Overview

Dataset statistics

Number of variables8
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory67.7 B

Variable types

Categorical5
Text1
Numeric1
DateTime1

Dataset

Description매년 상/하반기에 실시한 제주특별자치도의 정수장으로 유입되는 상수원수 수질검사결과에 대한 데이터로 취수원별 질산성질소 검출량의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/3082745/fileData.do

Alerts

해당연도 has constant value ""Constant
기준단위 has constant value ""Constant
담당부서 has constant value ""Constant
데이터기준일자 has constant value ""Constant
질산성질소농도 has 1 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-12 12:18:59.369766
Analysis finished2023-12-12 12:19:00.006683
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

해당연도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2022
78 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 78
100.0%

Length

2023-12-12T21:19:00.082069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:00.195386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 78
100.0%

구분
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size756.0 B
상반기
39 
하반기
39 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상반기 39
50.0%
하반기 39
50.0%

Length

2023-12-12T21:19:00.318285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:00.440244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상반기 39
50.0%
하반기 39
50.0%

정수장
Categorical

Distinct17
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
조천정수장
10 
남원정수장
10 
유수암정수장
8 
회수정수장
6 
서광정수장
6 
Other values (12)
38 

Length

Max length6
Median length5
Mean length5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
조천정수장 10
12.8%
남원정수장 10
12.8%
유수암정수장 8
10.3%
회수정수장 6
7.7%
서광정수장 6
7.7%
구좌정수장 6
7.7%
애월정수장 6
7.7%
기타 4
 
5.1%
도련정수장 4
 
5.1%
월산정수장 4
 
5.1%
Other values (7) 14
17.9%

Length

2023-12-12T21:19:00.591468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조천정수장 10
12.8%
남원정수장 10
12.8%
유수암정수장 8
10.3%
회수정수장 6
7.7%
서광정수장 6
7.7%
구좌정수장 6
7.7%
애월정수장 6
7.7%
월산정수장 4
 
5.1%
도련정수장 4
 
5.1%
기타 4
 
5.1%
Other values (7) 14
17.9%

취수원
Text

Distinct39
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T21:19:00.812560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.2820513
Min length6

Characters and Unicode

Total characters490
Distinct characters59
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row삼양 취수원
2nd row회천 취수원
3rd row선흘 취수원
4th row함덕 취수원
5th row조천 지하수
ValueCountFrequency (%)
취수원 44
28.2%
수원지 20
 
12.8%
지하수 14
 
9.0%
서광 4
 
2.6%
상예 4
 
2.6%
회수 4
 
2.6%
외도 4
 
2.6%
삼양3 2
 
1.3%
도련 2
 
1.3%
옹포 2
 
1.3%
Other values (28) 56
35.9%
2023-12-12T21:19:01.199056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 82
16.7%
78
15.9%
원 70
14.3%
취 44
 
9.0%
지 36
 
7.3%
하 14
 
2.9%
1 8
 
1.6%
2 8
 
1.6%
상 8
 
1.6%
회 6
 
1.2%
Other values (49) 136
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 392
80.0%
Space Separator 78
 
15.9%
Decimal Number 18
 
3.7%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 82
20.9%
원 70
17.9%
취 44
 
11.2%
지 36
 
9.2%
하 14
 
3.6%
상 8
 
2.0%
회 6
 
1.5%
귀 6
 
1.5%
삼 6
 
1.5%
도 6
 
1.5%
Other values (44) 114
29.1%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
2 8
44.4%
3 2
 
11.1%
Space Separator
ValueCountFrequency (%)
78
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 392
80.0%
Common 98
 
20.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 82
20.9%
원 70
17.9%
취 44
 
11.2%
지 36
 
9.2%
하 14
 
3.6%
상 8
 
2.0%
회 6
 
1.5%
귀 6
 
1.5%
삼 6
 
1.5%
도 6
 
1.5%
Other values (44) 114
29.1%
Common
ValueCountFrequency (%)
78
79.6%
1 8
 
8.2%
2 8
 
8.2%
. 2
 
2.0%
3 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 392
80.0%
ASCII 98
 
20.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 82
20.9%
원 70
17.9%
취 44
 
11.2%
지 36
 
9.2%
하 14
 
3.6%
상 8
 
2.0%
회 6
 
1.5%
귀 6
 
1.5%
삼 6
 
1.5%
도 6
 
1.5%
Other values (44) 114
29.1%
ASCII
ValueCountFrequency (%)
78
79.6%
1 8
 
8.2%
2 8
 
8.2%
. 2
 
2.0%
3 2
 
2.0%

질산성질소농도
Real number (ℝ)

ZEROS 

Distinct37
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0884615
Minimum0
Maximum9.7
Zeros1
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T21:19:01.354411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q11.1
median1.85
Q32.5
95-th percentile5.09
Maximum9.7
Range9.7
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.679052
Coefficient of variation (CV)0.80396599
Kurtosis8.9020644
Mean2.0884615
Median Absolute Deviation (MAD)0.75
Skewness2.5177565
Sum162.9
Variance2.8192158
MonotonicityNot monotonic
2023-12-12T21:19:01.522184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1.8 5
 
6.4%
2.5 5
 
6.4%
1.1 4
 
5.1%
1.5 4
 
5.1%
0.4 4
 
5.1%
2.0 3
 
3.8%
1.9 3
 
3.8%
2.3 3
 
3.8%
1.0 3
 
3.8%
2.4 3
 
3.8%
Other values (27) 41
52.6%
ValueCountFrequency (%)
0.0 1
 
1.3%
0.2 2
2.6%
0.3 2
2.6%
0.4 4
5.1%
0.5 1
 
1.3%
0.7 3
3.8%
0.8 2
2.6%
0.9 1
 
1.3%
1.0 3
3.8%
1.1 4
5.1%
ValueCountFrequency (%)
9.7 1
1.3%
9.4 1
1.3%
5.8 1
1.3%
5.6 1
1.3%
5.0 1
1.3%
4.5 1
1.3%
3.6 1
1.3%
3.3 1
1.3%
3.2 1
1.3%
3.1 1
1.3%

기준단위
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
10mg/L
78 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10mg/L
2nd row10mg/L
3rd row10mg/L
4th row10mg/L
5th row10mg/L

Common Values

ValueCountFrequency (%)
10mg/L 78
100.0%

Length

2023-12-12T21:19:01.684879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:01.811542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10mg/l 78
100.0%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
상수도부
78 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도부 78
100.0%

Length

2023-12-12T21:19:01.920158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:19:02.047682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도부 78
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
Minimum2023-01-13 00:00:00
Maximum2023-01-13 00:00:00
2023-12-12T21:19:02.171821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:19:02.289272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:18:59.610929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:19:02.391422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정수장취수원질산성질소농도
구분1.0000.0000.0000.000
정수장0.0001.0001.0000.759
취수원0.0001.0001.0000.909
질산성질소농도0.0000.7590.9091.000
2023-12-12T21:19:02.496899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분정수장
구분1.0000.000
정수장0.0001.000
2023-12-12T21:19:02.906029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
질산성질소농도구분정수장
질산성질소농도1.0000.0000.435
구분0.0001.0000.000
정수장0.4350.0001.000

Missing values

2023-12-12T21:18:59.790410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:18:59.946350image/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

해당연도구분정수장취수원질산성질소농도기준단위담당부서데이터기준일자
02022상반기조천정수장삼양 취수원3.310mg/L상수도부2023-01-13
12022상반기조천정수장회천 취수원5.010mg/L상수도부2023-01-13
22022상반기조천정수장선흘 취수원2.710mg/L상수도부2023-01-13
32022상반기조천정수장함덕 취수원2.210mg/L상수도부2023-01-13
42022상반기조천정수장조천 지하수1.410mg/L상수도부2023-01-13
52022상반기남원정수장의귀1 취수원1.310mg/L상수도부2023-01-13
62022상반기남원정수장의귀2 취수원0.710mg/L상수도부2023-01-13
72022상반기남원정수장신흥1 취수원1.810mg/L상수도부2023-01-13
82022상반기남원정수장신흥2 취수원2.510mg/L상수도부2023-01-13
92022상반기남원정수장남원 지하수0.510mg/L상수도부2023-01-13
해당연도구분정수장취수원질산성질소농도기준단위담당부서데이터기준일자
682022하반기월산정수장이호 수원지2.010mg/L상수도부2023-01-13
692022하반기오라정수장용담 수원지1.510mg/L상수도부2023-01-13
702022하반기어승생정수장어승생 수원지0.210mg/L상수도부2023-01-13
712022하반기한림정수장옹포 수원지9.410mg/L상수도부2023-01-13
722022하반기도련정수장도련 지하수2.210mg/L상수도부2023-01-13
732022하반기도련정수장삼양3 수원지2.710mg/L상수도부2023-01-13
742022하반기별도봉정수장삼양1.2 수원지1.610mg/L상수도부2023-01-13
752022하반기강정정수장강정 수원지2.510mg/L상수도부2023-01-13
762022하반기기타상예 수원지5.610mg/L상수도부2023-01-13
772022하반기기타서홍 수원지1.110mg/L상수도부2023-01-13