Overview

Dataset statistics

Number of variables15
Number of observations135
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.9 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 9 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 9 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 주택건축 and 3 other fieldsHigh correlation
기타 불편사항 is highly overall correlated with 청소 and 3 other fieldsHigh correlation
총합계 is highly overall correlated with 년도 and 10 other fieldsHigh correlation
교통 has unique valuesUnique
총합계 has unique valuesUnique
보건 has 4 (3.0%) zerosZeros
경제/산업 has 82 (60.7%) zerosZeros
소방안전 has 28 (20.7%) zerosZeros

Reproduction

Analysis started2024-03-30 05:40:38.907028
Analysis finished2024-03-30 05:41:59.328926
Duration1 minute and 20.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.7037
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:41:59.556003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2018
Q32020.5
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.2760416
Coefficient of variation (CV)0.0016236485
Kurtosis-1.1772713
Mean2017.7037
Median Absolute Deviation (MAD)3
Skewness-0.010370147
Sum272390
Variance10.732449
MonotonicityIncreasing
2024-03-30T05:42:00.094768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2013 12
8.9%
2014 12
8.9%
2015 12
8.9%
2016 12
8.9%
2017 12
8.9%
2018 12
8.9%
2019 12
8.9%
2020 12
8.9%
2021 12
8.9%
2022 12
8.9%
Other values (2) 15
11.1%
ValueCountFrequency (%)
2012 5
3.7%
2013 12
8.9%
2014 12
8.9%
2015 12
8.9%
2016 12
8.9%
2017 12
8.9%
2018 12
8.9%
2019 12
8.9%
2020 12
8.9%
2021 12
8.9%
ValueCountFrequency (%)
2023 10
7.4%
2022 12
8.9%
2021 12
8.9%
2020 12
8.9%
2019 12
8.9%
2018 12
8.9%
2017 12
8.9%
2016 12
8.9%
2015 12
8.9%
2014 12
8.9%


Real number (ℝ)

Distinct12
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5555556
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:00.427141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39.5
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4482673
Coefficient of variation (CV)0.52600687
Kurtosis-1.2116366
Mean6.5555556
Median Absolute Deviation (MAD)3
Skewness-0.037633403
Sum885
Variance11.890547
MonotonicityNot monotonic
2024-03-30T05:42:00.800424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 12
8.9%
9 12
8.9%
10 12
8.9%
11 11
8.1%
12 11
8.1%
1 11
8.1%
2 11
8.1%
3 11
8.1%
4 11
8.1%
5 11
8.1%
Other values (2) 22
16.3%
ValueCountFrequency (%)
1 11
8.1%
2 11
8.1%
3 11
8.1%
4 11
8.1%
5 11
8.1%
6 11
8.1%
7 11
8.1%
8 12
8.9%
9 12
8.9%
10 12
8.9%
ValueCountFrequency (%)
12 11
8.1%
11 11
8.1%
10 12
8.9%
9 12
8.9%
8 12
8.9%
7 11
8.1%
6 11
8.1%
5 11
8.1%
4 11
8.1%
3 11
8.1%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27637.519
Minimum46
Maximum77223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:01.301509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile347.6
Q17480.5
median27307
Q343942
95-th percentile65584.8
Maximum77223
Range77177
Interquartile range (IQR)36461.5

Descriptive statistics

Standard deviation21206.092
Coefficient of variation (CV)0.76729365
Kurtosis-1.0439862
Mean27637.519
Median Absolute Deviation (MAD)18752
Skewness0.31609396
Sum3731065
Variance4.4969836 × 108
MonotonicityNot monotonic
2024-03-30T05:42:01.968642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.7%
45637 1
 
0.7%
39628 1
 
0.7%
38404 1
 
0.7%
35082 1
 
0.7%
33380 1
 
0.7%
33170 1
 
0.7%
39210 1
 
0.7%
45510 1
 
0.7%
83 1
 
0.7%
Other values (125) 125
92.6%
ValueCountFrequency (%)
46 1
0.7%
83 1
0.7%
87 1
0.7%
99 1
0.7%
149 1
0.7%
195 1
0.7%
251 1
0.7%
389 1
0.7%
579 1
0.7%
713 1
0.7%
ValueCountFrequency (%)
77223 1
0.7%
72640 1
0.7%
67792 1
0.7%
67467 1
0.7%
65903 1
0.7%
65894 1
0.7%
65631 1
0.7%
65565 1
0.7%
63571 1
0.7%
62497 1
0.7%

도로
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1409.4
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:02.404376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile371
Q1926
median1318
Q31867
95-th percentile2659.3
Maximum5000
Range4966
Interquartile range (IQR)941

Descriptive statistics

Standard deviation752.73168
Coefficient of variation (CV)0.53407953
Kurtosis3.0357471
Mean1409.4
Median Absolute Deviation (MAD)485
Skewness0.99814905
Sum190269
Variance566604.99
MonotonicityNot monotonic
2024-03-30T05:42:02.990020image/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%
57 1
 
0.7%
1932 1
 
0.7%
1377 1
 
0.7%
1388 1
 
0.7%
1792 1
 
0.7%
1831 1
 
0.7%
Other values (121) 121
89.6%
ValueCountFrequency (%)
34 1
0.7%
57 1
0.7%
60 1
0.7%
86 1
0.7%
105 1
0.7%
187 1
0.7%
238 1
0.7%
428 1
0.7%
439 1
0.7%
447 1
0.7%
ValueCountFrequency (%)
5000 1
0.7%
3494 1
0.7%
2998 1
0.7%
2877 1
0.7%
2834 1
0.7%
2780 1
0.7%
2758 1
0.7%
2617 1
0.7%
2557 1
0.7%
2531 1
0.7%

청소
Real number (ℝ)

HIGH CORRELATION 

Distinct134
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2713.6815
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:03.520323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile33.2
Q11633
median3161
Q33747.5
95-th percentile4960.6
Maximum8515
Range8507
Interquartile range (IQR)2114.5

Descriptive statistics

Standard deviation1632.1848
Coefficient of variation (CV)0.60146515
Kurtosis0.12334645
Mean2713.6815
Median Absolute Deviation (MAD)783
Skewness-0.062888492
Sum366347
Variance2664027.3
MonotonicityNot monotonic
2024-03-30T05:42:04.211975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.5%
15 1
 
0.7%
4086 1
 
0.7%
3785 1
 
0.7%
3321 1
 
0.7%
3294 1
 
0.7%
3417 1
 
0.7%
3459 1
 
0.7%
3761 1
 
0.7%
3876 1
 
0.7%
Other values (124) 124
91.9%
ValueCountFrequency (%)
8 1
0.7%
9 1
0.7%
15 1
0.7%
17 1
0.7%
22 2
1.5%
29 1
0.7%
35 1
0.7%
62 1
0.7%
66 1
0.7%
67 1
0.7%
ValueCountFrequency (%)
8515 1
0.7%
5966 1
0.7%
5938 1
0.7%
5664 1
0.7%
5259 1
0.7%
5254 1
0.7%
5144 1
0.7%
4882 1
0.7%
4793 1
0.7%
4731 1
0.7%

주택건축
Real number (ℝ)

HIGH CORRELATION 

Distinct122
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean399.34074
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:04.748513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.7
Q1159.5
median355
Q3495.5
95-th percentile975.2
Maximum3185
Range3183
Interquartile range (IQR)336

Descriptive statistics

Standard deviation426.48207
Coefficient of variation (CV)1.0679653
Kurtosis17.826939
Mean399.34074
Median Absolute Deviation (MAD)173
Skewness3.5313459
Sum53911
Variance181886.96
MonotonicityNot monotonic
2024-03-30T05:42:05.345951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.2%
9 3
 
2.2%
36 2
 
1.5%
466 2
 
1.5%
443 2
 
1.5%
602 2
 
1.5%
174 2
 
1.5%
302 2
 
1.5%
2 2
 
1.5%
352 2
 
1.5%
Other values (112) 113
83.7%
ValueCountFrequency (%)
2 2
1.5%
3 1
 
0.7%
5 1
 
0.7%
6 1
 
0.7%
7 1
 
0.7%
8 1
 
0.7%
9 3
2.2%
11 1
 
0.7%
13 1
 
0.7%
15 1
 
0.7%
ValueCountFrequency (%)
3185 1
0.7%
2464 1
0.7%
1957 1
0.7%
1636 1
0.7%
1363 1
0.7%
1012 1
0.7%
999 1
0.7%
965 1
0.7%
759 1
0.7%
752 1
0.7%

치수방재
Real number (ℝ)

HIGH CORRELATION 

Distinct121
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean253.40741
Minimum0
Maximum807
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:06.023975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17.5
Q1105.5
median222
Q3378.5
95-th percentile544
Maximum807
Range807
Interquartile range (IQR)273

Descriptive statistics

Standard deviation173.55262
Coefficient of variation (CV)0.68487588
Kurtosis0.099001239
Mean253.40741
Median Absolute Deviation (MAD)137
Skewness0.62978212
Sum34210
Variance30120.512
MonotonicityNot monotonic
2024-03-30T05:42:06.486051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
156 2
 
1.5%
384 2
 
1.5%
201 2
 
1.5%
207 2
 
1.5%
304 2
 
1.5%
325 2
 
1.5%
165 2
 
1.5%
102 2
 
1.5%
127 2
 
1.5%
56 2
 
1.5%
Other values (111) 115
85.2%
ValueCountFrequency (%)
0 1
0.7%
2 1
0.7%
7 1
0.7%
9 2
1.5%
11 1
0.7%
14 1
0.7%
19 1
0.7%
20 1
0.7%
22 1
0.7%
28 1
0.7%
ValueCountFrequency (%)
807 1
0.7%
720 1
0.7%
706 1
0.7%
672 1
0.7%
646 1
0.7%
593 1
0.7%
558 1
0.7%
538 1
0.7%
510 1
0.7%
505 1
0.7%

가로정비
Real number (ℝ)

HIGH CORRELATION 

Distinct133
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4551.2593
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:07.317579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile79.7
Q13460.5
median4537
Q35792.5
95-th percentile9636.6
Maximum12906
Range12895
Interquartile range (IQR)2332

Descriptive statistics

Standard deviation2612.3731
Coefficient of variation (CV)0.57398908
Kurtosis0.44892572
Mean4551.2593
Median Absolute Deviation (MAD)1248
Skewness0.31602901
Sum614420
Variance6824493.3
MonotonicityNot monotonic
2024-03-30T05:42:07.943151image/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
 
0.7%
4868 1
 
0.7%
4761 1
 
0.7%
4743 1
 
0.7%
4663 1
 
0.7%
4602 1
 
0.7%
4203 1
 
0.7%
6310 1
 
0.7%
Other values (123) 123
91.1%
ValueCountFrequency (%)
11 1
0.7%
34 1
0.7%
50 1
0.7%
53 1
0.7%
59 1
0.7%
69 1
0.7%
72 1
0.7%
83 1
0.7%
97 1
0.7%
151 1
0.7%
ValueCountFrequency (%)
12906 1
0.7%
10761 1
0.7%
10527 1
0.7%
10396 1
0.7%
10196 1
0.7%
9945 1
0.7%
9806 1
0.7%
9564 1
0.7%
9169 1
0.7%
8910 1
0.7%

보건
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct109
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean222.88889
Minimum0
Maximum1206
Zeros4
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:08.713572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q153
median149
Q3350
95-th percentile566.9
Maximum1206
Range1206
Interquartile range (IQR)297

Descriptive statistics

Standard deviation212.95447
Coefficient of variation (CV)0.95542884
Kurtosis2.5493711
Mean222.88889
Median Absolute Deviation (MAD)126
Skewness1.3524912
Sum30090
Variance45349.607
MonotonicityNot monotonic
2024-03-30T05:42:09.426163image/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
 
2.2%
258 3
 
2.2%
4 2
 
1.5%
346 2
 
1.5%
42 2
 
1.5%
126 2
 
1.5%
1 2
 
1.5%
149 2
 
1.5%
Other values (99) 109
80.7%
ValueCountFrequency (%)
0 4
3.0%
1 2
1.5%
2 2
1.5%
3 2
1.5%
4 2
1.5%
7 1
 
0.7%
8 2
1.5%
9 1
 
0.7%
11 1
 
0.7%
13 1
 
0.7%
ValueCountFrequency (%)
1206 1
0.7%
803 1
0.7%
726 1
0.7%
707 1
0.7%
694 1
0.7%
688 1
0.7%
583 1
0.7%
560 1
0.7%
550 2
1.5%
546 1
0.7%

공원녹지
Real number (ℝ)

HIGH CORRELATION 

Distinct127
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean374.93333
Minimum3
Maximum1091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:10.077975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile27.6
Q1139
median276
Q3603.5
95-th percentile907.1
Maximum1091
Range1088
Interquartile range (IQR)464.5

Descriptive statistics

Standard deviation297.88509
Coefficient of variation (CV)0.79450148
Kurtosis-0.61621442
Mean374.93333
Median Absolute Deviation (MAD)185
Skewness0.74848065
Sum50616
Variance88735.525
MonotonicityNot monotonic
2024-03-30T05:42:10.746157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160 2
 
1.5%
378 2
 
1.5%
70 2
 
1.5%
51 2
 
1.5%
693 2
 
1.5%
91 2
 
1.5%
182 2
 
1.5%
276 2
 
1.5%
745 1
 
0.7%
777 1
 
0.7%
Other values (117) 117
86.7%
ValueCountFrequency (%)
3 1
0.7%
4 1
0.7%
6 1
0.7%
10 1
0.7%
14 1
0.7%
15 1
0.7%
22 1
0.7%
30 1
0.7%
35 1
0.7%
42 1
0.7%
ValueCountFrequency (%)
1091 1
0.7%
1068 1
0.7%
1055 1
0.7%
1030 1
0.7%
970 1
0.7%
964 1
0.7%
919 1
0.7%
902 1
0.7%
895 1
0.7%
885 1
0.7%

환경
Real number (ℝ)

HIGH CORRELATION 

Distinct125
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1233.0667
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:11.392554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.7
Q1271.5
median1043
Q31556
95-th percentile3788.3
Maximum9985
Range9984
Interquartile range (IQR)1284.5

Descriptive statistics

Standard deviation1484.2811
Coefficient of variation (CV)1.2037314
Kurtosis13.391189
Mean1233.0667
Median Absolute Deviation (MAD)666
Skewness3.1878707
Sum166464
Variance2203090.2
MonotonicityNot monotonic
2024-03-30T05:42:12.057090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 3
 
2.2%
1549 2
 
1.5%
1153 2
 
1.5%
1044 2
 
1.5%
34 2
 
1.5%
1066 2
 
1.5%
50 2
 
1.5%
641 2
 
1.5%
4 2
 
1.5%
2054 1
 
0.7%
Other values (115) 115
85.2%
ValueCountFrequency (%)
1 1
 
0.7%
2 1
 
0.7%
4 2
1.5%
6 3
2.2%
7 1
 
0.7%
13 1
 
0.7%
15 1
 
0.7%
17 1
 
0.7%
19 1
 
0.7%
20 1
 
0.7%
ValueCountFrequency (%)
9985 1
0.7%
8225 1
0.7%
6539 1
0.7%
6285 1
0.7%
5125 1
0.7%
4496 1
0.7%
4090 1
0.7%
3659 1
0.7%
2794 1
0.7%
2711 1
0.7%

경제/산업
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.75555556
Minimum0
Maximum7
Zeros82
Zeros (%)60.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:12.423094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3738858
Coefficient of variation (CV)1.8183783
Kurtosis7.8094237
Mean0.75555556
Median Absolute Deviation (MAD)0
Skewness2.676931
Sum102
Variance1.8875622
MonotonicityNot monotonic
2024-03-30T05:42:12.780847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 82
60.7%
1 33
24.4%
2 10
 
7.4%
4 4
 
3.0%
5 2
 
1.5%
7 2
 
1.5%
3 1
 
0.7%
6 1
 
0.7%
ValueCountFrequency (%)
0 82
60.7%
1 33
24.4%
2 10
 
7.4%
3 1
 
0.7%
4 4
 
3.0%
5 2
 
1.5%
6 1
 
0.7%
7 2
 
1.5%
ValueCountFrequency (%)
7 2
 
1.5%
6 1
 
0.7%
5 2
 
1.5%
4 4
 
3.0%
3 1
 
0.7%
2 10
 
7.4%
1 33
24.4%
0 82
60.7%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.0444444
Minimum0
Maximum65
Zeros28
Zeros (%)20.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:13.260458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q312.5
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation9.1111435
Coefficient of variation (CV)1.1326007
Kurtosis10.218099
Mean8.0444444
Median Absolute Deviation (MAD)5
Skewness2.3122925
Sum1086
Variance83.012935
MonotonicityNot monotonic
2024-03-30T05:42:13.793990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 28
20.7%
2 10
 
7.4%
8 10
 
7.4%
1 9
 
6.7%
3 8
 
5.9%
5 8
 
5.9%
4 7
 
5.2%
6 6
 
4.4%
20 6
 
4.4%
11 5
 
3.7%
Other values (17) 38
28.1%
ValueCountFrequency (%)
0 28
20.7%
1 9
 
6.7%
2 10
 
7.4%
3 8
 
5.9%
4 7
 
5.2%
5 8
 
5.9%
6 6
 
4.4%
7 4
 
3.0%
8 10
 
7.4%
10 3
 
2.2%
ValueCountFrequency (%)
65 1
 
0.7%
30 1
 
0.7%
27 1
 
0.7%
26 1
 
0.7%
25 1
 
0.7%
23 4
3.0%
22 1
 
0.7%
21 3
2.2%
20 6
4.4%
18 2
 
1.5%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct132
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2298.0222
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:14.339736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile51.8
Q1325.5
median2410
Q33437
95-th percentile5799.9
Maximum7847
Range7831
Interquartile range (IQR)3111.5

Descriptive statistics

Standard deviation1896.3448
Coefficient of variation (CV)0.82520736
Kurtosis-0.28858315
Mean2298.0222
Median Absolute Deviation (MAD)1373
Skewness0.56552646
Sum310233
Variance3596123.8
MonotonicityNot monotonic
2024-03-30T05:42:14.933829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 3
 
2.2%
3071 2
 
1.5%
16 1
 
0.7%
2870 1
 
0.7%
3254 1
 
0.7%
2782 1
 
0.7%
2688 1
 
0.7%
2385 1
 
0.7%
2533 1
 
0.7%
2998 1
 
0.7%
Other values (122) 122
90.4%
ValueCountFrequency (%)
16 1
0.7%
24 1
0.7%
28 1
0.7%
30 1
0.7%
33 1
0.7%
43 1
0.7%
49 1
0.7%
53 1
0.7%
54 1
0.7%
66 1
0.7%
ValueCountFrequency (%)
7847 1
0.7%
7191 1
0.7%
6947 1
0.7%
6184 1
0.7%
6055 1
0.7%
5972 1
0.7%
5893 1
0.7%
5760 1
0.7%
5545 1
0.7%
5493 1
0.7%

총합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct135
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43833
Minimum230
Maximum107800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:42:15.832140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1427.7
Q119111
median45878
Q365421.5
95-th percentile92844.7
Maximum107800
Range107570
Interquartile range (IQR)46310.5

Descriptive statistics

Standard deviation28736.377
Coefficient of variation (CV)0.65558773
Kurtosis-0.89538922
Mean43833
Median Absolute Deviation (MAD)22331
Skewness0.10997204
Sum5917455
Variance8.2577936 × 108
MonotonicityNot monotonic
2024-03-30T05:42:16.387532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.7%
67111 1
 
0.7%
59699 1
 
0.7%
54987 1
 
0.7%
50606 1
 
0.7%
49544 1
 
0.7%
50517 1
 
0.7%
57806 1
 
0.7%
69507 1
 
0.7%
427 1
 
0.7%
Other values (125) 125
92.6%
ValueCountFrequency (%)
230 1
0.7%
315 1
0.7%
342 1
0.7%
396 1
0.7%
427 1
0.7%
682 1
0.7%
1168 1
0.7%
1539 1
0.7%
2246 1
0.7%
2338 1
0.7%
ValueCountFrequency (%)
107800 1
0.7%
105908 1
0.7%
104091 1
0.7%
100706 1
0.7%
99268 1
0.7%
94613 1
0.7%
94321 1
0.7%
92212 1
0.7%
88513 1
0.7%
87543 1
0.7%

Interactions

2024-03-30T05:41:54.100918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:40.542467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:45.674325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:50.660426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:55.681871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:01.392979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:05.988845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:12.294225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:18.414706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:23.411617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:28.854656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:34.326087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:39.572489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:44.630047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:49.519011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:54.427168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:40.796121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:45.922485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:50.952466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:56.077865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:01.665296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:06.289743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:12.573762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:18.738310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:23.751927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:29.101352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:34.666018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:39.913658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:44.964358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:49.785664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:54.676676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:41.086079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:46.229149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:51.207639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:56.313475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:01.898388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:06.775265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:12.881321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:19.100345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:24.132210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:29.426100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:35.039222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:40.183457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:45.328081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:50.042761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:54.959569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:41.415585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:46.561148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:51.530525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:56.646781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:02.309312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:07.591435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:13.504598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:19.415622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:24.549393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:29.780479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:35.478671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:40.562741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:45.713989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:50.438645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:55.205889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:41.849710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:46.980873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:51.854071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:56.887120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:02.624775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:08.004277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:13.860069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:19.689229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:24.854050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:30.128687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:35.850190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:40.876593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:45.957661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:50.699888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:55.450141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:42.274444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:47.273361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:52.199872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:57.354708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:02.942429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:08.442514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:14.263870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:19.943399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:25.182822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:30.419315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:36.064198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:41.224575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:46.311142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:50.995186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:55.711278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:42.563295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:47.530377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:52.598075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:58.049821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:03.274901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:08.826080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:14.685838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:20.375703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:25.502586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:30.797561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:36.402983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:41.617076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:46.583480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:51.254109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:55.977518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:42.853805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:47.853569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:52.885481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:58.355375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:03.600699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:09.321981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:15.129239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:20.726482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:25.910345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:31.178671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:36.885995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:42.006943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:46.945011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:51.622882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:56.225800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:43.205096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:48.208651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:53.178523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:58.724433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:03.893944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:09.759751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:15.516397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:21.154329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:26.254705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:31.586917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:37.262526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:42.325345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:47.289818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:52.000084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:56.486555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:43.560762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:48.573480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:53.654905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:59.055386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:04.128829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:10.061084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:16.030238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:21.423588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:26.599753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:31.839653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:37.521461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:42.783761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:47.662358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:52.325533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:56.728024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:43.840449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:48.936001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:54.011290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:59.448525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:04.410169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:10.394578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:16.305512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:21.636782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:26.957440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:32.263505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:37.781615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:43.022419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:47.912253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:52.655810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:56.989088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:44.266552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:49.281815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:54.290336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:59.978387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:04.656924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:10.741618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:16.717782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:21.976726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:27.205606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:32.677904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:38.186028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:43.367170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:48.220572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:52.903343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:57.238324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:44.603089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:49.603511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:54.638960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:00.237915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:04.946215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:11.271995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:17.140151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:22.311010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:27.516774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:33.048413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:38.586515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:43.641146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:48.636701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:53.186036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:57.509638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:45.108850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:49.901390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:55.008202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:00.555715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:05.247753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:11.623819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:17.511046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:22.633114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:28.140610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:33.461100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:38.924957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:43.953347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:48.939127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:53.409919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:57.806043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:45.437358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:50.302103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:55.358134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:01.009090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:05.594714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:11.924382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:17.948290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:22.993858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:28.574873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:33.963208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:39.219267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:44.281149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:49.220462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:41:53.849446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T05:42:16.793621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9410.5370.6870.6040.6340.7640.4180.7490.5650.3630.5750.8620.900
0.0001.0000.0000.3820.1740.1530.5040.5610.3720.4250.2600.1600.0000.0000.000
교통0.9410.0001.0000.5880.6610.6070.7780.7200.6090.8180.5560.7200.6240.8410.962
도로0.5370.3820.5881.0000.4090.3880.6790.3530.8290.6950.2750.4140.2610.2850.575
청소0.6870.1740.6610.4091.0000.6040.4550.6430.4670.6120.6340.0000.4580.6940.687
주택건축0.6040.1530.6070.3880.6041.0000.3990.3170.4390.3880.9790.0000.4120.7600.577
치수방재0.6340.5040.7780.6790.4550.3991.0000.8090.7180.8660.4010.5750.3000.5280.804
가로정비0.7640.5610.7200.3530.6430.3170.8091.0000.3980.6900.2920.2130.0940.6420.751
보건0.4180.3720.6090.8290.4670.4390.7180.3981.0000.7290.5400.5630.4140.3540.629
공원녹지0.7490.4250.8180.6950.6120.3880.8660.6900.7291.0000.5070.5410.5490.6480.801
환경0.5650.2600.5560.2750.6340.9790.4010.2920.5400.5071.0000.0000.5060.5830.510
경제/산업0.3630.1600.7200.4140.0000.0000.5750.2130.5630.5410.0001.0000.0000.0870.560
소방안전0.5750.0000.6240.2610.4580.4120.3000.0940.4140.5490.5060.0001.0000.5210.545
기타 불편사항0.8620.0000.8410.2850.6940.7600.5280.6420.3540.6480.5830.0870.5211.0000.829
총합계0.9000.0000.9620.5750.6870.5770.8040.7510.6290.8010.5100.5600.5450.8291.000
2024-03-30T05:42:17.341615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.0990.9840.6330.5460.7590.6420.3920.7530.8120.7330.5530.4390.2740.958
-0.0991.0000.019-0.0500.0810.030-0.0090.0560.1400.0180.1040.1030.008-0.0040.039
교통0.9840.0191.0000.6620.6030.8010.6870.4500.8180.8530.7840.5700.4540.3090.987
도로0.633-0.0500.6621.0000.5490.5250.8140.5650.7370.8320.5070.3150.3570.1020.695
청소0.5460.0810.6030.5491.0000.7380.6440.7360.7600.7210.7530.2820.4500.6240.660
주택건축0.7590.0300.8010.5250.7381.0000.5690.5040.7740.7260.9260.3800.5690.6370.837
치수방재0.642-0.0090.6870.8140.6440.5691.0000.7350.8260.8770.5630.3770.3730.2460.728
가로정비0.3920.0560.4500.5650.7360.5040.7351.0000.6820.6500.5140.1740.2340.3810.523
보건0.7530.1400.8180.7370.7600.7740.8260.6821.0000.9270.8140.4390.4950.4730.861
공원녹지0.8120.0180.8530.8320.7210.7260.8770.6500.9271.0000.7320.4650.5110.3530.880
환경0.7330.1040.7840.5070.7530.9260.5630.5140.8140.7321.0000.3500.5510.6450.828
경제/산업0.5530.1030.5700.3150.2820.3800.3770.1740.4390.4650.3501.0000.1320.0640.536
소방안전0.4390.0080.4540.3570.4500.5690.3730.2340.4950.5110.5510.1321.0000.6480.457
기타 불편사항0.274-0.0040.3090.1020.6240.6370.2460.3810.4730.3530.6450.0640.6481.0000.354
총합계0.9580.0390.9870.6950.6600.8370.7280.5230.8610.8800.8280.5360.4570.3541.000

Missing values

2024-03-30T05:41:58.298900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T05:41:59.046017image/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
1252023154307145226504431903773108214579004370869
1262023254449140327196163785304142356779105371097
1272023365903193833254305931052725175910872099107800
128202346779218813200447503994546075316325011694321
1292023565565233937707528077681803103021772011492212
13020236635712557354249370659781206105521021011987543
13120237674672617349541967255194838571102109988513
13220238658942780386940055842493688951153509285947
13320239726402834422840753885925501091138070133105908
134202310772232877427930550570835101068126470109100706