Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory158.0 B

Variable types

Numeric5
Categorical11
DateTime1

Dataset

Description데이터 생성일, 행정동 명, 행정동 코드 등을 기준으로 1000m 격자별 유동인구, 노인 유동인구, 구급처 주거, 구급처 도로, 구급처 상업, 출동빈도, 질병출동, 질병 외 출동 지수를 조회하는 강원소방 동적 소방지수 정보 조회 서비스
Author강원도
URLhttps://www.data.go.kr/data/15098606/fileData.do

Alerts

법정동코드 is highly overall correlated with 격자ID and 3 other fieldsHigh correlation
법정동명 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
유동인구지수 is highly overall correlated with 노인유동인구지수High correlation
노인유동인구지수 is highly overall correlated with 유동인구지수High correlation
구급처_주거지수 is highly overall correlated with 출동빈도지수 and 1 other fieldsHigh correlation
구급처_도로(교통)지수 is highly overall correlated with 출동빈도지수 and 1 other fieldsHigh correlation
출동빈도지수 is highly overall correlated with 구급처_주거지수 and 3 other fieldsHigh correlation
질병출동지수 is highly overall correlated with 구급처_주거지수 and 1 other fieldsHigh correlation
질병외출동지수 is highly overall correlated with 구급처_도로(교통)지수 and 1 other fieldsHigh correlation
구급처_주거지수 is highly imbalanced (96.6%)Imbalance
구급처_도로(교통)지수 is highly imbalanced (99.2%)Imbalance
구급처_상업(산업)지수 is highly imbalanced (99.1%)Imbalance
구급처_자연지수 is highly imbalanced (99.6%)Imbalance
구급처_기타지수 is highly imbalanced (99.0%)Imbalance
출동빈도지수 is highly imbalanced (95.8%)Imbalance
질병출동지수 is highly imbalanced (95.1%)Imbalance
질병외출동지수 is highly imbalanced (97.7%)Imbalance
노인유동인구지수 has 786 (7.9%) zerosZeros

Reproduction

Analysis started2023-12-12 06:59:01.213810
Analysis finished2023-12-12 06:59:06.847699
Duration5.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

격자ID
Real number (ℝ)

HIGH CORRELATION 

Distinct845
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41630301
Minimum35645684
Maximum49445574
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:59:06.926226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35645684
5-th percentile36845724
Q138045314
median39445204
Q347545714
95-th percentile48745704
Maximum49445574
Range13799890
Interquartile range (IQR)9500400

Descriptive statistics

Standard deviation4585585.2
Coefficient of variation (CV)0.11015018
Kurtosis-1.4324572
Mean41630301
Median Absolute Deviation (MAD)1799300
Skewness0.60624331
Sum4.1630301 × 1011
Variance2.1027592 × 1013
MonotonicityNot monotonic
2023-12-12T15:59:07.134087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47645724 30
 
0.3%
37845854 30
 
0.3%
37745824 29
 
0.3%
38945074 29
 
0.3%
39645324 29
 
0.3%
39645264 29
 
0.3%
39345234 29
 
0.3%
47745764 29
 
0.3%
47945744 28
 
0.3%
39845244 28
 
0.3%
Other values (835) 9710
97.1%
ValueCountFrequency (%)
35645684 3
 
< 0.1%
35745684 21
0.2%
35745694 1
 
< 0.1%
35745704 18
0.2%
35845764 23
0.2%
35845774 11
0.1%
35945694 10
0.1%
35945714 4
 
< 0.1%
35945724 5
 
0.1%
35945814 5
 
0.1%
ValueCountFrequency (%)
49445574 11
0.1%
49445564 11
0.1%
49445554 10
0.1%
49345644 9
 
0.1%
49345634 10
0.1%
49345624 6
 
0.1%
49345574 3
 
< 0.1%
49345564 1
 
< 0.1%
49245654 16
0.2%
49245644 24
0.2%

격자X축좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct88
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean416322.1
Minimum356475
Maximum494475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:59:07.313788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum356475
5-th percentile368475
Q1380475
median394475
Q3475475
95-th percentile487475
Maximum494475
Range138000
Interquartile range (IQR)95000

Descriptive statistics

Standard deviation45855.285
Coefficient of variation (CV)0.11014377
Kurtosis-1.4324411
Mean416322.1
Median Absolute Deviation (MAD)18000
Skewness0.60619485
Sum4.163221 × 109
Variance2.1027072 × 109
MonotonicityNot monotonic
2023-12-12T15:59:07.480437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394475 310
 
3.1%
393475 294
 
2.9%
378475 294
 
2.9%
396475 286
 
2.9%
375475 275
 
2.8%
380475 272
 
2.7%
476475 272
 
2.7%
477475 271
 
2.7%
379475 252
 
2.5%
478475 250
 
2.5%
Other values (78) 7224
72.2%
ValueCountFrequency (%)
356475 3
 
< 0.1%
357475 40
 
0.4%
358475 34
 
0.3%
359475 32
 
0.3%
360475 109
1.1%
361475 40
 
0.4%
362475 18
 
0.2%
363475 26
 
0.3%
364475 26
 
0.3%
365475 15
 
0.1%
ValueCountFrequency (%)
494475 32
 
0.3%
493475 29
 
0.3%
492475 110
1.1%
491475 150
1.5%
490475 80
0.8%
489475 54
 
0.5%
488475 25
 
0.2%
487475 58
 
0.6%
486475 97
1.0%
485475 67
0.7%

격자Y축좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean559189
Minimum505475
Maximum607475
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:59:07.631879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum505475
5-th percentile519475
Q1529475
median570475
Q3582475
95-th percentile591475
Maximum607475
Range102000
Interquartile range (IQR)53000

Descriptive statistics

Standard deviation26846.204
Coefficient of variation (CV)0.048009178
Kurtosis-1.4507837
Mean559189
Median Absolute Deviation (MAD)17000
Skewness-0.37047285
Sum5.59189 × 109
Variance7.2071868 × 108
MonotonicityNot monotonic
2023-12-12T15:59:07.795358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
582475 309
 
3.1%
570475 273
 
2.7%
525475 267
 
2.7%
583475 259
 
2.6%
584475 257
 
2.6%
586475 254
 
2.5%
529475 253
 
2.5%
585475 251
 
2.5%
572475 250
 
2.5%
526475 240
 
2.4%
Other values (81) 7387
73.9%
ValueCountFrequency (%)
505475 5
 
0.1%
506475 26
0.3%
507475 55
0.5%
508475 63
0.6%
509475 21
 
0.2%
510475 63
0.6%
511475 32
0.3%
512475 28
0.3%
513475 12
 
0.1%
514475 26
0.3%
ValueCountFrequency (%)
607475 2
 
< 0.1%
605475 11
 
0.1%
604475 9
 
0.1%
603475 20
0.2%
601475 1
 
< 0.1%
600475 13
 
0.1%
598475 1
 
< 0.1%
597475 16
 
0.2%
596475 32
0.3%
595475 48
0.5%

시간
Categorical

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
12
 
612
13
 
545
17
 
541
14
 
530
11
 
528
Other values (19)
7244 

Length

Max length5
Median length2
Mean length2.9774
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22
2nd row20
3rd row22
4th row="04"
5th row18

Common Values

ValueCountFrequency (%)
12 612
 
6.1%
13 545
 
5.5%
17 541
 
5.4%
14 530
 
5.3%
11 528
 
5.3%
16 524
 
5.2%
10 524
 
5.2%
15 516
 
5.2%
="09" 501
 
5.0%
18 442
 
4.4%
Other values (14) 4737
47.4%

Length

2023-12-12T15:59:07.944439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12 612
 
6.1%
13 545
 
5.5%
17 541
 
5.4%
14 530
 
5.3%
11 528
 
5.3%
16 524
 
5.2%
10 524
 
5.2%
15 516
 
5.2%
09 501
 
5.0%
18 442
 
4.4%
Other values (14) 4737
47.4%

생성일자
Date

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-01-01 00:00:00
Maximum2020-01-08 00:00:00
2023-12-12T15:59:08.060846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:08.162665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

법정동명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
강원도 원주시
3711 
강원도 강릉시
3336 
강원도 춘천시
2953 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도 원주시
2nd row강원도 원주시
3rd row강원도 원주시
4th row강원도 강릉시
5th row강원도 강릉시

Common Values

ValueCountFrequency (%)
강원도 원주시 3711
37.1%
강원도 강릉시 3336
33.4%
강원도 춘천시 2953
29.5%

Length

2023-12-12T15:59:08.291745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:08.400980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 10000
50.0%
원주시 3711
 
18.6%
강릉시 3336
 
16.7%
춘천시 2953
 
14.8%

법정동코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4213000000
3711 
4215000000
3336 
4211000000
2953 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4213000000
2nd row4213000000
3rd row4213000000
4th row4215000000
5th row4215000000

Common Values

ValueCountFrequency (%)
4213000000 3711
37.1%
4215000000 3336
33.4%
4211000000 2953
29.5%

Length

2023-12-12T15:59:08.550494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:08.719398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4213000000 3711
37.1%
4215000000 3336
33.4%
4211000000 2953
29.5%

유동인구지수
Real number (ℝ)

HIGH CORRELATION 

Distinct6624
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean414.96707
Minimum0
Maximum13390.87
Zeros11
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:59:08.878544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1695
Q15.2675
median29.525
Q3242.0125
95-th percentile2451.23
Maximum13390.87
Range13390.87
Interquartile range (IQR)236.745

Descriptive statistics

Standard deviation1043.4071
Coefficient of variation (CV)2.5144336
Kurtosis25.966245
Mean414.96707
Median Absolute Deviation (MAD)28.105
Skewness4.402542
Sum4149670.7
Variance1088698.4
MonotonicityNot monotonic
2023-12-12T15:59:09.064258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.02 43
 
0.4%
1.0 39
 
0.4%
1.01 38
 
0.4%
1.08 37
 
0.4%
1.16 35
 
0.4%
1.05 34
 
0.3%
1.12 32
 
0.3%
1.03 32
 
0.3%
1.27 31
 
0.3%
1.06 30
 
0.3%
Other values (6614) 9649
96.5%
ValueCountFrequency (%)
0.0 11
 
0.1%
1.0 39
0.4%
1.01 38
0.4%
1.02 43
0.4%
1.03 32
0.3%
1.04 25
0.2%
1.05 34
0.3%
1.06 30
0.3%
1.07 15
 
0.1%
1.08 37
0.4%
ValueCountFrequency (%)
13390.87 1
< 0.1%
13205.11 1
< 0.1%
12177.19 1
< 0.1%
12165.86 1
< 0.1%
12014.6 1
< 0.1%
10798.63 1
< 0.1%
10705.0 1
< 0.1%
9297.6 1
< 0.1%
8848.33 1
< 0.1%
8674.72 1
< 0.1%

노인유동인구지수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3665
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.192952
Minimum0
Maximum1391.8
Zeros786
Zeros (%)7.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:59:09.233690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.36
median2.28
Q318.99
95-th percentile240.1705
Maximum1391.8
Range1391.8
Interquartile range (IQR)18.63

Descriptive statistics

Standard deviation106.06236
Coefficient of variation (CV)2.7061589
Kurtosis29.732082
Mean39.192952
Median Absolute Deviation (MAD)2.24
Skewness4.729963
Sum391929.52
Variance11249.224
MonotonicityNot monotonic
2023-12-12T15:59:09.399300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 786
 
7.9%
0.12 110
 
1.1%
0.16 85
 
0.9%
0.18 78
 
0.8%
0.08 74
 
0.7%
0.2 72
 
0.7%
0.06 67
 
0.7%
0.14 63
 
0.6%
0.3 63
 
0.6%
0.15 61
 
0.6%
Other values (3655) 8541
85.4%
ValueCountFrequency (%)
0.0 786
7.9%
0.01 5
 
0.1%
0.02 21
 
0.2%
0.03 31
 
0.3%
0.04 54
 
0.5%
0.05 30
 
0.3%
0.06 67
 
0.7%
0.07 41
 
0.4%
0.08 74
 
0.7%
0.09 44
 
0.4%
ValueCountFrequency (%)
1391.8 1
< 0.1%
1346.33 1
< 0.1%
1325.53 1
< 0.1%
1230.85 1
< 0.1%
1186.59 1
< 0.1%
1186.39 1
< 0.1%
1088.1 1
< 0.1%
1046.06 1
< 0.1%
1044.85 1
< 0.1%
1019.48 1
< 0.1%

구급처_주거지수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9941 
1
 
56
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9941
99.4%
1 56
 
0.6%
2 3
 
< 0.1%

Length

2023-12-12T15:59:09.588663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:09.728077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9941
99.4%
1 56
 
0.6%
2 3
 
< 0.1%

구급처_도로(교통)지수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9986 
1
 
9
2
 
4
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 9986
99.9%
1 9
 
0.1%
2 4
 
< 0.1%
3 1
 
< 0.1%

Length

2023-12-12T15:59:09.860085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:09.991947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9986
99.9%
1 9
 
0.1%
2 4
 
< 0.1%
3 1
 
< 0.1%

구급처_상업(산업)지수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9992 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9992
99.9%
1 8
 
0.1%

Length

2023-12-12T15:59:10.103783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:10.224057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9992
99.9%
1 8
 
0.1%

구급처_자연지수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9997 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9997
> 99.9%
1 3
 
< 0.1%

Length

2023-12-12T15:59:10.370135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:10.497458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9997
> 99.9%
1 3
 
< 0.1%

구급처_기타지수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9991 
1
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9991
99.9%
1 9
 
0.1%

Length

2023-12-12T15:59:10.616301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:10.730531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9991
99.9%
1 9
 
0.1%

출동빈도지수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9902 
1
 
88
2
 
8
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9902
99.0%
1 88
 
0.9%
2 8
 
0.1%
3 2
 
< 0.1%

Length

2023-12-12T15:59:10.874507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:11.020894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9902
99.0%
1 88
 
0.9%
2 8
 
0.1%
3 2
 
< 0.1%

질병출동지수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9945 
1
 
55

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9945
99.5%
1 55
 
0.5%

Length

2023-12-12T15:59:11.132979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:11.236045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9945
99.5%
1 55
 
0.5%

질병외출동지수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9953 
1
 
41
2
 
4
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 9953
99.5%
1 41
 
0.4%
2 4
 
< 0.1%
3 2
 
< 0.1%

Length

2023-12-12T15:59:11.338821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:59:11.439975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9953
99.5%
1 41
 
0.4%
2 4
 
< 0.1%
3 2
 
< 0.1%

Interactions

2023-12-12T15:59:05.429770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:03.412499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:03.883309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.440039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.912170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:05.811921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:03.517148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.001608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.529076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:05.008185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:05.948519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:03.612084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.124714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.642562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:05.104850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:06.109995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:03.695157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.226839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.727256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:05.196678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:06.273576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:03.789360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.333347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:04.820325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:59:05.311559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:59:11.545110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자ID격자X축좌표격자Y축좌표시간생성일자법정동명법정동코드유동인구지수노인유동인구지수구급처_주거지수구급처_도로(교통)지수구급처_상업(산업)지수구급처_자연지수구급처_기타지수출동빈도지수질병출동지수질병외출동지수
격자ID1.0001.0000.7460.0380.0480.9350.9350.1210.1340.0150.0000.0000.0000.1130.0230.0630.000
격자X축좌표1.0001.0000.7460.0380.0480.9350.9350.1210.1340.0150.0000.0000.0000.1130.0230.0630.000
격자Y축좌표0.7460.7461.0000.0370.0650.8820.8820.1890.1800.0000.0000.0000.0800.0000.0000.0100.000
시간0.0380.0380.0371.0000.1900.0840.0840.1070.0860.0420.0320.0000.0000.0000.0260.0220.000
생성일자0.0480.0480.0650.1901.0000.0390.0390.0320.0220.0000.0000.0000.0220.0100.0110.0220.000
법정동명0.9350.9350.8820.0840.0391.0001.0000.1090.1100.0600.0130.0020.0000.0000.0130.0150.007
법정동코드0.9350.9350.8820.0840.0391.0001.0000.1090.1100.0600.0130.0020.0000.0000.0130.0150.007
유동인구지수0.1210.1210.1890.1070.0320.1090.1091.0000.9250.2320.1120.1130.0000.0890.1830.1680.138
노인유동인구지수0.1340.1340.1800.0860.0220.1100.1100.9251.0000.2430.2410.1920.0000.0640.2680.1960.233
구급처_주거지수0.0150.0150.0000.0420.0000.0600.0600.2320.2431.0000.0000.0000.0000.0000.6690.4960.320
구급처_도로(교통)지수0.0000.0000.0000.0320.0000.0130.0130.1120.2410.0001.0000.0000.0000.0000.9100.0590.965
구급처_상업(산업)지수0.0000.0000.0000.0000.0000.0020.0020.1130.1920.0000.0001.0000.0000.0000.4450.2560.328
구급처_자연지수0.0000.0000.0800.0000.0220.0000.0000.0000.0000.0000.0000.0001.0000.0000.2750.0000.402
구급처_기타지수0.1130.1130.0000.0000.0100.0000.0000.0890.0640.0000.0000.0000.0001.0000.4710.4410.152
출동빈도지수0.0230.0230.0000.0260.0110.0130.0130.1830.2680.6690.9100.4450.2750.4711.0000.9270.979
질병출동지수0.0630.0630.0100.0220.0220.0150.0150.1680.1960.4960.0590.2560.0000.4410.9271.0000.118
질병외출동지수0.0000.0000.0000.0000.0000.0070.0070.1380.2330.3200.9650.3280.4020.1520.9790.1181.000
2023-12-12T15:59:12.028433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구급처_주거지수구급처_상업(산업)지수구급처_자연지수질병출동지수법정동코드질병외출동지수시간구급처_도로(교통)지수출동빈도지수법정동명구급처_기타지수
구급처_주거지수1.0000.0000.0000.7560.0180.3090.0190.0000.6980.0180.000
구급처_상업(산업)지수0.0001.0000.0000.1650.0040.2190.0000.0000.3000.0040.000
구급처_자연지수0.0000.0001.0000.0000.0000.2690.0000.0000.1830.0000.000
질병출동지수0.7560.1650.0001.0000.0260.0780.0170.0390.7560.0260.291
법정동코드0.0180.0040.0000.0261.0000.0070.0380.0120.0121.0000.000
질병외출동지수0.3090.2190.2690.0780.0071.0000.0000.7470.8010.0070.101
시간0.0190.0000.0000.0170.0380.0001.0000.0150.0120.0380.000
구급처_도로(교통)지수0.0000.0000.0000.0390.0120.7470.0151.0000.6060.0120.000
출동빈도지수0.6980.3000.1830.7560.0120.8010.0120.6061.0000.0120.318
법정동명0.0180.0040.0000.0261.0000.0070.0380.0120.0121.0000.000
구급처_기타지수0.0000.0000.0000.2910.0000.1010.0000.0000.3180.0001.000
2023-12-12T15:59:12.173090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
격자ID격자X축좌표격자Y축좌표유동인구지수노인유동인구지수시간법정동명법정동코드구급처_주거지수구급처_도로(교통)지수구급처_상업(산업)지수구급처_자연지수구급처_기타지수출동빈도지수질병출동지수질병외출동지수
격자ID1.0001.000-0.2380.1000.1060.0140.9400.9400.0090.0000.0000.0000.0840.0110.0470.000
격자X축좌표1.0001.000-0.2450.1010.1080.0140.9400.9400.0090.0000.0000.0000.0840.0110.0470.000
격자Y축좌표-0.238-0.2451.0000.0190.0320.0140.8200.8200.0000.0000.0000.0610.0000.0000.0100.000
유동인구지수0.1000.1010.0191.0000.9290.0390.0650.0650.1420.0670.0860.0000.0680.1100.1290.083
노인유동인구지수0.1060.1080.0320.9291.0000.0310.0650.0650.1490.1460.1470.0000.0490.1630.1500.141
시간0.0140.0140.0140.0390.0311.0000.0380.0380.0190.0150.0000.0000.0000.0120.0170.000
법정동명0.9400.9400.8200.0650.0650.0381.0001.0000.0180.0120.0040.0000.0000.0120.0260.007
법정동코드0.9400.9400.8200.0650.0650.0381.0001.0000.0180.0120.0040.0000.0000.0120.0260.007
구급처_주거지수0.0090.0090.0000.1420.1490.0190.0180.0181.0000.0000.0000.0000.0000.6980.7560.309
구급처_도로(교통)지수0.0000.0000.0000.0670.1460.0150.0120.0120.0001.0000.0000.0000.0000.6060.0390.747
구급처_상업(산업)지수0.0000.0000.0000.0860.1470.0000.0040.0040.0000.0001.0000.0000.0000.3000.1650.219
구급처_자연지수0.0000.0000.0610.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.1830.0000.269
구급처_기타지수0.0840.0840.0000.0680.0490.0000.0000.0000.0000.0000.0000.0001.0000.3180.2910.101
출동빈도지수0.0110.0110.0000.1100.1630.0120.0120.0120.6980.6060.3000.1830.3181.0000.7560.801
질병출동지수0.0470.0470.0100.1290.1500.0170.0260.0260.7560.0390.1650.0000.2910.7561.0000.078
질병외출동지수0.0000.0000.0000.0830.1410.0000.0070.0070.3090.7470.2190.2690.1010.8010.0781.000

Missing values

2023-12-12T15:59:06.450822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:59:06.735042image/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

격자ID격자X축좌표격자Y축좌표시간생성일자법정동명법정동코드유동인구지수노인유동인구지수구급처_주거지수구급처_도로(교통)지수구급처_상업(산업)지수구급처_자연지수구급처_기타지수출동빈도지수질병출동지수질병외출동지수
4934239745244397475524475222020-01-04강원도 원주시42130000001176.0290.2900000000
6104339845364398475536475202020-01-05강원도 원주시42130000004.350.2600000000
6204139745324397475532475222020-01-05강원도 원주시421300000033.334.8900000000
8809247445844474475584475="04"2020-01-08강원도 강릉시42150000003.960.000000000
4668347645734476475573475182020-01-04강원도 강릉시42150000001031.5954.7500000000
4710236946044369475604475192020-01-04강원도 춘천시42110000009.810.000000000
6111537445834374475583475212020-01-05강원도 춘천시42110000005.560.2800000000
3232548045754480475575475152020-01-03강원도 강릉시42150000002204.41263.2900000000
6366939445264394475526475="03"2020-01-06강원도 원주시42130000001047.4960.1700000000
9390538145884381475588475152020-01-08강원도 춘천시42110000001.080.0800000000
격자ID격자X축좌표격자Y축좌표시간생성일자법정동명법정동코드유동인구지수노인유동인구지수구급처_주거지수구급처_도로(교통)지수구급처_상업(산업)지수구급처_자연지수구급처_기타지수출동빈도지수질병출동지수질병외출동지수
7204647345884473475588475192020-01-06강원도 강릉시42150000001061.22183.4900000000
1188239245214392475521475212020-01-01강원도 원주시421300000066.083.9200000000
2952337945924379475592475112020-01-03강원도 춘천시421100000066.961.3200000000
3156647345854473475585475142020-01-03강원도 강릉시4215000000414.3743.1700000000
9439036545794365475579475162020-01-08강원도 춘천시42110000001.160.000000000
5333138745264387475526475="08"2020-01-05강원도 원주시4213000000110.5311.4600000000
6937936645694366475569475152020-01-06강원도 춘천시421100000011.011.0600000000
3789739745304397475530475="01"2020-01-04강원도 원주시42130000006.440.3600000000
1552539845344398475534475="07"2020-01-02강원도 원주시42130000001.040.3200000000
3459537345854373475585475192020-01-03강원도 춘천시4211000000224.0310.600000000