Overview

Dataset statistics

Number of variables15
Number of observations127
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 KiB
Average record size in memory136.0 B

Variable types

Numeric15

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-12051/F/1/datasetView.do

Alerts

년도 is highly overall correlated with 교통 and 9 other fieldsHigh correlation
교통 is highly overall correlated with 년도 and 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 11 other fieldsHigh correlation
환경 is highly overall correlated with 년도 and 10 other fieldsHigh correlation
소방안전 is highly overall correlated with 년도 and 10 other fieldsHigh correlation
기타 불편사항 is highly overall correlated with 교통 and 8 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 (64.6%) zerosZeros
소방안전 has 20 (15.7%) zerosZeros

Reproduction

Analysis started2024-03-30 05:26:07.837091
Analysis finished2024-03-30 05:27:40.805051
Duration1 minute and 32.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.3701
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:41.073743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation3.0855607
Coefficient of variation (CV)0.0015294966
Kurtosis-1.1654012
Mean2017.3701
Median Absolute Deviation (MAD)3
Skewness-0.0085868694
Sum256206
Variance9.5206849
MonotonicityIncreasing
2024-03-30T05:27:41.521003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2013 12
9.4%
2014 12
9.4%
2015 12
9.4%
2016 12
9.4%
2017 12
9.4%
2018 12
9.4%
2019 12
9.4%
2020 12
9.4%
2021 12
9.4%
2022 12
9.4%
Other values (2) 7
5.5%
ValueCountFrequency (%)
2012 5
3.9%
2013 12
9.4%
2014 12
9.4%
2015 12
9.4%
2016 12
9.4%
2017 12
9.4%
2018 12
9.4%
2019 12
9.4%
2020 12
9.4%
2021 12
9.4%
ValueCountFrequency (%)
2023 2
 
1.6%
2022 12
9.4%
2021 12
9.4%
2020 12
9.4%
2019 12
9.4%
2018 12
9.4%
2017 12
9.4%
2016 12
9.4%
2015 12
9.4%
2014 12
9.4%


Real number (ℝ)

Distinct12
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5590551
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:41.930980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.5
median7
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation3.5088404
Coefficient of variation (CV)0.53496126
Kurtosis-1.2470051
Mean6.5590551
Median Absolute Deviation (MAD)3
Skewness-0.039754797
Sum833
Variance12.311961
MonotonicityNot monotonic
2024-03-30T05:27:42.439601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 11
8.7%
9 11
8.7%
10 11
8.7%
11 11
8.7%
12 11
8.7%
1 11
8.7%
2 11
8.7%
3 10
7.9%
4 10
7.9%
5 10
7.9%
Other values (2) 20
15.7%
ValueCountFrequency (%)
1 11
8.7%
2 11
8.7%
3 10
7.9%
4 10
7.9%
5 10
7.9%
6 10
7.9%
7 10
7.9%
8 11
8.7%
9 11
8.7%
10 11
8.7%
ValueCountFrequency (%)
12 11
8.7%
11 11
8.7%
10 11
8.7%
9 11
8.7%
8 11
8.7%
7 10
7.9%
6 10
7.9%
5 10
7.9%
4 10
7.9%
3 10
7.9%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25078.819
Minimum46
Maximum65631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:42.823082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile292.4
Q17005.5
median23552
Q341263.5
95-th percentile55849
Maximum65631
Range65585
Interquartile range (IQR)34258

Descriptive statistics

Standard deviation19125.295
Coefficient of variation (CV)0.76260748
Kurtosis-1.2437558
Mean25078.819
Median Absolute Deviation (MAD)17487
Skewness0.23039506
Sum3185010
Variance3.6577691 × 108
MonotonicityNot monotonic
2024-03-30T05:27:43.621588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.8%
83 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%
38404 1
 
0.8%
39628 1
 
0.8%
Other values (117) 117
92.1%
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 (%)
65631 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%
54449 1
0.8%
54307 1
0.8%
53254 1
0.8%

도로
Real number (ℝ)

HIGH CORRELATION 

Distinct123
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.0551
Minimum34
Maximum5000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:44.042030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile295
Q1882.5
median1259
Q31763
95-th percentile2381.5
Maximum5000
Range4966
Interquartile range (IQR)880.5

Descriptive statistics

Standard deviation718.96131
Coefficient of variation (CV)0.53571668
Kurtosis4.6347121
Mean1342.0551
Median Absolute Deviation (MAD)452
Skewness1.223831
Sum170441
Variance516905.37
MonotonicityNot monotonic
2024-03-30T05:27:44.654804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1726 2
 
1.6%
1166 2
 
1.6%
1318 2
 
1.6%
2019 2
 
1.6%
57 1
 
0.8%
2350 1
 
0.8%
2111 1
 
0.8%
1831 1
 
0.8%
1792 1
 
0.8%
1388 1
 
0.8%
Other values (113) 113
89.0%
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%
2993 1
0.8%
2758 1
0.8%
2531 1
0.8%
2483 1
0.8%
2395 1
0.8%
2350 1
0.8%
2328 1
0.8%
2197 1
0.8%

청소
Real number (ℝ)

HIGH CORRELATION 

Distinct126
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2650.685
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:45.187366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile30.8
Q11290
median3024
Q33713.5
95-th percentile5065.4
Maximum8515
Range8507
Interquartile range (IQR)2423.5

Descriptive statistics

Standard deviation1660.3999
Coefficient of variation (CV)0.62640408
Kurtosis0.084857104
Mean2650.685
Median Absolute Deviation (MAD)858
Skewness0.031994373
Sum336637
Variance2756927.9
MonotonicityNot monotonic
2024-03-30T05:27:45.809977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.6%
15 1
 
0.8%
4389 1
 
0.8%
4086 1
 
0.8%
3761 1
 
0.8%
3459 1
 
0.8%
3417 1
 
0.8%
3294 1
 
0.8%
3321 1
 
0.8%
3785 1
 
0.8%
Other values (116) 116
91.3%
ValueCountFrequency (%)
8 1
0.8%
9 1
0.8%
15 1
0.8%
17 1
0.8%
22 2
1.6%
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 

Distinct114
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean395.73228
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:46.397217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8.3
Q1119
median352
Q3497
95-th percentile988.8
Maximum3185
Range3183
Interquartile range (IQR)378

Descriptive statistics

Standard deviation438.48133
Coefficient of variation (CV)1.1080252
Kurtosis16.985705
Mean395.73228
Median Absolute Deviation (MAD)178
Skewness3.4797536
Sum50258
Variance192265.88
MonotonicityNot monotonic
2024-03-30T05:27:46.850288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.4%
9 3
 
2.4%
443 2
 
1.6%
2 2
 
1.6%
352 2
 
1.6%
466 2
 
1.6%
302 2
 
1.6%
602 2
 
1.6%
174 2
 
1.6%
36 2
 
1.6%
Other values (104) 105
82.7%
ValueCountFrequency (%)
2 2
1.6%
3 1
 
0.8%
5 1
 
0.8%
6 1
 
0.8%
7 1
 
0.8%
8 1
 
0.8%
9 3
2.4%
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%
743 1
0.8%

치수방재
Real number (ℝ)

HIGH CORRELATION 

Distinct113
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.93701
Minimum0
Maximum720
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:47.381807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.5
Q1102
median212
Q3354
95-th percentile458.4
Maximum720
Range720
Interquartile range (IQR)252

Descriptive statistics

Standard deviation150.96508
Coefficient of variation (CV)0.65370676
Kurtosis-0.31210289
Mean230.93701
Median Absolute Deviation (MAD)131
Skewness0.40414335
Sum29329
Variance22790.456
MonotonicityNot monotonic
2024-03-30T05:27:47.931228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127 2
 
1.6%
156 2
 
1.6%
154 2
 
1.6%
207 2
 
1.6%
325 2
 
1.6%
304 2
 
1.6%
201 2
 
1.6%
181 2
 
1.6%
165 2
 
1.6%
384 2
 
1.6%
Other values (103) 107
84.3%
ValueCountFrequency (%)
0 1
0.8%
2 1
0.8%
7 1
0.8%
9 2
1.6%
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 (%)
720 1
0.8%
647 1
0.8%
510 1
0.8%
489 1
0.8%
477 1
0.8%
464 1
0.8%
462 1
0.8%
450 1
0.8%
445 1
0.8%
431 1
0.8%

가로정비
Real number (ℝ)

HIGH CORRELATION 

Distinct125
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4368.8661
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:48.531059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile75.3
Q13163
median4511
Q35599
95-th percentile9091.3
Maximum12906
Range12895
Interquartile range (IQR)2436

Descriptive statistics

Standard deviation2535.2424
Coefficient of variation (CV)0.58029757
Kurtosis0.71686201
Mean4368.8661
Median Absolute Deviation (MAD)1166
Skewness0.34676236
Sum554846
Variance6427454
MonotonicityNot monotonic
2024-03-30T05:27:49.147719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4281 2
 
1.6%
516 2
 
1.6%
11 1
 
0.8%
5494 1
 
0.8%
5488 1
 
0.8%
5730 1
 
0.8%
7263 1
 
0.8%
5800 1
 
0.8%
4761 1
 
0.8%
6563 1
 
0.8%
Other values (115) 115
90.6%
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%
10396 1
0.8%
10196 1
0.8%
9806 1
0.8%
9564 1
0.8%
9169 1
0.8%
8910 1
0.8%
8494 1
0.8%
8001 1
0.8%

보건
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct102
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.46457
Minimum0
Maximum726
Zeros4
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:49.834065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q142
median131
Q3300.5
95-th percentile548.8
Maximum726
Range726
Interquartile range (IQR)258.5

Descriptive statistics

Standard deviation186.33447
Coefficient of variation (CV)0.92951327
Kurtosis0.12713873
Mean200.46457
Median Absolute Deviation (MAD)111
Skewness0.97461718
Sum25459
Variance34720.536
MonotonicityNot monotonic
2024-03-30T05:27:50.542128image/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
 
2.4%
258 3
 
2.4%
1 2
 
1.6%
128 2
 
1.6%
4 2
 
1.6%
126 2
 
1.6%
118 2
 
1.6%
346 2
 
1.6%
Other values (92) 101
79.5%
ValueCountFrequency (%)
0 4
3.1%
1 2
1.6%
2 2
1.6%
3 2
1.6%
4 2
1.6%
7 1
 
0.8%
8 2
1.6%
9 1
 
0.8%
11 1
 
0.8%
13 1
 
0.8%
ValueCountFrequency (%)
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%
538 1
0.8%

공원녹지
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean339.44094
Minimum3
Maximum970
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:51.053505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile24.4
Q1123
median270
Q3512
95-th percentile878.1
Maximum970
Range967
Interquartile range (IQR)389

Descriptive statistics

Standard deviation268.05566
Coefficient of variation (CV)0.78969748
Kurtosis-0.46448267
Mean339.44094
Median Absolute Deviation (MAD)168
Skewness0.80514781
Sum43109
Variance71853.836
MonotonicityNot monotonic
2024-03-30T05:27:51.622274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182 2
 
1.6%
160 2
 
1.6%
276 2
 
1.6%
70 2
 
1.6%
693 2
 
1.6%
51 2
 
1.6%
378 2
 
1.6%
91 2
 
1.6%
264 1
 
0.8%
369 1
 
0.8%
Other values (109) 109
85.8%
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 (%)
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%
876 1
0.8%
856 1
0.8%
848 1
0.8%

환경
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1217.063
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:52.202334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.3
Q1226.5
median974
Q31549
95-th percentile3960.7
Maximum9985
Range9984
Interquartile range (IQR)1322.5

Descriptive statistics

Standard deviation1525.7288
Coefficient of variation (CV)1.2536153
Kurtosis12.784188
Mean1217.063
Median Absolute Deviation (MAD)667
Skewness3.1528086
Sum154567
Variance2327848.3
MonotonicityNot monotonic
2024-03-30T05:27:53.098764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 3
 
2.4%
1044 2
 
1.6%
1066 2
 
1.6%
1549 2
 
1.6%
34 2
 
1.6%
50 2
 
1.6%
641 2
 
1.6%
4 2
 
1.6%
4496 1
 
0.8%
6539 1
 
0.8%
Other values (108) 108
85.0%
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
4 2
1.6%
6 3
2.4%
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)

ZEROS 

Distinct6
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56692913
Minimum0
Maximum6
Zeros82
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:53.595358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1.0203528
Coefficient of variation (CV)1.799789
Kurtosis8.486654
Mean0.56692913
Median Absolute Deviation (MAD)0
Skewness2.6395869
Sum72
Variance1.0411199
MonotonicityNot monotonic
2024-03-30T05:27:54.033913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 82
64.6%
1 31
 
24.4%
2 8
 
6.3%
4 4
 
3.1%
3 1
 
0.8%
6 1
 
0.8%
ValueCountFrequency (%)
0 82
64.6%
1 31
 
24.4%
2 8
 
6.3%
3 1
 
0.8%
4 4
 
3.1%
6 1
 
0.8%
ValueCountFrequency (%)
6 1
 
0.8%
4 4
 
3.1%
3 1
 
0.8%
2 8
 
6.3%
1 31
 
24.4%
0 82
64.6%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.5511811
Minimum0
Maximum65
Zeros20
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:54.392653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q313.5
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation9.1605682
Coefficient of variation (CV)1.0712635
Kurtosis10.210697
Mean8.5511811
Median Absolute Deviation (MAD)5
Skewness2.2967149
Sum1086
Variance83.91601
MonotonicityNot monotonic
2024-03-30T05:27:54.799699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 20
15.7%
2 10
 
7.9%
8 10
 
7.9%
1 9
 
7.1%
3 8
 
6.3%
5 8
 
6.3%
4 7
 
5.5%
6 6
 
4.7%
20 6
 
4.7%
11 5
 
3.9%
Other values (17) 38
29.9%
ValueCountFrequency (%)
0 20
15.7%
1 9
7.1%
2 10
7.9%
3 8
 
6.3%
4 7
 
5.5%
5 8
 
6.3%
6 6
 
4.7%
7 4
 
3.1%
8 10
7.9%
10 3
 
2.4%
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
2.4%
20 6
4.7%
18 2
 
1.6%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct125
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2435.8268
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:55.493148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile50.2
Q1456
median2559
Q33446
95-th percentile5853.1
Maximum7847
Range7831
Interquartile range (IQR)2990

Descriptive statistics

Standard deviation1871.1955
Coefficient of variation (CV)0.76819728
Kurtosis-0.25762424
Mean2435.8268
Median Absolute Deviation (MAD)1210
Skewness0.50485867
Sum309350
Variance3501372.6
MonotonicityNot monotonic
2024-03-30T05:27:56.262385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3442 2
 
1.6%
3071 2
 
1.6%
16 1
 
0.8%
2759 1
 
0.8%
2998 1
 
0.8%
2870 1
 
0.8%
2533 1
 
0.8%
2385 1
 
0.8%
2688 1
 
0.8%
2782 1
 
0.8%
Other values (115) 115
90.6%
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 

Distinct127
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40586.654
Minimum230
Maximum104091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:27:56.871022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1279.3
Q117694
median40897
Q363281.5
95-th percentile76825.4
Maximum104091
Range103861
Interquartile range (IQR)45587.5

Descriptive statistics

Standard deviation26362.306
Coefficient of variation (CV)0.64953141
Kurtosis-1.0071851
Mean40586.654
Median Absolute Deviation (MAD)22673
Skewness0.012081085
Sum5154505
Variance6.9497118 × 108
MonotonicityNot monotonic
2024-03-30T05:27:57.309408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.8%
427 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%
54987 1
 
0.8%
59699 1
 
0.8%
Other values (117) 117
92.1%
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 (%)
104091 1
0.8%
99268 1
0.8%
94613 1
0.8%
83077 1
0.8%
81979 1
0.8%
79948 1
0.8%
78128 1
0.8%
73786 1
0.8%
73765 1
0.8%
73449 1
0.8%

Interactions

2024-03-30T05:27:34.836393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:10.520070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:21.256223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:27.876524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:35.950933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:42.744726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:48.066537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:53.532817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:58.835088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:03.272161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:07.690079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:12.201199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:17.042231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:22.340768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:29.615459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:35.149668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:10.925250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:21.765691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:28.324938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:36.529418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:43.164097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:48.313371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:53.874374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:59.228590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:03.699489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:07.944347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:12.459994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:17.360561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:22.737571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:29.983707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:35.416335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:11.729875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:22.211502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:28.967061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:36.928748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:43.649959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:48.810237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:54.225110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:59.561605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:04.001819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:08.226460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:12.802453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:17.586492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:23.115019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:30.312562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:35.753859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:12.605105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:22.679086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:29.379251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:37.250764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:43.991819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:49.349862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:54.536021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:59.896357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:04.255996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:08.640430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:13.170767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:17.880691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:23.410800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:30.578262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:36.108942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:13.802456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:23.070058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:29.780065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:37.652615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:44.261943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:49.584362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:54.850493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:00.240775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:04.515572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:08.894469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:13.447501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:18.198349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:23.657428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:31.143239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:36.401526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:14.830973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:23.365509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:30.396518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:37.940914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:44.561767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:49.880711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:55.250096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:00.567614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:04.775121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:09.223934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:13.718382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:18.578011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:24.072200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:31.401791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:36.653575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:15.559444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:23.710906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:30.839592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:38.434789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:44.878086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:50.196523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:55.684142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:00.851998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:05.031901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:09.587724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:14.010494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:18.841081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:24.452650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:31.669646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:36.929797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:16.084581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:24.114381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:31.319502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:39.147216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:45.386307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:50.502683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:56.145213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:01.111314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:05.310525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:09.893582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:14.324707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:19.105689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:25.044489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:32.085383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:37.304643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:16.576785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:24.515572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:32.021236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:39.488079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:45.815448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:51.001117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:56.528402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:01.415809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:05.576873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:10.142552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:14.607380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:19.727733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:25.539778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:32.456067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:37.583123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:17.125028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:25.115169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:32.363832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:39.911574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:46.238139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:51.303367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:56.799460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:01.724451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:05.853157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:10.514709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:14.945032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:20.071024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:26.162026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:32.749467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:37.828065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:17.873096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:25.590806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:33.150245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:40.514463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:46.664767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:51.638294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:57.058055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:01.982261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:06.138426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:10.849911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:15.493296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:20.365386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:27.036572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:33.066075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:38.125091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:18.872046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:26.027980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:33.488955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:41.071337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:46.901781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:52.032605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:57.333666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:02.226330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:06.396652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:11.141712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:15.911323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:20.762281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:27.712988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:33.488663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:38.386439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:19.376444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:26.483027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:34.300585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:41.539046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:47.152102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:52.433258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:57.722946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:02.478398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:06.744700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:11.396888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:16.218303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:21.167650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:28.049136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:33.807329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:38.776080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:20.032620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:26.921421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:34.737152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:41.818333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:47.402060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:52.835711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:58.063839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:02.749298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:07.107217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:11.654428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:16.477619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:21.435269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:28.407372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:34.135847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:39.061644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:20.732022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:27.364341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:35.239774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:42.373120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:47.839026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:53.146389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:26:58.399966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:03.028613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:07.447841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:11.918732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:16.762612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:21.883565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:28.988581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:27:34.464880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T05:27:57.641755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9660.5080.6990.6120.6150.7870.6510.7140.5640.3410.5910.8680.782
0.0001.0000.0000.4010.1720.1950.3830.4610.5240.4020.2590.1800.0000.0000.000
교통0.9660.0001.0000.5650.7300.6660.7260.7390.7810.7550.5930.4130.6420.8960.853
도로0.5080.4010.5651.0000.3560.3770.6270.3500.6650.6960.2190.1140.3230.3370.582
청소0.6990.1720.7300.3561.0000.6050.5310.6570.5780.6010.6530.0000.4960.7250.833
주택건축0.6120.1950.6660.3770.6051.0000.3790.3560.5250.3930.9790.0000.4640.7700.710
치수방재0.6150.3830.7260.6270.5310.3791.0000.8430.7700.8290.3610.2780.3480.6420.658
가로정비0.7870.4610.7390.3500.6570.3560.8431.0000.6200.7200.3090.0000.1090.7080.612
보건0.6510.5240.7810.6650.5780.5250.7700.6201.0000.8360.5700.4590.6110.7000.677
공원녹지0.7140.4020.7550.6960.6010.3930.8290.7200.8361.0000.4380.4140.6040.6860.651
환경0.5640.2590.5930.2190.6530.9790.3610.3090.5700.4381.0000.0000.5540.6120.664
경제/산업0.3410.1800.4130.1140.0000.0000.2780.0000.4590.4140.0001.0000.2700.2880.346
소방안전0.5910.0000.6420.3230.4960.4640.3480.1090.6110.6040.5540.2701.0000.4980.587
기타 불편사항0.8680.0000.8960.3370.7250.7700.6420.7080.7000.6860.6120.2880.4981.0000.726
총합계0.7820.0000.8530.5820.8330.7100.6580.6120.6770.6510.6640.3460.5870.7261.000
2024-03-30T05:27:58.230559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.1040.9810.5780.5470.7920.5780.3380.7290.7840.7550.4720.6850.4700.952
-0.1041.0000.022-0.0680.0640.041-0.0080.0710.1460.0130.1100.1140.007-0.0050.042
교통0.9810.0221.0000.6090.6070.8390.6300.4030.8020.8290.8090.4910.7020.5110.985
도로0.578-0.0680.6091.0000.5320.5230.7900.5430.7040.8080.4940.2060.5510.2330.649
청소0.5470.0640.6070.5321.0000.7670.6480.7510.7750.7300.7740.2370.5720.7490.673
주택건축0.7920.0410.8390.5230.7671.0000.5800.5190.7920.7490.9330.3760.6700.7410.877
치수방재0.578-0.0080.6300.7900.6480.5801.0000.7250.8130.8600.5620.2640.5950.4230.681
가로정비0.3380.0710.4030.5430.7510.5190.7251.0000.6810.6380.5190.0840.3710.5160.486
보건0.7290.1460.8020.7040.7750.7920.8130.6811.0000.9210.8250.3680.6880.6470.852
공원녹지0.7840.0130.8290.8080.7300.7490.8600.6380.9211.0000.7440.3710.7410.5370.862
환경0.7550.1100.8090.4940.7740.9330.5620.5190.8250.7441.0000.3270.6720.7640.856
경제/산업0.4720.1140.4910.2060.2370.3760.2640.0840.3680.3710.3271.0000.3170.2210.452
소방안전0.6850.0070.7020.5510.5720.6700.5950.3710.6880.7410.6720.3171.0000.5840.702
기타 불편사항0.470-0.0050.5110.2330.7490.7410.4230.5160.6470.5370.7640.2210.5841.0000.562
총합계0.9520.0420.9850.6490.6730.8770.6810.4860.8520.8620.8560.4520.7020.5621.000

Missing values

2024-03-30T05:27:39.498949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T05:27:40.463451image/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
11720225595811588316160236947495458791829023307183077
11820226568181665319446648942815608561549220412078128
119202275644918533245318539436275387271252115694781979
12020228584862993321242664759273708761371221280699268
12120229600882328345446638442367269641593112215979948
1222022106563150002941483333490970766819230016694613
1232022116249715502830502296521034650019831068104091
124202212523321615209635216536001492001781205473449
1252023154307145226504431903773108214579004370869
1262023254449140327196163785304142356779105371097