Overview

Dataset statistics

Number of variables7
Number of observations186
Missing cells51
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.2 KiB
Average record size in memory61.7 B

Variable types

Categorical3
Numeric4

Dataset

Description상수도요금 업종별 부과 집계 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=9S1TG529ZC8BNF8Y8M7W12125746&infSeq=1

Alerts

집계년도 has constant value ""Constant
부과액 is highly overall correlated with 부과량(㎥) and 1 other fieldsHigh correlation
부과량(㎥) is highly overall correlated with 부과액 and 1 other fieldsHigh correlation
평균단가(원/㎥) is highly overall correlated with 부과액 and 3 other fieldsHigh correlation
최초1㎥요금(원/㎥) is highly overall correlated with 평균단가(원/㎥) and 1 other fieldsHigh correlation
업종구분명 is highly overall correlated with 평균단가(원/㎥) and 1 other fieldsHigh correlation
최초1㎥요금(원/㎥) has 51 (27.4%) missing valuesMissing
부과액 has 82 (44.1%) zerosZeros
부과량(㎥) has 82 (44.1%) zerosZeros
평균단가(원/㎥) has 82 (44.1%) zerosZeros
최초1㎥요금(원/㎥) has 31 (16.7%) zerosZeros

Reproduction

Analysis started2023-12-10 21:01:09.772150
Analysis finished2023-12-10 21:01:11.758343
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2021
186 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 186
100.0%

Length

2023-12-11T06:01:11.827252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:11.922886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 186
100.0%

시군명
Categorical

Distinct31
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
가평군
 
6
고양시
 
6
과천시
 
6
광명시
 
6
광주시
 
6
Other values (26)
156 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row가평군
3rd row가평군
4th row가평군
5th row가평군

Common Values

ValueCountFrequency (%)
가평군 6
 
3.2%
고양시 6
 
3.2%
과천시 6
 
3.2%
광명시 6
 
3.2%
광주시 6
 
3.2%
구리시 6
 
3.2%
군포시 6
 
3.2%
김포시 6
 
3.2%
남양주시 6
 
3.2%
동두천시 6
 
3.2%
Other values (21) 126
67.7%

Length

2023-12-11T06:01:12.034765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 6
 
3.2%
안양시 6
 
3.2%
하남시 6
 
3.2%
포천시 6
 
3.2%
평택시 6
 
3.2%
파주시 6
 
3.2%
이천시 6
 
3.2%
의정부시 6
 
3.2%
의왕시 6
 
3.2%
용인시 6
 
3.2%
Other values (21) 126
67.7%

업종구분명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
공공용(업무용)
31 
일반용(영업용)
31 
가정용
31 
욕탕1종(대중탕용)
31 
공업용(산업 및 공업용)
31 

Length

Max length13
Median length9
Mean length7.6666667
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공공용(업무용)
2nd row일반용(영업용)
3rd row가정용
4th row욕탕1종(대중탕용)
5th row공업용(산업 및 공업용)

Common Values

ValueCountFrequency (%)
공공용(업무용) 31
16.7%
일반용(영업용) 31
16.7%
가정용 31
16.7%
욕탕1종(대중탕용) 31
16.7%
공업용(산업 및 공업용) 31
16.7%
욕탕2종 31
16.7%

Length

2023-12-11T06:01:12.458193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:01:12.586304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용(업무용 31
12.5%
일반용(영업용 31
12.5%
가정용 31
12.5%
욕탕1종(대중탕용 31
12.5%
공업용(산업 31
12.5%
및 31
12.5%
공업용 31
12.5%
욕탕2종 31
12.5%

부과액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5577060.7
Minimum0
Maximum59274370
Zeros82
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:01:12.751189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median84281.5
Q36710394.5
95-th percentile25986625
Maximum59274370
Range59274370
Interquartile range (IQR)6710394.5

Descriptive statistics

Standard deviation10534441
Coefficient of variation (CV)1.8888876
Kurtosis7.0098964
Mean5577060.7
Median Absolute Deviation (MAD)84281.5
Skewness2.5210637
Sum1.0373333 × 109
Variance1.1097444 × 1014
MonotonicityNot monotonic
2023-12-11T06:01:12.957425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 82
44.1%
131288 1
 
0.5%
5240096 1
 
0.5%
7652748 1
 
0.5%
23177 1
 
0.5%
529968 1
 
0.5%
6436195 1
 
0.5%
25156746 1
 
0.5%
35968994 1
 
0.5%
6722338 1
 
0.5%
Other values (95) 95
51.1%
ValueCountFrequency (%)
0 82
44.1%
1424 1
 
0.5%
4752 1
 
0.5%
7117 1
 
0.5%
10788 1
 
0.5%
23177 1
 
0.5%
25951 1
 
0.5%
43673 1
 
0.5%
52004 1
 
0.5%
75552 1
 
0.5%
ValueCountFrequency (%)
59274370 1
0.5%
53169457 1
0.5%
44579489 1
0.5%
39626641 1
0.5%
39528339 1
0.5%
35989033 1
0.5%
35968994 1
0.5%
31209487 1
0.5%
27198681 1
0.5%
26062492 1
0.5%

부과량(㎥)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8084954.6
Minimum0
Maximum91778247
Zeros82
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:01:13.159857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median83523.5
Q38200052.8
95-th percentile45998511
Maximum91778247
Range91778247
Interquartile range (IQR)8200052.8

Descriptive statistics

Standard deviation16832918
Coefficient of variation (CV)2.0820052
Kurtosis8.1565989
Mean8084954.6
Median Absolute Deviation (MAD)83523.5
Skewness2.8004659
Sum1.5038016 × 109
Variance2.8334712 × 1014
MonotonicityNot monotonic
2023-12-11T06:01:13.328199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 82
44.1%
105200 1
 
0.5%
3858687 1
 
0.5%
11964041 1
 
0.5%
27807 1
 
0.5%
529027 1
 
0.5%
6611970 1
 
0.5%
21324035 1
 
0.5%
83864108 1
 
0.5%
6101407 1
 
0.5%
Other values (95) 95
51.1%
ValueCountFrequency (%)
0 82
44.1%
2358 1
 
0.5%
4640 1
 
0.5%
6011 1
 
0.5%
10344 1
 
0.5%
15018 1
 
0.5%
27807 1
 
0.5%
37538 1
 
0.5%
49773 1
 
0.5%
50096 1
 
0.5%
ValueCountFrequency (%)
91778247 1
0.5%
83864108 1
0.5%
79015519 1
0.5%
69404716 1
0.5%
63698118 1
0.5%
58511700 1
0.5%
57370662 1
0.5%
56273590 1
0.5%
49051484 1
0.5%
46877261 1
0.5%

평균단가(원/㎥)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean519.94473
Minimum0
Maximum2012.1
Zeros82
Zeros (%)44.1%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:01:13.492814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median453.455
Q3988.475
95-th percentile1500.8825
Maximum2012.1
Range2012.1
Interquartile range (IQR)988.475

Descriptive statistics

Standard deviation547.40017
Coefficient of variation (CV)1.0528045
Kurtosis-0.90857498
Mean519.94473
Median Absolute Deviation (MAD)453.455
Skewness0.56723495
Sum96709.72
Variance299646.95
MonotonicityNot monotonic
2023-12-11T06:01:13.673009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 82
44.1%
1247.98 1
 
0.5%
1358.0 1
 
0.5%
639.65 1
 
0.5%
833.5 1
 
0.5%
1001.78 1
 
0.5%
973.42 1
 
0.5%
1179.74 1
 
0.5%
428.9 1
 
0.5%
1101.77 1
 
0.5%
Other values (95) 95
51.1%
ValueCountFrequency (%)
0.0 82
44.1%
61.0 1
 
0.5%
192.0 1
 
0.5%
280.48 1
 
0.5%
300.29 1
 
0.5%
389.82 1
 
0.5%
401.12 1
 
0.5%
428.9 1
 
0.5%
435.27 1
 
0.5%
445.42 1
 
0.5%
ValueCountFrequency (%)
2012.1 1
0.5%
1754.94 1
0.5%
1727.99 1
0.5%
1724.33 1
0.5%
1685.74 1
0.5%
1638.57 1
0.5%
1610.07 1
0.5%
1533.84 1
0.5%
1500.95 1
0.5%
1500.92 1
0.5%

최초1㎥요금(원/㎥)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct77
Distinct (%)57.0%
Missing51
Missing (%)27.4%
Infinite0
Infinite (%)0.0%
Mean608.45926
Minimum0
Maximum1728
Zeros31
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:01:13.833247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1316.5
median630
Q3895
95-th percentile1282.6
Maximum1728
Range1728
Interquartile range (IQR)578.5

Descriptive statistics

Standard deviation430.57081
Coefficient of variation (CV)0.70764115
Kurtosis-0.61369494
Mean608.45926
Median Absolute Deviation (MAD)270
Skewness0.10274146
Sum82142
Variance185391.22
MonotonicityNot monotonic
2023-12-11T06:01:14.001489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31
 
16.7%
900 3
 
1.6%
890 3
 
1.6%
650 3
 
1.6%
850 3
 
1.6%
640 3
 
1.6%
540 3
 
1.6%
580 2
 
1.1%
440 2
 
1.1%
1270 2
 
1.1%
Other values (67) 80
43.0%
(Missing) 51
27.4%
ValueCountFrequency (%)
0 31
16.7%
190 1
 
0.5%
270 1
 
0.5%
303 1
 
0.5%
330 1
 
0.5%
370 1
 
0.5%
375 1
 
0.5%
400 2
 
1.1%
410 1
 
0.5%
432 1
 
0.5%
ValueCountFrequency (%)
1728 1
0.5%
1670 1
0.5%
1500 1
0.5%
1410 1
0.5%
1358 2
1.1%
1312 1
0.5%
1270 2
1.1%
1248 1
0.5%
1240 1
0.5%
1218 1
0.5%

Interactions

2023-12-11T06:01:11.134018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.057601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.420015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.736400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:11.232283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.149772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.498795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.832903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:11.328656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.239718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.572701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.928648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:11.446294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.332597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:10.658561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:01:11.032532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:01:14.127302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업종구분명부과액부과량(㎥)평균단가(원/㎥)최초1㎥요금(원/㎥)
시군명1.0000.0000.2140.0000.0000.000
업종구분명0.0001.0000.6030.5210.7420.748
부과액0.2140.6031.0000.9370.6590.451
부과량(㎥)0.0000.5210.9371.0000.6950.619
평균단가(원/㎥)0.0000.7420.6590.6951.0000.930
최초1㎥요금(원/㎥)0.0000.7480.4510.6190.9301.000
2023-12-11T06:01:14.254517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분명시군명
업종구분명1.0000.000
시군명0.0001.000
2023-12-11T06:01:14.366511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과액부과량(㎥)평균단가(원/㎥)최초1㎥요금(원/㎥)시군명업종구분명
부과액1.0000.9920.7680.4040.0660.367
부과량(㎥)0.9921.0000.7280.3160.0000.303
평균단가(원/㎥)0.7680.7281.0000.9590.0000.506
최초1㎥요금(원/㎥)0.4040.3160.9591.0000.0000.510
시군명0.0660.0000.0000.0001.0000.000
업종구분명0.3670.3030.5060.5100.0001.000

Missing values

2023-12-11T06:01:11.585165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:01:11.710449image/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

집계년도시군명업종구분명부과액부과량(㎥)평균단가(원/㎥)최초1㎥요금(원/㎥)
02021가평군공공용(업무용)1312881052001247.981358
12021가평군일반용(영업용)394309022468531754.941248
22021가평군가정용30130983231386932.45833
32021가평군욕탕1종(대중탕용)25951150181727.991728
42021가평군공업용(산업 및 공업용)86233708001218.01218
52021가평군욕탕2종000.00
62021고양시욕탕2종000.00
72021고양시일반용(영업용)2540333931259632812.66598
82021고양시공공용(업무용)000.0<NA>
92021고양시가정용3952833979015519500.26495
집계년도시군명업종구분명부과액부과량(㎥)평균단가(원/㎥)최초1㎥요금(원/㎥)
1762021하남시욕탕1종(대중탕용)84431123961681.11590
1772021하남시공업용(산업 및 공업용)157508245539641.0739
1782021하남시욕탕2종000.00
1792021하남시일반용(영업용)1021296810675784956.65770
1802021화성시욕탕1종(대중탕용)1127481066941056.74967
1812021화성시공업용(산업 및 공업용)000.0<NA>
1822021화성시일반용(영업용)53169457490514841083.95825
1832021화성시욕탕2종000.00
1842021화성시공공용(업무용)000.0<NA>
1852021화성시가정용3962664163698118622.1555