Overview

Dataset statistics

Number of variables5
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory47.1 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15821/S/1/datasetView.do

Alerts

아파트명 has constant value ""Constant
아파트코드 has constant value ""Constant
년월일 has constant value ""Constant
비용명 has unique valuesUnique
금액 has 13 (50.0%) zerosZeros

Reproduction

Analysis started2024-04-20 22:07:37.807210
Analysis finished2024-04-20 22:07:39.049345
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
서초트라팰리스1차
26 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서초트라팰리스1차
2nd row서초트라팰리스1차
3rd row서초트라팰리스1차
4th row서초트라팰리스1차
5th row서초트라팰리스1차

Common Values

ValueCountFrequency (%)
서초트라팰리스1차 26
100.0%

Length

2024-04-21T07:07:39.102387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T07:07:39.175693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서초트라팰리스1차 26
100.0%

아파트코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
A13792306
26 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA13792306
2nd rowA13792306
3rd rowA13792306
4th rowA13792306
5th rowA13792306

Common Values

ValueCountFrequency (%)
A13792306 26
100.0%

Length

2024-04-21T07:07:39.252772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T07:07:39.321880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a13792306 26
100.0%

비용명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2024-04-21T07:07:39.463198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8.5
Mean length6.1923077
Min length2

Characters and Unicode

Total characters161
Distinct characters53
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

Unique26 ?
Unique (%)100.0%

Sample

1st row현금
2nd row예금
3rd row관리비미수금
4th row미수관리비예치금
5th row선급비용
ValueCountFrequency (%)
현금 1
 
3.8%
예금 1
 
3.8%
미처분이익잉여금 1
 
3.8%
공동주택적립금 1
 
3.8%
관리비예치금 1
 
3.8%
장기수선충당부채 1
 
3.8%
수선유지비충당부채 1
 
3.8%
퇴직급여충당부채 1
 
3.8%
연차수당충당부채 1
 
3.8%
상여충당부채 1
 
3.8%
Other values (16) 16
61.5%
2024-04-21T07:07:39.725893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
금 13
 
8.1%
당 10
 
6.2%
기 8
 
5.0%
충 7
 
4.3%
비 7
 
4.3%
수 7
 
4.3%
예 6
 
3.7%
채 6
 
3.7%
부 6
 
3.7%
급 5
 
3.1%
Other values (43) 86
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 13
 
8.1%
당 10
 
6.2%
기 8
 
5.0%
충 7
 
4.3%
비 7
 
4.3%
수 7
 
4.3%
예 6
 
3.7%
채 6
 
3.7%
부 6
 
3.7%
급 5
 
3.1%
Other values (43) 86
53.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 13
 
8.1%
당 10
 
6.2%
기 8
 
5.0%
충 7
 
4.3%
비 7
 
4.3%
수 7
 
4.3%
예 6
 
3.7%
채 6
 
3.7%
부 6
 
3.7%
급 5
 
3.1%
Other values (43) 86
53.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
금 13
 
8.1%
당 10
 
6.2%
기 8
 
5.0%
충 7
 
4.3%
비 7
 
4.3%
수 7
 
4.3%
예 6
 
3.7%
채 6
 
3.7%
부 6
 
3.7%
급 5
 
3.1%
Other values (43) 86
53.4%

년월일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
200512
26 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200512
2nd row200512
3rd row200512
4th row200512
5th row200512

Common Values

ValueCountFrequency (%)
200512 26
100.0%

Length

2024-04-21T07:07:39.838673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T07:07:39.928086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200512 26
100.0%

금액
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25721833
Minimum-384400
Maximum2.08275 × 108
Zeros13
Zeros (%)50.0%
Negative2
Negative (%)7.7%
Memory size366.0 B
2024-04-21T07:07:40.021395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-384400
5-th percentile-172080
Q10
median0
Q313219234
95-th percentile1.4407137 × 108
Maximum2.08275 × 108
Range2.086594 × 108
Interquartile range (IQR)13219234

Descriptive statistics

Standard deviation54871716
Coefficient of variation (CV)2.133274
Kurtosis4.8669232
Mean25721833
Median Absolute Deviation (MAD)1672
Skewness2.345231
Sum6.6876765 × 108
Variance3.0109053 × 1015
MonotonicityNot monotonic
2024-04-21T07:07:40.114339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 13
50.0%
238180 1
 
3.8%
48927204 1
 
3.8%
86165080 1
 
3.8%
150060000 1
 
3.8%
11578392 1
 
3.8%
1198900 1
 
3.8%
23063730 1
 
3.8%
13766181 1
 
3.8%
-384400 1
 
3.8%
Other values (4) 4
 
15.4%
ValueCountFrequency (%)
-384400 1
 
3.8%
-229440 1
 
3.8%
0 13
50.0%
3344 1
 
3.8%
238180 1
 
3.8%
1198900 1
 
3.8%
11578392 1
 
3.8%
13766181 1
 
3.8%
23063730 1
 
3.8%
48927204 1
 
3.8%
ValueCountFrequency (%)
208275000 1
3.8%
150060000 1
3.8%
126105483 1
3.8%
86165080 1
3.8%
48927204 1
3.8%
23063730 1
3.8%
13766181 1
3.8%
11578392 1
3.8%
1198900 1
3.8%
238180 1
3.8%

Interactions

2024-04-21T07:07:38.801714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T07:07:40.175581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비용명금액
비용명1.0001.000
금액1.0001.000

Missing values

2024-04-21T07:07:38.929157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T07:07:39.014563image/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
0서초트라팰리스1차A13792306현금200512238180
1서초트라팰리스1차A13792306예금20051248927204
2서초트라팰리스1차A13792306관리비미수금20051286165080
3서초트라팰리스1차A13792306미수관리비예치금200512150060000
4서초트라팰리스1차A13792306선급비용20051211578392
5서초트라팰리스1차A13792306가지급금2005121198900
6서초트라팰리스1차A13792306기타당좌자산2005120
7서초트라팰리스1차A13792306장기수선충당예금2005120
8서초트라팰리스1차A13792306퇴직급여충당예금2005120
9서초트라팰리스1차A13792306비품20051223063730
아파트명아파트코드비용명년월일금액
16서초트라팰리스1차A13792306기타유동부채2005120
17서초트라팰리스1차A13792306상여충당부채2005120
18서초트라팰리스1차A13792306연차수당충당부채2005120
19서초트라팰리스1차A13792306퇴직급여충당부채2005120
20서초트라팰리스1차A13792306수선유지비충당부채2005120
21서초트라팰리스1차A13792306장기수선충당부채2005120
22서초트라팰리스1차A13792306관리비예치금200512208275000
23서초트라팰리스1차A13792306공동주택적립금2005120
24서초트라팰리스1차A13792306미처분이익잉여금2005120
25서초트라팰리스1차A13792306당기순이익2005123344