Overview

Dataset statistics

Number of variables4
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory35.3 B

Variable types

Numeric1
Text1
Categorical2

Alerts

생성날짜 has constant value ""Constant
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:36:49.443166
Analysis finished2023-12-10 12:36:50.196460
Duration0.75 seconds
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%
Mean1162.47
Minimum1112
Maximum1212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:50.628135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1112
5-th percentile1117.95
Q11137.75
median1162.5
Q31187.25
95-th percentile1207.05
Maximum1212
Range100
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.062613
Coefficient of variation (CV)0.025000742
Kurtosis-1.1920587
Mean1162.47
Median Absolute Deviation (MAD)25
Skewness-0.0059162588
Sum116247
Variance844.63545
MonotonicityNot monotonic
2023-12-10T21:36:50.851816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1212 1
 
1.0%
1147 1
 
1.0%
1137 1
 
1.0%
1138 1
 
1.0%
1139 1
 
1.0%
1141 1
 
1.0%
1142 1
 
1.0%
1143 1
 
1.0%
1144 1
 
1.0%
1150 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1112 1
1.0%
1113 1
1.0%
1114 1
1.0%
1116 1
1.0%
1117 1
1.0%
1118 1
1.0%
1119 1
1.0%
1120 1
1.0%
1121 1
1.0%
1122 1
1.0%
ValueCountFrequency (%)
1212 1
1.0%
1211 1
1.0%
1210 1
1.0%
1209 1
1.0%
1208 1
1.0%
1207 1
1.0%
1206 1
1.0%
1205 1
1.0%
1204 1
1.0%
1203 1
1.0%

기관명
Text

Distinct51
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T21:36:51.277506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length12.38
Min length7

Characters and Unicode

Total characters1238
Distinct characters115
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

Unique28 ?
Unique (%)28.0%

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)한국화학융합시험연구원 10
 
8.5%
재 9
 
7.6%
fiti시험연구원(오창분원 9
 
7.6%
재)한국환경수도연구원 6
 
5.1%
주)그린환경 5
 
4.2%
재)한국건설생활환경시험연구원 5
 
4.2%
사)대한산업보건협회 4
 
3.4%
재)환경보건기술연구원 4
 
3.4%
사)kotiti시험연구원 3
 
2.5%
주)경북환경 3
 
2.5%
Other values (44) 60
50.8%
2023-12-10T21:36:51.931488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 110
 
8.9%
) 110
 
8.9%
경 70
 
5.7%
구 65
 
5.3%
원 63
 
5.1%
연 62
 
5.0%
환 61
 
4.9%
재 59
 
4.8%
한 33
 
2.7%
국 30
 
2.4%
Other values (105) 575
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 942
76.1%
Open Punctuation 110
 
8.9%
Close Punctuation 110
 
8.9%
Uppercase Letter 57
 
4.6%
Space Separator 18
 
1.5%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 70
 
7.4%
구 65
 
6.9%
원 63
 
6.7%
연 62
 
6.6%
환 61
 
6.5%
재 59
 
6.3%
한 33
 
3.5%
국 30
 
3.2%
시 28
 
3.0%
험 28
 
3.0%
Other values (93) 443
47.0%
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 (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 942
76.1%
Common 239
 
19.3%
Latin 57
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 70
 
7.4%
구 65
 
6.9%
원 63
 
6.7%
연 62
 
6.6%
환 61
 
6.5%
재 59
 
6.3%
한 33
 
3.5%
국 30
 
3.2%
시 28
 
3.0%
험 28
 
3.0%
Other values (93) 443
47.0%
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 (%)
( 110
46.0%
) 110
46.0%
18
 
7.5%
_ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 942
76.1%
ASCII 296
 
23.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 110
37.2%
) 110
37.2%
I 24
 
8.1%
18
 
6.1%
T 15
 
5.1%
F 9
 
3.0%
K 3
 
1.0%
O 3
 
1.0%
E 1
 
0.3%
H 1
 
0.3%
Other values (2) 2
 
0.7%
Hangul
ValueCountFrequency (%)
경 70
 
7.4%
구 65
 
6.9%
원 63
 
6.7%
연 62
 
6.6%
환 61
 
6.5%
재 59
 
6.3%
한 33
 
3.5%
국 30
 
3.2%
시 28
 
3.0%
험 28
 
3.0%
Other values (93) 443
47.0%

분야
Categorical

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수질
24 
토양
24 
대기
13 
실내공기질
9 
환경유해인자
6 
Other values (9)
24 

Length

Max length12
Median length2
Mean length3.06
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
수질 24
24.0%
토양 24
24.0%
대기 13
13.0%
실내공기질 9
 
9.0%
환경유해인자 6
 
6.0%
먹는물 6
 
6.0%
폐기물 5
 
5.0%
악취 4
 
4.0%
복합악취 2
 
2.0%
폐기물(절연유PCBs) 2
 
2.0%
Other values (4) 5
 
5.0%

Length

2023-12-10T21:36:52.162132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수질 24
24.0%
토양 24
24.0%
대기 13
13.0%
실내공기질 9
 
9.0%
환경유해인자 6
 
6.0%
먹는물 6
 
6.0%
폐기물 5
 
5.0%
악취 4
 
4.0%
복합악취 2
 
2.0%
폐기물(절연유pcbs 2
 
2.0%
Other values (4) 5
 
5.0%

생성날짜
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
201912
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201912
2nd row201912
3rd row201912
4th row201912
5th row201912

Common Values

ValueCountFrequency (%)
201912 100
100.0%

Length

2023-12-10T21:36:52.362066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:52.510893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201912 100
100.0%

Interactions

2023-12-10T21:36:49.717266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:36:52.601292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호기관명분야
번호1.0000.9890.398
기관명0.9891.0000.000
분야0.3980.0001.000
2023-12-10T21:36:52.752034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호분야
번호1.0000.151
분야0.1511.000

Missing values

2023-12-10T21:36:50.008813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:36:50.147831image/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

번호기관명분야생성날짜
01212(사)KOTITI시험연구원환경유해인자201912
11210(사)KOTITI시험연구원수질201912
21211(사)KOTITI시험연구원먹는물201912
31209(사)대한산업보건협회 광주전남북지역본부실내공기질201912
41208(사)대한산업보건협회 대전충남북지역본부실내공기질201912
51207(사)대한산업보건협회 서울지역본부실내공기질201912
61206(사)대한산업보건협회 전북산업보건센터실내공기질201912
71205(사)대한산업안전협회환경유해인자201912
81204(유)대명환경법인대기201912
91202(유)대신환경개발수질2201912
번호기관명분야생성날짜
901123(주)국토엔지니어링토양201912
911121(주)국토해양환경기술단수질201912
921119(주)그린비즈토양누출검사201912
931120(주)그린비즈토양(누출)201912
941118(주)그린이엔지수질201912
951117(주)그린환경대기201912
961116(주)그린환경악취201912
971114(주)그린환경토양201912
981113(주)그린환경수질201912
991112(주)그린환경실내공기질201912