Overview

Dataset statistics

Number of variables9
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory81.7 B

Variable types

Categorical5
Text1
Numeric3

Dataset

Description전라남도 함평군 관내 사방댐 현황에 대한 자료입니다. 이 자료는 전라남도 함평군 관내 소재지, 위치, 사방댐종류 등의 내용을 포함합니다.
Author전라남도 함평군
URLhttps://www.data.go.kr/data/15037392/fileData.do

Alerts

시공형식 has constant value ""Constant
사업완료년도 is highly overall correlated with 윗 너비(m) and 2 other fieldsHigh correlation
윗 너비(m) is highly overall correlated with 사업완료년도 and 1 other fieldsHigh correlation
아랫너비(m) is highly overall correlated with 사업완료년도 and 1 other fieldsHigh correlation
시행청 is highly overall correlated with 사업완료년도 and 1 other fieldsHigh correlation
시공목적 is highly overall correlated with 시행청High correlation
시공위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:49:11.815356
Analysis finished2023-12-12 14:49:13.490941
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시행청
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
전라남도
16 
함평군
6 
서부지방산림청 영암국유림관리소
 
1

Length

Max length16
Median length4
Mean length4.2608696
Min length3

Unique

Unique1 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
전라남도 16
69.6%
함평군 6
 
26.1%
서부지방산림청 영암국유림관리소 1
 
4.3%

Length

2023-12-12T23:49:13.570070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:13.729500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 16
66.7%
함평군 6
 
25.0%
서부지방산림청 1
 
4.2%
영암국유림관리소 1
 
4.2%

시공위치
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-12T23:49:14.018081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length15.478261
Min length15

Characters and Unicode

Total characters356
Distinct characters47
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row함평군 나산면 우치리 산49
2nd row함평군 나산면 원선리 산53
3rd row함평군 나산면 원선리 산57
4th row함평군 나산면 원선리 산55
5th row함평군 대동면 상옥리 산83
ValueCountFrequency (%)
함평군 23
25.0%
대동면 7
 
7.6%
나산면 7
 
7.6%
해보면 5
 
5.4%
금계리 4
 
4.3%
운교리 4
 
4.3%
원선리 3
 
3.3%
신광면 3
 
3.3%
월암리 2
 
2.2%
산57 2
 
2.2%
Other values (31) 32
34.8%
2023-12-12T23:49:14.651396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
19.7%
산 31
 
8.7%
평 24
 
6.7%
함 23
 
6.5%
면 23
 
6.5%
리 23
 
6.5%
군 23
 
6.5%
1 10
 
2.8%
5 10
 
2.8%
0 8
 
2.2%
Other values (37) 111
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 229
64.3%
Space Separator 70
 
19.7%
Decimal Number 52
 
14.6%
Dash Punctuation 5
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 31
13.5%
평 24
10.5%
함 23
10.0%
면 23
10.0%
리 23
10.0%
군 23
10.0%
나 7
 
3.1%
대 7
 
3.1%
동 7
 
3.1%
보 5
 
2.2%
Other values (25) 56
24.5%
Decimal Number
ValueCountFrequency (%)
1 10
19.2%
5 10
19.2%
0 8
15.4%
4 5
9.6%
3 5
9.6%
2 4
 
7.7%
6 3
 
5.8%
7 3
 
5.8%
8 2
 
3.8%
9 2
 
3.8%
Space Separator
ValueCountFrequency (%)
70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 229
64.3%
Common 127
35.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 31
13.5%
평 24
10.5%
함 23
10.0%
면 23
10.0%
리 23
10.0%
군 23
10.0%
나 7
 
3.1%
대 7
 
3.1%
동 7
 
3.1%
보 5
 
2.2%
Other values (25) 56
24.5%
Common
ValueCountFrequency (%)
70
55.1%
1 10
 
7.9%
5 10
 
7.9%
0 8
 
6.3%
4 5
 
3.9%
- 5
 
3.9%
3 5
 
3.9%
2 4
 
3.1%
6 3
 
2.4%
7 3
 
2.4%
Other values (2) 4
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 229
64.3%
ASCII 127
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
55.1%
1 10
 
7.9%
5 10
 
7.9%
0 8
 
6.3%
4 5
 
3.9%
- 5
 
3.9%
3 5
 
3.9%
2 4
 
3.1%
6 3
 
2.4%
7 3
 
2.4%
Other values (2) 4
 
3.1%
Hangul
ValueCountFrequency (%)
산 31
13.5%
평 24
10.5%
함 23
10.0%
면 23
10.0%
리 23
10.0%
군 23
10.0%
나 7
 
3.1%
대 7
 
3.1%
동 7
 
3.1%
보 5
 
2.2%
Other values (25) 56
24.5%

사업완료년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.7391
Minimum2003
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:49:14.917330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2004.3
Q12009.5
median2012
Q32019
95-th percentile2022
Maximum2022
Range19
Interquartile range (IQR)9.5

Descriptive statistics

Standard deviation5.9712751
Coefficient of variation (CV)0.0029652675
Kurtosis-1.0892015
Mean2013.7391
Median Absolute Deviation (MAD)4
Skewness-0.0036677724
Sum46316
Variance35.656126
MonotonicityNot monotonic
2023-12-12T23:49:15.168727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2022 4
17.4%
2012 2
 
8.7%
2011 2
 
8.7%
2010 2
 
8.7%
2009 2
 
8.7%
2015 2
 
8.7%
2004 1
 
4.3%
2003 1
 
4.3%
2007 1
 
4.3%
2008 1
 
4.3%
Other values (5) 5
21.7%
ValueCountFrequency (%)
2003 1
4.3%
2004 1
4.3%
2007 1
4.3%
2008 1
4.3%
2009 2
8.7%
2010 2
8.7%
2011 2
8.7%
2012 2
8.7%
2015 2
8.7%
2016 1
4.3%
ValueCountFrequency (%)
2022 4
17.4%
2021 1
 
4.3%
2020 1
 
4.3%
2018 1
 
4.3%
2017 1
 
4.3%
2016 1
 
4.3%
2015 2
8.7%
2012 2
8.7%
2011 2
8.7%
2010 2
8.7%

시공목적
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
저사
17 
저사
5 
저사저수
 
1

Length

Max length4
Median length2
Mean length2.3043478
Min length2

Unique

Unique1 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
저사 17
73.9%
저사 5
 
21.7%
저사저수 1
 
4.3%

Length

2023-12-12T23:49:15.498182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:15.734592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
저사 22
95.7%
저사저수 1
 
4.3%

시공형식
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
불투과형
23 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불투과형 23
100.0%

Length

2023-12-12T23:49:15.935488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:16.123572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불투과형 23
100.0%

사방댐종류
Categorical

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
콘크리트댐
10 
전석댐
9 
블록댐
3 
기타
 
1

Length

Max length5
Median length3
Mean length3.826087
Min length2

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row전석댐
2nd row전석댐
3rd row전석댐
4th row전석댐
5th row콘크리트댐

Common Values

ValueCountFrequency (%)
콘크리트댐 10
43.5%
전석댐 9
39.1%
블록댐 3
 
13.0%
기타 1
 
4.3%

Length

2023-12-12T23:49:16.291106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:16.466434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
콘크리트댐 10
43.5%
전석댐 9
39.1%
블록댐 3
 
13.0%
기타 1
 
4.3%

윗 너비(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.652174
Minimum15
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:49:16.620309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile21.2
Q126
median31
Q337
95-th percentile44.5
Maximum47
Range32
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.8486171
Coefficient of variation (CV)0.24796455
Kurtosis-0.27176248
Mean31.652174
Median Absolute Deviation (MAD)6
Skewness0.0052625132
Sum728
Variance61.600791
MonotonicityNot monotonic
2023-12-12T23:49:16.779143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
37 5
21.7%
26 2
 
8.7%
28 2
 
8.7%
34 1
 
4.3%
21 1
 
4.3%
15 1
 
4.3%
23 1
 
4.3%
25 1
 
4.3%
31 1
 
4.3%
39 1
 
4.3%
Other values (7) 7
30.4%
ValueCountFrequency (%)
15 1
4.3%
21 1
4.3%
23 1
4.3%
24 1
4.3%
25 1
4.3%
26 2
8.7%
28 2
8.7%
29 1
4.3%
30 1
4.3%
31 1
4.3%
ValueCountFrequency (%)
47 1
 
4.3%
45 1
 
4.3%
40 1
 
4.3%
39 1
 
4.3%
37 5
21.7%
34 1
 
4.3%
32 1
 
4.3%
31 1
 
4.3%
30 1
 
4.3%
29 1
 
4.3%

아랫너비(m)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)73.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.782609
Minimum11
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T23:49:17.359574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile14.1
Q118
median21
Q325
95-th percentile32.5
Maximum38
Range27
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.1493275
Coefficient of variation (CV)0.28230446
Kurtosis1.1128398
Mean21.782609
Median Absolute Deviation (MAD)4
Skewness0.79081515
Sum501
Variance37.814229
MonotonicityNot monotonic
2023-12-12T23:49:17.579561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
18 3
13.0%
20 3
13.0%
25 2
 
8.7%
22 2
 
8.7%
17 1
 
4.3%
14 1
 
4.3%
11 1
 
4.3%
15 1
 
4.3%
24 1
 
4.3%
28 1
 
4.3%
Other values (7) 7
30.4%
ValueCountFrequency (%)
11 1
 
4.3%
14 1
 
4.3%
15 1
 
4.3%
16 1
 
4.3%
17 1
 
4.3%
18 3
13.0%
20 3
13.0%
21 1
 
4.3%
22 2
8.7%
23 1
 
4.3%
ValueCountFrequency (%)
38 1
4.3%
33 1
4.3%
28 1
4.3%
27 1
4.3%
26 1
4.3%
25 2
8.7%
24 1
4.3%
23 1
4.3%
22 2
8.7%
21 1
4.3%

유효높이(m)
Categorical

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
4.0
11 
3.0
9 
5.0
2 
1.5
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row4.0
2nd row4.0
3rd row5.0
4th row3.0
5th row4.0

Common Values

ValueCountFrequency (%)
4.0 11
47.8%
3.0 9
39.1%
5.0 2
 
8.7%
1.5 1
 
4.3%

Length

2023-12-12T23:49:17.849212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:49:18.073603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4.0 11
47.8%
3.0 9
39.1%
5.0 2
 
8.7%
1.5 1
 
4.3%

Interactions

2023-12-12T23:49:12.882820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:12.238022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:12.548274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:13.015609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:12.342807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:12.676452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:13.119848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:12.438044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:49:12.787130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:49:18.245631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시행청시공위치사업완료년도시공목적사방댐종류윗 너비(m)아랫너비(m)유효높이(m)
시행청1.0001.0000.8360.9280.0000.2390.0000.000
시공위치1.0001.0001.0001.0001.0001.0001.0001.000
사업완료년도0.8361.0001.0000.6660.8470.2550.2660.000
시공목적0.9281.0000.6661.0000.0000.0000.4870.000
사방댐종류0.0001.0000.8470.0001.0000.3210.5680.570
윗 너비(m)0.2391.0000.2550.0000.3211.0000.8570.624
아랫너비(m)0.0001.0000.2660.4870.5680.8571.0000.660
유효높이(m)0.0001.0000.0000.0000.5700.6240.6601.000
2023-12-12T23:49:18.525224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시행청사방댐종류시공목적유효높이(m)
시행청1.0000.0000.6710.000
사방댐종류0.0001.0000.0000.239
시공목적0.6710.0001.0000.000
유효높이(m)0.0000.2390.0001.000
2023-12-12T23:49:18.731210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업완료년도윗 너비(m)아랫너비(m)시행청시공목적사방댐종류유효높이(m)
사업완료년도1.000-0.606-0.5470.6770.4710.4350.000
윗 너비(m)-0.6061.0000.9000.0000.0000.2470.326
아랫너비(m)-0.5470.9001.0000.0000.1610.3210.404
시행청0.6770.0000.0001.0000.6710.0000.000
시공목적0.4710.0000.1610.6711.0000.0000.000
사방댐종류0.4350.2470.3210.0000.0001.0000.239
유효높이(m)0.0000.3260.4040.0000.0000.2391.000

Missing values

2023-12-12T23:49:13.267496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:49:13.437530image/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

시행청시공위치사업완료년도시공목적시공형식사방댐종류윗 너비(m)아랫너비(m)유효높이(m)
0전라남도함평군 나산면 우치리 산492012저사불투과형전석댐34234.0
1전라남도함평군 나산면 원선리 산532004저사불투과형전석댐45264.0
2전라남도함평군 나산면 원선리 산572011저사불투과형전석댐37255.0
3전라남도함평군 나산면 원선리 산552012저사불투과형전석댐32223.0
4전라남도함평군 대동면 상옥리 산832010저사불투과형콘크리트댐30164.0
5전라남도함평군 대동면 연암리 산802010저사불투과형전석댐37274.0
6전라남도함평군 대동면 운교리 산572003저사불투과형콘크리트댐40223.0
7전라남도함평군 대동면 향교리 산1-12009저사불투과형콘크리트댐28203.0
8전라남도함평군 해보면 금계리 산342007저사불투과형전석댐37254.0
9전라남도함평군 해보면 금계리 산50-102008저사불투과형콘크리트댐37333.0
시행청시공위치사업완료년도시공목적시공형식사방댐종류윗 너비(m)아랫너비(m)유효높이(m)
13전라남도함평군 대동면 운교리 산132015저사불투과형블록댐26174.0
14전라남도함평군 신광면 월암리 산40-12016저사불투과형블록댐39284.0
15전라남도함평군 신광면 삼덕리 산1762017저사불투과형콘크리트댐31205.0
16서부지방산림청 영암국유림관리소함평군 나산면 구산리 산402018저사불투과형콘크리트댐25203.0
17함평군함평군 대동면 운교리 102020저사불투과형전석댐26184.0
18함평군함평군 신광면 월암리 산222021저사저수불투과형전석댐37244.0
19함평군함평군 손불면 북성리 산102022저사불투과형콘크리트댐23153.0
20함평군함평군 나산면 우치리 산412022저사불투과형전석댐15111.5
21함평군함평군 나산면 신평리 산652022저사불투과형콘크리트댐28184.0
22함평군함평군 해보면 금계리 산36-12022저사불투과형콘크리트댐21143.0