Overview

Dataset statistics

Number of variables15
Number of observations121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.1 KiB
Average record size in memory136.1 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 8 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 년도 and 9 other fieldsHigh correlation
총합계 is highly overall correlated with 년도 and 11 other fieldsHigh correlation
교통 has unique valuesUnique
총합계 has unique valuesUnique
보건 has 4 (3.3%) zerosZeros
경제/산업 has 80 (66.1%) zerosZeros
소방안전 has 15 (12.4%) zerosZeros

Reproduction

Analysis started2024-03-30 05:24:10.835109
Analysis finished2024-03-30 05:25:37.869408
Duration1 minute and 27.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.124
Minimum2012
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:38.063967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12015
median2017
Q32020
95-th percentile2022
Maximum2022
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9483618
Coefficient of variation (CV)0.0014616662
Kurtosis-1.1599382
Mean2017.124
Median Absolute Deviation (MAD)3
Skewness-0.0043558841
Sum244072
Variance8.6928375
MonotonicityIncreasing
2024-03-30T05:25:38.520806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2013 12
9.9%
2014 12
9.9%
2015 12
9.9%
2016 12
9.9%
2017 12
9.9%
2018 12
9.9%
2019 12
9.9%
2020 12
9.9%
2021 12
9.9%
2022 8
6.6%
ValueCountFrequency (%)
2012 5
4.1%
2013 12
9.9%
2014 12
9.9%
2015 12
9.9%
2016 12
9.9%
2017 12
9.9%
2018 12
9.9%
2019 12
9.9%
2020 12
9.9%
2021 12
9.9%
ValueCountFrequency (%)
2022 8
6.6%
2021 12
9.9%
2020 12
9.9%
2019 12
9.9%
2018 12
9.9%
2017 12
9.9%
2016 12
9.9%
2015 12
9.9%
2014 12
9.9%
2013 12
9.9%


Real number (ℝ)

Distinct12
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5123967
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:38.839527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.4547448
Coefficient of variation (CV)0.53048746
Kurtosis-1.2072886
Mean6.5123967
Median Absolute Deviation (MAD)3
Skewness-0.010252341
Sum788
Variance11.935262
MonotonicityNot monotonic
2024-03-30T05:25:39.160602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 11
9.1%
9 10
8.3%
10 10
8.3%
11 10
8.3%
12 10
8.3%
1 10
8.3%
2 10
8.3%
3 10
8.3%
4 10
8.3%
5 10
8.3%
Other values (2) 20
16.5%
ValueCountFrequency (%)
1 10
8.3%
2 10
8.3%
3 10
8.3%
4 10
8.3%
5 10
8.3%
6 10
8.3%
7 10
8.3%
8 11
9.1%
9 10
8.3%
10 10
8.3%
ValueCountFrequency (%)
12 10
8.3%
11 10
8.3%
10 10
8.3%
9 10
8.3%
8 11
9.1%
7 10
8.3%
6 10
8.3%
5 10
8.3%
4 10
8.3%
3 10
8.3%

교통
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23435.587
Minimum46
Maximum59581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:39.678372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46
5-th percentile251
Q16605
median21294
Q339628
95-th percentile51365
Maximum59581
Range59535
Interquartile range (IQR)33023

Descriptive statistics

Standard deviation18034.987
Coefficient of variation (CV)0.76955561
Kurtosis-1.2855621
Mean23435.587
Median Absolute Deviation (MAD)16148
Skewness0.23154858
Sum2835706
Variance3.2526077 × 108
MonotonicityNot monotonic
2024-03-30T05:25:40.267631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46 1
 
0.8%
33170 1
 
0.8%
35082 1
 
0.8%
38404 1
 
0.8%
39628 1
 
0.8%
42206 1
 
0.8%
38355 1
 
0.8%
40621 1
 
0.8%
41523 1
 
0.8%
41234 1
 
0.8%
Other values (111) 111
91.7%
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 (%)
59581 1
0.8%
58486 1
0.8%
56818 1
0.8%
56449 1
0.8%
53254 1
0.8%
51854 1
0.8%
51365 1
0.8%
50225 1
0.8%
49825 1
0.8%
49080 1
0.8%

도로
Real number (ℝ)

HIGH CORRELATION 

Distinct117
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1298.2893
Minimum34
Maximum3494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:40.711952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile238
Q1856
median1223
Q31734
95-th percentile2350
Maximum3494
Range3460
Interquartile range (IQR)878

Descriptive statistics

Standard deviation648.15197
Coefficient of variation (CV)0.49923541
Kurtosis0.35533994
Mean1298.2893
Median Absolute Deviation (MAD)440
Skewness0.40763231
Sum157093
Variance420100.97
MonotonicityNot monotonic
2024-03-30T05:25:41.163553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1726 2
 
1.7%
2019 2
 
1.7%
1166 2
 
1.7%
1318 2
 
1.7%
57 1
 
0.8%
657 1
 
0.8%
1377 1
 
0.8%
1972 1
 
0.8%
1932 1
 
0.8%
1983 1
 
0.8%
Other values (107) 107
88.4%
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 (%)
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%
2197 1
0.8%
2191 1
0.8%
2168 1
0.8%

청소
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2644.1901
Minimum8
Maximum8515
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:41.609819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile29
Q1863
median3082
Q33734
95-th percentile5144
Maximum8515
Range8507
Interquartile range (IQR)2871

Descriptive statistics

Standard deviation1698.7587
Coefficient of variation (CV)0.64244953
Kurtosis-0.043196965
Mean2644.1901
Median Absolute Deviation (MAD)875
Skewness0.042403337
Sum319947
Variance2885781
MonotonicityNot monotonic
2024-03-30T05:25:42.198448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 2
 
1.7%
15 1
 
0.8%
2598 1
 
0.8%
3294 1
 
0.8%
3321 1
 
0.8%
3785 1
 
0.8%
5254 1
 
0.8%
5664 1
 
0.8%
5966 1
 
0.8%
5938 1
 
0.8%
Other values (110) 110
90.9%
ValueCountFrequency (%)
8 1
0.8%
9 1
0.8%
15 1
0.8%
17 1
0.8%
22 2
1.7%
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 

Distinct112
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean391.70248
Minimum2
Maximum3185
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:42.972186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile8
Q187
median336
Q3496
95-th percentile999
Maximum3185
Range3183
Interquartile range (IQR)409

Descriptive statistics

Standard deviation448.58133
Coefficient of variation (CV)1.1452093
Kurtosis16.323829
Mean391.70248
Median Absolute Deviation (MAD)192
Skewness3.4413604
Sum47396
Variance201225.21
MonotonicityNot monotonic
2024-03-30T05:25:43.737650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
274 3
 
2.5%
9 3
 
2.5%
36 2
 
1.7%
302 2
 
1.7%
174 2
 
1.7%
602 2
 
1.7%
2 2
 
1.7%
367 1
 
0.8%
396 1
 
0.8%
664 1
 
0.8%
Other values (102) 102
84.3%
ValueCountFrequency (%)
2 2
1.7%
3 1
 
0.8%
5 1
 
0.8%
6 1
 
0.8%
7 1
 
0.8%
8 1
 
0.8%
9 3
2.5%
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 

Distinct109
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.95868
Minimum0
Maximum720
Zeros1
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:44.713899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14
Q1101
median207
Q3352
95-th percentile462
Maximum720
Range720
Interquartile range (IQR)251

Descriptive statistics

Standard deviation152.88326
Coefficient of variation (CV)0.67066215
Kurtosis-0.29879126
Mean227.95868
Median Absolute Deviation (MAD)129
Skewness0.44995798
Sum27583
Variance23373.29
MonotonicityNot monotonic
2024-03-30T05:25:45.377330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127 2
 
1.7%
102 2
 
1.7%
304 2
 
1.7%
181 2
 
1.7%
325 2
 
1.7%
154 2
 
1.7%
207 2
 
1.7%
156 2
 
1.7%
56 2
 
1.7%
201 2
 
1.7%
Other values (99) 101
83.5%
ValueCountFrequency (%)
0 1
0.8%
2 1
0.8%
7 1
0.8%
9 2
1.7%
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 

Distinct119
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4362.0992
Minimum11
Maximum12906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:46.127126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile72
Q13051
median4511
Q35664
95-th percentile9169
Maximum12906
Range12895
Interquartile range (IQR)2613

Descriptive statistics

Standard deviation2593.2863
Coefficient of variation (CV)0.59450421
Kurtosis0.57019226
Mean4362.0992
Median Absolute Deviation (MAD)1289
Skewness0.34798701
Sum527814
Variance6725133.9
MonotonicityNot monotonic
2024-03-30T05:25:46.867441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
516 2
 
1.7%
4281 2
 
1.7%
11 1
 
0.8%
3797 1
 
0.8%
4743 1
 
0.8%
4761 1
 
0.8%
5800 1
 
0.8%
7263 1
 
0.8%
5730 1
 
0.8%
5488 1
 
0.8%
Other values (109) 109
90.1%
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 

Distinct98
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192.40496
Minimum0
Maximum694
Zeros4
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:47.540017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q140
median128
Q3300
95-th percentile545
Maximum694
Range694
Interquartile range (IQR)260

Descriptive statistics

Standard deviation177.91302
Coefficient of variation (CV)0.92468002
Kurtosis-0.11621578
Mean192.40496
Median Absolute Deviation (MAD)108
Skewness0.89798113
Sum23281
Variance31653.043
MonotonicityNot monotonic
2024-03-30T05:25:48.124854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4
 
3.3%
66 4
 
3.3%
32 3
 
2.5%
258 3
 
2.5%
126 2
 
1.7%
4 2
 
1.7%
118 2
 
1.7%
378 2
 
1.7%
300 2
 
1.7%
42 2
 
1.7%
Other values (88) 95
78.5%
ValueCountFrequency (%)
0 4
3.3%
1 2
1.7%
2 2
1.7%
3 2
1.7%
4 2
1.7%
7 1
 
0.8%
8 2
1.7%
9 1
 
0.8%
11 1
 
0.8%
13 1
 
0.8%
ValueCountFrequency (%)
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%
528 1
0.8%
521 1
0.8%

공원녹지
Real number (ℝ)

HIGH CORRELATION 

Distinct113
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean332.28926
Minimum3
Maximum970
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:48.883222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile22
Q1116
median265
Q3497
95-th percentile876
Maximum970
Range967
Interquartile range (IQR)381

Descriptive statistics

Standard deviation265.95953
Coefficient of variation (CV)0.8003856
Kurtosis-0.44581749
Mean332.28926
Median Absolute Deviation (MAD)164
Skewness0.82282252
Sum40207
Variance70734.474
MonotonicityNot monotonic
2024-03-30T05:25:49.505913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
276 2
 
1.7%
182 2
 
1.7%
378 2
 
1.7%
70 2
 
1.7%
160 2
 
1.7%
51 2
 
1.7%
91 2
 
1.7%
693 2
 
1.7%
583 1
 
0.8%
624 1
 
0.8%
Other values (103) 103
85.1%
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%
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%
791 1
0.8%

환경
Real number (ℝ)

HIGH CORRELATION 

Distinct112
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1206.0248
Minimum1
Maximum9985
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:50.183180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q1217
median961
Q31522
95-th percentile4090
Maximum9985
Range9984
Interquartile range (IQR)1305

Descriptive statistics

Standard deviation1557.6445
Coefficient of variation (CV)1.2915526
Kurtosis12.376795
Mean1206.0248
Median Absolute Deviation (MAD)666
Skewness3.1336402
Sum145929
Variance2426256.4
MonotonicityNot monotonic
2024-03-30T05:25:50.836164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 3
 
2.5%
50 2
 
1.7%
1549 2
 
1.7%
1066 2
 
1.7%
641 2
 
1.7%
34 2
 
1.7%
1044 2
 
1.7%
4 2
 
1.7%
1107 1
 
0.8%
788 1
 
0.8%
Other values (102) 102
84.3%
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
4 2
1.7%
6 3
2.5%
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 (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55371901
Minimum0
Maximum6
Zeros80
Zeros (%)66.1%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:51.320545image/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 deviation1.0323954
Coefficient of variation (CV)1.8644752
Kurtosis8.6386971
Mean0.55371901
Median Absolute Deviation (MAD)0
Skewness2.6951303
Sum67
Variance1.0658402
MonotonicityNot monotonic
2024-03-30T05:25:51.793828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 80
66.1%
1 28
 
23.1%
2 7
 
5.8%
4 4
 
3.3%
3 1
 
0.8%
6 1
 
0.8%
ValueCountFrequency (%)
0 80
66.1%
1 28
 
23.1%
2 7
 
5.8%
3 1
 
0.8%
4 4
 
3.3%
6 1
 
0.8%
ValueCountFrequency (%)
6 1
 
0.8%
4 4
 
3.3%
3 1
 
0.8%
2 7
 
5.8%
1 28
 
23.1%
0 80
66.1%

소방안전
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8760331
Minimum0
Maximum65
Zeros15
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:52.239331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q314
95-th percentile23
Maximum65
Range65
Interquartile range (IQR)12

Descriptive statistics

Standard deviation9.2119218
Coefficient of variation (CV)1.0378422
Kurtosis10.219407
Mean8.8760331
Median Absolute Deviation (MAD)5
Skewness2.2991552
Sum1074
Variance84.859504
MonotonicityNot monotonic
2024-03-30T05:25:52.689398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 15
12.4%
2 10
 
8.3%
8 10
 
8.3%
1 9
 
7.4%
3 8
 
6.6%
5 8
 
6.6%
4 7
 
5.8%
6 6
 
5.0%
20 6
 
5.0%
11 5
 
4.1%
Other values (17) 37
30.6%
ValueCountFrequency (%)
0 15
12.4%
1 9
7.4%
2 10
8.3%
3 8
6.6%
4 7
5.8%
5 8
6.6%
6 6
 
5.0%
7 4
 
3.3%
8 10
8.3%
10 3
 
2.5%
ValueCountFrequency (%)
65 1
 
0.8%
30 1
 
0.8%
27 1
 
0.8%
26 1
 
0.8%
25 1
 
0.8%
23 4
3.3%
22 1
 
0.8%
21 3
2.5%
20 6
5.0%
18 2
 
1.7%

기타 불편사항
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2535.595
Minimum16
Maximum7847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:53.142394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile66
Q1562
median2688
Q33474
95-th percentile5893
Maximum7847
Range7831
Interquartile range (IQR)2912

Descriptive statistics

Standard deviation1853.0529
Coefficient of variation (CV)0.73081581
Kurtosis-0.23389097
Mean2535.595
Median Absolute Deviation (MAD)1226
Skewness0.46939792
Sum306807
Variance3433805.2
MonotonicityNot monotonic
2024-03-30T05:25:53.769330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3442 2
 
1.7%
3071 2
 
1.7%
16 1
 
0.8%
5461 1
 
0.8%
2782 1
 
0.8%
3254 1
 
0.8%
3434 1
 
0.8%
2881 1
 
0.8%
3356 1
 
0.8%
3311 1
 
0.8%
Other values (109) 109
90.1%
ValueCountFrequency (%)
16 1
0.8%
24 1
0.8%
28 1
0.8%
30 1
0.8%
33 1
0.8%
49 1
0.8%
66 1
0.8%
97 1
0.8%
98 1
0.8%
99 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 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38516.017
Minimum230
Maximum99268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-30T05:25:54.367434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum230
5-th percentile1168
Q116076
median38336
Q361043
95-th percentile72633
Maximum99268
Range99038
Interquartile range (IQR)44967

Descriptive statistics

Standard deviation25102.918
Coefficient of variation (CV)0.6517527
Kurtosis-1.150761
Mean38516.017
Median Absolute Deviation (MAD)22707
Skewness-0.036519641
Sum4660438
Variance6.3015648 × 108
MonotonicityNot monotonic
2024-03-30T05:25:55.026783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
230 1
 
0.8%
50517 1
 
0.8%
50606 1
 
0.8%
54987 1
 
0.8%
59699 1
 
0.8%
66417 1
 
0.8%
62711 1
 
0.8%
62998 1
 
0.8%
66096 1
 
0.8%
63922 1
 
0.8%
Other values (111) 111
91.7%
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 (%)
99268 1
0.8%
83077 1
0.8%
81979 1
0.8%
78128 1
0.8%
73786 1
0.8%
73765 1
0.8%
72633 1
0.8%
72502 1
0.8%
71331 1
0.8%
69859 1
0.8%

Interactions

2024-03-30T05:25:31.285535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:16.370767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:21.621627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:26.351022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:32.043694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:37.933920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:42.863321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:49.053477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:54.129204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:59.643862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:05.151760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:11.206255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:16.175687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:21.205614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:25.977352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:31.547142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:16.850837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:21.868123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:26.706821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:32.455409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:38.168080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:43.164010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:49.377704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:54.384110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:59.973164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:05.482054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:11.567348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:16.635457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:21.530180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:26.377786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:31.807600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:17.196578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:22.109225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:27.333426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:32.836782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:38.447889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:43.657237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:49.747499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:54.889559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:00.287321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:05.880657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:11.924574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:16.917883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:21.851935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:26.838974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:32.109923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:17.483945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:22.399106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:27.638578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:33.146347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:38.704645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:44.353111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:50.076402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:55.254007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:00.593792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:06.367768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:12.282374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:17.206829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:22.104244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:27.239899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:32.439599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:17.931633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:22.826889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:27.968981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:33.562620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:39.096650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:44.918528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:50.411851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:55.515482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:00.894326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:06.848619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:12.601640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:17.634963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:22.532558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:27.616235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:32.756563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:18.291791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:23.118814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:28.191030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:34.067241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:39.370734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:45.351995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:50.675675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:55.781345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:01.214719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:07.285393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:12.893423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:18.026150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:22.983387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:27.941381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:33.202119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:18.660484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:23.503062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:28.504186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:34.394388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:39.657043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:45.933385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:51.013462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:56.187564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:01.492454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:07.711317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:13.239837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:18.377064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:23.405463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:28.377728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:33.582647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:19.116569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:23.868728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:29.043503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:34.855353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:40.216052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:46.429850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:51.368238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:56.600989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:01.840356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:08.164546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:13.583113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:18.761806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:23.755603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:28.806008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:33.865669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:19.453473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:24.177234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:29.363665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:35.124747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:40.518281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:46.746210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:51.744160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:56.986022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:02.227837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:08.566633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:13.850924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:19.083241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:24.050018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:29.167768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:34.205500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:19.796171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:24.475981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:29.654816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:35.668283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:40.821662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:47.257434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:52.162963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:57.429574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:02.601391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:09.273630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:14.245836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:19.430436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:24.308032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:29.449714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:34.450524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:20.277040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:24.780061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:29.903992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:35.940747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:41.170902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:47.519103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:52.390927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:57.822607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:02.954664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:09.588723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:14.559455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:19.646359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:24.549489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:29.725948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:34.734174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:20.507266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:25.260797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:30.303622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:36.188624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:41.550701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:47.866737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:52.773597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:58.212744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:03.340035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:09.978440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:14.873565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:19.950158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:24.806727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:30.011374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:35.033862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:20.749941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:25.494745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:30.607090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:36.568355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:41.881290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:48.100659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:53.066829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:58.572685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:03.719216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:10.339777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:15.203551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:20.278671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:25.093517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:30.280689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:35.431922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:20.980456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:25.749440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:31.158583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:37.047568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:42.161787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:48.436886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:53.371191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:58.950908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:04.160639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:10.617451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:15.550573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:20.597020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:25.349076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:30.554431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:36.054415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:21.278613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:26.051161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:31.685370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:37.549132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:42.505884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:48.781924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:53.775447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:24:59.334413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:04.642978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:10.887870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:15.905055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:20.989877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:25.638293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-30T05:25:30.921288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T05:25:55.473241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.0000.0000.9690.7070.6930.6120.6370.7840.6310.7250.5600.3690.6410.8820.901
0.0001.0000.0000.5060.1290.1850.4450.4720.6060.3400.2470.2010.0000.0000.000
교통0.9690.0001.0000.7220.7300.6300.7770.7610.7980.7540.6070.4270.6880.9040.955
도로0.7070.5060.7221.0000.3930.3640.8830.6500.7580.8100.0000.1660.4060.4980.815
청소0.6930.1290.7300.3931.0000.5960.5230.6510.5950.6080.6610.0000.5160.7500.712
주택건축0.6120.1850.6300.3640.5961.0000.3710.3390.5300.3820.9790.0000.5030.7810.642
치수방재0.6370.4450.7770.8830.5230.3711.0000.8380.7850.8240.3550.2720.3850.6810.875
가로정비0.7840.4720.7610.6500.6510.3390.8381.0000.6250.7200.3040.0000.1570.7480.759
보건0.6310.6060.7980.7580.5950.5300.7850.6251.0000.8280.5820.4370.6270.7260.844
공원녹지0.7250.3400.7540.8100.6080.3820.8240.7200.8281.0000.4490.4390.6310.7420.802
환경0.5600.2470.6070.0000.6610.9790.3550.3040.5820.4491.0000.0000.5720.6230.505
경제/산업0.3690.2010.4270.1660.0000.0000.2720.0000.4370.4390.0001.0000.3330.3390.350
소방안전0.6410.0000.6880.4060.5160.5030.3850.1570.6270.6310.5720.3331.0000.4930.635
기타 불편사항0.8820.0000.9040.4980.7500.7810.6810.7480.7260.7420.6230.3390.4931.0000.882
총합계0.9010.0000.9550.8150.7120.6420.8750.7590.8440.8020.5050.3500.6350.8821.000
2024-03-30T05:25:56.164167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도교통도로청소주택건축치수방재가로정비보건공원녹지환경경제/산업소방안전기타 불편사항총합계
년도1.000-0.1330.9800.5650.5990.8100.5940.3680.7490.8100.7830.4700.8660.6330.947
-0.1331.000-0.002-0.0990.0700.045-0.0070.0780.122-0.0010.0660.0900.0170.0110.020
교통0.980-0.0021.0000.5940.6610.8590.6470.4350.8210.8540.8350.4910.8830.6760.984
도로0.565-0.0990.5941.0000.5460.5190.7960.5630.6890.8070.4860.1980.6270.2880.637
청소0.5990.0700.6610.5461.0000.7880.6580.7610.7920.7380.7960.2500.5740.7620.730
주택건축0.8100.0450.8590.5190.7881.0000.5860.5320.8080.7560.9530.3790.7570.8380.898
치수방재0.594-0.0070.6470.7960.6580.5861.0000.7340.8200.8640.5830.2610.6460.4700.700
가로정비0.3680.0780.4350.5630.7610.5320.7341.0000.7000.6500.5380.0880.3960.5420.523
보건0.7490.1220.8210.6890.7920.8080.8200.7001.0000.9210.8320.3720.7630.7280.873
공원녹지0.810-0.0010.8540.8070.7380.7560.8640.6500.9211.0000.7560.3730.8050.5940.888
환경0.7830.0660.8350.4860.7960.9530.5830.5380.8320.7561.0000.3220.7590.8570.882
경제/산업0.4700.0900.4910.1980.2500.3790.2610.0880.3720.3730.3221.0000.3690.2750.446
소방안전0.8660.0170.8830.6270.5740.7570.6460.3960.7630.8050.7590.3691.0000.5380.874
기타 불편사항0.6330.0110.6760.2880.7620.8380.4700.5420.7280.5940.8570.2750.5381.0000.727
총합계0.9470.0200.9840.6370.7300.8980.7000.5230.8730.8880.8820.4460.8740.7271.000

Missing values

2024-03-30T05:25:36.454057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T05:25:37.362564image/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
111202111490801243293537637640522114191066118216165259
11220211247891120126524831814533116354893413205763863
1132022147919100124253031473749114272693215224762349
1142022241541116622473432073149121293999421162655081
11520223479901601267143835038581645441445021223665584
11620224532541415302449846442683006931333015344272633
11720225595811588316160236947495458791829023307183077
11820226568181665319446648942815608561549220412078128
119202275644918533245318539436275387271252115694781979
12020228584862993321242664759273708761371221280699268