Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory173.0 B

Variable types

Categorical11
Numeric6
DateTime2

Dataset

Description전북특별자치도 진안군 상하수도요금관리시스템 검침정보에 대한 데이터입니다. 당월검침일, 전월검침일, 당월사용량, 납기마감일 등의 정보를 제공합니다.
Author전북특별자치도 진안군
URLhttps://www.data.go.kr/data/15070412/fileData.do

Alerts

도 has constant value ""Constant
시군 has constant value ""Constant
자원구분 has constant value ""Constant
부번호 has constant value ""Constant
검침차수 has constant value ""Constant
검침주기 has constant value ""Constant
당월출수량 has constant value ""Constant
전월출수량 has constant value ""Constant
납기마감일 is highly overall correlated with 검침년월High correlation
검침년월 is highly overall correlated with 납기마감일High correlation
당월지침 is highly overall correlated with 당월사용량 and 2 other fieldsHigh correlation
당월사용량 is highly overall correlated with 당월지침 and 2 other fieldsHigh correlation
전월지침 is highly overall correlated with 당월지침 and 2 other fieldsHigh correlation
전월사용량 is highly overall correlated with 당월지침 and 2 other fieldsHigh correlation
지하수출수량 is highly imbalanced (99.3%)Imbalance
당월지침 is highly skewed (γ1 = 59.40656949)Skewed
전월지침 is highly skewed (γ1 = 59.68659562)Skewed
당월지침 has 324 (3.2%) zerosZeros
당월사용량 has 2242 (22.4%) zerosZeros
전월지침 has 341 (3.4%) zerosZeros
전월사용량 has 2279 (22.8%) zerosZeros

Reproduction

Analysis started2024-03-14 20:44:17.478900
Analysis finished2024-03-14 20:44:32.009683
Duration14.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

납기마감일
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-06-30
1257 
2023-08-31
1222 
2023-05-31
1206 
2023-01-31
1183 
2023-04-30
1169 
Other values (4)
3963 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-31
2nd row2023-06-30
3rd row2023-06-30
4th row2023-02-28
5th row2023-01-31

Common Values

ValueCountFrequency (%)
2023-06-30 1257
12.6%
2023-08-31 1222
12.2%
2023-05-31 1206
12.1%
2023-01-31 1183
11.8%
2023-04-30 1169
11.7%
2023-02-28 1160
11.6%
2023-07-31 1136
11.4%
2023-03-31 1130
11.3%
2023-09-30 537
5.4%

Length

2024-03-15T05:44:32.197957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:32.547770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-30 1257
12.6%
2023-08-31 1222
12.2%
2023-05-31 1206
12.1%
2023-01-31 1183
11.8%
2023-04-30 1169
11.7%
2023-02-28 1160
11.6%
2023-07-31 1136
11.4%
2023-03-31 1130
11.3%
2023-09-30 537
5.4%

도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전북특별자치도
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북특별자치도 10000
100.0%

Length

2024-03-15T05:44:32.955244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:33.111876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 10000
100.0%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
진안군
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진안군 10000
100.0%

Length

2024-03-15T05:44:33.297246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:33.553707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진안군 10000
100.0%

수용가번호
Real number (ℝ)

Distinct6868
Distinct (%)68.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0512216 × 109
Minimum1.0000001 × 109
Maximum1.1070067 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:44:33.883965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.0000001 × 109
5-th percentile1.0070083 × 109
Q11.0660025 × 109
median5.0040025 × 109
Q38.0041782 × 109
95-th percentile1.1002012 × 1010
Maximum1.1070067 × 1010
Range1.0070067 × 1010
Interquartile range (IQR)6.9381758 × 109

Descriptive statistics

Standard deviation3.5282671 × 109
Coefficient of variation (CV)0.69849779
Kurtosis-1.4075551
Mean5.0512216 × 109
Median Absolute Deviation (MAD)3.9350021 × 109
Skewness0.20677298
Sum5.0512216 × 1013
Variance1.2448669 × 1019
MonotonicityNot monotonic
2024-03-15T05:44:34.326492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10001005000 5
 
0.1%
11011002300 5
 
0.1%
1064002300 5
 
0.1%
9014000500 5
 
0.1%
1095002900 5
 
0.1%
1007019900 5
 
0.1%
7032001700 5
 
0.1%
11007002600 5
 
0.1%
4013001630 5
 
0.1%
1007009700 5
 
0.1%
Other values (6858) 9950
99.5%
ValueCountFrequency (%)
1000000120 1
 
< 0.1%
1001000102 1
 
< 0.1%
1001000103 1
 
< 0.1%
1001000104 1
 
< 0.1%
1001000200 3
< 0.1%
1001000300 2
< 0.1%
1001000303 3
< 0.1%
1001000400 1
 
< 0.1%
1001000402 1
 
< 0.1%
1001000800 2
< 0.1%
ValueCountFrequency (%)
11070067000 1
< 0.1%
11015023600 2
< 0.1%
11015023300 1
< 0.1%
11015023200 1
< 0.1%
11015023120 1
< 0.1%
11015023110 1
< 0.1%
11015023100 1
< 0.1%
11015022800 2
< 0.1%
11015022720 1
< 0.1%
11015022600 2
< 0.1%

자원구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2024-03-15T05:44:34.742056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:35.031389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

부번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2024-03-15T05:44:35.347387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:35.636746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

검침년월
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-06
1257 
2023-08
1222 
2023-05
1206 
2023-01
1183 
2023-04
1169 
Other values (4)
3963 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03
2nd row2023-06
3rd row2023-06
4th row2023-02
5th row2023-01

Common Values

ValueCountFrequency (%)
2023-06 1257
12.6%
2023-08 1222
12.2%
2023-05 1206
12.1%
2023-01 1183
11.8%
2023-04 1169
11.7%
2023-02 1160
11.6%
2023-07 1136
11.4%
2023-03 1130
11.3%
2023-09 537
5.4%

Length

2024-03-15T05:44:36.041250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:36.246784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06 1257
12.6%
2023-08 1222
12.2%
2023-05 1206
12.1%
2023-01 1183
11.8%
2023-04 1169
11.7%
2023-02 1160
11.6%
2023-07 1136
11.4%
2023-03 1130
11.3%
2023-09 537
5.4%

검침일
Real number (ℝ)

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.9231
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:44:36.488570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median5
Q320
95-th percentile24
Maximum30
Range29
Interquartile range (IQR)15

Descriptive statistics

Standard deviation7.7171719
Coefficient of variation (CV)0.86485323
Kurtosis-0.49013635
Mean8.9231
Median Absolute Deviation (MAD)0
Skewness1.081346
Sum89231
Variance59.554742
MonotonicityNot monotonic
2024-03-15T05:44:36.855942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
5 6289
62.9%
20 1597
 
16.0%
1 1004
 
10.0%
25 315
 
3.1%
21 164
 
1.6%
23 138
 
1.4%
22 136
 
1.4%
24 99
 
1.0%
2 73
 
0.7%
26 56
 
0.6%
Other values (11) 129
 
1.3%
ValueCountFrequency (%)
1 1004
 
10.0%
2 73
 
0.7%
5 6289
62.9%
10 1
 
< 0.1%
13 1
 
< 0.1%
15 2
 
< 0.1%
16 6
 
0.1%
17 6
 
0.1%
18 6
 
0.1%
19 2
 
< 0.1%
ValueCountFrequency (%)
30 28
 
0.3%
29 13
 
0.1%
28 37
 
0.4%
27 27
 
0.3%
26 56
 
0.6%
25 315
3.1%
24 99
 
1.0%
23 138
1.4%
22 136
1.4%
21 164
1.6%

검침차수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-15T05:44:37.213333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:37.390636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

검침주기
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-15T05:44:37.554761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:37.764025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

지하수출수량
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9994 
0
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 9994
99.9%
0 6
 
0.1%

Length

2024-03-15T05:44:37.926617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:38.086792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9994
99.9%
0 6
 
0.1%

당월검침일
Date

Distinct129
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-12-19 00:00:00
Maximum2023-09-05 00:00:00
2024-03-15T05:44:38.369231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:38.621948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

당월지침
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2289
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean928.1741
Minimum0
Maximum605640
Zeros324
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:44:38.995269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q167
median247
Q3704
95-th percentile2604.25
Maximum605640
Range605640
Interquartile range (IQR)637

Descriptive statistics

Standard deviation7370.9088
Coefficient of variation (CV)7.9412998
Kurtosis4599.9773
Mean928.1741
Median Absolute Deviation (MAD)220
Skewness59.406569
Sum9281741
Variance54330296
MonotonicityNot monotonic
2024-03-15T05:44:39.436103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 324
 
3.2%
1 283
 
2.8%
2 137
 
1.4%
3 100
 
1.0%
4 53
 
0.5%
6 46
 
0.5%
5 45
 
0.4%
15 44
 
0.4%
7 40
 
0.4%
17 39
 
0.4%
Other values (2279) 8889
88.9%
ValueCountFrequency (%)
0 324
3.2%
1 283
2.8%
2 137
1.4%
3 100
 
1.0%
4 53
 
0.5%
5 45
 
0.4%
6 46
 
0.5%
7 40
 
0.4%
8 38
 
0.4%
9 37
 
0.4%
ValueCountFrequency (%)
605640 1
< 0.1%
150669 1
< 0.1%
144308 1
< 0.1%
142369 1
< 0.1%
138473 1
< 0.1%
106121 1
< 0.1%
105304 1
< 0.1%
70795 1
< 0.1%
69236 1
< 0.1%
62853 1
< 0.1%

당월사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct260
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.1039
Minimum0
Maximum3459
Zeros2242
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:44:39.818247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q316
95-th percentile48
Maximum3459
Range3459
Interquartile range (IQR)15

Descriptive statistics

Standard deviation89.428112
Coefficient of variation (CV)4.6811443
Kurtosis519.08777
Mean19.1039
Median Absolute Deviation (MAD)7
Skewness19.630348
Sum191039
Variance7997.3872
MonotonicityNot monotonic
2024-03-15T05:44:40.074694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2242
22.4%
1 431
 
4.3%
5 421
 
4.2%
2 399
 
4.0%
4 395
 
4.0%
3 379
 
3.8%
6 374
 
3.7%
8 372
 
3.7%
7 365
 
3.6%
9 333
 
3.3%
Other values (250) 4289
42.9%
ValueCountFrequency (%)
0 2242
22.4%
1 431
 
4.3%
2 399
 
4.0%
3 379
 
3.8%
4 395
 
4.0%
5 421
 
4.2%
6 374
 
3.7%
7 365
 
3.6%
8 372
 
3.7%
9 333
 
3.3%
ValueCountFrequency (%)
3459 1
< 0.1%
2987 1
< 0.1%
2101 1
< 0.1%
2087 1
< 0.1%
1939 1
< 0.1%
1904 1
< 0.1%
1816 1
< 0.1%
1701 1
< 0.1%
1526 1
< 0.1%
1516 1
< 0.1%

당월출수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-15T05:44:40.317083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:40.570817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

전월검침일
Date

Distinct134
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-09-05 00:00:00
Maximum2023-08-05 00:00:00
2024-03-15T05:44:41.052358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:41.295880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전월지침
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2266
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean913.1881
Minimum0
Maximum600500
Zeros341
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:44:41.691650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q163
median235.5
Q3692
95-th percentile2573.05
Maximum600500
Range600500
Interquartile range (IQR)629

Descriptive statistics

Standard deviation7294.7055
Coefficient of variation (CV)7.9881741
Kurtosis4633.6182
Mean913.1881
Median Absolute Deviation (MAD)213.5
Skewness59.686596
Sum9131881
Variance53212729
MonotonicityNot monotonic
2024-03-15T05:44:42.030606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 341
 
3.4%
1 289
 
2.9%
2 142
 
1.4%
3 106
 
1.1%
4 62
 
0.6%
6 49
 
0.5%
8 48
 
0.5%
15 47
 
0.5%
5 46
 
0.5%
9 41
 
0.4%
Other values (2256) 8829
88.3%
ValueCountFrequency (%)
0 341
3.4%
1 289
2.9%
2 142
1.4%
3 106
 
1.1%
4 62
 
0.6%
5 46
 
0.5%
6 49
 
0.5%
7 39
 
0.4%
8 48
 
0.5%
9 41
 
0.4%
ValueCountFrequency (%)
600500 1
< 0.1%
148568 1
< 0.1%
142369 1
< 0.1%
140282 1
< 0.1%
136947 1
< 0.1%
105733 1
< 0.1%
104969 1
< 0.1%
69986 1
< 0.1%
68472 1
< 0.1%
61805 1
< 0.1%

전월사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct252
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.7945
Minimum0
Maximum3293
Zeros2279
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T05:44:42.280370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q316
95-th percentile47
Maximum3293
Range3293
Interquartile range (IQR)15

Descriptive statistics

Standard deviation88.637711
Coefficient of variation (CV)4.7161516
Kurtosis511.2551
Mean18.7945
Median Absolute Deviation (MAD)7
Skewness19.60573
Sum187945
Variance7856.6437
MonotonicityNot monotonic
2024-03-15T05:44:42.695422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2279
22.8%
1 441
 
4.4%
5 434
 
4.3%
3 403
 
4.0%
7 381
 
3.8%
2 381
 
3.8%
6 372
 
3.7%
4 366
 
3.7%
8 362
 
3.6%
10 354
 
3.5%
Other values (242) 4227
42.3%
ValueCountFrequency (%)
0 2279
22.8%
1 441
 
4.4%
2 381
 
3.8%
3 403
 
4.0%
4 366
 
3.7%
5 434
 
4.3%
6 372
 
3.7%
7 381
 
3.8%
8 362
 
3.6%
9 301
 
3.0%
ValueCountFrequency (%)
3293 1
< 0.1%
2987 1
< 0.1%
2288 1
< 0.1%
2170 1
< 0.1%
2087 1
< 0.1%
1861 1
< 0.1%
1809 1
< 0.1%
1683 1
< 0.1%
1606 1
< 0.1%
1368 1
< 0.1%

전월출수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-15T05:44:43.104488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:44:43.301111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

Interactions

2024-03-15T05:44:28.369436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:18.742863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:20.833108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:22.853792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:24.482244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:26.010479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:28.704502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:19.002398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:21.364954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:23.113865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:24.748177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:26.365043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:29.132680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:19.306093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:21.713749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:23.387684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:24.937433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:26.789456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:29.679425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:19.644061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:22.026637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:23.656113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:25.172786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:27.075027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:30.358840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:19.972167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:22.305876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:23.934982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:25.455483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:27.502849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:30.599537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:20.371596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:22.578593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:24.210846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:25.734411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:44:27.987831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:44:43.421885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
납기마감일수용가번호검침년월검침일지하수출수량당월지침당월사용량전월지침전월사용량
납기마감일1.0000.0001.0000.0000.0220.0000.0000.0000.000
수용가번호0.0001.0000.0000.4680.0000.0040.0360.0040.044
검침년월1.0000.0001.0000.0000.0220.0000.0000.0000.000
검침일0.0000.4680.0001.0000.0150.0330.0480.0330.057
지하수출수량0.0220.0000.0220.0151.0000.0000.0000.0000.000
당월지침0.0000.0040.0000.0330.0001.0000.7281.0000.855
당월사용량0.0000.0360.0000.0480.0000.7281.0000.7280.854
전월지침0.0000.0040.0000.0330.0001.0000.7281.0000.855
전월사용량0.0000.0440.0000.0570.0000.8550.8540.8551.000
2024-03-15T05:44:43.624436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지하수출수량납기마감일검침년월
지하수출수량1.0000.0220.022
납기마감일0.0221.0001.000
검침년월0.0221.0001.000
2024-03-15T05:44:43.787483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수용가번호검침일당월지침당월사용량전월지침전월사용량납기마감일검침년월지하수출수량
수용가번호1.0000.2610.033-0.0990.035-0.0920.0000.0000.000
검침일0.2611.000-0.164-0.109-0.164-0.1160.0000.0000.015
당월지침0.033-0.1641.0000.6030.9900.6080.0000.0000.000
당월사용량-0.099-0.1090.6031.0000.5800.8610.0000.0000.000
전월지침0.035-0.1640.9900.5801.0000.5960.0000.0000.000
전월사용량-0.092-0.1160.6080.8610.5961.0000.0000.0000.000
납기마감일0.0000.0000.0000.0000.0000.0001.0001.0000.022
검침년월0.0000.0000.0000.0000.0000.0001.0001.0000.022
지하수출수량0.0000.0150.0000.0000.0000.0000.0220.0221.000

Missing values

2024-03-15T05:44:30.899387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:44:31.706325image/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

납기마감일도시군수용가번호자원구분부번호검침년월검침일검침차수검침주기지하수출수량당월검침일당월지침당월사용량당월출수량전월검침일전월지침전월사용량전월출수량
334972023-03-31전북특별자치도진안군8001103500112023-0350012023-02-203461702023-01-20329150
578802023-06-30전북특별자치도진안군3002024400112023-0650012023-05-2282002023-04-218200
625712023-06-30전북특별자치도진안군9011000600112023-0650012023-05-231542002023-04-24154200
197722023-02-28전북특별자치도진안군1068008500112023-0250012023-02-01171002023-01-0117100
57392023-01-31전북특별자치도진안군1007024920112023-0150012023-01-011343502022-12-0199270
487032023-05-31전북특별자치도진안군8002157100112023-0550012023-04-211631002023-03-2115380
413372023-04-30전북특별자치도진안군9027001200112023-04250012023-03-238181602023-02-24802220
667292023-06-30전북특별자치도진안군8005199614112023-06200012023-05-2249302023-04-224640
398242023-04-30전북특별자치도진안군4011003700112023-0450012023-04-010002023-03-01000
406742023-04-30전북특별자치도진안군1010006100112023-0450012023-04-0124723702023-03-012435330
납기마감일도시군수용가번호자원구분부번호검침년월검침일검침차수검침주기지하수출수량당월검침일당월지침당월사용량당월출수량전월검침일전월지침전월사용량전월출수량
668572023-06-30전북특별자치도진안군1054006500112023-0650012023-05-2016481602023-04-201632190
14192023-01-31전북특별자치도진안군4006003500112023-01200012023-01-014002022-12-01440
701212023-07-31전북특별자치도진안군8005192700112023-0750012023-06-229231902023-05-22904120
545872023-05-31전북특별자치도진안군9023002300112023-05210012023-04-244051002023-03-2339530
769252023-07-31전북특별자치도진안군1100000100112023-07260012023-06-1912203002023-05-1911901450
29242023-01-31전북특별자치도진안군8001138500112023-0110012023-01-019857402022-12-01911940
69562023-01-31전북특별자치도진안군2006016152112023-0150012022-12-2986402022-11-248280
433992023-04-30전북특별자치도진안군11006007310112023-04200012023-03-205003302023-02-20467100
719862023-07-31전북특별자치도진안군9028002400112023-07200012023-06-24115302023-05-2111240
915652023-09-30전북특별자치도진안군6007002200112023-0910012023-08-201090902023-07-201081190