Overview

Dataset statistics

Number of variables15
Number of observations138
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.3 KiB
Average record size in memory135.9 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 8 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 10 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 83 (60.1%) zerosZeros
소방안전 has 31 (22.5%) zerosZeros

Reproduction

Analysis started2024-04-20 16:56:31.254783
Analysis finished2024-04-20 16:57:23.468355
Duration52.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.8261
Minimum2012
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:23.579032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2018
Q32021
95-th percentile2023
Maximum2024
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.343832
Coefficient of variation (CV)0.0016571458
Kurtosis-1.1789517
Mean2017.8261
Median Absolute Deviation (MAD)3
Skewness-0.012690436
Sum278460
Variance11.181212
MonotonicityIncreasing
2024-04-21T01:57:23.956570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2013 12
8.7%
2014 12
8.7%
2015 12
8.7%
2016 12
8.7%
2017 12
8.7%
2018 12
8.7%
2019 12
8.7%
2020 12
8.7%
2021 12
8.7%
2022 12
8.7%
Other values (3) 18
13.0%
ValueCountFrequency (%)
2012 5
3.6%
2013 12
8.7%
2014 12
8.7%
2015 12
8.7%
2016 12
8.7%
2017 12
8.7%
2018 12
8.7%
2019 12
8.7%
2020 12
8.7%
2021 12
8.7%
ValueCountFrequency (%)
2024 1
 
0.7%
2023 12
8.7%
2022 12
8.7%
2021 12
8.7%
2020 12
8.7%
2019 12
8.7%
2018 12
8.7%
2017 12
8.7%
2016 12
8.7%
2015 12
8.7%


Real number (ℝ)

Distinct12
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5869565
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:24.528016image/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 deviation3.494998
Coefficient of variation (CV)0.53059376
Kurtosis-1.2328022
Mean6.5869565
Median Absolute Deviation (MAD)3
Skewness-0.049209998
Sum909
Variance12.215011
MonotonicityNot monotonic
2024-04-21T01:57:24.882459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 12
8.7%
9 12
8.7%
10 12
8.7%
11 12
8.7%
12 12
8.7%
1 12
8.7%
2 11
8.0%
3 11
8.0%
4 11
8.0%
5 11
8.0%
Other values (2) 22
15.9%
ValueCountFrequency (%)
1 12
8.7%
2 11
8.0%
3 11
8.0%
4 11
8.0%
5 11
8.0%
6 11
8.0%
7 11
8.0%
8 12
8.7%
9 12
8.7%
10 12
8.7%
ValueCountFrequency (%)
12 12
8.7%
11 12
8.7%
10 12
8.7%
9 12
8.7%
8 12
8.7%
7 11
8.0%
6 11
8.0%
5 11
8.0%
4 11
8.0%
3 11
8.0%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28277.978
Minimum46
Maximum77223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:25.272688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile368.3
Q17734
median27816.5
Q345856.75
95-th percentile65574.9
Maximum77223
Range77177
Interquartile range (IQR)38122.75

Descriptive statistics

Standard deviation21412.081
Coefficient of variation (CV)0.75719984
Kurtosis-1.1194617
Mean28277.978
Median Absolute Deviation (MAD)19990
Skewness0.26733449
Sum3902361
Variance4.584772 × 108
MonotonicityNot monotonic
2024-04-21T01:57:25.723093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.7%
45930 1
 
0.7%
35082 1
 
0.7%
33380 1
 
0.7%
33170 1
 
0.7%
39210 1
 
0.7%
45637 1
 
0.7%
45510 1
 
0.7%
42374 1
 
0.7%
48473 1
 
0.7%
Other values (128) 128
92.8%
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 

Distinct133
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1419.7536
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:26.084924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile399.5
Q1938.5
median1337.5
Q31874
95-th percentile2638.15
Maximum5000
Range4966
Interquartile range (IQR)935.5

Descriptive statistics

Standard deviation748.16108
Coefficient of variation (CV)0.52696543
Kurtosis2.9963748
Mean1419.7536
Median Absolute Deviation (MAD)474.5
Skewness0.96013149
Sum195926
Variance559745
MonotonicityNot monotonic
2024-04-21T01:57:26.336719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2019 2
 
1.4%
1166 2
 
1.4%
1803 2
 
1.4%
1318 2
 
1.4%
1726 2
 
1.4%
57 1
 
0.7%
2111 1
 
0.7%
1388 1
 
0.7%
1792 1
 
0.7%
1831 1
 
0.7%
Other values (123) 123
89.1%
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 

Distinct137
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2724.1667
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:26.599001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile34.1
Q11690
median3138
Q33730.25
95-th percentile4921.3
Maximum8515
Range8507
Interquartile range (IQR)2040.25

Descriptive statistics

Standard deviation1616.6742
Coefficient of variation (CV)0.59345641
Kurtosis0.17637283
Mean2724.1667
Median Absolute Deviation (MAD)750.5
Skewness-0.081221035
Sum375935
Variance2613635.4
MonotonicityNot monotonic
2024-04-21T01:57:27.035306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.4%
15 1
 
0.7%
3782 1
 
0.7%
3294 1
 
0.7%
3417 1
 
0.7%
3459 1
 
0.7%
3761 1
 
0.7%
4086 1
 
0.7%
3876 1
 
0.7%
3708 1
 
0.7%
Other values (127) 127
92.0%
ValueCountFrequency (%)
8 1
0.7%
9 1
0.7%
15 1
0.7%
17 1
0.7%
22 2
1.4%
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 

Distinct123
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean397.47826
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:27.437973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.85
Q1173.25
median354
Q3494.5
95-th percentile970.1
Maximum3185
Range3183
Interquartile range (IQR)321.25

Descriptive statistics

Standard deviation421.99542
Coefficient of variation (CV)1.0616818
Kurtosis18.298106
Mean397.47826
Median Absolute Deviation (MAD)161
Skewness3.5773846
Sum54852
Variance178080.13
MonotonicityNot monotonic
2024-04-21T01:57:27.872763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.2%
302 3
 
2.2%
9 3
 
2.2%
36 2
 
1.4%
466 2
 
1.4%
354 2
 
1.4%
443 2
 
1.4%
174 2
 
1.4%
602 2
 
1.4%
483 2
 
1.4%
Other values (113) 115
83.3%
ValueCountFrequency (%)
2 2
1.4%
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 

Distinct124
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean256.05797
Minimum0
Maximum807
Zeros1
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:28.291127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.25
Q1110
median226.5
Q3378.75
95-th percentile541
Maximum807
Range807
Interquartile range (IQR)268.75

Descriptive statistics

Standard deviation172.66713
Coefficient of variation (CV)0.67432828
Kurtosis0.062929144
Mean256.05797
Median Absolute Deviation (MAD)138
Skewness0.58893747
Sum35336
Variance29813.938
MonotonicityNot monotonic
2024-04-21T01:57:28.750791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
154 2
 
1.4%
102 2
 
1.4%
384 2
 
1.4%
304 2
 
1.4%
165 2
 
1.4%
207 2
 
1.4%
181 2
 
1.4%
201 2
 
1.4%
127 2
 
1.4%
156 2
 
1.4%
Other values (114) 118
85.5%
ValueCountFrequency (%)
0 1
0.7%
2 1
0.7%
7 1
0.7%
9 2
1.4%
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 

Distinct136
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4553.442
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:29.183741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile81.35
Q13582
median4558.5
Q35771.25
95-th percentile9600.3
Maximum12906
Range12895
Interquartile range (IQR)2189.25

Descriptive statistics

Standard deviation2585.2207
Coefficient of variation (CV)0.56775088
Kurtosis0.51572829
Mean4553.442
Median Absolute Deviation (MAD)1192.5
Skewness0.31629761
Sum628375
Variance6683366.2
MonotonicityNot monotonic
2024-04-21T01:57:29.598510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4281 2
 
1.4%
516 2
 
1.4%
11 1
 
0.7%
5785 1
 
0.7%
4663 1
 
0.7%
4602 1
 
0.7%
4203 1
 
0.7%
4868 1
 
0.7%
6310 1
 
0.7%
4651 1
 
0.7%
Other values (126) 126
91.3%
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 

Distinct112
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean222.25362
Minimum0
Maximum1206
Zeros4
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:29.896759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q160.75
median156.5
Q3346
95-th percentile563.45
Maximum1206
Range1206
Interquartile range (IQR)285.25

Descriptive statistics

Standard deviation210.81417
Coefficient of variation (CV)0.94852973
Kurtosis2.6660369
Mean222.25362
Median Absolute Deviation (MAD)128
Skewness1.371816
Sum30671
Variance44442.614
MonotonicityNot monotonic
2024-04-21T01:57:30.244197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
2.9%
66 4
 
2.9%
258 3
 
2.2%
32 3
 
2.2%
83 2
 
1.4%
550 2
 
1.4%
42 2
 
1.4%
126 2
 
1.4%
149 2
 
1.4%
128 2
 
1.4%
Other values (102) 112
81.2%
ValueCountFrequency (%)
0 4
2.9%
1 2
1.4%
2 2
1.4%
3 2
1.4%
4 2
1.4%
7 1
 
0.7%
8 2
1.4%
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
1.4%
546 1
0.7%

공원녹지
Real number (ℝ)

HIGH CORRELATION 

Distinct130
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean375.78261
Minimum3
Maximum1091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:30.537022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile28.8
Q1141.5
median283
Q3575.25
95-th percentile904.55
Maximum1091
Range1088
Interquartile range (IQR)433.75

Descriptive statistics

Standard deviation295.04491
Coefficient of variation (CV)0.78514786
Kurtosis-0.58502496
Mean375.78261
Median Absolute Deviation (MAD)186.5
Skewness0.74594996
Sum51858
Variance87051.5
MonotonicityNot monotonic
2024-04-21T01:57:30.847306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
276 2
 
1.4%
51 2
 
1.4%
378 2
 
1.4%
70 2
 
1.4%
91 2
 
1.4%
160 2
 
1.4%
182 2
 
1.4%
693 2
 
1.4%
347 1
 
0.7%
497 1
 
0.7%
Other values (120) 120
87.0%
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 

Distinct128
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1222.471
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:31.208488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.85
Q1298
median1035.5
Q31549
95-th percentile3723.65
Maximum9985
Range9984
Interquartile range (IQR)1251

Descriptive statistics

Standard deviation1469.6827
Coefficient of variation (CV)1.202223
Kurtosis13.761035
Mean1222.471
Median Absolute Deviation (MAD)628
Skewness3.2319764
Sum168701
Variance2159967.3
MonotonicityNot monotonic
2024-04-21T01:57:31.875830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 3
 
2.2%
50 2
 
1.4%
1044 2
 
1.4%
1153 2
 
1.4%
34 2
 
1.4%
1066 2
 
1.4%
641 2
 
1.4%
1549 2
 
1.4%
4 2
 
1.4%
1076 1
 
0.7%
Other values (118) 118
85.5%
ValueCountFrequency (%)
1 1
 
0.7%
2 1
 
0.7%
4 2
1.4%
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 (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.76811594
Minimum0
Maximum7
Zeros83
Zeros (%)60.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:32.226556image/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 deviation1.3685191
Coefficient of variation (CV)1.781657
Kurtosis7.6412137
Mean0.76811594
Median Absolute Deviation (MAD)0
Skewness2.6303226
Sum106
Variance1.8728446
MonotonicityNot monotonic
2024-04-21T01:57:32.572793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 83
60.1%
1 33
 
23.9%
2 12
 
8.7%
4 4
 
2.9%
5 2
 
1.4%
7 2
 
1.4%
3 1
 
0.7%
6 1
 
0.7%
ValueCountFrequency (%)
0 83
60.1%
1 33
 
23.9%
2 12
 
8.7%
3 1
 
0.7%
4 4
 
2.9%
5 2
 
1.4%
6 1
 
0.7%
7 2
 
1.4%
ValueCountFrequency (%)
7 2
 
1.4%
6 1
 
0.7%
5 2
 
1.4%
4 4
 
2.9%
3 1
 
0.7%
2 12
 
8.7%
1 33
 
23.9%
0 83
60.1%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8695652
Minimum0
Maximum65
Zeros31
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:32.921949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q312
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.087431
Coefficient of variation (CV)1.1547564
Kurtosis10.247727
Mean7.8695652
Median Absolute Deviation (MAD)5
Skewness2.3218391
Sum1086
Variance82.581403
MonotonicityNot monotonic
2024-04-21T01:57:33.301749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 31
22.5%
2 10
 
7.2%
8 10
 
7.2%
1 9
 
6.5%
3 8
 
5.8%
5 8
 
5.8%
4 7
 
5.1%
6 6
 
4.3%
20 6
 
4.3%
11 5
 
3.6%
Other values (17) 38
27.5%
ValueCountFrequency (%)
0 31
22.5%
1 9
 
6.5%
2 10
 
7.2%
3 8
 
5.8%
4 7
 
5.1%
5 8
 
5.8%
6 6
 
4.3%
7 4
 
2.9%
8 10
 
7.2%
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
4.3%
18 2
 
1.4%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct135
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2249.8986
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:33.703340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile52.4
Q1232.25
median2336.5
Q33418.25
95-th percentile5779.95
Maximum7847
Range7831
Interquartile range (IQR)3186

Descriptive statistics

Standard deviation1903.2567
Coefficient of variation (CV)0.84593001
Kurtosis-0.29056762
Mean2249.8986
Median Absolute Deviation (MAD)1535.5
Skewness0.5889509
Sum310486
Variance3622386.1
MonotonicityNot monotonic
2024-04-21T01:57:34.158526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 3
 
2.2%
3071 2
 
1.4%
16 1
 
0.7%
3567 1
 
0.7%
2688 1
 
0.7%
2385 1
 
0.7%
2533 1
 
0.7%
2870 1
 
0.7%
2998 1
 
0.7%
3371 1
 
0.7%
Other values (125) 125
90.6%
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%
56 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 

Distinct138
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44490.457
Minimum230
Maximum107800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:57:34.593542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1483.35
Q119315
median47597
Q366336.75
95-th percentile92528.35
Maximum107800
Range107570
Interquartile range (IQR)47021.75

Descriptive statistics

Standard deviation28763.729
Coefficient of variation (CV)0.64651459
Kurtosis-0.93237404
Mean44490.457
Median Absolute Deviation (MAD)22026
Skewness0.06370176
Sum6139683
Variance8.2735211 × 108
MonotonicityNot monotonic
2024-04-21T01:57:35.027526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.7%
68704 1
 
0.7%
50606 1
 
0.7%
49544 1
 
0.7%
50517 1
 
0.7%
57806 1
 
0.7%
67111 1
 
0.7%
69507 1
 
0.7%
63909 1
 
0.7%
69259 1
 
0.7%
Other values (128) 128
92.8%
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

2024-04-21T01:57:19.007088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:32.109314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:35.832947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:39.524766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:43.512754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.176486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:49.130311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:52.867767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:56.912441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.906654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:03.095970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:06.952408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:10.389261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.656946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:15.372071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:19.257974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:32.357036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:36.077301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:39.786717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:43.700181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.319919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:49.380683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:53.125820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:57.171587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:00.059664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:03.343553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:07.199717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:10.541460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.808230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:15.530387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:19.498576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:32.600029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:36.316687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:40.037031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:43.941905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.458962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:49.627289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:53.592256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:57.416117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:00.200085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:03.784870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:07.441254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:10.689288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.960562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:15.684347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:19.765144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:32.862886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:36.574136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:40.304207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:44.198851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.613152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:49.891443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:53.859031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:57.685311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:00.360500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:04.042826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:07.699306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:10.853545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:13.145071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:15.939160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:20.003134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:33.102964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:36.813156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:40.553464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:44.434530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.748542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:50.130348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:54.111587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:57.930131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:00.499825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:04.277897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:07.939528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.000219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:13.523722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:16.187215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:20.236949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:33.338793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:37.043695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:40.796625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:44.662933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.874619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:50.365853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:54.353389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:58.170642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:00.636444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:04.508910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:08.169446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.136665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:13.677320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:16.427463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:20.483936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:33.586109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:37.291152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:41.056084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:44.858863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:47.017818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:50.609859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:54.608502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:58.422375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:00.861632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:04.751278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:08.417645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.288086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:13.847813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:16.683885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:20.745364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:33.847639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:37.547274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:41.325247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.017435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:47.195756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:50.873232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:54.874817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:58.692184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:01.121262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:05.007350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:08.674985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.450765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:14.039439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:16.953091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:20.990565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:34.095074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:37.794550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:41.588785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.160838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:47.440032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:51.121540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:55.128076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:58.868098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:01.367645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:05.249949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:08.921965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.601804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:14.216974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:17.206913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:21.237769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:34.343332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:38.037250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:41.842697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.305714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:47.680324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:51.371044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:55.381531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.013994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:01.613853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:05.491790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:09.166237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.750828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:14.396579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:17.464437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:21.475999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:34.583585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:38.278548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:42.094112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.442890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:47.917315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:51.610849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:55.629308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.157546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:01.851351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:05.725243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:09.407403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:11.895715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:14.565423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:17.713408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:21.716775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:34.825932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:38.520836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:42.346422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.583031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:48.150257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:51.854649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:55.875730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.297742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:02.092803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:05.962489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:09.642285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.039444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:14.732519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:17.962641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:21.968686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:35.080201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:38.774577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:42.824473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.733969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:48.397684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:52.109732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:56.138324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.453251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:02.345695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:06.212114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:09.847593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.196844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:14.919870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:18.228129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:22.217147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:35.329778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:39.018479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:43.086858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:45.879630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:48.642507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:52.361696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:56.392329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.602814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:02.594846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:06.456799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:10.052407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.345928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:15.067251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:18.485758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:22.476903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:35.590709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:39.287844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:43.336548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:46.035991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:48.894604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:52.623219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:56.661904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:56:59.766122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:02.856421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:06.712336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:10.247951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:12.510674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:15.227161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:18.755705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T01:57:35.310161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9430.5720.6880.4990.6620.7730.4220.7680.4210.4480.6060.8700.896
0.0001.0000.0000.3610.1800.1830.4640.5560.3690.3980.2830.1980.0000.0000.000
교통0.9430.0001.0000.5930.6640.5880.7790.7250.5950.8090.5500.7260.6140.8330.961
도로0.5720.3610.5931.0000.4020.3800.6790.3500.8250.6940.2450.4290.2280.2510.583
청소0.6880.1800.6640.4021.0000.5900.4560.6430.4740.6020.6200.0000.4440.6870.689
주택건축0.4990.1830.5880.3800.5901.0000.3870.3120.4270.3890.9790.0000.4150.7600.554
치수방재0.6620.4640.7790.6790.4560.3871.0000.8070.7190.8610.3800.5630.2580.4930.803
가로정비0.7730.5560.7250.3500.6430.3120.8071.0000.4050.6980.2800.2230.0000.6250.749
보건0.4220.3690.5950.8250.4740.4270.7190.4051.0000.7340.5270.5550.4060.3250.617
공원녹지0.7680.3980.8090.6940.6020.3890.8610.6980.7341.0000.4910.5320.5330.6110.793
환경0.4210.2830.5500.2450.6200.9790.3800.2800.5270.4911.0000.0000.5140.5890.485
경제/산업0.4480.1980.7260.4290.0000.0000.5630.2230.5550.5320.0001.0000.0000.0990.562
소방안전0.6060.0000.6140.2280.4440.4150.2580.0000.4060.5330.5140.0001.0000.5280.519
기타 불편사항0.8700.0000.8330.2510.6870.7600.4930.6250.3250.6110.5890.0990.5281.0000.818
총합계0.8960.0000.9610.5830.6890.5540.8030.7490.6170.7930.4850.5620.5190.8181.000
2024-04-21T01:57:35.677107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.0810.9830.6390.5310.7280.6460.3800.7320.8020.7030.5530.3610.2080.958
-0.0811.0000.033-0.0490.0840.030-0.0010.0480.1420.0200.0970.138-0.006-0.0160.050
교통0.9830.0331.0000.6690.5890.7740.6920.4400.8040.8470.7590.5730.3800.2460.988
도로0.639-0.0490.6691.0000.5430.5140.8120.5580.7320.8320.4970.3170.3140.0720.700
청소0.5310.0840.5890.5431.0000.7370.6390.7350.7590.7180.7480.2820.4340.6060.645
주택건축0.7280.0300.7740.5140.7371.0000.5570.5020.7730.7210.9280.3730.5630.6300.811
치수방재0.646-0.0010.6920.8120.6390.5571.0000.7260.8200.8730.5500.3830.3310.2110.731
가로정비0.3800.0480.4400.5580.7350.5020.7261.0000.6790.6450.5100.1670.2260.3710.511
보건0.7320.1420.8040.7320.7590.7730.8200.6791.0000.9250.8130.4350.4760.4580.847
공원녹지0.8020.0200.8470.8320.7180.7210.8730.6450.9251.0000.7270.4630.4800.3280.874
환경0.7030.0970.7590.4970.7480.9280.5500.5100.8130.7271.0000.3430.5470.6390.803
경제/산업0.5530.1380.5730.3170.2820.3730.3830.1670.4350.4630.3431.0000.1000.0400.541
소방안전0.361-0.0060.3800.3140.4340.5630.3310.2260.4760.4800.5470.1001.0000.6680.387
기타 불편사항0.208-0.0160.2460.0720.6060.6300.2110.3710.4580.3280.6390.0400.6681.0000.292
총합계0.9580.0500.9880.7000.6450.8110.7310.5110.8470.8740.8030.5410.3870.2921.000

Missing values

2024-04-21T01:57:22.840331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T01:57:23.344737image/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
128202346779218813200447503994546075316325011694321
1292023565565233937707528077681803103021772011492212
13020236635712557354249370659781206105521021011987543
13120237674672617349541967255194838571102109988513
13220238658942780386940055842493688951153509285947
13320239726402834422840753885925501091138070133105908
134202310772232877427930550570835101068126470109100706
135202311584241722371535442652872705527902014076452
13620231257408180329083023293832172310698205773075
1372024155464213229652853714836139380749005672701