Overview

Dataset statistics

Number of variables15
Number of observations131
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.4 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 10 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 11 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 1 other fieldsHigh correlation
소방안전 is highly overall correlated with 년도 and 8 other fieldsHigh correlation
기타 불편사항 is highly overall correlated with 청소 and 4 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 (3.1%) zerosZeros
경제/산업 has 82 (62.6%) zerosZeros
소방안전 has 24 (18.3%) zerosZeros

Reproduction

Analysis started2024-03-30 05:28:06.718412
Analysis finished2024-03-30 05:29:26.145432
Duration1 minute and 19.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.542
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:26.304296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2018
Q32020
95-th percentile2022
Maximum2023
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.1895491
Coefficient of variation (CV)0.0015809084
Kurtosis-1.1591931
Mean2017.542
Median Absolute Deviation (MAD)3
Skewness-5.0923046 × 10-5
Sum264298
Variance10.173224
MonotonicityIncreasing
2024-03-30T05:29:26.735907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2013 12
9.2%
2014 12
9.2%
2015 12
9.2%
2016 12
9.2%
2017 12
9.2%
2018 12
9.2%
2019 12
9.2%
2020 12
9.2%
2021 12
9.2%
2022 12
9.2%
Other values (2) 11
8.4%
ValueCountFrequency (%)
2012 5
3.8%
2013 12
9.2%
2014 12
9.2%
2015 12
9.2%
2016 12
9.2%
2017 12
9.2%
2018 12
9.2%
2019 12
9.2%
2020 12
9.2%
2021 12
9.2%
ValueCountFrequency (%)
2023 6
4.6%
2022 12
9.2%
2021 12
9.2%
2020 12
9.2%
2019 12
9.2%
2018 12
9.2%
2017 12
9.2%
2016 12
9.2%
2015 12
9.2%
2014 12
9.2%


Real number (ℝ)

Distinct12
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4961832
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:27.124214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.5
median6
Q39.5
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4782269
Coefficient of variation (CV)0.53542623
Kurtosis-1.2307427
Mean6.4961832
Median Absolute Deviation (MAD)3
Skewness0.0033198527
Sum851
Variance12.098062
MonotonicityNot monotonic
2024-03-30T05:29:27.449231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 11
8.4%
9 11
8.4%
10 11
8.4%
11 11
8.4%
12 11
8.4%
1 11
8.4%
2 11
8.4%
3 11
8.4%
4 11
8.4%
5 11
8.4%
Other values (2) 21
16.0%
ValueCountFrequency (%)
1 11
8.4%
2 11
8.4%
3 11
8.4%
4 11
8.4%
5 11
8.4%
6 11
8.4%
7 10
7.6%
8 11
8.4%
9 11
8.4%
10 11
8.4%
ValueCountFrequency (%)
12 11
8.4%
11 11
8.4%
10 11
8.4%
9 11
8.4%
8 11
8.4%
7 10
7.6%
6 11
8.4%
5 11
8.4%
4 11
8.4%
3 11
8.4%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26319.397
Minimum46
Maximum67792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:28.050116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile320
Q17271
median23941
Q341640.5
95-th percentile59834.5
Maximum67792
Range67746
Interquartile range (IQR)34369.5

Descriptive statistics

Standard deviation20095.557
Coefficient of variation (CV)0.76352651
Kurtosis-1.1664924
Mean26319.397
Median Absolute Deviation (MAD)17352
Skewness0.26336943
Sum3447841
Variance4.0383143 × 108
MonotonicityNot monotonic
2024-03-30T05:29:28.683877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.8%
41523 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%
33380 1
 
0.8%
Other values (121) 121
92.4%
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%
65903 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%
58486 1
0.8%
56818 1
0.8%

도로
Real number (ℝ)

HIGH CORRELATION 

Distinct127
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1367.6412
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:29.300238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile333
Q1905.5
median1307
Q31812
95-th percentile2439
Maximum5000
Range4966
Interquartile range (IQR)906.5

Descriptive statistics

Standard deviation724.17834
Coefficient of variation (CV)0.529509
Kurtosis4.1070179
Mean1367.6412
Median Absolute Deviation (MAD)455
Skewness1.1181582
Sum179161
Variance524434.26
MonotonicityNot monotonic
2024-03-30T05:29:29.919968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019 2
 
1.5%
1166 2
 
1.5%
1318 2
 
1.5%
1726 2
 
1.5%
1377 1
 
0.8%
1983 1
 
0.8%
1932 1
 
0.8%
1972 1
 
0.8%
57 1
 
0.8%
1662 1
 
0.8%
Other values (117) 117
89.3%
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%
2758 1
0.8%
2557 1
0.8%
2531 1
0.8%
2483 1
0.8%
2395 1
0.8%
2350 1
0.8%
2339 1
0.8%

청소
Real number (ℝ)

HIGH CORRELATION 

Distinct130
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2675.3893
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:30.515940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile32
Q11488
median3082
Q33713.5
95-th percentile5013
Maximum8515
Range8507
Interquartile range (IQR)2225.5

Descriptive statistics

Standard deviation1641.0573
Coefficient of variation (CV)0.61339009
Kurtosis0.13406875
Mean2675.3893
Median Absolute Deviation (MAD)835
Skewness-0.0091930062
Sum350476
Variance2693069
MonotonicityNot monotonic
2024-03-30T05:29:31.088211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.5%
15 1
 
0.8%
3417 1
 
0.8%
5966 1
 
0.8%
5664 1
 
0.8%
5254 1
 
0.8%
3785 1
 
0.8%
3321 1
 
0.8%
3294 1
 
0.8%
3459 1
 
0.8%
Other values (120) 120
91.6%
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 

Distinct118
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean399.84733
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:31.592091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.5
Q1143
median354
Q3497
95-th percentile982
Maximum3185
Range3183
Interquartile range (IQR)354

Descriptive statistics

Standard deviation432.9103
Coefficient of variation (CV)1.082689
Kurtosis17.227826
Mean399.84733
Median Absolute Deviation (MAD)176
Skewness3.4783625
Sum52380
Variance187411.33
MonotonicityNot monotonic
2024-03-30T05:29:32.207788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.3%
9 3
 
2.3%
483 2
 
1.5%
352 2
 
1.5%
602 2
 
1.5%
466 2
 
1.5%
36 2
 
1.5%
174 2
 
1.5%
302 2
 
1.5%
2 2
 
1.5%
Other values (108) 109
83.2%
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 

Distinct117
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean243.79389
Minimum0
Maximum807
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:32.938052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.5
Q1102.5
median216
Q3367
95-th percentile496
Maximum807
Range807
Interquartile range (IQR)264.5

Descriptive statistics

Standard deviation166.68149
Coefficient of variation (CV)0.68369838
Kurtosis0.3905753
Mean243.79389
Median Absolute Deviation (MAD)133
Skewness0.67190193
Sum31937
Variance27782.719
MonotonicityNot monotonic
2024-03-30T05:29:33.739574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181 2
 
1.5%
102 2
 
1.5%
156 2
 
1.5%
304 2
 
1.5%
207 2
 
1.5%
384 2
 
1.5%
325 2
 
1.5%
201 2
 
1.5%
165 2
 
1.5%
127 2
 
1.5%
Other values (107) 111
84.7%
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%
646 1
0.8%
593 1
0.8%
510 1
0.8%
503 1
0.8%
489 1
0.8%
477 1
0.8%
464 1
0.8%

가로정비
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4496.0076
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:34.355435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile77.5
Q13261
median4533
Q35757.5
95-th percentile9685
Maximum12906
Range12895
Interquartile range (IQR)2496.5

Descriptive statistics

Standard deviation2616.9816
Coefficient of variation (CV)0.58206786
Kurtosis0.50938758
Mean4496.0076
Median Absolute Deviation (MAD)1252
Skewness0.35230254
Sum588977
Variance6848592.4
MonotonicityNot monotonic
2024-03-30T05:29:35.023065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
516 2
 
1.5%
4281 2
 
1.5%
11 1
 
0.8%
4602 1
 
0.8%
7263 1
 
0.8%
5800 1
 
0.8%
4761 1
 
0.8%
4743 1
 
0.8%
4663 1
 
0.8%
4203 1
 
0.8%
Other values (119) 119
90.8%
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 

Distinct106
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215.10687
Minimum0
Maximum1206
Zeros4
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:35.884286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q144.5
median148
Q3328.5
95-th percentile571.5
Maximum1206
Range1206
Interquartile range (IQR)284

Descriptive statistics

Standard deviation211.05531
Coefficient of variation (CV)0.98116488
Kurtosis3.0615957
Mean215.10687
Median Absolute Deviation (MAD)123
Skewness1.4792106
Sum28179
Variance44544.342
MonotonicityNot monotonic
2024-03-30T05:29:36.602602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
3.1%
66 4
 
3.1%
32 3
 
2.3%
258 3
 
2.3%
378 2
 
1.5%
300 2
 
1.5%
149 2
 
1.5%
346 2
 
1.5%
42 2
 
1.5%
118 2
 
1.5%
Other values (96) 105
80.2%
ValueCountFrequency (%)
0 4
3.1%
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 

Distinct123
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean356.52672
Minimum3
Maximum1055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:38.156843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile26
Q1131.5
median273
Q3542.5
95-th percentile884.5
Maximum1055
Range1052
Interquartile range (IQR)411

Descriptive statistics

Standard deviation282.16507
Coefficient of variation (CV)0.79142757
Kurtosis-0.53336433
Mean356.52672
Median Absolute Deviation (MAD)176
Skewness0.77591804
Sum46705
Variance79617.128
MonotonicityNot monotonic
2024-03-30T05:29:39.655905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160 2
 
1.5%
693 2
 
1.5%
276 2
 
1.5%
70 2
 
1.5%
51 2
 
1.5%
91 2
 
1.5%
182 2
 
1.5%
378 2
 
1.5%
264 1
 
0.8%
539 1
 
0.8%
Other values (113) 113
86.3%
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%
885 1
0.8%
884 1
0.8%
879 1
0.8%
875 1
0.8%

환경
Real number (ℝ)

HIGH CORRELATION 

Distinct122
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1233.3206
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:40.372337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.5
Q1239
median1035
Q31578
95-th percentile3874.5
Maximum9985
Range9984
Interquartile range (IQR)1339

Descriptive statistics

Standard deviation1506.8254
Coefficient of variation (CV)1.2217629
Kurtosis12.922551
Mean1233.3206
Median Absolute Deviation (MAD)692
Skewness3.1415947
Sum161565
Variance2270522.7
MonotonicityNot monotonic
2024-03-30T05:29:41.216393image/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%
1066 2
 
1.5%
1549 2
 
1.5%
34 2
 
1.5%
641 2
 
1.5%
4 2
 
1.5%
779 1
 
0.8%
2098 1
 
0.8%
Other values (112) 112
85.5%
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%
Mean0.6259542
Minimum0
Maximum6
Zeros82
Zeros (%)62.6%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:41.661280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2.5
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0907716
Coefficient of variation (CV)1.7425742
Kurtosis7.1679258
Mean0.6259542
Median Absolute Deviation (MAD)0
Skewness2.4884374
Sum82
Variance1.1897827
MonotonicityNot monotonic
2024-03-30T05:29:42.100052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 82
62.6%
1 32
 
24.4%
2 10
 
7.6%
4 4
 
3.1%
3 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
ValueCountFrequency (%)
0 82
62.6%
1 32
 
24.4%
2 10
 
7.6%
3 1
 
0.8%
4 4
 
3.1%
5 1
 
0.8%
6 1
 
0.8%
ValueCountFrequency (%)
6 1
 
0.8%
5 1
 
0.8%
4 4
 
3.1%
3 1
 
0.8%
2 10
 
7.6%
1 32
 
24.4%
0 82
62.6%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2900763
Minimum0
Maximum65
Zeros24
Zeros (%)18.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:42.570595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5
median5
Q313
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation9.1386656
Coefficient of variation (CV)1.1023621
Kurtosis10.200026
Mean8.2900763
Median Absolute Deviation (MAD)5
Skewness2.3024635
Sum1086
Variance83.515208
MonotonicityNot monotonic
2024-03-30T05:29:43.035232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 24
18.3%
2 10
 
7.6%
8 10
 
7.6%
1 9
 
6.9%
3 8
 
6.1%
5 8
 
6.1%
4 7
 
5.3%
6 6
 
4.6%
20 6
 
4.6%
11 5
 
3.8%
Other values (17) 38
29.0%
ValueCountFrequency (%)
0 24
18.3%
1 9
 
6.9%
2 10
7.6%
3 8
 
6.1%
4 7
 
5.3%
5 8
 
6.1%
6 6
 
4.6%
7 4
 
3.1%
8 10
7.6%
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
3.1%
22 1
 
0.8%
21 3
2.3%
20 6
4.6%
18 2
 
1.5%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2364.8855
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:43.401981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile51
Q1407
median2533
Q33441
95-th percentile5826.5
Maximum7847
Range7831
Interquartile range (IQR)3034

Descriptive statistics

Standard deviation1885.3964
Coefficient of variation (CV)0.79724638
Kurtosis-0.27872847
Mean2364.8855
Median Absolute Deviation (MAD)1240
Skewness0.53428873
Sum309800
Variance3554719.6
MonotonicityNot monotonic
2024-03-30T05:29:43.880274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3071 2
 
1.5%
99 2
 
1.5%
2385 1
 
0.8%
2881 1
 
0.8%
3434 1
 
0.8%
3254 1
 
0.8%
2782 1
 
0.8%
2688 1
 
0.8%
16 1
 
0.8%
3311 1
 
0.8%
Other values (119) 119
90.8%
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 

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42262.45
Minimum230
Maximum107800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:29:44.317333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1353.5
Q118515.5
median43389
Q363886
95-th percentile85310
Maximum107800
Range107570
Interquartile range (IQR)45370.5

Descriptive statistics

Standard deviation27661.911
Coefficient of variation (CV)0.65452691
Kurtosis-0.90528013
Mean42262.45
Median Absolute Deviation (MAD)22707
Skewness0.083650793
Sum5536381
Variance7.6518132 × 108
MonotonicityNot monotonic
2024-03-30T05:29:44.848759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.8%
66096 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%
49544 1
 
0.8%
Other values (121) 121
92.4%
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%
87543 1
0.8%
83077 1
0.8%
81979 1
0.8%
79948 1
0.8%

Interactions

2024-03-30T05:29:19.731851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:08.187332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:13.109810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:18.106985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:22.755198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:26.827930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:31.974027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:38.197395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:43.371394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:48.371543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:53.451789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:58.389550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:03.797940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:08.894530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:14.326452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:20.030137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:08.540628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:13.423816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:18.433654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:23.019002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:27.072034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:32.339668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:38.528489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:43.629508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:48.612267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:53.727032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:58.722235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:04.149250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:09.170353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:14.596918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:20.394404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:08.911119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:13.912333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:18.765194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:23.308064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:27.385462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:32.665163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:38.798750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:43.936527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:48.893842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:54.037804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:58.953114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:04.505674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:09.468933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:14.933383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:20.701289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:09.285654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:14.169299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:19.063590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:23.576410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:27.696542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:32.963792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:39.206175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:44.321759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:49.375857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:54.558297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:59.278695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:04.815703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:09.865635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:15.356906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:21.063145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:09.567166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:14.471708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:19.393992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:23.813362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:28.043995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:33.220964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:39.525842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:44.587730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:49.668472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:54.865392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:59.683377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:05.064299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:10.330033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:15.787678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:21.350182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:09.973423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:14.808311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:19.751134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:24.041628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:28.318086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:33.445761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:39.811590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:44.812615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:49.984923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:55.218638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:59.910569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:05.475569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:10.640602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:16.097784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:21.648285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:10.387708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:15.233790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:20.020234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:24.311860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:28.636551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:33.708562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:40.105309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:45.123976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:50.240630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:55.492372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:00.161294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:05.799826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:11.063102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:16.506215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:22.144817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:10.702504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:15.510341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:20.592191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:24.644777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:28.993119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:34.006938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:40.589480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:45.415419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:50.736288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:55.776934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:00.523087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:06.073894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:11.331105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:16.936164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:22.661313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:11.052171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:15.805900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:20.978411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:24.882396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:29.369544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:34.362906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:40.971976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:45.771062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:51.157949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:56.026492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:00.875257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:06.351188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:11.816842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:17.294703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:22.960092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:11.308526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:16.161958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:21.245165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:25.110107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:29.675607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:34.649481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:41.412118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:46.108076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:51.490319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:56.325963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:01.127226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:06.772245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:12.187896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:17.568950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:23.243789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:11.571271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:16.508432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:21.522656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:25.344344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:30.064916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:35.160646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:41.756925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:46.639911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:51.863034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:56.622422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:01.540720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:07.012259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:12.505729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:17.933932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:23.502110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:11.875148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:16.839077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:21.742630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:25.641992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:30.565866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:35.754293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:42.065136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:46.944135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:52.186641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:57.000136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:01.879304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:07.277740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:12.865161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:18.252510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:23.860764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:12.254024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:17.098968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:21.997383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:25.898070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:31.007905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:36.383838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:42.382572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:47.252599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:52.497713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:57.371738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:02.472409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:07.639148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:13.266376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:18.644969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:24.152549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:12.529261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:17.418983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:22.234361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:26.303226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:31.352854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:37.279481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:42.777617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:47.627428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:52.759380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:57.687025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:02.857163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:07.989141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:13.625491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:18.982975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:24.520912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:12.872652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:17.789764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:22.515020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:26.577442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:31.680192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:37.783618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:43.120322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:47.991593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:53.179228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:28:58.097259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:03.356913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:08.368724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:14.049732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:29:19.414180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T05:29:45.163432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9630.5040.6970.6070.5850.7740.4040.7560.5560.3500.5790.8630.895
0.0001.0000.0000.3830.1970.1700.5150.5360.3870.4600.2610.1770.0000.0000.000
교통0.9630.0001.0000.5210.6770.6240.7400.7340.6280.7730.5530.4670.6560.8880.959
도로0.5040.3830.5211.0000.3840.3930.6590.3460.8300.6570.2940.0000.2720.2760.535
청소0.6970.1970.6770.3841.0000.6200.4520.6420.4610.6340.6430.0000.4740.7100.692
주택건축0.6070.1700.6240.3930.6201.0000.3900.3150.4520.4260.9790.0000.4260.7620.593
치수방재0.5850.5150.7400.6590.4520.3901.0000.8190.7210.8460.3870.4840.2920.5250.808
가로정비0.7740.5360.7340.3460.6420.3150.8191.0000.3960.7000.2680.2090.1210.6710.756
보건0.4040.3870.6280.8300.4610.4520.7210.3961.0000.7660.5340.2990.4690.4220.671
공원녹지0.7560.4600.7730.6570.6340.4260.8460.7000.7661.0000.5480.4930.5740.6380.785
환경0.5560.2610.5530.2940.6430.9790.3870.2680.5340.5481.0000.0000.5260.5940.503
경제/산업0.3500.1770.4670.0000.0000.0000.4840.2090.2990.4930.0001.0000.0000.1570.478
소방안전0.5790.0000.6560.2720.4740.4260.2920.1210.4690.5740.5260.0001.0000.5100.553
기타 불편사항0.8630.0000.8880.2760.7100.7620.5250.6710.4220.6380.5940.1570.5101.0000.837
총합계0.8950.0000.9590.5350.6920.5930.8080.7560.6710.7850.5030.4780.5530.8371.000
2024-03-30T05:29:45.821446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.1300.9830.6010.5360.7840.6130.3800.7400.7980.7510.5140.5550.3670.955
-0.1301.000-0.008-0.0760.0650.033-0.0280.0460.130-0.0040.1010.0760.0350.0230.015
교통0.983-0.0081.0000.6320.5940.8290.6610.4400.8090.8400.8030.5320.5710.4050.986
도로0.601-0.0760.6321.0000.5320.5360.7990.5620.7200.8190.5080.2540.4590.1730.669
청소0.5360.0650.5940.5321.0000.7590.6370.7390.7620.7170.7640.2450.5240.7010.656
주택건축0.7840.0330.8290.5360.7591.0000.5840.5200.7900.7470.9310.3920.5990.6720.865
치수방재0.613-0.0280.6610.7990.6370.5841.0000.7410.8190.8690.5700.3230.4770.3310.706
가로정비0.3800.0460.4400.5620.7390.5200.7411.0000.6860.6510.5230.1450.2820.4280.516
보건0.7400.1300.8090.7200.7620.7900.8190.6861.0000.9240.8240.4020.5870.5570.855
공원녹지0.798-0.0040.8400.8190.7170.7470.8690.6510.9241.0000.7440.4170.6240.4440.871
환경0.7510.1010.8030.5080.7640.9310.5700.5230.8240.7441.0000.3470.5900.6870.847
경제/산업0.5140.0760.5320.2540.2450.3920.3230.1450.4020.4170.3471.0000.2230.1410.495
소방안전0.5550.0350.5710.4590.5240.5990.4770.2820.5870.6240.5900.2231.0000.6180.573
기타 불편사항0.3670.0230.4050.1730.7010.6720.3310.4280.5570.4440.6870.1410.6181.0000.453
총합계0.9550.0150.9860.6690.6560.8650.7060.5160.8550.8710.8470.4950.5730.4531.000

Missing values

2024-03-30T05:29:25.040348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T05:29:25.851751image/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
12120229600882328345446638442367269641593112215979948
1222022106563150002941483333490970766819230016694613
1232022116249715502830502296521034650019831068104091
124202212523321615209635216536001492001781205473449
1252023154307145226504431903773108214579004370869
1262023254449140327196163785304142356779105371097
1272023365903193833254305931052725175910872099107800
128202346779218813200447503994546075316325011694321
1292023565565233937707528077681803103021772011492212
13020236635712557354249370659781206105521021011987543