Overview

Dataset statistics

Number of variables9
Number of observations115
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory77.1 B

Variable types

Numeric4
Categorical1
Text3
DateTime1

Dataset

Description광주광역시 광산구에 위치한 수리시설 현황 (시설명, 위치, 규모, 준공연도, 위도, 경도 등)에 대한 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3082252/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 준공연도 and 1 other fieldsHigh correlation
준공연도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:00:10.925035
Analysis finished2023-12-12 19:00:15.153273
Duration4.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58
Minimum1
Maximum115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T04:00:15.278494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.7
Q129.5
median58
Q386.5
95-th percentile109.3
Maximum115
Range114
Interquartile range (IQR)57

Descriptive statistics

Standard deviation33.341666
Coefficient of variation (CV)0.5748563
Kurtosis-1.2
Mean58
Median Absolute Deviation (MAD)29
Skewness0
Sum6670
Variance1111.6667
MonotonicityStrictly increasing
2023-12-13T04:00:15.511483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
74 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
Other values (105) 105
91.3%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
관정
54 
저수지
35 
양수장
16 
집수암거
6 
보
 
4

Length

Max length4
Median length3
Mean length2.5130435
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관정 54
47.0%
저수지 35
30.4%
양수장 16
 
13.9%
집수암거 6
 
5.2%
보 4
 
3.5%

Length

2023-12-13T04:00:15.741152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:00:15.947273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관정 54
47.0%
저수지 35
30.4%
양수장 16
 
13.9%
집수암거 6
 
5.2%
보 4
 
3.5%

시설명
Text

Distinct112
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T04:00:16.413400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9826087
Min length2

Characters and Unicode

Total characters343
Distinct characters74
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)94.8%

Sample

1st row가삼제
2nd row가야제
3rd row가정1제
4th row가정2제
5th row광산제
ValueCountFrequency (%)
금석 2
 
1.7%
등임1 2
 
1.7%
용봉1 2
 
1.7%
용동1 1
 
0.9%
왕동3 1
 
0.9%
용봉4 1
 
0.9%
고룡3 1
 
0.9%
도산2 1
 
0.9%
신창4 1
 
0.9%
신촌1 1
 
0.9%
Other values (102) 102
88.7%
2023-12-13T04:00:17.160414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 42
 
12.2%
제 35
 
10.2%
산 24
 
7.0%
2 19
 
5.5%
신 12
 
3.5%
정 11
 
3.2%
용 10
 
2.9%
3 10
 
2.9%
동 9
 
2.6%
룡 9
 
2.6%
Other values (64) 162
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
77.6%
Decimal Number 77
 
22.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 35
 
13.2%
산 24
 
9.0%
신 12
 
4.5%
정 11
 
4.1%
용 10
 
3.8%
동 9
 
3.4%
룡 9
 
3.4%
봉 9
 
3.4%
내 7
 
2.6%
등 7
 
2.6%
Other values (58) 133
50.0%
Decimal Number
ValueCountFrequency (%)
1 42
54.5%
2 19
24.7%
3 10
 
13.0%
4 4
 
5.2%
5 1
 
1.3%
6 1
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
77.6%
Common 77
 
22.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 35
 
13.2%
산 24
 
9.0%
신 12
 
4.5%
정 11
 
4.1%
용 10
 
3.8%
동 9
 
3.4%
룡 9
 
3.4%
봉 9
 
3.4%
내 7
 
2.6%
등 7
 
2.6%
Other values (58) 133
50.0%
Common
ValueCountFrequency (%)
1 42
54.5%
2 19
24.7%
3 10
 
13.0%
4 4
 
5.2%
5 1
 
1.3%
6 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
77.6%
ASCII 77
 
22.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 42
54.5%
2 19
24.7%
3 10
 
13.0%
4 4
 
5.2%
5 1
 
1.3%
6 1
 
1.3%
Hangul
ValueCountFrequency (%)
제 35
 
13.2%
산 24
 
9.0%
신 12
 
4.5%
정 11
 
4.1%
용 10
 
3.8%
동 9
 
3.4%
룡 9
 
3.4%
봉 9
 
3.4%
내 7
 
2.6%
등 7
 
2.6%
Other values (58) 133
50.0%

주소
Text

Distinct114
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T04:00:17.718437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.278261
Min length16

Characters and Unicode

Total characters2102
Distinct characters63
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

Unique113 ?
Unique (%)98.3%

Sample

1st row광주광역시 광산구 지평동 596-2
2nd row광주광역시 광산구 산정동 700-1
3rd row광주광역시 광산구 두정동 312-1
4th row광주광역시 광산구 두정동 427
5th row광주광역시 광산구 광산동 산37
ValueCountFrequency (%)
광주광역시 115
25.0%
광산구 115
25.0%
등임동 8
 
1.7%
광산동 7
 
1.5%
신룡동 6
 
1.3%
용봉동 6
 
1.3%
덕림동 5
 
1.1%
대산동 5
 
1.1%
임곡동 4
 
0.9%
본덕동 4
 
0.9%
Other values (148) 185
40.2%
2023-12-13T04:00:18.509034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 352
16.7%
345
16.4%
산 155
 
7.4%
동 118
 
5.6%
역 115
 
5.5%
시 115
 
5.5%
구 115
 
5.5%
주 115
 
5.5%
1 78
 
3.7%
- 76
 
3.6%
Other values (53) 518
24.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1264
60.1%
Decimal Number 417
 
19.8%
Space Separator 345
 
16.4%
Dash Punctuation 76
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 352
27.8%
산 155
12.3%
동 118
 
9.3%
역 115
 
9.1%
시 115
 
9.1%
구 115
 
9.1%
주 115
 
9.1%
신 13
 
1.0%
임 12
 
0.9%
룡 10
 
0.8%
Other values (41) 144
11.4%
Decimal Number
ValueCountFrequency (%)
1 78
18.7%
2 63
15.1%
3 51
12.2%
5 42
10.1%
6 37
8.9%
4 34
8.2%
7 31
 
7.4%
9 28
 
6.7%
0 27
 
6.5%
8 26
 
6.2%
Space Separator
ValueCountFrequency (%)
345
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1264
60.1%
Common 838
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 352
27.8%
산 155
12.3%
동 118
 
9.3%
역 115
 
9.1%
시 115
 
9.1%
구 115
 
9.1%
주 115
 
9.1%
신 13
 
1.0%
임 12
 
0.9%
룡 10
 
0.8%
Other values (41) 144
11.4%
Common
ValueCountFrequency (%)
345
41.2%
1 78
 
9.3%
- 76
 
9.1%
2 63
 
7.5%
3 51
 
6.1%
5 42
 
5.0%
6 37
 
4.4%
4 34
 
4.1%
7 31
 
3.7%
9 28
 
3.3%
Other values (2) 53
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1264
60.1%
ASCII 838
39.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 352
27.8%
산 155
12.3%
동 118
 
9.3%
역 115
 
9.1%
시 115
 
9.1%
구 115
 
9.1%
주 115
 
9.1%
신 13
 
1.0%
임 12
 
0.9%
룡 10
 
0.8%
Other values (41) 144
11.4%
ASCII
ValueCountFrequency (%)
345
41.2%
1 78
 
9.3%
- 76
 
9.1%
2 63
 
7.5%
3 51
 
6.1%
5 42
 
5.0%
6 37
 
4.4%
4 34
 
4.1%
7 31
 
3.7%
9 28
 
3.3%
Other values (2) 53
 
6.3%

규모
Text

Distinct57
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T04:00:18.898989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.2434783
Min length2

Characters and Unicode

Total characters833
Distinct characters20
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)42.6%

Sample

1st rowL=77m H=9.3m
2nd rowL=217m H=4.8m
3rd rowL=108m H=4.3m
4th rowL=32m H=6.3m
5th rowL=67m H=5.8m
ValueCountFrequency (%)
7.5hp 19
 
12.3%
3.0hp 11
 
7.1%
10hp 9
 
5.8%
50hp 9
 
5.8%
5.0hp 8
 
5.2%
5.5hp 5
 
3.2%
23hp 3
 
1.9%
h=4m 3
 
1.9%
l=80m 2
 
1.3%
h=6.3m 2
 
1.3%
Other values (74) 83
53.9%
2023-12-13T04:00:19.488412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 78
 
9.4%
m 78
 
9.4%
h 75
 
9.0%
p 75
 
9.0%
. 75
 
9.0%
5 73
 
8.8%
0 67
 
8.0%
H 39
 
4.7%
39
 
4.7%
L 39
 
4.7%
Other values (10) 195
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 333
40.0%
Lowercase Letter 228
27.4%
Math Symbol 78
 
9.4%
Uppercase Letter 78
 
9.4%
Other Punctuation 75
 
9.0%
Space Separator 39
 
4.7%
Other Letter 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 73
21.9%
0 67
20.1%
1 38
11.4%
7 37
11.1%
3 31
9.3%
2 22
 
6.6%
6 22
 
6.6%
4 19
 
5.7%
8 16
 
4.8%
9 8
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
m 78
34.2%
h 75
32.9%
p 75
32.9%
Uppercase Letter
ValueCountFrequency (%)
H 39
50.0%
L 39
50.0%
Other Letter
ValueCountFrequency (%)
소 1
50.0%
형 1
50.0%
Math Symbol
ValueCountFrequency (%)
= 78
100.0%
Other Punctuation
ValueCountFrequency (%)
. 75
100.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 525
63.0%
Latin 306
36.7%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
= 78
14.9%
. 75
14.3%
5 73
13.9%
0 67
12.8%
39
7.4%
1 38
7.2%
7 37
7.0%
3 31
 
5.9%
2 22
 
4.2%
6 22
 
4.2%
Other values (3) 43
8.2%
Latin
ValueCountFrequency (%)
m 78
25.5%
h 75
24.5%
p 75
24.5%
H 39
12.7%
L 39
12.7%
Hangul
ValueCountFrequency (%)
소 1
50.0%
형 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 831
99.8%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 78
9.4%
m 78
9.4%
h 75
 
9.0%
p 75
 
9.0%
. 75
 
9.0%
5 73
 
8.8%
0 67
 
8.1%
H 39
 
4.7%
39
 
4.7%
L 39
 
4.7%
Other values (8) 193
23.2%
Hangul
ValueCountFrequency (%)
소 1
50.0%
형 1
50.0%

준공연도
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1978.7565
Minimum1945
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T04:00:19.715813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1945
5-th percentile1945
Q11951
median1979
Q32001
95-th percentile2016.6
Maximum2019
Range74
Interquartile range (IQR)50

Descriptive statistics

Standard deviation25.031766
Coefficient of variation (CV)0.012650251
Kurtosis-1.3667286
Mean1978.7565
Median Absolute Deviation (MAD)22
Skewness-0.072075109
Sum227557
Variance626.58932
MonotonicityNot monotonic
2023-12-13T04:00:19.937910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1945 27
23.5%
2001 15
13.0%
1978 8
 
7.0%
1968 7
 
6.1%
1995 7
 
6.1%
2009 5
 
4.3%
1960 4
 
3.5%
2019 4
 
3.5%
2011 3
 
2.6%
1994 3
 
2.6%
Other values (22) 32
27.8%
ValueCountFrequency (%)
1945 27
23.5%
1948 2
 
1.7%
1954 1
 
0.9%
1958 2
 
1.7%
1959 1
 
0.9%
1960 4
 
3.5%
1967 1
 
0.9%
1968 7
 
6.1%
1969 2
 
1.7%
1977 1
 
0.9%
ValueCountFrequency (%)
2019 4
 
3.5%
2018 2
 
1.7%
2016 1
 
0.9%
2015 1
 
0.9%
2014 1
 
0.9%
2012 1
 
0.9%
2011 3
 
2.6%
2009 5
 
4.3%
2007 1
 
0.9%
2001 15
13.0%

위도
Real number (ℝ)

Distinct114
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.167633
Minimum35.073985
Maximum35.253031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T04:00:20.194545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.073985
5-th percentile35.079713
Q135.133809
median35.179468
Q335.196245
95-th percentile35.228563
Maximum35.253031
Range0.17904594
Interquartile range (IQR)0.062435896

Descriptive statistics

Standard deviation0.045239403
Coefficient of variation (CV)0.0012863932
Kurtosis-0.62293116
Mean35.167633
Median Absolute Deviation (MAD)0.031689365
Skewness-0.40395892
Sum4044.2778
Variance0.0020466036
MonotonicityNot monotonic
2023-12-13T04:00:20.460675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.1891069468181 2
 
1.7%
35.1512731771811 1
 
0.9%
35.1669230548331 1
 
0.9%
35.1962927735692 1
 
0.9%
35.102986229545 1
 
0.9%
35.0787520089558 1
 
0.9%
35.2078297411958 1
 
0.9%
35.1262613897305 1
 
0.9%
35.1890811260487 1
 
0.9%
35.1188035620183 1
 
0.9%
Other values (104) 104
90.4%
ValueCountFrequency (%)
35.0739849111805 1
0.9%
35.0742588885343 1
0.9%
35.0773861105062 1
0.9%
35.0773964578465 1
0.9%
35.0784564572787 1
0.9%
35.0787520089558 1
0.9%
35.08012485185 1
0.9%
35.0819517714306 1
0.9%
35.0866932192603 1
0.9%
35.0867609020131 1
0.9%
ValueCountFrequency (%)
35.2530308467467 1
0.9%
35.2490543837973 1
0.9%
35.2434439102308 1
0.9%
35.2391162686852 1
0.9%
35.2387845676305 1
0.9%
35.2291415256763 1
0.9%
35.2283150605135 1
0.9%
35.2280099173465 1
0.9%
35.2277408081839 1
0.9%
35.2256161951178 1
0.9%

경도
Real number (ℝ)

Distinct114
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.74865
Minimum126.6552
Maximum126.8548
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T04:00:20.855670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.6552
5-th percentile126.66579
Q1126.71882
median126.75753
Q3126.77472
95-th percentile126.83844
Maximum126.8548
Range0.19959268
Interquartile range (IQR)0.055898636

Descriptive statistics

Standard deviation0.048268894
Coefficient of variation (CV)0.00038082373
Kurtosis-0.19319527
Mean126.74865
Median Absolute Deviation (MAD)0.021534514
Skewness-0.090423025
Sum14576.095
Variance0.0023298862
MonotonicityNot monotonic
2023-12-13T04:00:21.129742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.675177975416 2
 
1.7%
126.717235866462 1
 
0.9%
126.666226544774 1
 
0.9%
126.709820915887 1
 
0.9%
126.758479791973 1
 
0.9%
126.767440837307 1
 
0.9%
126.768696881656 1
 
0.9%
126.789754641474 1
 
0.9%
126.849234137529 1
 
0.9%
126.813936610242 1
 
0.9%
Other values (104) 104
90.4%
ValueCountFrequency (%)
126.655204793445 1
0.9%
126.657603856226 1
0.9%
126.659012238858 1
0.9%
126.660317341691 1
0.9%
126.660990068256 1
0.9%
126.664765469167 1
0.9%
126.666226544774 1
0.9%
126.670296435977 1
0.9%
126.672480649701 1
0.9%
126.672919461971 1
0.9%
ValueCountFrequency (%)
126.854797472076 1
0.9%
126.854690296414 1
0.9%
126.853585769208 1
0.9%
126.853201732144 1
0.9%
126.849234137529 1
0.9%
126.841474163262 1
0.9%
126.837141759768 1
0.9%
126.832381749304 1
0.9%
126.818426105613 1
0.9%
126.813936610242 1
0.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T04:00:21.346383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:21.510690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T04:00:13.928100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:11.454525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:12.159239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:12.785997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:14.109992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:11.626237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:12.317461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:13.364623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:14.390424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:11.794208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:12.472125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:13.552540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:14.589004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:11.980725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:12.633829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:00:13.736560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:00:21.635156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분규모준공연도위도경도
연번1.0000.9670.8780.9010.4790.437
구분0.9671.0001.0000.8940.6270.494
규모0.8781.0001.0000.9320.2900.339
준공연도0.9010.8940.9321.0000.2870.513
위도0.4790.6270.2900.2871.0000.563
경도0.4370.4940.3390.5130.5631.000
2023-12-13T04:00:21.800449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번준공연도위도경도구분
연번1.0000.917-0.2220.0580.730
준공연도0.9171.000-0.2890.0640.586
위도-0.222-0.2891.0000.0750.301
경도0.0580.0640.0751.0000.220
구분0.7300.5860.3010.2201.000

Missing values

2023-12-13T04:00:14.849806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:00:15.067037image/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

연번구분시설명주소규모준공연도위도경도데이터기준일자
01저수지가삼제광주광역시 광산구 지평동 596-2L=77m H=9.3m196835.151273126.7172362022-12-31
12저수지가야제광주광역시 광산구 산정동 700-1L=217m H=4.8m194535.175058126.790452022-12-31
23저수지가정1제광주광역시 광산구 두정동 312-1L=108m H=4.3m194535.222105126.7607422022-12-31
34저수지가정2제광주광역시 광산구 두정동 427L=32m H=6.3m196835.227741126.7627852022-12-31
45저수지광산제광주광역시 광산구 광산동 산37L=67m H=5.8m194535.253031126.7561692022-12-31
56저수지내등제광주광역시 광산구 등임동 260L=145m H=6.3m194535.181364126.7635682022-12-31
67저수지내산1제광주광역시 광산구 내산동 662-1L=69m H=8.1m194535.124366126.660992022-12-31
78저수지내산2제광주광역시 광산구 내산동 산127L=90m H=10m194535.116284126.6590122022-12-31
89저수지두정제광주광역시 광산구 신룡동 405L=156m H=5.6m194535.218358126.7704122022-12-31
910저수지박호제광주광역시 광산구 박호동 43-1L=83m H=4m194535.178066126.7577752022-12-31
연번구분시설명주소규모준공연도위도경도데이터기준일자
105106관정선동2광주광역시 광산구 선동 713-65.0hp201135.196197126.7497632022-12-31
106107관정신룡3광주광역시 광산구 신룡동 1915.0hp201135.229142126.7752212022-12-31
107108관정신가3광주광역시 광산구 신가동 224-2소형201235.177309126.8323822022-12-31
108109관정산정3광주광역시 광산구 산정동 2195.0hp201535.169749126.7954462022-12-31
109110관정내산2광주광역시 광산구 내산동 산1623.0hp201835.122752126.6552052022-12-31
110111관정덕림1광주광역시 광산구 덕림동 9973.0hp201835.190962126.6576042022-12-31
111112관정신룡4광주광역시 광산구 신룡동 251-153.0hp201935.225616126.7742622022-12-31
112113관정용봉6광주광역시 광산구 용봉동 376-63.0hp201935.074259126.7742292022-12-31
113114관정용동1광주광역시 광산구 용동 521-13.0hp201935.135873126.7456932022-12-31
114115관정본덕3광주광역시 광산구 본덕동 9671.0hp201935.086693126.7882892022-12-31