Overview

Dataset statistics

Number of variables10
Number of observations81
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory86.6 B

Variable types

Text2
Categorical2
DateTime1
Numeric5

Dataset

Description전라남도 장흥군 내의 저수지현황의 데이터로 저수지의 저수량, 수혜면적, 유역면적, 소재지 등의 데이터를 제공합니다.
Author전라남도 장흥군
URLhttps://www.data.go.kr/data/15021290/fileData.do

Alerts

관리구분 has constant value ""Constant
관리자 has constant value ""Constant
수혜면적 is highly overall correlated with 총저수량High correlation
유역면적 is highly overall correlated with 총저수량High correlation
총저수량 is highly overall correlated with 수혜면적 and 2 other fieldsHigh correlation
제당높이 is highly overall correlated with 총저수량High correlation

Reproduction

Analysis started2023-12-12 12:05:24.989467
Analysis finished2023-12-12 12:05:28.233104
Duration3.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct79
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T21:05:28.473294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.1111111
Min length2

Characters and Unicode

Total characters171
Distinct characters89
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

Unique77 ?
Unique (%)95.1%

Sample

1st row석동
2nd row덕제
3rd row평화
4th row연산
5th row우목
ValueCountFrequency (%)
내동 2
 
2.5%
덕산 2
 
2.5%
효자 1
 
1.2%
정암 1
 
1.2%
죽동 1
 
1.2%
선정 1
 
1.2%
서봉 1
 
1.2%
하동 1
 
1.2%
청용 1
 
1.2%
밤제 1
 
1.2%
Other values (69) 69
85.2%
2023-12-12T21:05:29.006132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 13
 
7.6%
산 8
 
4.7%
곡 8
 
4.7%
내 5
 
2.9%
금 4
 
2.3%
상 4
 
2.3%
정 4
 
2.3%
용 4
 
2.3%
진 4
 
2.3%
촌 3
 
1.8%
Other values (79) 114
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
97.7%
Decimal Number 2
 
1.2%
Open Punctuation 1
 
0.6%
Close Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 13
 
7.8%
산 8
 
4.8%
곡 8
 
4.8%
내 5
 
3.0%
금 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
용 4
 
2.4%
진 4
 
2.4%
촌 3
 
1.8%
Other values (75) 110
65.9%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167
97.7%
Common 4
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 13
 
7.8%
산 8
 
4.8%
곡 8
 
4.8%
내 5
 
3.0%
금 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
용 4
 
2.4%
진 4
 
2.4%
촌 3
 
1.8%
Other values (75) 110
65.9%
Common
ValueCountFrequency (%)
2 1
25.0%
( 1
25.0%
) 1
25.0%
1 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167
97.7%
ASCII 4
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 13
 
7.8%
산 8
 
4.8%
곡 8
 
4.8%
내 5
 
3.0%
금 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
용 4
 
2.4%
진 4
 
2.4%
촌 3
 
1.8%
Other values (75) 110
65.9%
ASCII
ValueCountFrequency (%)
2 1
25.0%
( 1
25.0%
) 1
25.0%
1 1
25.0%

관리구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
시군
81 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시군 81
100.0%

Length

2023-12-12T21:05:29.148061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:05:29.268100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군 81
100.0%

관리자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
장흥군
81 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
장흥군 81
100.0%

Length

2023-12-12T21:05:29.401995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:05:29.531820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장흥군 81
100.0%

소재지
Text

Distinct80
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T21:05:29.831378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length20.567901
Min length18

Characters and Unicode

Total characters1666
Distinct characters92
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

Unique79 ?
Unique (%)97.5%

Sample

1st row전라남도 장흥군 장흥읍 영전리 659
2nd row전라남도 장흥군 장흥읍 덕제리 111
3rd row전라남도 장흥군 장흥읍 평화리 244
4th row전라남도 장흥군 장흥읍 연산리 357
5th row전라남도 장흥군 장흥읍 우산리 10
ValueCountFrequency (%)
전라남도 81
20.0%
장흥군 81
20.0%
장동면 14
 
3.5%
장평면 11
 
2.7%
부산면 11
 
2.7%
용산면 11
 
2.7%
운주리 8
 
2.0%
관산읍 7
 
1.7%
안양면 7
 
1.7%
유치면 6
 
1.5%
Other values (130) 168
41.5%
2023-12-12T21:05:30.278621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
324
19.4%
장 111
 
6.7%
흥 89
 
5.3%
전 83
 
5.0%
남 81
 
4.9%
도 81
 
4.9%
군 81
 
4.9%
라 81
 
4.9%
리 81
 
4.9%
면 65
 
3.9%
Other values (82) 589
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1054
63.3%
Space Separator 324
 
19.4%
Decimal Number 261
 
15.7%
Dash Punctuation 27
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 111
10.5%
흥 89
 
8.4%
전 83
 
7.9%
남 81
 
7.7%
도 81
 
7.7%
군 81
 
7.7%
라 81
 
7.7%
리 81
 
7.7%
면 65
 
6.2%
산 42
 
4.0%
Other values (70) 259
24.6%
Decimal Number
ValueCountFrequency (%)
1 47
18.0%
4 33
12.6%
2 31
11.9%
3 29
11.1%
7 29
11.1%
5 26
10.0%
6 23
8.8%
9 21
8.0%
0 12
 
4.6%
8 10
 
3.8%
Space Separator
ValueCountFrequency (%)
324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1054
63.3%
Common 612
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 111
10.5%
흥 89
 
8.4%
전 83
 
7.9%
남 81
 
7.7%
도 81
 
7.7%
군 81
 
7.7%
라 81
 
7.7%
리 81
 
7.7%
면 65
 
6.2%
산 42
 
4.0%
Other values (70) 259
24.6%
Common
ValueCountFrequency (%)
324
52.9%
1 47
 
7.7%
4 33
 
5.4%
2 31
 
5.1%
3 29
 
4.7%
7 29
 
4.7%
- 27
 
4.4%
5 26
 
4.2%
6 23
 
3.8%
9 21
 
3.4%
Other values (2) 22
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1054
63.3%
ASCII 612
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
324
52.9%
1 47
 
7.7%
4 33
 
5.4%
2 31
 
5.1%
3 29
 
4.7%
7 29
 
4.7%
- 27
 
4.4%
5 26
 
4.2%
6 23
 
3.8%
9 21
 
3.4%
Other values (2) 22
 
3.6%
Hangul
ValueCountFrequency (%)
장 111
10.5%
흥 89
 
8.4%
전 83
 
7.9%
남 81
 
7.7%
도 81
 
7.7%
군 81
 
7.7%
라 81
 
7.7%
리 81
 
7.7%
면 65
 
6.2%
산 42
 
4.0%
Other values (70) 259
24.6%

준공일자
Date

Distinct28
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size780.0 B
Minimum1923-01-01 00:00:00
Maximum2010-05-10 00:00:00
2023-12-12T21:05:30.410264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:30.523539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

수혜면적
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.309877
Minimum2
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T21:05:30.656175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.6
Q19.1
median15
Q320.5
95-th percentile32
Maximum110
Range108
Interquartile range (IQR)11.4

Descriptive statistics

Standard deviation14.605775
Coefficient of variation (CV)0.84378271
Kurtosis20.361704
Mean17.309877
Median Absolute Deviation (MAD)5.5
Skewness3.6837808
Sum1402.1
Variance213.32865
MonotonicityNot monotonic
2023-12-12T21:05:30.801969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0 3
 
3.7%
20.2 2
 
2.5%
12.9 2
 
2.5%
5.5 2
 
2.5%
8.0 2
 
2.5%
17.0 2
 
2.5%
6.0 2
 
2.5%
9.7 2
 
2.5%
30.0 2
 
2.5%
16.0 2
 
2.5%
Other values (52) 60
74.1%
ValueCountFrequency (%)
2.0 1
 
1.2%
2.8 1
 
1.2%
3.0 1
 
1.2%
3.2 1
 
1.2%
3.6 1
 
1.2%
3.7 1
 
1.2%
4.0 3
3.7%
5.5 2
2.5%
6.0 2
2.5%
6.2 1
 
1.2%
ValueCountFrequency (%)
110.0 1
1.2%
60.0 1
1.2%
50.5 1
1.2%
40.0 1
1.2%
32.0 1
1.2%
30.0 2
2.5%
28.5 1
1.2%
28.2 2
2.5%
27.2 1
1.2%
26.0 1
1.2%

유역면적
Real number (ℝ)

HIGH CORRELATION 

Distinct66
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.916296
Minimum10
Maximum550
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T21:05:30.952263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15
Q133
median50
Q395
95-th percentile185
Maximum550
Range540
Interquartile range (IQR)62

Descriptive statistics

Standard deviation84.358175
Coefficient of variation (CV)1.096753
Kurtosis16.574801
Mean76.916296
Median Absolute Deviation (MAD)29
Skewness3.6193977
Sum6230.22
Variance7116.3017
MonotonicityNot monotonic
2023-12-12T21:05:31.101934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.0 4
 
4.9%
42.0 3
 
3.7%
35.0 3
 
3.7%
50.0 2
 
2.5%
21.0 2
 
2.5%
82.0 2
 
2.5%
31.0 2
 
2.5%
38.0 2
 
2.5%
34.0 2
 
2.5%
37.0 2
 
2.5%
Other values (56) 57
70.4%
ValueCountFrequency (%)
10.0 1
 
1.2%
12.0 1
 
1.2%
13.0 1
 
1.2%
15.0 4
4.9%
17.0 1
 
1.2%
19.0 1
 
1.2%
20.0 1
 
1.2%
21.0 2
2.5%
22.0 1
 
1.2%
23.0 1
 
1.2%
ValueCountFrequency (%)
550.0 1
1.2%
463.0 1
1.2%
249.0 1
1.2%
196.0 1
1.2%
185.0 1
1.2%
167.8 1
1.2%
160.0 1
1.2%
158.0 1
1.2%
151.0 1
1.2%
137.0 1
1.2%

총저수량
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)67.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.958025
Minimum1
Maximum694
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T21:05:31.239109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q17
median16.4
Q337
95-th percentile206.3
Maximum694
Range693
Interquartile range (IQR)30

Descriptive statistics

Standard deviation96.080793
Coefficient of variation (CV)1.9625137
Kurtosis25.886784
Mean48.958025
Median Absolute Deviation (MAD)12.6
Skewness4.5080243
Sum3965.6
Variance9231.5187
MonotonicityNot monotonic
2023-12-12T21:05:31.402398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 7
 
8.6%
10.0 4
 
4.9%
7.0 4
 
4.9%
5.0 3
 
3.7%
20.0 3
 
3.7%
29.0 2
 
2.5%
9.0 2
 
2.5%
37.0 2
 
2.5%
21.0 2
 
2.5%
14.0 2
 
2.5%
Other values (45) 50
61.7%
ValueCountFrequency (%)
1.0 1
 
1.2%
2.0 2
 
2.5%
2.4 1
 
1.2%
3.0 7
8.6%
3.5 1
 
1.2%
5.0 3
3.7%
5.7 1
 
1.2%
6.0 1
 
1.2%
7.0 4
4.9%
7.5 1
 
1.2%
ValueCountFrequency (%)
694.0 1
1.2%
308.0 1
1.2%
288.0 1
1.2%
239.0 1
1.2%
206.3 1
1.2%
167.2 1
1.2%
148.0 1
1.2%
147.6 1
1.2%
135.4 1
1.2%
129.0 1
1.2%

제당높이
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)61.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4388889
Minimum1
Maximum27.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T21:05:31.872122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.4
Q15
median7
Q39.4
95-th percentile13.3
Maximum27.5
Range26.5
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation4.0643111
Coefficient of variation (CV)0.54635997
Kurtosis6.4952653
Mean7.4388889
Median Absolute Deviation (MAD)2.3
Skewness1.8158427
Sum602.55
Variance16.518625
MonotonicityNot monotonic
2023-12-12T21:05:32.010268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 8
 
9.9%
6.0 6
 
7.4%
12.0 5
 
6.2%
4.0 3
 
3.7%
4.5 3
 
3.7%
8.5 3
 
3.7%
5.0 2
 
2.5%
8.3 2
 
2.5%
4.7 2
 
2.5%
7.6 2
 
2.5%
Other values (40) 45
55.6%
ValueCountFrequency (%)
1.0 1
1.2%
1.4 1
1.2%
2.0 1
1.2%
2.3 1
1.2%
2.4 1
1.2%
2.5 1
1.2%
3.0 2
2.5%
3.2 1
1.2%
3.3 1
1.2%
3.5 1
1.2%
ValueCountFrequency (%)
27.5 1
 
1.2%
17.0 1
 
1.2%
16.7 1
 
1.2%
15.0 1
 
1.2%
13.3 1
 
1.2%
12.3 1
 
1.2%
12.0 5
6.2%
11.7 1
 
1.2%
11.5 1
 
1.2%
11.45 1
 
1.2%

제당길이
Real number (ℝ)

Distinct68
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean132.79012
Minimum18
Maximum513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T21:05:32.138505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile30
Q172
median111
Q3150
95-th percentile378
Maximum513
Range495
Interquartile range (IQR)78

Descriptive statistics

Standard deviation97.148818
Coefficient of variation (CV)0.73159672
Kurtosis3.8188041
Mean132.79012
Median Absolute Deviation (MAD)39
Skewness1.9336109
Sum10756
Variance9437.8929
MonotonicityNot monotonic
2023-12-12T21:05:32.274202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72 3
 
3.7%
64 2
 
2.5%
400 2
 
2.5%
120 2
 
2.5%
111 2
 
2.5%
83 2
 
2.5%
80 2
 
2.5%
95 2
 
2.5%
124 2
 
2.5%
115 2
 
2.5%
Other values (58) 60
74.1%
ValueCountFrequency (%)
18 1
1.2%
26 1
1.2%
28 1
1.2%
29 1
1.2%
30 1
1.2%
32 1
1.2%
47 1
1.2%
49 1
1.2%
50 1
1.2%
54 1
1.2%
ValueCountFrequency (%)
513 1
1.2%
400 2
2.5%
393 1
1.2%
378 1
1.2%
364 1
1.2%
330 1
1.2%
300 1
1.2%
212 1
1.2%
204 2
2.5%
202 1
1.2%

Interactions

2023-12-12T21:05:27.526537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:25.672958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.112702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.577964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.043781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.619495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:25.756247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.212441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.677737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.144061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.705703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:25.842693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.304796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.766637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.237055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.786995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:25.927280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.412635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.856866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.349112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.871247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.016017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.491780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:26.948219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:05:27.445039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:05:32.374019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지준공일자수혜면적유역면적총저수량제당높이제당길이
시설명1.0000.9960.9870.9930.0001.0000.9840.990
소재지0.9961.0000.9960.9871.0001.0000.9900.980
준공일자0.9870.9961.0000.9530.7360.8240.8790.587
수혜면적0.9930.9870.9531.0000.9280.7800.7730.342
유역면적0.0001.0000.7360.9281.0000.7110.7070.342
총저수량1.0001.0000.8240.7800.7111.0000.7240.506
제당높이0.9840.9900.8790.7730.7070.7241.0000.000
제당길이0.9900.9800.5870.3420.3420.5060.0001.000
2023-12-12T21:05:32.487173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수혜면적유역면적총저수량제당높이제당길이
수혜면적1.0000.4620.7190.3460.491
유역면적0.4621.0000.5240.2410.322
총저수량0.7190.5241.0000.5060.472
제당높이0.3460.2410.5061.000-0.053
제당길이0.4910.3220.472-0.0531.000

Missing values

2023-12-12T21:05:28.002733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:05:28.171086image/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

시설명관리구분관리자소재지준공일자수혜면적유역면적총저수량제당높이제당길이
0석동시군장흥군전라남도 장흥군 장흥읍 영전리 6591969-01-0111.079.029.06.062
1덕제시군장흥군전라남도 장흥군 장흥읍 덕제리 1111966-01-0119.8126.082.010.8189
2평화시군장흥군전라남도 장흥군 장흥읍 평화리 2441986-01-0128.265.0106.87.0300
3연산시군장흥군전라남도 장흥군 장흥읍 연산리 3571943-01-0123.064.829.07.0200
4우목시군장흥군전라남도 장흥군 장흥읍 우산리 101969-01-0120.537.034.57.2204
5부평시군장흥군전라남도 장흥군 관산읍 부평리 403-21941-01-0119.0123.032.36.0202
6용전시군장흥군전라남도 장흥군 관산읍 용전리 577-11951-01-0112.015.025.77.0154
7옥당시군장흥군전라남도 장흥군 관산읍 옥당리 451942-01-0113.031.010.07.0115
8우산시군장흥군전라남도 장흥군 관산읍 삼산리 18071968-01-0118.072.08.02.5400
9외약시군장흥군전라남도 장흥군 관산읍 외동리 170-11942-01-0113.738.07.06.095
시설명관리구분관리자소재지준공일자수혜면적유역면적총저수량제당높이제당길이
71효자시군장흥군전라남도 장흥군 부산면 금자리 7421963-01-013.712.07.04.0102
72사곡시군장흥군전라남도 장흥군 부산면 호계리 1061942-01-0113.791.017.05.3129
73이곡시군장흥군전라남도 장흥군 부산면 호계리 341-61945-01-0118.7118.038.08.3120
74월만시군장흥군전라남도 장흥군 부산면 호계리 195-41967-01-0115.321.07.57.550
75역기시군장흥군전라남도 장흥군 부산면 호계리 4181975-01-0150.563.081.012.0124
76진목대시군장흥군전라남도 장흥군 회진면 진목리 953-231968-01-0130.0111.03.04.0513
77진목소시군장흥군전라남도 장흥군 회진면 진목리 4471968-01-019.715.05.76.070
78회진시군장흥군전라남도 장흥군 회진면 회진리 6411970-01-012.833.02.012.030
79덕산시군장흥군전라남도 장흥군 회진면 덕산리 9601945-01-019.115.03.01.4212
80장산시군장흥군전라남도 장흥군 회진면 덕산리 9451923-01-0112.450.014.14.0140