
3.8%
지 2119
 
3.1%
단 1645
 
2.4%
대 1553
 
2.2%
이 1546
 
2.2%
동 1476
 
2.1%
신 1274
 
1.8%
차 1232
 
1.8%
Other values (378) 50433
72.8%
Latin
ValueCountFrequency (%)
e 209
16.4%
S 150
11.8%
C 137
10.7%
K 131
10.3%
M 92
 
7.2%
D 92
 
7.2%
I 49
 
3.8%
E 46
 
3.6%
L 41
 
3.2%
H 40
 
3.1%
Other values (19) 288
22.6%
Common
ValueCountFrequency (%)
1301
24.1%
2 1034
19.1%
1 1028
19.0%
3 467
 
8.6%
4 245
 
4.5%
5 205
 
3.8%
6 168
 
3.1%
) 163
 
3.0%
( 163
 
3.0%
7 134
 
2.5%
Other values (6) 497
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69280
91.2%
ASCII 6672
 
8.8%
Number Forms 8
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2694
 
3.9%
파 2658
 
3.8%
트 2650
 
3.8%
지 2119
 
3.1%
단 1645
 
2.4%
대 1553
 
2.2%
이 1546
 
2.2%
동 1476
 
2.1%
신 1274
 
1.8%
차 1232
 
1.8%
Other values (378) 50433
72.8%
ASCII
ValueCountFrequency (%)
1301
19.5%
2 1034
15.5%
1 1028
15.4%
3 467
 
7.0%
4 245
 
3.7%
e 209
 
3.1%
5 205
 
3.1%
6 168
 
2.5%
) 163
 
2.4%
( 163
 
2.4%
Other values (34) 1689
25.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 8
100.0%

아파트코드
Text

Distinct2183
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:25:28.931010image/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

Unique230 ?
Unique (%)2.3%

Sample

1st rowA12086001
2nd rowA13375901
3rd rowA14381512
4th rowA10025104
5th rowA15805403
ValueCountFrequency (%)
a13822004 23
 
0.2%
a13377703 22
 
0.2%
a10023887 20
 
0.2%
a13527203 20
 
0.2%
a13201209 20
 
0.2%
a13824006 19
 
0.2%
a13405201 19
 
0.2%
a10026988 19
 
0.2%
a10025614 19
 
0.2%
a10026180 18
 
0.2%
Other values (2173) 9801
98.0%
2024-05-11T02:25:30.075505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18932
21.0%
1 16999
18.9%
A 9982
11.1%
2 8630
9.6%
3 8605
9.6%
5 6176
 
6.9%
8 5365
 
6.0%
7 4776
 
5.3%
4 4218
 
4.7%
6 3365
 
3.7%
Other values (2) 2952
 
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 18932
23.7%
1 16999
21.2%
2 8630
10.8%
3 8605
10.8%
5 6176
 
7.7%
8 5365
 
6.7%
7 4776
 
6.0%
4 4218
 
5.3%
6 3365
 
4.2%
9 2934
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9982
99.8%
B 18
 
0.2%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18932
23.7%
1 16999
21.2%
2 8630
10.8%
3 8605
10.8%
5 6176
 
7.7%
8 5365
 
6.7%
7 4776
 
6.0%
4 4218
 
5.3%
6 3365
 
4.2%
9 2934
 
3.7%
Latin
ValueCountFrequency (%)
A 9982
99.8%
B 18
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18932
21.0%
1 16999
18.9%
A 9982
11.1%
2 8630
9.6%
3 8605
9.6%
5 6176
 
6.9%
8 5365
 
6.0%
7 4776
 
5.3%
4 4218
 
4.7%
6 3365
 
3.7%
Other values (2) 2952
 
3.3%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3233 
승강기수익
1105 
잡수익
994 
주차장수익
966 
기타운영수익
959 
Other values (10)
2743 

Length

Max length9
Median length5
Mean length4.8261
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row주차장수익
2nd row주차장수익
3rd row승강기수익
4th row기타운영수익
5th row광고료수익

Common Values

ValueCountFrequency (%)
연체료수익 3233
32.3%
승강기수익 1105
 
11.1%
잡수익 994
 
9.9%
주차장수익 966
 
9.7%
기타운영수익 959
 
9.6%
광고료수익 847
 
8.5%
이자수익 679
 
6.8%
검침수익 331
 
3.3%
부과차익 260
 
2.6%
임대료수익 221
 
2.2%
Other values (5) 405
 
4.0%

Length

2024-05-11T02:25:30.600707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3233
32.3%
승강기수익 1105
 
11.1%
잡수익 994
 
9.9%
주차장수익 966
 
9.7%
기타운영수익 959
 
9.6%
광고료수익 847
 
8.5%
이자수익 679
 
6.8%
검침수익 331
 
3.3%
부과차익 260
 
2.6%
임대료수익 221
 
2.2%
Other values (5) 405
 
4.0%

년월일
Real number (ℝ)

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230916
Minimum20230901
Maximum20230930
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:25:31.166681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230901
5-th percentile20230901
Q120230908
median20230916
Q320230925
95-th percentile20230930
Maximum20230930
Range29
Interquartile range (IQR)17

Descriptive statistics

Standard deviation8.9627315
Coefficient of variation (CV)4.4302154 × 10-7
Kurtosis-1.2520784
Mean20230916
Median Absolute Deviation (MAD)8
Skewness-0.05959283
Sum2.0230916 × 1011
Variance80.330557
MonotonicityNot monotonic
2024-05-11T02:25:31.737216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20230930 745
 
7.4%
20230925 580
 
5.8%
20230927 573
 
5.7%
20230901 530
 
5.3%
20230911 522
 
5.2%
20230904 487
 
4.9%
20230905 466
 
4.7%
20230918 429
 
4.3%
20230926 412
 
4.1%
20230916 400
 
4.0%
Other values (20) 4856
48.6%
ValueCountFrequency (%)
20230901 530
5.3%
20230902 123
 
1.2%
20230903 103
 
1.0%
20230904 487
4.9%
20230905 466
4.7%
20230906 380
3.8%
20230907 313
3.1%
20230908 372
3.7%
20230909 167
 
1.7%
20230910 79
 
0.8%
ValueCountFrequency (%)
20230930 745
7.4%
20230929 94
 
0.9%
20230928 157
 
1.6%
20230927 573
5.7%
20230926 412
4.1%
20230925 580
5.8%
20230924 232
 
2.3%
20230923 145
 
1.5%
20230922 371
3.7%
20230921 336
3.4%

금액
Real number (ℝ)

SKEWED 

Distinct3646
Distinct (%)36.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317933.09
Minimum-30126590
Maximum1.261065 × 108
Zeros19
Zeros (%)0.2%
Negative40
Negative (%)0.4%
Memory size166.0 KiB
2024-05-11T02:25:32.334241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-30126590
5-th percentile150
Q12190
median24915.5
Q3100000
95-th percentile1170700
Maximum1.261065 × 108
Range1.5623309 × 108
Interquartile range (IQR)97810

Descriptive statistics

Standard deviation2244194.2
Coefficient of variation (CV)7.0586996
Kurtosis1200.8487
Mean317933.09
Median Absolute Deviation (MAD)24482
Skewness27.120699
Sum3.1793309 × 109
Variance5.0364074 × 1012
MonotonicityNot monotonic
2024-05-11T02:25:33.240184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 523
 
5.2%
30000 506
 
5.1%
50000 444
 
4.4%
150000 169
 
1.7%
60000 157
 
1.6%
70000 153
 
1.5%
40000 126
 
1.3%
200000 120
 
1.2%
20000 114
 
1.1%
80000 102
 
1.0%
Other values (3636) 7586
75.9%
ValueCountFrequency (%)
-30126590 1
< 0.1%
-7287500 1
< 0.1%
-5022570 1
< 0.1%
-4850000 1
< 0.1%
-4300000 1
< 0.1%
-2356364 1
< 0.1%
-550000 1
< 0.1%
-260000 1
< 0.1%
-231000 1
< 0.1%
-200000 1
< 0.1%
ValueCountFrequency (%)
126106500 1
< 0.1%
71392920 1
< 0.1%
59099955 1
< 0.1%
45000000 1
< 0.1%
43309091 1
< 0.1%
37740170 1
< 0.1%
35515000 1
< 0.1%
30000000 1
< 0.1%
29568000 1
< 0.1%
26666666 1
< 0.1%

내용
Text

Distinct6003
Distinct (%)60.1%
Missing12
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T02:25:34.476344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length67
Mean length14.726572
Min length2

Characters and Unicode

Total characters147089
Distinct characters739
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5734 ?
Unique (%)57.4%

Sample

1st row805호-3차량 8만원, 1003호 3만원, 803호(이재준) 5만원) 09월분 입금
2nd row1-905호외
3rd row승강기사용료 전입(504동902호)
4th row9월분 카페더 센트럴추가 이용세대,키즈룸 이용세대 부과분
5th row게시판광고료-태학관
ValueCountFrequency (%)
관리비 3404
 
12.6%
연체료 3237
 
12.0%
수납 3235
 
12.0%
9월분 406
 
1.5%
승강기 373
 
1.4%
353
 
1.3%
승강기사용료 289
 
1.1%
9월 275
 
1.0%
사용료 255
 
0.9%
8월분 192
 
0.7%
Other values (7785) 15025
55.6%
2024-05-11T02:25:36.092619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17442
 
11.9%
0 5720
 
3.9%
료 5544
 
3.8%
1 5252
 
3.6%
수 4963
 
3.4%
비 4243
 
2.9%
리 4186
 
2.8%
관 3761
 
2.6%
체 3475
 
2.4%
2 3425
 
2.3%
Other values (729) 89078
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91483
62.2%
Decimal Number 24551
 
16.7%
Space Separator 17442
 
11.9%
Close Punctuation 3291
 
2.2%
Open Punctuation 3276
 
2.2%
Other Punctuation 3018
 
2.1%
Dash Punctuation 2624
 
1.8%
Uppercase Letter 741
 
0.5%
Math Symbol 397
 
0.3%
Lowercase Letter 156
 
0.1%
Other values (5) 110
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5544
 
6.1%
수 4963
 
5.4%
비 4243
 
4.6%
리 4186
 
4.6%
관 3761
 
4.1%
체 3475
 
3.8%
연 3343
 
3.7%
납 3297
 
3.6%
용 1885
 
2.1%
사 1803
 
2.0%
Other values (639) 54983
60.1%
Uppercase Letter
ValueCountFrequency (%)
N 73
 
9.9%
C 63
 
8.5%
K 60
 
8.1%
T 57
 
7.7%
B 54
 
7.3%
G 47
 
6.3%
L 47
 
6.3%
S 43
 
5.8%
O 41
 
5.5%
A 37
 
5.0%
Other values (14) 219
29.6%
Lowercase Letter
ValueCountFrequency (%)
o 39
25.0%
c 14
 
9.0%
n 13
 
8.3%
s 13
 
8.3%
e 12
 
7.7%
t 10
 
6.4%
k 9
 
5.8%
a 7
 
4.5%
x 6
 
3.8%
u 5
 
3.2%
Other values (13) 28
17.9%
Other Punctuation
ValueCountFrequency (%)
/ 991
32.8%
. 969
32.1%
, 673
22.3%
: 198
 
6.6%
* 89
 
2.9%
@ 28
 
0.9%
% 27
 
0.9%
& 16
 
0.5%
# 15
 
0.5%
' 7
 
0.2%
Other values (3) 5
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 5720
23.3%
1 5252
21.4%
2 3425
14.0%
9 2336
9.5%
3 2089
 
8.5%
4 1462
 
6.0%
8 1274
 
5.2%
5 1187
 
4.8%
6 940
 
3.8%
7 866
 
3.5%
Math Symbol
ValueCountFrequency (%)
~ 340
85.6%
> 17
 
4.3%
+ 15
 
3.8%
× 9
 
2.3%
< 8
 
2.0%
= 4
 
1.0%
＞ 2
 
0.5%
÷ 1
 
0.3%
⇒ 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3184
96.7%
] 107
 
3.3%
Open Punctuation
ValueCountFrequency (%)
( 3168
96.7%
[ 108
 
3.3%
Space Separator
ValueCountFrequency (%)
17442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2624
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 102
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%
Currency Symbol
ValueCountFrequency (%)
￦ 2
100.0%
Other Symbol
ValueCountFrequency (%)
☆ 2
100.0%
Other Number
ValueCountFrequency (%)
① 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91478
62.2%
Common 54709
37.2%
Latin 897
 
0.6%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5544
 
6.1%
수 4963
 
5.4%
비 4243
 
4.6%
리 4186
 
4.6%
관 3761
 
4.1%
체 3475
 
3.8%
연 3343
 
3.7%
납 3297
 
3.6%
용 1885
 
2.1%
사 1803
 
2.0%
Other values (637) 54978
60.1%
Latin
ValueCountFrequency (%)
N 73
 
8.1%
C 63
 
7.0%
K 60
 
6.7%
T 57
 
6.4%
B 54
 
6.0%
G 47
 
5.2%
L 47
 
5.2%
S 43
 
4.8%
O 41
 
4.6%
o 39
 
4.3%
Other values (37) 373
41.6%
Common
ValueCountFrequency (%)
17442
31.9%
0 5720
 
10.5%
1 5252
 
9.6%
2 3425
 
6.3%
) 3184
 
5.8%
( 3168
 
5.8%
- 2624
 
4.8%
9 2336
 
4.3%
3 2089
 
3.8%
4 1462
 
2.7%
Other values (33) 8007
14.6%
Han
ValueCountFrequency (%)
入 4
80.0%
大 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91478
62.2%
ASCII 55587
37.8%
None 15
 
< 0.1%
CJK 5
 
< 0.1%
Misc Symbols 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
Arrows 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17442
31.4%
0 5720
 
10.3%
1 5252
 
9.4%
2 3425
 
6.2%
) 3184
 
5.7%
( 3168
 
5.7%
- 2624
 
4.7%
9 2336
 
4.2%
3 2089
 
3.8%
4 1462
 
2.6%
Other values (72) 8885
16.0%
Hangul
ValueCountFrequency (%)
료 5544
 
6.1%
수 4963
 
5.4%
비 4243
 
4.6%
리 4186
 
4.6%
관 3761
 
4.1%
체 3475
 
3.8%
연 3343
 
3.7%
납 3297
 
3.6%
용 1885
 
2.1%
사 1803
 
2.0%
Other values (637) 54978
60.1%
None
ValueCountFrequency (%)
× 9
60.0%
￦ 2
 
13.3%
＞ 2
 
13.3%
÷ 1
 
6.7%
· 1
 
6.7%
CJK
ValueCountFrequency (%)
入 4
80.0%
大 1
 
20.0%
Misc Symbols
ValueCountFrequency (%)
☆ 2
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 1
100.0%
Arrows
ValueCountFrequency (%)
⇒ 1
100.0%

Interactions

2024-05-11T02:25:25.951554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:25:25.414439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:25:26.208244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:25:25.707752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:25:36.416092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.5040.335
년월일0.5041.0000.299
금액0.3350.2991.000
2024-05-11T02:25:36.742556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0380.210
금액0.0381.0000.146
비용명0.2100.1461.000

Missing values

2024-05-11T02:25:26.621621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:25:26.986764image/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
12277홍제태영으뜸A12086001주차장수익20230927160000805호-3차량 8만원, 1003호 3만원, 803호(이재준) 5만원) 09월분 입금
22011한남하이츠A13375901주차장수익20230927600001-905호외
42924광장현대5단지A14381512승강기수익2023092790910승강기사용료 전입(504동902호)
3911고덕센트럴 아이파크A10025104기타운영수익20230930123962009월분 카페더 센트럴추가 이용세대,키즈룸 이용세대 부과분
55156목동금호어울림A15805403광고료수익2023090650000게시판광고료-태학관
10825롯데캐슬천지인A11087601주차장수익2023092683591현대카드
52565등촌주공5단지A15703309이자수익202309165495신한은 관리비통장에 대한 수입이자
22979성수한강한신A13382802기타운영수익20230905181829월 창고관리비
46287관악드림타운제2A15105503잡수익20230920100548월발생분 부과차액
23567암사삼성광나루A13405002광고료수익2023091160000게시판광고 - 정관장
아파트명아파트코드비용명년월일금액내용
18762신내새한아파트A13187406재활용품수익20230927212800재활용 기금 입금 [10월분]
6532래미안서초에스티지에스아파트A10026411승강기수익20230915200000승강기수입(204-404)9/23전출
26220일원목련타운A13523005승강기수익20230911300000승강기 사용료(102-504)세대보수공사
33271송파파크데일2단지A13812005임대료수익202309118000002023.05월 임대료
3558신촌숲 아이파크 아파트A10024974승강기수익20230918100000107-406 승강기사용료/전출
23978강일리버파크2단지A13410003기타운영수익202309301500009월 어린이집시설관리수입
36091상계주공16단지A13920803부과차익20230930120509월 관리비 부과차액
3103DMC롯데캐슬더퍼스트A10024828기타운영수익20230908941270국민카드 휘트니스 카드매출
42245자양더샵스타시티A14319012승강기수익2023091150000B동2506호 전출 승강기이용료
21229마장신성미소지움A13305003주차장수익202309302586670주차수입(내부)