Overview

Dataset statistics

Number of variables15
Number of observations136
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.1 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 9 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 2 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 (2.9%) zerosZeros
경제/산업 has 82 (60.3%) zerosZeros
소방안전 has 29 (21.3%) zerosZeros

Reproduction

Analysis started2024-03-30 05:38:53.909693
Analysis finished2024-03-30 05:40:14.644797
Duration1 minute and 20.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.7426
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:14.963423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2018
Q32021
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.2953308
Coefficient of variation (CV)0.0016331769
Kurtosis-1.1834159
Mean2017.7426
Median Absolute Deviation (MAD)3
Skewness-0.014884674
Sum274413
Variance10.859205
MonotonicityIncreasing
2024-03-30T05:40:15.322799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2013 12
8.8%
2014 12
8.8%
2015 12
8.8%
2016 12
8.8%
2017 12
8.8%
2018 12
8.8%
2019 12
8.8%
2020 12
8.8%
2021 12
8.8%
2022 12
8.8%
Other values (2) 16
11.8%
ValueCountFrequency (%)
2012 5
3.7%
2013 12
8.8%
2014 12
8.8%
2015 12
8.8%
2016 12
8.8%
2017 12
8.8%
2018 12
8.8%
2019 12
8.8%
2020 12
8.8%
2021 12
8.8%
ValueCountFrequency (%)
2023 11
8.1%
2022 12
8.8%
2021 12
8.8%
2020 12
8.8%
2019 12
8.8%
2018 12
8.8%
2017 12
8.8%
2016 12
8.8%
2015 12
8.8%
2014 12
8.8%


Real number (ℝ)

Distinct12
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5882353
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:15.685982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4565463
Coefficient of variation (CV)0.52465435
Kurtosis-1.2205236
Mean6.5882353
Median Absolute Deviation (MAD)3
Skewness-0.049888511
Sum896
Variance11.947712
MonotonicityNot monotonic
2024-03-30T05:40:16.150643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 12
8.8%
9 12
8.8%
10 12
8.8%
11 12
8.8%
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
16.2%
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
8.8%
9 12
8.8%
10 12
8.8%
ValueCountFrequency (%)
12 11
8.1%
11 12
8.8%
10 12
8.8%
9 12
8.8%
8 12
8.8%
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 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27863.89
Minimum46
Maximum77223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:17.038240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile354.5
Q17577.75
median27440
Q345541.75
95-th percentile65581.5
Maximum77223
Range77177
Interquartile range (IQR)37964

Descriptive statistics

Standard deviation21291.699
Coefficient of variation (CV)0.76413232
Kurtosis-1.0712572
Mean27863.89
Median Absolute Deviation (MAD)19207
Skewness0.3003034
Sum3789489
Variance4.5333643 × 108
MonotonicityNot monotonic
2024-03-30T05:40:17.551576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.7%
45510 1
 
0.7%
38404 1
 
0.7%
35082 1
 
0.7%
33380 1
 
0.7%
33170 1
 
0.7%
39210 1
 
0.7%
45637 1
 
0.7%
45930 1
 
0.7%
30922 1
 
0.7%
Other values (126) 126
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 

Distinct132
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1411.6985
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:18.278828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile380.5
Q1931
median1327
Q31860
95-th percentile2652.25
Maximum5000
Range4966
Interquartile range (IQR)929

Descriptive statistics

Standard deviation750.41751
Coefficient of variation (CV)0.53157065
Kurtosis3.0517643
Mean1411.6985
Median Absolute Deviation (MAD)475.5
Skewness0.9910564
Sum191991
Variance563126.43
MonotonicityNot monotonic
2024-03-30T05:40:18.889632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1726 2
 
1.5%
2019 2
 
1.5%
1166 2
 
1.5%
1318 2
 
1.5%
1972 1
 
0.7%
1377 1
 
0.7%
1388 1
 
0.7%
1792 1
 
0.7%
1831 1
 
0.7%
57 1
 
0.7%
Other values (122) 122
89.7%
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 

Distinct135
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2721.0441
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:19.398415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile33.5
Q11649.5
median3177.5
Q33740.75
95-th percentile4947.5
Maximum8515
Range8507
Interquartile range (IQR)2091.25

Descriptive statistics

Standard deviation1628.3937
Coefficient of variation (CV)0.59844444
Kurtosis0.13113834
Mean2721.0441
Median Absolute Deviation (MAD)764
Skewness-0.074871488
Sum370062
Variance2651666.1
MonotonicityNot monotonic
2024-03-30T05:40:19.960214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.5%
15 1
 
0.7%
3876 1
 
0.7%
3321 1
 
0.7%
3294 1
 
0.7%
3417 1
 
0.7%
3459 1
 
0.7%
3761 1
 
0.7%
4086 1
 
0.7%
3782 1
 
0.7%
Other values (125) 125
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 (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean399.00735
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:20.661699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.75
Q1166.25
median354.5
Q3495.25
95-th percentile973.5
Maximum3185
Range3183
Interquartile range (IQR)329

Descriptive statistics

Standard deviation424.91736
Coefficient of variation (CV)1.0649362
Kurtosis17.984345
Mean399.00735
Median Absolute Deviation (MAD)171.5
Skewness3.5460409
Sum54265
Variance180554.76
MonotonicityNot monotonic
2024-03-30T05:40:21.154203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.2%
9 3
 
2.2%
443 2
 
1.5%
302 2
 
1.5%
352 2
 
1.5%
2 2
 
1.5%
354 2
 
1.5%
466 2
 
1.5%
483 2
 
1.5%
36 2
 
1.5%
Other values (112) 114
83.8%
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 

Distinct122
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean254.67647
Minimum0
Maximum807
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:21.750047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17.75
Q1106.75
median224
Q3379.25
95-th percentile543
Maximum807
Range807
Interquartile range (IQR)272.5

Descriptive statistics

Standard deviation173.54085
Coefficient of variation (CV)0.68141691
Kurtosis0.064716043
Mean254.67647
Median Absolute Deviation (MAD)139.5
Skewness0.61030438
Sum34636
Variance30116.428
MonotonicityNot monotonic
2024-03-30T05:40:22.340713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
156 2
 
1.5%
102 2
 
1.5%
384 2
 
1.5%
304 2
 
1.5%
165 2
 
1.5%
207 2
 
1.5%
201 2
 
1.5%
127 2
 
1.5%
325 2
 
1.5%
181 2
 
1.5%
Other values (112) 116
85.3%
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 

Distinct134
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4556.6691
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:22.881058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile80.25
Q13518.25
median4558.5
Q35788.75
95-th percentile9624.5
Maximum12906
Range12895
Interquartile range (IQR)2270.5

Descriptive statistics

Standard deviation2603.4442
Coefficient of variation (CV)0.57134809
Kurtosis0.46771664
Mean4556.6691
Median Absolute Deviation (MAD)1220
Skewness0.31073436
Sum619707
Variance6777921.8
MonotonicityNot monotonic
2024-03-30T05:40:23.889227image/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 (124) 124
91.2%
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 

Distinct110
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean223.23529
Minimum0
Maximum1206
Zeros4
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:24.517529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q156
median156.5
Q3348
95-th percentile565.75
Maximum1206
Range1206
Interquartile range (IQR)292

Descriptive statistics

Standard deviation212.20274
Coefficient of variation (CV)0.95057882
Kurtosis2.5767423
Mean223.23529
Median Absolute Deviation (MAD)132.5
Skewness1.3517524
Sum30360
Variance45030.003
MonotonicityNot monotonic
2024-03-30T05:40:25.345093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
2.9%
66 4
 
2.9%
32 3
 
2.2%
258 3
 
2.2%
118 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 (100) 110
80.9%
ValueCountFrequency (%)
0 4
2.9%
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 

Distinct128
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean376.23529
Minimum3
Maximum1091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:25.854880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile28
Q1139.5
median276
Q3593.25
95-th percentile906.25
Maximum1091
Range1088
Interquartile range (IQR)453.75

Descriptive statistics

Standard deviation297.1679
Coefficient of variation (CV)0.78984588
Kurtosis-0.62353582
Mean376.23529
Median Absolute Deviation (MAD)185
Skewness0.7364961
Sum51168
Variance88308.759
MonotonicityNot monotonic
2024-03-30T05:40:26.303255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
276 2
 
1.5%
51 2
 
1.5%
70 2
 
1.5%
378 2
 
1.5%
91 2
 
1.5%
182 2
 
1.5%
693 2
 
1.5%
160 2
 
1.5%
706 1
 
0.7%
848 1
 
0.7%
Other values (118) 118
86.8%
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 

Distinct126
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1229.8088
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:26.966163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.75
Q1283.25
median1039.5
Q31552.5
95-th percentile3766.75
Maximum9985
Range9984
Interquartile range (IQR)1269.25

Descriptive statistics

Standard deviation1479.2615
Coefficient of variation (CV)1.2028386
Kurtosis13.516268
Mean1229.8088
Median Absolute Deviation (MAD)651.5
Skewness3.2027283
Sum167254
Variance2188214.5
MonotonicityNot monotonic
2024-03-30T05:40:27.764044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 3
 
2.2%
4 2
 
1.5%
641 2
 
1.5%
1549 2
 
1.5%
1153 2
 
1.5%
50 2
 
1.5%
1044 2
 
1.5%
1066 2
 
1.5%
34 2
 
1.5%
1760 1
 
0.7%
Other values (116) 116
85.3%
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%
Mean0.76470588
Minimum0
Maximum7
Zeros82
Zeros (%)60.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:28.336363image/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 deviation1.3729411
Coefficient of variation (CV)1.7953845
Kurtosis7.6877625
Mean0.76470588
Median Absolute Deviation (MAD)0
Skewness2.6476016
Sum104
Variance1.8849673
MonotonicityNot monotonic
2024-03-30T05:40:29.010983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 82
60.3%
1 33
24.3%
2 11
 
8.1%
4 4
 
2.9%
5 2
 
1.5%
7 2
 
1.5%
3 1
 
0.7%
6 1
 
0.7%
ValueCountFrequency (%)
0 82
60.3%
1 33
24.3%
2 11
 
8.1%
3 1
 
0.7%
4 4
 
2.9%
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
 
2.9%
3 1
 
0.7%
2 11
 
8.1%
1 33
24.3%
0 82
60.3%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9852941
Minimum0
Maximum65
Zeros29
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:29.486021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q312.25
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation9.1035079
Coefficient of variation (CV)1.1400341
Kurtosis10.22655
Mean7.9852941
Median Absolute Deviation (MAD)5
Skewness2.3152863
Sum1086
Variance82.873856
MonotonicityNot monotonic
2024-03-30T05:40:29.981423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 29
21.3%
2 10
 
7.4%
8 10
 
7.4%
1 9
 
6.6%
3 8
 
5.9%
5 8
 
5.9%
4 7
 
5.1%
6 6
 
4.4%
20 6
 
4.4%
11 5
 
3.7%
Other values (17) 38
27.9%
ValueCountFrequency (%)
0 29
21.3%
1 9
 
6.6%
2 10
 
7.4%
3 8
 
5.9%
4 7
 
5.1%
5 8
 
5.9%
6 6
 
4.4%
7 4
 
2.9%
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
2.9%
22 1
 
0.7%
21 3
2.2%
20 6
4.4%
18 2
 
1.5%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct133
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2282.1544
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:30.811244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile52
Q1289.25
median2397.5
Q33435.5
95-th percentile5793.25
Maximum7847
Range7831
Interquartile range (IQR)3146.25

Descriptive statistics

Standard deviation1898.349
Coefficient of variation (CV)0.8318232
Kurtosis-0.28894346
Mean2282.1544
Median Absolute Deviation (MAD)1417.5
Skewness0.57390627
Sum310373
Variance3603728.9
MonotonicityNot monotonic
2024-03-30T05:40:31.335327image/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%
2998 1
 
0.7%
2782 1
 
0.7%
2688 1
 
0.7%
2385 1
 
0.7%
2533 1
 
0.7%
2870 1
 
0.7%
3567 1
 
0.7%
Other values (123) 123
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 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44072.846
Minimum230
Maximum107800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-30T05:40:31.830201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1446.25
Q119193
median46057.5
Q365712
95-th percentile92739.25
Maximum107800
Range107570
Interquartile range (IQR)46519

Descriptive statistics

Standard deviation28766.056
Coefficient of variation (CV)0.65269342
Kurtosis-0.91144507
Mean44072.846
Median Absolute Deviation (MAD)22399
Skewness0.094382093
Sum5993907
Variance8.27486 × 108
MonotonicityNot monotonic
2024-03-30T05:40:32.228992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.7%
69507 1
 
0.7%
54987 1
 
0.7%
50606 1
 
0.7%
49544 1
 
0.7%
50517 1
 
0.7%
57806 1
 
0.7%
67111 1
 
0.7%
68704 1
 
0.7%
55495 1
 
0.7%
Other values (126) 126
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

2024-03-30T05:40:07.574847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:55.812090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:01.935144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:06.394198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:10.586382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:14.847148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:19.885607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:24.485607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:29.581890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:34.719285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:39.766104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:44.193156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:49.367772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:54.921837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:00.207166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:07.983160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:56.134871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:02.324623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:06.637513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:10.840856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:15.224203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:20.124090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:24.745830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:29.934103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:35.062116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:40.079783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:44.555376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:50.053135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:55.269996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:00.601428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:08.515789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:56.555269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:02.631545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:06.916209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:11.093528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:15.518361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:20.358385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:25.007336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:30.179682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:35.577965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:40.472229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:44.861019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:50.389609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:55.635223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:00.963005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:09.019226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:57.045577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:02.988403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:07.193137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:11.371302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:15.900147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:20.752109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:25.417798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:30.532093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:36.114740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:40.753322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:45.233693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:50.755595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:56.088302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:01.698195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:09.491413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:57.491462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:03.333831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:07.438515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:11.610866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:16.175655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:21.148801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:25.782490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:30.906357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:36.374989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:41.004221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:45.488655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:51.124830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:56.374607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:02.208198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:09.821144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:57.925946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:03.647454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:07.686871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:11.852815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:16.463837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:21.406642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:26.084558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:31.269859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:36.668629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:41.235628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:45.884466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:51.530370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:56.711325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:02.660393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:10.342773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:58.481009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:03.915758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:07.969090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:12.131314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:16.912959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:21.924100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:26.430784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:31.640710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:37.000754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:41.599376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:46.236418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:51.980591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:57.006680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:03.037383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:10.738775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:58.976522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:04.195396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:08.251402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:12.413062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:17.213986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:22.220562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:26.824950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:32.016467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:37.334719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:41.972477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:46.583151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:52.327070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:57.396869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:03.558678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:10.997201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:59.348113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:04.472333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:08.523465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:12.662694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:17.456676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:22.538476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:27.136015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:32.298523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:37.595319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:42.303636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:46.947753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:52.673033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:57.746315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:04.032327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:11.320980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:38:59.613082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:04.807776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:08.925966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:12.962806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:17.758517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:22.834864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:27.481855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:32.552278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:37.929721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:42.549251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:47.228659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:52.919075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:58.011229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:04.577771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:11.575495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:00.015533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:05.045383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:09.237930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:13.236057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:18.007910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:23.110910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:27.862779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:32.802825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:38.239561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:42.799265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:47.711161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:53.241935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:58.350984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:04.930468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:11.881986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:00.348773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:05.284343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:09.493106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:13.488567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:18.426736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:23.342608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:28.211471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:33.081033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:38.541886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:43.111470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:48.043766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:53.575927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:58.589102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:05.323332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:12.209634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:00.738694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:05.532956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:09.746786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:13.756109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:18.758937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:23.601977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:28.429730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:33.412978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:38.805897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:43.380575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:48.388353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:53.902483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:59.025636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:05.907927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:12.609653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:01.088125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:05.851464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:10.005823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:14.002790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:19.056790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:23.835478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:28.725904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:33.890799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:39.071012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:43.674553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:48.662727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:54.272715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:59.433774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:06.652135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:12.983561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:01.575903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:06.179696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:10.289967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:14.383953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:19.511454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:24.103623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:29.143803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:34.357842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:39.444987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:43.944313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:49.005773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:54.634516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:39:59.885748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:40:07.154809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T05:40:32.525678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9410.5350.6860.6060.6280.7640.4130.7380.5610.3760.5740.8620.900
0.0001.0000.0000.3770.1650.1590.4840.5620.3670.4060.2670.1720.0000.0000.000
교통0.9410.0001.0000.5890.6570.6040.7740.7220.6020.8140.5530.7240.6190.8370.963
도로0.5350.3770.5891.0000.4040.3930.6780.3580.8290.6970.2620.4200.2490.2740.578
청소0.6860.1650.6570.4041.0000.6040.4500.6430.4680.5990.6290.0000.4540.6910.687
주택건축0.6060.1590.6040.3930.6041.0000.4030.3220.4400.3930.9790.0000.4070.7590.570
치수방재0.6280.4840.7740.6780.4500.4031.0000.8080.7200.8630.3930.5680.2880.5130.800
가로정비0.7640.5620.7220.3580.6430.3220.8081.0000.3990.6970.2830.2010.0870.6380.748
보건0.4130.3670.6020.8290.4680.4400.7200.3991.0000.7310.5350.5590.4130.3440.618
공원녹지0.7380.4060.8140.6970.5990.3930.8630.6970.7311.0000.4940.5400.5360.6300.797
환경0.5610.2670.5530.2620.6290.9790.3930.2830.5350.4941.0000.0000.5090.5850.501
경제/산업0.3760.1720.7240.4200.0000.0000.5680.2010.5590.5400.0001.0000.0000.0810.563
소방안전0.5740.0000.6190.2490.4540.4070.2880.0870.4130.5360.5090.0001.0000.5230.538
기타 불편사항0.8620.0000.8370.2740.6910.7590.5130.6380.3440.6300.5850.0810.5231.0000.822
총합계0.9000.0000.9630.5780.6870.5700.8000.7480.6180.7970.5010.5630.5380.8221.000
2024-03-30T05:40:32.959255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.0820.9840.6330.5450.7520.6470.3920.7500.8130.7240.5620.4120.2540.959
-0.0821.0000.032-0.0450.0870.0300.0010.0590.1420.0240.1000.116-0.006-0.0160.051
교통0.9840.0321.0000.6630.6010.7940.6910.4500.8170.8530.7760.5780.4290.2890.988
도로0.633-0.0450.6631.0000.5490.5240.8120.5650.7380.8330.5050.3210.3460.0960.695
청소0.5450.0870.6010.5491.0000.7330.6440.7350.7580.7190.7470.2870.4350.6110.658
주택건축0.7520.0300.7940.5240.7331.0000.5640.5000.7720.7240.9260.3770.5650.6320.831
치수방재0.6470.0010.6910.8120.6440.5641.0000.7330.8250.8760.5570.3860.3530.2310.731
가로정비0.3920.0590.4500.5650.7350.5000.7331.0000.6800.6470.5090.1770.2250.3720.522
보건0.7500.1420.8170.7380.7580.7720.8250.6801.0000.9270.8120.4400.4840.4640.859
공원녹지0.8130.0240.8530.8330.7190.7240.8760.6470.9271.0000.7290.4700.4960.3410.880
환경0.7240.1000.7760.5050.7470.9260.5570.5090.8120.7291.0000.3460.5490.6420.820
경제/산업0.5620.1160.5780.3210.2870.3770.3860.1770.4400.4700.3461.0000.1130.0480.544
소방안전0.412-0.0060.4290.3460.4350.5650.3530.2250.4840.4960.5490.1131.0000.6550.432
기타 불편사항0.254-0.0160.2890.0960.6110.6320.2310.3720.4640.3410.6420.0480.6551.0000.334
총합계0.9590.0510.9880.6950.6580.8310.7310.5220.8590.8800.8200.5440.4320.3341.000

Missing values

2024-03-30T05:40:13.480348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T05:40:14.331016image/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
1262023254449140327196163785304142356779105371097
1272023365903193833254305931052725175910872099107800
128202346779218813200447503994546075316325011694321
1292023565565233937707528077681803103021772011492212
13020236635712557354249370659781206105521021011987543
13120237674672617349541967255194838571102109988513
13220238658942780386940055842493688951153509285947
13320239726402834422840753885925501091138070133105908
134202310772232877427930550570835101068126470109100706
135202311584241722371535442652872705527902014076452