Overview

Dataset statistics

Number of variables8
Number of observations750
Missing cells642
Missing cells (%)10.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.9 KiB
Average record size in memory68.2 B

Variable types

Numeric4
Categorical2
Text2

Dataset

Description경상남도 하동군에 설치된 스마트워터 미터기(원격검침기) 현황을 설치일자, 스마트워터미터기 명칭, 스마트워터미티거ㅣ 규격, 설치 수도관로, 수용가읍면, 수용가도로면주소, 수용가위도, 수용가경도 의 항목으로 구분하여 데이터 제공
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15110929

Alerts

순번 is highly overall correlated with 수용가위도 and 2 other fieldsHigh correlation
수용가위도 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
수용가경도 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
설치일자 is highly overall correlated with 순번 and 3 other fieldsHigh correlation
수용가읍면 is highly overall correlated with 수용가경도 and 1 other fieldsHigh correlation
스마트워터미터기 명칭 has 641 (85.5%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:41:13.967017
Analysis finished2023-12-10 22:41:15.988308
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct750
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean375.5
Minimum1
Maximum750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-11T07:41:16.048517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.45
Q1188.25
median375.5
Q3562.75
95-th percentile712.55
Maximum750
Range749
Interquartile range (IQR)374.5

Descriptive statistics

Standard deviation216.65064
Coefficient of variation (CV)0.57696575
Kurtosis-1.2
Mean375.5
Median Absolute Deviation (MAD)187.5
Skewness0
Sum281625
Variance46937.5
MonotonicityStrictly increasing
2023-12-11T07:41:16.205202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
505 1
 
0.1%
496 1
 
0.1%
497 1
 
0.1%
498 1
 
0.1%
499 1
 
0.1%
500 1
 
0.1%
501 1
 
0.1%
502 1
 
0.1%
503 1
 
0.1%
Other values (740) 740
98.7%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
750 1
0.1%
749 1
0.1%
748 1
0.1%
747 1
0.1%
746 1
0.1%
745 1
0.1%
744 1
0.1%
743 1
0.1%
742 1
0.1%
741 1
0.1%

설치일자
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2022-07-10
69 
2021-01-27
63 
2021-01-29
60 
2022-11-15
59 
2021-01-28
51 
Other values (35)
448 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique7 ?
Unique (%)0.9%

Sample

1st row2021-01-26
2nd row2021-01-26
3rd row2022-09-15
4th row2021-01-26
5th row2021-01-26

Common Values

ValueCountFrequency (%)
2022-07-10 69
 
9.2%
2021-01-27 63
 
8.4%
2021-01-29 60
 
8.0%
2022-11-15 59
 
7.9%
2021-01-28 51
 
6.8%
2022-11-24 50
 
6.7%
2022-11-21 37
 
4.9%
2022-05-25 35
 
4.7%
2021-01-26 35
 
4.7%
2022-11-14 33
 
4.4%
Other values (30) 258
34.4%

Length

2023-12-11T07:41:16.319350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-07-10 69
 
9.2%
2021-01-27 63
 
8.4%
2021-01-29 60
 
8.0%
2022-11-15 59
 
7.9%
2021-01-28 51
 
6.8%
2022-11-24 50
 
6.7%
2022-11-21 37
 
4.9%
2022-05-25 35
 
4.7%
2021-01-26 35
 
4.7%
2022-11-14 33
 
4.4%
Other values (30) 258
34.4%

스마트워터미터기 명칭
Text

MISSING 

Distinct105
Distinct (%)96.3%
Missing641
Missing (%)85.5%
Memory size6.0 KiB
2023-12-11T07:41:16.593843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.8807339
Min length3

Characters and Unicode

Total characters641
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)93.6%

Sample

1st row북방교회
2nd row북방마을회관
3rd row공동선별장
4th row녹색체험
5th row토동선별장
ValueCountFrequency (%)
이름없음 3
 
2.7%
청룡소2-a 2
 
1.8%
코코세라믹 2
 
1.8%
농업법인bsf 1
 
0.9%
두꺼비야시장 1
 
0.9%
경제사업장 1
 
0.9%
농협 1
 
0.9%
하동군산림조합 1
 
0.9%
하동영림서장 1
 
0.9%
하동우체국 1
 
0.9%
Other values (97) 97
87.4%
2023-12-11T07:41:16.991443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 38
 
5.9%
소 35
 
5.5%
1 27
 
4.2%
곡 18
 
2.8%
두 17
 
2.7%
a 15
 
2.3%
관 15
 
2.3%
동 14
 
2.2%
장 13
 
2.0%
천 12
 
1.9%
Other values (165) 437
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 489
76.3%
Decimal Number 61
 
9.5%
Dash Punctuation 38
 
5.9%
Lowercase Letter 29
 
4.5%
Close Punctuation 9
 
1.4%
Open Punctuation 9
 
1.4%
Uppercase Letter 4
 
0.6%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 35
 
7.2%
곡 18
 
3.7%
두 17
 
3.5%
관 15
 
3.1%
동 14
 
2.9%
장 13
 
2.7%
천 12
 
2.5%
덕 11
 
2.2%
청 9
 
1.8%
교 8
 
1.6%
Other values (147) 337
68.9%
Decimal Number
ValueCountFrequency (%)
1 27
44.3%
2 11
18.0%
3 8
 
13.1%
4 6
 
9.8%
5 4
 
6.6%
9 3
 
4.9%
0 2
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
F 1
25.0%
S 1
25.0%
B 1
25.0%
C 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
a 15
51.7%
b 11
37.9%
c 3
 
10.3%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 489
76.3%
Common 119
 
18.6%
Latin 33
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 35
 
7.2%
곡 18
 
3.7%
두 17
 
3.5%
관 15
 
3.1%
동 14
 
2.9%
장 13
 
2.7%
천 12
 
2.5%
덕 11
 
2.2%
청 9
 
1.8%
교 8
 
1.6%
Other values (147) 337
68.9%
Common
ValueCountFrequency (%)
- 38
31.9%
1 27
22.7%
2 11
 
9.2%
) 9
 
7.6%
( 9
 
7.6%
3 8
 
6.7%
4 6
 
5.0%
5 4
 
3.4%
9 3
 
2.5%
2
 
1.7%
Latin
ValueCountFrequency (%)
a 15
45.5%
b 11
33.3%
c 3
 
9.1%
F 1
 
3.0%
S 1
 
3.0%
B 1
 
3.0%
C 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 489
76.3%
ASCII 152
 
23.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 38
25.0%
1 27
17.8%
a 15
 
9.9%
b 11
 
7.2%
2 11
 
7.2%
) 9
 
5.9%
( 9
 
5.9%
3 8
 
5.3%
4 6
 
3.9%
5 4
 
2.6%
Other values (8) 14
 
9.2%
Hangul
ValueCountFrequency (%)
소 35
 
7.2%
곡 18
 
3.7%
두 17
 
3.5%
관 15
 
3.1%
동 14
 
2.9%
장 13
 
2.7%
천 12
 
2.5%
덕 11
 
2.2%
청 9
 
1.8%
교 8
 
1.6%
Other values (147) 337
68.9%

스마트워터미터기 규격
Real number (ℝ)

Distinct10
Distinct (%)1.3%
Missing1
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean21.615487
Minimum15
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-11T07:41:17.086938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile15
Q115
median15
Q315
95-th percentile80
Maximum300
Range285
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30.425794
Coefficient of variation (CV)1.4075923
Kurtosis34.969623
Mean21.615487
Median Absolute Deviation (MAD)0
Skewness5.5921981
Sum16190
Variance925.72896
MonotonicityNot monotonic
2023-12-11T07:41:17.165482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
15 698
93.1%
80 14
 
1.9%
150 11
 
1.5%
200 6
 
0.8%
20 5
 
0.7%
100 5
 
0.7%
50 5
 
0.7%
300 2
 
0.3%
25 2
 
0.3%
250 1
 
0.1%
(Missing) 1
 
0.1%
ValueCountFrequency (%)
15 698
93.1%
20 5
 
0.7%
25 2
 
0.3%
50 5
 
0.7%
80 14
 
1.9%
100 5
 
0.7%
150 11
 
1.5%
200 6
 
0.8%
250 1
 
0.1%
300 2
 
0.3%
ValueCountFrequency (%)
300 2
 
0.3%
250 1
 
0.1%
200 6
 
0.8%
150 11
 
1.5%
100 5
 
0.7%
80 14
 
1.9%
50 5
 
0.7%
25 2
 
0.3%
20 5
 
0.7%
15 698
93.1%

수용가읍면
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
옥종면
448 
하동읍
177 
금남면
103 
진교면
 
14
금성면
 
6

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
옥종면 448
59.7%
하동읍 177
 
23.6%
금남면 103
 
13.7%
진교면 14
 
1.9%
금성면 6
 
0.8%
적량면 2
 
0.3%

Length

2023-12-11T07:41:17.258935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:41:17.345465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
옥종면 448
59.7%
하동읍 177
 
23.6%
금남면 103
 
13.7%
진교면 14
 
1.9%
금성면 6
 
0.8%
적량면 2
 
0.3%

수용가도로명주소
Text

Distinct741
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-11T07:41:17.559679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length13.872
Min length5

Characters and Unicode

Total characters10404
Distinct characters150
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

Unique734 ?
Unique (%)97.9%

Sample

1st row고성산동학로824-6
2nd row옥수로333
3rd row한계길 138
4th row옥단로1398
5th row안계길81
ValueCountFrequency (%)
양구 99
 
5.1%
읍내리 95
 
4.9%
양구1길 57
 
2.9%
대도리 57
 
2.9%
북방우회길 54
 
2.8%
북방중앙길 35
 
1.8%
삼장길 30
 
1.5%
양구2길 23
 
1.2%
불무길 20
 
1.0%
동곡길 18
 
0.9%
Other values (986) 1448
74.8%
2023-12-11T07:41:17.896556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1227
 
11.8%
1 896
 
8.6%
길 596
 
5.7%
- 572
 
5.5%
2 558
 
5.4%
( 477
 
4.6%
) 477
 
4.6%
3 421
 
4.0%
4 352
 
3.4%
6 289
 
2.8%
Other values (140) 4539
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4009
38.5%
Decimal Number 3642
35.0%
Space Separator 1227
 
11.8%
Dash Punctuation 572
 
5.5%
Open Punctuation 477
 
4.6%
Close Punctuation 477
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 596
 
14.9%
리 288
 
7.2%
양 212
 
5.3%
구 211
 
5.3%
대 157
 
3.9%
중 143
 
3.6%
도 135
 
3.4%
로 121
 
3.0%
방 104
 
2.6%
북 104
 
2.6%
Other values (126) 1938
48.3%
Decimal Number
ValueCountFrequency (%)
1 896
24.6%
2 558
15.3%
3 421
11.6%
4 352
 
9.7%
6 289
 
7.9%
5 272
 
7.5%
7 267
 
7.3%
8 224
 
6.2%
0 187
 
5.1%
9 176
 
4.8%
Space Separator
ValueCountFrequency (%)
1227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 572
100.0%
Open Punctuation
ValueCountFrequency (%)
( 477
100.0%
Close Punctuation
ValueCountFrequency (%)
) 477
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6395
61.5%
Hangul 4009
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 596
 
14.9%
리 288
 
7.2%
양 212
 
5.3%
구 211
 
5.3%
대 157
 
3.9%
중 143
 
3.6%
도 135
 
3.4%
로 121
 
3.0%
방 104
 
2.6%
북 104
 
2.6%
Other values (126) 1938
48.3%
Common
ValueCountFrequency (%)
1227
19.2%
1 896
14.0%
- 572
8.9%
2 558
8.7%
( 477
 
7.5%
) 477
 
7.5%
3 421
 
6.6%
4 352
 
5.5%
6 289
 
4.5%
5 272
 
4.3%
Other values (4) 854
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6395
61.5%
Hangul 4009
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1227
19.2%
1 896
14.0%
- 572
8.9%
2 558
8.7%
( 477
 
7.5%
) 477
 
7.5%
3 421
 
6.6%
4 352
 
5.5%
6 289
 
4.5%
5 272
 
4.3%
Other values (4) 854
13.4%
Hangul
ValueCountFrequency (%)
길 596
 
14.9%
리 288
 
7.2%
양 212
 
5.3%
구 211
 
5.3%
대 157
 
3.9%
중 143
 
3.6%
도 135
 
3.4%
로 121
 
3.0%
방 104
 
2.6%
북 104
 
2.6%
Other values (126) 1938
48.3%

수용가위도
Real number (ℝ)

HIGH CORRELATION 

Distinct728
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.1195
Minimum34.926528
Maximum37.528585
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-11T07:41:18.007512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.926528
5-th percentile34.932142
Q135.069908
median35.161125
Q335.166548
95-th percentile35.177883
Maximum37.528585
Range2.602057
Interquartile range (IQR)0.09664

Descriptive statistics

Standard deviation0.17311255
Coefficient of variation (CV)0.0049292429
Kurtosis148.59026
Mean35.1195
Median Absolute Deviation (MAD)0.014571
Skewness10.674036
Sum26339.625
Variance0.029967954
MonotonicityNot monotonic
2023-12-11T07:41:18.127730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.93095 3
 
0.4%
37.528585 3
 
0.4%
34.931133 2
 
0.3%
35.1758 2
 
0.3%
35.166178 2
 
0.3%
35.161739 2
 
0.3%
35.163139 2
 
0.3%
35.161496 2
 
0.3%
35.070945 2
 
0.3%
35.161968 2
 
0.3%
Other values (718) 728
97.1%
ValueCountFrequency (%)
34.926528 1
 
0.1%
34.928253 1
 
0.1%
34.928375 1
 
0.1%
34.929904 1
 
0.1%
34.929935 1
 
0.1%
34.930267 1
 
0.1%
34.930744 1
 
0.1%
34.930805 1
 
0.1%
34.93082 1
 
0.1%
34.93095 3
0.4%
ValueCountFrequency (%)
37.528585 3
0.4%
35.228145 1
 
0.1%
35.227832 1
 
0.1%
35.221214 1
 
0.1%
35.221195 1
 
0.1%
35.220565 1
 
0.1%
35.203384 1
 
0.1%
35.196983 1
 
0.1%
35.196689 1
 
0.1%
35.195652 1
 
0.1%

수용가경도
Real number (ℝ)

HIGH CORRELATION 

Distinct730
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.85361
Minimum127.16815
Maximum127.93198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-11T07:41:18.462503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.16815
5-th percentile127.74604
Q1127.82962
median127.87929
Q3127.90362
95-th percentile127.93037
Maximum127.93198
Range0.763835
Interquartile range (IQR)0.0740035

Descriptive statistics

Standard deviation0.078379781
Coefficient of variation (CV)0.00061304317
Kurtosis21.53697
Mean127.85361
Median Absolute Deviation (MAD)0.041173
Skewness-3.0340238
Sum95890.205
Variance0.0061433901
MonotonicityNot monotonic
2023-12-11T07:41:18.588621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.168146 3
 
0.4%
127.746505 3
 
0.4%
127.832931 2
 
0.3%
127.83258 2
 
0.3%
127.749305 2
 
0.3%
127.888114 2
 
0.3%
127.929635 2
 
0.3%
127.748794 2
 
0.3%
127.879051 2
 
0.3%
127.831901 2
 
0.3%
Other values (720) 728
97.1%
ValueCountFrequency (%)
127.168146 3
0.4%
127.731986 1
 
0.1%
127.732032 1
 
0.1%
127.732421 1
 
0.1%
127.73265 1
 
0.1%
127.733108 1
 
0.1%
127.735812 1
 
0.1%
127.738914 1
 
0.1%
127.740791 1
 
0.1%
127.740875 1
 
0.1%
ValueCountFrequency (%)
127.931981 1
0.1%
127.931942 1
0.1%
127.931939 1
0.1%
127.9319 1
0.1%
127.931716 1
0.1%
127.93167 1
0.1%
127.93161 1
0.1%
127.931555 1
0.1%
127.93152 1
0.1%
127.931441 1
0.1%

Interactions

2023-12-11T07:41:15.363024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.363452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.697417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.031448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.461990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.444208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.778287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.110238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.547560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.529818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.868081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.189297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.631861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.608636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:14.945382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:41:15.263824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:41:18.665447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번설치일자스마트워터미터기 규격수용가읍면수용가위도수용가경도
순번1.0000.9570.3580.6890.3070.757
설치일자0.9571.0000.8040.8490.8940.995
스마트워터미터기 규격0.3580.8041.0000.4180.0000.145
수용가읍면0.6890.8490.4181.0000.2560.876
수용가위도0.3070.8940.0000.2561.0000.679
수용가경도0.7570.9950.1450.8760.6791.000
2023-12-11T07:41:18.758454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용가읍면설치일자
수용가읍면1.0000.558
설치일자0.5581.000
2023-12-11T07:41:18.822893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번스마트워터미터기 규격수용가위도수용가경도설치일자수용가읍면
순번1.000-0.008-0.519-0.5560.6830.452
스마트워터미터기 규격-0.0081.000-0.132-0.1090.4760.264
수용가위도-0.519-0.1321.0000.4260.7050.109
수용가경도-0.556-0.1090.4261.0000.8900.748
설치일자0.6830.4760.7050.8901.0000.558
수용가읍면0.4520.2640.1090.7480.5581.000

Missing values

2023-12-11T07:41:15.757019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:41:15.863507image/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.
2023-12-11T07:41:15.944616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번설치일자스마트워터미터기 명칭스마트워터미터기 규격수용가읍면수용가도로명주소수용가위도수용가경도
012021-01-26<NA>15옥종면고성산동학로824-635.168709127.903612
122021-01-26<NA>15옥종면옥수로33335.168687127.903622
232022-09-15<NA>15옥종면한계길 13835.168791127.903261
342021-01-26<NA>15옥종면옥단로139835.168917127.903011
452021-01-26<NA>15옥종면안계길8135.169296127.903107
562021-01-26<NA>15옥종면한계길 140-535.169427127.902948
672021-01-26<NA>15옥종면한계길 146-935.16938127.902014
782021-01-26<NA>15옥종면한계길 14635.169126127.902103
892021-10-06<NA>15옥종면한계길 148-635.16902127.901957
9102021-10-05북방교회15옥종면고성산동학로 72535.16489127.928131
순번설치일자스마트워터미터기 명칭스마트워터미터기 규격수용가읍면수용가도로명주소수용가위도수용가경도
7407412022-11-15맛샘골법인15옥종면동곡길 35-3435.165779127.896629
7417422022-11-25<NA>15옥종면삼장길 133-1335.162143127.905593
7427432022-11-25<NA>15옥종면삼장길 133-1235.162117127.905319
7437442022-11-15<NA>15옥종면동곡길 35-3935.166362127.896545
7447452022-11-25<NA>15옥종면북방리 984-3( 불무안길26-39)35.156486127.909507
7457462022-11-25<NA>15옥종면불무길 32-3035.163002127.91838
7467472022-11-25<NA>15옥종면불무안길 26-4335.156429127.909263
7477482022-11-23<NA>15옥종면불무길 435.161891127.923065
7487492022-11-23농업법인BSF15옥종면옥수로119-2035.176147127.894523
7497502022-11-22수용가015하동읍하동읍 읍내리 333-6 (하마길63)35.070926127.750457