Overview

Dataset statistics

Number of variables6
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory53.2 B

Variable types

Categorical3
Numeric3

Dataset

Description안동시의 도시계획시설로 결정된 시설녹지(완충녹지, 경관녹지, 연결녹지) 개소수 및 면적 등의 항목을 제공합니다.
Author경상북도 안동시
URLhttps://www.data.go.kr/data/15112518/fileData.do

Alerts

시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
기준 연도 is highly overall correlated with 면적(천제곱미터)High correlation
녹지수(개) is highly overall correlated with 면적(천제곱미터) and 1 other fieldsHigh correlation
면적(천제곱미터) is highly overall correlated with 기준 연도 and 2 other fieldsHigh correlation
녹지 구분 is highly overall correlated with 녹지수(개) and 1 other fieldsHigh correlation
녹지수(개) has 12 (21.1%) zerosZeros
면적(천제곱미터) has 12 (21.1%) zerosZeros

Reproduction

Analysis started2024-03-15 01:26:51.809684
Analysis finished2024-03-15 01:26:54.877606
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
안동시
57 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
안동시 57
100.0%

Length

2024-03-15T10:26:55.084331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:26:55.647523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
안동시 57
100.0%

기준 연도
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014
Minimum2005
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T10:26:56.069414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2005.8
Q12009
median2014
Q32019
95-th percentile2022.2
Maximum2023
Range18
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.525913
Coefficient of variation (CV)0.0027437502
Kurtosis-1.2064826
Mean2014
Median Absolute Deviation (MAD)5
Skewness0
Sum114798
Variance30.535714
MonotonicityIncreasing
2024-03-15T10:26:56.504314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2005 3
 
5.3%
2006 3
 
5.3%
2023 3
 
5.3%
2022 3
 
5.3%
2021 3
 
5.3%
2020 3
 
5.3%
2019 3
 
5.3%
2018 3
 
5.3%
2017 3
 
5.3%
2016 3
 
5.3%
Other values (9) 27
47.4%
ValueCountFrequency (%)
2005 3
5.3%
2006 3
5.3%
2007 3
5.3%
2008 3
5.3%
2009 3
5.3%
2010 3
5.3%
2011 3
5.3%
2012 3
5.3%
2013 3
5.3%
2014 3
5.3%
ValueCountFrequency (%)
2023 3
5.3%
2022 3
5.3%
2021 3
5.3%
2020 3
5.3%
2019 3
5.3%
2018 3
5.3%
2017 3
5.3%
2016 3
5.3%
2015 3
5.3%
2014 3
5.3%

녹지 구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
완충녹지
19 
경관녹지
19 
연결녹지
19 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완충녹지
2nd row경관녹지
3rd row연결녹지
4th row완충녹지
5th row경관녹지

Common Values

ValueCountFrequency (%)
완충녹지 19
33.3%
경관녹지 19
33.3%
연결녹지 19
33.3%

Length

2024-03-15T10:26:57.092183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:26:57.777093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완충녹지 19
33.3%
경관녹지 19
33.3%
연결녹지 19
33.3%

녹지수(개)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.912281
Minimum0
Maximum140
Zeros12
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T10:26:58.133629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median24
Q379
95-th percentile106.2
Maximum140
Range140
Interquartile range (IQR)73

Descriptive statistics

Standard deviation42.284868
Coefficient of variation (CV)1.0335495
Kurtosis-0.85543171
Mean40.912281
Median Absolute Deviation (MAD)24
Skewness0.68222036
Sum2332
Variance1788.01
MonotonicityNot monotonic
2024-03-15T10:26:58.535883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 12
21.1%
6 10
17.5%
71 4
 
7.0%
87 3
 
5.3%
4 2
 
3.5%
49 2
 
3.5%
54 2
 
3.5%
28 2
 
3.5%
105 2
 
3.5%
22 2
 
3.5%
Other values (14) 16
28.1%
ValueCountFrequency (%)
0 12
21.1%
4 2
 
3.5%
6 10
17.5%
13 2
 
3.5%
22 2
 
3.5%
24 1
 
1.8%
26 1
 
1.8%
28 2
 
3.5%
42 1
 
1.8%
48 1
 
1.8%
ValueCountFrequency (%)
140 1
 
1.8%
139 1
 
1.8%
107 1
 
1.8%
106 1
 
1.8%
105 2
3.5%
99 2
3.5%
91 1
 
1.8%
89 1
 
1.8%
88 1
 
1.8%
87 3
5.3%

면적(천제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean211674.3
Minimum0
Maximum840850
Zeros12
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T10:26:58.931466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114124
median155791
Q3311613
95-th percentile789122.8
Maximum840850
Range840850
Interquartile range (IQR)297489

Descriptive statistics

Standard deviation260427.79
Coefficient of variation (CV)1.2303232
Kurtosis0.75930717
Mean211674.3
Median Absolute Deviation (MAD)141672
Skewness1.3365716
Sum12065435
Variance6.7822635 × 1010
MonotonicityNot monotonic
2024-03-15T10:26:59.310280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 12
21.1%
14126 9
15.8%
235363 3
 
5.3%
14124 2
 
3.5%
840850 2
 
3.5%
776521 2
 
3.5%
712284 2
 
3.5%
315709 2
 
3.5%
172877 2
 
3.5%
24916 2
 
3.5%
Other values (17) 19
33.3%
ValueCountFrequency (%)
0 12
21.1%
14119 1
 
1.8%
14124 2
 
3.5%
14126 9
15.8%
24916 2
 
3.5%
85678 1
 
1.8%
155791 2
 
3.5%
164996 1
 
1.8%
172877 2
 
3.5%
207906 1
 
1.8%
ValueCountFrequency (%)
840850 2
3.5%
839530 1
1.8%
776521 2
3.5%
714859 1
1.8%
712284 2
3.5%
356156 1
1.8%
352288 1
1.8%
319852 1
1.8%
315709 2
3.5%
315614 1
1.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
2024-02-28
57 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-28
2nd row2024-02-28
3rd row2024-02-28
4th row2024-02-28
5th row2024-02-28

Common Values

ValueCountFrequency (%)
2024-02-28 57
100.0%

Length

2024-03-15T10:26:59.707200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:27:00.005821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-28 57
100.0%

Interactions

2024-03-15T10:26:53.582961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:52.020382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:52.797159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:53.849595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:52.283904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:53.065602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:54.094883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:52.548113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:26:53.327494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:27:00.185759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도녹지 구분녹지수(개)면적(천제곱미터)
기준 연도1.0000.0000.5360.459
녹지 구분0.0001.0000.8690.856
녹지수(개)0.5360.8691.0000.969
면적(천제곱미터)0.4590.8560.9691.000
2024-03-15T10:27:00.415944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연도녹지수(개)면적(천제곱미터)녹지 구분
기준 연도1.0000.3750.5130.000
녹지수(개)0.3751.0000.8580.793
면적(천제곱미터)0.5130.8581.0000.804
녹지 구분0.0000.7930.8041.000

Missing values

2024-03-15T10:26:54.406325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:26:54.730958image/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

시군구기준 연도녹지 구분녹지수(개)면적(천제곱미터)데이터기준일자
0안동시2005완충녹지711728772024-02-28
1안동시2005경관녹지002024-02-28
2안동시2005연결녹지002024-02-28
3안동시2006완충녹지711728772024-02-28
4안동시2006경관녹지002024-02-28
5안동시2006연결녹지002024-02-28
6안동시2007완충녹지792353632024-02-28
7안동시2007경관녹지002024-02-28
8안동시2007연결녹지002024-02-28
9안동시2008완충녹지712353632024-02-28
시군구기준 연도녹지 구분녹지수(개)면적(천제곱미터)데이터기준일자
47안동시2020연결녹지6141262024-02-28
48안동시2021완충녹지882197202024-02-28
49안동시2021경관녹지498408502024-02-28
50안동시2021연결녹지6141262024-02-28
51안동시2022완충녹지872180362024-02-28
52안동시2022경관녹지498408502024-02-28
53안동시2022연결녹지6141262024-02-28
54안동시2023완충녹지872079062024-02-28
55안동시2023경관녹지488395302024-02-28
56안동시2023연결녹지6141262024-02-28