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 2218 (22.2%) zerosZeros

Reproduction

Analysis started2024-05-11 06:00:06.490163
Analysis finished2024-05-11 06:00:07.349612
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2197
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:00:07.561907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length7.2552
Min length2

Characters and Unicode

Total characters72552
Distinct characters436
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)1.2%

Sample

1st row중계주공10단지
2nd row상계한일유엔아이
3rd rowe편한세상마포리버파크
4th row목동진도1차
5th row약수하이츠아파트(임대)
ValueCountFrequency (%)
아파트 137
 
1.3%
래미안 33
 
0.3%
아이파크 23
 
0.2%
잠실레이크팰리스 14
 
0.1%
래미안밤섬리베뉴 14
 
0.1%
은평뉴타운상림마을6단지 14
 
0.1%
e편한세상 13
 
0.1%
힐스테이트 13
 
0.1%
신반포 13
 
0.1%
고덕 13
 
0.1%
Other values (2261) 10345
97.3%
2024-05-11T15:00:08.158119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 2384
 
3.3%
파 2342
 
3.2%
트 2095
 
2.9%
대 1876
 
2.6%
동 1776
 
2.4%
지 1769
 
2.4%
차 1567
 
2.2%
신 1529
 
2.1%
단 1385
 
1.9%
성 1333
 
1.8%
Other values (426) 54496
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66423
91.6%
Decimal Number 3780
 
5.2%
Uppercase Letter 743
 
1.0%
Space Separator 699
 
1.0%
Lowercase Letter 312
 
0.4%
Open Punctuation 170
 
0.2%
Close Punctuation 170
 
0.2%
Dash Punctuation 131
 
0.2%
Other Punctuation 117
 
0.2%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 2384
 
3.6%
파 2342
 
3.5%
트 2095
 
3.2%
대 1876
 
2.8%
동 1776
 
2.7%
지 1769
 
2.7%
차 1567
 
2.4%
신 1529
 
2.3%
단 1385
 
2.1%
성 1333
 
2.0%
Other values (380) 48367
72.8%
Uppercase Letter
ValueCountFrequency (%)
C 108
14.5%
K 105
14.1%
S 104
14.0%
M 62
8.3%
D 62
8.3%
L 61
8.2%
I 43
 
5.8%
H 41
 
5.5%
G 25
 
3.4%
E 23
 
3.1%
Other values (7) 109
14.7%
Lowercase Letter
ValueCountFrequency (%)
e 173
55.4%
i 28
 
9.0%
l 26
 
8.3%
s 17
 
5.4%
v 16
 
5.1%
k 16
 
5.1%
c 8
 
2.6%
g 8
 
2.6%
a 8
 
2.6%
w 7
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 1178
31.2%
2 1120
29.6%
3 470
 
12.4%
4 255
 
6.7%
5 219
 
5.8%
6 162
 
4.3%
7 108
 
2.9%
9 97
 
2.6%
8 86
 
2.3%
0 85
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 96
82.1%
. 21
 
17.9%
Space Separator
ValueCountFrequency (%)
699
100.0%
Open Punctuation
ValueCountFrequency (%)
( 170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66423
91.6%
Common 5070
 
7.0%
Latin 1059
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 2384
 
3.6%
파 2342
 
3.5%
트 2095
 
3.2%
대 1876
 
2.8%
동 1776
 
2.7%
지 1769
 
2.7%
차 1567
 
2.4%
신 1529
 
2.3%
단 1385
 
2.1%
성 1333
 
2.0%
Other values (380) 48367
72.8%
Latin
ValueCountFrequency (%)
e 173
16.3%
C 108
 
10.2%
K 105
 
9.9%
S 104
 
9.8%
M 62
 
5.9%
D 62
 
5.9%
L 61
 
5.8%
I 43
 
4.1%
H 41
 
3.9%
i 28
 
2.6%
Other values (19) 272
25.7%
Common
ValueCountFrequency (%)
1 1178
23.2%
2 1120
22.1%
699
13.8%
3 470
 
9.3%
4 255
 
5.0%
5 219
 
4.3%
( 170
 
3.4%
) 170
 
3.4%
6 162
 
3.2%
- 131
 
2.6%
Other values (7) 496
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66423
91.6%
ASCII 6125
 
8.4%
Number Forms 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 2384
 
3.6%
파 2342
 
3.5%
트 2095
 
3.2%
대 1876
 
2.8%
동 1776
 
2.7%
지 1769
 
2.7%
차 1567
 
2.4%
신 1529
 
2.3%
단 1385
 
2.1%
성 1333
 
2.0%
Other values (380) 48367
72.8%
ASCII
ValueCountFrequency (%)
1 1178
19.2%
2 1120
18.3%
699
11.4%
3 470
 
7.7%
4 255
 
4.2%
5 219
 
3.6%
e 173
 
2.8%
( 170
 
2.8%
) 170
 
2.8%
6 162
 
2.6%
Other values (35) 1509
24.6%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%

아파트코드
Text

Distinct2204
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:00:08.601387image/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

Unique117 ?
Unique (%)1.2%

Sample

1st rowA13986004
2nd rowA13920205
3rd rowA10028006
4th rowA15882104
5th rowA10045402
ValueCountFrequency (%)
a13822001 14
 
0.1%
a12179505 12
 
0.1%
a15288611 11
 
0.1%
a12013202 11
 
0.1%
a15703304 11
 
0.1%
a10045302 11
 
0.1%
a13905105 11
 
0.1%
a13821004 11
 
0.1%
a14380414 11
 
0.1%
a13987306 11
 
0.1%
Other values (2194) 9886
98.9%
2024-05-11T15:00:09.204577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18456
20.5%
1 17604
19.6%
A 9989
11.1%
3 8885
9.9%
2 8171
9.1%
5 6260
 
7.0%
8 5663
 
6.3%
7 4760
 
5.3%
4 3916
 
4.4%
6 3344
 
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 18456
23.1%
1 17604
22.0%
3 8885
11.1%
2 8171
10.2%
5 6260
 
7.8%
8 5663
 
7.1%
7 4760
 
5.9%
4 3916
 
4.9%
6 3344
 
4.2%
9 2941
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 9989
99.9%
B 11
 
0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18456
23.1%
1 17604
22.0%
3 8885
11.1%
2 8171
10.2%
5 6260
 
7.8%
8 5663
 
7.1%
7 4760
 
5.9%
4 3916
 
4.9%
6 3344
 
4.2%
9 2941
 
3.7%
Latin
ValueCountFrequency (%)
A 9989
99.9%
B 11
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18456
20.5%
1 17604
19.6%
A 9989
11.1%
3 8885
9.9%
2 8171
9.1%
5 6260
 
7.0%
8 5663
 
6.3%
7 4760
 
5.3%
4 3916
 
4.4%
6 3344
 
3.7%
Other values (2) 2952
 
3.3%

비용명
Text

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:00:09.572856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length5.9969
Min length2

Characters and Unicode

Total characters59969
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 row장기수선충당예금
2nd row퇴직급여충당부채
3rd row장기수선충당예금
4th row관리비예치금
5th row가수금
ValueCountFrequency (%)
예금 333
 
3.3%
공동주택적립금 319
 
3.2%
퇴직급여충당부채 317
 
3.2%
미처분이익잉여금 311
 
3.1%
장기수선충당부채 309
 
3.1%
당기순이익 309
 
3.1%
선급비용 305
 
3.0%
예수금 300
 
3.0%
장기수선충당예금 299
 
3.0%
연차수당충당부채 297
 
3.0%
Other values (67) 6901
69.0%
2024-05-11T15:00:10.086918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 4715
 
7.9%
당 3770
 
6.3%
수 3181
 
5.3%
충 3092
 
5.2%
비 3007
 
5.0%
부 2972
 
5.0%
채 2685
 
4.5%
기 2359
 
3.9%
선 1915
 
3.2%
예 1793
 
3.0%
Other values (97) 30480
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59969
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 4715
 
7.9%
당 3770
 
6.3%
수 3181
 
5.3%
충 3092
 
5.2%
비 3007
 
5.0%
부 2972
 
5.0%
채 2685
 
4.5%
기 2359
 
3.9%
선 1915
 
3.2%
예 1793
 
3.0%
Other values (97) 30480
50.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59969
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 4715
 
7.9%
당 3770
 
6.3%
수 3181
 
5.3%
충 3092
 
5.2%
비 3007
 
5.0%
부 2972
 
5.0%
채 2685
 
4.5%
기 2359
 
3.9%
선 1915
 
3.2%
예 1793
 
3.0%
Other values (97) 30480
50.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59969
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 4715
 
7.9%
당 3770
 
6.3%
수 3181
 
5.3%
충 3092
 
5.2%
비 3007
 
5.0%
부 2972
 
5.0%
채 2685
 
4.5%
기 2359
 
3.9%
선 1915
 
3.2%
예 1793
 
3.0%
Other values (97) 30480
50.8%

년월일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202007
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202007
2nd row202007
3rd row202007
4th row202007
5th row202007

Common Values

ValueCountFrequency (%)
202007 10000
100.0%

Length

2024-05-11T15:00:10.278374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:00:10.402515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202007 10000
100.0%

금액
Real number (ℝ)

ZEROS 

Distinct7439
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74471242
Minimum-4.1436094 × 108
Maximum8.0600576 × 109
Zeros2218
Zeros (%)22.2%
Negative349
Negative (%)3.5%
Memory size166.0 KiB
2024-05-11T15:00:10.589091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4.1436094 × 108
5-th percentile0
Q10
median3276050
Q333037224
95-th percentile3.5670219 × 108
Maximum8.0600576 × 109
Range8.4744185 × 109
Interquartile range (IQR)33037224

Descriptive statistics

Standard deviation3.0636794 × 108
Coefficient of variation (CV)4.1139094
Kurtosis203.89124
Mean74471242
Median Absolute Deviation (MAD)3276050
Skewness11.881101
Sum7.4471242 × 1011
Variance9.3861314 × 1016
MonotonicityNot monotonic
2024-05-11T15:00:10.801020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2218
 
22.2%
500000 32
 
0.3%
250000 24
 
0.2%
300000 18
 
0.2%
20000000 15
 
0.1%
484000 13
 
0.1%
200000 11
 
0.1%
242000 11
 
0.1%
2000000 10
 
0.1%
1000000 9
 
0.1%
Other values (7429) 7639
76.4%
ValueCountFrequency (%)
-414360936 1
< 0.1%
-272693490 1
< 0.1%
-241847440 1
< 0.1%
-230356964 1
< 0.1%
-173982688 1
< 0.1%
-144739812 1
< 0.1%
-119335150 1
< 0.1%
-102315520 1
< 0.1%
-88521217 1
< 0.1%
-85222720 1
< 0.1%
ValueCountFrequency (%)
8060057555 1
< 0.1%
7252359073 1
< 0.1%
6577801845 2
< 0.1%
6262167228 1
< 0.1%
5264362142 1
< 0.1%
5204261155 1
< 0.1%
5184606532 1
< 0.1%
5143453658 1
< 0.1%
5097470478 1
< 0.1%
4461069091 1
< 0.1%

Interactions

2024-05-11T15:00:07.015328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:00:10.899470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명금액
비용명1.0000.509
금액0.5091.000

Missing values

2024-05-11T15:00:07.171452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:00:07.295878image/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
44261중계주공10단지A13986004장기수선충당예금20200714098813
40180상계한일유엔아이A13920205퇴직급여충당부채2020070
5569e편한세상마포리버파크A10028006장기수선충당예금202007350696170
67648목동진도1차A15882104관리비예치금20200716926000
6018약수하이츠아파트(임대)A10045402가수금2020076033861
47237한일유앤아이A14272303주차장충당부채2020070
42915상계신동아A13982003단기보증금2020071556000
38088포스코더샵스타리버A13824001선수관리비2020070
14283휘경동일스위트리버A13009206미수금2020070
26498삼성한솔A13509004현금2020071496880
아파트명아파트코드비용명년월일금액
9227마포도화우성A12104007비품감가상각누계액202007-16447890
66888목동12단지A15807706공동체활성화단체지원적립금20200716830100
44633중계성원1차A13986606단기차입금2020070
62560마곡엠밸리14단지A15721010기타유동부채20200732962277
58433벽산타운3단지A15384501기타의비유동부채2020070
16068묵동금호어울림A13114103기타유형자산2020070
68578은평뉴타운상림마을제3단지A41279908선급비용20200711312040
14454래미안장안2차A13010005장기수선충당부채2020072270379583
8856홍은유원A12084302예수금2020071531788
27106압구정 현대(10,13,14차)A13511101비품202007242000