Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory488.3 KiB
Average record size in memory50.0 B

Variable types

Text3
Categorical1
Numeric1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15820/S/1/datasetView.do

Alerts

년월일 has constant value ""Constant
금액 has 2324 (23.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:55:45.000521
Analysis finished2024-05-11 05:55:46.252271
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2118
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:55:46.522195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length7.3526
Min length2

Characters and Unicode

Total characters73526
Distinct characters432
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

Unique106 ?
Unique (%)1.1%

Sample

1st row방배대우효령
2nd row신내동성3차아파트
3rd row보라매삼성쉐르빌
4th row염창한화꿈에그린
5th row신월수명산SK-VIEW
ValueCountFrequency (%)
아파트 171
 
1.6%
래미안 35
 
0.3%
e편한세상 30
 
0.3%
아이파크 28
 
0.3%
sk뷰 22
 
0.2%
이편한세상 19
 
0.2%
답십리우성그린 16
 
0.1%
푸르지오 16
 
0.1%
경남아너스빌 13
 
0.1%
송파 13
 
0.1%
Other values (2200) 10448
96.6%
2024-05-11T14:55:47.195524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2452
 
3.3%
파 2446
 
3.3%
트 2360
 
3.2%
지 1784
 
2.4%
대 1709
 
2.3%
동 1609
 
2.2%
차 1507
 
2.0%
신 1465
 
2.0%
이 1403
 
1.9%
단 1369
 
1.9%
Other values (422) 55422
75.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67453
91.7%
Decimal Number 3554
 
4.8%
Space Separator 892
 
1.2%
Uppercase Letter 855
 
1.2%
Lowercase Letter 270
 
0.4%
Close Punctuation 137
 
0.2%
Open Punctuation 137
 
0.2%
Dash Punctuation 121
 
0.2%
Other Punctuation 101
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2452
 
3.6%
파 2446
 
3.6%
트 2360
 
3.5%
지 1784
 
2.6%
대 1709
 
2.5%
동 1609
 
2.4%
차 1507
 
2.2%
신 1465
 
2.2%
이 1403
 
2.1%
단 1369
 
2.0%
Other values (377) 49349
73.2%
Uppercase Letter
ValueCountFrequency (%)
S 157
18.4%
K 120
14.0%
C 109
12.7%
D 72
8.4%
M 72
8.4%
H 51
 
6.0%
L 50
 
5.8%
I 46
 
5.4%
E 44
 
5.1%
V 29
 
3.4%
Other values (7) 105
12.3%
Lowercase Letter
ValueCountFrequency (%)
e 177
65.6%
s 19
 
7.0%
i 18
 
6.7%
k 16
 
5.9%
l 12
 
4.4%
w 11
 
4.1%
v 9
 
3.3%
h 4
 
1.5%
c 2
 
0.7%
g 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 1055
29.7%
2 1036
29.2%
3 473
13.3%
4 264
 
7.4%
5 195
 
5.5%
6 158
 
4.4%
8 105
 
3.0%
7 99
 
2.8%
9 97
 
2.7%
0 72
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 78
77.2%
. 23
 
22.8%
Space Separator
ValueCountFrequency (%)
892
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67453
91.7%
Common 4942
 
6.7%
Latin 1131
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2452
 
3.6%
파 2446
 
3.6%
트 2360
 
3.5%
지 1784
 
2.6%
대 1709
 
2.5%
동 1609
 
2.4%
차 1507
 
2.2%
신 1465
 
2.2%
이 1403
 
2.1%
단 1369
 
2.0%
Other values (377) 49349
73.2%
Latin
ValueCountFrequency (%)
e 177
15.6%
S 157
13.9%
K 120
10.6%
C 109
9.6%
D 72
 
6.4%
M 72
 
6.4%
H 51
 
4.5%
L 50
 
4.4%
I 46
 
4.1%
E 44
 
3.9%
Other values (19) 233
20.6%
Common
ValueCountFrequency (%)
1 1055
21.3%
2 1036
21.0%
892
18.0%
3 473
9.6%
4 264
 
5.3%
5 195
 
3.9%
6 158
 
3.2%
) 137
 
2.8%
( 137
 
2.8%
- 121
 
2.4%
Other values (6) 474
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67453
91.7%
ASCII 6067
 
8.3%
Number Forms 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2452
 
3.6%
파 2446
 
3.6%
트 2360
 
3.5%
지 1784
 
2.6%
대 1709
 
2.5%
동 1609
 
2.4%
차 1507
 
2.2%
신 1465
 
2.2%
이 1403
 
2.1%
단 1369
 
2.0%
Other values (377) 49349
73.2%
ASCII
ValueCountFrequency (%)
1 1055
17.4%
2 1036
17.1%
892
14.7%
3 473
 
7.8%
4 264
 
4.4%
5 195
 
3.2%
e 177
 
2.9%
6 158
 
2.6%
S 157
 
2.6%
) 137
 
2.3%
Other values (34) 1523
25.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 6
100.0%

아파트코드
Text

Distinct2122
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:55:47.768965image/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

Unique106 ?
Unique (%)1.1%

Sample

1st rowA13706303
2nd rowA13113004
3rd rowA15672002
4th rowA15786424
5th rowA15882201
ValueCountFrequency (%)
a13003404 16
 
0.2%
a13681701 13
 
0.1%
a14072901 13
 
0.1%
a13984004 12
 
0.1%
a13822003 12
 
0.1%
a12182901 12
 
0.1%
a12010203 12
 
0.1%
a13824001 11
 
0.1%
a15205405 11
 
0.1%
a13983712 11
 
0.1%
Other values (2112) 9877
98.8%
2024-05-11T14:55:48.488497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18539
20.6%
1 17548
19.5%
A 9987
11.1%
3 8854
9.8%
2 8398
9.3%
5 6148
 
6.8%
8 5500
 
6.1%
7 4572
 
5.1%
4 4151
 
4.6%
6 3372
 
3.7%
Other values (2) 2931
 
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 18539
23.2%
1 17548
21.9%
3 8854
11.1%
2 8398
10.5%
5 6148
 
7.7%
8 5500
 
6.9%
7 4572
 
5.7%
4 4151
 
5.2%
6 3372
 
4.2%
9 2918
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 9987
99.9%
B 13
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18539
23.2%
1 17548
21.9%
3 8854
11.1%
2 8398
10.5%
5 6148
 
7.7%
8 5500
 
6.9%
7 4572
 
5.7%
4 4151
 
5.2%
6 3372
 
4.2%
9 2918
 
3.6%
Latin
ValueCountFrequency (%)
A 9987
99.9%
B 13
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18539
20.6%
1 17548
19.5%
A 9987
11.1%
3 8854
9.8%
2 8398
9.3%
5 6148
 
6.8%
8 5500
 
6.1%
7 4572
 
5.1%
4 4151
 
4.6%
6 3372
 
3.7%
Other values (2) 2931
 
3.3%

비용명
Text

Distinct76
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:55:48.930740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length5.9898
Min length2

Characters and Unicode

Total characters59898
Distinct characters107
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row퇴직급여충당부채
2nd row선수관리비
3rd row공동체활성화단체지원적립금
4th row상여충당부채
5th row퇴직급여충당부채
ValueCountFrequency (%)
당기순이익 353
 
3.5%
미처분이익잉여금 340
 
3.4%
공동주택적립금 319
 
3.2%
선급비용 312
 
3.1%
관리비미수금 311
 
3.1%
연차수당충당부채 310
 
3.1%
퇴직급여충당부채 304
 
3.0%
장기수선충당부채 299
 
3.0%
예금 298
 
3.0%
예수금 298
 
3.0%
Other values (66) 6856
68.6%
2024-05-11T14:55:49.559055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 4583
 
7.7%
당 3856
 
6.4%
수 3107
 
5.2%
충 3003
 
5.0%
비 2987
 
5.0%
부 2876
 
4.8%
채 2619
 
4.4%
기 2530
 
4.2%
선 1913
 
3.2%
예 1684
 
2.8%
Other values (97) 30740
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59898
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 4583
 
7.7%
당 3856
 
6.4%
수 3107
 
5.2%
충 3003
 
5.0%
비 2987
 
5.0%
부 2876
 
4.8%
채 2619
 
4.4%
기 2530
 
4.2%
선 1913
 
3.2%
예 1684
 
2.8%
Other values (97) 30740
51.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59898
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 4583
 
7.7%
당 3856
 
6.4%
수 3107
 
5.2%
충 3003
 
5.0%
비 2987
 
5.0%
부 2876
 
4.8%
채 2619
 
4.4%
기 2530
 
4.2%
선 1913
 
3.2%
예 1684
 
2.8%
Other values (97) 30740
51.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59898
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 4583
 
7.7%
당 3856
 
6.4%
수 3107
 
5.2%
충 3003
 
5.0%
비 2987
 
5.0%
부 2876
 
4.8%
채 2619
 
4.4%
기 2530
 
4.2%
선 1913
 
3.2%
예 1684
 
2.8%
Other values (97) 30740
51.3%

년월일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202304
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202304
2nd row202304
3rd row202304
4th row202304
5th row202304

Common Values

ValueCountFrequency (%)
202304 10000
100.0%

Length

2024-05-11T14:55:49.779717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:55:49.920650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202304 10000
100.0%

금액
Real number (ℝ)

ZEROS 

Distinct7366
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80351512
Minimum-9.1137224 × 108
Maximum7.5041691 × 109
Zeros2324
Zeros (%)23.2%
Negative377
Negative (%)3.8%
Memory size166.0 KiB
2024-05-11T14:55:50.080933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-9.1137224 × 108
5-th percentile0
Q10
median3148610
Q337103310
95-th percentile3.9892145 × 108
Maximum7.5041691 × 109
Range8.4155413 × 109
Interquartile range (IQR)37103310

Descriptive statistics

Standard deviation2.9935315 × 108
Coefficient of variation (CV)3.7255446
Kurtosis137.26621
Mean80351512
Median Absolute Deviation (MAD)3148610
Skewness9.5049123
Sum8.0351512 × 1011
Variance8.9612306 × 1016
MonotonicityNot monotonic
2024-05-11T14:55:50.299305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2324
 
23.2%
250000 23
 
0.2%
500000 19
 
0.2%
300000 17
 
0.2%
484000 12
 
0.1%
242000 11
 
0.1%
5000000 10
 
0.1%
30000000 10
 
0.1%
1000000 10
 
0.1%
20000000 9
 
0.1%
Other values (7356) 7555
75.5%
ValueCountFrequency (%)
-911372242 1
< 0.1%
-498514932 1
< 0.1%
-473885767 1
< 0.1%
-389001283 1
< 0.1%
-381131445 1
< 0.1%
-306567664 1
< 0.1%
-166462990 1
< 0.1%
-157879880 1
< 0.1%
-148374920 1
< 0.1%
-113445035 1
< 0.1%
ValueCountFrequency (%)
7504169091 1
< 0.1%
7019180303 1
< 0.1%
5225770286 1
< 0.1%
4773892864 1
< 0.1%
4680055287 1
< 0.1%
4589417198 1
< 0.1%
4569925684 1
< 0.1%
4326345391 1
< 0.1%
4196283678 1
< 0.1%
3739007211 1
< 0.1%

Interactions

2024-05-11T14:55:45.781487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:55:50.434028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명금액
비용명1.0000.460
금액0.4601.000

Missing values

2024-05-11T14:55:45.967755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:55:46.143953image/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

아파트명아파트코드비용명년월일금액
35312방배대우효령A13706303퇴직급여충당부채2023040
18364신내동성3차아파트A13113004선수관리비202304137160000
60521보라매삼성쉐르빌A15672002공동체활성화단체지원적립금2023041000000
64878염창한화꿈에그린A15786424상여충당부채2023040
67289신월수명산SK-VIEWA15882201퇴직급여충당부채20230437335920
65600목동트윈빌A15805502주차장충당부채202304154916890
4713래미안개포루체하임A10025823관리비예치금202304531820000
34919석관중앙하이츠A13681701기타당좌자산2023040
45336중계현대2차(4동)A13985904당기순이익20230417443339
16261답십리동아A13003406비품감가상각누계액202304-5711310
아파트명아파트코드비용명년월일금액
23094도봉래미안A13293505선급비용20230414838680
61594우장산롯데3차A15701601장기수선충당부채202304219703581
38034거여1단지A13811206기타충당예금2023040
26395신성둔촌미소지움1차A13406205기타당좌자산202304503000
51274포레나 신길A15005501기타당좌자산202304615000
28679청담대림A13510006공동주택적립금예금2023040
42185동진신안A13922907가수금2023041000
45373중계염광아름빌A13985907미부과관리비202304196577866
64887염창현대1차A15786426비품2023049189900
19977신내중앙하이츠A13186907기타당좌자산2023042197360