Overview

Dataset statistics

Number of variables10
Number of observations39
Missing cells80
Missing cells (%)20.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory86.4 B

Variable types

Categorical1
Text3
Numeric3
Boolean3

Dataset

Description경기도 안산시 근방의 자동기상관측장비(AWS)의 설치 현황으로 시군명,지점명,소재지도로명주소,소재지지번주소,소재지우편번호,위도(WGS84),경도(WGS84),기상청 관리 장비,경기도 관리 장비,시군 관리 장비 등의 목록을 제공합니다.
Author경기도 안산시
URLhttps://www.data.go.kr/data/15091611/fileData.do

Alerts

기상청 관리 장비 has constant value ""Constant
경기도 관리 장비 has constant value ""Constant
시군 관리 장비 has constant value ""Constant
소재지우편번호 is highly overall correlated with 위도(WGS84) and 1 other fieldsHigh correlation
위도(WGS84) is highly overall correlated with 소재지우편번호High correlation
시군명 is highly overall correlated with 소재지우편번호High correlation
소재지도로명주소 has 1 (2.6%) missing valuesMissing
소재지우편번호 has 1 (2.6%) missing valuesMissing
기상청 관리 장비 has 26 (66.7%) missing valuesMissing
경기도 관리 장비 has 20 (51.3%) missing valuesMissing
시군 관리 장비 has 32 (82.1%) missing valuesMissing
지점명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도(WGS84) has unique valuesUnique
경도(WGS84) has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:26:20.866240
Analysis finished2023-12-11 23:26:22.426934
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size444.0 B
화성시
8 
평택시
7 
용인시
6 
광명시
3 
안산시
3 
Other values (7)
12 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)5.1%

Sample

1st row과천시
2nd row광명시
3rd row광명시
4th row광명시
5th row군포시

Common Values

ValueCountFrequency (%)
화성시 8
20.5%
평택시 7
17.9%
용인시 6
15.4%
광명시 3
 
7.7%
안산시 3
 
7.7%
군포시 2
 
5.1%
수원시 2
 
5.1%
안양시 2
 
5.1%
오산시 2
 
5.1%
의왕시 2
 
5.1%
Other values (2) 2
 
5.1%

Length

2023-12-12T08:26:22.489207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 8
20.5%
평택시 7
17.9%
용인시 6
15.4%
광명시 3
 
7.7%
안산시 3
 
7.7%
군포시 2
 
5.1%
수원시 2
 
5.1%
안양시 2
 
5.1%
오산시 2
 
5.1%
의왕시 2
 
5.1%
Other values (2) 2
 
5.1%

지점명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-12T08:26:22.647677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.5897436
Min length2

Characters and Unicode

Total characters101
Distinct characters63
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row과천
2nd row광명
3rd row소하
4th row학온동
5th row군포
ValueCountFrequency (%)
3
 
7.1%
과천 1
 
2.4%
포승 1
 
2.4%
오전동 1
 
2.4%
의왕 1
 
2.4%
고덕면 1
 
2.4%
서탄면 1
 
2.4%
송탄 1
 
2.4%
청북 1
 
2.4%
평택 1
 
2.4%
Other values (30) 30
71.4%
2023-12-12T08:26:23.072632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 6
 
5.9%
산 4
 
4.0%
3
 
3.0%
안 3
 
3.0%
리 3
 
3.0%
수 3
 
3.0%
* 3
 
3.0%
면 3
 
3.0%
도 3
 
3.0%
전 2
 
2.0%
Other values (53) 68
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95
94.1%
Space Separator 3
 
3.0%
Other Punctuation 3
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6
 
6.3%
산 4
 
4.2%
안 3
 
3.2%
리 3
 
3.2%
수 3
 
3.2%
면 3
 
3.2%
도 3
 
3.2%
전 2
 
2.1%
오 2
 
2.1%
용 2
 
2.1%
Other values (51) 64
67.4%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
* 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95
94.1%
Common 6
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6
 
6.3%
산 4
 
4.2%
안 3
 
3.2%
리 3
 
3.2%
수 3
 
3.2%
면 3
 
3.2%
도 3
 
3.2%
전 2
 
2.1%
오 2
 
2.1%
용 2
 
2.1%
Other values (51) 64
67.4%
Common
ValueCountFrequency (%)
3
50.0%
* 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95
94.1%
ASCII 6
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 6
 
6.3%
산 4
 
4.2%
안 3
 
3.2%
리 3
 
3.2%
수 3
 
3.2%
면 3
 
3.2%
도 3
 
3.2%
전 2
 
2.1%
오 2
 
2.1%
용 2
 
2.1%
Other values (51) 64
67.4%
ASCII
ValueCountFrequency (%)
3
50.0%
* 3
50.0%

소재지도로명주소
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Memory size444.0 B
2023-12-12T08:26:23.346512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length19.631579
Min length13

Characters and Unicode

Total characters746
Distinct characters102
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

Unique38 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 상하벌로 110
2nd row경기도 광명시 철산로 1
3rd row경기도 광명시 기아로 169-3
4th row경기도 광명시 도고내로 48
5th row경기도 군포시 번영로550번길 6
ValueCountFrequency (%)
경기도 38
 
21.1%
화성시 7
 
3.9%
평택시 7
 
3.9%
용인시 6
 
3.3%
처인구 5
 
2.8%
광명시 3
 
1.7%
안산시 3
 
1.7%
단원구 2
 
1.1%
안양시 2
 
1.1%
서신면 2
 
1.1%
Other values (99) 105
58.3%
2023-12-12T08:26:23.757996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
19.0%
기 43
 
5.8%
경 40
 
5.4%
도 40
 
5.4%
시 39
 
5.2%
1 32
 
4.3%
로 31
 
4.2%
2 26
 
3.5%
3 20
 
2.7%
길 16
 
2.1%
Other values (92) 317
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 457
61.3%
Space Separator 142
 
19.0%
Decimal Number 136
 
18.2%
Dash Punctuation 11
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 43
 
9.4%
경 40
 
8.8%
도 40
 
8.8%
시 39
 
8.5%
로 31
 
6.8%
길 16
 
3.5%
구 13
 
2.8%
인 13
 
2.8%
번 10
 
2.2%
평 10
 
2.2%
Other values (80) 202
44.2%
Decimal Number
ValueCountFrequency (%)
1 32
23.5%
2 26
19.1%
3 20
14.7%
5 13
9.6%
0 9
 
6.6%
6 9
 
6.6%
9 8
 
5.9%
4 7
 
5.1%
8 6
 
4.4%
7 6
 
4.4%
Space Separator
ValueCountFrequency (%)
142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 457
61.3%
Common 289
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 43
 
9.4%
경 40
 
8.8%
도 40
 
8.8%
시 39
 
8.5%
로 31
 
6.8%
길 16
 
3.5%
구 13
 
2.8%
인 13
 
2.8%
번 10
 
2.2%
평 10
 
2.2%
Other values (80) 202
44.2%
Common
ValueCountFrequency (%)
142
49.1%
1 32
 
11.1%
2 26
 
9.0%
3 20
 
6.9%
5 13
 
4.5%
- 11
 
3.8%
0 9
 
3.1%
6 9
 
3.1%
9 8
 
2.8%
4 7
 
2.4%
Other values (2) 12
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 457
61.3%
ASCII 289
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
49.1%
1 32
 
11.1%
2 26
 
9.0%
3 20
 
6.9%
5 13
 
4.5%
- 11
 
3.8%
0 9
 
3.1%
6 9
 
3.1%
9 8
 
2.8%
4 7
 
2.4%
Other values (2) 12
 
4.2%
Hangul
ValueCountFrequency (%)
기 43
 
9.4%
경 40
 
8.8%
도 40
 
8.8%
시 39
 
8.5%
로 31
 
6.8%
길 16
 
3.5%
구 13
 
2.8%
인 13
 
2.8%
번 10
 
2.2%
평 10
 
2.2%
Other values (80) 202
44.2%

소재지지번주소
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-12T08:26:24.054600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length21.461538
Min length17

Characters and Unicode

Total characters837
Distinct characters111
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

Unique39 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 과천동 758번지
2nd row경기도 광명시 철산동 260번지
3rd row경기도 광명시 소하동 637-3번지
4th row경기도 광명시 가학동 101번지
5th row경기도 군포시 금정동 849-1번지 무궁화아파트
ValueCountFrequency (%)
경기도 39
 
20.9%
화성시 8
 
4.3%
평택시 7
 
3.7%
용인시 6
 
3.2%
처인구 5
 
2.7%
서신면 3
 
1.6%
광명시 3
 
1.6%
안산시 3
 
1.6%
안양시 2
 
1.1%
군포시 2
 
1.1%
Other values (104) 109
58.3%
2023-12-12T08:26:24.531178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
17.7%
도 40
 
4.8%
시 40
 
4.8%
기 40
 
4.8%
경 39
 
4.7%
번 37
 
4.4%
지 37
 
4.4%
1 29
 
3.5%
동 25
 
3.0%
- 22
 
2.6%
Other values (101) 380
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 520
62.1%
Space Separator 148
 
17.7%
Decimal Number 147
 
17.6%
Dash Punctuation 22
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 40
 
7.7%
시 40
 
7.7%
기 40
 
7.7%
경 39
 
7.5%
번 37
 
7.1%
지 37
 
7.1%
동 25
 
4.8%
리 16
 
3.1%
구 14
 
2.7%
인 12
 
2.3%
Other values (89) 220
42.3%
Decimal Number
ValueCountFrequency (%)
1 29
19.7%
4 20
13.6%
3 19
12.9%
6 15
10.2%
0 13
8.8%
9 12
8.2%
5 11
 
7.5%
2 10
 
6.8%
7 9
 
6.1%
8 9
 
6.1%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 520
62.1%
Common 317
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 40
 
7.7%
시 40
 
7.7%
기 40
 
7.7%
경 39
 
7.5%
번 37
 
7.1%
지 37
 
7.1%
동 25
 
4.8%
리 16
 
3.1%
구 14
 
2.7%
인 12
 
2.3%
Other values (89) 220
42.3%
Common
ValueCountFrequency (%)
148
46.7%
1 29
 
9.1%
- 22
 
6.9%
4 20
 
6.3%
3 19
 
6.0%
6 15
 
4.7%
0 13
 
4.1%
9 12
 
3.8%
5 11
 
3.5%
2 10
 
3.2%
Other values (2) 18
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 520
62.1%
ASCII 317
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
46.7%
1 29
 
9.1%
- 22
 
6.9%
4 20
 
6.3%
3 19
 
6.0%
6 15
 
4.7%
0 13
 
4.1%
9 12
 
3.8%
5 11
 
3.5%
2 10
 
3.2%
Other values (2) 18
 
5.7%
Hangul
ValueCountFrequency (%)
도 40
 
7.7%
시 40
 
7.7%
기 40
 
7.7%
경 39
 
7.5%
번 37
 
7.1%
지 37
 
7.1%
동 25
 
4.8%
리 16
 
3.1%
구 14
 
2.7%
인 12
 
2.3%
Other values (89) 220
42.3%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct38
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean16754.842
Minimum13817
Maximum18598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T08:26:24.663813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13817
5-th percentile14052.6
Q115688.5
median17090
Q317951.25
95-th percentile18556.9
Maximum18598
Range4781
Interquartile range (IQR)2262.75

Descriptive statistics

Standard deviation1538.2199
Coefficient of variation (CV)0.091807485
Kurtosis-0.95522467
Mean16754.842
Median Absolute Deviation (MAD)1216.5
Skewness-0.5430384
Sum636684
Variance2366120.5
MonotonicityNot monotonic
2023-12-12T08:26:24.782619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
13817 1
 
2.6%
17946 1
 
2.6%
16077 1
 
2.6%
17770 1
 
2.6%
17704 1
 
2.6%
17730 1
 
2.6%
17793 1
 
2.6%
17903 1
 
2.6%
17953 1
 
2.6%
18556 1
 
2.6%
Other values (28) 28
71.8%
ValueCountFrequency (%)
13817 1
2.6%
13971 1
2.6%
14067 1
2.6%
14235 1
2.6%
14322 1
2.6%
14341 1
2.6%
14957 1
2.6%
15345 1
2.6%
15634 1
2.6%
15645 1
2.6%
ValueCountFrequency (%)
18598 1
2.6%
18562 1
2.6%
18556 1
2.6%
18555 1
2.6%
18554 1
2.6%
18549 1
2.6%
18411 1
2.6%
18269 1
2.6%
18137 1
2.6%
17953 1
2.6%

위도(WGS84)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.225871
Minimum36.9672
Maximum37.475778
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T08:26:24.903788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.9672
5-th percentile36.987369
Q137.12428
median37.214972
Q337.348361
95-th percentile37.440028
Maximum37.475778
Range0.50857778
Interquartile range (IQR)0.22408111

Descriptive statistics

Standard deviation0.13951785
Coefficient of variation (CV)0.0037478734
Kurtosis-0.91856457
Mean37.225871
Median Absolute Deviation (MAD)0.10918222
Skewness-0.0095767629
Sum1451.809
Variance0.019465231
MonotonicityNot monotonic
2023-12-12T08:26:25.033438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
37.44028 1
 
2.6%
37.47577778 1
 
2.6%
37.355 1
 
2.6%
37.34172222 1
 
2.6%
37.0481 1
 
2.6%
37.1136 1
 
2.6%
37.06644167 1
 
2.6%
37.0467 1
 
2.6%
36.98769 1
 
2.6%
36.98447778 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
36.9672 1
2.6%
36.98447778 1
2.6%
36.98769 1
2.6%
37.0467 1
2.6%
37.0481 1
2.6%
37.06644167 1
2.6%
37.08453 1
2.6%
37.10579 1
2.6%
37.1136 1
2.6%
37.1189 1
2.6%
ValueCountFrequency (%)
37.47577778 1
2.6%
37.44028 1
2.6%
37.44 1
2.6%
37.4217 1
2.6%
37.4089 1
2.6%
37.4061 1
2.6%
37.39158333 1
2.6%
37.3642 1
2.6%
37.35872222 1
2.6%
37.355 1
2.6%

경도(WGS84)
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94845
Minimum126.5787
Maximum127.36632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-12T08:26:25.177635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5787
5-th percentile126.65024
Q1126.84598
median126.95892
Q3127.04325
95-th percentile127.2246
Maximum127.36632
Range0.78762
Interquartile range (IQR)0.19726945

Descriptive statistics

Standard deviation0.17369508
Coefficient of variation (CV)0.0013682332
Kurtosis0.11716035
Mean126.94845
Median Absolute Deviation (MAD)0.1054278
Skewness0.052724523
Sum4950.9894
Variance0.03016998
MonotonicityNot monotonic
2023-12-12T08:26:25.587370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
127.00249 1
 
2.6%
126.8664722 1
 
2.6%
126.9753 1
 
2.6%
126.9709444 1
 
2.6%
127.0183 1
 
2.6%
127.0364 1
 
2.6%
127.0648972 1
 
2.6%
126.9706 1
 
2.6%
127.10879 1
 
2.6%
126.8534889 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
126.5787 1
2.6%
126.6128 1
2.6%
126.6544 1
2.6%
126.7109167 1
2.6%
126.7411667 1
2.6%
126.77389 1
2.6%
126.7844 1
2.6%
126.82094 1
2.6%
126.8211944 1
2.6%
126.83848 1
2.6%
ValueCountFrequency (%)
127.36632 1
2.6%
127.25 1
2.6%
127.22178 1
2.6%
127.1892778 1
2.6%
127.18765 1
2.6%
127.1164 1
2.6%
127.10879 1
2.6%
127.0657778 1
2.6%
127.0648972 1
2.6%
127.04873 1
2.6%

기상청 관리 장비
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)7.7%
Missing26
Missing (%)66.7%
Memory size210.0 B
True
13 
(Missing)
26 
ValueCountFrequency (%)
True 13
33.3%
(Missing) 26
66.7%
2023-12-12T08:26:25.769993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경기도 관리 장비
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)5.3%
Missing20
Missing (%)51.3%
Memory size210.0 B
True
19 
(Missing)
20 
ValueCountFrequency (%)
True 19
48.7%
(Missing) 20
51.3%
2023-12-12T08:26:25.865476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시군 관리 장비
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing32
Missing (%)82.1%
Memory size210.0 B
True
7 
(Missing)
32 
ValueCountFrequency (%)
True 7
 
17.9%
(Missing) 32
82.1%
2023-12-12T08:26:25.949525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T08:26:21.805979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.260660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.530634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.892038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.338192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.618666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.977530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.439137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:26:21.701951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:26:26.010737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명지점명소재지도로명주소소재지지번주소소재지우편번호위도(WGS84)경도(WGS84)
시군명1.0001.0001.0001.0000.9700.7970.390
지점명1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.9701.0001.0001.0001.0000.8960.835
위도(WGS84)0.7971.0001.0001.0000.8961.0000.000
경도(WGS84)0.3901.0001.0001.0000.8350.0001.000
2023-12-12T08:26:26.132042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호위도(WGS84)경도(WGS84)시군명
소재지우편번호1.000-0.814-0.0520.842
위도(WGS84)-0.8141.000-0.1820.470
경도(WGS84)-0.052-0.1821.0000.138
시군명0.8420.4700.1381.000

Missing values

2023-12-12T08:26:22.092612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:26:22.228758image/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.
2023-12-12T08:26:22.359010image/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

시군명지점명소재지도로명주소소재지지번주소소재지우편번호위도(WGS84)경도(WGS84)기상청 관리 장비경기도 관리 장비시군 관리 장비
0과천시과천경기도 과천시 상하벌로 110경기도 과천시 과천동 758번지1381737.44028127.00249Y<NA><NA>
1광명시광명경기도 광명시 철산로 1경기도 광명시 철산동 260번지1423537.475778126.866472<NA>Y<NA>
2광명시소하경기도 광명시 기아로 169-3경기도 광명시 소하동 637-3번지1432237.44126.898333<NA>Y<NA>
3광명시학온동경기도 광명시 도고내로 48경기도 광명시 가학동 101번지1434137.4217126.8575<NA><NA>Y
4군포시군포경기도 군포시 번영로550번길 6경기도 군포시 금정동 849-1번지 무궁화아파트1583637.358722126.937472<NA>Y<NA>
5군포시수리산길경기도 군포시 수리산로 153경기도 군포시 산본동 1149-6번지1581937.3642126.9169<NA>Y<NA>
6수원시경기경기도 수원시 팔달구 향교로 93경기도 수원시 팔달구 매산로3가 13번지1645737.271833127.011833<NA>Y<NA>
7수원시수원경기도 수원시 권선구 권선로 276경기도 수원시 권선구 고색동 894-93번지1662337.25746126.983Y<NA><NA>
8시흥시신현동경기도 시흥시 신현로 46경기도 시흥시 포동 20-33번지1495737.4061126.7844<NA>Y<NA>
9안산시고잔경기도 안산시 단원구 인현중앙길 30경기도 안산시 단원구 고잔동 665번지1534537.324306126.821194<NA>Y<NA>
시군명지점명소재지도로명주소소재지지번주소소재지우편번호위도(WGS84)경도(WGS84)기상청 관리 장비경기도 관리 장비시군 관리 장비
29평택시포승경기도 평택시 포승읍 평택항로268번길 147경기도 평택시 포승읍 도곡리 1217번지1795336.984478126.853489<NA>Y<NA>
30평택시현덕면경기도 평택시 현덕면 인광길 84경기도 평택시 현덕면 인광리 402-12번지1794636.9672126.9214<NA><NA>Y
31화성시도리도<NA>경기도 화성시 서신면 백미리 산 1441855637.1189126.6128Y<NA><NA>
32화성시서신경기도 화성시 서신면 전디길 29경기도 화성시 서신면 매화리 464번지1855537.16375126.710917<NA>Y<NA>
33화성시송산경기도 화성시 송산면 봉가북길 18경기도 화성시 송산면 봉가리 133-1번지1854937.214972126.741167<NA>Y<NA>
34화성시운평경기도 화성시 우정읍 평밭길 50-11경기도 화성시 우정읍 운평리 931번지1856237.08453126.77389Y<NA><NA>
35화성시전곡항경기도 화성시 서신면 전곡항로14번길 11-10경기도 화성시 서신면 전곡리 896번지1855437.18565126.6544Y<NA><NA>
36화성시진안 *경기도 화성시 경기대로1010번길 8경기도 화성시 병점동 369번지1841137.206056127.037778<NA>Y<NA>
37화성시향남경기도 화성시 향남읍 향남로 399경기도 화성시 향남읍 행정리 436-6번지1859837.13107126.920457<NA>Y<NA>
38화성시화성경기도 화성시 남양읍 남양로 599-17경기도 화성시 남양읍 신남리 34-1번지1826937.19525126.82094Y<NA><NA>