Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory124.0 B

Variable types

Categorical1
Numeric12

Dataset

Description경기도 의정부시 관내 상수도 사용주소별 사용량 현황을 제공하는 데이터입니다. 수도 사용주소는 동명으로 표기되어 있으며 사용주소별 월별 사용량을 제공하고 있습니다. 주소, 1월 사용량, 2월 사용량, 3월 사용량, 4월 사용량, 5월 사용량, 6월 사용량, 7월 사용량, 8월 사용량, 9월 사용량, 10월 사용량, 11월 사용량, 12월 사용량
Author경기도 의정부시
URLhttps://www.data.go.kr/data/15039900/fileData.do

Alerts

1월사용량 is highly skewed (γ1 = 23.70671025)Skewed
2월사용량 is highly skewed (γ1 = 22.63791046)Skewed
3월사용량 is highly skewed (γ1 = 22.09082495)Skewed
4월사용량 is highly skewed (γ1 = 23.37181907)Skewed
5월사용량 is highly skewed (γ1 = 20.96576695)Skewed
6월사용량 is highly skewed (γ1 = 24.31286816)Skewed
7월사용량 is highly skewed (γ1 = 22.40955632)Skewed
8월사용량 is highly skewed (γ1 = 22.22343316)Skewed
9월사용량 is highly skewed (γ1 = 24.55311978)Skewed
10월사용량 is highly skewed (γ1 = 22.34008379)Skewed
11월사용량 is highly skewed (γ1 = 21.36883895)Skewed
12월사용량 is highly skewed (γ1 = 22.83526417)Skewed
1월사용량 has 1058 (10.6%) zerosZeros
2월사용량 has 1205 (12.0%) zerosZeros
3월사용량 has 1167 (11.7%) zerosZeros
4월사용량 has 1078 (10.8%) zerosZeros
5월사용량 has 1007 (10.1%) zerosZeros
6월사용량 has 1017 (10.2%) zerosZeros
7월사용량 has 1118 (11.2%) zerosZeros
8월사용량 has 1270 (12.7%) zerosZeros
9월사용량 has 1031 (10.3%) zerosZeros
10월사용량 has 948 (9.5%) zerosZeros
11월사용량 has 1049 (10.5%) zerosZeros
12월사용량 has 1315 (13.2%) zerosZeros

Reproduction

Analysis started2023-12-12 19:48:17.962313
Analysis finished2023-12-12 19:48:44.278784
Duration26.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주소
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
의정부1동
1810 
의정부2동
1692 
가능동
1042 
호원1동
992 
흥선동
844 
Other values (11)
3620 

Length

Max length7
Median length5
Mean length4.0378
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row호원1동
2nd row호원1동
3rd row의정부1동
4th row송산2동
5th row의정부1동

Common Values

ValueCountFrequency (%)
의정부1동 1810
18.1%
의정부2동 1692
16.9%
가능동 1042
10.4%
호원1동 992
9.9%
흥선동 844
8.4%
자금동 637
 
6.4%
송산1동 620
 
6.2%
신곡1동 529
 
5.3%
녹양동 453
 
4.5%
송산2동 446
 
4.5%
Other values (6) 935
9.3%

Length

2023-12-13T04:48:44.384389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의정부1동 1810
18.1%
의정부2동 1692
16.9%
가능동 1042
10.4%
호원1동 992
9.9%
흥선동 844
8.4%
자금동 637
 
6.4%
송산1동 620
 
6.2%
신곡1동 529
 
5.3%
녹양동 453
 
4.5%
송산2동 446
 
4.5%
Other values (6) 935
9.3%

1월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct343
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.8078
Minimum0
Maximum31795
Zeros1058
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:44.584328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q326
95-th percentile82
Maximum31795
Range31795
Interquartile range (IQR)20

Descriptive statistics

Standard deviation756.0485
Coefficient of variation (CV)11.149875
Kurtosis685.8482
Mean67.8078
Median Absolute Deviation (MAD)9
Skewness23.70671
Sum678078
Variance571609.34
MonotonicityNot monotonic
2023-12-13T04:48:44.779246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1058
 
10.6%
5 357
 
3.6%
8 356
 
3.6%
7 351
 
3.5%
11 343
 
3.4%
6 337
 
3.4%
10 319
 
3.2%
4 317
 
3.2%
13 316
 
3.2%
15 303
 
3.0%
Other values (333) 5943
59.4%
ValueCountFrequency (%)
0 1058
10.6%
1 187
 
1.9%
2 187
 
1.9%
3 254
 
2.5%
4 317
 
3.2%
5 357
 
3.6%
6 337
 
3.4%
7 351
 
3.5%
8 356
 
3.6%
9 302
 
3.0%
ValueCountFrequency (%)
31795 1
< 0.1%
25627 1
< 0.1%
21672 1
< 0.1%
17730 1
< 0.1%
17091 1
< 0.1%
15422 1
< 0.1%
14832 1
< 0.1%
14457 1
< 0.1%
14280 1
< 0.1%
14118 1
< 0.1%

2월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct336
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.1362
Minimum0
Maximum23619
Zeros1205
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:44.996639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q326
95-th percentile79
Maximum23619
Range23619
Interquartile range (IQR)20

Descriptive statistics

Standard deviation679.02123
Coefficient of variation (CV)10.754864
Kurtosis577.65973
Mean63.1362
Median Absolute Deviation (MAD)9
Skewness22.63791
Sum631362
Variance461069.84
MonotonicityNot monotonic
2023-12-13T04:48:45.217188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1205
 
12.0%
8 343
 
3.4%
7 341
 
3.4%
11 336
 
3.4%
10 325
 
3.2%
5 319
 
3.2%
13 313
 
3.1%
15 295
 
2.9%
14 290
 
2.9%
6 275
 
2.8%
Other values (326) 5958
59.6%
ValueCountFrequency (%)
0 1205
12.0%
1 157
 
1.6%
2 175
 
1.8%
3 256
 
2.6%
4 266
 
2.7%
5 319
 
3.2%
6 275
 
2.8%
7 341
 
3.4%
8 343
 
3.4%
9 258
 
2.6%
ValueCountFrequency (%)
23619 1
< 0.1%
20529 1
< 0.1%
18818 1
< 0.1%
18387 1
< 0.1%
17793 1
< 0.1%
17461 1
< 0.1%
15762 1
< 0.1%
15674 1
< 0.1%
15661 1
< 0.1%
12870 1
< 0.1%

3월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct334
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.6711
Minimum0
Maximum23336
Zeros1167
Zeros (%)11.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:45.429215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q326
95-th percentile80
Maximum23336
Range23336
Interquartile range (IQR)20

Descriptive statistics

Standard deviation604.73427
Coefficient of variation (CV)10.134458
Kurtosis566.87957
Mean59.6711
Median Absolute Deviation (MAD)9
Skewness22.090825
Sum596711
Variance365703.54
MonotonicityNot monotonic
2023-12-13T04:48:45.614852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1167
 
11.7%
6 329
 
3.3%
7 321
 
3.2%
10 320
 
3.2%
11 317
 
3.2%
9 312
 
3.1%
13 308
 
3.1%
12 307
 
3.1%
8 300
 
3.0%
5 300
 
3.0%
Other values (324) 6019
60.2%
ValueCountFrequency (%)
0 1167
11.7%
1 198
 
2.0%
2 186
 
1.9%
3 251
 
2.5%
4 273
 
2.7%
5 300
 
3.0%
6 329
 
3.3%
7 321
 
3.2%
8 300
 
3.0%
9 312
 
3.1%
ValueCountFrequency (%)
23336 1
< 0.1%
16203 1
< 0.1%
15775 1
< 0.1%
15326 1
< 0.1%
15144 1
< 0.1%
13572 1
< 0.1%
13492 1
< 0.1%
13324 1
< 0.1%
11946 1
< 0.1%
11830 1
< 0.1%

4월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct332
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.2066
Minimum0
Maximum27485
Zeros1078
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:45.804053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median12
Q323
95-th percentile71
Maximum27485
Range27485
Interquartile range (IQR)17

Descriptive statistics

Standard deviation681.05851
Coefficient of variation (CV)10.948332
Kurtosis647.40297
Mean62.2066
Median Absolute Deviation (MAD)8
Skewness23.371819
Sum622066
Variance463840.69
MonotonicityNot monotonic
2023-12-13T04:48:45.983736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1078
 
10.8%
7 405
 
4.0%
10 372
 
3.7%
8 367
 
3.7%
5 363
 
3.6%
12 354
 
3.5%
9 353
 
3.5%
11 346
 
3.5%
6 343
 
3.4%
4 333
 
3.3%
Other values (322) 5686
56.9%
ValueCountFrequency (%)
0 1078
10.8%
1 197
 
2.0%
2 225
 
2.2%
3 272
 
2.7%
4 333
 
3.3%
5 363
 
3.6%
6 343
 
3.4%
7 405
 
4.0%
8 367
 
3.7%
9 353
 
3.5%
ValueCountFrequency (%)
27485 1
< 0.1%
21481 1
< 0.1%
17582 1
< 0.1%
17285 1
< 0.1%
17105 1
< 0.1%
16415 1
< 0.1%
15659 1
< 0.1%
14624 1
< 0.1%
14497 1
< 0.1%
13246 1
< 0.1%

5월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct333
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.507
Minimum0
Maximum21289
Zeros1007
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:46.534255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q325
95-th percentile79
Maximum21289
Range21289
Interquartile range (IQR)19

Descriptive statistics

Standard deviation646.04704
Coefficient of variation (CV)10.503634
Kurtosis487.61563
Mean61.507
Median Absolute Deviation (MAD)9
Skewness20.965767
Sum615070
Variance417376.77
MonotonicityNot monotonic
2023-12-13T04:48:46.787836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1007
 
10.1%
6 389
 
3.9%
5 362
 
3.6%
10 353
 
3.5%
7 341
 
3.4%
12 323
 
3.2%
13 323
 
3.2%
16 319
 
3.2%
8 313
 
3.1%
9 311
 
3.1%
Other values (323) 5959
59.6%
ValueCountFrequency (%)
0 1007
10.1%
1 180
 
1.8%
2 174
 
1.7%
3 278
 
2.8%
4 308
 
3.1%
5 362
 
3.6%
6 389
 
3.9%
7 341
 
3.4%
8 313
 
3.1%
9 311
 
3.1%
ValueCountFrequency (%)
21289 1
< 0.1%
16830 1
< 0.1%
16438 1
< 0.1%
16436 1
< 0.1%
16030 1
< 0.1%
15486 1
< 0.1%
14825 1
< 0.1%
14374 1
< 0.1%
14297 1
< 0.1%
13939 1
< 0.1%

6월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct356
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.2404
Minimum0
Maximum35187
Zeros1017
Zeros (%)10.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:46.998369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q326
95-th percentile83
Maximum35187
Range35187
Interquartile range (IQR)20

Descriptive statistics

Standard deviation839.73342
Coefficient of variation (CV)11.46544
Kurtosis713.20796
Mean73.2404
Median Absolute Deviation (MAD)9
Skewness24.312868
Sum732404
Variance705152.21
MonotonicityNot monotonic
2023-12-13T04:48:47.230040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1017
 
10.2%
5 360
 
3.6%
10 359
 
3.6%
6 346
 
3.5%
11 338
 
3.4%
8 335
 
3.4%
13 306
 
3.1%
7 305
 
3.0%
9 301
 
3.0%
14 301
 
3.0%
Other values (346) 6032
60.3%
ValueCountFrequency (%)
0 1017
10.2%
1 163
 
1.6%
2 198
 
2.0%
3 234
 
2.3%
4 284
 
2.8%
5 360
 
3.6%
6 346
 
3.5%
7 305
 
3.0%
8 335
 
3.4%
9 301
 
3.0%
ValueCountFrequency (%)
35187 1
< 0.1%
29227 1
< 0.1%
22655 1
< 0.1%
21099 1
< 0.1%
19867 1
< 0.1%
19689 1
< 0.1%
18676 1
< 0.1%
18504 1
< 0.1%
14978 1
< 0.1%
14649 1
< 0.1%

7월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct355
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.275
Minimum0
Maximum30616
Zeros1118
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:47.439620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q327
95-th percentile86
Maximum30616
Range30616
Interquartile range (IQR)21

Descriptive statistics

Standard deviation763.07311
Coefficient of variation (CV)10.557912
Kurtosis600.44691
Mean72.275
Median Absolute Deviation (MAD)9
Skewness22.409556
Sum722750
Variance582280.57
MonotonicityNot monotonic
2023-12-13T04:48:47.650629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1118
 
11.2%
6 382
 
3.8%
7 347
 
3.5%
5 339
 
3.4%
9 327
 
3.3%
8 313
 
3.1%
4 308
 
3.1%
12 302
 
3.0%
11 300
 
3.0%
10 287
 
2.9%
Other values (345) 5977
59.8%
ValueCountFrequency (%)
0 1118
11.2%
1 160
 
1.6%
2 179
 
1.8%
3 225
 
2.2%
4 308
 
3.1%
5 339
 
3.4%
6 382
 
3.8%
7 347
 
3.5%
8 313
 
3.1%
9 327
 
3.3%
ValueCountFrequency (%)
30616 1
< 0.1%
21698 1
< 0.1%
20696 1
< 0.1%
19477 1
< 0.1%
18104 1
< 0.1%
17028 1
< 0.1%
16513 1
< 0.1%
16006 1
< 0.1%
15801 1
< 0.1%
14944 1
< 0.1%

8월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct347
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.1506
Minimum0
Maximum29868
Zeros1270
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:47.914096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q327
95-th percentile84
Maximum29868
Range29868
Interquartile range (IQR)21

Descriptive statistics

Standard deviation788.6917
Coefficient of variation (CV)10.781753
Kurtosis592.501
Mean73.1506
Median Absolute Deviation (MAD)10
Skewness22.223433
Sum731506
Variance622034.6
MonotonicityNot monotonic
2023-12-13T04:48:48.131688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1270
 
12.7%
10 345
 
3.5%
8 332
 
3.3%
6 331
 
3.3%
7 330
 
3.3%
5 303
 
3.0%
4 301
 
3.0%
13 295
 
2.9%
12 293
 
2.9%
15 283
 
2.8%
Other values (337) 5917
59.2%
ValueCountFrequency (%)
0 1270
12.7%
1 154
 
1.5%
2 173
 
1.7%
3 213
 
2.1%
4 301
 
3.0%
5 303
 
3.0%
6 331
 
3.3%
7 330
 
3.3%
8 332
 
3.3%
9 262
 
2.6%
ValueCountFrequency (%)
29868 1
< 0.1%
28269 1
< 0.1%
18922 1
< 0.1%
17427 1
< 0.1%
17116 1
< 0.1%
16868 1
< 0.1%
16448 1
< 0.1%
15414 1
< 0.1%
15015 1
< 0.1%
14744 1
< 0.1%

9월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct383
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.6067
Minimum0
Maximum40047
Zeros1031
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:48.359399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median14
Q328
95-th percentile92
Maximum40047
Range40047
Interquartile range (IQR)21

Descriptive statistics

Standard deviation866.12408
Coefficient of variation (CV)11.018451
Kurtosis768.12092
Mean78.6067
Median Absolute Deviation (MAD)9
Skewness24.55312
Sum786067
Variance750170.92
MonotonicityNot monotonic
2023-12-13T04:48:48.571317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1031
 
10.3%
10 345
 
3.5%
6 340
 
3.4%
7 326
 
3.3%
9 318
 
3.2%
13 313
 
3.1%
14 311
 
3.1%
11 310
 
3.1%
12 305
 
3.0%
8 301
 
3.0%
Other values (373) 6100
61.0%
ValueCountFrequency (%)
0 1031
10.3%
1 143
 
1.4%
2 177
 
1.8%
3 224
 
2.2%
4 294
 
2.9%
5 285
 
2.9%
6 340
 
3.4%
7 326
 
3.3%
8 301
 
3.0%
9 318
 
3.2%
ValueCountFrequency (%)
40047 1
< 0.1%
27420 1
< 0.1%
20679 1
< 0.1%
19688 1
< 0.1%
19185 1
< 0.1%
18001 1
< 0.1%
17429 1
< 0.1%
17324 1
< 0.1%
16915 1
< 0.1%
16892 1
< 0.1%

10월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct351
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.2043
Minimum0
Maximum32513
Zeros948
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:48.816092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median15
Q327
95-th percentile84
Maximum32513
Range32513
Interquartile range (IQR)20

Descriptive statistics

Standard deviation827.41245
Coefficient of variation (CV)11.002196
Kurtosis596.19733
Mean75.2043
Median Absolute Deviation (MAD)9
Skewness22.340084
Sum752043
Variance684611.36
MonotonicityNot monotonic
2023-12-13T04:48:49.020638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 948
 
9.5%
6 362
 
3.6%
7 346
 
3.5%
11 327
 
3.3%
9 319
 
3.2%
12 318
 
3.2%
10 315
 
3.1%
16 312
 
3.1%
5 304
 
3.0%
8 298
 
3.0%
Other values (341) 6151
61.5%
ValueCountFrequency (%)
0 948
9.5%
1 168
 
1.7%
2 162
 
1.6%
3 241
 
2.4%
4 284
 
2.8%
5 304
 
3.0%
6 362
 
3.6%
7 346
 
3.5%
8 298
 
3.0%
9 319
 
3.2%
ValueCountFrequency (%)
32513 1
< 0.1%
26606 1
< 0.1%
21992 1
< 0.1%
20472 1
< 0.1%
19189 1
< 0.1%
17990 1
< 0.1%
17788 1
< 0.1%
16482 1
< 0.1%
15478 1
< 0.1%
15198 1
< 0.1%

11월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct349
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.2431
Minimum0
Maximum20803
Zeros1049
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:49.241756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q326
95-th percentile83
Maximum20803
Range20803
Interquartile range (IQR)20

Descriptive statistics

Standard deviation627.71343
Coefficient of variation (CV)10.084868
Kurtosis521.40313
Mean62.2431
Median Absolute Deviation (MAD)9
Skewness21.368839
Sum622431
Variance394024.15
MonotonicityNot monotonic
2023-12-13T04:48:49.461777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1049
 
10.5%
7 371
 
3.7%
6 360
 
3.6%
5 335
 
3.4%
4 335
 
3.4%
11 331
 
3.3%
9 329
 
3.3%
8 328
 
3.3%
10 326
 
3.3%
15 321
 
3.2%
Other values (339) 5915
59.2%
ValueCountFrequency (%)
0 1049
10.5%
1 171
 
1.7%
2 198
 
2.0%
3 233
 
2.3%
4 335
 
3.4%
5 335
 
3.4%
6 360
 
3.6%
7 371
 
3.7%
8 328
 
3.3%
9 329
 
3.3%
ValueCountFrequency (%)
20803 1
< 0.1%
19346 1
< 0.1%
17721 1
< 0.1%
16724 1
< 0.1%
15216 1
< 0.1%
15100 1
< 0.1%
14730 1
< 0.1%
14305 1
< 0.1%
11488 1
< 0.1%
11167 1
< 0.1%

12월사용량
Real number (ℝ)

SKEWED  ZEROS 

Distinct342
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.194
Minimum0
Maximum27875
Zeros1315
Zeros (%)13.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:48:49.646285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median13
Q325
95-th percentile81
Maximum27875
Range27875
Interquartile range (IQR)20

Descriptive statistics

Standard deviation699.14204
Coefficient of variation (CV)10.891081
Kurtosis615.1656
Mean64.194
Median Absolute Deviation (MAD)9
Skewness22.835264
Sum641940
Variance488799.6
MonotonicityNot monotonic
2023-12-13T04:48:49.853107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1315
 
13.2%
6 375
 
3.8%
7 340
 
3.4%
10 334
 
3.3%
8 326
 
3.3%
5 316
 
3.2%
9 312
 
3.1%
12 306
 
3.1%
11 305
 
3.0%
13 293
 
2.9%
Other values (332) 5778
57.8%
ValueCountFrequency (%)
0 1315
13.2%
1 191
 
1.9%
2 210
 
2.1%
3 250
 
2.5%
4 283
 
2.8%
5 316
 
3.2%
6 375
 
3.8%
7 340
 
3.4%
8 326
 
3.3%
9 312
 
3.1%
ValueCountFrequency (%)
27875 1
< 0.1%
21227 1
< 0.1%
20878 1
< 0.1%
16724 1
< 0.1%
14868 1
< 0.1%
14489 1
< 0.1%
13963 1
< 0.1%
13418 1
< 0.1%
13381 1
< 0.1%
13215 1
< 0.1%

Interactions

2023-12-13T04:48:42.312726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:23.713469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.614608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.174573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.644377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.502964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.105766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.820215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.530036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.121235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.184728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.757899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.430389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:23.853282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.788410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.297553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.773894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.613101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.277152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.964830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.672717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.264453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.339676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.864091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.557829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:24.007790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.910002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.427837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.916655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.724606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.414293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.104188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.797400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.383343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.480682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.972604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.684923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:24.188462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.026383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.545393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:29.043653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.839493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.521080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.249601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.932911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.516599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.615921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.096948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.818213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:24.370784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.154381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.668974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:29.188289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.997416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.638319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.407977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.053857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.649726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.744178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.220799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.916741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:24.529539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.276395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.786616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:29.324586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.126885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.774770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.546847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.179150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.791489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.862030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.346606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:43.093991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:24.682365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.444891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.917590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:29.781040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.258829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:32.936553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.695516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.325985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:37.930411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.979552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.461135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:43.237124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:24.845068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.569108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.029936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:29.883469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.403797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.068851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.849757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.439963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:38.091524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.134396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.588215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:43.371758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.007014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.690763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.138959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.005624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.561902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.210897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:34.992506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.585471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:38.239645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.259883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.719212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:43.508227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.163629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.824221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.298282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.152818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.710619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.363473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.133135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.735198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:38.757439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.405495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:41.900723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:43.623167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.319248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:26.952888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.422917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.294559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.845994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.516613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.271514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.880974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:38.905585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.521157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.052322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:43.752376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:25.459868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:27.055300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:28.537303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:30.397483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:31.967491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:33.664588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:35.400276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:36.991137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:39.045897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:40.633531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:48:42.192274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:48:50.039186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소1월사용량2월사용량3월사용량4월사용량5월사용량6월사용량7월사용량8월사용량9월사용량10월사용량11월사용량12월사용량
주소1.0000.1620.0640.0920.1500.0950.1170.0870.1220.0880.0990.0620.125
1월사용량0.1621.0000.0000.0000.1780.0000.0000.0000.0000.0750.0000.0000.000
2월사용량0.0640.0001.0000.2510.1400.3640.1880.0000.2750.1380.3570.0000.116
3월사용량0.0920.0000.2511.0000.1710.1710.0000.0000.1800.4400.1850.0000.212
4월사용량0.1500.1780.1400.1711.0000.4730.3390.7870.0000.1930.2540.1340.212
5월사용량0.0950.0000.3640.1710.4731.0000.0000.0000.2330.1930.2500.0950.000
6월사용량0.1170.0000.1880.0000.3390.0001.0000.4600.1460.0000.1100.0340.095
7월사용량0.0870.0000.0000.0000.7870.0000.4601.0000.0000.0000.2160.0000.046
8월사용량0.1220.0000.2750.1800.0000.2330.1460.0001.0000.1300.2150.0000.322
9월사용량0.0880.0750.1380.4400.1930.1930.0000.0000.1301.0000.1360.0000.073
10월사용량0.0990.0000.3570.1850.2540.2500.1100.2160.2150.1361.0000.1460.000
11월사용량0.0620.0000.0000.0000.1340.0950.0340.0000.0000.0000.1461.0000.197
12월사용량0.1250.0000.1160.2120.2120.0000.0950.0460.3220.0730.0000.1971.000
2023-12-13T04:48:50.257917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1월사용량2월사용량3월사용량4월사용량5월사용량6월사용량7월사용량8월사용량9월사용량10월사용량11월사용량12월사용량주소
1월사용량1.0000.0610.0710.0890.0690.1030.1160.0260.0410.0430.0200.0300.067
2월사용량0.0611.0000.1730.0890.1320.0860.0830.0890.0790.0720.1050.0680.025
3월사용량0.0710.1731.0000.0820.1390.0750.0600.0920.1060.0930.0740.0600.032
4월사용량0.0890.0890.0821.0000.2150.1600.1500.0710.1030.0600.0750.0630.062
5월사용량0.0690.1320.1390.2151.0000.1560.1260.0860.0840.0940.0810.0790.039
6월사용량0.1030.0860.0750.1600.1561.0000.1930.0290.0730.0420.0420.0620.048
7월사용량0.1160.0830.0600.1500.1260.1931.0000.0630.0510.0430.0680.0560.036
8월사용량0.0260.0890.0920.0710.0860.0290.0631.0000.1170.1310.1180.1220.043
9월사용량0.0410.0790.1060.1030.0840.0730.0510.1171.0000.1770.0750.0760.031
10월사용량0.0430.0720.0930.0600.0940.0420.0430.1310.1771.0000.1050.1150.041
11월사용량0.0200.1050.0740.0750.0810.0420.0680.1180.0750.1051.0000.1050.024
12월사용량0.0300.0680.0600.0630.0790.0620.0560.1220.0760.1150.1051.0000.044
주소0.0670.0250.0320.0620.0390.0480.0360.0430.0310.0410.0240.0441.000

Missing values

2023-12-13T04:48:43.946815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:48:44.170220image/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

주소1월사용량2월사용량3월사용량4월사용량5월사용량6월사용량7월사용량8월사용량9월사용량10월사용량11월사용량12월사용량
22711호원1동6797134171835049
21241호원1동11352022151183523700
13553의정부1동08010575411823
35709송산2동462518822150016027
14487의정부1동472052702021144125
35759송산2동0191491100231778
36479송산1동16320151819301623102027
8576의정부2동101420296321131926538105
11892의정부1동5731044413243113130
10484의정부2동10138215291015221226248
주소1월사용량2월사용량3월사용량4월사용량5월사용량6월사용량7월사용량8월사용량9월사용량10월사용량11월사용량12월사용량
42462가능동860881817622813305148
7109의정부2동11701971976681077
25916호원1동43122151620141518171320
16293의정부1동1822891102735180738
24050호원1동00201531161382116220
48712흥선동1702812918223325860
1298의정부1동0610762306622
85의정부1동2701110653444
34113송산2동6823266713770203510429
28353신곡1동0951422176038522