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 2378 (23.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:58:20.854506
Analysis finished2024-05-11 05:58:21.958174
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2199
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:58:22.205193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length7.3422
Min length2

Characters and Unicode

Total characters73422
Distinct characters434
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

Unique122 ?
Unique (%)1.2%

Sample

1st row답십리동서울한양
2nd row상계동아불암
3rd row상계성림(미라보)
4th row중곡SK
5th row여의도대교
ValueCountFrequency (%)
아파트 153
 
1.4%
래미안 38
 
0.4%
e편한세상 29
 
0.3%
푸르지오 20
 
0.2%
아이파크 19
 
0.2%
경남아너스빌 17
 
0.2%
염창 17
 
0.2%
보라매 15
 
0.1%
sk뷰 14
 
0.1%
고덕 14
 
0.1%
Other values (2276) 10347
96.9%
2024-05-11T14:58:22.836880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2482
 
3.4%
파 2412
 
3.3%
트 2299
 
3.1%
지 1854
 
2.5%
대 1712
 
2.3%
동 1662
 
2.3%
단 1488
 
2.0%
신 1477
 
2.0%
차 1441
 
2.0%
이 1363
 
1.9%
Other values (424) 55232
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67390
91.8%
Decimal Number 3614
 
4.9%
Uppercase Letter 840
 
1.1%
Space Separator 765
 
1.0%
Lowercase Letter 320
 
0.4%
Close Punctuation 138
 
0.2%
Open Punctuation 138
 
0.2%
Dash Punctuation 122
 
0.2%
Other Punctuation 88
 
0.1%
Letter Number 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2482
 
3.7%
파 2412
 
3.6%
트 2299
 
3.4%
지 1854
 
2.8%
대 1712
 
2.5%
동 1662
 
2.5%
단 1488
 
2.2%
신 1477
 
2.2%
차 1441
 
2.1%
이 1363
 
2.0%
Other values (380) 49200
73.0%
Uppercase Letter
ValueCountFrequency (%)
S 134
16.0%
C 112
13.3%
K 103
12.3%
D 80
9.5%
M 80
9.5%
L 63
7.5%
H 51
 
6.1%
E 48
 
5.7%
I 43
 
5.1%
V 28
 
3.3%
Other values (7) 98
11.7%
Decimal Number
ValueCountFrequency (%)
1 1076
29.8%
2 1036
28.7%
3 486
13.4%
4 262
 
7.2%
5 207
 
5.7%
6 143
 
4.0%
7 135
 
3.7%
8 102
 
2.8%
9 94
 
2.6%
0 73
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
e 214
66.9%
l 22
 
6.9%
i 21
 
6.6%
k 16
 
5.0%
v 15
 
4.7%
s 13
 
4.1%
w 7
 
2.2%
c 6
 
1.9%
g 3
 
0.9%
a 3
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 70
79.5%
. 18
 
20.5%
Space Separator
ValueCountFrequency (%)
765
100.0%
Close Punctuation
ValueCountFrequency (%)
) 138
100.0%
Open Punctuation
ValueCountFrequency (%)
( 138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67390
91.8%
Common 4865
 
6.6%
Latin 1167
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2482
 
3.7%
파 2412
 
3.6%
트 2299
 
3.4%
지 1854
 
2.8%
대 1712
 
2.5%
동 1662
 
2.5%
단 1488
 
2.2%
신 1477
 
2.2%
차 1441
 
2.1%
이 1363
 
2.0%
Other values (380) 49200
73.0%
Latin
ValueCountFrequency (%)
e 214
18.3%
S 134
11.5%
C 112
9.6%
K 103
8.8%
D 80
 
6.9%
M 80
 
6.9%
L 63
 
5.4%
H 51
 
4.4%
E 48
 
4.1%
I 43
 
3.7%
Other values (18) 239
20.5%
Common
ValueCountFrequency (%)
1 1076
22.1%
2 1036
21.3%
765
15.7%
3 486
10.0%
4 262
 
5.4%
5 207
 
4.3%
6 143
 
2.9%
) 138
 
2.8%
( 138
 
2.8%
7 135
 
2.8%
Other values (6) 479
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67390
91.8%
ASCII 6025
 
8.2%
Number Forms 7
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2482
 
3.7%
파 2412
 
3.6%
트 2299
 
3.4%
지 1854
 
2.8%
대 1712
 
2.5%
동 1662
 
2.5%
단 1488
 
2.2%
신 1477
 
2.2%
차 1441
 
2.1%
이 1363
 
2.0%
Other values (380) 49200
73.0%
ASCII
ValueCountFrequency (%)
1 1076
17.9%
2 1036
17.2%
765
12.7%
3 486
 
8.1%
4 262
 
4.3%
e 214
 
3.6%
5 207
 
3.4%
6 143
 
2.4%
) 138
 
2.3%
( 138
 
2.3%
Other values (33) 1560
25.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 7
100.0%

아파트코드
Text

Distinct2205
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:58:23.305895image/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

Unique122 ?
Unique (%)1.2%

Sample

1st rowA13003002
2nd rowA13989701
3rd rowA13980903
4th rowA14322001
5th rowA15001016
ValueCountFrequency (%)
a13613011 13
 
0.1%
a15176202 12
 
0.1%
a13782602 12
 
0.1%
a15086702 12
 
0.1%
a13816002 12
 
0.1%
a13203302 12
 
0.1%
a13510007 12
 
0.1%
a13084804 11
 
0.1%
a13006003 11
 
0.1%
a14072701 11
 
0.1%
Other values (2195) 9882
98.8%
2024-05-11T14:58:24.004972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18356
20.4%
1 17557
19.5%
A 9996
11.1%
3 8826
9.8%
2 8285
9.2%
5 6233
 
6.9%
8 5629
 
6.3%
7 4757
 
5.3%
4 3925
 
4.4%
6 3331
 
3.7%
Other values (2) 3105
 
3.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18356
22.9%
1 17557
21.9%
3 8826
11.0%
2 8285
10.4%
5 6233
 
7.8%
8 5629
 
7.0%
7 4757
 
5.9%
4 3925
 
4.9%
6 3331
 
4.2%
9 3101
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
A 9996
> 99.9%
B 4
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18356
22.9%
1 17557
21.9%
3 8826
11.0%
2 8285
10.4%
5 6233
 
7.8%
8 5629
 
7.0%
7 4757
 
5.9%
4 3925
 
4.9%
6 3331
 
4.2%
9 3101
 
3.9%
Latin
ValueCountFrequency (%)
A 9996
> 99.9%
B 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18356
20.4%
1 17557
19.5%
A 9996
11.1%
3 8826
9.8%
2 8285
9.2%
5 6233
 
6.9%
8 5629
 
6.3%
7 4757
 
5.3%
4 3925
 
4.4%
6 3331
 
3.7%
Other values (2) 3105
 
3.5%

비용명
Text

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:58:24.466934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.9917
Min length2

Characters and Unicode

Total characters59917
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

Unique0 ?
Unique (%)0.0%

Sample

1st row미수관리비예치금
2nd row기타당좌자산
3rd row선수관리비
4th row미지급금
5th row전신전화가입권
ValueCountFrequency (%)
미처분이익잉여금 320
 
3.2%
장기수선충당부채 320
 
3.2%
예금 319
 
3.2%
관리비미수금 310
 
3.1%
연차수당충당부채 310
 
3.1%
선급비용 306
 
3.1%
미부과관리비 304
 
3.0%
장기수선충당예금 302
 
3.0%
당기순이익 294
 
2.9%
가수금 286
 
2.9%
Other values (67) 6929
69.3%
2024-05-11T14:58:25.135238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 4517
 
7.5%
당 3869
 
6.5%
수 3215
 
5.4%
충 3081
 
5.1%
비 3053
 
5.1%
부 2989
 
5.0%
채 2666
 
4.4%
기 2515
 
4.2%
선 1980
 
3.3%
예 1700
 
2.8%
Other values (97) 30332
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59917
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 4517
 
7.5%
당 3869
 
6.5%
수 3215
 
5.4%
충 3081
 
5.1%
비 3053
 
5.1%
부 2989
 
5.0%
채 2666
 
4.4%
기 2515
 
4.2%
선 1980
 
3.3%
예 1700
 
2.8%
Other values (97) 30332
50.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59917
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 4517
 
7.5%
당 3869
 
6.5%
수 3215
 
5.4%
충 3081
 
5.1%
비 3053
 
5.1%
부 2989
 
5.0%
채 2666
 
4.4%
기 2515
 
4.2%
선 1980
 
3.3%
예 1700
 
2.8%
Other values (97) 30332
50.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59917
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 4517
 
7.5%
당 3869
 
6.5%
수 3215
 
5.4%
충 3081
 
5.1%
비 3053
 
5.1%
부 2989
 
5.0%
채 2666
 
4.4%
기 2515
 
4.2%
선 1980
 
3.3%
예 1700
 
2.8%
Other values (97) 30332
50.6%

년월일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202112
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202112
2nd row202112
3rd row202112
4th row202112
5th row202112

Common Values

ValueCountFrequency (%)
202112 10000
100.0%

Length

2024-05-11T14:58:25.362418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:25.514155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202112 10000
100.0%

금액
Real number (ℝ)

ZEROS 

Distinct7274
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80472469
Minimum-8.9305253 × 108
Maximum1.0640625 × 1010
Zeros2378
Zeros (%)23.8%
Negative334
Negative (%)3.3%
Memory size166.0 KiB
2024-05-11T14:58:25.691717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-8.9305253 × 108
5-th percentile0
Q10
median2879762.5
Q336962190
95-th percentile3.8588375 × 108
Maximum1.0640625 × 1010
Range1.1533678 × 1010
Interquartile range (IQR)36962190

Descriptive statistics

Standard deviation3.2240806 × 108
Coefficient of variation (CV)4.0064393
Kurtosis235.81306
Mean80472469
Median Absolute Deviation (MAD)2879762.5
Skewness12.195382
Sum8.0472469 × 1011
Variance1.0394696 × 1017
MonotonicityNot monotonic
2024-05-11T14:58:26.234922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2378
 
23.8%
500000 31
 
0.3%
250000 16
 
0.2%
484000 15
 
0.1%
242000 14
 
0.1%
1000000 13
 
0.1%
300000 11
 
0.1%
55000 11
 
0.1%
200000 10
 
0.1%
30000 10
 
0.1%
Other values (7264) 7491
74.9%
ValueCountFrequency (%)
-893052528 1
< 0.1%
-303423180 1
< 0.1%
-247014444 1
< 0.1%
-245767416 1
< 0.1%
-145121865 1
< 0.1%
-138590250 1
< 0.1%
-123413690 1
< 0.1%
-116332434 1
< 0.1%
-97530000 1
< 0.1%
-81131170 1
< 0.1%
ValueCountFrequency (%)
10640625223 1
< 0.1%
6933255644 1
< 0.1%
6726470588 1
< 0.1%
6180208844 1
< 0.1%
5651974236 1
< 0.1%
5606103188 1
< 0.1%
5108569960 1
< 0.1%
5055983083 1
< 0.1%
4984590254 1
< 0.1%
4981990062 1
< 0.1%

Interactions

2024-05-11T14:58:21.512712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:58:26.431371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명금액
비용명1.0000.570
금액0.5701.000

Missing values

2024-05-11T14:58:21.717236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:58:21.883944image/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
14878답십리동서울한양A13003002미수관리비예치금2021120
46474상계동아불암A13989701기타당좌자산2021120
43829상계성림(미라보)A13980903선수관리비20211234340000
49996중곡SKA14322001미지급금2021128889350
50918여의도대교A15001016전신전화가입권202112484000
54914봉천은천1단지A15106101관리비미수금20211241982360
40130가락금호A13880407선급비용20211218287000
42019중계3벽산A13922103가수금202112-175098
58257구로중앙하이츠아파트A15285804미수관리비예치금2021120
59681독산한신A15383307비품20211245789380
아파트명아파트코드비용명년월일금액
18369면목두산4,5단지A13184107미지급금20211275845062
66266염창동아3차A15786227퇴직급여충당부채20211293547818
41938중계청암3단지A13922001미지급비용2021120
28019삼성서광A13509006기타유동부채2021120
16210휘경센트레빌A13078301미부과관리비20211266762970
16134이문삼성래미안아파트A13076801주차장충당예금20211241518016
35410반포미도2차A13770105현금202112123444
61381신동아5A15609006장기수선충당예금202112529147485
25515성내삼성A13403101미부과관리비202112396375117
58735신도림우성3차A15288804가지급금202112126830