Overview

Dataset statistics

Number of variables8
Number of observations22
Missing cells20
Missing cells (%)11.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory70.0 B

Variable types

Text1
Unsupported7

Dataset

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

Alerts

Unnamed: 1 has 2 (9.1%) missing valuesMissing
Unnamed: 2 has 3 (13.6%) missing valuesMissing
Unnamed: 3 has 3 (13.6%) missing valuesMissing
Unnamed: 4 has 3 (13.6%) missing valuesMissing
Unnamed: 5 has 3 (13.6%) missing valuesMissing
Unnamed: 6 has 3 (13.6%) missing valuesMissing
Unnamed: 7 has 3 (13.6%) missing valuesMissing
2016년 1월 has unique valuesUnique
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:21:53.498273
Analysis finished2024-03-14 00:21:53.878793
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2016년 1월
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-03-14T09:21:53.996687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length16
Mean length10.590909
Min length2

Characters and Unicode

Total characters233
Distinct characters70
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row용담호 유입하천 수질조사결과
2nd row□ 조사지점 : 용담호 유입하천
3rd row□ 시험항목 ○ 매월 :
4th row채수지점
5th row채수일시
ValueCountFrequency (%)
용담호 2
 
5.7%
유입하천 2
 
5.7%
□ 2
 
5.7%
2
 
5.7%
po4-p(mg/l 1
 
2.9%
nh3-n(mg/l 1
 
2.9%
no2-n(mg/l 1
 
2.9%
no3-n(mg/l 1
 
2.9%
t-n(mg/l 1
 
2.9%
chl-a(mg/m3 1
 
2.9%
Other values (21) 21
60.0%
2024-03-14T09:21:54.301162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 15
 
6.4%
) 15
 
6.4%
m 15
 
6.4%
/ 14
 
6.0%
13
 
5.6%
L 12
 
5.2%
g 11
 
4.7%
N 7
 
3.0%
- 7
 
3.0%
수 6
 
2.6%
Other values (60) 118
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75
32.2%
Uppercase Letter 41
17.6%
Lowercase Letter 32
13.7%
Other Punctuation 16
 
6.9%
Open Punctuation 15
 
6.4%
Close Punctuation 15
 
6.4%
Space Separator 13
 
5.6%
Decimal Number 11
 
4.7%
Dash Punctuation 7
 
3.0%
Control 4
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 6
 
8.0%
균 4
 
5.3%
장 4
 
5.3%
군 4
 
5.3%
대 4
 
5.3%
사 3
 
4.0%
분 2
 
2.7%
담 2
 
2.7%
원 2
 
2.7%
도 2
 
2.7%
Other values (27) 42
56.0%
Uppercase Letter
ValueCountFrequency (%)
L 12
29.3%
N 7
17.1%
O 6
14.6%
P 3
 
7.3%
D 3
 
7.3%
S 3
 
7.3%
H 2
 
4.9%
C 2
 
4.9%
T 2
 
4.9%
B 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
m 15
46.9%
g 11
34.4%
a 1
 
3.1%
l 1
 
3.1%
h 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%
Other Symbol
ValueCountFrequency (%)
□ 2
50.0%
℃ 1
25.0%
○ 1
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 14
87.5%
: 2
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
36.5%
Hangul 75
32.2%
Latin 72
30.9%
Greek 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 6
 
8.0%
균 4
 
5.3%
장 4
 
5.3%
군 4
 
5.3%
대 4
 
5.3%
사 3
 
4.0%
분 2
 
2.7%
담 2
 
2.7%
원 2
 
2.7%
도 2
 
2.7%
Other values (27) 42
56.0%
Latin
ValueCountFrequency (%)
m 15
20.8%
L 12
16.7%
g 11
15.3%
N 7
9.7%
O 6
 
8.3%
P 3
 
4.2%
D 3
 
4.2%
S 3
 
4.2%
H 2
 
2.8%
C 2
 
2.8%
Other values (7) 8
11.1%
Common
ValueCountFrequency (%)
( 15
17.6%
) 15
17.6%
/ 14
16.5%
13
15.3%
- 7
8.2%
4
 
4.7%
0 4
 
4.7%
3 3
 
3.5%
1 2
 
2.4%
: 2
 
2.4%
Other values (5) 6
 
7.1%
Greek
ValueCountFrequency (%)
μ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153
65.7%
Hangul 75
32.2%
Geometric Shapes 3
 
1.3%
Letterlike Symbols 1
 
0.4%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 15
 
9.8%
) 15
 
9.8%
m 15
 
9.8%
/ 14
 
9.2%
13
 
8.5%
L 12
 
7.8%
g 11
 
7.2%
N 7
 
4.6%
- 7
 
4.6%
O 6
 
3.9%
Other values (19) 38
24.8%
Hangul
ValueCountFrequency (%)
수 6
 
8.0%
균 4
 
5.3%
장 4
 
5.3%
군 4
 
5.3%
대 4
 
5.3%
사 3
 
4.0%
분 2
 
2.7%
담 2
 
2.7%
원 2
 
2.7%
도 2
 
2.7%
Other values (27) 42
56.0%
Geometric Shapes
ValueCountFrequency (%)
□ 2
66.7%
○ 1
33.3%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
None
ValueCountFrequency (%)
μ 1
100.0%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Missing values

2024-03-14T09:21:53.592532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:21:53.693897image/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.
2024-03-14T09:21:53.805398image/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

2016년 1월Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0용담호 유입하천 수질조사결과NaNNaNNaNNaNNaNNaNNaN
1□ 조사지점 : 용담호 유입하천NaNNaNNaNNaNNaNNaNNaN
2□ 시험항목 ○ 매월 :\n수온, pH, DO, 전기전도도, BOD, COD, SS, T-N, T-P, 분원성대장균군수, 총대장균군수, NO2-N, NO3-N, NH3-N, PO4-P, 클로로필-aNaNNaNNaNNaNNaNNaN
3채수지점통학교동정교천천1교오봉교섬티교구암교금성교
4채수일시2016.01.21\n10:202016.01.21\n10:382016.01.21\n10:462016.01.21\n10:542016.01.21\n11:302016.01.21\n13:082016.01.21\n13:23
5검사기간2016.01.21-\n01.312016.01.21-\n01.312016.01.21-\n01.312016.01.21-\n01.312016.01.21-\n01.312016.01.21-\n01.312016.01.21-\n01.31
6수온(℃)1.70.80.20.80.30.51.6
7pH8.58.58.26.98.28.18.2
8DO(mg/L)12.112.511.910.812.211.711.7
9전기전도도 (μS/cm)20834632330637514989
2016년 1월Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
12NH3-N(mg/L)0.0180.2620.2150.0710.0290.0180.017
13NO2-N(mg/L)0.0150.0250.0160.0110.0060.0050.003
14NO3-N(mg/L)4.093.9654.1365.6732.8252.411.845
15T-N(mg/L)5.295.2285.4946.8583.5513.2862.253
16PO4-P(mg/L)0.0080.0030.0070.0040.0030.0030.003
17T-P(mg/L)0.0360.0260.0280.0240.0150.0120.012
18Chl-a(mg/m3)0.50.51.51.211.80.4
19SS(mg/L)1.81.41.70.60.90.50.5
20총대장균군 (총대장균군수/100mL)36537077510010050100
21분원성대장균군 (분원성대장균군수/100mL)28130703<120<110