Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory69.3 B

Variable types

Numeric1
Categorical4
Text3

Dataset

Description샘플 데이터
Author지디에스컨설팅그룹
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=0b2018f0-3072-11eb-a877-a5b67dc5814b

Alerts

학제 has constant value ""Constant
수소이온농도 is highly overall correlated with 잔류염소 and 1 other fieldsHigh correlation
잔류염소 is highly overall correlated with 수소이온농도 and 1 other fieldsHigh correlation
탁도 is highly overall correlated with 수소이온농도 and 1 other fieldsHigh correlation
고유번호 has unique valuesUnique
학교명 has unique valuesUnique
주소 has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:22:35.892326
Analysis finished2023-12-10 13:22:37.391279
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고유번호
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.91
Minimum1
Maximum146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:22:37.503026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.9
Q138.75
median71.5
Q3108.5
95-th percentile138.05
Maximum146
Range145
Interquartile range (IQR)69.75

Descriptive statistics

Standard deviation41.346551
Coefficient of variation (CV)0.55941755
Kurtosis-1.1588508
Mean73.91
Median Absolute Deviation (MAD)35.5
Skewness0.077675636
Sum7391
Variance1709.5373
MonotonicityStrictly increasing
2023-12-10T22:22:37.778137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
90 1
 
1.0%
108 1
 
1.0%
107 1
 
1.0%
105 1
 
1.0%
103 1
 
1.0%
100 1
 
1.0%
99 1
 
1.0%
98 1
 
1.0%
93 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
4 1
1.0%
5 1
1.0%
9 1
1.0%
11 1
1.0%
13 1
1.0%
14 1
1.0%
15 1
1.0%
16 1
1.0%
17 1
1.0%
ValueCountFrequency (%)
146 1
1.0%
144 1
1.0%
142 1
1.0%
140 1
1.0%
139 1
1.0%
138 1
1.0%
137 1
1.0%
136 1
1.0%
135 1
1.0%
134 1
1.0%

학제
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
어린이집
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 100
100.0%

Length

2023-12-10T22:22:37.997909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:38.166315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 100
100.0%

학교명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:22:38.468945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.15
Min length6

Characters and Unicode

Total characters715
Distinct characters161
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row이루숲어린이집
2nd row꿈초롱어린이집
3rd row패트와매트어린이집
4th row연두어린이집
5th row동부어린이집
ValueCountFrequency (%)
어린이집 5
 
4.7%
이루숲어린이집 1
 
0.9%
통통어린이집 1
 
0.9%
훈민정음 1
 
0.9%
킹스키즈어린이집 1
 
0.9%
슬기어린이집 1
 
0.9%
사랑어린이집 1
 
0.9%
사임당 1
 
0.9%
푸른금산어린이집 1
 
0.9%
아이맘어린이집 1
 
0.9%
Other values (92) 92
86.8%
2023-12-10T22:22:39.055794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 111
15.5%
린 101
 
14.1%
집 100
 
14.0%
어 100
 
14.0%
아 10
 
1.4%
나 9
 
1.3%
사 8
 
1.1%
리 7
 
1.0%
지 6
 
0.8%
6
 
0.8%
Other values (151) 257
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 702
98.2%
Space Separator 6
 
0.8%
Uppercase Letter 4
 
0.6%
Lowercase Letter 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 111
15.8%
린 101
14.4%
집 100
14.2%
어 100
14.2%
아 10
 
1.4%
나 9
 
1.3%
사 8
 
1.1%
리 7
 
1.0%
지 6
 
0.9%
은 6
 
0.9%
Other values (145) 244
34.8%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
C 1
25.0%
W 1
25.0%
Y 1
25.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 702
98.2%
Latin 7
 
1.0%
Common 6
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 111
15.8%
린 101
14.4%
집 100
14.2%
어 100
14.2%
아 10
 
1.4%
나 9
 
1.3%
사 8
 
1.1%
리 7
 
1.0%
지 6
 
0.9%
은 6
 
0.9%
Other values (145) 244
34.8%
Latin
ValueCountFrequency (%)
c 3
42.9%
A 1
 
14.3%
C 1
 
14.3%
W 1
 
14.3%
Y 1
 
14.3%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 702
98.2%
ASCII 13
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 111
15.8%
린 101
14.4%
집 100
14.2%
어 100
14.2%
아 10
 
1.4%
나 9
 
1.3%
사 8
 
1.1%
리 7
 
1.0%
지 6
 
0.9%
은 6
 
0.9%
Other values (145) 244
34.8%
ASCII
ValueCountFrequency (%)
6
46.2%
c 3
23.1%
A 1
 
7.7%
C 1
 
7.7%
W 1
 
7.7%
Y 1
 
7.7%

주소
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:22:39.590364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length40
Mean length29.1
Min length15

Characters and Unicode

Total characters2910
Distinct characters163
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row강원도 춘천시 백석골길22번길 21-21 이루숲어린이집(퇴계동)
2nd row강원도 춘천시 부평길 7 한신아파트 4동 105호(후평동 864)
3rd row강원도 춘천시 영서로 2169 103동101호 (퇴계동, 퇴계이안아파트)
4th row강원도 춘천시 대룡산길 132-12 (사암리 572-2)
5th row강원도 춘천시 충열로 32 102동 106호(우두동,동부아파트)
ValueCountFrequency (%)
춘천시 100
 
17.4%
강원도 94
 
16.4%
퇴계동 13
 
2.3%
동면 12
 
2.1%
후평동 10
 
1.7%
동내면 10
 
1.7%
강원 6
 
1.0%
효자동 5
 
0.9%
11 4
 
0.7%
안마산로 4
 
0.7%
Other values (242) 316
55.1%
2023-12-10T22:22:40.300731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
475
 
16.3%
1 162
 
5.6%
동 127
 
4.4%
천 117
 
4.0%
춘 113
 
3.9%
강 104
 
3.6%
시 101
 
3.5%
원 101
 
3.5%
도 94
 
3.2%
2 90
 
3.1%
Other values (153) 1426
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1665
57.2%
Decimal Number 560
 
19.2%
Space Separator 475
 
16.3%
Close Punctuation 70
 
2.4%
Open Punctuation 70
 
2.4%
Dash Punctuation 34
 
1.2%
Other Punctuation 33
 
1.1%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 127
 
7.6%
천 117
 
7.0%
춘 113
 
6.8%
강 104
 
6.2%
시 101
 
6.1%
원 101
 
6.1%
도 94
 
5.6%
길 65
 
3.9%
로 60
 
3.6%
계 43
 
2.6%
Other values (135) 740
44.4%
Decimal Number
ValueCountFrequency (%)
1 162
28.9%
2 90
16.1%
0 74
13.2%
3 53
 
9.5%
4 48
 
8.6%
6 35
 
6.2%
7 32
 
5.7%
8 25
 
4.5%
5 23
 
4.1%
9 18
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
475
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 33
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1665
57.2%
Common 1242
42.7%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 127
 
7.6%
천 117
 
7.0%
춘 113
 
6.8%
강 104
 
6.2%
시 101
 
6.1%
원 101
 
6.1%
도 94
 
5.6%
길 65
 
3.9%
로 60
 
3.6%
계 43
 
2.6%
Other values (135) 740
44.4%
Common
ValueCountFrequency (%)
475
38.2%
1 162
 
13.0%
2 90
 
7.2%
0 74
 
6.0%
) 70
 
5.6%
( 70
 
5.6%
3 53
 
4.3%
4 48
 
3.9%
6 35
 
2.8%
- 34
 
2.7%
Other values (5) 131
 
10.5%
Latin
ValueCountFrequency (%)
e 1
33.3%
L 1
33.3%
H 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1665
57.2%
ASCII 1245
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
475
38.2%
1 162
 
13.0%
2 90
 
7.2%
0 74
 
5.9%
) 70
 
5.6%
( 70
 
5.6%
3 53
 
4.3%
4 48
 
3.9%
6 35
 
2.8%
- 34
 
2.7%
Other values (8) 134
 
10.8%
Hangul
ValueCountFrequency (%)
동 127
 
7.6%
천 117
 
7.0%
춘 113
 
6.8%
강 104
 
6.2%
시 101
 
6.1%
원 101
 
6.1%
도 94
 
5.6%
길 65
 
3.9%
로 60
 
3.6%
계 43
 
2.6%
Other values (135) 740
44.4%

연락처
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:22:40.775014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02
Min length12

Characters and Unicode

Total characters1202
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row033-243-8833
2nd row033-256-0879
3rd row070-8688-8616
4th row033-262-1443
5th row033-253-3407
ValueCountFrequency (%)
033-243-8833 1
 
1.0%
033-241-1782 1
 
1.0%
033-252-4828 1
 
1.0%
033-262-7000 1
 
1.0%
033-257-3387 1
 
1.0%
033-255-5521 1
 
1.0%
033-261-4020 1
 
1.0%
033-243-9154 1
 
1.0%
033-254-4544 1
 
1.0%
033-256-2218 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T22:22:41.467480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 253
21.0%
- 200
16.6%
2 166
13.8%
0 145
12.1%
5 93
 
7.7%
4 72
 
6.0%
6 71
 
5.9%
1 60
 
5.0%
8 52
 
4.3%
7 52
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1002
83.4%
Dash Punctuation 200
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 253
25.2%
2 166
16.6%
0 145
14.5%
5 93
 
9.3%
4 72
 
7.2%
6 71
 
7.1%
1 60
 
6.0%
8 52
 
5.2%
7 52
 
5.2%
9 38
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 253
21.0%
- 200
16.6%
2 166
13.8%
0 145
12.1%
5 93
 
7.7%
4 72
 
6.0%
6 71
 
5.9%
1 60
 
5.0%
8 52
 
4.3%
7 52
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 253
21.0%
- 200
16.6%
2 166
13.8%
0 145
12.1%
5 93
 
7.7%
4 72
 
6.0%
6 71
 
5.9%
1 60
 
5.0%
8 52
 
4.3%
7 52
 
4.3%

수소이온농도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
6.9
88 
7.7
12 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6.9
2nd row6.9
3rd row6.9
4th row6.9
5th row7.7

Common Values

ValueCountFrequency (%)
6.9 88
88.0%
7.7 12
 
12.0%

Length

2023-12-10T22:22:41.701566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:41.894571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6.9 88
88.0%
7.7 12
 
12.0%

잔류염소
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.5
88 
0.4
12 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.5 88
88.0%
0.4 12
 
12.0%

Length

2023-12-10T22:22:42.092314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:42.263781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.5 88
88.0%
0.4 12
 
12.0%

탁도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.06
88 
0.05
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.06
2nd row0.06
3rd row0.06
4th row0.06
5th row0.05

Common Values

ValueCountFrequency (%)
0.06 88
88.0%
0.05 12
 
12.0%

Length

2023-12-10T22:22:42.514666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:22:42.826653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.06 88
88.0%
0.05 12
 
12.0%

Interactions

2023-12-10T22:22:36.714870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:22:42.956141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호학교명주소연락처수소이온농도잔류염소탁도
고유번호1.0001.0001.0001.0000.0000.0000.000
학교명1.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.000
수소이온농도0.0001.0001.0001.0001.0000.9970.997
잔류염소0.0001.0001.0001.0000.9971.0000.997
탁도0.0001.0001.0001.0000.9970.9971.000
2023-12-10T22:22:43.121757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수소이온농도잔류염소탁도
수소이온농도1.0000.9520.952
잔류염소0.9521.0000.952
탁도0.9520.9521.000
2023-12-10T22:22:43.678816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고유번호수소이온농도잔류염소탁도
고유번호1.0000.0000.0000.000
수소이온농도0.0001.0000.9520.952
잔류염소0.0000.9521.0000.952
탁도0.0000.9520.9521.000

Missing values

2023-12-10T22:22:37.005954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:22:37.323305image/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

고유번호학제학교명주소연락처수소이온농도잔류염소탁도
01어린이집이루숲어린이집강원도 춘천시 백석골길22번길 21-21 이루숲어린이집(퇴계동)033-243-88336.90.50.06
14어린이집꿈초롱어린이집강원도 춘천시 부평길 7 한신아파트 4동 105호(후평동 864)033-256-08796.90.50.06
25어린이집패트와매트어린이집강원도 춘천시 영서로 2169 103동101호 (퇴계동, 퇴계이안아파트)070-8688-86166.90.50.06
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614어린이집일성어린이집강원도 춘천시 우묵길78번길 25 203동103호 (퇴계동, 일성아파트)033-243-89666.90.50.06
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98144어린이집샛별어린이집강원도 춘천시 동면 만천로 107 107동 101호(만천리, 한일유앤아이아파트)033-251-85846.90.50.06
99146어린이집코아루 어린이집강원도 춘천시 새청말길 26 관리동1층 (우두동, 강변코아루아파트)033-255-34547.70.40.05