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 2404 (24.0%) zerosZeros

Reproduction

Analysis started2024-05-11 05:56:51.753698
Analysis finished2024-05-11 05:56:52.895404
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct2233
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:56:53.143671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length7.4124
Min length2

Characters and Unicode

Total characters74124
Distinct characters436
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

Unique108 ?
Unique (%)1.1%

Sample

1st row방배래미안
2nd row힐스테이트청계
3rd row디엠씨한양
4th row길음뉴타운11단지 롯데캐슬골든힐스아파트
5th row신내진로아파트
ValueCountFrequency (%)
아파트 168
 
1.6%
래미안 40
 
0.4%
e편한세상 19
 
0.2%
sk뷰 17
 
0.2%
푸르지오 15
 
0.1%
강남한신휴플러스 15
 
0.1%
아이파크상도동 14
 
0.1%
아이파크 14
 
0.1%
송파 13
 
0.1%
북한산 13
 
0.1%
Other values (2314) 10451
97.0%
2024-05-11T14:56:53.752194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 2514
 
3.4%
아 2474
 
3.3%
트 2316
 
3.1%
지 1881
 
2.5%
대 1763
 
2.4%
동 1671
 
2.3%
단 1479
 
2.0%
차 1462
 
2.0%
신 1434
 
1.9%
이 1364
 
1.8%
Other values (426) 55766
75.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67718
91.4%
Decimal Number 3688
 
5.0%
Uppercase Letter 940
 
1.3%
Space Separator 865
 
1.2%
Lowercase Letter 389
 
0.5%
Open Punctuation 143
 
0.2%
Close Punctuation 143
 
0.2%
Dash Punctuation 128
 
0.2%
Other Punctuation 101
 
0.1%
Letter Number 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 2514
 
3.7%
아 2474
 
3.7%
트 2316
 
3.4%
지 1881
 
2.8%
대 1763
 
2.6%
동 1671
 
2.5%
단 1479
 
2.2%
차 1462
 
2.2%
신 1434
 
2.1%
이 1364
 
2.0%
Other values (381) 49360
72.9%
Uppercase Letter
ValueCountFrequency (%)
S 149
15.9%
C 143
15.2%
K 116
12.3%
D 100
10.6%
M 100
10.6%
L 61
6.5%
H 61
6.5%
I 43
 
4.6%
E 40
 
4.3%
V 31
 
3.3%
Other values (7) 96
10.2%
Lowercase Letter
ValueCountFrequency (%)
e 178
45.8%
l 50
 
12.9%
i 46
 
11.8%
v 30
 
7.7%
k 19
 
4.9%
s 18
 
4.6%
c 14
 
3.6%
w 14
 
3.6%
a 7
 
1.8%
g 7
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 1135
30.8%
2 1024
27.8%
3 525
14.2%
4 247
 
6.7%
5 203
 
5.5%
6 180
 
4.9%
8 105
 
2.8%
9 96
 
2.6%
7 89
 
2.4%
0 84
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 75
74.3%
. 26
 
25.7%
Space Separator
ValueCountFrequency (%)
865
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67718
91.4%
Common 5068
 
6.8%
Latin 1338
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 2514
 
3.7%
아 2474
 
3.7%
트 2316
 
3.4%
지 1881
 
2.8%
대 1763
 
2.6%
동 1671
 
2.5%
단 1479
 
2.2%
차 1462
 
2.2%
신 1434
 
2.1%
이 1364
 
2.0%
Other values (381) 49360
72.9%
Latin
ValueCountFrequency (%)
e 178
13.3%
S 149
11.1%
C 143
10.7%
K 116
 
8.7%
D 100
 
7.5%
M 100
 
7.5%
L 61
 
4.6%
H 61
 
4.6%
l 50
 
3.7%
i 46
 
3.4%
Other values (19) 334
25.0%
Common
ValueCountFrequency (%)
1 1135
22.4%
2 1024
20.2%
865
17.1%
3 525
10.4%
4 247
 
4.9%
5 203
 
4.0%
6 180
 
3.6%
( 143
 
2.8%
) 143
 
2.8%
- 128
 
2.5%
Other values (6) 475
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67718
91.4%
ASCII 6397
 
8.6%
Number Forms 9
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 2514
 
3.7%
아 2474
 
3.7%
트 2316
 
3.4%
지 1881
 
2.8%
대 1763
 
2.6%
동 1671
 
2.5%
단 1479
 
2.2%
차 1462
 
2.2%
신 1434
 
2.1%
이 1364
 
2.0%
Other values (381) 49360
72.9%
ASCII
ValueCountFrequency (%)
1 1135
17.7%
2 1024
16.0%
865
13.5%
3 525
 
8.2%
4 247
 
3.9%
5 203
 
3.2%
6 180
 
2.8%
e 178
 
2.8%
S 149
 
2.3%
( 143
 
2.2%
Other values (34) 1748
27.3%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

아파트코드
Text

Distinct2238
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:56:54.323522image/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

Unique109 ?
Unique (%)1.1%

Sample

1st rowA13785301
2nd rowA10026104
3rd rowA12081703
4th rowA10025753
5th rowA13187203
ValueCountFrequency (%)
a15603203 14
 
0.1%
a15788302 13
 
0.1%
a14075201 12
 
0.1%
a13204506 12
 
0.1%
a13876111 11
 
0.1%
a15010303 11
 
0.1%
a13986306 11
 
0.1%
a15601103 11
 
0.1%
a13922907 11
 
0.1%
a15205305 11
 
0.1%
Other values (2228) 9883
98.8%
2024-05-11T14:56:55.053136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18553
20.6%
1 17607
19.6%
A 9998
11.1%
3 8784
9.8%
2 8242
9.2%
5 6292
 
7.0%
8 5474
 
6.1%
7 4668
 
5.2%
4 3968
 
4.4%
6 3366
 
3.7%
Other values (2) 3048
 
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 18553
23.2%
1 17607
22.0%
3 8784
11.0%
2 8242
10.3%
5 6292
 
7.9%
8 5474
 
6.8%
7 4668
 
5.8%
4 3968
 
5.0%
6 3366
 
4.2%
9 3046
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
A 9998
> 99.9%
B 2
 
< 0.1%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18553
23.2%
1 17607
22.0%
3 8784
11.0%
2 8242
10.3%
5 6292
 
7.9%
8 5474
 
6.8%
7 4668
 
5.8%
4 3968
 
5.0%
6 3366
 
4.2%
9 3046
 
3.8%
Latin
ValueCountFrequency (%)
A 9998
> 99.9%
B 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18553
20.6%
1 17607
19.6%
A 9998
11.1%
3 8784
9.8%
2 8242
9.2%
5 6292
 
7.0%
8 5474
 
6.1%
7 4668
 
5.2%
4 3968
 
4.4%
6 3366
 
3.7%
Other values (2) 3048
 
3.4%

비용명
Text

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T14:56:55.444614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.0174
Min length2

Characters and Unicode

Total characters60174
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 row당기순이익
2nd row비품감가상각누계액
3rd row임차보증금
4th row경비비충당부채
5th row연차수당충당부채
ValueCountFrequency (%)
당기순이익 330
 
3.3%
예수금 321
 
3.2%
장기수선충당부채 317
 
3.2%
미처분이익잉여금 314
 
3.1%
공동주택적립금 312
 
3.1%
관리비미수금 307
 
3.1%
연차수당충당부채 297
 
3.0%
퇴직급여충당부채 296
 
3.0%
비품 293
 
2.9%
장기수선충당예금 290
 
2.9%
Other values (67) 6923
69.2%
2024-05-11T14:56:56.000071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 4616
 
7.7%
당 3850
 
6.4%
수 3175
 
5.3%
비 3057
 
5.1%
충 3038
 
5.0%
부 2930
 
4.9%
채 2631
 
4.4%
기 2567
 
4.3%
선 1924
 
3.2%
예 1752
 
2.9%
Other values (97) 30634
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60174
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 4616
 
7.7%
당 3850
 
6.4%
수 3175
 
5.3%
비 3057
 
5.1%
충 3038
 
5.0%
부 2930
 
4.9%
채 2631
 
4.4%
기 2567
 
4.3%
선 1924
 
3.2%
예 1752
 
2.9%
Other values (97) 30634
50.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60174
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 4616
 
7.7%
당 3850
 
6.4%
수 3175
 
5.3%
비 3057
 
5.1%
충 3038
 
5.0%
부 2930
 
4.9%
채 2631
 
4.4%
기 2567
 
4.3%
선 1924
 
3.2%
예 1752
 
2.9%
Other values (97) 30634
50.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60174
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 4616
 
7.7%
당 3850
 
6.4%
수 3175
 
5.3%
비 3057
 
5.1%
충 3038
 
5.0%
부 2930
 
4.9%
채 2631
 
4.4%
기 2567
 
4.3%
선 1924
 
3.2%
예 1752
 
2.9%
Other values (97) 30634
50.9%

년월일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
202211
10000 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202211
2nd row202211
3rd row202211
4th row202211
5th row202211

Common Values

ValueCountFrequency (%)
202211 10000
100.0%

Length

2024-05-11T14:56:56.232927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:56:56.401371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202211 10000
100.0%

금액
Real number (ℝ)

ZEROS 

Distinct7264
Distinct (%)72.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78442339
Minimum-3.0480155 × 108
Maximum7.9696948 × 109
Zeros2404
Zeros (%)24.0%
Negative316
Negative (%)3.2%
Memory size166.0 KiB
2024-05-11T14:56:56.639651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.0480155 × 108
5-th percentile0
Q10
median3190293
Q335590695
95-th percentile3.6519962 × 108
Maximum7.9696948 × 109
Range8.2744963 × 109
Interquartile range (IQR)35590695

Descriptive statistics

Standard deviation3.1475446 × 108
Coefficient of variation (CV)4.0125583
Kurtosis172.78921
Mean78442339
Median Absolute Deviation (MAD)3190293
Skewness10.954263
Sum7.8442339 × 1011
Variance9.9070371 × 1016
MonotonicityNot monotonic
2024-05-11T14:56:56.900545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2404
 
24.0%
500000 30
 
0.3%
250000 25
 
0.2%
300000 14
 
0.1%
20000000 12
 
0.1%
1000000 12
 
0.1%
3000000 10
 
0.1%
484000 9
 
0.1%
30000000 9
 
0.1%
5000000 9
 
0.1%
Other values (7254) 7466
74.7%
ValueCountFrequency (%)
-304801554 1
< 0.1%
-282000000 1
< 0.1%
-230922000 1
< 0.1%
-217586902 1
< 0.1%
-189646440 1
< 0.1%
-181655535 1
< 0.1%
-176217090 1
< 0.1%
-172538742 1
< 0.1%
-133996205 1
< 0.1%
-124133098 1
< 0.1%
ValueCountFrequency (%)
7969694790 1
< 0.1%
6760034048 1
< 0.1%
6708736961 1
< 0.1%
6456490884 1
< 0.1%
5670790872 1
< 0.1%
5350536280 1
< 0.1%
4893464632 1
< 0.1%
4841359797 1
< 0.1%
4749517431 1
< 0.1%
4641096323 1
< 0.1%

Interactions

2024-05-11T14:56:52.486244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:56:57.039253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명금액
비용명1.0000.478
금액0.4781.000

Missing values

2024-05-11T14:56:52.707713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:56:52.841802image/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
37862방배래미안A13785301당기순이익20221130570791
4691힐스테이트청계A10026104비품감가상각누계액202211-18004480
11196디엠씨한양A12081703임차보증금2022110
3970길음뉴타운11단지 롯데캐슬골든힐스아파트A10025753경비비충당부채20221115461780
20304신내진로아파트A13187203연차수당충당부채20221113276145
5157꿈의숲코오롱하늘채아파트A10026571공동주택적립금20221142827106
32069역삼럭키A13585804가수금202211235240
13337망원2차대림A12182401수선유지비충당부채2022112104973
19334면목늘푸른동아아파트A13183504기타의비유동부채2022110
37462방배신삼호A13782602관리비예치금202211167349650
아파트명아파트코드비용명년월일금액
15275갈현한솔아파트A12281801기타의비유동부채2022110
43556중계주공5단지A13922114비품20221153973280
70013목동10단지A15873701예수금2022116473910
35474정릉스카이쌍용A13676504주차장충당부채2022110
25463래미안하이리버A13380302장기수선충당부채202211340365110
60855남서울힐스테이트A15370103장기수선충당부채2022111202515593
21972창동대동A13204501선급금202211311260
49454청화아파트A14086001선수관리비202211115692000
65592마곡푸르지오A15722004기타충당부채2022110
30684역삼삼익A13527006예수금2022111649850