Overview

Dataset statistics

Number of variables10
Number of observations1884
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory163.9 KiB
Average record size in memory89.1 B

Variable types

Numeric7
Categorical3

Dataset

Description데이터 생성일, 행정동 명, 행정동 코드 등을 기준으로 1000m 격자별 소방서, 소방서 거리, 응급의료센터, 의료기관, 특정소방대상물 지수를 조회하는 강원소방 정적 소방지수 데이터
Author강원도
URLhttps://www.data.go.kr/data/15098608/fileData.do

Alerts

법정동명 is highly overall correlated with 격자ID and 3 other fieldsHigh correlation
법정동코드 is highly overall correlated with 격자ID and 3 other fieldsHigh correlation
격자ID is highly overall correlated with 격자X축좌표 and 2 other fieldsHigh correlation
격자X축좌표 is highly overall correlated with 격자ID and 2 other fieldsHigh correlation
격자Y축좌표 is highly overall correlated with 법정동명 and 1 other fieldsHigh correlation
소방서거리지수 is highly overall correlated with 특정소방대상물지수High correlation
응급의료센터지수 is highly overall correlated with 의료기관지수High correlation
의료기관지수 is highly overall correlated with 응급의료센터지수High correlation
특정소방대상물지수 is highly overall correlated with 소방서거리지수High correlation
소방서지수 is highly imbalanced (94.0%)Imbalance
격자ID has unique valuesUnique
소방서거리지수 has unique valuesUnique
응급의료센터지수 has 1831 (97.2%) zerosZeros
의료기관지수 has 1766 (93.7%) zerosZeros

Reproduction

Analysis started2023-12-12 16:42:05.688436
Analysis finished2023-12-12 16:42:13.841414
Duration8.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

격자ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1884
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41192347
Minimum35645684
Maximum49445564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:13.936049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35645684
5-th percentile36545846
Q137920302
median39145259
Q346845839
95-th percentile48545682
Maximum49445564
Range13799880
Interquartile range (IQR)8925537.5

Descriptive statistics

Standard deviation4396404
Coefficient of variation (CV)0.10672866
Kurtosis-1.2173392
Mean41192347
Median Absolute Deviation (MAD)1699550
Skewness0.70379796
Sum7.7606382 × 1010
Variance1.9328368 × 1013
MonotonicityNot monotonic
2023-12-13T01:42:14.131701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36945754 1
 
0.1%
38345134 1
 
0.1%
38345334 1
 
0.1%
38345294 1
 
0.1%
38345264 1
 
0.1%
38545174 1
 
0.1%
38345254 1
 
0.1%
38345244 1
 
0.1%
38345214 1
 
0.1%
38345204 1
 
0.1%
Other values (1874) 1874
99.5%
ValueCountFrequency (%)
35645684 1
0.1%
35745694 1
0.1%
35745704 1
0.1%
35845694 1
0.1%
35845754 1
0.1%
35845764 1
0.1%
35845774 1
0.1%
35845804 1
0.1%
35845814 1
0.1%
35945684 1
0.1%
ValueCountFrequency (%)
49445564 1
0.1%
49345634 1
0.1%
49345614 1
0.1%
49345584 1
0.1%
49345574 1
0.1%
49245654 1
0.1%
49245644 1
0.1%
49245634 1
0.1%
49245624 1
0.1%
49245614 1
0.1%

격자X축좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct104
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean411942.62
Minimum356475
Maximum494475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:14.355100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum356475
5-th percentile365475
Q1379225
median391475
Q3468475
95-th percentile485475
Maximum494475
Range138000
Interquartile range (IQR)89250

Descriptive statistics

Standard deviation43963.794
Coefficient of variation (CV)0.1067231
Kurtosis-1.2173431
Mean411942.62
Median Absolute Deviation (MAD)17000
Skewness0.70374119
Sum7.760999 × 108
Variance1.9328152 × 109
MonotonicityNot monotonic
2023-12-13T01:42:14.515258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
381475 46
 
2.4%
379475 46
 
2.4%
382475 46
 
2.4%
380475 45
 
2.4%
390475 42
 
2.2%
383475 39
 
2.1%
389475 37
 
2.0%
391475 36
 
1.9%
378475 35
 
1.9%
473475 35
 
1.9%
Other values (94) 1477
78.4%
ValueCountFrequency (%)
356475 1
 
0.1%
357475 2
 
0.1%
358475 6
 
0.3%
359475 12
0.6%
360475 9
0.5%
361475 9
0.5%
362475 12
0.6%
363475 16
0.8%
364475 16
0.8%
365475 20
1.1%
ValueCountFrequency (%)
494475 1
 
0.1%
493475 4
 
0.2%
492475 12
0.6%
491475 11
0.6%
490475 10
0.5%
489475 15
0.8%
488475 13
0.7%
487475 12
0.6%
486475 12
0.6%
485475 15
0.8%

격자Y축좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean558576.91
Minimum505475
Maximum607475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:14.729943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum505475
5-th percentile512475
Q1529475
median568475
Q3582475
95-th percentile597475
Maximum607475
Range102000
Interquartile range (IQR)53000

Descriptive statistics

Standard deviation28604.992
Coefficient of variation (CV)0.051210481
Kurtosis-1.291631
Mean558576.91
Median Absolute Deviation (MAD)19000
Skewness-0.33071515
Sum1.0523589 × 109
Variance8.1824558 × 108
MonotonicityNot monotonic
2023-12-13T01:42:14.914234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
583475 45
 
2.4%
582475 43
 
2.3%
572475 40
 
2.1%
570475 38
 
2.0%
571475 38
 
2.0%
573475 37
 
2.0%
580475 37
 
2.0%
584475 36
 
1.9%
581475 35
 
1.9%
569475 34
 
1.8%
Other values (91) 1501
79.7%
ValueCountFrequency (%)
505475 7
 
0.4%
506475 11
0.6%
507475 11
0.6%
508475 12
0.6%
509475 13
0.7%
510475 11
0.6%
511475 20
1.1%
512475 19
1.0%
513475 17
0.9%
514475 19
1.0%
ValueCountFrequency (%)
607475 2
 
0.1%
606475 1
 
0.1%
605475 6
 
0.3%
604475 8
0.4%
603475 7
0.4%
602475 9
0.5%
601475 11
0.6%
600475 12
0.6%
599475 12
0.6%
598475 16
0.8%

법정동명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
강원도 원주시
661 
강원도 춘천시
650 
강원도 강릉시
573 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도 춘천시
2nd row강원도 춘천시
3rd row강원도 춘천시
4th row강원도 춘천시
5th row강원도 춘천시

Common Values

ValueCountFrequency (%)
강원도 원주시 661
35.1%
강원도 춘천시 650
34.5%
강원도 강릉시 573
30.4%

Length

2023-12-13T01:42:15.075379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:42:15.201529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 1884
50.0%
원주시 661
 
17.5%
춘천시 650
 
17.3%
강릉시 573
 
15.2%

법정동코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
4213000000
661 
4211000000
650 
4215000000
573 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4211000000
2nd row4211000000
3rd row4211000000
4th row4211000000
5th row4211000000

Common Values

ValueCountFrequency (%)
4213000000 661
35.1%
4211000000 650
34.5%
4215000000 573
30.4%

Length

2023-12-13T01:42:15.342447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:42:15.808981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4213000000 661
35.1%
4211000000 650
34.5%
4215000000 573
30.4%

소방서지수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size14.8 KiB
0
1863 
1
 
18
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1863
98.9%
1 18
 
1.0%
2 3
 
0.2%

Length

2023-12-13T01:42:15.928956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:42:16.039265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1863
98.9%
1 18
 
1.0%
2 3
 
0.2%

소방서거리지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1884
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8108423
Minimum0.143859
Maximum27.040613
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:16.180383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.143859
5-th percentile1.2896996
Q13.480688
median5.816867
Q38.87891
95-th percentile16.854532
Maximum27.040613
Range26.896754
Interquartile range (IQR)5.398222

Descriptive statistics

Standard deviation4.6394859
Coefficient of variation (CV)0.68119121
Kurtosis1.7925152
Mean6.8108423
Median Absolute Deviation (MAD)2.6287605
Skewness1.2785166
Sum12831.627
Variance21.52483
MonotonicityNot monotonic
2023-12-13T01:42:16.387826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.534607 1
 
0.1%
8.958741 1
 
0.1%
11.089058 1
 
0.1%
7.08312 1
 
0.1%
4.081222 1
 
0.1%
5.235494 1
 
0.1%
3.082348 1
 
0.1%
2.086466 1
 
0.1%
0.979104 1
 
0.1%
1.960377 1
 
0.1%
Other values (1874) 1874
99.5%
ValueCountFrequency (%)
0.143859 1
0.1%
0.220821 1
0.1%
0.286733 1
0.1%
0.342254 1
0.1%
0.354064 1
0.1%
0.358265 1
0.1%
0.372032 1
0.1%
0.37213 1
0.1%
0.374742 1
0.1%
0.414325 1
0.1%
ValueCountFrequency (%)
27.040613 1
0.1%
26.691773 1
0.1%
26.438149 1
0.1%
26.258318 1
0.1%
25.860154 1
0.1%
25.637477 1
0.1%
25.308302 1
0.1%
25.041006 1
0.1%
23.645858 1
0.1%
23.084192 1
0.1%

응급의료센터지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.074309979
Minimum0
Maximum18
Zeros1831
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:16.525889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.67170909
Coefficient of variation (CV)9.0392851
Kurtosis365.45392
Mean0.074309979
Median Absolute Deviation (MAD)0
Skewness16.825524
Sum140
Variance0.4511931
MonotonicityNot monotonic
2023-12-13T01:42:16.667032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1831
97.2%
1 25
 
1.3%
2 11
 
0.6%
3 10
 
0.5%
7 3
 
0.2%
5 1
 
0.1%
6 1
 
0.1%
18 1
 
0.1%
13 1
 
0.1%
ValueCountFrequency (%)
0 1831
97.2%
1 25
 
1.3%
2 11
 
0.6%
3 10
 
0.5%
5 1
 
0.1%
6 1
 
0.1%
7 3
 
0.2%
13 1
 
0.1%
18 1
 
0.1%
ValueCountFrequency (%)
18 1
 
0.1%
13 1
 
0.1%
7 3
 
0.2%
6 1
 
0.1%
5 1
 
0.1%
3 10
 
0.5%
2 11
 
0.6%
1 25
 
1.3%
0 1831
97.2%

의료기관지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51380042
Minimum0
Maximum106
Zeros1766
Zeros (%)93.7%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:16.811528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum106
Range106
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.4521794
Coefficient of variation (CV)8.6651922
Kurtosis303.2038
Mean0.51380042
Median Absolute Deviation (MAD)0
Skewness15.870691
Sum968
Variance19.821902
MonotonicityNot monotonic
2023-12-13T01:42:17.019854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 1766
93.7%
1 43
 
2.3%
2 23
 
1.2%
3 6
 
0.3%
12 5
 
0.3%
4 5
 
0.3%
9 4
 
0.2%
5 4
 
0.2%
8 3
 
0.2%
18 3
 
0.2%
Other values (16) 22
 
1.2%
ValueCountFrequency (%)
0 1766
93.7%
1 43
 
2.3%
2 23
 
1.2%
3 6
 
0.3%
4 5
 
0.3%
5 4
 
0.2%
6 2
 
0.1%
7 3
 
0.2%
8 3
 
0.2%
9 4
 
0.2%
ValueCountFrequency (%)
106 1
0.1%
88 1
0.1%
69 1
0.1%
61 1
0.1%
47 1
0.1%
32 1
0.1%
29 1
0.1%
24 1
0.1%
23 2
0.1%
22 1
0.1%

특정소방대상물지수
Real number (ℝ)

HIGH CORRELATION 

Distinct211
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.133758
Minimum0
Maximum1741
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size16.7 KiB
2023-12-13T01:42:17.181400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median12
Q333
95-th percentile144.7
Maximum1741
Range1741
Interquartile range (IQR)29

Descriptive statistics

Standard deviation108.02112
Coefficient of variation (CV)2.6915278
Kurtosis74.213819
Mean40.133758
Median Absolute Deviation (MAD)10
Skewness7.3846229
Sum75612
Variance11668.563
MonotonicityNot monotonic
2023-12-13T01:42:17.375713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 206
 
10.9%
2 135
 
7.2%
3 110
 
5.8%
4 92
 
4.9%
6 66
 
3.5%
10 61
 
3.2%
5 59
 
3.1%
11 54
 
2.9%
7 54
 
2.9%
9 47
 
2.5%
Other values (201) 1000
53.1%
ValueCountFrequency (%)
0 1
 
0.1%
1 206
10.9%
2 135
7.2%
3 110
5.8%
4 92
4.9%
5 59
 
3.1%
6 66
 
3.5%
7 54
 
2.9%
8 42
 
2.2%
9 47
 
2.5%
ValueCountFrequency (%)
1741 1
0.1%
1465 1
0.1%
1057 1
0.1%
1026 1
0.1%
988 1
0.1%
966 1
0.1%
899 1
0.1%
882 1
0.1%
841 1
0.1%
725 1
0.1%

Interactions

2023-12-13T01:42:12.413276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:06.632321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.621013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:08.934739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.782286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.546124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.543036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:12.576701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:06.786072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.766817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.089842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.905111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.668493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.686411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:12.854254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:06.955261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.905588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.195112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.019238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.832823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.822495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:12.981894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.088576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:08.009626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.298430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.117326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.988905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.931016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:13.113648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.210155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:08.491040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.398432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.209718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.136027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:12.052634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:13.266250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.348580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:08.640440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.515667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.319641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.278734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:12.185397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:13.388488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:07.478404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:08.798258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:09.638283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:10.417711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:11.392899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:42:12.295157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:42:17.524322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자ID격자X축좌표격자Y축좌표법정동명법정동코드소방서지수소방서거리지수응급의료센터지수의료기관지수특정소방대상물지수
격자ID1.0001.0000.6790.8920.8920.0000.4690.0000.0000.000
격자X축좌표1.0001.0000.6790.8920.8920.0000.4690.0000.0000.000
격자Y축좌표0.6790.6791.0000.8790.8790.0000.6900.0560.0000.029
법정동명0.8920.8920.8791.0001.0000.0000.3610.0710.0000.000
법정동코드0.8920.8920.8791.0001.0000.0000.3610.0710.0000.000
소방서지수0.0000.0000.0000.0000.0001.0000.2300.4810.4420.596
소방서거리지수0.4690.4690.6900.3610.3610.2301.0000.1730.0950.270
응급의료센터지수0.0000.0000.0560.0710.0710.4810.1731.0000.9470.891
의료기관지수0.0000.0000.0000.0000.0000.4420.0950.9471.0000.953
특정소방대상물지수0.0000.0000.0290.0000.0000.5960.2700.8910.9531.000
2023-12-13T01:42:17.689587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명소방서지수법정동코드
법정동명1.0000.0001.000
소방서지수0.0001.0000.000
법정동코드1.0000.0001.000
2023-12-13T01:42:17.880775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자ID격자X축좌표격자Y축좌표소방서거리지수응급의료센터지수의료기관지수특정소방대상물지수법정동명법정동코드소방서지수
격자ID1.0001.000-0.240-0.0840.0330.0310.0330.8680.8680.000
격자X축좌표1.0001.000-0.250-0.0830.0330.0310.0320.8680.8680.000
격자Y축좌표-0.240-0.2501.0000.1090.011-0.044-0.0010.8140.8140.000
소방서거리지수-0.084-0.0830.1091.000-0.230-0.310-0.5180.2320.2320.141
응급의료센터지수0.0330.0330.011-0.2301.0000.6730.2490.0290.0290.226
의료기관지수0.0310.031-0.044-0.3100.6731.0000.3590.0000.0000.217
특정소방대상물지수0.0330.032-0.001-0.5180.2490.3591.0000.0000.0000.322
법정동명0.8680.8680.8140.2320.0290.0000.0001.0001.0000.000
법정동코드0.8680.8680.8140.2320.0290.0000.0001.0001.0000.000
소방서지수0.0000.0000.0000.1410.2260.2170.3220.0000.0001.000

Missing values

2023-12-13T01:42:13.563725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:42:13.764788image/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

격자ID격자X축좌표격자Y축좌표법정동명법정동코드소방서지수소방서거리지수응급의료센터지수의료기관지수특정소방대상물지수
036945754369475575475강원도 춘천시421100000010.5346070037
137545954375475595475강원도 춘천시421100000004.6665860059
237545964375475596475강원도 춘천시421100000005.494733002
337545974375475597475강원도 춘천시421100000006.372964006
437545984375475598475강원도 춘천시421100000007.2831820018
537545994375475599475강원도 춘천시421100000008.214762006
637645714376475571475강원도 춘천시421100000008.548152008
737645724376475572475강원도 춘천시421100000008.0743660015
837645734376475573475강원도 춘천시421100000007.7024380015
937645744376475574475강원도 춘천시421100000007.447643009
격자ID격자X축좌표격자Y축좌표법정동명법정동코드소방서지수소방서거리지수응급의료센터지수의료기관지수특정소방대상물지수
187447145614471475561475강원도 강릉시4215000000012.261804003
187547045884470475588475강원도 강릉시421500000003.7673890026
187647045904470475590475강원도 강릉시421500000005.289849008
187747145464471475546475강원도 강릉시4215000000021.852474001
187847145494471475549475강원도 강릉시4215000000020.708695001
187947145514471475551475강원도 강릉시4215000000020.160209004
188047145524471475552475강원도 강릉시4215000000019.955884003
188147145534471475553475강원도 강릉시4215000000019.481401001
188247045894470475589475강원도 강릉시421500000004.481540035
188349445564494475556475강원도 강릉시421500000003.3414480016