Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells5
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 = 51.84785192)Skewed

Reproduction

Analysis started2024-05-11 02:27:08.323935
Analysis finished2024-05-11 02:27:14.076328
Duration5.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2183
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:27:14.447699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.4841
Min length2

Characters and Unicode

Total characters74841
Distinct characters431
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

Unique247 ?
Unique (%)2.5%

Sample

1st row잠실파크리오
2nd row한화진넥스빌
3rd rowe편한세상 영등포 아델포레
4th row길음뉴타운11단지 롯데캐슬골든힐스아파트
5th row화곡대림아파트
ValueCountFrequency (%)
아파트 210
 
1.9%
래미안 58
 
0.5%
e편한세상 43
 
0.4%
아이파크 33
 
0.3%
고덕 29
 
0.3%
sk뷰 26
 
0.2%
마포래미안푸르지오 24
 
0.2%
센트럴 20
 
0.2%
영등포 20
 
0.2%
잠실엘스아파트 19
 
0.2%
Other values (2264) 10462
95.6%
2024-05-11T02:27:16.004214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 2643
 
3.5%
아 2638
 
3.5%
트 2528
 
3.4%
지 2072
 
2.8%
단 1615
 
2.2%
대 1605
 
2.1%
동 1554
 
2.1%
이 1523
 
2.0%
신 1385
 
1.9%
차 1251
 
1.7%
Other values (421) 56027
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68324
91.3%
Decimal Number 3620
 
4.8%
Space Separator 1055
 
1.4%
Uppercase Letter 926
 
1.2%
Lowercase Letter 365
 
0.5%
Close Punctuation 161
 
0.2%
Open Punctuation 161
 
0.2%
Dash Punctuation 131
 
0.2%
Other Punctuation 94
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2643
 
3.9%
아 2638
 
3.9%
트 2528
 
3.7%
지 2072
 
3.0%
단 1615
 
2.4%
대 1605
 
2.3%
동 1554
 
2.3%
이 1523
 
2.2%
신 1385
 
2.0%
차 1251
 
1.8%
Other values (376) 49510
72.5%
Uppercase Letter
ValueCountFrequency (%)
S 154
16.6%
C 124
13.4%
K 121
13.1%
D 98
10.6%
M 98
10.6%
L 48
 
5.2%
H 47
 
5.1%
I 47
 
5.1%
E 39
 
4.2%
A 32
 
3.5%
Other values (7) 118
12.7%
Lowercase Letter
ValueCountFrequency (%)
e 206
56.4%
l 32
 
8.8%
s 28
 
7.7%
k 28
 
7.7%
i 26
 
7.1%
v 20
 
5.5%
c 8
 
2.2%
w 7
 
1.9%
h 4
 
1.1%
a 3
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 1034
28.6%
2 1017
28.1%
3 459
12.7%
4 253
 
7.0%
5 227
 
6.3%
6 181
 
5.0%
7 146
 
4.0%
9 139
 
3.8%
8 84
 
2.3%
0 80
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 67
71.3%
. 27
28.7%
Space Separator
ValueCountFrequency (%)
1055
100.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68324
91.3%
Common 5222
 
7.0%
Latin 1295
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2643
 
3.9%
아 2638
 
3.9%
트 2528
 
3.7%
지 2072
 
3.0%
단 1615
 
2.4%
대 1605
 
2.3%
동 1554
 
2.3%
이 1523
 
2.2%
신 1385
 
2.0%
차 1251
 
1.8%
Other values (376) 49510
72.5%
Latin
ValueCountFrequency (%)
e 206
15.9%
S 154
11.9%
C 124
 
9.6%
K 121
 
9.3%
D 98
 
7.6%
M 98
 
7.6%
L 48
 
3.7%
H 47
 
3.6%
I 47
 
3.6%
E 39
 
3.0%
Other values (19) 313
24.2%
Common
ValueCountFrequency (%)
1055
20.2%
1 1034
19.8%
2 1017
19.5%
3 459
8.8%
4 253
 
4.8%
5 227
 
4.3%
6 181
 
3.5%
) 161
 
3.1%
( 161
 
3.1%
7 146
 
2.8%
Other values (6) 528
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68324
91.3%
ASCII 6513
 
8.7%
Number Forms 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 2643
 
3.9%
아 2638
 
3.9%
트 2528
 
3.7%
지 2072
 
3.0%
단 1615
 
2.4%
대 1605
 
2.3%
동 1554
 
2.3%
이 1523
 
2.2%
신 1385
 
2.0%
차 1251
 
1.8%
Other values (376) 49510
72.5%
ASCII
ValueCountFrequency (%)
1055
16.2%
1 1034
15.9%
2 1017
15.6%
3 459
 
7.0%
4 253
 
3.9%
5 227
 
3.5%
e 206
 
3.2%
6 181
 
2.8%
) 161
 
2.5%
( 161
 
2.5%
Other values (34) 1759
27.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%

아파트코드
Text

Distinct2188
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T02:27:17.045683image/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

Unique249 ?
Unique (%)2.5%

Sample

1st rowA13824006
2nd rowA13579504
3rd rowA10024725
4th rowA10025753
5th rowA15788302
ValueCountFrequency (%)
a12175203 24
 
0.2%
a13822004 19
 
0.2%
a13824006 18
 
0.2%
a10026988 18
 
0.2%
a13204409 18
 
0.2%
a12179004 18
 
0.2%
a10028021 17
 
0.2%
a13707010 17
 
0.2%
a13527203 17
 
0.2%
a13583507 17
 
0.2%
Other values (2178) 9817
98.2%
2024-05-11T02:27:18.415359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18727
20.8%
1 17070
19.0%
A 9997
11.1%
3 8640
9.6%
2 8421
9.4%
5 6204
 
6.9%
8 5393
 
6.0%
7 4812
 
5.3%
4 4280
 
4.8%
6 3400
 
3.8%
Other values (2) 3056
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
88.9%
Uppercase Letter 10000
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18727
23.4%
1 17070
21.3%
3 8640
10.8%
2 8421
10.5%
5 6204
 
7.8%
8 5393
 
6.7%
7 4812
 
6.0%
4 4280
 
5.3%
6 3400
 
4.2%
9 3053
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9997
> 99.9%
B 3
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18727
23.4%
1 17070
21.3%
3 8640
10.8%
2 8421
10.5%
5 6204
 
7.8%
8 5393
 
6.7%
7 4812
 
6.0%
4 4280
 
5.3%
6 3400
 
4.2%
9 3053
 
3.8%
Latin
ValueCountFrequency (%)
A 9997
> 99.9%
B 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18727
20.8%
1 17070
19.0%
A 9997
11.1%
3 8640
9.6%
2 8421
9.4%
5 6204
 
6.9%
8 5393
 
6.0%
7 4812
 
5.3%
4 4280
 
4.8%
6 3400
 
3.8%
Other values (2) 3056
 
3.4%

비용명
Categorical

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
연체료수익
3328 
잡수익
1000 
이자수익
977 
광고료수익
918 
주차장수익
892 
Other values (10)
2885 

Length

Max length9
Median length5
Mean length4.8017
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연체료수익 3328
33.3%
잡수익 1000
 
10.0%
이자수익 977
 
9.8%
광고료수익 918
 
9.2%
주차장수익 892
 
8.9%
승강기수익 841
 
8.4%
기타운영수익 809
 
8.1%
검침수익 307
 
3.1%
재활용품수익 228
 
2.3%
임대료수익 220
 
2.2%
Other values (5) 480
 
4.8%

Length

2024-05-11T02:27:19.071493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연체료수익 3328
33.3%
잡수익 1000
 
10.0%
이자수익 977
 
9.8%
광고료수익 918
 
9.2%
주차장수익 892
 
8.9%
승강기수익 841
 
8.4%
기타운영수익 809
 
8.1%
검침수익 307
 
3.1%
재활용품수익 228
 
2.3%
임대료수익 220
 
2.2%
Other values (5) 480
 
4.8%

년월일
Real number (ℝ)

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20221217
Minimum20221201
Maximum20221231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T02:27:19.503830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20221201
5-th percentile20221201
Q120221209
median20221218
Q320221226
95-th percentile20221231
Maximum20221231
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.5267349
Coefficient of variation (CV)4.7112568 × 10-7
Kurtosis-1.2440303
Mean20221217
Median Absolute Deviation (MAD)8
Skewness-0.17267573
Sum2.0221217 × 1011
Variance90.758677
MonotonicityNot monotonic
2024-05-11T02:27:20.073306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20221231 754
 
7.5%
20221230 540
 
5.4%
20221201 517
 
5.2%
20221212 481
 
4.8%
20221226 441
 
4.4%
20221205 424
 
4.2%
20221223 417
 
4.2%
20221227 416
 
4.2%
20221217 380
 
3.8%
20221219 368
 
3.7%
Other values (21) 5262
52.6%
ValueCountFrequency (%)
20221201 517
5.2%
20221202 344
3.4%
20221203 83
 
0.8%
20221204 69
 
0.7%
20221205 424
4.2%
20221206 325
3.2%
20221207 271
2.7%
20221208 262
2.6%
20221209 272
2.7%
20221210 327
3.3%
ValueCountFrequency (%)
20221231 754
7.5%
20221230 540
5.4%
20221229 367
3.7%
20221228 321
3.2%
20221227 416
4.2%
20221226 441
4.4%
20221225 283
 
2.8%
20221224 173
 
1.7%
20221223 417
4.2%
20221222 281
 
2.8%

금액
Real number (ℝ)

SKEWED 

Distinct3860
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean328090.53
Minimum-11326700
Maximum3.0056453 × 108
Zeros26
Zeros (%)0.3%
Negative64
Negative (%)0.6%
Memory size166.0 KiB
2024-05-11T02:27:20.564198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-11326700
5-th percentile100
Q12060.75
median20000
Q390000
95-th percentile970004
Maximum3.0056453 × 108
Range3.1189123 × 108
Interquartile range (IQR)87939.25

Descriptive statistics

Standard deviation4085538.1
Coefficient of variation (CV)12.452472
Kurtosis3346.1759
Mean328090.53
Median Absolute Deviation (MAD)19600
Skewness51.847852
Sum3.2809053 × 109
Variance1.6691621 × 1013
MonotonicityNot monotonic
2024-05-11T02:27:21.197941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 506
 
5.1%
30000 504
 
5.0%
100000 421
 
4.2%
60000 144
 
1.4%
40000 135
 
1.4%
70000 126
 
1.3%
150000 120
 
1.2%
200000 120
 
1.2%
20000 117
 
1.2%
500 95
 
0.9%
Other values (3850) 7712
77.1%
ValueCountFrequency (%)
-11326700 1
< 0.1%
-7700000 1
< 0.1%
-7510910 1
< 0.1%
-5494400 1
< 0.1%
-4477090 1
< 0.1%
-2357320 1
< 0.1%
-1500000 1
< 0.1%
-1443300 1
< 0.1%
-1302840 1
< 0.1%
-1192800 1
< 0.1%
ValueCountFrequency (%)
300564532 1
< 0.1%
169380000 1
< 0.1%
136080000 1
< 0.1%
61460100 1
< 0.1%
57386487 1
< 0.1%
50047900 1
< 0.1%
42803489 1
< 0.1%
40500000 1
< 0.1%
30336780 1
< 0.1%
29614100 1
< 0.1%

내용
Text

Distinct5909
Distinct (%)59.1%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T02:27:22.144578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length66
Mean length14.532766
Min length2

Characters and Unicode

Total characters145255
Distinct characters768
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5634 ?
Unique (%)56.4%

Sample

1st row독서실 월이용권2건
2nd row관리비 연체료 수납
3rd row11월 부과차익
4th row관리비 연체료 수납
5th row12월 주차료 수입(소녀수산-은동환)
ValueCountFrequency (%)
관리비 3513
 
13.2%
수납 3333
 
12.6%
연체료 3331
 
12.5%
624
 
2.4%
12월분 379
 
1.4%
12월 264
 
1.0%
승강기 262
 
1.0%
입금 206
 
0.8%
11월분 206
 
0.8%
사용료 200
 
0.8%
Other values (7620) 14235
53.6%
2024-05-11T02:27:23.864243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16912
 
11.6%
1 6866
 
4.7%
료 5266
 
3.6%
수 5135
 
3.5%
2 5046
 
3.5%
0 4562
 
3.1%
비 4364
 
3.0%
리 4294
 
3.0%
관 3926
 
2.7%
체 3561
 
2.5%
Other values (758) 85323
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89761
61.8%
Decimal Number 23606
 
16.3%
Space Separator 16912
 
11.6%
Other Punctuation 4823
 
3.3%
Open Punctuation 3208
 
2.2%
Close Punctuation 3207
 
2.2%
Dash Punctuation 2511
 
1.7%
Uppercase Letter 673
 
0.5%
Math Symbol 341
 
0.2%
Connector Punctuation 106
 
0.1%
Other values (4) 107
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
료 5266
 
5.9%
수 5135
 
5.7%
비 4364
 
4.9%
리 4294
 
4.8%
관 3926
 
4.4%
체 3561
 
4.0%
연 3421
 
3.8%
납 3391
 
3.8%
이 1801
 
2.0%
용 1626
 
1.8%
Other values (673) 52976
59.0%
Uppercase Letter
ValueCountFrequency (%)
T 70
 
10.4%
B 61
 
9.1%
N 58
 
8.6%
C 46
 
6.8%
K 45
 
6.7%
A 42
 
6.2%
L 38
 
5.6%
O 34
 
5.1%
E 34
 
5.1%
D 30
 
4.5%
Other values (15) 215
31.9%
Lowercase Letter
ValueCountFrequency (%)
o 29
28.2%
k 12
11.7%
s 12
11.7%
x 10
 
9.7%
t 7
 
6.8%
e 7
 
6.8%
n 7
 
6.8%
c 4
 
3.9%
d 3
 
2.9%
p 3
 
2.9%
Other values (8) 9
 
8.7%
Other Punctuation
ValueCountFrequency (%)
? 1924
39.9%
. 971
20.1%
/ 892
18.5%
, 638
 
13.2%
: 194
 
4.0%
* 111
 
2.3%
@ 29
 
0.6%
% 24
 
0.5%
# 14
 
0.3%
& 10
 
0.2%
Other values (3) 16
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 6866
29.1%
2 5046
21.4%
0 4562
19.3%
3 1810
 
7.7%
4 1284
 
5.4%
5 1041
 
4.4%
6 812
 
3.4%
7 796
 
3.4%
9 742
 
3.1%
8 647
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 299
87.7%
+ 13
 
3.8%
> 10
 
2.9%
× 9
 
2.6%
= 6
 
1.8%
< 2
 
0.6%
→ 1
 
0.3%
⇒ 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 3121
97.3%
[ 87
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 3120
97.3%
] 87
 
2.7%
Other Symbol
ValueCountFrequency (%)
㈜ 1
50.0%
㎡ 1
50.0%
Space Separator
ValueCountFrequency (%)
16912
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2511
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 106
100.0%
Other Number
ValueCountFrequency (%)
⑧ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 89752
61.8%
Common 54717
37.7%
Latin 776
 
0.5%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
료 5266
 
5.9%
수 5135
 
5.7%
비 4364
 
4.9%
리 4294
 
4.8%
관 3926
 
4.4%
체 3561
 
4.0%
연 3421
 
3.8%
납 3391
 
3.8%
이 1801
 
2.0%
용 1626
 
1.8%
Other values (669) 52967
59.0%
Latin
ValueCountFrequency (%)
T 70
 
9.0%
B 61
 
7.9%
N 58
 
7.5%
C 46
 
5.9%
K 45
 
5.8%
A 42
 
5.4%
L 38
 
4.9%
O 34
 
4.4%
E 34
 
4.4%
D 30
 
3.9%
Other values (33) 318
41.0%
Common
ValueCountFrequency (%)
16912
30.9%
1 6866
12.5%
2 5046
 
9.2%
0 4562
 
8.3%
( 3121
 
5.7%
) 3120
 
5.7%
- 2511
 
4.6%
? 1924
 
3.5%
3 1810
 
3.3%
4 1284
 
2.3%
Other values (31) 7561
13.8%
Han
ValueCountFrequency (%)
入 6
60.0%
內 1
 
10.0%
月 1
 
10.0%
分 1
 
10.0%
不 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89749
61.8%
ASCII 55480
38.2%
None 10
 
< 0.1%
CJK 10
 
< 0.1%
Compat Jamo 2
 
< 0.1%
Arrows 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16912
30.5%
1 6866
12.4%
2 5046
 
9.1%
0 4562
 
8.2%
( 3121
 
5.6%
) 3120
 
5.6%
- 2511
 
4.5%
? 1924
 
3.5%
3 1810
 
3.3%
4 1284
 
2.3%
Other values (69) 8324
15.0%
Hangul
ValueCountFrequency (%)
료 5266
 
5.9%
수 5135
 
5.7%
비 4364
 
4.9%
리 4294
 
4.8%
관 3926
 
4.4%
체 3561
 
4.0%
연 3421
 
3.8%
납 3391
 
3.8%
이 1801
 
2.0%
용 1626
 
1.8%
Other values (666) 52964
59.0%
None
ValueCountFrequency (%)
× 9
90.0%
㈜ 1
 
10.0%
CJK
ValueCountFrequency (%)
入 6
60.0%
內 1
 
10.0%
月 1
 
10.0%
分 1
 
10.0%
不 1
 
10.0%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
50.0%
ㅇ 1
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
⑧ 1
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
Arrows
ValueCountFrequency (%)
→ 1
50.0%
⇒ 1
50.0%

Interactions

2024-05-11T02:27:12.239212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:27:11.149545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:27:12.723325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:27:11.637324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T02:27:24.259962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명년월일금액
비용명1.0000.4770.179
년월일0.4771.0000.036
금액0.1790.0361.000
2024-05-11T02:27:24.547427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년월일금액비용명
년월일1.0000.0300.199
금액0.0301.0000.084
비용명0.1990.0841.000

Missing values

2024-05-11T02:27:13.269119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T02:27:13.913122image/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
38496잠실파크리오A13824006기타운영수익20221225100000독서실 월이용권2건
29848한화진넥스빌A13579504연체료수익202212314840관리비 연체료 수납
2496e편한세상 영등포 아델포레A10024725잡수익20221222138111월 부과차익
5046길음뉴타운11단지 롯데캐슬골든힐스아파트A10025753연체료수익202212312070관리비 연체료 수납
61594화곡대림아파트A15788302주차장수익202212287000012월 주차료 수입(소녀수산-은동환)
25610성내2차e-편한세상A13403001연체료수익202212274050관리비 연체료 수납
8639개포4차현대아파트A10027571연체료수익2022122717360관리비 연체료 수납
55622관악벽산타운5단지A15303205재활용품수익202212312388500???? ??(23.01.01~23.12.31)28,662,000?? 1/12??/????
8348상도파크자이 아파트A10027424재활용품수익2022123123636412월분 재활용품판매수익[(삼성리사이클링]
10977효성주얼리시티아파트A11041001기타운영수익20221215-3300헬스출입카드보증금 환급/B-712/남 헬스56
아파트명아파트코드비용명년월일금액내용
43565월계동신A13984604광고료수익2022121730000일일장 - 과일
2366용산센트럴파크A10024691연체료수익2022121371730관리비 연체료 수납
55899독산계룡A15381402주차장수익20221207800002022. 12월 주차료 - FANGTIANS
38901잠실5단지아파트A13879102연체료수익202212191330관리비 연체료 수납
40703중계양지대림2차A13922110광고료수익2022121215000원교육원 연구소 광고수입(201-201)주민 할인 53.
30106은마A13583507승강기수익2022120955000승강기사용료(17-1003)
16658수색대림한숲타운제2A12287203연체료수익20221219770관리비 연체료 수납
50449당산현대5차A15080507연체료수익20221214590관리비 연체료 수납
40056상계우방A13920001연체료수익202212015530관리비 연체료 수납
13165마포도화우성아파트A12104007승강기수익20221207200000전입시 승강기 사용료 입금(13-308호)