Overview

Dataset statistics

Number of variables15
Number of observations130
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.3 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 10 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 9 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 (63.1%) zerosZeros
소방안전 has 23 (17.7%) zerosZeros

Reproduction

Analysis started2024-04-20 16:57:40.243958
Analysis finished2024-04-20 16:58:35.188246
Duration54.94 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%
Mean2017.5
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:35.298153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2017.5
Q32020
95-th percentile2022
Maximum2023
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.1653404
Coefficient of variation (CV)0.001568942
Kurtosis-1.1575155
Mean2017.5
Median Absolute Deviation (MAD)2.5
Skewness0
Sum262275
Variance10.01938
MonotonicityIncreasing
2024-04-21T01:58:35.523302image/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) 10
7.7%
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 5
3.8%
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%
Mean6.5
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:35.752044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.25
median6.5
Q39.75
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation3.4914069
Coefficient of variation (CV)0.53713953
Kurtosis-1.2442322
Mean6.5
Median Absolute Deviation (MAD)3.5
Skewness0
Sum845
Variance12.189922
MonotonicityNot monotonic
2024-04-21T01:58:35.974013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 11
8.5%
9 11
8.5%
10 11
8.5%
11 11
8.5%
12 11
8.5%
1 11
8.5%
2 11
8.5%
3 11
8.5%
4 11
8.5%
5 11
8.5%
Other values (2) 20
15.4%
ValueCountFrequency (%)
1 11
8.5%
2 11
8.5%
3 11
8.5%
4 11
8.5%
5 11
8.5%
6 10
7.7%
7 10
7.7%
8 11
8.5%
9 11
8.5%
10 11
8.5%
ValueCountFrequency (%)
12 11
8.5%
11 11
8.5%
10 11
8.5%
9 11
8.5%
8 11
8.5%
7 10
7.7%
6 10
7.7%
5 11
8.5%
4 11
8.5%
3 11
8.5%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26032.846
Minimum46
Maximum67792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:36.294294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile313.1
Q17263.5
median23820
Q341536.5
95-th percentile59088.25
Maximum67792
Range67746
Interquartile range (IQR)34273

Descriptive statistics

Standard deviation19902.812
Coefficient of variation (CV)0.76452694
Kurtosis-1.1613566
Mean26032.846
Median Absolute Deviation (MAD)17443.5
Skewness0.26547794
Sum3384270
Variance3.9612193 × 108
MonotonicityNot monotonic
2024-04-21T01:58:36.748845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.8%
41293 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%
35082 1
 
0.8%
Other values (120) 120
92.3%
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%
62497 1
0.8%
60088 1
0.8%
59581 1
0.8%
58486 1
0.8%
56818 1
0.8%
56449 1
0.8%

도로
Real number (ℝ)

HIGH CORRELATION 

Distinct126
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1358.4308
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:37.062013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile323.5
Q1900.25
median1290.5
Q31807.5
95-th percentile2374.75
Maximum5000
Range4966
Interquartile range (IQR)907.25

Descriptive statistics

Standard deviation719.2555
Coefficient of variation (CV)0.52947527
Kurtosis4.363129
Mean1358.4308
Median Absolute Deviation (MAD)441
Skewness1.1532043
Sum176596
Variance517328.48
MonotonicityNot monotonic
2024-04-21T01:58:37.313774image/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 (116) 116
89.2%
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%
2531 1
0.8%
2483 1
0.8%
2395 1
0.8%
2350 1
0.8%
2331 1
0.8%
2328 1
0.8%

청소
Real number (ℝ)

HIGH CORRELATION 

Distinct129
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2668.7231
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:37.559153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile31.7
Q11432
median3064.5
Q33716.25
95-th percentile5026.1
Maximum8515
Range8507
Interquartile range (IQR)2284.25

Descriptive statistics

Standard deviation1645.6242
Coefficient of variation (CV)0.61663355
Kurtosis0.12310302
Mean2668.7231
Median Absolute Deviation (MAD)839
Skewness0.0020043578
Sum346934
Variance2708078.9
MonotonicityNot monotonic
2024-04-21T01:58:37.804747image/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 (119) 119
91.5%
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 

Distinct117
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean399.13077
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:38.046856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.45
Q1141.5
median353
Q3497.5
95-th percentile983.7
Maximum3185
Range3183
Interquartile range (IQR)356

Descriptive statistics

Standard deviation434.50702
Coefficient of variation (CV)1.0886332
Kurtosis17.116401
Mean399.13077
Median Absolute Deviation (MAD)178
Skewness3.4721852
Sum51887
Variance188796.35
MonotonicityNot monotonic
2024-04-21T01:58:38.621481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.3%
9 3
 
2.3%
466 2
 
1.5%
36 2
 
1.5%
602 2
 
1.5%
483 2
 
1.5%
352 2
 
1.5%
174 2
 
1.5%
443 2
 
1.5%
302 2
 
1.5%
Other values (107) 108
83.1%
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 

Distinct116
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean240.22308
Minimum0
Maximum805
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:39.039096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.25
Q1102.25
median215.5
Q3364.75
95-th percentile483.6
Maximum805
Range805
Interquartile range (IQR)262.5

Descriptive statistics

Standard deviation162.20889
Coefficient of variation (CV)0.67524276
Kurtosis0.32000867
Mean240.22308
Median Absolute Deviation (MAD)133
Skewness0.61620325
Sum31229
Variance26311.725
MonotonicityNot monotonic
2024-04-21T01:58:39.344053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165 2
 
1.5%
325 2
 
1.5%
9 2
 
1.5%
201 2
 
1.5%
71 2
 
1.5%
156 2
 
1.5%
56 2
 
1.5%
127 2
 
1.5%
154 2
 
1.5%
102 2
 
1.5%
Other values (106) 110
84.6%
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 (%)
805 1
0.8%
720 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%
462 1
0.8%

가로정비
Real number (ℝ)

HIGH CORRELATION 

Distinct128
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4484.5923
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:39.608865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile76.95
Q13219
median4531.5
Q35713.5
95-th percentile9697.1
Maximum12906
Range12895
Interquartile range (IQR)2494.5

Descriptive statistics

Standard deviation2623.8191
Coefficient of variation (CV)0.58507416
Kurtosis0.50594779
Mean4484.5923
Median Absolute Deviation (MAD)1226
Skewness0.36411801
Sum582997
Variance6884426.7
MonotonicityNot monotonic
2024-04-21T01:58:39.873512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4281 2
 
1.5%
516 2
 
1.5%
4663 1
 
0.8%
5730 1
 
0.8%
7263 1
 
0.8%
5800 1
 
0.8%
4761 1
 
0.8%
4743 1
 
0.8%
11 1
 
0.8%
5494 1
 
0.8%
Other values (118) 118
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 

Distinct105
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207.48462
Minimum0
Maximum803
Zeros4
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:40.125598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q143.25
median145
Q3310
95-th percentile555.5
Maximum803
Range803
Interquartile range (IQR)266.75

Descriptive statistics

Standard deviation192.9241
Coefficient of variation (CV)0.92982365
Kurtosis0.28580065
Mean207.48462
Median Absolute Deviation (MAD)119.5
Skewness1.0056201
Sum26973
Variance37219.709
MonotonicityNot monotonic
2024-04-21T01:58:40.391434image/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%
126 2
 
1.5%
Other values (95) 104
80.0%
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 (%)
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%
545 1
0.8%

공원녹지
Real number (ℝ)

HIGH CORRELATION 

Distinct122
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean351.13846
Minimum3
Maximum1028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:40.662172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile25.6
Q1128.25
median272.5
Q3540.5
95-th percentile881.75
Maximum1028
Range1025
Interquartile range (IQR)412.25

Descriptive statistics

Standard deviation276.40967
Coefficient of variation (CV)0.78718142
Kurtosis-0.56907851
Mean351.13846
Median Absolute Deviation (MAD)173.5
Skewness0.76325351
Sum45648
Variance76402.306
MonotonicityNot monotonic
2024-04-21T01:58:40.909860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160 2
 
1.5%
91 2
 
1.5%
276 2
 
1.5%
70 2
 
1.5%
51 2
 
1.5%
693 2
 
1.5%
182 2
 
1.5%
378 2
 
1.5%
257 1
 
0.8%
264 1
 
0.8%
Other values (112) 112
86.2%
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 (%)
1028 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%
856 1
0.8%

환경
Real number (ℝ)

HIGH CORRELATION 

Distinct121
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1226.6385
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:41.157309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.45
Q1234.5
median1017
Q31559.5
95-th percentile3896.05
Maximum9985
Range9984
Interquartile range (IQR)1325

Descriptive statistics

Standard deviation1510.7048
Coefficient of variation (CV)1.2315811
Kurtosis12.943315
Mean1226.6385
Median Absolute Deviation (MAD)683
Skewness3.1539755
Sum159463
Variance2282229
MonotonicityNot monotonic
2024-04-21T01:58:41.412311image/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%
579 1
 
0.8%
2075 1
 
0.8%
Other values (111) 111
85.4%
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 (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.62307692
Minimum0
Maximum6
Zeros82
Zeros (%)63.1%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:41.610462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2.55
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0944921
Coefficient of variation (CV)1.7565922
Kurtosis7.1376585
Mean0.62307692
Median Absolute Deviation (MAD)0
Skewness2.4902328
Sum81
Variance1.1979129
MonotonicityNot monotonic
2024-04-21T01:58:41.789723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 82
63.1%
1 31
 
23.8%
2 10
 
7.7%
4 4
 
3.1%
3 1
 
0.8%
6 1
 
0.8%
5 1
 
0.8%
ValueCountFrequency (%)
0 82
63.1%
1 31
 
23.8%
2 10
 
7.7%
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
 
7.7%
1 31
 
23.8%
0 82
63.1%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3538462
Minimum0
Maximum65
Zeros23
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:41.995842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5.5
Q313
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)11

Descriptive statistics

Standard deviation9.1447121
Coefficient of variation (CV)1.0946709
Kurtosis10.199796
Mean8.3538462
Median Absolute Deviation (MAD)5
Skewness2.3006068
Sum1086
Variance83.62576
MonotonicityNot monotonic
2024-04-21T01:58:42.238102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 23
17.7%
2 10
 
7.7%
8 10
 
7.7%
1 9
 
6.9%
3 8
 
6.2%
5 8
 
6.2%
4 7
 
5.4%
6 6
 
4.6%
20 6
 
4.6%
11 5
 
3.8%
Other values (17) 38
29.2%
ValueCountFrequency (%)
0 23
17.7%
1 9
 
6.9%
2 10
7.7%
3 8
 
6.2%
4 7
 
5.4%
5 8
 
6.2%
6 6
 
4.6%
7 4
 
3.1%
8 10
7.7%
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 

Distinct128
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2382.1615
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:42.571562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile50.8
Q1418.25
median2540.5
Q33441.5
95-th percentile5833.15
Maximum7847
Range7831
Interquartile range (IQR)3023.25

Descriptive statistics

Standard deviation1882.2524
Coefficient of variation (CV)0.79014473
Kurtosis-0.27471779
Mean2382.1615
Median Absolute Deviation (MAD)1238.5
Skewness0.52660583
Sum309681
Variance3542874
MonotonicityNot monotonic
2024-04-21T01:58:42.936050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3071 2
 
1.5%
99 2
 
1.5%
16 1
 
0.8%
3356 1
 
0.8%
2881 1
 
0.8%
3434 1
 
0.8%
3254 1
 
0.8%
2782 1
 
0.8%
2688 1
 
0.8%
3640 1
 
0.8%
Other values (118) 118
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 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41914.138
Minimum230
Maximum107800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-21T01:58:43.318018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1334.95
Q118299.75
median43001.5
Q363789.75
95-th percentile82582.9
Maximum107800
Range107570
Interquartile range (IQR)45490

Descriptive statistics

Standard deviation27479.023
Coefficient of variation (CV)0.6556027
Kurtosis-0.88578823
Mean41914.138
Median Absolute Deviation (MAD)22470
Skewness0.089399895
Sum5448838
Variance7.5509668 × 108
MonotonicityNot monotonic
2024-04-21T01:58:43.765709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.8%
61221 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%
50606 1
 
0.8%
Other values (120) 120
92.3%
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%
83077 1
0.8%
81979 1
0.8%
79948 1
0.8%
78128 1
0.8%

Interactions

2024-04-21T01:58:30.867267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:41.080983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:44.763682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:48.645070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:52.409160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:56.047793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:59.847324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:03.394067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:06.429682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:09.211136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:13.031515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:16.712369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:20.169541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:23.442225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:26.800981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:31.108530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:41.320269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:45.000980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:48.893716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:52.647286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:56.282186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:00.056619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:03.650769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:06.573318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:09.461079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:13.272146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:16.952430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:20.418556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:23.588553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:27.054136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:31.351740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:41.558093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:45.236947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:49.137912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:52.882745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:56.518017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:00.198347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:03.903262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:06.716403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:09.709159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:13.508409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:17.193675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:20.662154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:23.729469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:27.302578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:31.602660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:41.810412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:45.489827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:49.395509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:53.134349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:56.762730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:00.456502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:04.166206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:06.870051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:09.969517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:13.761271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:17.445214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:20.920151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:23.888205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:27.566892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:31.842530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:42.046729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:45.731409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:49.638165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:53.367100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:56.996902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:00.696602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:04.414762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:07.013599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:10.218416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:13.997324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:17.684964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:21.162188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:24.057927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:27.813945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:32.076821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:42.276284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:45.961472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:49.877105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:53.597919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:57.220742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:00.929317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:04.655449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:07.146917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:10.458593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:14.230815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:17.913558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:21.396078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:24.295098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:28.059878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:32.322671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:42.532016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:46.213036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:50.129363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:53.839152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:57.461469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:01.175263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:04.913057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:07.294660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:10.714550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:14.475024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:18.157934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:21.645611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:24.546643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:28.320699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:32.580467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:42.796429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:46.683846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:50.392287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:54.096106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:57.712911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:01.434067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:05.177523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:07.455092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:10.982648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:14.733789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:18.413882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:21.905056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:24.807548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:28.593806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:32.829295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:43.042142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:46.932578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:50.644337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:54.337482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:57.952972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:01.685350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:05.333632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:07.601099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:11.238819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:14.978139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:18.658633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:22.103654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:25.058614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:28.849689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:33.087026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:43.302396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:47.192041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:50.906224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:54.594318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:58.203826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:01.949376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:05.497558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:07.759413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:11.505159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:15.236571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:18.918905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:22.262584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:25.318448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:29.115851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:33.327142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:43.540387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:47.433795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:51.151890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:54.829115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:58.649931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:02.156016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:05.647410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:08.116163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:11.751902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:15.471521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:19.078896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:22.404216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:25.561974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:29.365971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:33.565516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:43.778354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:47.668353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:51.395366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:55.066803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:58.882343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:02.379882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:05.798399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:08.255873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:12.003074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:15.710315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:19.232571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:22.583411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:25.802309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:29.613975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:33.815108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:44.022053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:47.911521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:51.647555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:55.309405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:59.123893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:02.634093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:05.953126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:08.458480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:12.262020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:15.962438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:19.624068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:22.832452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:26.053313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:30.086820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:34.060799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:44.267230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:48.153389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:51.897809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:55.554778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:59.362347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:02.882705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:06.109789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:08.697596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:12.515758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:16.212033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:19.791117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:23.080302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:26.299049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:30.346600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:34.324454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:44.524925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:48.410372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:52.163856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:55.809011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:57:59.615309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:03.148899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:06.278121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:08.966105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:12.784574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:16.471156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:19.979612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:23.300749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:26.561918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T01:58:30.613749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T01:58:44.014797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9630.5040.7000.6050.5730.7750.6270.7320.5600.3580.5820.8640.893
0.0001.0000.0000.3880.1840.1690.5000.5380.5440.4860.2530.1980.0000.0000.000
교통0.9630.0001.0000.5320.6790.6240.7510.7360.7680.7650.5460.4870.6550.8880.958
도로0.5040.3880.5321.0000.3740.3950.6320.3220.6640.6610.2290.0000.2920.2980.557
청소0.7000.1840.6790.3741.0000.6210.4450.6420.5580.6610.6500.0000.4800.7150.692
주택건축0.6050.1690.6240.3950.6211.0000.3880.3090.5280.4040.9800.0000.4330.7640.594
치수방재0.5730.5000.7510.6320.4450.3881.0000.8360.8210.8560.3760.4900.3050.5500.822
가로정비0.7750.5380.7360.3220.6420.3090.8361.0000.6240.6740.2430.2090.1300.6770.762
보건0.6270.5440.7680.6640.5580.5280.8210.6241.0000.8770.5350.4840.5460.6090.818
공원녹지0.7320.4860.7650.6610.6610.4040.8560.6740.8771.0000.5000.4570.5620.6460.775
환경0.5600.2530.5460.2290.6500.9800.3760.2430.5350.5001.0000.0000.5340.5980.483
경제/산업0.3580.1980.4870.0000.0000.0000.4900.2090.4840.4570.0001.0000.0000.1800.520
소방안전0.5820.0000.6550.2920.4800.4330.3050.1300.5460.5620.5340.0001.0000.5070.551
기타 불편사항0.8640.0000.8880.2980.7150.7640.5500.6770.6090.6460.5980.1800.5071.0000.836
총합계0.8930.0000.9580.5570.6920.5940.8220.7620.8180.7750.4830.5200.5510.8361.000
2024-04-21T01:58:44.283958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.1290.9830.5930.5380.7860.6040.3750.7350.7940.7490.5080.5860.3920.954
-0.1291.000-0.006-0.0760.0640.035-0.0270.0470.133-0.0030.1020.0780.0340.0210.017
교통0.983-0.0061.0000.6240.5970.8310.6540.4360.8050.8370.8020.5260.6020.4300.986
도로0.593-0.0760.6241.0000.5330.5330.7950.5590.7140.8150.5020.2450.4860.1910.662
청소0.5380.0640.5970.5331.0000.7610.6380.7410.7660.7200.7670.2430.5370.7130.660
주택건축0.7860.0350.8310.5330.7611.0000.5830.5210.7920.7490.9320.3900.6160.6880.868
치수방재0.604-0.0270.6540.7950.6380.5831.0000.7400.8150.8660.5650.3140.5060.3530.700
가로정비0.3750.0470.4360.5590.7410.5210.7401.0000.6850.6500.5220.1400.3000.4440.513
보건0.7350.1330.8050.7140.7660.7920.8150.6851.0000.9220.8240.3950.6180.5840.852
공원녹지0.794-0.0030.8370.8150.7200.7490.8660.6500.9221.0000.7420.4100.6560.4690.868
환경0.7490.1020.8020.5020.7670.9320.5650.5220.8240.7421.0000.3420.6160.7110.847
경제/산업0.5080.0780.5260.2450.2430.3900.3140.1400.3950.4100.3421.0000.2370.1530.489
소방안전0.5860.0340.6020.4860.5370.6160.5060.3000.6180.6560.6160.2371.0000.6100.603
기타 불편사항0.3920.0210.4300.1910.7130.6880.3530.4440.5840.4690.7110.1530.6101.0000.478
총합계0.9540.0170.9860.6620.6600.8680.7000.5130.8520.8680.8470.4890.6030.4781.000

Missing values

2024-04-21T01:58:34.689741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T01:58:35.042724image/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
12020228584862998321442664659273708751371221281099268
12120229600882328345446638442367269641593112215979948
1222022106563150002941483333490970766819230016694613
1232022116249715502830502296521034650019831068104091
124202212523321615209635216536001492001781205473449
1252023154307145226504431903773108214579004370869
1262023254449140327196163785304142356779105371097
1272023365903193833254305931052725175910872099107800
128202346779218813200447503994546075316325011694321
1292023565565233137707528057679803102821772011492212