Overview

Dataset statistics

Number of variables7
Number of observations149
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.6 KiB
Average record size in memory58.9 B

Variable types

Numeric2
Text2
Categorical2
DateTime1

Dataset

Description광주광역시내의 수돗물의 원활한 공급을 위한 유량, 유압, 유속을 측정하는 유량계실과 배수시설, 탁도계에 대한 현황입니다.
Author광주광역시 상수도사업본부
URLhttps://www.data.go.kr/data/15099826/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 구High correlation
구 is highly overall correlated with 연번High correlation
계약전력 is highly imbalanced (85.1%)Imbalance
연번 has unique valuesUnique
유량계명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:56:07.842772
Analysis finished2023-12-12 10:56:09.249966
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct149
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75
Minimum1
Maximum149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T19:56:09.384020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.4
Q138
median75
Q3112
95-th percentile141.6
Maximum149
Range148
Interquartile range (IQR)74

Descriptive statistics

Standard deviation43.156691
Coefficient of variation (CV)0.57542255
Kurtosis-1.2
Mean75
Median Absolute Deviation (MAD)37
Skewness0
Sum11175
Variance1862.5
MonotonicityStrictly increasing
2023-12-12T19:56:09.725875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
Other values (139) 139
93.3%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%

유량계명
Text

UNIQUE 

Distinct149
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T19:56:10.355494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.4563758
Min length2

Characters and Unicode

Total characters664
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique149 ?
Unique (%)100.0%

Sample

1st row산수-1
2nd row산수-2
3rd row산수-3
4th row산수-4
5th row산수-5
ValueCountFrequency (%)
진월 2
 
1.3%
산수-1 1
 
0.7%
지원-14 1
 
0.7%
본촌-각화2 1
 
0.7%
일곡1 1
 
0.7%
지원-10 1
 
0.7%
지원-11 1
 
0.7%
지원-12 1
 
0.7%
지원-13 1
 
0.7%
지원-15 1
 
0.7%
Other values (140) 140
92.7%
2023-12-12T19:56:11.172406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 99
 
14.9%
1 73
 
11.0%
2 53
 
8.0%
산 27
 
4.1%
송 25
 
3.8%
화 24
 
3.6%
각 23
 
3.5%
지 23
 
3.5%
원 21
 
3.2%
3 20
 
3.0%
Other values (56) 276
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 340
51.2%
Decimal Number 215
32.4%
Dash Punctuation 99
 
14.9%
Close Punctuation 4
 
0.6%
Open Punctuation 4
 
0.6%
Space Separator 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 27
 
7.9%
송 25
 
7.4%
화 24
 
7.1%
각 23
 
6.8%
지 23
 
6.8%
원 21
 
6.2%
월 17
 
5.0%
정 17
 
5.0%
봉 15
 
4.4%
하 15
 
4.4%
Other values (42) 133
39.1%
Decimal Number
ValueCountFrequency (%)
1 73
34.0%
2 53
24.7%
3 20
 
9.3%
4 14
 
6.5%
5 13
 
6.0%
7 11
 
5.1%
6 10
 
4.7%
8 9
 
4.2%
9 6
 
2.8%
0 6
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 340
51.2%
Common 324
48.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 27
 
7.9%
송 25
 
7.4%
화 24
 
7.1%
각 23
 
6.8%
지 23
 
6.8%
원 21
 
6.2%
월 17
 
5.0%
정 17
 
5.0%
봉 15
 
4.4%
하 15
 
4.4%
Other values (42) 133
39.1%
Common
ValueCountFrequency (%)
- 99
30.6%
1 73
22.5%
2 53
16.4%
3 20
 
6.2%
4 14
 
4.3%
5 13
 
4.0%
7 11
 
3.4%
6 10
 
3.1%
8 9
 
2.8%
9 6
 
1.9%
Other values (4) 16
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 340
51.2%
ASCII 324
48.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 99
30.6%
1 73
22.5%
2 53
16.4%
3 20
 
6.2%
4 14
 
4.3%
5 13
 
4.0%
7 11
 
3.4%
6 10
 
3.1%
8 9
 
2.8%
9 6
 
1.9%
Other values (4) 16
 
4.9%
Hangul
ValueCountFrequency (%)
산 27
 
7.9%
송 25
 
7.4%
화 24
 
7.1%
각 23
 
6.8%
지 23
 
6.8%
원 21
 
6.2%
월 17
 
5.0%
정 17
 
5.0%
봉 15
 
4.4%
하 15
 
4.4%
Other values (42) 133
39.1%

구
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
북구
48 
광산구
33 
서구
28 
남구
28 
동구
12 

Length

Max length3
Median length2
Mean length2.2214765
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
북구 48
32.2%
광산구 33
22.1%
서구 28
18.8%
남구 28
18.8%
동구 12
 
8.1%

Length

2023-12-12T19:56:11.404219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:56:11.625244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 48
32.2%
광산구 33
22.1%
서구 28
18.8%
남구 28
18.8%
동구 12
 
8.1%

설치위치
Text

Distinct147
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T19:56:12.001405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length14.731544
Min length6

Characters and Unicode

Total characters2195
Distinct characters183
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

Unique145 ?
Unique (%)97.3%

Sample

1st row산수동 541-56(필문대로 152)
2nd row계림동 579-7(횡단보도 옆)
3rd row계림동 579-7(전화박스 옆)
4th row산수동 553-33(무등로 474)
5th row산수동 367-20
ValueCountFrequency (%)
앞 13
 
3.1%
월산동 8
 
1.9%
농성동 6
 
1.4%
옆 6
 
1.4%
중흥동 6
 
1.4%
행암동 5
 
1.2%
우산동 5
 
1.2%
노대동 4
 
0.9%
풍암동 4
 
0.9%
횡단보도 4
 
0.9%
Other values (296) 361
85.5%
2023-12-12T19:56:12.659378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
 
12.5%
동 150
 
6.8%
1 139
 
6.3%
- 106
 
4.8%
2 84
 
3.8%
3 81
 
3.7%
5 81
 
3.7%
) 75
 
3.4%
( 75
 
3.4%
8 70
 
3.2%
Other values (173) 1059
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 913
41.6%
Decimal Number 747
34.0%
Space Separator 275
 
12.5%
Dash Punctuation 106
 
4.8%
Close Punctuation 75
 
3.4%
Open Punctuation 75
 
3.4%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 150
 
16.4%
로 63
 
6.9%
산 35
 
3.8%
대 28
 
3.1%
암 24
 
2.6%
도 18
 
2.0%
남 15
 
1.6%
앞 15
 
1.6%
길 14
 
1.5%
월 14
 
1.5%
Other values (157) 537
58.8%
Decimal Number
ValueCountFrequency (%)
1 139
18.6%
2 84
11.2%
3 81
10.8%
5 81
10.8%
8 70
9.4%
7 65
8.7%
6 64
8.6%
9 55
 
7.4%
4 54
 
7.2%
0 54
 
7.2%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
@ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1282
58.4%
Hangul 913
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 150
 
16.4%
로 63
 
6.9%
산 35
 
3.8%
대 28
 
3.1%
암 24
 
2.6%
도 18
 
2.0%
남 15
 
1.6%
앞 15
 
1.6%
길 14
 
1.5%
월 14
 
1.5%
Other values (157) 537
58.8%
Common
ValueCountFrequency (%)
275
21.5%
1 139
10.8%
- 106
 
8.3%
2 84
 
6.6%
3 81
 
6.3%
5 81
 
6.3%
) 75
 
5.9%
( 75
 
5.9%
8 70
 
5.5%
7 65
 
5.1%
Other values (6) 231
18.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1282
58.4%
Hangul 913
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
21.5%
1 139
10.8%
- 106
 
8.3%
2 84
 
6.6%
3 81
 
6.3%
5 81
 
6.3%
) 75
 
5.9%
( 75
 
5.9%
8 70
 
5.5%
7 65
 
5.1%
Other values (6) 231
18.0%
Hangul
ValueCountFrequency (%)
동 150
 
16.4%
로 63
 
6.9%
산 35
 
3.8%
대 28
 
3.1%
암 24
 
2.6%
도 18
 
2.0%
남 15
 
1.6%
앞 15
 
1.6%
길 14
 
1.5%
월 14
 
1.5%
Other values (157) 537
58.8%

관경
Real number (ℝ)

Distinct15
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean293.48993
Minimum80
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T19:56:12.907958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum80
5-th percentile120
Q1200
median250
Q3350
95-th percentile560
Maximum1000
Range920
Interquartile range (IQR)150

Descriptive statistics

Standard deviation149.20024
Coefficient of variation (CV)0.50836578
Kurtosis4.7914283
Mean293.48993
Median Absolute Deviation (MAD)100
Skewness1.7091529
Sum43730
Variance22260.711
MonotonicityNot monotonic
2023-12-12T19:56:13.090657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
300 25
16.8%
150 25
16.8%
250 25
16.8%
400 21
14.1%
200 19
12.8%
350 10
 
6.7%
500 7
 
4.7%
100 7
 
4.7%
600 4
 
2.7%
900 1
 
0.7%
Other values (5) 5
 
3.4%
ValueCountFrequency (%)
80 1
 
0.7%
100 7
 
4.7%
150 25
16.8%
200 19
12.8%
250 25
16.8%
300 25
16.8%
350 10
 
6.7%
400 21
14.1%
450 1
 
0.7%
500 7
 
4.7%
ValueCountFrequency (%)
1000 1
 
0.7%
900 1
 
0.7%
800 1
 
0.7%
700 1
 
0.7%
600 4
 
2.7%
500 7
 
4.7%
450 1
 
0.7%
400 21
14.1%
350 10
 
6.7%
300 25
16.8%

계약전력
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
주택용-3KW
144 
<NA>
 
4
일반용-4KW
 
1

Length

Max length7
Median length7
Mean length6.9194631
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row주택용-3KW
2nd row주택용-3KW
3rd row주택용-3KW
4th row주택용-3KW
5th row주택용-3KW

Common Values

ValueCountFrequency (%)
주택용-3KW 144
96.6%
<NA> 4
 
2.7%
일반용-4KW 1
 
0.7%

Length

2023-12-12T19:56:13.323511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:56:13.515380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택용-3kw 144
96.6%
na 4
 
2.7%
일반용-4kw 1
 
0.7%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2022-10-26 00:00:00
Maximum2022-10-26 00:00:00
2023-12-12T19:56:13.669634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:13.844347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:56:08.594512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:08.293462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:08.804101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:56:08.452376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:56:13.964701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구관경계약전력
연번1.0000.9930.4680.000
구0.9931.0000.3720.000
관경0.4680.3721.0000.000
계약전력0.0000.0000.0001.000
2023-12-12T19:56:14.125519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구계약전력
구1.0000.000
계약전력0.0001.000
2023-12-12T19:56:14.267580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관경구계약전력
연번1.000-0.1000.8630.000
관경-0.1001.0000.1590.000
구0.8630.1591.0000.000
계약전력0.0000.0000.0001.000

Missing values

2023-12-12T19:56:08.969998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:56:09.173326image/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

연번유량계명구설치위치관경계약전력데이터기준일
01산수-1동구산수동 541-56(필문대로 152)300주택용-3KW2022-10-26
12산수-2동구계림동 579-7(횡단보도 옆)150주택용-3KW2022-10-26
23산수-3동구계림동 579-7(전화박스 옆)250주택용-3KW2022-10-26
34산수-4동구산수동 553-33(무등로 474)200주택용-3KW2022-10-26
45산수-5동구산수동 367-20200주택용-3KW2022-10-26
56산수-6동구궁동 1-1(제봉로 171)250주택용-3KW2022-10-26
67산수-7동구호남동 48(중앙로 148번길 2)300주택용-3KW2022-10-26
78용산택지동구용산동 386250주택용-3KW2022-10-26
89월남1동구월남동642200주택용-3KW2022-10-26
910지원-27동구학동 165-3(백서로 116)250주택용-3KW2022-10-26
연번유량계명구설치위치관경계약전력데이터기준일
139140송정-6광산구도산동 884-20200주택용-3KW2022-10-26
140141송정-7광산구도산동 1130-2200주택용-3KW2022-10-26
141142송정8광산구장록동 752-1일원350주택용-3KW2022-10-26
142143송정8-1광산구용곡동 399-5부근100주택용-3KW2022-10-26
143144송정9광산구복룡동 566일원100주택용-3KW2022-10-26
144145진곡-1광산구오선동 622(진곡산단3번로 58)250주택용-3KW2022-10-26
145146진곡-2광산구진곡동 636(진곡산단3번로 59-13)250주택용-3KW2022-10-26
146147평동광산구월전동 58-8250주택용-3KW2022-10-26
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