Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells3
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory57.1 B

Variable types

Numeric2
DateTime1
Categorical2
Text1

Dataset

Description부산광역시상수도사업본부_수용가정보시스템_물이용요금정보_20230126
Author부산광역시 상수도사업본부
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15083446

Alerts

연번 is highly overall correlated with 취수율High correlation
취수율 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
부과율 is highly overall correlated with 취수율High correlation
설명 has 3 (12.0%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 07:09:43.213016
Analysis finished2024-04-21 07:09:44.586152
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-04-21T16:09:44.709696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2024-04-21T16:09:44.964830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

적용년월
Date

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
Minimum2010-02-01 00:00:00
Maximum2022-02-01 00:00:00
2024-04-21T16:09:45.199931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:09:45.470276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

취수율
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)52.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90692
Minimum0.877
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size353.0 B
2024-04-21T16:09:45.706660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.877
5-th percentile0.8822
Q10.888
median0.889
Q30.918
95-th percentile0.9506
Maximum1
Range0.123
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.028108302
Coefficient of variation (CV)0.030993144
Kurtosis3.8370897
Mean0.90692
Median Absolute Deviation (MAD)0.012
Skewness1.7346247
Sum22.673
Variance0.00079007667
MonotonicityNot monotonic
2024-04-21T16:09:45.923395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.888 5
20.0%
0.929 4
16.0%
0.889 4
16.0%
0.916 3
12.0%
1.0 1
 
4.0%
0.918 1
 
4.0%
0.904 1
 
4.0%
0.956 1
 
4.0%
0.883 1
 
4.0%
0.877 1
 
4.0%
Other values (3) 3
12.0%
ValueCountFrequency (%)
0.877 1
 
4.0%
0.882 1
 
4.0%
0.883 1
 
4.0%
0.887 1
 
4.0%
0.888 5
20.0%
0.889 4
16.0%
0.904 1
 
4.0%
0.906 1
 
4.0%
0.916 3
12.0%
0.918 1
 
4.0%
ValueCountFrequency (%)
1.0 1
 
4.0%
0.956 1
 
4.0%
0.929 4
16.0%
0.918 1
 
4.0%
0.916 3
12.0%
0.906 1
 
4.0%
0.904 1
 
4.0%
0.889 4
16.0%
0.888 5
20.0%
0.887 1
 
4.0%

부과율
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
160
12 
170
8 
150
4 
140
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row140
2nd row150
3rd row150
4th row150
5th row160

Common Values

ValueCountFrequency (%)
160 12
48.0%
170 8
32.0%
150 4
 
16.0%
140 1
 
4.0%

Length

2024-04-21T16:09:46.138829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:09:46.312109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
160 12
48.0%
170 8
32.0%
150 4
 
16.0%
140 1
 
4.0%

부과율(BOD)
Categorical

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size328.0 B
100
20 
70
4 
60
 
1

Length

Max length3
Median length3
Mean length2.8
Min length2

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row100
2nd row60
3rd row100
4th row100
5th row100

Common Values

ValueCountFrequency (%)
100 20
80.0%
70 4
 
16.0%
60 1
 
4.0%

Length

2024-04-21T16:09:46.501871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:09:46.777899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100 20
80.0%
70 4
 
16.0%
60 1
 
4.0%

설명
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing3
Missing (%)12.0%
Memory size328.0 B
2024-04-21T16:09:47.679899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43.5
Mean length35.954545
Min length18

Characters and Unicode

Total characters791
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row주한미군관련 시설 물이용부담금 부과단가 변경 요청(경영관리팀-1883,2019.4.5.)
2nd row2010년 4월 납기 부과율 변경
3rd row2011년 2월 납기 부과율 변경
4th row2012년 2월 납기 부과율 변경
5th row2012년 3월 납기 부과율 변경
ValueCountFrequency (%)
변경 8
 
5.4%
2월 7
 
4.8%
100 7
 
4.8%
납기 6
 
4.1%
납기분(격월 6
 
4.1%
6
 
4.1%
물이용부담금 6
 
4.1%
1개월 6
 
4.1%
70 6
 
4.1%
부과율 6
 
4.1%
Other values (56) 83
56.5%
2024-04-21T16:09:49.066279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
16.1%
1 63
 
8.0%
0 61
 
7.7%
2 60
 
7.6%
월 39
 
4.9%
. 27
 
3.4%
부 22
 
2.8%
년 21
 
2.7%
경 19
 
2.4%
( 18
 
2.3%
Other values (55) 334
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
41.7%
Decimal Number 243
30.7%
Space Separator 127
 
16.1%
Other Punctuation 48
 
6.1%
Open Punctuation 18
 
2.3%
Close Punctuation 17
 
2.1%
Dash Punctuation 8
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 39
 
11.8%
부 22
 
6.7%
년 21
 
6.4%
경 19
 
5.8%
납 16
 
4.8%
기 16
 
4.8%
개 14
 
4.2%
변 12
 
3.6%
과 12
 
3.6%
분 11
 
3.3%
Other values (38) 148
44.8%
Decimal Number
ValueCountFrequency (%)
1 63
25.9%
0 61
25.1%
2 60
24.7%
3 11
 
4.5%
4 11
 
4.5%
5 9
 
3.7%
7 9
 
3.7%
6 7
 
2.9%
9 7
 
2.9%
8 5
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 27
56.2%
, 14
29.2%
: 7
 
14.6%
Space Separator
ValueCountFrequency (%)
127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 461
58.3%
Hangul 330
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
월 39
 
11.8%
부 22
 
6.7%
년 21
 
6.4%
경 19
 
5.8%
납 16
 
4.8%
기 16
 
4.8%
개 14
 
4.2%
변 12
 
3.6%
과 12
 
3.6%
분 11
 
3.3%
Other values (38) 148
44.8%
Common
ValueCountFrequency (%)
127
27.5%
1 63
13.7%
0 61
13.2%
2 60
13.0%
. 27
 
5.9%
( 18
 
3.9%
) 17
 
3.7%
, 14
 
3.0%
3 11
 
2.4%
4 11
 
2.4%
Other values (7) 52
11.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 461
58.3%
Hangul 330
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
27.5%
1 63
13.7%
0 61
13.2%
2 60
13.0%
. 27
 
5.9%
( 18
 
3.9%
) 17
 
3.7%
, 14
 
3.0%
3 11
 
2.4%
4 11
 
2.4%
Other values (7) 52
11.3%
Hangul
ValueCountFrequency (%)
월 39
 
11.8%
부 22
 
6.7%
년 21
 
6.4%
경 19
 
5.8%
납 16
 
4.8%
기 16
 
4.8%
개 14
 
4.2%
변 12
 
3.6%
과 12
 
3.6%
분 11
 
3.3%
Other values (38) 148
44.8%

Interactions

2024-04-21T16:09:43.870985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:09:43.539532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:09:44.048463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:09:43.697460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T16:09:49.325783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번적용년월취수율부과율부과율(BOD)설명
연번1.0000.9560.4250.7840.0001.000
적용년월0.9561.0000.9350.9020.0001.000
취수율0.4250.9351.0000.9520.0001.000
부과율0.7840.9020.9521.0000.3241.000
부과율(BOD)0.0000.0000.0000.3241.0001.000
설명1.0001.0001.0001.0001.0001.000
2024-04-21T16:09:49.593517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부과율부과율(BOD)
부과율1.0000.298
부과율(BOD)0.2981.000
2024-04-21T16:09:49.760739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번취수율부과율부과율(BOD)
연번1.000-0.6440.4990.000
취수율-0.6441.0000.8130.000
부과율0.4990.8131.0000.298
부과율(BOD)0.0000.0000.2981.000

Missing values

2024-04-21T16:09:44.288681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T16:09:44.504010image/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

연번적용년월취수율부과율부과율(BOD)설명
012019-041.0140100주한미군관련 시설 물이용부담금 부과단가 변경 요청(경영관리팀-1883,2019.4.5.)
122010-020.92915060<NA>
232010-020.929150100<NA>
342010-040.9291501002010년 4월 납기 부과율 변경
452011-020.9181601002011년 2월 납기 부과율 변경
562011-020.929150100<NA>
672012-020.9161601002012년 2월 납기 부과율 변경
782012-030.916160702012년 3월 납기 부과율 변경
892012-050.9161601002012년 5월 납기 부과율 변경
9102013-020.8881601002013년 2월납기분 (2013.1.1 이후 사용량)부터
연번적용년월취수율부과율부과율(BOD)설명
15162014-040.889160702014년 4월 납기분(격월 : 전1개월 100, 후1개월 70)
16172014-050.8891601002014년 5월 납기분(격월:전1개월 70, 후1개월 100)
17182015-020.9041701002015년 2월 납기분 취수율 및 부과율 변경(2015. 1. 1이후 사용량부터)
18192016-020.9561701002016년 2월 납기분부터 적용(경영관리팀-608,2016.01.29.)
19202017-020.8831701002017년 2월분부터 적용(경영관리팀-639, 2017.2.1.)
20212021-020.8771701002021년 물이용부담금 부과계수 및 단가 변경 안내(경영관리팀-569, 2021.2.2.)
21222020-020.8821701002020년 물이용부담금 부과단가 변경(경영관리팀-545(2020.1.30.)
22232022-020.8871701002022년 물이용부담금 부과계수 및 단가 변경 안내(요금감사팀-601, 2022.2.4.)
23242018-020.9061701002018년 2월 물이용부담금 부과단가 변경사항 알림 (경영관리팀-471,2018.1.23)
24252019-020.8891701002019년 2월 납기 물이용부담금 부과단가 변경(경영관리팀-462, 2019.1.22.)