Overview

Dataset statistics

Number of variables7
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory58.5 B

Variable types

Categorical5
Text2

Dataset

Description제주특별자치도개발공사가 생산하는 제주삼다수 수질검사 정보로 일반세균, 냄새, 경도, 색도 등 다양한 검사 및 결과 정보입니다.
Author제주특별자치도개발공사
URLhttps://www.data.go.kr/data/15112155/fileData.do

Alerts

채수일시 has constant value ""Constant
검사목적 has constant value ""Constant
채수지주소 has constant value ""Constant
시료명 has constant value ""Constant
결과 is highly imbalanced (62.6%)Imbalance
항목 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:17:04.466281
Analysis finished2024-04-06 08:17:05.339764
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

채수일시
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-30
52 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-30
2nd row2024-01-30
3rd row2024-01-30
4th row2024-01-30
5th row2024-01-30

Common Values

ValueCountFrequency (%)
2024-01-30 52
100.0%

Length

2024-04-06T17:17:05.531843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:05.806445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-30 52
100.0%

검사목적
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
참고용
52 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
참고용 52
100.0%

Length

2024-04-06T17:17:06.076063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:06.295007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
참고용 52
100.0%

채수지주소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
제추특별자치도 제주시 조천읍 남조로 1717-35
52 

Length

Max length27
Median length27
Mean length27
Min length27

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제추특별자치도 제주시 조천읍 남조로 1717-35
2nd row제추특별자치도 제주시 조천읍 남조로 1717-35
3rd row제추특별자치도 제주시 조천읍 남조로 1717-35
4th row제추특별자치도 제주시 조천읍 남조로 1717-35
5th row제추특별자치도 제주시 조천읍 남조로 1717-35

Common Values

ValueCountFrequency (%)
제추특별자치도 제주시 조천읍 남조로 1717-35 52
100.0%

Length

2024-04-06T17:17:06.511062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:06.780204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제추특별자치도 52
20.0%
제주시 52
20.0%
조천읍 52
20.0%
남조로 52
20.0%
1717-35 52
20.0%

시료명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
L4-2024.01.30.(2.0L)
52 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowL4-2024.01.30.(2.0L)
2nd rowL4-2024.01.30.(2.0L)
3rd rowL4-2024.01.30.(2.0L)
4th rowL4-2024.01.30.(2.0L)
5th rowL4-2024.01.30.(2.0L)

Common Values

ValueCountFrequency (%)
L4-2024.01.30.(2.0L) 52
100.0%

Length

2024-04-06T17:17:06.965831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:07.134946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
l4-2024.01.30.(2.0l 52
100.0%

항목
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-04-06T17:17:07.529101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length30.5
Mean length18.134615
Min length7

Characters and Unicode

Total characters943
Distinct characters163
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row(저온)일반세균(Total Colony Counts in 21 ℃)
2nd row(중온)일반세균(Total Colony Counts in 35 ℃)
3rd row총대장균군(Total Coliform)
4th row분원성연쇄상구균(Feacal Streptococcus)
5th row녹농균(Pseudomonas aeruginosa)
ValueCountFrequency (%)
counts 2
 
2.8%
in 2
 
2.8%
colony 2
 
2.8%
℃ 2
 
2.8%
저온)일반세균(total 1
 
1.4%
벤젠(benzene 1
 
1.4%
사염화탄소(tetrachlorocarbon 1
 
1.4%
1,1-디클로로에틸렌(1,1-dichloroethylene 1
 
1.4%
크실렌(xylene 1
 
1.4%
에틸벤젠(ethylebenzene 1
 
1.4%
Other values (58) 58
80.6%
2024-04-06T17:17:08.331248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 60
 
6.4%
( 54
 
5.7%
) 54
 
5.7%
e 53
 
5.6%
n 50
 
5.3%
r 42
 
4.5%
i 38
 
4.0%
a 36
 
3.8%
l 34
 
3.6%
t 28
 
3.0%
Other values (153) 494
52.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 480
50.9%
Other Letter 223
23.6%
Uppercase Letter 63
 
6.7%
Open Punctuation 54
 
5.7%
Close Punctuation 54
 
5.7%
Decimal Number 25
 
2.7%
Space Separator 20
 
2.1%
Dash Punctuation 13
 
1.4%
Other Punctuation 9
 
1.0%
Other Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 15
 
6.7%
소 8
 
3.6%
온 8
 
3.6%
성 6
 
2.7%
균 6
 
2.7%
산 6
 
2.7%
이 6
 
2.7%
클 6
 
2.7%
라 5
 
2.2%
에 5
 
2.2%
Other values (102) 152
68.2%
Lowercase Letter
ValueCountFrequency (%)
o 60
12.5%
e 53
11.0%
n 50
10.4%
r 42
8.8%
i 38
 
7.9%
a 36
 
7.5%
l 34
 
7.1%
t 28
 
5.8%
u 20
 
4.2%
h 19
 
4.0%
Other values (11) 100
20.8%
Uppercase Letter
ValueCountFrequency (%)
C 14
22.2%
T 9
14.3%
S 6
9.5%
A 4
 
6.3%
D 4
 
6.3%
B 3
 
4.8%
N 3
 
4.8%
F 3
 
4.8%
M 3
 
4.8%
P 3
 
4.8%
Other values (9) 11
17.5%
Decimal Number
ValueCountFrequency (%)
1 15
60.0%
3 3
 
12.0%
2 3
 
12.0%
4 3
 
12.0%
5 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 543
57.6%
Hangul 223
23.6%
Common 177
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 15
 
6.7%
소 8
 
3.6%
온 8
 
3.6%
성 6
 
2.7%
균 6
 
2.7%
산 6
 
2.7%
이 6
 
2.7%
클 6
 
2.7%
라 5
 
2.2%
에 5
 
2.2%
Other values (102) 152
68.2%
Latin
ValueCountFrequency (%)
o 60
 
11.0%
e 53
 
9.8%
n 50
 
9.2%
r 42
 
7.7%
i 38
 
7.0%
a 36
 
6.6%
l 34
 
6.3%
t 28
 
5.2%
u 20
 
3.7%
h 19
 
3.5%
Other values (30) 163
30.0%
Common
ValueCountFrequency (%)
( 54
30.5%
) 54
30.5%
20
 
11.3%
1 15
 
8.5%
- 13
 
7.3%
, 9
 
5.1%
3 3
 
1.7%
2 3
 
1.7%
4 3
 
1.7%
℃ 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 718
76.1%
Hangul 223
 
23.6%
Letterlike Symbols 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 60
 
8.4%
( 54
 
7.5%
) 54
 
7.5%
e 53
 
7.4%
n 50
 
7.0%
r 42
 
5.8%
i 38
 
5.3%
a 36
 
5.0%
l 34
 
4.7%
t 28
 
3.9%
Other values (40) 269
37.5%
Hangul
ValueCountFrequency (%)
로 15
 
6.7%
소 8
 
3.6%
온 8
 
3.6%
성 6
 
2.7%
균 6
 
2.7%
산 6
 
2.7%
이 6
 
2.7%
클 6
 
2.7%
라 5
 
2.2%
에 5
 
2.2%
Other values (102) 152
68.2%
Letterlike Symbols
ValueCountFrequency (%)
℃ 2
100.0%

기준
Text

Distinct32
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-04-06T17:17:08.729249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.769231
Min length2

Characters and Unicode

Total characters560
Distinct characters29
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)42.3%

Sample

1st row100 CFU/mL 이하
2nd row20 CFU/mL 이하
3rd row불검출/250 mL
4th row불검출/250 mL
5th row불검출/250 mL
ValueCountFrequency (%)
이하 43
30.1%
mg/l 39
27.3%
0.01 7
 
4.9%
ml 6
 
4.2%
불검출/250 5
 
3.5%
0.3 3
 
2.1%
0.03 3
 
2.1%
0.005 2
 
1.4%
cfu/ml 2
 
1.4%
0.05 2
 
1.4%
Other values (26) 31
21.7%
2024-04-06T17:17:09.471423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
16.2%
0 75
13.4%
m 47
8.4%
/ 47
8.4%
L 47
8.4%
하 43
7.7%
이 43
7.7%
g 39
7.0%
. 34
 
6.1%
5 17
 
3.0%
Other values (19) 77
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135
24.1%
Other Letter 110
19.6%
Space Separator 91
16.2%
Lowercase Letter 86
15.4%
Other Punctuation 81
14.5%
Uppercase Letter 56
10.0%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 75
55.6%
5 17
 
12.6%
1 16
 
11.9%
2 13
 
9.6%
3 8
 
5.9%
4 2
 
1.5%
7 2
 
1.5%
6 1
 
0.7%
9 1
 
0.7%
Other Letter
ValueCountFrequency (%)
하 43
39.1%
이 43
39.1%
불 7
 
6.4%
검 7
 
6.4%
출 7
 
6.4%
없 1
 
0.9%
음 1
 
0.9%
도 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
L 47
83.9%
U 3
 
5.4%
C 2
 
3.6%
F 2
 
3.6%
N 1
 
1.8%
T 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
m 47
54.7%
g 39
45.3%
Other Punctuation
ValueCountFrequency (%)
/ 47
58.0%
. 34
42.0%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 308
55.0%
Latin 142
25.4%
Hangul 110
 
19.6%

Most frequent character per script

Common
ValueCountFrequency (%)
91
29.5%
0 75
24.4%
/ 47
15.3%
. 34
 
11.0%
5 17
 
5.5%
1 16
 
5.2%
2 13
 
4.2%
3 8
 
2.6%
4 2
 
0.6%
7 2
 
0.6%
Other values (3) 3
 
1.0%
Latin
ValueCountFrequency (%)
m 47
33.1%
L 47
33.1%
g 39
27.5%
U 3
 
2.1%
C 2
 
1.4%
F 2
 
1.4%
N 1
 
0.7%
T 1
 
0.7%
Hangul
ValueCountFrequency (%)
하 43
39.1%
이 43
39.1%
불 7
 
6.4%
검 7
 
6.4%
출 7
 
6.4%
없 1
 
0.9%
음 1
 
0.9%
도 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 450
80.4%
Hangul 110
 
19.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
20.2%
0 75
16.7%
m 47
10.4%
/ 47
10.4%
L 47
10.4%
g 39
8.7%
. 34
 
7.6%
5 17
 
3.8%
1 16
 
3.6%
2 13
 
2.9%
Other values (11) 24
 
5.3%
Hangul
ValueCountFrequency (%)
하 43
39.1%
이 43
39.1%
불 7
 
6.4%
검 7
 
6.4%
출 7
 
6.4%
없 1
 
0.9%
음 1
 
0.9%
도 1
 
0.9%

결과
Categorical

IMBALANCE 

Distinct8
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size548.0 B
불검출
43 
0
 
3
0.4
 
1
20
 
1
없음
 
1
Other values (3)
 
3

Length

Max length4
Median length3
Mean length2.8269231
Min length1

Unique

Unique6 ?
Unique (%)11.5%

Sample

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

Common Values

ValueCountFrequency (%)
불검출 43
82.7%
0 3
 
5.8%
0.4 1
 
1.9%
20 1
 
1.9%
없음 1
 
1.9%
8 1
 
1.9%
6.7 1
 
1.9%
0.04 1
 
1.9%

Length

2024-04-06T17:17:09.778691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:17:10.058895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불검출 43
82.7%
0 3
 
5.8%
0.4 1
 
1.9%
20 1
 
1.9%
없음 1
 
1.9%
8 1
 
1.9%
6.7 1
 
1.9%
0.04 1
 
1.9%

Correlations

2024-04-06T17:17:10.223612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
항목기준결과
항목1.0001.0001.000
기준1.0001.0000.979
결과1.0000.9791.000

Missing values

2024-04-06T17:17:04.961234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:17:05.257970image/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

채수일시검사목적채수지주소시료명항목기준결과
02024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)(저온)일반세균(Total Colony Counts in 21 ℃)100 CFU/mL 이하0
12024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)(중온)일반세균(Total Colony Counts in 35 ℃)20 CFU/mL 이하0
22024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)총대장균군(Total Coliform)불검출/250 mL불검출
32024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)분원성연쇄상구균(Feacal Streptococcus)불검출/250 mL불검출
42024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)녹농균(Pseudomonas aeruginosa)불검출/250 mL불검출
52024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)아황산환원혐기성포자형성균(Clostridium perfringens)불검출/50 mL불검출
62024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)쉬겔라(Shigella)불검출/250 mL불검출
72024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)살모넬라(Salmonella)불검출/250 mL불검출
82024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)납(Lead)0.01 mg/L 이하불검출
92024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)불소(Fluoride)2.0 mg/L 이하불검출
채수일시검사목적채수지주소시료명항목기준결과
422024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)색도(Color)5도 이하0
432024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)음이온계면활성제(Anionic Surfactants)불검출불검출
442024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)수소이온농도(pH)4.5-9.58
452024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)아연(Zinc)3 mg/L 이하불검출
462024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)염소이온(Chloride)250 mg/L 이하6.7
472024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)철(Iron)0.3 mg/L 이하불검출
482024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)망간(Manganese)0.3 mg/L 이하불검출
492024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)탁도(Turbidity)1 NTU 이하0.04
502024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)황산이온(Sulfate)250 mg/L 이하불검출
512024-01-30참고용제추특별자치도 제주시 조천읍 남조로 1717-35L4-2024.01.30.(2.0L)알루미늄(Aluminium)0.2 mg/L 이하불검출