Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells1
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory44.9 B

Variable types

Text1
Unsupported2
Categorical2

Dataset

Description경상남도 양산시 2013년도 교동 남부동 다방동 덕계동 동면 등 26개 동별 공시지가 최고가, 최저가, 기준일, 결정공시일을 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://www.data.go.kr/data/15053062/fileData.do

Alerts

결정공시일 is highly overall correlated with 기준일High correlation
기준일 is highly overall correlated with 결정공시일High correlation
기준일 is highly imbalanced (77.1%)Imbalance
결정공시일 is highly imbalanced (77.1%)Imbalance
동별 has 1 (3.7%) missing valuesMissing
결정지가 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 09:26:14.079190
Analysis finished2023-12-12 09:26:14.483660
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동별
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Memory size348.0 B
2023-12-12T18:26:14.680488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8846154
Min length2

Characters and Unicode

Total characters75
Distinct characters35
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 row교동
2nd row남부동
3rd row다방동
4th row덕계동
5th row동면
ValueCountFrequency (%)
교동 1
 
3.8%
남부동 1
 
3.8%
하북면 1
 
3.8%
평산동 1
 
3.8%
중부동 1
 
3.8%
주진동 1
 
3.8%
주남동 1
 
3.8%
유산동 1
 
3.8%
원동면 1
 
3.8%
용당동 1
 
3.8%
Other values (16) 16
61.5%
2023-12-12T18:26:15.110761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
30.7%
면 4
 
5.3%
북 4
 
5.3%
산 3
 
4.0%
곡 3
 
4.0%
주 3
 
4.0%
부 3
 
4.0%
계 2
 
2.7%
남 2
 
2.7%
호 2
 
2.7%
Other values (25) 26
34.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
30.7%
면 4
 
5.3%
북 4
 
5.3%
산 3
 
4.0%
곡 3
 
4.0%
주 3
 
4.0%
부 3
 
4.0%
계 2
 
2.7%
남 2
 
2.7%
호 2
 
2.7%
Other values (25) 26
34.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
30.7%
면 4
 
5.3%
북 4
 
5.3%
산 3
 
4.0%
곡 3
 
4.0%
주 3
 
4.0%
부 3
 
4.0%
계 2
 
2.7%
남 2
 
2.7%
호 2
 
2.7%
Other values (25) 26
34.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
30.7%
면 4
 
5.3%
북 4
 
5.3%
산 3
 
4.0%
곡 3
 
4.0%
주 3
 
4.0%
부 3
 
4.0%
계 2
 
2.7%
남 2
 
2.7%
호 2
 
2.7%
Other values (25) 26
34.7%

결정지가
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

Unnamed: 2
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size348.0 B

기준일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
2013.1.1.
26 
<NA>
 
1

Length

Max length9
Median length9
Mean length8.8148148
Min length4

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row<NA>
2nd row2013.1.1.
3rd row2013.1.1.
4th row2013.1.1.
5th row2013.1.1.

Common Values

ValueCountFrequency (%)
2013.1.1. 26
96.3%
<NA> 1
 
3.7%

Length

2023-12-12T18:26:15.311071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:26:15.440403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013.1.1 26
96.3%
na 1
 
3.7%

결정공시일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
2013.5.31.
26 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.7777778
Min length4

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row<NA>
2nd row2013.5.31.
3rd row2013.5.31.
4th row2013.5.31.
5th row2013.5.31.

Common Values

ValueCountFrequency (%)
2013.5.31. 26
96.3%
<NA> 1
 
3.7%

Length

2023-12-12T18:26:15.589082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:26:15.729850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013.5.31 26
96.3%
na 1
 
3.7%

Correlations

2023-12-12T18:26:15.810893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별
동별1.000
2023-12-12T18:26:15.929583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결정공시일기준일
결정공시일1.0001.000
기준일1.0001.000
2023-12-12T18:26:16.046078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일결정공시일
기준일1.0001.000
결정공시일1.0001.000

Missing values

2023-12-12T18:26:14.278521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:26:14.425843image/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

동별결정지가Unnamed: 2기준일결정공시일
0<NA>최저가최고가<NA><NA>
1교동18808630002013.1.1.2013.5.31.
2남부동434022100002013.1.1.2013.5.31.
3다방동21406810002013.1.1.2013.5.31.
4덕계동27517500002013.1.1.2013.5.31.
5동면50615000002013.1.1.2013.5.31.
6매곡동1712680002013.1.1.2013.5.31.
7명곡동6932380002013.1.1.2013.5.31.
8명동1057430002013.1.1.2013.5.31.
9물금읍32024800002013.1.1.2013.5.31.
동별결정지가Unnamed: 2기준일결정공시일
17어곡동3134500002013.1.1.2013.5.31.
18용당동2544610002013.1.1.2013.5.31.
19원동면1253430002013.1.1.2013.5.31.
20유산동13204770002013.1.1.2013.5.31.
21주남동2514560002013.1.1.2013.5.31.
22주진동2646090002013.1.1.2013.5.31.
23중부동259031200002013.1.1.2013.5.31.
24평산동8917200002013.1.1.2013.5.31.
25하북면8915700002013.1.1.2013.5.31.
26호계동3463870002013.1.1.2013.5.31.