Overview

Dataset statistics

Number of variables10
Number of observations128
Missing cells328
Missing cells (%)25.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.5 KiB
Average record size in memory84.0 B

Variable types

Categorical1
Text3
Numeric3
Boolean3

Dataset

Description자동기상관측장비(AWS) 설치 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=IW2T5YWJTM7NUZ2QPVU025865983&infSeq=1

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 WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
소재지도로명주소 has 37 (28.9%) missing valuesMissing
소재지우편번호 has 15 (11.7%) missing valuesMissing
WGS84위도 has 10 (7.8%) missing valuesMissing
WGS84경도 has 10 (7.8%) missing valuesMissing
기상청 관리 장비 has 84 (65.6%) missing valuesMissing
경기도 관리 장비 has 62 (48.4%) missing valuesMissing
시군 관리 장비 has 110 (85.9%) missing valuesMissing
지점명 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:44:59.277296
Analysis finished2023-12-10 21:45:01.331216
Duration2.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
포천시
12 
연천군
9 
화성시
 
8
여주시
 
8
평택시
 
7
Other values (26)
84 

Length

Max length4
Median length3
Mean length3.0625
Min length3

Unique

Unique3 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
포천시 12
 
9.4%
연천군 9
 
7.0%
화성시 8
 
6.2%
여주시 8
 
6.2%
평택시 7
 
5.5%
파주시 7
 
5.5%
안성시 7
 
5.5%
용인시 6
 
4.7%
이천시 6
 
4.7%
양주시 6
 
4.7%
Other values (21) 52
40.6%

Length

2023-12-11T06:45:01.391660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
포천시 12
 
9.4%
연천군 9
 
7.0%
화성시 8
 
6.2%
여주시 8
 
6.2%
평택시 7
 
5.5%
파주시 7
 
5.5%
안성시 7
 
5.5%
용인시 6
 
4.7%
이천시 6
 
4.7%
양주시 6
 
4.7%
Other values (21) 52
40.6%

지점명
Text

UNIQUE 

Distinct128
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T06:45:01.653117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.4765625
Min length2

Characters and Unicode

Total characters317
Distinct characters118
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

Unique128 ?
Unique (%)100.0%

Sample

1st row가평조종
2nd row신천 *
3rd row외서
4th row읍내
5th row청평
ValueCountFrequency (%)
11
 
7.9%
가평조종 1
 
0.7%
설봉 1
 
0.7%
오전동 1
 
0.7%
의왕 1
 
0.7%
신곡 1
 
0.7%
의정부 1
 
0.7%
마장 1
 
0.7%
모가 1
 
0.7%
신둔 1
 
0.7%
Other values (119) 119
85.6%
2023-12-11T06:45:01.997897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 15
 
4.7%
남 11
 
3.5%
11
 
3.5%
* 11
 
3.5%
천 10
 
3.2%
면 9
 
2.8%
산 8
 
2.5%
신 8
 
2.5%
성 6
 
1.9%
양 6
 
1.9%
Other values (108) 222
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 295
93.1%
Space Separator 11
 
3.5%
Other Punctuation 11
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 15
 
5.1%
남 11
 
3.7%
천 10
 
3.4%
면 9
 
3.1%
산 8
 
2.7%
신 8
 
2.7%
성 6
 
2.0%
양 6
 
2.0%
포 6
 
2.0%
현 6
 
2.0%
Other values (106) 210
71.2%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
* 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 295
93.1%
Common 22
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 15
 
5.1%
남 11
 
3.7%
천 10
 
3.4%
면 9
 
3.1%
산 8
 
2.7%
신 8
 
2.7%
성 6
 
2.0%
양 6
 
2.0%
포 6
 
2.0%
현 6
 
2.0%
Other values (106) 210
71.2%
Common
ValueCountFrequency (%)
11
50.0%
* 11
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
93.1%
ASCII 22
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 15
 
5.1%
남 11
 
3.7%
천 10
 
3.4%
면 9
 
3.1%
산 8
 
2.7%
신 8
 
2.7%
성 6
 
2.0%
양 6
 
2.0%
포 6
 
2.0%
현 6
 
2.0%
Other values (106) 210
71.2%
ASCII
ValueCountFrequency (%)
11
50.0%
* 11
50.0%

소재지도로명주소
Text

MISSING 

Distinct91
Distinct (%)100.0%
Missing37
Missing (%)28.9%
Memory size1.1 KiB
2023-12-11T06:45:02.198451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length19.285714
Min length14

Characters and Unicode

Total characters1755
Distinct characters152
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

Unique91 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 청평면 강변로 17
2nd row경기도 가평군 청평면 경춘로 88
3rd row경기도 고양시 덕양구 고양시청로 10
4th row경기도 과천시 상하벌로 110
5th row경기도 광명시 시청로 20
ValueCountFrequency (%)
경기도 91
 
21.1%
포천시 9
 
2.1%
여주시 7
 
1.6%
파주시 6
 
1.4%
평택시 5
 
1.2%
양주시 5
 
1.2%
광주시 5
 
1.2%
용인시 5
 
1.2%
화성시 5
 
1.2%
안성시 5
 
1.2%
Other values (254) 288
66.8%
2023-12-11T06:45:02.515250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
340
19.4%
경 95
 
5.4%
도 93
 
5.3%
기 93
 
5.3%
시 88
 
5.0%
로 79
 
4.5%
1 73
 
4.2%
2 48
 
2.7%
면 39
 
2.2%
4 30
 
1.7%
Other values (142) 777
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1090
62.1%
Space Separator 340
 
19.4%
Decimal Number 308
 
17.5%
Dash Punctuation 17
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 95
 
8.7%
도 93
 
8.5%
기 93
 
8.5%
시 88
 
8.1%
로 79
 
7.2%
면 39
 
3.6%
길 29
 
2.7%
천 28
 
2.6%
주 24
 
2.2%
양 20
 
1.8%
Other values (130) 502
46.1%
Decimal Number
ValueCountFrequency (%)
1 73
23.7%
2 48
15.6%
4 30
9.7%
3 30
9.7%
6 28
 
9.1%
0 27
 
8.8%
5 22
 
7.1%
7 19
 
6.2%
9 17
 
5.5%
8 14
 
4.5%
Space Separator
ValueCountFrequency (%)
340
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1090
62.1%
Common 665
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 95
 
8.7%
도 93
 
8.5%
기 93
 
8.5%
시 88
 
8.1%
로 79
 
7.2%
면 39
 
3.6%
길 29
 
2.7%
천 28
 
2.6%
주 24
 
2.2%
양 20
 
1.8%
Other values (130) 502
46.1%
Common
ValueCountFrequency (%)
340
51.1%
1 73
 
11.0%
2 48
 
7.2%
4 30
 
4.5%
3 30
 
4.5%
6 28
 
4.2%
0 27
 
4.1%
5 22
 
3.3%
7 19
 
2.9%
9 17
 
2.6%
Other values (2) 31
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1090
62.1%
ASCII 665
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
340
51.1%
1 73
 
11.0%
2 48
 
7.2%
4 30
 
4.5%
3 30
 
4.5%
6 28
 
4.2%
0 27
 
4.1%
5 22
 
3.3%
7 19
 
2.9%
9 17
 
2.6%
Other values (2) 31
 
4.7%
Hangul
ValueCountFrequency (%)
경 95
 
8.7%
도 93
 
8.5%
기 93
 
8.5%
시 88
 
8.1%
로 79
 
7.2%
면 39
 
3.6%
길 29
 
2.7%
천 28
 
2.6%
주 24
 
2.2%
양 20
 
1.8%
Other values (130) 502
46.1%

소재지지번주소
Text

UNIQUE 

Distinct128
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-11T06:45:02.724625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length25.46875
Min length15

Characters and Unicode

Total characters3260
Distinct characters209
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 조종면 현리 209, 현리정수장
2nd row경기도 가평군 설악면 신천리 156-1, 설악면행정복지센터
3rd row경기도 가평군 청평면 청평리 620-7
4th row경기도 가평군 가평읍 승안리 98-1, 가평군농업기술센터 입구
5th row경기도 가평군 청평면 대성리 393-3
ValueCountFrequency (%)
경기도 128
 
18.6%
포천시 12
 
1.7%
연천군 9
 
1.3%
화성시 8
 
1.2%
여주시 8
 
1.2%
평택시 7
 
1.0%
안성시 7
 
1.0%
파주시 7
 
1.0%
양주시 6
 
0.9%
용인시 6
 
0.9%
Other values (439) 492
71.3%
2023-12-11T06:45:03.029644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
562
 
17.2%
기 140
 
4.3%
도 138
 
4.2%
경 132
 
4.0%
시 117
 
3.6%
- 87
 
2.7%
리 86
 
2.6%
면 82
 
2.5%
1 80
 
2.5%
, 75
 
2.3%
Other values (199) 1761
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2058
63.1%
Space Separator 562
 
17.2%
Decimal Number 476
 
14.6%
Dash Punctuation 87
 
2.7%
Other Punctuation 75
 
2.3%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 140
 
6.8%
도 138
 
6.7%
경 132
 
6.4%
시 117
 
5.7%
리 86
 
4.2%
면 82
 
4.0%
동 72
 
3.5%
지 66
 
3.2%
천 48
 
2.3%
정 44
 
2.1%
Other values (185) 1133
55.1%
Decimal Number
ValueCountFrequency (%)
1 80
16.8%
2 62
13.0%
3 58
12.2%
4 52
10.9%
5 48
10.1%
6 40
8.4%
0 37
7.8%
7 34
7.1%
8 34
7.1%
9 31
 
6.5%
Space Separator
ValueCountFrequency (%)
562
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Other Punctuation
ValueCountFrequency (%)
, 75
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2058
63.1%
Common 1200
36.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 140
 
6.8%
도 138
 
6.7%
경 132
 
6.4%
시 117
 
5.7%
리 86
 
4.2%
면 82
 
4.0%
동 72
 
3.5%
지 66
 
3.2%
천 48
 
2.3%
정 44
 
2.1%
Other values (185) 1133
55.1%
Common
ValueCountFrequency (%)
562
46.8%
- 87
 
7.2%
1 80
 
6.7%
, 75
 
6.2%
2 62
 
5.2%
3 58
 
4.8%
4 52
 
4.3%
5 48
 
4.0%
6 40
 
3.3%
0 37
 
3.1%
Other values (3) 99
 
8.2%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2058
63.1%
ASCII 1202
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
562
46.8%
- 87
 
7.2%
1 80
 
6.7%
, 75
 
6.2%
2 62
 
5.2%
3 58
 
4.8%
4 52
 
4.3%
5 48
 
4.0%
6 40
 
3.3%
0 37
 
3.1%
Other values (4) 101
 
8.4%
Hangul
ValueCountFrequency (%)
기 140
 
6.8%
도 138
 
6.7%
경 132
 
6.4%
시 117
 
5.7%
리 86
 
4.2%
면 82
 
4.0%
동 72
 
3.5%
지 66
 
3.2%
천 48
 
2.3%
정 44
 
2.1%
Other values (185) 1133
55.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct112
Distinct (%)99.1%
Missing15
Missing (%)11.7%
Infinite0
Infinite (%)0.0%
Mean13736.805
Minimum10123
Maximum18598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T06:45:03.144877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10123
5-th percentile10806
Q111164
median12613
Q317027
95-th percentile18321.8
Maximum18598
Range8475
Interquartile range (IQR)5863

Descriptive statistics

Standard deviation2756.9026
Coefficient of variation (CV)0.2006946
Kurtosis-1.3130953
Mean13736.805
Median Absolute Deviation (MAD)1568
Skewness0.54929678
Sum1552259
Variance7600511.9
MonotonicityNot monotonic
2023-12-11T06:45:03.255553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10800 2
 
1.6%
11045 1
 
0.8%
10858 1
 
0.8%
10803 1
 
0.8%
10934 1
 
0.8%
10948 1
 
0.8%
17421 1
 
0.8%
17327 1
 
0.8%
17300 1
 
0.8%
17408 1
 
0.8%
Other values (102) 102
79.7%
(Missing) 15
 
11.7%
ValueCountFrequency (%)
10123 1
0.8%
10460 1
0.8%
10548 1
0.8%
10800 2
1.6%
10803 1
0.8%
10808 1
0.8%
10858 1
0.8%
10934 1
0.8%
10948 1
0.8%
11003 1
0.8%
ValueCountFrequency (%)
18598 1
0.8%
18562 1
0.8%
18556 1
0.8%
18555 1
0.8%
18554 1
0.8%
18401 1
0.8%
18269 1
0.8%
18130 1
0.8%
18015 1
0.8%
17946 1
0.8%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct118
Distinct (%)100.0%
Missing10
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean37.51996
Minimum36.951767
Maximum38.172579
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T06:45:03.364654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.951767
5-th percentile37.04532
Q137.248998
median37.437587
Q337.828998
95-th percentile38.062636
Maximum38.172579
Range1.2208125
Interquartile range (IQR)0.58000019

Descriptive statistics

Standard deviation0.33649071
Coefficient of variation (CV)0.008968312
Kurtosis-1.1537511
Mean37.51996
Median Absolute Deviation (MAD)0.27607339
Skewness0.2159208
Sum4427.3553
Variance0.113226
MonotonicityNot monotonic
2023-12-11T06:45:03.480256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3374703781 1
 
0.8%
37.9519692633 1
 
0.8%
37.908011841 1
 
0.8%
37.748755353 1
 
0.8%
37.7761588985 1
 
0.8%
37.1203220977 1
 
0.8%
37.2641847528 1
 
0.8%
37.3268058219 1
 
0.8%
37.2747699594 1
 
0.8%
37.1687432579 1
 
0.8%
Other values (108) 108
84.4%
(Missing) 10
 
7.8%
ValueCountFrequency (%)
36.9517666318 1
0.8%
36.9673433617 1
0.8%
36.979993115 1
0.8%
36.9851845472 1
0.8%
37.0230156078 1
0.8%
37.0423309148 1
0.8%
37.0458477239 1
0.8%
37.0598825532 1
0.8%
37.0676621984 1
0.8%
37.080211613 1
0.8%
ValueCountFrequency (%)
38.1725791554 1
0.8%
38.15772941 1
0.8%
38.1366069916 1
0.8%
38.0965166652 1
0.8%
38.089292204 1
0.8%
38.0851875866 1
0.8%
38.0586559112 1
0.8%
38.0474311724 1
0.8%
38.0405825186 1
0.8%
38.0269316038 1
0.8%

WGS84경도
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)100.0%
Missing10
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean127.12688
Minimum126.55226
Maximum127.75498
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-11T06:45:03.602727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55226
5-th percentile126.71549
Q1126.93654
median127.08879
Q3127.28726
95-th percentile127.59088
Maximum127.75498
Range1.2027268
Interquartile range (IQR)0.35072071

Descriptive statistics

Standard deviation0.2650356
Coefficient of variation (CV)0.0020848117
Kurtosis-0.42426976
Mean127.12688
Median Absolute Deviation (MAD)0.17008976
Skewness0.23746742
Sum15000.971
Variance0.070243868
MonotonicityNot monotonic
2023-12-11T06:45:03.719908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9676097942 1
 
0.8%
126.9302083566 1
 
0.8%
126.7118994303 1
 
0.8%
126.7777588312 1
 
0.8%
126.8512218426 1
 
0.8%
127.6112278537 1
 
0.8%
127.4841768333 1
 
0.8%
127.4344988526 1
 
0.8%
127.4427082262 1
 
0.8%
127.4826986529 1
 
0.8%
Other values (108) 108
84.4%
(Missing) 10
 
7.8%
ValueCountFrequency (%)
126.5522572407 1
0.8%
126.5787108549 1
0.8%
126.6128500908 1
0.8%
126.6535933125 1
0.8%
126.7086691403 1
0.8%
126.7118994303 1
0.8%
126.7161234951 1
0.8%
126.7626731331 1
0.8%
126.7658092011 1
0.8%
126.7738417337 1
0.8%
ValueCountFrequency (%)
127.7549840009 1
0.8%
127.7133717031 1
0.8%
127.6790809929 1
0.8%
127.6623026525 1
0.8%
127.6396413163 1
0.8%
127.6112278537 1
0.8%
127.5872905518 1
0.8%
127.5448724152 1
0.8%
127.5413041602 1
0.8%
127.5333610209 1
0.8%

기상청 관리 장비
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)2.3%
Missing84
Missing (%)65.6%
Memory size388.0 B
True
44 
(Missing)
84 
ValueCountFrequency (%)
True 44
34.4%
(Missing) 84
65.6%
2023-12-11T06:45:03.817454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경기도 관리 장비
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.5%
Missing62
Missing (%)48.4%
Memory size388.0 B
True
66 
(Missing)
62 
ValueCountFrequency (%)
True 66
51.6%
(Missing) 62
48.4%
2023-12-11T06:45:03.898048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시군 관리 장비
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)5.6%
Missing110
Missing (%)85.9%
Memory size388.0 B
True
18 
(Missing)
110 
ValueCountFrequency (%)
True 18
 
14.1%
(Missing) 110
85.9%
2023-12-11T06:45:03.961349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-11T06:45:00.585344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:44:59.742306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:45:00.010982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:45:00.674448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:44:59.818417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:45:00.356320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:45:00.780833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:44:59.916271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:45:00.468408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:45:04.011665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명소재지도로명주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.9920.9470.901
소재지도로명주소1.0001.0001.0001.0001.000
소재지우편번호0.9921.0001.0000.8330.803
WGS84위도0.9471.0000.8331.0000.000
WGS84경도0.9011.0000.8030.0001.000
2023-12-11T06:45:04.087132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명
소재지우편번호1.000-0.9120.0580.842
WGS84위도-0.9121.000-0.0750.592
WGS84경도0.058-0.0751.0000.489
시군명0.8420.5920.4891.000

Missing values

2023-12-11T06:45:00.920861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:45:01.093624image/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.
2023-12-11T06:45:01.247398image/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

시군명지점명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도기상청 관리 장비경기도 관리 장비시군 관리 장비
0가평군가평조종<NA>경기도 가평군 조종면 현리 209, 현리정수장<NA><NA><NA>Y<NA><NA>
1가평군신천 *<NA>경기도 가평군 설악면 신천리 156-1, 설악면행정복지센터1246737.675851127.494307<NA>Y<NA>
2가평군외서경기도 가평군 청평면 강변로 17경기도 가평군 청평면 청평리 620-71245337.734601127.414262<NA>Y<NA>
3가평군읍내<NA>경기도 가평군 가평읍 승안리 98-1, 가평군농업기술센터 입구1240837.845984127.500715<NA>Y<NA>
4가평군청평경기도 가평군 청평면 경춘로 88경기도 가평군 청평면 대성리 393-31245737.684091127.379237Y<NA><NA>
5고양시고양<NA>경기도 고양시 덕양구 용두동 산 17-231054837.635416126.886723Y<NA><NA>
6고양시능곡<NA>경기도 고양시 일산동구 성석동 산 69-2<NA><NA><NA>Y<NA><NA>
7고양시주교경기도 고양시 덕양구 고양시청로 10경기도 고양시 덕양구 주교동 6001046037.658411126.831965<NA>Y<NA>
8과천시과천경기도 과천시 상하벌로 110경기도 과천시 과천동 758번지1381737.438535127.005543Y<NA><NA>
9광명시광명경기도 광명시 시청로 20경기도 광명시 철산3동 222-11423437.477129126.863769<NA>Y<NA>
시군명지점명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도기상청 관리 장비경기도 관리 장비시군 관리 장비
118하남시춘궁 *경기도 하남시 서하남로 488경기도 하남시 춘궁동 334-1, 하남시노인복지회관1302037.521982127.194051<NA>Y<NA>
119하남시하남경기도 하남시 대청로 10경기도 하남시 신장동 520-2, 하남시청1295137.539276127.214536<NA>Y<NA>
120화성시도리도<NA>경기도 화성시 서신면 백미리 산 1441855637.118498126.61285Y<NA><NA>
121화성시서신경기도 화성시 서신면 궁평항로 1702경기도 화성시 서신면 매화리 277, 서신면행정복지센터1855537.165742126.708669<NA>Y<NA>
122화성시송산<NA>경기도 화성시 송산면 삼존리 1286, 송산체육공원<NA><NA><NA><NA>Y<NA>
123화성시운평<NA>경기도 화성시 우정읍 운평리 601-61856237.084399126.773842Y<NA><NA>
124화성시전곡항경기도 화성시 서신면 전곡항로14번길 16-17경기도 화성시 서신면 전곡리 10751855437.184437126.653593Y<NA><NA>
125화성시진안 *경기도 화성시 병점3로 23경기도 화성시 진안동 526-2, 화성동부출장소1840137.208803127.035536<NA>Y<NA>
126화성시향남경기도 화성시 향남읍 향남로 399경기도 화성시 향남읍 행정리 436-6, 화성소방서1859837.130938126.92056<NA>Y<NA>
127화성시화성경기도 화성시 남양읍 남양로 599-17경기도 화성시 남양읍 신남리 34-1번지1826937.19475126.820738Y<NA><NA>