Overview

Dataset statistics

Number of variables15
Number of observations133
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.7 KiB
Average record size in memory136.0 B

Variable types

Numeric15

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-12051/F/1/datasetView.do

Alerts

년도 is highly overall correlated with 교통 and 9 other fieldsHigh correlation
교통 is highly overall correlated with 년도 and 10 other fieldsHigh correlation
도로 is highly overall correlated with 년도 and 9 other fieldsHigh correlation
청소 is highly overall correlated with 년도 and 10 other fieldsHigh correlation
주택건축 is highly overall correlated with 년도 and 11 other fieldsHigh correlation
치수방재 is highly overall correlated with 년도 and 9 other fieldsHigh correlation
가로정비 is highly overall correlated with 도로 and 7 other fieldsHigh correlation
보건 is highly overall correlated with 년도 and 11 other fieldsHigh correlation
공원녹지 is highly overall correlated with 년도 and 10 other fieldsHigh correlation
환경 is highly overall correlated with 년도 and 11 other fieldsHigh correlation
경제/산업 is highly overall correlated with 년도 and 2 other fieldsHigh correlation
소방안전 is highly overall correlated with 교통 and 6 other fieldsHigh correlation
기타 불편사항 is highly overall correlated with 청소 and 4 other fieldsHigh correlation
총합계 is highly overall correlated with 년도 and 11 other fieldsHigh correlation
교통 has unique valuesUnique
총합계 has unique valuesUnique
보건 has 4 (3.0%) zerosZeros
경제/산업 has 82 (61.7%) zerosZeros
소방안전 has 26 (19.5%) zerosZeros

Reproduction

Analysis started2024-03-30 05:44:12.730626
Analysis finished2024-03-30 05:45:31.385362
Duration1 minute and 18.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.6241
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:31.552275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2018
Q32020
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.234758
Coefficient of variation (CV)0.0016032511
Kurtosis-1.1665157
Mean2017.6241
Median Absolute Deviation (MAD)3
Skewness-0.0034507707
Sum268344
Variance10.463659
MonotonicityIncreasing
2024-03-30T05:45:31.909507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2013 12
9.0%
2014 12
9.0%
2015 12
9.0%
2016 12
9.0%
2017 12
9.0%
2018 12
9.0%
2019 12
9.0%
2020 12
9.0%
2021 12
9.0%
2022 12
9.0%
Other values (2) 13
9.8%
ValueCountFrequency (%)
2012 5
3.8%
2013 12
9.0%
2014 12
9.0%
2015 12
9.0%
2016 12
9.0%
2017 12
9.0%
2018 12
9.0%
2019 12
9.0%
2020 12
9.0%
2021 12
9.0%
ValueCountFrequency (%)
2023 8
6.0%
2022 12
9.0%
2021 12
9.0%
2020 12
9.0%
2019 12
9.0%
2018 12
9.0%
2017 12
9.0%
2016 12
9.0%
2015 12
9.0%
2014 12
9.0%


Real number (ℝ)

Distinct12
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5112782
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:32.259857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.454502
Coefficient of variation (CV)0.5305413
Kurtosis-1.2082065
Mean6.5112782
Median Absolute Deviation (MAD)3
Skewness-0.0093142275
Sum866
Variance11.933584
MonotonicityNot monotonic
2024-03-30T05:45:32.709099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 12
9.0%
9 11
8.3%
10 11
8.3%
11 11
8.3%
12 11
8.3%
1 11
8.3%
2 11
8.3%
3 11
8.3%
4 11
8.3%
5 11
8.3%
Other values (2) 22
16.5%
ValueCountFrequency (%)
1 11
8.3%
2 11
8.3%
3 11
8.3%
4 11
8.3%
5 11
8.3%
6 11
8.3%
7 11
8.3%
8 12
9.0%
9 11
8.3%
10 11
8.3%
ValueCountFrequency (%)
12 11
8.3%
11 11
8.3%
10 11
8.3%
9 11
8.3%
8 12
9.0%
7 11
8.3%
6 11
8.3%
5 11
8.3%
4 11
8.3%
3 11
8.3%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26926.331
Minimum46
Maximum67792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:33.471425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile333.8
Q17286
median24970
Q342206
95-th percentile62926.6
Maximum67792
Range67746
Interquartile range (IQR)34920

Descriptive statistics

Standard deviation20543.444
Coefficient of variation (CV)0.76294999
Kurtosis-1.155241
Mean26926.331
Median Absolute Deviation (MAD)17404
Skewness0.26950194
Sum3581202
Variance4.2203308 × 108
MonotonicityNot monotonic
2024-03-30T05:45:34.114435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.8%
40621 1
 
0.8%
41293 1
 
0.8%
40405 1
 
0.8%
42374 1
 
0.8%
45930 1
 
0.8%
45510 1
 
0.8%
45637 1
 
0.8%
39210 1
 
0.8%
33170 1
 
0.8%
Other values (123) 123
92.5%
ValueCountFrequency (%)
46 1
0.8%
83 1
0.8%
87 1
0.8%
99 1
0.8%
149 1
0.8%
195 1
0.8%
251 1
0.8%
389 1
0.8%
579 1
0.8%
713 1
0.8%
ValueCountFrequency (%)
67792 1
0.8%
67467 1
0.8%
65903 1
0.8%
65894 1
0.8%
65631 1
0.8%
65565 1
0.8%
63571 1
0.8%
62497 1
0.8%
60088 1
0.8%
59581 1
0.8%

도로
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1387.6541
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:34.667576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile352
Q1916
median1318
Q31831
95-th percentile2541.4
Maximum5000
Range4966
Interquartile range (IQR)915

Descriptive statistics

Standard deviation736.89994
Coefficient of variation (CV)0.53104006
Kurtosis3.5689652
Mean1387.6541
Median Absolute Deviation (MAD)474
Skewness1.0538153
Sum184558
Variance543021.52
MonotonicityNot monotonic
2024-03-30T05:45:35.186313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019 2
 
1.5%
1726 2
 
1.5%
1166 2
 
1.5%
1318 2
 
1.5%
1792 1
 
0.8%
1972 1
 
0.8%
1377 1
 
0.8%
1388 1
 
0.8%
1831 1
 
0.8%
1983 1
 
0.8%
Other values (119) 119
89.5%
ValueCountFrequency (%)
34 1
0.8%
57 1
0.8%
60 1
0.8%
86 1
0.8%
105 1
0.8%
187 1
0.8%
238 1
0.8%
428 1
0.8%
439 1
0.8%
447 1
0.8%
ValueCountFrequency (%)
5000 1
0.8%
3494 1
0.8%
2998 1
0.8%
2780 1
0.8%
2758 1
0.8%
2617 1
0.8%
2557 1
0.8%
2531 1
0.8%
2483 1
0.8%
2395 1
0.8%

청소
Real number (ℝ)

HIGH CORRELATION 

Distinct132
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2690.5263
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:35.752606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile32.6
Q11600
median3115
Q33719
95-th percentile4986.8
Maximum8515
Range8507
Interquartile range (IQR)2119

Descriptive statistics

Standard deviation1633.3758
Coefficient of variation (CV)0.60708411
Kurtosis0.14764436
Mean2690.5263
Median Absolute Deviation (MAD)786
Skewness-0.03343385
Sum357840
Variance2667916.4
MonotonicityNot monotonic
2024-03-30T05:45:36.341818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.5%
15 1
 
0.8%
3761 1
 
0.8%
5254 1
 
0.8%
3785 1
 
0.8%
3321 1
 
0.8%
3294 1
 
0.8%
3417 1
 
0.8%
3459 1
 
0.8%
4086 1
 
0.8%
Other values (122) 122
91.7%
ValueCountFrequency (%)
8 1
0.8%
9 1
0.8%
15 1
0.8%
17 1
0.8%
22 2
1.5%
29 1
0.8%
35 1
0.8%
62 1
0.8%
66 1
0.8%
67 1
0.8%
ValueCountFrequency (%)
8515 1
0.8%
5966 1
0.8%
5938 1
0.8%
5664 1
0.8%
5259 1
0.8%
5254 1
0.8%
5144 1
0.8%
4882 1
0.8%
4793 1
0.8%
4731 1
0.8%

주택건축
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean399.99248
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:36.961084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.6
Q1146
median355
Q3496
95-th percentile978.6
Maximum3185
Range3183
Interquartile range (IQR)350

Descriptive statistics

Standard deviation429.62137
Coefficient of variation (CV)1.0740736
Kurtosis17.521289
Mean399.99248
Median Absolute Deviation (MAD)175
Skewness3.5030931
Sum53199
Variance184574.52
MonotonicityNot monotonic
2024-03-30T05:45:37.616472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.3%
9 3
 
2.3%
174 2
 
1.5%
36 2
 
1.5%
443 2
 
1.5%
602 2
 
1.5%
466 2
 
1.5%
483 2
 
1.5%
352 2
 
1.5%
2 2
 
1.5%
Other values (110) 111
83.5%
ValueCountFrequency (%)
2 2
1.5%
3 1
 
0.8%
5 1
 
0.8%
6 1
 
0.8%
7 1
 
0.8%
8 1
 
0.8%
9 3
2.3%
11 1
 
0.8%
13 1
 
0.8%
15 1
 
0.8%
ValueCountFrequency (%)
3185 1
0.8%
2464 1
0.8%
1957 1
0.8%
1636 1
0.8%
1363 1
0.8%
1012 1
0.8%
999 1
0.8%
965 1
0.8%
759 1
0.8%
752 1
0.8%

치수방재
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.37594
Minimum0
Maximum807
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:38.336877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q1103
median218
Q3376
95-th percentile529.2
Maximum807
Range807
Interquartile range (IQR)273

Descriptive statistics

Standard deviation171.66068
Coefficient of variation (CV)0.68836102
Kurtosis0.25756863
Mean249.37594
Median Absolute Deviation (MAD)134
Skewness0.67312722
Sum33167
Variance29467.388
MonotonicityNot monotonic
2024-03-30T05:45:39.009518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71 2
 
1.5%
156 2
 
1.5%
154 2
 
1.5%
127 2
 
1.5%
325 2
 
1.5%
207 2
 
1.5%
201 2
 
1.5%
304 2
 
1.5%
384 2
 
1.5%
165 2
 
1.5%
Other values (109) 113
85.0%
ValueCountFrequency (%)
0 1
0.8%
2 1
0.8%
7 1
0.8%
9 2
1.5%
11 1
0.8%
14 1
0.8%
19 1
0.8%
20 1
0.8%
22 1
0.8%
28 1
0.8%
ValueCountFrequency (%)
807 1
0.8%
720 1
0.8%
706 1
0.8%
672 1
0.8%
646 1
0.8%
593 1
0.8%
558 1
0.8%
510 1
0.8%
503 1
0.8%
489 1
0.8%

가로정비
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4501.8421
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:39.622275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile78.6
Q13345
median4533
Q35730
95-th percentile9660.8
Maximum12906
Range12895
Interquartile range (IQR)2385

Descriptive statistics

Standard deviation2598.6885
Coefficient of variation (CV)0.57725003
Kurtosis0.5509639
Mean4501.8421
Median Absolute Deviation (MAD)1197
Skewness0.34788521
Sum598745
Variance6753181.9
MonotonicityNot monotonic
2024-03-30T05:45:40.160094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4281 2
 
1.5%
516 2
 
1.5%
11 1
 
0.8%
4203 1
 
0.8%
5800 1
 
0.8%
4761 1
 
0.8%
4743 1
 
0.8%
4663 1
 
0.8%
4602 1
 
0.8%
4868 1
 
0.8%
Other values (121) 121
91.0%
ValueCountFrequency (%)
11 1
0.8%
34 1
0.8%
50 1
0.8%
53 1
0.8%
59 1
0.8%
69 1
0.8%
72 1
0.8%
83 1
0.8%
97 1
0.8%
151 1
0.8%
ValueCountFrequency (%)
12906 1
0.8%
10761 1
0.8%
10527 1
0.8%
10396 1
0.8%
10196 1
0.8%
9945 1
0.8%
9806 1
0.8%
9564 1
0.8%
9169 1
0.8%
8910 1
0.8%

보건
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct108
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.27068
Minimum0
Maximum1206
Zeros4
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:40.689487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q147
median149
Q3346
95-th percentile569.2
Maximum1206
Range1206
Interquartile range (IQR)299

Descriptive statistics

Standard deviation211.14006
Coefficient of variation (CV)0.96733129
Kurtosis2.8889771
Mean218.27068
Median Absolute Deviation (MAD)124
Skewness1.4276933
Sum29030
Variance44580.123
MonotonicityNot monotonic
2024-03-30T05:45:41.337309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
3.0%
66 4
 
3.0%
32 3
 
2.3%
258 3
 
2.3%
149 2
 
1.5%
42 2
 
1.5%
346 2
 
1.5%
126 2
 
1.5%
1 2
 
1.5%
128 2
 
1.5%
Other values (98) 107
80.5%
ValueCountFrequency (%)
0 4
3.0%
1 2
1.5%
2 2
1.5%
3 2
1.5%
4 2
1.5%
7 1
 
0.8%
8 2
1.5%
9 1
 
0.8%
11 1
 
0.8%
13 1
 
0.8%
ValueCountFrequency (%)
1206 1
0.8%
803 1
0.8%
726 1
0.8%
707 1
0.8%
694 1
0.8%
688 1
0.8%
583 1
0.8%
560 1
0.8%
550 1
0.8%
546 1
0.8%

공원녹지
Real number (ℝ)

HIGH CORRELATION 

Distinct125
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean364.33835
Minimum3
Maximum1055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:41.896824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile26.8
Q1138
median275
Q3545
95-th percentile889
Maximum1055
Range1052
Interquartile range (IQR)407

Descriptive statistics

Standard deviation287.12971
Coefficient of variation (CV)0.78808533
Kurtosis-0.6564285
Mean364.33835
Median Absolute Deviation (MAD)179
Skewness0.73361129
Sum48457
Variance82443.468
MonotonicityNot monotonic
2024-03-30T05:45:42.431103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
693 2
 
1.5%
51 2
 
1.5%
70 2
 
1.5%
276 2
 
1.5%
91 2
 
1.5%
378 2
 
1.5%
182 2
 
1.5%
160 2
 
1.5%
884 1
 
0.8%
760 1
 
0.8%
Other values (115) 115
86.5%
ValueCountFrequency (%)
3 1
0.8%
4 1
0.8%
6 1
0.8%
10 1
0.8%
14 1
0.8%
15 1
0.8%
22 1
0.8%
30 1
0.8%
35 1
0.8%
42 1
0.8%
ValueCountFrequency (%)
1055 1
0.8%
1030 1
0.8%
970 1
0.8%
964 1
0.8%
919 1
0.8%
902 1
0.8%
895 1
0.8%
885 1
0.8%
884 1
0.8%
879 1
0.8%

환경
Real number (ℝ)

HIGH CORRELATION 

Distinct123
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1231.7293
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:43.020740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.6
Q1248
median1036
Q31563
95-th percentile3831.4
Maximum9985
Range9984
Interquartile range (IQR)1315

Descriptive statistics

Standard deviation1495.4256
Coefficient of variation (CV)1.2140862
Kurtosis13.169655
Mean1231.7293
Median Absolute Deviation (MAD)687
Skewness3.1677897
Sum163820
Variance2236297.8
MonotonicityNot monotonic
2024-03-30T05:45:44.023729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 3
 
2.3%
50 2
 
1.5%
1044 2
 
1.5%
1153 2
 
1.5%
1066 2
 
1.5%
1549 2
 
1.5%
34 2
 
1.5%
641 2
 
1.5%
4 2
 
1.5%
779 1
 
0.8%
Other values (113) 113
85.0%
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
4 2
1.5%
6 3
2.3%
7 1
 
0.8%
13 1
 
0.8%
15 1
 
0.8%
17 1
 
0.8%
19 1
 
0.8%
20 1
 
0.8%
ValueCountFrequency (%)
9985 1
0.8%
8225 1
0.8%
6539 1
0.8%
6285 1
0.8%
5125 1
0.8%
4496 1
0.8%
4090 1
0.8%
3659 1
0.8%
2794 1
0.8%
2711 1
0.8%

경제/산업
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66165414
Minimum0
Maximum6
Zeros82
Zeros (%)61.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:44.528739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3.4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1473766
Coefficient of variation (CV)1.7341032
Kurtosis6.5166655
Mean0.66165414
Median Absolute Deviation (MAD)0
Skewness2.4367215
Sum88
Variance1.316473
MonotonicityNot monotonic
2024-03-30T05:45:44.984908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 82
61.7%
1 33
24.8%
2 10
 
7.5%
4 4
 
3.0%
5 2
 
1.5%
3 1
 
0.8%
6 1
 
0.8%
ValueCountFrequency (%)
0 82
61.7%
1 33
24.8%
2 10
 
7.5%
3 1
 
0.8%
4 4
 
3.0%
5 2
 
1.5%
6 1
 
0.8%
ValueCountFrequency (%)
6 1
 
0.8%
5 2
 
1.5%
4 4
 
3.0%
3 1
 
0.8%
2 10
 
7.5%
1 33
24.8%
0 82
61.7%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)20.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1654135
Minimum0
Maximum65
Zeros26
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:45.344892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q313
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)12

Descriptive statistics

Standard deviation9.125539
Coefficient of variation (CV)1.1175844
Kurtosis10.20578
Mean8.1654135
Median Absolute Deviation (MAD)5
Skewness2.3069244
Sum1086
Variance83.275461
MonotonicityNot monotonic
2024-03-30T05:45:45.785986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 26
19.5%
2 10
 
7.5%
8 10
 
7.5%
1 9
 
6.8%
3 8
 
6.0%
5 8
 
6.0%
4 7
 
5.3%
6 6
 
4.5%
20 6
 
4.5%
11 5
 
3.8%
Other values (17) 38
28.6%
ValueCountFrequency (%)
0 26
19.5%
1 9
 
6.8%
2 10
 
7.5%
3 8
 
6.0%
4 7
 
5.3%
5 8
 
6.0%
6 6
 
4.5%
7 4
 
3.0%
8 10
 
7.5%
10 3
 
2.3%
ValueCountFrequency (%)
65 1
 
0.8%
30 1
 
0.8%
27 1
 
0.8%
26 1
 
0.8%
25 1
 
0.8%
23 4
3.0%
22 1
 
0.8%
21 3
2.3%
20 6
4.5%
18 2
 
1.5%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct130
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2330.7594
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:46.420876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile51.4
Q1382
median2492
Q33440
95-th percentile5813.2
Maximum7847
Range7831
Interquartile range (IQR)3058

Descriptive statistics

Standard deviation1891.4859
Coefficient of variation (CV)0.81153204
Kurtosis-0.28539322
Mean2330.7594
Median Absolute Deviation (MAD)1252
Skewness0.54939664
Sum309991
Variance3577719
MonotonicityNot monotonic
2024-03-30T05:45:47.149419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 3
 
2.3%
3071 2
 
1.5%
2533 1
 
0.8%
3434 1
 
0.8%
3254 1
 
0.8%
2782 1
 
0.8%
2688 1
 
0.8%
2385 1
 
0.8%
16 1
 
0.8%
3356 1
 
0.8%
Other values (120) 120
90.2%
ValueCountFrequency (%)
16 1
0.8%
24 1
0.8%
28 1
0.8%
30 1
0.8%
33 1
0.8%
43 1
0.8%
49 1
0.8%
53 1
0.8%
54 1
0.8%
66 1
0.8%
ValueCountFrequency (%)
7847 1
0.8%
7191 1
0.8%
6947 1
0.8%
6184 1
0.8%
6055 1
0.8%
5972 1
0.8%
5893 1
0.8%
5760 1
0.8%
5545 1
0.8%
5493 1
0.8%

총합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct133
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42938.654
Minimum230
Maximum107800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:45:47.740609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1390.6
Q118947
median44713
Q363922
95-th percentile87931
Maximum107800
Range107570
Interquartile range (IQR)44975

Descriptive statistics

Standard deviation27996.24
Coefficient of variation (CV)0.65200554
Kurtosis-0.94303118
Mean42938.654
Median Absolute Deviation (MAD)22398
Skewness0.069766713
Sum5710841
Variance7.8378947 × 108
MonotonicityNot monotonic
2024-03-30T05:45:48.288898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.8%
62998 1
 
0.8%
61221 1
 
0.8%
63570 1
 
0.8%
63909 1
 
0.8%
68704 1
 
0.8%
69507 1
 
0.8%
67111 1
 
0.8%
57806 1
 
0.8%
50517 1
 
0.8%
Other values (123) 123
92.5%
ValueCountFrequency (%)
230 1
0.8%
315 1
0.8%
342 1
0.8%
396 1
0.8%
427 1
0.8%
682 1
0.8%
1168 1
0.8%
1539 1
0.8%
2246 1
0.8%
2338 1
0.8%
ValueCountFrequency (%)
107800 1
0.8%
104091 1
0.8%
99268 1
0.8%
94613 1
0.8%
94321 1
0.8%
92212 1
0.8%
88513 1
0.8%
87543 1
0.8%
85947 1
0.8%
83077 1
0.8%

Interactions

2024-03-30T05:45:25.228741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:14.112340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:19.122314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:24.848834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:29.659390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:33.402889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:37.410190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:42.439810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:47.750967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:53.103285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:58.441432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:03.696920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:09.211171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:14.071224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:19.929955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:25.520687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:14.467334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:19.421155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:25.130260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:29.903827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:33.634471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:37.840738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:42.800544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:48.030540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:53.500903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:58.923368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:04.042045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:09.498549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:14.453920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:20.312162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:25.888364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:14.807117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:19.747276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:25.388617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:30.139220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:33.931263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:38.255714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:43.198573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:48.278291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:53.834613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:59.470083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:04.451432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:09.814569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:14.811827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:20.590151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:26.259640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:15.127056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:20.068720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:25.703338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:30.395421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:34.184876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:38.600013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:43.487683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:48.608005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:54.246307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:59.800951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:04.800344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:10.118509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:15.253531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:20.875314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:26.604271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:15.454048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:20.290817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:26.367801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:30.636472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:34.495514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:38.888626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:43.775318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:48.914305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:54.511673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:00.069963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:05.173518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:10.515494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:15.700303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:21.592699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:26.902331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:15.830489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:20.564502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:26.747630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:30.930891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:34.745160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:39.127126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:44.239372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:49.223013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:54.758599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:00.452538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:05.449246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:10.795406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:16.049795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:21.922710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:27.220755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:16.136715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:20.861133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:27.229271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:31.151669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:34.988489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:39.394129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:44.634429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:49.513671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:55.142713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:00.751789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:05.795048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:11.091372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:16.430932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:22.247486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:27.539236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:16.494133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:21.280803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:27.520541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:31.384850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:35.247036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:39.671262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:45.025544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:49.880046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:55.496227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:01.047056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:06.196806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:11.443167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:16.920797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:22.647649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:27.893083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:16.751757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:21.778027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:27.768030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:31.630806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:35.487545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:39.927384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:45.333775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:50.259735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:55.951137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:01.310467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:06.829042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:11.809690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:17.350938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:23.150283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:28.259888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:17.119491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:22.254407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:28.017684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:31.951602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:35.786902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:40.243763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:45.607625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:50.565822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:56.347721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:01.658042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:07.078531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:12.117922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:17.727822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:23.468441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:28.609563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:17.482479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:22.680055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:28.255236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:32.219569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:36.041470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:40.739680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:45.951673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:50.891845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:56.732933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:02.016041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:07.382768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:12.360869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:18.086995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:23.746279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:28.993990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:17.799934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:23.022372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:28.571751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:32.435600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:36.298748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:41.027794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:46.352611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:51.574605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:57.079791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:02.342265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:07.746372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:12.724346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:18.455771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:24.012200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:29.260815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:18.166107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:23.695165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:28.810333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:32.663159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:36.569434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:41.335991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:46.741132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:51.943744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:57.551572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:02.781934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:08.126594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:13.126633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:18.931305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:24.283106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:29.527684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:18.426485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:24.074041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:29.063167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:32.905140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:36.822913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:41.658191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:47.011579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:52.369296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:57.803975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:03.079396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:08.457985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:13.410093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:19.215242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:24.610317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:29.902754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:18.762371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:24.442673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:29.348110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:33.154360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:37.122360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:42.164333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:47.441244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:52.772719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:44:58.103272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:03.367285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:08.849503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:13.832435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:19.560593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:45:24.892519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T05:45:48.705442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9640.5190.6920.6090.6110.7730.4030.7600.5610.3730.5760.8620.897
0.0001.0000.0000.3880.2010.1450.5230.5430.3900.4640.2600.1550.0000.0000.000
교통0.9640.0001.0000.5470.6770.6260.7460.7300.6050.7590.5530.5030.6580.8890.954
도로0.5190.3880.5471.0000.4050.3960.6710.3550.8230.6770.2740.0000.2590.2710.536
청소0.6920.2010.6770.4051.0000.6180.4530.6430.4550.6400.6440.0000.4630.7030.692
주택건축0.6090.1450.6260.3960.6181.0000.3990.3240.4540.4350.9790.0000.4140.7600.581
치수방재0.6110.5230.7460.6710.4530.3991.0000.8110.7110.8510.3890.5530.2930.5210.823
가로정비0.7730.5430.7300.3550.6430.3240.8111.0000.4000.7050.2740.0000.0790.6610.758
보건0.4030.3900.6050.8230.4550.4540.7110.4001.0000.7650.5370.3490.4390.3880.632
공원녹지0.7600.4640.7590.6770.6400.4350.8510.7050.7651.0000.5530.4690.5420.6200.780
환경0.5610.2600.5530.2740.6440.9790.3890.2740.5370.5531.0000.0000.5160.5880.501
경제/산업0.3730.1550.5030.0000.0000.0000.5530.0000.3490.4690.0001.0000.0000.1740.449
소방안전0.5760.0000.6580.2590.4630.4140.2930.0790.4390.5420.5160.0001.0000.5160.545
기타 불편사항0.8620.0000.8890.2710.7030.7600.5210.6610.3880.6200.5880.1740.5161.0000.828
총합계0.8970.0000.9540.5360.6920.5810.8230.7580.6320.7800.5010.4490.5450.8281.000
2024-03-30T05:45:49.229926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.1210.9830.6170.5360.7750.6280.3750.7450.8050.7390.5310.4950.3170.957
-0.1211.000-0.002-0.0690.0680.033-0.0230.0440.1300.0010.1000.0800.0280.0140.020
교통0.983-0.0021.0000.6470.5930.8190.6750.4340.8120.8460.7910.5480.5110.3540.987
도로0.617-0.0690.6471.0000.5350.5350.8070.5530.7280.8250.5050.2810.4070.1350.682
청소0.5360.0680.5930.5351.0000.7520.6370.7310.7580.7140.7580.2560.4920.6670.653
주택건축0.7750.0330.8190.5350.7521.0000.5800.5160.7860.7420.9300.3910.5800.6490.855
치수방재0.628-0.0230.6750.8070.6370.5801.0000.7290.8220.8730.5650.3470.4240.2850.717
가로정비0.3750.0440.4340.5530.7310.5160.7291.0000.6780.6410.5170.1420.2730.4180.510
보건0.7450.1300.8120.7280.7580.7860.8220.6781.0000.9250.8190.4150.5440.5160.857
공원녹지0.8050.0010.8460.8250.7140.7420.8730.6410.9251.0000.7370.4370.5690.3980.875
환경0.7390.1000.7910.5050.7580.9300.5650.5170.8190.7371.0000.3470.5740.6690.836
경제/산업0.5310.0800.5480.2810.2560.3910.3470.1420.4150.4370.3471.0000.1830.1050.512
소방안전0.4950.0280.5110.4070.4920.5800.4240.2730.5440.5690.5740.1831.0000.6340.514
기타 불편사항0.3170.0140.3540.1350.6670.6490.2850.4180.5160.3980.6690.1050.6341.0000.400
총합계0.9570.0200.9870.6820.6530.8550.7170.5100.8570.8750.8360.5120.5140.4001.000

Missing values

2024-03-30T05:45:30.486806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T05:45:31.121562image/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

년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
020128465715371101060016230
12012983105172115044670049427
220121087868898302240033396
320121199602252691320128342
420121214934920342410024315
52013119523829719530660030682
6201322516192292259315400661168
720133389710351556723511500981539
820134579106662630971421300972246
920135713121467135615106421011032491
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
1232022116249715502830502296521034650019831068104091
124202212523321615209635216536001492001781205473449
1252023154307145226504431903773108214579004370869
1262023254449140327196163785304142356779105371097
1272023365903193833254305931052725175910872099107800
128202346779218813200447503994546075316325011694321
1292023565565233937707528077681803103021772011492212
13020236635712557354249370659781206105521021011987543
13120237674672617349541967255194838571102109988513
13220238658942780386940055842493688951153509285947