Overview

Dataset statistics

Number of variables8
Number of observations453
Missing cells16
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.8 KiB
Average record size in memory67.3 B

Variable types

Categorical2
Text3
Numeric3

Dataset

Description경기도_소방_경찰_지구대_치안센터 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=41VAY96U9345A3ZOQH9D21046057&infSeq=1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
소재지도로명주소 has 6 (1.3%) missing valuesMissing

Reproduction

Analysis started2023-12-10 21:29:54.951014
Analysis finished2023-12-10 21:29:56.516912
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
성남시
35 
수원시
 
31
안산시
 
25
부천시
 
23
고양시
 
23
Other values (26)
316 

Length

Max length4
Median length3
Mean length3.0794702
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row과천시
5th row광명시

Common Values

ValueCountFrequency (%)
성남시 35
 
7.7%
수원시 31
 
6.8%
안산시 25
 
5.5%
부천시 23
 
5.1%
고양시 23
 
5.1%
용인시 22
 
4.9%
화성시 21
 
4.6%
평택시 19
 
4.2%
남양주시 18
 
4.0%
안양시 18
 
4.0%
Other values (21) 218
48.1%

Length

2023-12-11T06:29:56.572617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 35
 
7.7%
수원시 31
 
6.8%
안산시 25
 
5.5%
부천시 23
 
5.1%
고양시 23
 
5.1%
용인시 22
 
4.9%
화성시 21
 
4.6%
평택시 19
 
4.2%
남양주시 18
 
4.0%
안양시 18
 
4.0%
Other values (21) 218
48.1%

시설구분명
Categorical

Distinct4
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
파출소
262 
지구대
110 
경찰관서
46 
소방서
35 

Length

Max length4
Median length3
Mean length3.1015453
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
파출소 262
57.8%
지구대 110
24.3%
경찰관서 46
 
10.2%
소방서 35
 
7.7%

Length

2023-12-11T06:29:56.681170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:29:56.773021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
파출소 262
57.8%
지구대 110
24.3%
경찰관서 46
 
10.2%
소방서 35
 
7.7%

기관명
Text

Distinct434
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-11T06:29:57.001552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length2
Mean length3.392936
Min length2

Characters and Unicode

Total characters1537
Distinct characters194
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique419 ?
Unique (%)92.5%

Sample

1st row경기도 가평소방서
2nd row경기도 고양소방서
3rd row경기도 일산소방서
4th row경기도 과천소방서
5th row경기도 광명소방서
ValueCountFrequency (%)
경기도 35
 
7.2%
중앙 6
 
1.2%
원곡 2
 
0.4%
탄현 2
 
0.4%
금광 2
 
0.4%
백석 2
 
0.4%
송내 2
 
0.4%
송산 2
 
0.4%
부곡 2
 
0.4%
은행 2
 
0.4%
Other values (425) 431
88.3%
2023-12-11T06:29:57.373234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
서 97
 
6.3%
경 84
 
5.5%
안 61
 
4.0%
찰 46
 
3.0%
도 45
 
2.9%
소 41
 
2.7%
센 39
 
2.5%
치 39
 
2.5%
터 39
 
2.5%
기 38
 
2.5%
Other values (184) 1008
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1486
96.7%
Space Separator 35
 
2.3%
Decimal Number 15
 
1.0%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 97
 
6.5%
경 84
 
5.7%
안 61
 
4.1%
찰 46
 
3.1%
도 45
 
3.0%
소 41
 
2.8%
센 39
 
2.6%
치 39
 
2.6%
터 39
 
2.6%
기 38
 
2.6%
Other values (178) 957
64.4%
Decimal Number
ValueCountFrequency (%)
2 6
40.0%
1 5
33.3%
3 3
20.0%
4 1
 
6.7%
Space Separator
ValueCountFrequency (%)
35
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1486
96.7%
Common 50
 
3.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 97
 
6.5%
경 84
 
5.7%
안 61
 
4.1%
찰 46
 
3.1%
도 45
 
3.0%
소 41
 
2.8%
센 39
 
2.6%
치 39
 
2.6%
터 39
 
2.6%
기 38
 
2.6%
Other values (178) 957
64.4%
Common
ValueCountFrequency (%)
35
70.0%
2 6
 
12.0%
1 5
 
10.0%
3 3
 
6.0%
4 1
 
2.0%
Latin
ValueCountFrequency (%)
T 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1486
96.7%
ASCII 51
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
서 97
 
6.5%
경 84
 
5.7%
안 61
 
4.1%
찰 46
 
3.1%
도 45
 
3.0%
소 41
 
2.8%
센 39
 
2.6%
치 39
 
2.6%
터 39
 
2.6%
기 38
 
2.6%
Other values (178) 957
64.4%
ASCII
ValueCountFrequency (%)
35
68.6%
2 6
 
11.8%
1 5
 
9.8%
3 3
 
5.9%
T 1
 
2.0%
4 1
 
2.0%

소재지지번주소
Text

Distinct450
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-11T06:29:57.570754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.417219
Min length15

Characters and Unicode

Total characters9702
Distinct characters234
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

Unique447 ?
Unique (%)98.7%

Sample

1st row경기도 가평군 가평읍 대곡리 213-5번지
2nd row경기도 고양시 덕양구 성사2동 740
3rd row경기도 고양시 장항동 779
4th row경기도 과천시 중앙동 40번지
5th row경기도 광명시 소하동 1336
ValueCountFrequency (%)
경기도 453
 
21.3%
성남시 35
 
1.6%
수원시 31
 
1.5%
안산시 25
 
1.2%
고양시 23
 
1.1%
부천시 23
 
1.1%
용인시 22
 
1.0%
화성시 21
 
1.0%
평택시 19
 
0.9%
남양주시 18
 
0.8%
Other values (974) 1455
68.5%
2023-12-11T06:29:57.862034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1672
 
17.2%
기 468
 
4.8%
도 464
 
4.8%
경 456
 
4.7%
지 443
 
4.6%
시 436
 
4.5%
번 423
 
4.4%
1 353
 
3.6%
동 331
 
3.4%
- 327
 
3.4%
Other values (224) 4329
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5939
61.2%
Decimal Number 1762
 
18.2%
Space Separator 1672
 
17.2%
Dash Punctuation 327
 
3.4%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 468
 
7.9%
도 464
 
7.8%
경 456
 
7.7%
지 443
 
7.5%
시 436
 
7.3%
번 423
 
7.1%
동 331
 
5.6%
구 170
 
2.9%
리 161
 
2.7%
양 127
 
2.1%
Other values (210) 2460
41.4%
Decimal Number
ValueCountFrequency (%)
1 353
20.0%
2 215
12.2%
3 200
11.4%
4 172
9.8%
5 170
9.6%
6 146
8.3%
7 145
8.2%
8 132
 
7.5%
9 121
 
6.9%
0 108
 
6.1%
Space Separator
ValueCountFrequency (%)
1672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 327
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5939
61.2%
Common 3763
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 468
 
7.9%
도 464
 
7.8%
경 456
 
7.7%
지 443
 
7.5%
시 436
 
7.3%
번 423
 
7.1%
동 331
 
5.6%
구 170
 
2.9%
리 161
 
2.7%
양 127
 
2.1%
Other values (210) 2460
41.4%
Common
ValueCountFrequency (%)
1672
44.4%
1 353
 
9.4%
- 327
 
8.7%
2 215
 
5.7%
3 200
 
5.3%
4 172
 
4.6%
5 170
 
4.5%
6 146
 
3.9%
7 145
 
3.9%
8 132
 
3.5%
Other values (4) 231
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5939
61.2%
ASCII 3763
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1672
44.4%
1 353
 
9.4%
- 327
 
8.7%
2 215
 
5.7%
3 200
 
5.3%
4 172
 
4.6%
5 170
 
4.5%
6 146
 
3.9%
7 145
 
3.9%
8 132
 
3.5%
Other values (4) 231
 
6.1%
Hangul
ValueCountFrequency (%)
기 468
 
7.9%
도 464
 
7.8%
경 456
 
7.7%
지 443
 
7.5%
시 436
 
7.3%
번 423
 
7.1%
동 331
 
5.6%
구 170
 
2.9%
리 161
 
2.7%
양 127
 
2.1%
Other values (210) 2460
41.4%

소재지도로명주소
Text

MISSING 

Distinct445
Distinct (%)99.6%
Missing6
Missing (%)1.3%
Memory size3.7 KiB
2023-12-11T06:29:58.083179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length18.809843
Min length13

Characters and Unicode

Total characters8408
Distinct characters251
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)99.1%

Sample

1st row경기도 가평군 가평읍 가화로 36
2nd row경기도 고양시 덕양구 고양대로 1342
3rd row경기도 고양시 일산동구 중앙로 1325
4th row경기도 과천시 통영로 12
5th row경기도 광명시 금하로 472
ValueCountFrequency (%)
경기도 447
 
21.4%
성남시 35
 
1.7%
수원시 31
 
1.5%
부천시 23
 
1.1%
안산시 23
 
1.1%
고양시 23
 
1.1%
용인시 21
 
1.0%
화성시 21
 
1.0%
평택시 19
 
0.9%
안양시 18
 
0.9%
Other values (848) 1431
68.4%
2023-12-11T06:29:58.404891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1645
19.6%
경 469
 
5.6%
기 461
 
5.5%
도 457
 
5.4%
시 434
 
5.2%
로 415
 
4.9%
1 304
 
3.6%
2 174
 
2.1%
3 170
 
2.0%
구 161
 
1.9%
Other values (241) 3718
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5334
63.4%
Space Separator 1645
 
19.6%
Decimal Number 1391
 
16.5%
Dash Punctuation 37
 
0.4%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 469
 
8.8%
기 461
 
8.6%
도 457
 
8.6%
시 434
 
8.1%
로 415
 
7.8%
구 161
 
3.0%
양 126
 
2.4%
길 121
 
2.3%
안 103
 
1.9%
천 101
 
1.9%
Other values (228) 2486
46.6%
Decimal Number
ValueCountFrequency (%)
1 304
21.9%
2 174
12.5%
3 170
12.2%
5 132
9.5%
4 115
 
8.3%
6 115
 
8.3%
7 110
 
7.9%
0 97
 
7.0%
9 93
 
6.7%
8 81
 
5.8%
Space Separator
ValueCountFrequency (%)
1645
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5334
63.4%
Common 3074
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 469
 
8.8%
기 461
 
8.6%
도 457
 
8.6%
시 434
 
8.1%
로 415
 
7.8%
구 161
 
3.0%
양 126
 
2.4%
길 121
 
2.3%
안 103
 
1.9%
천 101
 
1.9%
Other values (228) 2486
46.6%
Common
ValueCountFrequency (%)
1645
53.5%
1 304
 
9.9%
2 174
 
5.7%
3 170
 
5.5%
5 132
 
4.3%
4 115
 
3.7%
6 115
 
3.7%
7 110
 
3.6%
0 97
 
3.2%
9 93
 
3.0%
Other values (3) 119
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5334
63.4%
ASCII 3074
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1645
53.5%
1 304
 
9.9%
2 174
 
5.7%
3 170
 
5.5%
5 132
 
4.3%
4 115
 
3.7%
6 115
 
3.7%
7 110
 
3.6%
0 97
 
3.2%
9 93
 
3.0%
Other values (3) 119
 
3.9%
Hangul
ValueCountFrequency (%)
경 469
 
8.8%
기 461
 
8.6%
도 457
 
8.6%
시 434
 
8.1%
로 415
 
7.8%
구 161
 
3.0%
양 126
 
2.4%
길 121
 
2.3%
안 103
 
1.9%
천 101
 
1.9%
Other values (228) 2486
46.6%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct434
Distinct (%)96.2%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean14159.559
Minimum10011
Maximum18634
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-11T06:29:58.541470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10011
5-th percentile10393.5
Q112060
median13962
Q316474
95-th percentile18138
Maximum18634
Range8623
Interquartile range (IQR)4414

Descriptive statistics

Standard deviation2534.2883
Coefficient of variation (CV)0.17898074
Kurtosis-1.2367868
Mean14159.559
Median Absolute Deviation (MAD)2264
Skewness0.1262208
Sum6385961
Variance6422617.4
MonotonicityNot monotonic
2023-12-11T06:29:58.668380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15335 4
 
0.9%
12419 2
 
0.4%
16335 2
 
0.4%
13352 2
 
0.4%
12529 2
 
0.4%
12555 2
 
0.4%
15002 2
 
0.4%
14734 2
 
0.4%
17379 2
 
0.4%
11763 2
 
0.4%
Other values (424) 429
94.7%
ValueCountFrequency (%)
10011 1
0.2%
10019 1
0.2%
10024 1
0.2%
10039 1
0.2%
10057 1
0.2%
10080 1
0.2%
10090 1
0.2%
10092 1
0.2%
10108 1
0.2%
10113 1
0.2%
ValueCountFrequency (%)
18634 1
0.2%
18598 1
0.2%
18593 1
0.2%
18567 1
0.2%
18557 1
0.2%
18555 1
0.2%
18553 1
0.2%
18550 1
0.2%
18537 1
0.2%
18527 1
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct448
Distinct (%)99.8%
Missing4
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean37.451667
Minimum36.941307
Maximum38.184679
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-11T06:29:58.789491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.941307
5-th percentile37.040935
Q137.284812
median37.409584
Q337.643324
95-th percentile37.896405
Maximum38.184679
Range1.2433721
Interquartile range (IQR)0.35851177

Descriptive statistics

Standard deviation0.2547704
Coefficient of variation (CV)0.0068026451
Kurtosis-0.23140908
Mean37.451667
Median Absolute Deviation (MAD)0.15481641
Skewness0.41632819
Sum16815.798
Variance0.064907955
MonotonicityNot monotonic
2023-12-11T06:29:58.920387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4414696918 2
 
0.4%
37.1596427041 1
 
0.2%
37.322036774 1
 
0.2%
37.4792374062 1
 
0.2%
37.4498234909 1
 
0.2%
37.4779323664 1
 
0.2%
37.5308653738 1
 
0.2%
37.5203690699 1
 
0.2%
37.4861275241 1
 
0.2%
37.4962879242 1
 
0.2%
Other values (438) 438
96.7%
(Missing) 4
 
0.9%
ValueCountFrequency (%)
36.941307103 1
0.2%
36.9646371548 1
0.2%
36.9646852732 1
0.2%
36.9741598754 1
0.2%
36.9760582794 1
0.2%
36.9822966773 1
0.2%
36.9849968156 1
0.2%
36.99045917 1
0.2%
36.9917996768 1
0.2%
36.9948660902 1
0.2%
ValueCountFrequency (%)
38.1846791657 1
0.2%
38.1572485356 1
0.2%
38.0995583039 1
0.2%
38.0982867177 1
0.2%
38.0915848649 1
0.2%
38.0844996875 1
0.2%
38.0571398208 1
0.2%
38.04833739 1
0.2%
38.033091921 1
0.2%
38.0296407981 1
0.2%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct448
Distinct (%)99.8%
Missing4
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean127.05562
Minimum126.39266
Maximum127.7529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-11T06:29:59.049114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.39266
5-th percentile126.74072
Q1126.86384
median127.04764
Q3127.18461
95-th percentile127.51642
Maximum127.7529
Range1.3602398
Interquartile range (IQR)0.32076728

Descriptive statistics

Standard deviation0.23863786
Coefficient of variation (CV)0.0018782158
Kurtosis0.077305804
Mean127.05562
Median Absolute Deviation (MAD)0.15943334
Skewness0.52954835
Sum57047.972
Variance0.05694803
MonotonicityNot monotonic
2023-12-11T06:29:59.186271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1439622518 2
 
0.4%
127.0661176308 1
 
0.2%
126.831518505 1
 
0.2%
126.8527652958 1
 
0.2%
126.8882082601 1
 
0.2%
126.8689234163 1
 
0.2%
126.8157121723 1
 
0.2%
126.7748234169 1
 
0.2%
126.8078752352 1
 
0.2%
126.7905698562 1
 
0.2%
Other values (438) 438
96.7%
(Missing) 4
 
0.9%
ValueCountFrequency (%)
126.3926552177 1
0.2%
126.5520873101 1
0.2%
126.5574205565 1
0.2%
126.5825241375 1
0.2%
126.5839753445 1
0.2%
126.5975636374 1
0.2%
126.621512871 1
0.2%
126.6233905127 1
0.2%
126.631700429 1
0.2%
126.6677265765 1
0.2%
ValueCountFrequency (%)
127.752895034 1
0.2%
127.7109939243 1
0.2%
127.7087054418 1
0.2%
127.6797438945 1
0.2%
127.6742929623 1
0.2%
127.6616674147 1
0.2%
127.6469043619 1
0.2%
127.6368043796 1
0.2%
127.6361320716 1
0.2%
127.6355247485 1
0.2%

Interactions

2023-12-11T06:29:55.971916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:55.464483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:55.731872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:56.052332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:55.542072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:55.807136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:56.139215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:55.645746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:29:55.888924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:29:59.278250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설구분명소재지우편번호WGS84위도WGS84경도
시군명1.0000.3370.9930.9470.906
시설구분명0.3371.0000.3390.1710.189
소재지우편번호0.9930.3391.0000.9100.835
WGS84위도0.9470.1710.9101.0000.490
WGS84경도0.9060.1890.8350.4901.000
2023-12-11T06:29:59.366644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분명시군명
시설구분명1.0000.175
시군명0.1751.000
2023-12-11T06:29:59.445467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명시설구분명
소재지우편번호1.000-0.9120.0430.9170.207
WGS84위도-0.9121.000-0.0930.7060.102
WGS84경도0.043-0.0931.0000.5960.113
시군명0.9170.7060.5961.0000.175
시설구분명0.2070.1020.1130.1751.000

Missing values

2023-12-11T06:29:56.252455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:29:56.367087image/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.
2023-12-11T06:29:56.462776image/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

시군명시설구분명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
0가평군소방서경기도 가평소방서경기도 가평군 가평읍 대곡리 213-5번지경기도 가평군 가평읍 가화로 361241937.823343127.516589
1고양시소방서경기도 고양소방서경기도 고양시 덕양구 성사2동 740경기도 고양시 덕양구 고양대로 13421045537.655092126.833208
2고양시소방서경기도 일산소방서경기도 고양시 장항동 779경기도 고양시 일산동구 중앙로 13251040137.663269126.769608
3과천시소방서경기도 과천소방서경기도 과천시 중앙동 40번지경기도 과천시 통영로 121380737.428556126.99052
4광명시소방서경기도 광명소방서경기도 광명시 소하동 1336경기도 광명시 금하로 4721431637.448732126.885173
5광주시소방서경기도 광주소방서경기도 광주시 초월읍 대쌍령리 450-7경기도 광주시 초월읍 무들로 1121273537.385596127.299514
6구리시소방서경기도 구리소방서경기도 구리시 교문동 354-6경기도 구리시 아차산로487번길 461195237.59828127.12783
7군포시소방서경기도 군포소방서경기도 군포시 산본동 1156번지경기도 군포시 고산로 4291587037.352569126.927115
8김포시소방서경기도 김포소방서경기도 김포시 걸포동 1550-18경기도 김포시 감암로 1111009237.64155126.708512
9남양주시소방서경기도 남양주소방서경기도 남양주시 평내동 570경기도 남양주시 평내로 251222437.643324127.232218
시군명시설구분명기관명소재지지번주소소재지도로명주소소재지우편번호WGS84위도WGS84경도
443부천시지구대소삼치안센터경기도 부천시 소사본동 159-58번지경기도 부천시 은성로51번길 101470337.475513126.796575
444광명시지구대철산1치안센터경기도 광명시 철산동 56-28번지경기도 광명시 광복로38번길 31420937.488017126.863591
445시흥시파출소목감치안센터경기도 시흥시 논곡동 147-8번지 목감치안센터경기도 시흥시 동서로 11151498437.388526126.861269
446화성시파출소제부치안센터경기도 화성시 서신면 제부리 289-3번지경기도 화성시 서신면 해안길 421-51855337.176995126.621513
447과천시지구대대공원치안센터경기도 과천시 막계동 산7-1번지경기도 과천시 대공원광장로 1041382937.436192127.012746
448이천시파출소단월치안센터경기도 이천시 단월동 520-4번지경기도 이천시 단월로 531740037.223249127.449958
449안성시파출소고삼치안센터경기도 안성시 고삼면 가유리 287-1번지경기도 안성시 고삼면 고삼호수로 91750537.083102127.262127
450양평군파출소봉상치안센터경기도 양평군 단월면 봉상리 589-1번지경기도 양평군 단월면 경강로 35261252937.514608127.646904
451의정부시지구대북부치안센터경기도 의정부시 가능동 640번지경기도 의정부시 신촌로63번길 81167737.750682127.041711
452고양시파출소송포치안센터경기도 고양시 일산서구 대화동 2314번지경기도 고양시 일산서구 대화로 1661022337.670321126.737211