Overview

Dataset statistics

Number of variables5
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.2 KiB
Average record size in memory43.3 B

Variable types

Numeric1
Text1
Categorical3

Alerts

생성날짜 has constant value ""Constant
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:05:43.511271
Analysis finished2023-12-10 12:05:44.604871
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean882.5
Minimum833
Maximum932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:05:44.722261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum833
5-th percentile837.95
Q1857.75
median882.5
Q3907.25
95-th percentile927.05
Maximum932
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.032874212
Kurtosis-1.2
Mean882.5
Median Absolute Deviation (MAD)25
Skewness0
Sum88250
Variance841.66667
MonotonicityStrictly decreasing
2023-12-10T21:05:44.927594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
932 1
 
1.0%
868 1
 
1.0%
858 1
 
1.0%
859 1
 
1.0%
860 1
 
1.0%
861 1
 
1.0%
862 1
 
1.0%
863 1
 
1.0%
864 1
 
1.0%
865 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
833 1
1.0%
834 1
1.0%
835 1
1.0%
836 1
1.0%
837 1
1.0%
838 1
1.0%
839 1
1.0%
840 1
1.0%
841 1
1.0%
842 1
1.0%
ValueCountFrequency (%)
932 1
1.0%
931 1
1.0%
930 1
1.0%
929 1
1.0%
928 1
1.0%
927 1
1.0%
926 1
1.0%
925 1
1.0%
924 1
1.0%
923 1
1.0%

기관명
Text

Distinct58
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:05:45.319024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length12.72
Min length7

Characters and Unicode

Total characters1272
Distinct characters124
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)40.0%

Sample

1st row(사)KOTITI시험연구원
2nd row(사)KOTITI시험연구원
3rd row(사)KOTITI시험연구원
4th row(사)대한산업보건협회 광주전남북지역본부
5th row(사)대한산업보건협회 대전충남북지역본부
ValueCountFrequency (%)
재 8
 
7.0%
fiti시험연구원(오창분원 8
 
7.0%
재)한국건설생활환경시험연구원 6
 
5.2%
재)한국환경수도연구원 6
 
5.2%
주)그린환경 5
 
4.3%
재)환경보건기술연구원 4
 
3.5%
주)대명환경기술연구소 4
 
3.5%
사)대한산업보건협회 4
 
3.5%
재)서해환경과학연구소 3
 
2.6%
주)경북환경 3
 
2.6%
Other values (52) 64
55.7%
2023-12-10T21:05:45.877652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 116
 
9.1%
) 116
 
9.1%
경 71
 
5.6%
환 64
 
5.0%
구 62
 
4.9%
연 59
 
4.6%
원 55
 
4.3%
재 49
 
3.9%
주 35
 
2.8%
기 31
 
2.4%
Other values (114) 614
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 959
75.4%
Open Punctuation 116
 
9.1%
Close Punctuation 116
 
9.1%
Uppercase Letter 57
 
4.5%
Space Separator 23
 
1.8%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 71
 
7.4%
환 64
 
6.7%
구 62
 
6.5%
연 59
 
6.2%
원 55
 
5.7%
재 49
 
5.1%
주 35
 
3.6%
기 31
 
3.2%
술 25
 
2.6%
한 25
 
2.6%
Other values (102) 483
50.4%
Uppercase Letter
ValueCountFrequency (%)
I 24
42.1%
T 15
26.3%
F 9
 
15.8%
K 3
 
5.3%
O 3
 
5.3%
E 1
 
1.8%
H 1
 
1.8%
S 1
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 959
75.4%
Common 256
 
20.1%
Latin 57
 
4.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 71
 
7.4%
환 64
 
6.7%
구 62
 
6.5%
연 59
 
6.2%
원 55
 
5.7%
재 49
 
5.1%
주 35
 
3.6%
기 31
 
3.2%
술 25
 
2.6%
한 25
 
2.6%
Other values (102) 483
50.4%
Latin
ValueCountFrequency (%)
I 24
42.1%
T 15
26.3%
F 9
 
15.8%
K 3
 
5.3%
O 3
 
5.3%
E 1
 
1.8%
H 1
 
1.8%
S 1
 
1.8%
Common
ValueCountFrequency (%)
( 116
45.3%
) 116
45.3%
23
 
9.0%
_ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 959
75.4%
ASCII 313
 
24.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 116
37.1%
) 116
37.1%
I 24
 
7.7%
23
 
7.3%
T 15
 
4.8%
F 9
 
2.9%
K 3
 
1.0%
O 3
 
1.0%
E 1
 
0.3%
H 1
 
0.3%
Other values (2) 2
 
0.6%
Hangul
ValueCountFrequency (%)
경 71
 
7.4%
환 64
 
6.7%
구 62
 
6.5%
연 59
 
6.2%
원 55
 
5.7%
재 49
 
5.1%
주 35
 
3.6%
기 31
 
3.2%
술 25
 
2.6%
한 25
 
2.6%
Other values (102) 483
50.4%

분야
Categorical

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수질
22 
토양
20 
대기
14 
실내공기질
13 
먹는물
8 
Other values (6)
23 

Length

Max length12
Median length2
Mean length2.98
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row환경유해인자
2nd row수질
3rd row먹는물
4th row실내공기질
5th row실내공기질

Common Values

ValueCountFrequency (%)
수질 22
22.0%
토양 20
20.0%
대기 14
14.0%
실내공기질 13
13.0%
먹는물 8
 
8.0%
환경유해인자 6
 
6.0%
수질2 6
 
6.0%
악취 5
 
5.0%
폐기물 4
 
4.0%
폐기물(절연유PCBs) 1
 
1.0%

Length

2023-12-10T21:05:46.131437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수질 22
22.0%
토양 20
20.0%
대기 14
14.0%
실내공기질 13
13.0%
먹는물 8
 
8.0%
환경유해인자 6
 
6.0%
수질2 6
 
6.0%
악취 5
 
5.0%
폐기물 4
 
4.0%
폐기물(절연유pcbs 1
 
1.0%

유효기간
Categorical

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20.01.01~22.12.31
35 
18.01.01~20.12.31
31 
19.01.01~21.12.31
23 
18.07.10~20.12.31
5 
19.07.08~21.12.31
 
2
Other values (4)
4 

Length

Max length17
Median length17
Mean length17
Min length17

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row19.01.01~21.12.31
2nd row20.01.01~22.12.31
3rd row19.01.01~21.12.31
4th row18.01.01~20.12.31
5th row19.01.01~21.12.31

Common Values

ValueCountFrequency (%)
20.01.01~22.12.31 35
35.0%
18.01.01~20.12.31 31
31.0%
19.01.01~21.12.31 23
23.0%
18.07.10~20.12.31 5
 
5.0%
19.07.08~21.12.31 2
 
2.0%
18.10.29~20.12.31 1
 
1.0%
18.04.11~20.12.31 1
 
1.0%
19.04.22~21.12.31 1
 
1.0%
19.09.25~21.12.31 1
 
1.0%

Length

2023-12-10T21:05:46.327516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:05:46.519333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20.01.01~22.12.31 35
35.0%
18.01.01~20.12.31 31
31.0%
19.01.01~21.12.31 23
23.0%
18.07.10~20.12.31 5
 
5.0%
19.07.08~21.12.31 2
 
2.0%
18.10.29~20.12.31 1
 
1.0%
18.04.11~20.12.31 1
 
1.0%
19.04.22~21.12.31 1
 
1.0%
19.09.25~21.12.31 1
 
1.0%

생성날짜
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20191217
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20191217
2nd row20191217
3rd row20191217
4th row20191217
5th row20191217

Common Values

ValueCountFrequency (%)
20191217 100
100.0%

Length

2023-12-10T21:05:46.836190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:05:46.996493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20191217 100
100.0%

Interactions

2023-12-10T21:05:43.874341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:05:47.103400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호기관명분야유효기간
번호1.0000.9940.3720.288
기관명0.9941.0000.0000.962
분야0.3720.0001.0000.389
유효기간0.2880.9620.3891.000
2023-12-10T21:05:47.272030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유효기간분야
유효기간1.0000.182
분야0.1821.000
2023-12-10T21:05:47.411016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호분야유효기간
번호1.0000.1650.137
분야0.1651.0000.182
유효기간0.1370.1821.000

Missing values

2023-12-10T21:05:44.040466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:05:44.543259image/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

번호기관명분야유효기간생성날짜
0932(사)KOTITI시험연구원환경유해인자19.01.01~21.12.3120191217
1931(사)KOTITI시험연구원수질20.01.01~22.12.3120191217
2930(사)KOTITI시험연구원먹는물19.01.01~21.12.3120191217
3929(사)대한산업보건협회 광주전남북지역본부실내공기질18.01.01~20.12.3120191217
4928(사)대한산업보건협회 대전충남북지역본부실내공기질19.01.01~21.12.3120191217
5927(사)대한산업보건협회 서울지역본부실내공기질20.01.01~22.12.3120191217
6926(사)대한산업보건협회 전북산업보건센터실내공기질19.01.01~21.12.3120191217
7925(사)대한산업안전협회환경유해인자19.01.01~21.12.3120191217
8924(사)대한산업안전협회실내공기질18.10.29~20.12.3120191217
9923(유)대명환경법인대기20.01.01~22.12.3120191217
번호기관명분야유효기간생성날짜
90842(주)녹색엔지니어링수질20.01.01~22.12.3120191217
91841(주)녹색엔지니어링대기20.01.01~22.12.3120191217
92840(주)누리환경기술센터실내공기질19.01.01~21.12.3120191217
93839(주)다솔물환경연구소먹는물18.07.10~20.12.3120191217
94838(주)단엔지니어링(기술진단전문기관)수질219.01.01~21.12.3120191217
95837(주)대명환경기술연구소수질18.01.01~20.12.3120191217
96836(주)대명환경기술연구소대기20.01.01~22.12.3120191217
97835(주)대명환경기술연구소악취20.01.01~22.12.3120191217
98834(주)대명환경기술연구소실내공기질20.01.01~22.12.3120191217
99833(주)대성기술단수질20.01.01~22.12.3120191217