Overview

Dataset statistics

Number of variables14
Number of observations29
Missing cells262
Missing cells (%)64.5%
Duplicate rows1
Duplicate rows (%)3.4%
Total size in memory3.5 KiB
Average record size in memory122.6 B

Variable types

Text8
Unsupported6

Dataset

Description용담호유입하천수질조사결과2016년1월
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202624

Alerts

Dataset has 1 (3.4%) duplicate rowsDuplicates
채수지점 has 11 (37.9%) missing valuesMissing
통학교 has 11 (37.9%) missing valuesMissing
동정교 has 11 (37.9%) missing valuesMissing
천천1교 has 11 (37.9%) missing valuesMissing
오봉교 has 11 (37.9%) missing valuesMissing
섬티교 has 11 (37.9%) missing valuesMissing
구암교 has 11 (37.9%) missing valuesMissing
금성교 has 11 (37.9%) missing valuesMissing
Unnamed: 8 has 29 (100.0%) missing valuesMissing
Unnamed: 9 has 29 (100.0%) missing valuesMissing
Unnamed: 10 has 29 (100.0%) missing valuesMissing
Unnamed: 11 has 29 (100.0%) missing valuesMissing
Unnamed: 12 has 29 (100.0%) missing valuesMissing
Unnamed: 13 has 29 (100.0%) missing valuesMissing
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:21:48.181072
Analysis finished2024-03-14 00:21:48.829832
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

채수지점
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:48.969373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length13
Mean length10
Min length2

Characters and Unicode

Total characters180
Distinct characters48
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row채수일시
2nd row검사기간
3rd row수온(℃)
4th rowpH
5th rowDO(mg/L)
ValueCountFrequency (%)
검사기간 1
 
4.8%
t-n(mg/l 1
 
4.8%
분원성대장균군수/100ml 1
 
4.8%
분원성대장균군 1
 
4.8%
총대장균군수/100ml 1
 
4.8%
총대장균군 1
 
4.8%
ss(mg/l 1
 
4.8%
chl-a(mg/m3 1
 
4.8%
t-p(mg/l 1
 
4.8%
po4-p(mg/l 1
 
4.8%
Other values (11) 11
52.4%
2024-03-14T09:21:49.258715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 15
 
8.3%
( 15
 
8.3%
m 15
 
8.3%
/ 14
 
7.8%
L 12
 
6.7%
g 11
 
6.1%
N 7
 
3.9%
- 7
 
3.9%
O 6
 
3.3%
수 4
 
2.2%
Other values (38) 74
41.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41
22.8%
Other Letter 41
22.8%
Lowercase Letter 32
17.8%
Close Punctuation 15
 
8.3%
Open Punctuation 15
 
8.3%
Other Punctuation 14
 
7.8%
Decimal Number 11
 
6.1%
Dash Punctuation 7
 
3.9%
Control 3
 
1.7%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 4
 
9.8%
대 4
 
9.8%
균 4
 
9.8%
장 4
 
9.8%
군 4
 
9.8%
총 2
 
4.9%
전 2
 
4.9%
도 2
 
4.9%
분 2
 
4.9%
원 2
 
4.9%
Other values (9) 11
26.8%
Uppercase Letter
ValueCountFrequency (%)
L 12
29.3%
N 7
17.1%
O 6
14.6%
S 3
 
7.3%
D 3
 
7.3%
P 3
 
7.3%
T 2
 
4.9%
C 2
 
4.9%
H 2
 
4.9%
B 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
m 15
46.9%
g 11
34.4%
h 1
 
3.1%
a 1
 
3.1%
l 1
 
3.1%
c 1
 
3.1%
μ 1
 
3.1%
p 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
0 4
36.4%
3 3
27.3%
1 2
18.2%
4 1
 
9.1%
2 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 72
40.0%
Common 66
36.7%
Hangul 41
22.8%
Greek 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 4
 
9.8%
대 4
 
9.8%
균 4
 
9.8%
장 4
 
9.8%
군 4
 
9.8%
총 2
 
4.9%
전 2
 
4.9%
도 2
 
4.9%
분 2
 
4.9%
원 2
 
4.9%
Other values (9) 11
26.8%
Latin
ValueCountFrequency (%)
m 15
20.8%
L 12
16.7%
g 11
15.3%
N 7
9.7%
O 6
 
8.3%
S 3
 
4.2%
D 3
 
4.2%
P 3
 
4.2%
T 2
 
2.8%
C 2
 
2.8%
Other values (7) 8
11.1%
Common
ValueCountFrequency (%)
) 15
22.7%
( 15
22.7%
/ 14
21.2%
- 7
10.6%
0 4
 
6.1%
3
 
4.5%
3 3
 
4.5%
1 2
 
3.0%
4 1
 
1.5%
℃ 1
 
1.5%
Greek
ValueCountFrequency (%)
μ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137
76.1%
Hangul 41
 
22.8%
None 1
 
0.6%
Letterlike Symbols 1
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 15
10.9%
( 15
10.9%
m 15
10.9%
/ 14
10.2%
L 12
 
8.8%
g 11
 
8.0%
N 7
 
5.1%
- 7
 
5.1%
O 6
 
4.4%
0 4
 
2.9%
Other values (17) 31
22.6%
Hangul
ValueCountFrequency (%)
수 4
 
9.8%
대 4
 
9.8%
균 4
 
9.8%
장 4
 
9.8%
군 4
 
9.8%
총 2
 
4.9%
전 2
 
4.9%
도 2
 
4.9%
분 2
 
4.9%
원 2
 
4.9%
Other values (9) 11
26.8%
None
ValueCountFrequency (%)
μ 1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

통학교
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:49.392465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16.5
Mean length6.1111111
Min length4

Characters and Unicode

Total characters110
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row2016.01.21 10:20
2nd row2016.01.21- 01.31
3rd row1.7
4th row8.5
5th row12.1
ValueCountFrequency (%)
2016.01.21 2
 
10.0%
4.090 1
 
5.0%
281 1
 
5.0%
365 1
 
5.0%
1.8 1
 
5.0%
0.5 1
 
5.0%
0.036 1
 
5.0%
0.008 1
 
5.0%
5.290 1
 
5.0%
10:20 1
 
5.0%
Other values (9) 9
45.0%
2024-03-14T09:21:49.697663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
20.9%
. 18
16.4%
1 16
14.5%
16
14.5%
2 10
9.1%
8 7
 
6.4%
5 5
 
4.5%
6 4
 
3.6%
3 3
 
2.7%
2
 
1.8%
Other values (5) 6
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
65.5%
Other Punctuation 19
 
17.3%
Space Separator 16
 
14.5%
Control 2
 
1.8%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
31.9%
1 16
22.2%
2 10
13.9%
8 7
 
9.7%
5 5
 
6.9%
6 4
 
5.6%
3 3
 
4.2%
9 2
 
2.8%
7 1
 
1.4%
4 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
20.9%
. 18
16.4%
1 16
14.5%
16
14.5%
2 10
9.1%
8 7
 
6.4%
5 5
 
4.5%
6 4
 
3.6%
3 3
 
2.7%
2
 
1.8%
Other values (5) 6
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
20.9%
. 18
16.4%
1 16
14.5%
16
14.5%
2 10
9.1%
8 7
 
6.4%
5 5
 
4.5%
6 4
 
3.6%
3 3
 
2.7%
2
 
1.8%
Other values (5) 6
 
5.5%

동정교
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:49.864362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length6.0555556
Min length3

Characters and Unicode

Total characters109
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row2016.01.21 10:38
2nd row2016.01.21- 01.31
3rd row0.8
4th row8.5
5th row12.5
ValueCountFrequency (%)
2016.01.21 2
 
10.0%
3.965 1
 
5.0%
30 1
 
5.0%
370 1
 
5.0%
1.4 1
 
5.0%
0.5 1
 
5.0%
0.026 1
 
5.0%
0.003 1
 
5.0%
5.228 1
 
5.0%
10:38 1
 
5.0%
Other values (9) 9
45.0%
2024-03-14T09:21:50.120928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
17.4%
. 18
16.5%
16
14.7%
2 13
11.9%
1 11
10.1%
3 7
 
6.4%
6 6
 
5.5%
5 6
 
5.5%
8 4
 
3.7%
2
 
1.8%
Other values (5) 7
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
65.1%
Other Punctuation 19
 
17.4%
Space Separator 16
 
14.7%
Control 2
 
1.8%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
26.8%
2 13
18.3%
1 11
15.5%
3 7
 
9.9%
6 6
 
8.5%
5 6
 
8.5%
8 4
 
5.6%
4 2
 
2.8%
9 2
 
2.8%
7 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
17.4%
. 18
16.5%
16
14.7%
2 13
11.9%
1 11
10.1%
3 7
 
6.4%
6 6
 
5.5%
5 6
 
5.5%
8 4
 
3.7%
2
 
1.8%
Other values (5) 7
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
17.4%
. 18
16.5%
16
14.7%
2 13
11.9%
1 11
10.1%
3 7
 
6.4%
6 6
 
5.5%
5 6
 
5.5%
8 4
 
3.7%
2
 
1.8%
Other values (5) 7
 
6.4%

천천1교
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:50.250605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16.5
Mean length6.1111111
Min length4

Characters and Unicode

Total characters110
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row2016.01.21 10:46
2nd row2016.01.21- 01.31
3rd row0.2
4th row8.2
5th row11.9
ValueCountFrequency (%)
2016.01.21 2
 
10.0%
4.136 1
 
5.0%
703 1
 
5.0%
775 1
 
5.0%
1.7 1
 
5.0%
1.5 1
 
5.0%
0.028 1
 
5.0%
0.007 1
 
5.0%
5.494 1
 
5.0%
10:46 1
 
5.0%
Other values (9) 9
45.0%
2024-03-14T09:21:50.510264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 18
16.4%
0 17
15.5%
1 16
14.5%
16
14.5%
2 10
9.1%
3 6
 
5.5%
6 5
 
4.5%
7 5
 
4.5%
5 4
 
3.6%
4 4
 
3.6%
Other values (5) 9
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
65.5%
Other Punctuation 19
 
17.3%
Space Separator 16
 
14.5%
Control 2
 
1.8%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
23.6%
1 16
22.2%
2 10
13.9%
3 6
 
8.3%
6 5
 
6.9%
7 5
 
6.9%
5 4
 
5.6%
4 4
 
5.6%
8 3
 
4.2%
9 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 18
16.4%
0 17
15.5%
1 16
14.5%
16
14.5%
2 10
9.1%
3 6
 
5.5%
6 5
 
4.5%
7 5
 
4.5%
5 4
 
3.6%
4 4
 
3.6%
Other values (5) 9
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 18
16.4%
0 17
15.5%
1 16
14.5%
16
14.5%
2 10
9.1%
3 6
 
5.5%
6 5
 
4.5%
7 5
 
4.5%
5 4
 
3.6%
4 4
 
3.6%
Other values (5) 9
8.2%

오봉교
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:50.638836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length6
Min length2

Characters and Unicode

Total characters108
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row2016.01.21 10:54
2nd row2016.01.21- 01.31
3rd row0.8
4th row6.9
5th row10.8
ValueCountFrequency (%)
2016.01.21 2
 
10.0%
5.673 1
 
5.0%
1 1
 
5.0%
100 1
 
5.0%
0.6 1
 
5.0%
1.2 1
 
5.0%
0.024 1
 
5.0%
0.004 1
 
5.0%
6.858 1
 
5.0%
10:54 1
 
5.0%
Other values (9) 9
45.0%
2024-03-14T09:21:50.887710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22
20.4%
. 18
16.7%
1 16
14.8%
15
13.9%
2 7
 
6.5%
6 7
 
6.5%
3 4
 
3.7%
8 4
 
3.7%
5 3
 
2.8%
4 3
 
2.8%
Other values (6) 9
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
64.8%
Other Punctuation 19
 
17.6%
Space Separator 15
 
13.9%
Control 2
 
1.9%
Dash Punctuation 1
 
0.9%
Math Symbol 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22
31.4%
1 16
22.9%
2 7
 
10.0%
6 7
 
10.0%
3 4
 
5.7%
8 4
 
5.7%
5 3
 
4.3%
4 3
 
4.3%
9 2
 
2.9%
7 2
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
< 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22
20.4%
. 18
16.7%
1 16
14.8%
15
13.9%
2 7
 
6.5%
6 7
 
6.5%
3 4
 
3.7%
8 4
 
3.7%
5 3
 
2.8%
4 3
 
2.8%
Other values (6) 9
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22
20.4%
. 18
16.7%
1 16
14.8%
15
13.9%
2 7
 
6.5%
6 7
 
6.5%
3 4
 
3.7%
8 4
 
3.7%
5 3
 
2.8%
4 3
 
2.8%
Other values (6) 9
8.3%

섬티교
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:51.020558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length6.0555556
Min length3

Characters and Unicode

Total characters109
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row2016.01.21 11:30
2nd row2016.01.21- 01.31
3rd row0.3
4th row8.2
5th row12.2
ValueCountFrequency (%)
2016.01.21 2
 
10.0%
2.825 1
 
5.0%
20 1
 
5.0%
100 1
 
5.0%
0.9 1
 
5.0%
1.0 1
 
5.0%
0.015 1
 
5.0%
0.003 1
 
5.0%
3.551 1
 
5.0%
11:30 1
 
5.0%
Other values (9) 9
45.0%
2024-03-14T09:21:51.310321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23
21.1%
. 18
16.5%
1 16
14.7%
16
14.7%
2 11
10.1%
3 6
 
5.5%
5 5
 
4.6%
6 4
 
3.7%
8 3
 
2.8%
2
 
1.8%
Other values (4) 5
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
65.1%
Other Punctuation 19
 
17.4%
Space Separator 16
 
14.7%
Control 2
 
1.8%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23
32.4%
1 16
22.5%
2 11
15.5%
3 6
 
8.5%
5 5
 
7.0%
6 4
 
5.6%
8 3
 
4.2%
9 2
 
2.8%
7 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23
21.1%
. 18
16.5%
1 16
14.7%
16
14.7%
2 11
10.1%
3 6
 
5.5%
5 5
 
4.6%
6 4
 
3.7%
8 3
 
2.8%
2
 
1.8%
Other values (4) 5
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23
21.1%
. 18
16.5%
1 16
14.7%
16
14.7%
2 11
10.1%
3 6
 
5.5%
5 5
 
4.6%
6 4
 
3.7%
8 3
 
2.8%
2
 
1.8%
Other values (4) 5
 
4.6%

구암교
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:51.459914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length5.9444444
Min length2

Characters and Unicode

Total characters107
Distinct characters16
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)88.9%

Sample

1st row2016.01.21 13:08
2nd row2016.01.21- 01.31
3rd row0.5
4th row8.1
5th row11.7
ValueCountFrequency (%)
0.5 2
 
10.0%
2016.01.21 2
 
10.0%
3.286 1
 
5.0%
2.410 1
 
5.0%
1 1
 
5.0%
50 1
 
5.0%
1.8 1
 
5.0%
0.012 1
 
5.0%
0.003 1
 
5.0%
13:08 1
 
5.0%
Other values (8) 8
40.0%
2024-03-14T09:21:51.713213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 22
20.6%
. 18
16.8%
1 18
16.8%
15
14.0%
2 7
 
6.5%
8 6
 
5.6%
3 5
 
4.7%
5 4
 
3.7%
6 3
 
2.8%
4 2
 
1.9%
Other values (6) 7
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
64.5%
Other Punctuation 19
 
17.8%
Space Separator 15
 
14.0%
Control 2
 
1.9%
Dash Punctuation 1
 
0.9%
Math Symbol 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 22
31.9%
1 18
26.1%
2 7
 
10.1%
8 6
 
8.7%
3 5
 
7.2%
5 4
 
5.8%
6 3
 
4.3%
4 2
 
2.9%
7 1
 
1.4%
9 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
< 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 22
20.6%
. 18
16.8%
1 18
16.8%
15
14.0%
2 7
 
6.5%
8 6
 
5.6%
3 5
 
4.7%
5 4
 
3.7%
6 3
 
2.8%
4 2
 
1.9%
Other values (6) 7
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 22
20.6%
. 18
16.8%
1 18
16.8%
15
14.0%
2 7
 
6.5%
8 6
 
5.6%
3 5
 
4.7%
5 4
 
3.7%
6 3
 
2.8%
4 2
 
1.9%
Other values (6) 7
 
6.5%

금성교
Text

MISSING 

Distinct16
Distinct (%)88.9%
Missing11
Missing (%)37.9%
Memory size364.0 B
2024-03-14T09:21:52.152755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length6
Min length3

Characters and Unicode

Total characters108
Distinct characters15
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)77.8%

Sample

1st row2016.01.21 13:23
2nd row2016.01.21- 01.31
3rd row1.6
4th row8.2
5th row11.7
ValueCountFrequency (%)
0.4 2
 
10.0%
2016.01.21 2
 
10.0%
0.003 2
 
10.0%
13:23 1
 
5.0%
10 1
 
5.0%
100 1
 
5.0%
0.5 1
 
5.0%
0.012 1
 
5.0%
2.253 1
 
5.0%
1.2 1
 
5.0%
Other values (7) 7
35.0%
2024-03-14T09:21:52.432525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
19.4%
. 18
16.7%
1 18
16.7%
16
14.8%
2 10
9.3%
3 6
 
5.6%
4 3
 
2.8%
6 3
 
2.8%
8 3
 
2.8%
5 3
 
2.8%
Other values (5) 7
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
64.8%
Other Punctuation 19
 
17.6%
Space Separator 16
 
14.8%
Control 2
 
1.9%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
30.0%
1 18
25.7%
2 10
14.3%
3 6
 
8.6%
4 3
 
4.3%
6 3
 
4.3%
8 3
 
4.3%
5 3
 
4.3%
7 2
 
2.9%
9 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 18
94.7%
: 1
 
5.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
19.4%
. 18
16.7%
1 18
16.7%
16
14.8%
2 10
9.3%
3 6
 
5.6%
4 3
 
2.8%
6 3
 
2.8%
8 3
 
2.8%
5 3
 
2.8%
Other values (5) 7
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
19.4%
. 18
16.7%
1 18
16.7%
16
14.8%
2 10
9.3%
3 6
 
5.6%
4 3
 
2.8%
6 3
 
2.8%
8 3
 
2.8%
5 3
 
2.8%
Other values (5) 7
 
6.5%

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing29
Missing (%)100.0%
Memory size393.0 B

Correlations

2024-03-14T09:21:52.510398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
채수지점통학교동정교천천1교오봉교섬티교구암교금성교
채수지점1.0001.0001.0001.0001.0001.0001.0001.000
통학교1.0001.0001.0001.0001.0001.0001.0001.000
동정교1.0001.0001.0001.0001.0001.0001.0001.000
천천1교1.0001.0001.0001.0001.0001.0001.0001.000
오봉교1.0001.0001.0001.0001.0001.0001.0001.000
섬티교1.0001.0001.0001.0001.0001.0001.0001.000
구암교1.0001.0001.0001.0001.0001.0001.0000.927
금성교1.0001.0001.0001.0001.0001.0000.9271.000

Missing values

2024-03-14T09:21:48.502836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:21:48.645123image/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.
2024-03-14T09:21:48.757498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

채수지점통학교동정교천천1교오봉교섬티교구암교금성교Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
0채수일시2016.01.21 10:202016.01.21 10:382016.01.21 10:462016.01.21 10:542016.01.21 11:302016.01.21 13:082016.01.21 13:23<NA><NA><NA><NA><NA><NA>
1검사기간2016.01.21- 01.312016.01.21- 01.312016.01.21- 01.312016.01.21- 01.312016.01.21- 01.312016.01.21- 01.312016.01.21- 01.31<NA><NA><NA><NA><NA><NA>
2수온(℃)1.70.80.20.80.30.51.6<NA><NA><NA><NA><NA><NA>
3pH8.58.58.26.98.28.18.2<NA><NA><NA><NA><NA><NA>
4DO(mg/L)12.112.511.910.812.211.711.7<NA><NA><NA><NA><NA><NA>
5전기전도도 (μS/cm)20834632330637514989<NA><NA><NA><NA><NA><NA>
6BOD(mg/L)0.80.90.80.90.60.30.4<NA><NA><NA><NA><NA><NA>
7COD(mg/L)2.02.22.32.31.80.81.2<NA><NA><NA><NA><NA><NA>
8NH3-N(mg/L)0.0180.2620.2150.0710.0290.0180.017<NA><NA><NA><NA><NA><NA>
9NO2-N(mg/L)0.0150.0250.0160.0110.0060.0050.003<NA><NA><NA><NA><NA><NA>
채수지점통학교동정교천천1교오봉교섬티교구암교금성교Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13
19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
25<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
26<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
27<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
28<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

채수지점통학교동정교천천1교오봉교섬티교구암교금성교# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>11