Overview

Dataset statistics

Number of variables4
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory38.0 B

Variable types

Categorical3
Numeric1

Dataset

Description부산광역시중구_U-옥외광고물통합관리시스템정비실적_20230918
Author부산광역시 중구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15123273

Alerts

정비(철거)건수 is highly overall correlated with 형태High correlation
분류 is highly overall correlated with 형태High correlation
형태 is highly overall correlated with 정비(철거)건수 and 1 other fieldsHigh correlation
정비(철거)건수 has 6 (18.2%) zerosZeros

Reproduction

Analysis started2023-12-10 16:50:59.705688
Analysis finished2023-12-10 16:51:00.363564
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정비년도
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
2022
11 
2021
11 
2020
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 11
33.3%
2021 11
33.3%
2020 11
33.3%

Length

2023-12-11T01:51:00.475975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:00.620074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 11
33.3%
2021 11
33.3%
2020 11
33.3%

분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
고정광고물
12 
유동광고물
12 
간판
9 

Length

Max length5
Median length5
Mean length4.1818182
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고정광고물
2nd row고정광고물
3rd row고정광고물
4th row고정광고물
5th row유동광고물

Common Values

ValueCountFrequency (%)
고정광고물 12
36.4%
유동광고물 12
36.4%
간판 9
27.3%

Length

2023-12-11T01:51:00.786055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:00.955126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정광고물 12
36.4%
유동광고물 12
36.4%
간판 9
27.3%

형태
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
돌출
6 
기타
6 
벽면이용
3 
옥상간판
3 
지주이용 등
3 
Other values (4)
12 

Length

Max length6
Median length2
Mean length2.8181818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row벽면이용
2nd row돌출
3rd row옥상간판
4th row지주이용 등
5th row현수막

Common Values

ValueCountFrequency (%)
돌출 6
18.2%
기타 6
18.2%
벽면이용 3
9.1%
옥상간판 3
9.1%
지주이용 등 3
9.1%
현수막 3
9.1%
벽보 3
9.1%
전단 3
9.1%
벽면 3
9.1%

Length

2023-12-11T01:51:01.177450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:51:01.451098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
돌출 6
16.7%
기타 6
16.7%
벽면이용 3
8.3%
옥상간판 3
8.3%
지주이용 3
8.3%
등 3
8.3%
현수막 3
8.3%
벽보 3
8.3%
전단 3
8.3%
벽면 3
8.3%

정비(철거)건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14951.091
Minimum0
Maximum175291
Zeros6
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-11T01:51:01.701785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median24
Q31239
95-th percentile146636
Maximum175291
Range175291
Interquartile range (IQR)1233

Descriptive statistics

Standard deviation45910.205
Coefficient of variation (CV)3.0706926
Kurtosis7.7422194
Mean14951.091
Median Absolute Deviation (MAD)24
Skewness3.0224699
Sum493386
Variance2.1077469 × 109
MonotonicityNot monotonic
2023-12-11T01:51:01.944089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 6
 
18.2%
24 2
 
6.1%
34 2
 
6.1%
22 1
 
3.0%
28 1
 
3.0%
23 1
 
3.0%
17 1
 
3.0%
197 1
 
3.0%
10559 1
 
3.0%
155291 1
 
3.0%
Other values (16) 16
48.5%
ValueCountFrequency (%)
0 6
18.2%
2 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%
8 1
 
3.0%
12 1
 
3.0%
17 1
 
3.0%
19 1
 
3.0%
22 1
 
3.0%
23 1
 
3.0%
ValueCountFrequency (%)
175291 1
3.0%
155291 1
3.0%
140866 1
3.0%
10559 1
3.0%
4031 1
3.0%
2098 1
3.0%
1641 1
3.0%
1629 1
3.0%
1239 1
3.0%
197 1
3.0%

Interactions

2023-12-11T01:50:59.956395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:51:02.103998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정비년도분류형태정비(철거)건수
정비년도1.0000.0000.0000.000
분류0.0001.0000.9670.442
형태0.0000.9671.0000.863
정비(철거)건수0.0000.4420.8631.000
2023-12-11T01:51:02.252792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
형태분류정비년도
형태1.0000.6990.000
분류0.6991.0000.000
정비년도0.0000.0001.000
2023-12-11T01:51:02.417130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정비(철거)건수정비년도분류형태
정비(철거)건수1.0000.0000.1630.516
정비년도0.0001.0000.0000.000
분류0.1630.0001.0000.699
형태0.5160.0000.6991.000

Missing values

2023-12-11T01:51:00.151489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:51:00.300648image/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

정비년도분류형태정비(철거)건수
02022고정광고물벽면이용22
12022고정광고물돌출34
22022고정광고물옥상간판0
32022고정광고물지주이용 등0
42022유동광고물현수막1641
52022유동광고물벽보140866
62022유동광고물전단2098
72022유동광고물기타127
82022간판벽면8
92022간판돌출12
정비년도분류형태정비(철거)건수
232020고정광고물돌출55
242020고정광고물옥상간판2
252020고정광고물지주이용 등6
262020유동광고물현수막1629
272020유동광고물벽보155291
282020유동광고물전단10559
292020유동광고물기타197
302020간판벽면17
312020간판돌출23
322020간판기타0