Overview

Dataset statistics

Number of variables18
Number of observations5021
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory784.7 KiB
Average record size in memory160.0 B

Variable types

Numeric16
Categorical1
DateTime1

Dataset

Description계획 관리 번호,관리기관코드,관리기관명,투수성포장_면적,투수성포장_대책량,침투측구_연장,침투측구_대책량,침투트렌치_연장,침투트렌치_대책량,원형침투통_개소,원형침투통_대책량,정방형침투통_개소,정방형침투통_대책량,이용시설_저장용량,이용시설_대책량,기타시설_개소,기타시설_대책량,검토요청일
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15647/S/1/datasetView.do

Alerts

관리기관코드 is highly overall correlated with 관리기관명High correlation
투수성포장_면적 is highly overall correlated with 투수성포장_대책량High correlation
투수성포장_대책량 is highly overall correlated with 투수성포장_면적High correlation
침투측구_연장 is highly overall correlated with 침투측구_대책량High correlation
침투측구_대책량 is highly overall correlated with 침투측구_연장High correlation
침투트렌치_연장 is highly overall correlated with 침투트렌치_대책량High correlation
침투트렌치_대책량 is highly overall correlated with 침투트렌치_연장High correlation
원형침투통_개소 is highly overall correlated with 원형침투통_대책량High correlation
원형침투통_대책량 is highly overall correlated with 원형침투통_개소High correlation
정방형침투통_개소 is highly overall correlated with 정방형침투통_대책량High correlation
정방형침투통_대책량 is highly overall correlated with 정방형침투통_개소High correlation
이용시설_저장용량 is highly overall correlated with 이용시설_대책량High correlation
이용시설_대책량 is highly overall correlated with 이용시설_저장용량High correlation
기타시설_개소 is highly overall correlated with 기타시설_대책량High correlation
기타시설_대책량 is highly overall correlated with 기타시설_개소High correlation
관리기관명 is highly overall correlated with 관리기관코드High correlation
투수성포장_면적 is highly skewed (γ1 = 22.08970501)Skewed
투수성포장_대책량 is highly skewed (γ1 = 22.09371942)Skewed
침투측구_연장 is highly skewed (γ1 = 23.49500664)Skewed
침투트렌치_대책량 is highly skewed (γ1 = 20.78181656)Skewed
이용시설_저장용량 is highly skewed (γ1 = 62.91941551)Skewed
이용시설_대책량 is highly skewed (γ1 = 62.93584403)Skewed
기타시설_개소 is highly skewed (γ1 = 46.25823038)Skewed
기타시설_대책량 is highly skewed (γ1 = 69.95628695)Skewed
계획 관리 번호 has unique valuesUnique
투수성포장_면적 has 1653 (32.9%) zerosZeros
투수성포장_대책량 has 1845 (36.7%) zerosZeros
침투측구_연장 has 4083 (81.3%) zerosZeros
침투측구_대책량 has 4146 (82.6%) zerosZeros
침투트렌치_연장 has 2352 (46.8%) zerosZeros
침투트렌치_대책량 has 2488 (49.6%) zerosZeros
원형침투통_개소 has 4675 (93.1%) zerosZeros
원형침투통_대책량 has 4800 (95.6%) zerosZeros
정방형침투통_개소 has 2726 (54.3%) zerosZeros
정방형침투통_대책량 has 3288 (65.5%) zerosZeros
이용시설_저장용량 has 1019 (20.3%) zerosZeros
이용시설_대책량 has 2533 (50.4%) zerosZeros
기타시설_개소 has 4965 (98.9%) zerosZeros
기타시설_대책량 has 4974 (99.1%) zerosZeros

Reproduction

Analysis started2024-05-17 22:01:08.376626
Analysis finished2024-05-17 22:02:24.709977
Duration1 minute and 16.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

계획 관리 번호
Real number (ℝ)

UNIQUE 

Distinct5021
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2711.6837
Minimum1
Maximum5386
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:24.857349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile301
Q11374
median2735
Q34041
95-th percentile5114
Maximum5386
Range5385
Interquartile range (IQR)2667

Descriptive statistics

Standard deviation1545.6902
Coefficient of variation (CV)0.57001123
Kurtosis-1.1920848
Mean2711.6837
Median Absolute Deviation (MAD)1333
Skewness-0.01611523
Sum13615364
Variance2389158.1
MonotonicityNot monotonic
2024-05-18T07:02:25.129902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
999 1
 
< 0.1%
2672 1
 
< 0.1%
2666 1
 
< 0.1%
2667 1
 
< 0.1%
2668 1
 
< 0.1%
2669 1
 
< 0.1%
267 1
 
< 0.1%
2670 1
 
< 0.1%
2671 1
 
< 0.1%
2673 1
 
< 0.1%
Other values (5011) 5011
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
5386 1
< 0.1%
5385 1
< 0.1%
5384 1
< 0.1%
5383 1
< 0.1%
5382 1
< 0.1%
5381 1
< 0.1%
5380 1
< 0.1%
5379 1
< 0.1%
5378 1
< 0.1%
5377 1
< 0.1%

관리기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1143.7224
Minimum1010
Maximum1250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:25.373454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1010
5-th percentile1030
Q11080
median1160
Q31210
95-th percentile1240
Maximum1250
Range240
Interquartile range (IQR)130

Descriptive statistics

Standard deviation70.516208
Coefficient of variation (CV)0.061655005
Kurtosis-1.148107
Mean1143.7224
Median Absolute Deviation (MAD)60
Skewness-0.26146391
Sum5742630
Variance4972.5357
MonotonicityNot monotonic
2024-05-18T07:02:25.606432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1160 556
 
11.1%
1240 298
 
5.9%
1220 295
 
5.9%
1230 290
 
5.8%
1190 278
 
5.5%
1070 266
 
5.3%
1170 238
 
4.7%
1120 235
 
4.7%
1040 226
 
4.5%
1180 218
 
4.3%
Other values (15) 2121
42.2%
ValueCountFrequency (%)
1010 109
2.2%
1020 122
2.4%
1030 148
2.9%
1040 226
4.5%
1050 144
2.9%
1060 213
4.2%
1070 266
5.3%
1080 144
2.9%
1090 165
3.3%
1100 77
 
1.5%
ValueCountFrequency (%)
1250 182
 
3.6%
1240 298
5.9%
1230 290
5.8%
1220 295
5.9%
1210 213
 
4.2%
1200 104
 
2.1%
1190 278
5.5%
1180 218
 
4.3%
1170 238
4.7%
1160 556
11.1%

관리기관명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size39.4 KiB
강서구청
556 
송파구청
 
298
서초구청
 
295
강남구청
 
290
영등포구청
 
278
Other values (20)
3304 

Length

Max length5
Median length4
Mean length4.097391
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row은평구청
2nd row동작구청
3rd row마포구청
4th row중구청
5th row관악구청

Common Values

ValueCountFrequency (%)
강서구청 556
 
11.1%
송파구청 298
 
5.9%
서초구청 295
 
5.9%
강남구청 290
 
5.8%
영등포구청 278
 
5.5%
중랑구청 266
 
5.3%
구로구청 238
 
4.7%
은평구청 235
 
4.7%
성동구청 226
 
4.5%
금천구청 218
 
4.3%
Other values (15) 2121
42.2%

Length

2024-05-18T07:02:25.937833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구청 556
 
11.1%
송파구청 298
 
5.9%
서초구청 295
 
5.9%
강남구청 290
 
5.8%
영등포구청 278
 
5.5%
중랑구청 266
 
5.3%
구로구청 238
 
4.7%
은평구청 235
 
4.7%
성동구청 226
 
4.5%
금천구청 218
 
4.3%
Other values (15) 2121
42.2%

투수성포장_면적
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1148
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean680.96335
Minimum0
Maximum139457
Zeros1653
Zeros (%)32.9%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:26.330358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median81
Q3290
95-th percentile2620
Maximum139457
Range139457
Interquartile range (IQR)290

Descriptive statistics

Standard deviation3571.5683
Coefficient of variation (CV)5.2448759
Kurtosis724.12109
Mean680.96335
Median Absolute Deviation (MAD)81
Skewness22.089705
Sum3419117
Variance12756100
MonotonicityNot monotonic
2024-05-18T07:02:26.756239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1653
32.9%
51 20
 
0.4%
37 19
 
0.4%
71 19
 
0.4%
60 19
 
0.4%
42 18
 
0.4%
81 17
 
0.3%
50 17
 
0.3%
44 17
 
0.3%
39 17
 
0.3%
Other values (1138) 3205
63.8%
ValueCountFrequency (%)
0 1653
32.9%
1 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 4
 
0.1%
6 2
 
< 0.1%
7 3
 
0.1%
8 5
 
0.1%
9 7
 
0.1%
11 3
 
0.1%
ValueCountFrequency (%)
139457 1
< 0.1%
118938 1
< 0.1%
63278 1
< 0.1%
39233 1
< 0.1%
36424 1
< 0.1%
31648 1
< 0.1%
28362 1
< 0.1%
27904 1
< 0.1%
25955 1
< 0.1%
25500 1
< 0.1%

투수성포장_대책량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct189
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.57857
Minimum0
Maximum2371
Zeros1845
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:27.184108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile45
Maximum2371
Range2371
Interquartile range (IQR)5

Descriptive statistics

Standard deviation60.715761
Coefficient of variation (CV)5.2438048
Kurtosis724.36843
Mean11.57857
Median Absolute Deviation (MAD)1
Skewness22.093719
Sum58136
Variance3686.4036
MonotonicityNot monotonic
2024-05-18T07:02:27.597686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1845
36.7%
1 754
15.0%
2 466
 
9.3%
3 344
 
6.9%
4 254
 
5.1%
5 199
 
4.0%
6 150
 
3.0%
7 127
 
2.5%
8 91
 
1.8%
9 59
 
1.2%
Other values (179) 732
 
14.6%
ValueCountFrequency (%)
0 1845
36.7%
1 754
15.0%
2 466
 
9.3%
3 344
 
6.9%
4 254
 
5.1%
5 199
 
4.0%
6 150
 
3.0%
7 127
 
2.5%
8 91
 
1.8%
9 59
 
1.2%
ValueCountFrequency (%)
2371 1
< 0.1%
2022 1
< 0.1%
1076 1
< 0.1%
667 1
< 0.1%
619 1
< 0.1%
538 1
< 0.1%
482 1
< 0.1%
474 1
< 0.1%
441 1
< 0.1%
433 1
< 0.1%

침투측구_연장
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct250
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.427206
Minimum0
Maximum4570
Zeros4083
Zeros (%)81.3%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:27.927155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile97
Maximum4570
Range4570
Interquartile range (IQR)0

Descriptive statistics

Standard deviation102.79548
Coefficient of variation (CV)5.2913156
Kurtosis868.90666
Mean19.427206
Median Absolute Deviation (MAD)0
Skewness23.495007
Sum97544
Variance10566.91
MonotonicityNot monotonic
2024-05-18T07:02:28.292738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4083
81.3%
10 16
 
0.3%
12 16
 
0.3%
40 16
 
0.3%
6 15
 
0.3%
44 15
 
0.3%
30 15
 
0.3%
26 14
 
0.3%
35 14
 
0.3%
60 13
 
0.3%
Other values (240) 804
 
16.0%
ValueCountFrequency (%)
0 4083
81.3%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 4
 
0.1%
4 9
 
0.2%
5 6
 
0.1%
6 15
 
0.3%
7 6
 
0.1%
8 12
 
0.2%
9 10
 
0.2%
ValueCountFrequency (%)
4570 1
< 0.1%
2577 1
< 0.1%
1302 1
< 0.1%
1300 1
< 0.1%
1237 1
< 0.1%
1137 1
< 0.1%
1106 1
< 0.1%
1069 1
< 0.1%
1048 1
< 0.1%
1031 1
< 0.1%

침투측구_대책량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0848437
Minimum0
Maximum206
Zeros4146
Zeros (%)82.6%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:28.696386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum206
Range206
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.4549195
Coefficient of variation (CV)5.0283001
Kurtosis520.47504
Mean1.0848437
Median Absolute Deviation (MAD)0
Skewness18.229136
Sum5447
Variance29.756147
MonotonicityNot monotonic
2024-05-18T07:02:29.102705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 4146
82.6%
1 168
 
3.3%
2 167
 
3.3%
3 127
 
2.5%
4 84
 
1.7%
5 78
 
1.6%
6 48
 
1.0%
7 24
 
0.5%
8 23
 
0.5%
10 23
 
0.5%
Other values (35) 133
 
2.6%
ValueCountFrequency (%)
0 4146
82.6%
1 168
 
3.3%
2 167
 
3.3%
3 127
 
2.5%
4 84
 
1.7%
5 78
 
1.6%
6 48
 
1.0%
7 24
 
0.5%
8 23
 
0.5%
9 16
 
0.3%
ValueCountFrequency (%)
206 1
< 0.1%
132 1
< 0.1%
98 1
< 0.1%
86 1
< 0.1%
74 1
< 0.1%
71 1
< 0.1%
65 1
< 0.1%
62 1
< 0.1%
61 1
< 0.1%
47 2
< 0.1%

침투트렌치_연장
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct319
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.894842
Minimum0
Maximum5004
Zeros2352
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:29.494519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11
Q352
95-th percentile153
Maximum5004
Range5004
Interquartile range (IQR)52

Descriptive statistics

Standard deviation130.07979
Coefficient of variation (CV)2.9634415
Kurtosis481.13087
Mean43.894842
Median Absolute Deviation (MAD)11
Skewness16.512546
Sum220396
Variance16920.753
MonotonicityNot monotonic
2024-05-18T07:02:29.808995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2352
46.8%
15 53
 
1.1%
20 52
 
1.0%
30 46
 
0.9%
27 43
 
0.9%
16 42
 
0.8%
17 39
 
0.8%
40 38
 
0.8%
52 36
 
0.7%
35 35
 
0.7%
Other values (309) 2285
45.5%
ValueCountFrequency (%)
0 2352
46.8%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 7
 
0.1%
4 7
 
0.1%
5 14
 
0.3%
6 19
 
0.4%
7 18
 
0.4%
8 19
 
0.4%
9 15
 
0.3%
ValueCountFrequency (%)
5004 1
< 0.1%
2142 1
< 0.1%
1964 1
< 0.1%
1855 1
< 0.1%
1833 1
< 0.1%
1727 1
< 0.1%
1691 1
< 0.1%
1274 1
< 0.1%
1242 1
< 0.1%
1211 1
< 0.1%

침투트렌치_대책량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct53
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3875722
Minimum0
Maximum339
Zeros2488
Zeros (%)49.6%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:30.118861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile9
Maximum339
Range339
Interquartile range (IQR)3

Descriptive statistics

Standard deviation7.8364734
Coefficient of variation (CV)3.2821933
Kurtosis735.38572
Mean2.3875722
Median Absolute Deviation (MAD)1
Skewness20.781817
Sum11988
Variance61.410316
MonotonicityNot monotonic
2024-05-18T07:02:30.494219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2488
49.6%
1 647
 
12.9%
2 528
 
10.5%
3 436
 
8.7%
4 280
 
5.6%
5 152
 
3.0%
6 108
 
2.2%
7 77
 
1.5%
8 50
 
1.0%
9 38
 
0.8%
Other values (43) 217
 
4.3%
ValueCountFrequency (%)
0 2488
49.6%
1 647
 
12.9%
2 528
 
10.5%
3 436
 
8.7%
4 280
 
5.6%
5 152
 
3.0%
6 108
 
2.2%
7 77
 
1.5%
8 50
 
1.0%
9 38
 
0.8%
ValueCountFrequency (%)
339 1
< 0.1%
128 2
< 0.1%
115 1
< 0.1%
106 1
< 0.1%
102 1
< 0.1%
87 1
< 0.1%
81 1
< 0.1%
73 1
< 0.1%
71 1
< 0.1%
69 1
< 0.1%

원형침투통_개소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.54212308
Minimum0
Maximum86
Zeros4675
Zeros (%)93.1%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:30.959990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum86
Range86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.3671823
Coefficient of variation (CV)6.211103
Kurtosis240.00423
Mean0.54212308
Median Absolute Deviation (MAD)0
Skewness13.388312
Sum2722
Variance11.337917
MonotonicityNot monotonic
2024-05-18T07:02:31.305120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 4675
93.1%
3 46
 
0.9%
4 40
 
0.8%
6 39
 
0.8%
5 39
 
0.8%
2 38
 
0.8%
8 25
 
0.5%
1 23
 
0.5%
7 19
 
0.4%
10 13
 
0.3%
Other values (24) 64
 
1.3%
ValueCountFrequency (%)
0 4675
93.1%
1 23
 
0.5%
2 38
 
0.8%
3 46
 
0.9%
4 40
 
0.8%
5 39
 
0.8%
6 39
 
0.8%
7 19
 
0.4%
8 25
 
0.5%
9 8
 
0.2%
ValueCountFrequency (%)
86 1
< 0.1%
71 1
< 0.1%
63 2
< 0.1%
60 2
< 0.1%
52 1
< 0.1%
48 1
< 0.1%
42 1
< 0.1%
37 1
< 0.1%
30 2
< 0.1%
29 1
< 0.1%

원형침투통_대책량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct13
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.086237801
Minimum0
Maximum15
Zeros4800
Zeros (%)95.6%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:31.643984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.62479623
Coefficient of variation (CV)7.2450389
Kurtosis251.24853
Mean0.086237801
Median Absolute Deviation (MAD)0
Skewness13.903743
Sum433
Variance0.39037033
MonotonicityNot monotonic
2024-05-18T07:02:32.012341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 4800
95.6%
1 153
 
3.0%
2 34
 
0.7%
3 9
 
0.2%
7 5
 
0.1%
5 4
 
0.1%
6 4
 
0.1%
4 4
 
0.1%
9 3
 
0.1%
15 2
 
< 0.1%
Other values (3) 3
 
0.1%
ValueCountFrequency (%)
0 4800
95.6%
1 153
 
3.0%
2 34
 
0.7%
3 9
 
0.2%
4 4
 
0.1%
5 4
 
0.1%
6 4
 
0.1%
7 5
 
0.1%
8 1
 
< 0.1%
9 3
 
0.1%
ValueCountFrequency (%)
15 2
 
< 0.1%
14 1
 
< 0.1%
11 1
 
< 0.1%
9 3
 
0.1%
8 1
 
< 0.1%
7 5
0.1%
6 4
0.1%
5 4
0.1%
4 4
0.1%
3 9
0.2%

정방형침투통_개소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct72
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.158335
Minimum0
Maximum267
Zeros2726
Zeros (%)54.3%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:32.412195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile15
Maximum267
Range267
Interquartile range (IQR)5

Descriptive statistics

Standard deviation10.315357
Coefficient of variation (CV)2.4806461
Kurtosis171.6364
Mean4.158335
Median Absolute Deviation (MAD)0
Skewness10.153113
Sum20879
Variance106.4066
MonotonicityNot monotonic
2024-05-18T07:02:32.686590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2726
54.3%
4 264
 
5.3%
5 253
 
5.0%
6 231
 
4.6%
3 225
 
4.5%
2 209
 
4.2%
8 153
 
3.0%
7 146
 
2.9%
9 118
 
2.4%
10 95
 
1.9%
Other values (62) 601
 
12.0%
ValueCountFrequency (%)
0 2726
54.3%
1 90
 
1.8%
2 209
 
4.2%
3 225
 
4.5%
4 264
 
5.3%
5 253
 
5.0%
6 231
 
4.6%
7 146
 
2.9%
8 153
 
3.0%
9 118
 
2.4%
ValueCountFrequency (%)
267 1
 
< 0.1%
207 1
 
< 0.1%
199 1
 
< 0.1%
129 2
< 0.1%
121 1
 
< 0.1%
119 1
 
< 0.1%
117 1
 
< 0.1%
109 2
< 0.1%
102 1
 
< 0.1%
97 3
0.1%

정방형침투통_대책량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.62417845
Minimum0
Maximum52
Zeros3288
Zeros (%)65.5%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:32.925044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum52
Range52
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7354876
Coefficient of variation (CV)2.780435
Kurtosis275.57264
Mean0.62417845
Median Absolute Deviation (MAD)0
Skewness12.742392
Sum3134
Variance3.0119173
MonotonicityNot monotonic
2024-05-18T07:02:33.186294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 3288
65.5%
1 1172
 
23.3%
2 307
 
6.1%
3 132
 
2.6%
4 46
 
0.9%
5 22
 
0.4%
6 11
 
0.2%
7 10
 
0.2%
14 5
 
0.1%
8 5
 
0.1%
Other values (15) 23
 
0.5%
ValueCountFrequency (%)
0 3288
65.5%
1 1172
 
23.3%
2 307
 
6.1%
3 132
 
2.6%
4 46
 
0.9%
5 22
 
0.4%
6 11
 
0.2%
7 10
 
0.2%
8 5
 
0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
52 1
< 0.1%
44 1
< 0.1%
30 1
< 0.1%
23 1
< 0.1%
22 1
< 0.1%
20 1
< 0.1%
19 2
< 0.1%
18 1
< 0.1%
17 1
< 0.1%
16 1
< 0.1%

이용시설_저장용량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct390
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.374826
Minimum0
Maximum115277
Zeros1019
Zeros (%)20.3%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:33.437065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q336
95-th percentile209
Maximum115277
Range115277
Interquartile range (IQR)34

Descriptive statistics

Standard deviation1700.6584
Coefficient of variation (CV)20.155993
Kurtosis4209.2645
Mean84.374826
Median Absolute Deviation (MAD)9
Skewness62.919416
Sum423646
Variance2892239
MonotonicityNot monotonic
2024-05-18T07:02:33.730800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1019
20.3%
2 286
 
5.7%
3 250
 
5.0%
4 246
 
4.9%
1 233
 
4.6%
5 152
 
3.0%
6 123
 
2.4%
7 93
 
1.9%
8 92
 
1.8%
9 92
 
1.8%
Other values (380) 2435
48.5%
ValueCountFrequency (%)
0 1019
20.3%
1 233
 
4.6%
2 286
 
5.7%
3 250
 
5.0%
4 246
 
4.9%
5 152
 
3.0%
6 123
 
2.4%
7 93
 
1.9%
8 92
 
1.8%
9 92
 
1.8%
ValueCountFrequency (%)
115277 1
< 0.1%
27350 1
< 0.1%
13126 1
< 0.1%
9301 1
< 0.1%
8403 1
< 0.1%
7047 1
< 0.1%
5538 1
< 0.1%
3148 1
< 0.1%
2211 1
< 0.1%
2089 1
< 0.1%

이용시설_대책량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct76
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7261502
Minimum0
Maximum6522
Zeros2533
Zeros (%)50.4%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:34.007781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile12
Maximum6522
Range6522
Interquartile range (IQR)2

Descriptive statistics

Standard deviation96.207928
Coefficient of variation (CV)20.356511
Kurtosis4211.0252
Mean4.7261502
Median Absolute Deviation (MAD)0
Skewness62.935844
Sum23730
Variance9255.9654
MonotonicityNot monotonic
2024-05-18T07:02:34.454120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2533
50.4%
1 972
 
19.4%
2 435
 
8.7%
3 234
 
4.7%
4 161
 
3.2%
5 123
 
2.4%
6 89
 
1.8%
7 57
 
1.1%
8 44
 
0.9%
11 43
 
0.9%
Other values (66) 330
 
6.6%
ValueCountFrequency (%)
0 2533
50.4%
1 972
 
19.4%
2 435
 
8.7%
3 234
 
4.7%
4 161
 
3.2%
5 123
 
2.4%
6 89
 
1.8%
7 57
 
1.1%
8 44
 
0.9%
9 33
 
0.7%
ValueCountFrequency (%)
6522 1
< 0.1%
1545 1
< 0.1%
742 1
< 0.1%
526 1
< 0.1%
475 1
< 0.1%
398 1
< 0.1%
312 1
< 0.1%
176 1
< 0.1%
125 1
< 0.1%
118 1
< 0.1%

기타시설_개소
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct40
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7153953
Minimum0
Maximum5493
Zeros4965
Zeros (%)98.9%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:34.840524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5493
Range5493
Interquartile range (IQR)0

Descriptive statistics

Standard deviation92.384359
Coefficient of variation (CV)24.865284
Kurtosis2560.4013
Mean3.7153953
Median Absolute Deviation (MAD)0
Skewness46.25823
Sum18655
Variance8534.8698
MonotonicityNot monotonic
2024-05-18T07:02:35.220784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 4965
98.9%
1 10
 
0.2%
16 2
 
< 0.1%
11 2
 
< 0.1%
102 2
 
< 0.1%
5 2
 
< 0.1%
197 2
 
< 0.1%
126 2
 
< 0.1%
8 2
 
< 0.1%
190 2
 
< 0.1%
Other values (30) 30
 
0.6%
ValueCountFrequency (%)
0 4965
98.9%
1 10
 
0.2%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 2
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
11 2
 
< 0.1%
12 1
 
< 0.1%
16 2
 
< 0.1%
ValueCountFrequency (%)
5493 1
< 0.1%
1914 1
< 0.1%
1793 1
< 0.1%
1218 1
< 0.1%
1062 1
< 0.1%
798 1
< 0.1%
746 1
< 0.1%
728 1
< 0.1%
623 1
< 0.1%
511 1
< 0.1%

기타시설_대책량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct24
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51404103
Minimum0
Maximum1886
Zeros4974
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size44.3 KiB
2024-05-18T07:02:35.583343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1886
Range1886
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26.730797
Coefficient of variation (CV)52.001291
Kurtosis4934.0262
Mean0.51404103
Median Absolute Deviation (MAD)0
Skewness69.956287
Sum2581
Variance714.53551
MonotonicityNot monotonic
2024-05-18T07:02:35.960791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 4974
99.1%
1 13
 
0.3%
2 6
 
0.1%
8 4
 
0.1%
24 2
 
< 0.1%
45 2
 
< 0.1%
10 2
 
< 0.1%
9 2
 
< 0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
Other values (14) 14
 
0.3%
ValueCountFrequency (%)
0 4974
99.1%
1 13
 
0.3%
2 6
 
0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 4
 
0.1%
9 2
 
< 0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
1886 1
< 0.1%
93 1
< 0.1%
66 1
< 0.1%
65 1
< 0.1%
61 1
< 0.1%
45 2
< 0.1%
41 1
< 0.1%
33 1
< 0.1%
30 1
< 0.1%
24 2
< 0.1%
Distinct1953
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Memory size39.4 KiB
Minimum2014-02-11 00:00:00
Maximum2024-04-26 00:00:00
2024-05-18T07:02:36.245553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:36.598109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-18T07:02:18.663746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:19.037459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:22.965720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:26.392173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:30.561661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:34.721281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:38.844652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:42.001034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:45.799273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:50.615852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:54.407153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:58.787019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:02.578356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:06.398810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:11.075020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:14.990878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:18.844678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:19.349367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:23.274225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:26.665524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:30.760293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:34.991994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:39.014023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:42.173661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:46.117346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:50.892009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:54.638061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:59.054294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:02.841457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:06.631795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-05-18T07:01:38.488132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:41.602639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:45.134974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:50.052541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:53.828288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:58.230517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:02.028466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:05.892068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:10.489273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:14.566196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:18.309258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:23.192445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:22.739968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:26.125813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:30.366633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:34.438502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:38.661622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:41.815133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:45.401313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:50.327078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:54.124818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:01:58.499801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:02.297078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:06.119731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:10.764410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:14.790900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:02:18.476755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T07:02:36.893746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계획 관리 번호관리기관코드관리기관명투수성포장_면적투수성포장_대책량침투측구_연장침투측구_대책량침투트렌치_연장침투트렌치_대책량원형침투통_개소원형침투통_대책량정방형침투통_개소정방형침투통_대책량이용시설_저장용량이용시설_대책량기타시설_개소기타시설_대책량
계획 관리 번호1.0000.2470.3940.0590.0550.0420.0200.0190.0240.0680.0600.0500.0240.0110.0110.0620.000
관리기관코드0.2471.0001.0000.0000.0000.0000.0000.0300.0460.0570.0620.0000.0240.0000.0000.0390.000
관리기관명0.3941.0001.0000.0200.0320.1070.1030.1240.1410.1200.0850.0430.0360.0000.0000.0560.000
투수성포장_면적0.0590.0000.0201.0001.0000.2180.2630.5820.2620.1880.0970.3050.2850.0000.0000.0000.234
투수성포장_대책량0.0550.0000.0321.0001.0000.2150.2590.6190.2770.1850.0940.3200.2970.0000.0000.0000.230
침투측구_연장0.0420.0000.1070.2180.2151.0000.9300.6700.8810.8410.4640.6140.6280.0000.0000.1941.000
침투측구_대책량0.0200.0000.1030.2630.2590.9301.0000.6880.6900.6700.4350.8440.6780.0000.0000.1651.000
침투트렌치_연장0.0190.0300.1240.5820.6190.6700.6881.0000.9090.7180.5530.5520.5540.0000.0000.0000.000
침투트렌치_대책량0.0240.0460.1410.2620.2770.8810.6900.9091.0000.8780.5690.5530.5270.0000.0000.0000.000
원형침투통_개소0.0680.0570.1200.1880.1850.8410.6700.7180.8781.0000.8900.2660.2360.0000.0000.0000.000
원형침투통_대책량0.0600.0620.0850.0970.0940.4640.4350.5530.5690.8901.0000.1840.1820.0000.0000.0000.000
정방형침투통_개소0.0500.0000.0430.3050.3200.6140.8440.5520.5530.2660.1841.0000.9040.0000.0000.1200.655
정방형침투통_대책량0.0240.0240.0360.2850.2970.6280.6780.5540.5270.2360.1820.9041.0000.0000.0000.0850.883
이용시설_저장용량0.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.0000.000
이용시설_대책량0.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0001.0000.0000.000
기타시설_개소0.0620.0390.0560.0000.0000.1940.1650.0000.0000.0000.0000.1200.0850.0000.0001.0000.000
기타시설_대책량0.0000.0000.0000.2340.2301.0001.0000.0000.0000.0000.0000.6550.8830.0000.0000.0001.000
2024-05-18T07:02:37.277039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계획 관리 번호관리기관코드투수성포장_면적투수성포장_대책량침투측구_연장침투측구_대책량침투트렌치_연장침투트렌치_대책량원형침투통_개소원형침투통_대책량정방형침투통_개소정방형침투통_대책량이용시설_저장용량이용시설_대책량기타시설_개소기타시설_대책량관리기관명
계획 관리 번호1.000-0.081-0.066-0.067-0.039-0.0370.0500.043-0.065-0.066-0.001-0.003-0.022-0.037-0.043-0.0480.149
관리기관코드-0.0811.0000.0080.009-0.001-0.0010.0120.012-0.012-0.017-0.003-0.0070.0110.024-0.012-0.0060.999
투수성포장_면적-0.0660.0081.0000.9900.0530.062-0.152-0.136-0.061-0.028-0.081-0.0610.3730.3880.1120.1050.009
투수성포장_대책량-0.0670.0090.9901.0000.0540.062-0.144-0.127-0.061-0.027-0.079-0.0570.3780.3930.1130.1060.014
침투측구_연장-0.039-0.0010.0530.0541.0000.972-0.163-0.1520.0430.0490.1410.1410.0920.1080.0480.0320.046
침투측구_대책량-0.037-0.0010.0620.0620.9721.000-0.163-0.1510.0420.0480.1380.1370.0980.1140.0400.0220.044
침투트렌치_연장0.0500.012-0.152-0.144-0.163-0.1631.0000.9830.1040.0960.4230.3720.0280.048-0.008-0.0140.055
침투트렌치_대책량0.0430.012-0.136-0.127-0.152-0.1510.9831.0000.1030.0970.4120.3680.0450.064-0.004-0.0100.061
원형침투통_개소-0.065-0.012-0.061-0.0610.0430.0420.1040.1031.0000.805-0.142-0.110-0.056-0.038-0.021-0.0180.042
원형침투통_대책량-0.066-0.017-0.028-0.0270.0490.0480.0960.0970.8051.000-0.099-0.071-0.023-0.014-0.014-0.0110.030
정방형침투통_개소-0.001-0.003-0.081-0.0790.1410.1380.4230.412-0.142-0.0991.0000.8980.0770.0950.0080.0000.018
정방형침투통_대책량-0.003-0.007-0.061-0.0570.1410.1370.3720.368-0.110-0.0710.8981.0000.0590.0780.0140.0050.014
이용시설_저장용량-0.0220.0110.3730.3780.0920.0980.0280.045-0.056-0.0230.0770.0591.0000.9320.0990.0920.000
이용시설_대책량-0.0370.0240.3880.3930.1080.1140.0480.064-0.038-0.0140.0950.0780.9321.0000.1120.1030.000
기타시설_개소-0.043-0.0120.1120.1130.0480.040-0.008-0.004-0.021-0.0140.0080.0140.0990.1121.0000.9160.024
기타시설_대책량-0.048-0.0060.1050.1060.0320.022-0.014-0.010-0.018-0.0110.0000.0050.0920.1030.9161.0000.000
관리기관명0.1490.9990.0090.0140.0460.0440.0550.0610.0420.0300.0180.0140.0000.0000.0240.0001.000

Missing values

2024-05-18T07:02:23.693755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:02:24.410877image/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

계획 관리 번호관리기관코드관리기관명투수성포장_면적투수성포장_대책량침투측구_연장침투측구_대책량침투트렌치_연장침투트렌치_대책량원형침투통_개소원형침투통_대책량정방형침투통_개소정방형침투통_대책량이용시설_저장용량이용시설_대책량기타시설_개소기타시설_대책량검토요청일
09991120은평구청00282000031151002016-02-03 00:00:00.0
19981200동작구청0000582005100002016-02-15 00:00:00.0
29971140마포구청36100000000121002016-02-15 00:00:00.0
39961020중구청20000000000171002016-02-04 00:00:00.0
49951210관악구청161345300000000002016-02-03 00:00:00.0
59941110노원구청11055200000020002016-02-11 00:00:00.0
69931020중구청75100452002050002016-02-03 00:00:00.0
79921250강동구청32455500000000764002016-02-11 00:00:00.0
89911110노원구청421301006100181002016-02-03 00:00:00.0
99901180금천구청000090006100002016-01-28 00:00:00.0
계획 관리 번호관리기관코드관리기관명투수성포장_면적투수성포장_대책량침투측구_연장침투측구_대책량침투트렌치_연장침투트렌치_대책량원형침투통_개소원형침투통_대책량정방형침투통_개소정방형침투통_대책량이용시설_저장용량이용시설_대책량기타시설_개소기타시설_대책량검토요청일
501110081190영등포구청166482834142418911002031267002016-02-05 00:00:00.0
501210061220서초구청22263817910000025424414002019-05-21 00:00:00.0
501310051020중구청5369402000051955002016-02-18 00:00:00.0
501410041020중구청19000000041101002016-02-04 00:00:00.0
501510031220서초구청0000000000191002016-02-15 00:00:00.0
501610011230강남구청0000412007100002016-02-16 00:00:00.0
501710001220서초구청205300603000000002016-02-03 00:00:00.0
50181001160강서구청447800000000945002014-07-24 00:00:00.0
5019101220서초구청00000000122473002014-04-01 00:00:00.0
502011020중구청169300000081261002014-02-11 00:00:00.0