Overview

Dataset statistics

Number of variables6
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory54.9 B

Variable types

Numeric2
Categorical1
Text3

Dataset

Description경상남도 하동군에 있는 도시숲 조성 현황 (연번, 연도, 종류, 소재지, 사업량(키로미터), 예산액(천원) 등)의 정보를 제공하고 있습니다
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15086123

Alerts

연번 is highly overall correlated with 연도High correlation
연도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:50:56.050981
Analysis finished2023-12-10 22:50:57.000846
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T07:50:57.058400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-11T07:50:57.479497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2016.8889
Minimum2011
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-11T07:50:57.624966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2011
5-th percentile2012
Q12014.5
median2018
Q32019
95-th percentile2020
Maximum2021
Range10
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.0042705
Coefficient of variation (CV)0.0014895568
Kurtosis-1.0152515
Mean2016.8889
Median Absolute Deviation (MAD)2
Skewness-0.57406918
Sum54456
Variance9.025641
MonotonicityIncreasing
2023-12-11T07:50:57.756681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2019 5
18.5%
2020 5
18.5%
2018 4
14.8%
2013 3
11.1%
2016 3
11.1%
2012 2
 
7.4%
2011 1
 
3.7%
2014 1
 
3.7%
2015 1
 
3.7%
2017 1
 
3.7%
ValueCountFrequency (%)
2011 1
 
3.7%
2012 2
 
7.4%
2013 3
11.1%
2014 1
 
3.7%
2015 1
 
3.7%
2016 3
11.1%
2017 1
 
3.7%
2018 4
14.8%
2019 5
18.5%
2020 5
18.5%
ValueCountFrequency (%)
2021 1
 
3.7%
2020 5
18.5%
2019 5
18.5%
2018 4
14.8%
2017 1
 
3.7%
2016 3
11.1%
2015 1
 
3.7%
2014 1
 
3.7%
2013 3
11.1%
2012 2
 
7.4%

종류
Categorical

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
가로수
20 
도시녹지
3 
학교숲
3 
도시숲
 
1

Length

Max length4
Median length3
Mean length3.1111111
Min length3

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row도시숲
2nd row도시녹지
3rd row학교숲
4th row도시녹지
5th row도시녹지

Common Values

ValueCountFrequency (%)
가로수 20
74.1%
도시녹지 3
 
11.1%
학교숲 3
 
11.1%
도시숲 1
 
3.7%

Length

2023-12-11T07:50:57.887763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:50:58.007925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로수 20
74.1%
도시녹지 3
 
11.1%
학교숲 3
 
11.1%
도시숲 1
 
3.7%

소재지
Text

Distinct22
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T07:50:58.201512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length13.851852
Min length6

Characters and Unicode

Total characters374
Distinct characters68
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)70.4%

Sample

1st row금성면 가린길 32 궁항초등학교
2nd row금성해안도로등
3rd row하동고등학교
4th row지방도 1005호선변
5th row국도 59호선변
ValueCountFrequency (%)
지방도 7
 
13.2%
1002호선변(왕벚나무 4
 
7.5%
국도 3
 
5.7%
1002호선(왕벚나무 2
 
3.8%
국도19호선변(왕벚나무 2
 
3.8%
국도19호선 2
 
3.8%
국도2호선변(배롱나무 2
 
3.8%
금성해안도로등 1
 
1.9%
해안도로(이팝나무,가시나무 1
 
1.9%
가린길 1
 
1.9%
Other values (28) 28
52.8%
2023-12-11T07:50:58.619781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
7.0%
도 22
 
5.9%
무 20
 
5.3%
선 19
 
5.1%
호 19
 
5.1%
나 18
 
4.8%
) 18
 
4.8%
( 18
 
4.8%
1 16
 
4.3%
변 15
 
4.0%
Other values (58) 183
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 253
67.6%
Decimal Number 54
 
14.4%
Space Separator 26
 
7.0%
Close Punctuation 18
 
4.8%
Open Punctuation 18
 
4.8%
Other Punctuation 4
 
1.1%
Math Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 22
 
8.7%
무 20
 
7.9%
선 19
 
7.5%
호 19
 
7.5%
나 18
 
7.1%
변 15
 
5.9%
국 12
 
4.7%
벚 10
 
4.0%
왕 10
 
4.0%
방 7
 
2.8%
Other values (46) 101
39.9%
Decimal Number
ValueCountFrequency (%)
1 16
29.6%
0 14
25.9%
9 10
18.5%
2 9
16.7%
5 2
 
3.7%
7 2
 
3.7%
3 1
 
1.9%
Space Separator
ValueCountFrequency (%)
26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 253
67.6%
Common 121
32.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 22
 
8.7%
무 20
 
7.9%
선 19
 
7.5%
호 19
 
7.5%
나 18
 
7.1%
변 15
 
5.9%
국 12
 
4.7%
벚 10
 
4.0%
왕 10
 
4.0%
방 7
 
2.8%
Other values (46) 101
39.9%
Common
ValueCountFrequency (%)
26
21.5%
) 18
14.9%
( 18
14.9%
1 16
13.2%
0 14
11.6%
9 10
 
8.3%
2 9
 
7.4%
, 4
 
3.3%
5 2
 
1.7%
7 2
 
1.7%
Other values (2) 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 253
67.6%
ASCII 121
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
21.5%
) 18
14.9%
( 18
14.9%
1 16
13.2%
0 14
11.6%
9 10
 
8.3%
2 9
 
7.4%
, 4
 
3.3%
5 2
 
1.7%
7 2
 
1.7%
Other values (2) 2
 
1.7%
Hangul
ValueCountFrequency (%)
도 22
 
8.7%
무 20
 
7.9%
선 19
 
7.5%
호 19
 
7.5%
나 18
 
7.1%
변 15
 
5.9%
국 12
 
4.7%
벚 10
 
4.0%
왕 10
 
4.0%
방 7
 
2.8%
Other values (46) 101
39.9%

사업량(키로미터)
Text

Distinct19
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T07:50:58.820634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.4074074
Min length1

Characters and Unicode

Total characters92
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)44.4%

Sample

1st row293(제곱미터)
2nd row5.44
3rd row0.02(헥타르)
4th row10
5th row7
ValueCountFrequency (%)
1 3
 
11.1%
0.4 2
 
7.4%
0.6 2
 
7.4%
0.5 2
 
7.4%
1.4 2
 
7.4%
2.8 2
 
7.4%
0.3 2
 
7.4%
1.2 1
 
3.7%
0.9 1
 
3.7%
1.7 1
 
3.7%
Other values (9) 9
33.3%
2023-12-11T07:50:59.178659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 21
22.8%
0 17
18.5%
1 8
 
8.7%
4 6
 
6.5%
2 6
 
6.5%
5 4
 
4.3%
) 3
 
3.3%
3 3
 
3.3%
9 3
 
3.3%
8 3
 
3.3%
Other values (10) 18
19.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
59.8%
Other Punctuation 21
 
22.8%
Other Letter 10
 
10.9%
Close Punctuation 3
 
3.3%
Open Punctuation 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
30.9%
1 8
14.5%
4 6
 
10.9%
2 6
 
10.9%
5 4
 
7.3%
3 3
 
5.5%
9 3
 
5.5%
8 3
 
5.5%
7 3
 
5.5%
6 2
 
3.6%
Other Letter
ValueCountFrequency (%)
헥 2
20.0%
르 2
20.0%
타 2
20.0%
제 1
10.0%
곱 1
10.0%
미 1
10.0%
터 1
10.0%
Other Punctuation
ValueCountFrequency (%)
. 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
89.1%
Hangul 10
 
10.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 21
25.6%
0 17
20.7%
1 8
 
9.8%
4 6
 
7.3%
2 6
 
7.3%
5 4
 
4.9%
) 3
 
3.7%
3 3
 
3.7%
9 3
 
3.7%
8 3
 
3.7%
Other values (3) 8
 
9.8%
Hangul
ValueCountFrequency (%)
헥 2
20.0%
르 2
20.0%
타 2
20.0%
제 1
10.0%
곱 1
10.0%
미 1
10.0%
터 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
89.1%
Hangul 10
 
10.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 21
25.6%
0 17
20.7%
1 8
 
9.8%
4 6
 
7.3%
2 6
 
7.3%
5 4
 
4.9%
) 3
 
3.7%
3 3
 
3.7%
9 3
 
3.7%
8 3
 
3.7%
Other values (3) 8
 
9.8%
Hangul
ValueCountFrequency (%)
헥 2
20.0%
르 2
20.0%
타 2
20.0%
제 1
10.0%
곱 1
10.0%
미 1
10.0%
터 1
10.0%

예산액(천원)
Text

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T07:50:59.413598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0740741
Min length6

Characters and Unicode

Total characters164
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)92.6%

Sample

1st row58,205
2nd row592,000
3rd row60,000
4th row87,315
5th row314,294
ValueCountFrequency (%)
60,000 2
 
7.4%
58,205 1
 
3.7%
28,043 1
 
3.7%
18,980 1
 
3.7%
19,500 1
 
3.7%
19,700 1
 
3.7%
33,220 1
 
3.7%
88,358 1
 
3.7%
63,170 1
 
3.7%
17,721 1
 
3.7%
Other values (16) 16
59.3%
2023-12-11T07:50:59.755197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 32
19.5%
, 27
16.5%
4 16
9.8%
3 14
8.5%
5 12
 
7.3%
2 12
 
7.3%
1 12
 
7.3%
9 12
 
7.3%
8 11
 
6.7%
7 10
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 137
83.5%
Other Punctuation 27
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32
23.4%
4 16
11.7%
3 14
10.2%
5 12
 
8.8%
2 12
 
8.8%
1 12
 
8.8%
9 12
 
8.8%
8 11
 
8.0%
7 10
 
7.3%
6 6
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 32
19.5%
, 27
16.5%
4 16
9.8%
3 14
8.5%
5 12
 
7.3%
2 12
 
7.3%
1 12
 
7.3%
9 12
 
7.3%
8 11
 
6.7%
7 10
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 32
19.5%
, 27
16.5%
4 16
9.8%
3 14
8.5%
5 12
 
7.3%
2 12
 
7.3%
1 12
 
7.3%
9 12
 
7.3%
8 11
 
6.7%
7 10
 
6.1%

Interactions

2023-12-11T07:50:56.625304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:50:56.445332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:50:56.721212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:50:56.542988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:50:59.850656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연도종류소재지사업량(키로미터)예산액(천원)
연번1.0000.9830.4810.8470.6450.937
연도0.9831.0000.6130.8690.4810.916
종류0.4810.6131.0001.0000.9671.000
소재지0.8470.8691.0001.0000.6620.944
사업량(키로미터)0.6450.4810.9670.6621.0000.954
예산액(천원)0.9370.9161.0000.9440.9541.000
2023-12-11T07:50:59.958217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연도종류
연번1.0000.9910.238
연도0.9911.0000.238
종류0.2380.2381.000

Missing values

2023-12-11T07:50:56.848415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:50:56.961212image/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

연번연도종류소재지사업량(키로미터)예산액(천원)
012011도시숲금성면 가린길 32 궁항초등학교293(제곱미터)58,205
122012도시녹지금성해안도로등5.44592,000
232012학교숲하동고등학교0.02(헥타르)60,000
342013도시녹지지방도 1005호선변1087,315
452013도시녹지국도 59호선변7314,294
562013학교숲하동읍 연화길 77 중앙중학교0.80(헥타르)59,917
672014가로수하동 두곡~화심 가로수 식재0.620,460
782015가로수흥룡마을 가로변134,932
892016학교숲하동여자고등학교0.560,000
9102016가로수국도19호선변(왕벚나무)2.890,184
연번연도종류소재지사업량(키로미터)예산액(천원)
17182019가로수국도 19호선변(무궁화)1.460,301
18192019가로수국도2호선변(배롱나무)0.419,098
19202019가로수국도19호선(왕벚나무)0.317,721
20212019가로수국도 19호선(왕벚나무)163,170
21222020가로수국도2호선변(배롱나무)1.788,358
22232020가로수고전 도로변(이팝나무)0.533,220
23242020가로수지방도 1002호선변(왕벚나무)0.319,700
24252020가로수국도19호선, 지방도 1002호선(왕벚나무)0.219,500
25262020가로수국도19호선, 지방도 1002호선(왕벚나무)0.418,980
26272021가로수국도19호선변(왕벚나무, 배롱나무)144,755