Overview

Dataset statistics

Number of variables8
Number of observations84
Missing cells3
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory68.6 B

Variable types

Numeric3
Categorical3
Text2

Dataset

Description경상남도 하동군의 사방사업 현황 (연번, 시군, 읍면, 리동, 지번, 댐종류, 시공연도, 사업비)의 정보를 제공하고 있습니다.
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15087591

Alerts

시군 has constant value ""Constant
연번 is highly overall correlated with 읍면High correlation
읍면 is highly overall correlated with 연번High correlation
사업비(천원) has 3 (3.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-13 00:11:38.466298
Analysis finished2024-03-13 00:11:39.567064
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.5
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T09:11:39.624886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.15
Q121.75
median42.5
Q363.25
95-th percentile79.85
Maximum84
Range83
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation24.392622
Coefficient of variation (CV)0.57394404
Kurtosis-1.2
Mean42.5
Median Absolute Deviation (MAD)21
Skewness0
Sum3570
Variance595
MonotonicityStrictly increasing
2024-03-13T09:11:39.757966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
하동군
84 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
하동군 84
100.0%

Length

2024-03-13T09:11:39.860437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:11:39.934489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
하동군 84
100.0%

읍면
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
옥종면
18 
북천면
12 
악양면
10 
금남면
8 
진교면
8 
Other values (6)
28 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옥종면 18
21.4%
북천면 12
14.3%
악양면 10
11.9%
금남면 8
9.5%
진교면 8
9.5%
적량면 6
 
7.1%
횡천면 6
 
7.1%
화개면 5
 
6.0%
청암면 5
 
6.0%
양보면 3
 
3.6%

Length

2024-03-13T09:11:40.007014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
옥종면 18
21.4%
북천면 12
14.3%
악양면 10
11.9%
금남면 8
9.5%
진교면 8
9.5%
적량면 6
 
7.1%
횡천면 6
 
7.1%
화개면 5
 
6.0%
청암면 5
 
6.0%
양보면 3
 
3.6%

리동
Text

Distinct42
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T09:11:40.149418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8928571
Min length2

Characters and Unicode

Total characters243
Distinct characters59
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

Unique23 ?
Unique (%)27.4%

Sample

1st row등촌리
2nd row등촌리
3rd row등촌리
4th row등촌리
5th row미점리
ValueCountFrequency (%)
직전리 8
 
9.5%
덕천리 5
 
6.0%
서리 5
 
6.0%
두양리 5
 
6.0%
등촌리 4
 
4.8%
월운리 4
 
4.8%
학리 3
 
3.6%
궁항리 3
 
3.6%
정금리 3
 
3.6%
화정리 3
 
3.6%
Other values (32) 41
48.8%
2024-03-13T09:11:40.404713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 84
34.6%
직 8
 
3.3%
전 8
 
3.3%
천 6
 
2.5%
신 6
 
2.5%
정 6
 
2.5%
양 6
 
2.5%
덕 5
 
2.1%
서 5
 
2.1%
두 5
 
2.1%
Other values (49) 104
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 84
34.6%
직 8
 
3.3%
전 8
 
3.3%
천 6
 
2.5%
신 6
 
2.5%
정 6
 
2.5%
양 6
 
2.5%
덕 5
 
2.1%
서 5
 
2.1%
두 5
 
2.1%
Other values (49) 104
42.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 84
34.6%
직 8
 
3.3%
전 8
 
3.3%
천 6
 
2.5%
신 6
 
2.5%
정 6
 
2.5%
양 6
 
2.5%
덕 5
 
2.1%
서 5
 
2.1%
두 5
 
2.1%
Other values (49) 104
42.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 84
34.6%
직 8
 
3.3%
전 8
 
3.3%
천 6
 
2.5%
신 6
 
2.5%
정 6
 
2.5%
양 6
 
2.5%
덕 5
 
2.1%
서 5
 
2.1%
두 5
 
2.1%
Other values (49) 104
42.8%

지번
Text

Distinct81
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-03-13T09:11:40.590726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length10
Mean length5.9047619
Min length3

Characters and Unicode

Total characters496
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)94.0%

Sample

1st row943천
2nd row943천
3rd row316임
4th row943천
5th row808구 외
ValueCountFrequency (%)
외 21
 
20.0%
943천 3
 
2.9%
733구 2
 
1.9%
1073-204천 2
 
1.9%
산56-1구 2
 
1.9%
산90-1외 1
 
1.0%
890구 1
 
1.0%
산49-1외 1
 
1.0%
산51임 1
 
1.0%
1514구외 1
 
1.0%
Other values (70) 70
66.7%
2024-03-13T09:11:40.901915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 86
17.3%
산 50
10.1%
- 36
 
7.3%
외 34
 
6.9%
2 32
 
6.5%
구 29
 
5.8%
7 28
 
5.6%
3 27
 
5.4%
6 26
 
5.2%
4 26
 
5.2%
Other values (9) 122
24.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 296
59.7%
Other Letter 141
28.4%
Dash Punctuation 36
 
7.3%
Space Separator 21
 
4.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 86
29.1%
2 32
 
10.8%
7 28
 
9.5%
3 27
 
9.1%
6 26
 
8.8%
4 26
 
8.8%
0 22
 
7.4%
8 18
 
6.1%
9 16
 
5.4%
5 15
 
5.1%
Other Letter
ValueCountFrequency (%)
산 50
35.5%
외 34
24.1%
구 29
20.6%
임 18
 
12.8%
천 10
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 355
71.6%
Hangul 141
 
28.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 86
24.2%
- 36
10.1%
2 32
 
9.0%
7 28
 
7.9%
3 27
 
7.6%
6 26
 
7.3%
4 26
 
7.3%
0 22
 
6.2%
21
 
5.9%
8 18
 
5.1%
Other values (4) 33
 
9.3%
Hangul
ValueCountFrequency (%)
산 50
35.5%
외 34
24.1%
구 29
20.6%
임 18
 
12.8%
천 10
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 355
71.6%
Hangul 141
 
28.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 86
24.2%
- 36
10.1%
2 32
 
9.0%
7 28
 
7.9%
3 27
 
7.6%
6 26
 
7.3%
4 26
 
7.3%
0 22
 
6.2%
21
 
5.9%
8 18
 
5.1%
Other values (4) 33
 
9.3%
Hangul
ValueCountFrequency (%)
산 50
35.5%
외 34
24.1%
구 29
20.6%
임 18
 
12.8%
천 10
 
7.1%

댐종류
Categorical

Distinct8
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size804.0 B
전석
29 
콘크리트
23 
큰돌
16 
콘크리트(전석)
11 
콘크리트(돌붙임)
 
2
Other values (3)
3 

Length

Max length9
Median length2
Mean length3.6071429
Min length2

Unique

Unique3 ?
Unique (%)3.6%

Sample

1st row전석
2nd row전석
3rd row콘크리트(전석)
4th row콘크리트
5th row전석

Common Values

ValueCountFrequency (%)
전석 29
34.5%
콘크리트 23
27.4%
큰돌 16
19.0%
콘크리트(전석) 11
 
13.1%
콘크리트(돌붙임) 2
 
2.4%
콘크리트(견치석) 1
 
1.2%
사방댐 1
 
1.2%
철강재 1
 
1.2%

Length

2024-03-13T09:11:41.016380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:11:41.109654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전석 29
34.5%
콘크리트 23
27.4%
큰돌 16
19.0%
콘크리트(전석 11
 
13.1%
콘크리트(돌붙임 2
 
2.4%
콘크리트(견치석 1
 
1.2%
사방댐 1
 
1.2%
철강재 1
 
1.2%

시공연도
Real number (ℝ)

Distinct27
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.2024
Minimum1986
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T09:11:41.208986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1986
5-th percentile1997.15
Q12008
median2012
Q32016
95-th percentile2021
Maximum2022
Range36
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.0159539
Coefficient of variation (CV)0.0034884375
Kurtosis2.0891646
Mean2011.2024
Median Absolute Deviation (MAD)4
Skewness-1.1559093
Sum168941
Variance49.223609
MonotonicityNot monotonic
2024-03-13T09:11:41.310776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2013 8
 
9.5%
2014 8
 
9.5%
2011 7
 
8.3%
2012 6
 
7.1%
2016 6
 
7.1%
2007 5
 
6.0%
2017 5
 
6.0%
2022 4
 
4.8%
2010 4
 
4.8%
2009 4
 
4.8%
Other values (17) 27
32.1%
ValueCountFrequency (%)
1986 1
1.2%
1989 1
1.2%
1996 1
1.2%
1997 2
2.4%
1998 1
1.2%
1999 1
1.2%
2001 1
1.2%
2002 1
1.2%
2003 1
1.2%
2004 1
1.2%
ValueCountFrequency (%)
2022 4
4.8%
2021 3
 
3.6%
2020 2
 
2.4%
2018 2
 
2.4%
2017 5
6.0%
2016 6
7.1%
2015 3
 
3.6%
2014 8
9.5%
2013 8
9.5%
2012 6
7.1%

사업비(천원)
Real number (ℝ)

MISSING 

Distinct81
Distinct (%)100.0%
Missing3
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean203955.25
Minimum18449
Maximum425455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-03-13T09:11:41.417375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18449
5-th percentile88320
Q1176419
median215304
Q3232866
95-th percentile274620
Maximum425455
Range407006
Interquartile range (IQR)56447

Descriptive statistics

Standard deviation61986.265
Coefficient of variation (CV)0.30392091
Kurtosis2.691575
Mean203955.25
Median Absolute Deviation (MAD)25527
Skewness-0.21512014
Sum16520375
Variance3.842297 × 109
MonotonicityNot monotonic
2024-03-13T09:11:41.525514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
149000 1
 
1.2%
196372 1
 
1.2%
191448 1
 
1.2%
224833 1
 
1.2%
250000 1
 
1.2%
276715 1
 
1.2%
215285 1
 
1.2%
215304 1
 
1.2%
235241 1
 
1.2%
269900 1
 
1.2%
Other values (71) 71
84.5%
(Missing) 3
 
3.6%
ValueCountFrequency (%)
18449 1
1.2%
29792 1
1.2%
60640 1
1.2%
74000 1
1.2%
88320 1
1.2%
122400 1
1.2%
123000 1
1.2%
123700 1
1.2%
130845 1
1.2%
140509 1
1.2%
ValueCountFrequency (%)
425455 1
1.2%
346059 1
1.2%
317168 1
1.2%
276715 1
1.2%
274620 1
1.2%
269900 1
1.2%
268837 1
1.2%
262770 1
1.2%
256650 1
1.2%
256175 1
1.2%

Interactions

2024-03-13T09:11:39.197218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:38.786997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:38.974595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:39.264363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:38.840496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:39.035833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:39.339156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:38.904701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T09:11:39.120021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T09:11:41.606680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면리동지번댐종류시공연도사업비(천원)
연번1.0000.9220.9820.9860.1510.4330.306
읍면0.9221.0000.9980.9920.3060.2430.248
리동0.9820.9981.0000.9970.1950.8400.885
지번0.9860.9920.9971.0000.9780.0000.000
댐종류0.1510.3060.1950.9781.0000.6570.527
시공연도0.4330.2430.8400.0000.6571.0000.728
사업비(천원)0.3060.2480.8850.0000.5270.7281.000
2024-03-13T09:11:41.698242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면댐종류
읍면1.0000.141
댐종류0.1411.000
2024-03-13T09:11:42.020978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시공연도사업비(천원)읍면댐종류
연번1.0000.3160.0520.7230.061
시공연도0.3161.0000.0910.1590.460
사업비(천원)0.0520.0911.0000.1460.364
읍면0.7230.1590.1461.0000.141
댐종류0.0610.4600.3640.1411.000

Missing values

2024-03-13T09:11:39.435323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T09:11:39.529400image/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

연번시군읍면리동지번댐종류시공연도사업비(천원)
01하동군악양면등촌리943천전석199760640
12하동군악양면등촌리943천전석2003130845
23하동군악양면등촌리316임콘크리트(전석)2005229304
34하동군악양면등촌리943천콘크리트2006254457
45하동군악양면미점리808구 외전석2011224659
56하동군악양면평사리산82-2 외콘크리트(돌붙임)2013225488
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