Overview

Dataset statistics

Number of variables11
Number of observations207
Missing cells321
Missing cells (%)14.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.7 KiB
Average record size in memory92.6 B

Variable types

Numeric3
Categorical3
Text3
Boolean2

Dataset

Description인천광역시 보건환경연구원 대기환경정보시스템 대기, 산성우, 중금속, 오존, 해양, 하천 등의 측정항목에 대한 데이터 목록입니다.
URLhttps://www.data.go.kr/data/15117396/fileData.do

Alerts

측정주기 is highly overall correlated with 측정값 유효자리수 and 4 other fieldsHigh correlation
사용구분 is highly overall correlated with 측정값 유효자리수 and 3 other fieldsHigh correlation
프로그램 코드 is highly overall correlated with 측정값 유효자리수 and 3 other fieldsHigh correlation
나미스 전송여부 is highly overall correlated with 측정항목 코드 and 5 other fieldsHigh correlation
측정항목 코드 is highly overall correlated with 측정값 유효자리수 and 3 other fieldsHigh correlation
측정값 유효자리수 is highly overall correlated with 측정항목 코드 and 5 other fieldsHigh correlation
나미스 코드 is highly overall correlated with 측정항목 코드 and 3 other fieldsHigh correlation
단위 is highly overall correlated with 측정항목 코드 and 6 other fieldsHigh correlation
사용구분 is highly imbalanced (72.1%)Imbalance
관리항목명 has 6 (2.9%) missing valuesMissing
통신기호 has 3 (1.4%) missing valuesMissing
나미스 코드 has 188 (90.8%) missing valuesMissing
나미스 전송여부 has 124 (59.9%) missing valuesMissing
측정값 유효자리수 has 23 (11.1%) zerosZeros

Reproduction

Analysis started2023-12-12 12:10:42.471996
Analysis finished2023-12-12 12:10:44.445616
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

측정항목 코드
Real number (ℝ)

HIGH CORRELATION 

Distinct152
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20688.947
Minimum1
Maximum79151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T21:10:44.511419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q126
median1004
Q371626
95-th percentile78138
Maximum79151
Range79150
Interquartile range (IQR)71600

Descriptive statistics

Standard deviation33451.007
Coefficient of variation (CV)1.616854
Kurtosis-0.90920928
Mean20688.947
Median Absolute Deviation (MAD)980
Skewness1.044902
Sum4282612
Variance1.1189699 × 109
MonotonicityNot monotonic
2023-12-12T21:10:44.645258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4
 
1.9%
2 3
 
1.4%
3 3
 
1.4%
4 3
 
1.4%
5 3
 
1.4%
6 3
 
1.4%
7 3
 
1.4%
16 3
 
1.4%
1012 2
 
1.0%
1011 2
 
1.0%
Other values (142) 178
86.0%
ValueCountFrequency (%)
1 4
1.9%
2 3
1.4%
3 3
1.4%
4 3
1.4%
5 3
1.4%
6 3
1.4%
7 3
1.4%
8 2
1.0%
9 2
1.0%
10 2
1.0%
ValueCountFrequency (%)
79151 1
0.5%
79141 1
0.5%
79131 1
0.5%
79121 1
0.5%
79111 1
0.5%
78191 1
0.5%
78181 1
0.5%
78171 1
0.5%
78161 1
0.5%
78151 1
0.5%

프로그램 코드
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
TMSV
85 
TMSA
34 
TMSH
33 
TMSO
20 
TMSI
18 
Other values (4)
17 

Length

Max length5
Median length4
Mean length4.0241546
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
TMSV 85
41.1%
TMSA 34
 
16.4%
TMSH 33
 
15.9%
TMSO 20
 
9.7%
TMSI 18
 
8.7%
TMSAR 5
 
2.4%
TMSR 5
 
2.4%
TMSS 4
 
1.9%
TMSG 3
 
1.4%

Length

2023-12-12T21:10:44.759932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:10:44.868956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
tmsv 85
41.1%
tmsa 34
 
16.4%
tmsh 33
 
15.9%
tmso 20
 
9.7%
tmsi 18
 
8.7%
tmsar 5
 
2.4%
tmsr 5
 
2.4%
tmss 4
 
1.9%
tmsg 3
 
1.4%

측정항목명
Text

Distinct159
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T21:10:45.206251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.9130435
Min length1

Characters and Unicode

Total characters810
Distinct characters111
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)57.0%

Sample

1st rowO3
2nd rowNO2
3rd rowNO
4th rowNOX
5th rowSO2
ValueCountFrequency (%)
co 4
 
1.9%
temp 4
 
1.9%
pb 3
 
1.4%
풍속 3
 
1.4%
h2s 3
 
1.4%
ec 3
 
1.4%
cod 3
 
1.4%
k 3
 
1.4%
ca 3
 
1.4%
do 2
 
0.9%
Other values (150) 181
85.4%
2023-12-12T21:10:45.820721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 47
 
5.8%
C 37
 
4.6%
O 31
 
3.8%
2 25
 
3.1%
N 24
 
3.0%
T 23
 
2.8%
D 21
 
2.6%
n 21
 
2.6%
M 20
 
2.5%
S 19
 
2.3%
Other values (101) 542
66.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 293
36.2%
Other Letter 223
27.5%
Lowercase Letter 177
21.9%
Decimal Number 55
 
6.8%
Dash Punctuation 47
 
5.8%
Other Number 7
 
0.9%
Space Separator 5
 
0.6%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탄 19
 
8.5%
펜 13
 
5.8%
도 13
 
5.8%
벤 9
 
4.0%
틸 9
 
4.0%
강 9
 
4.0%
우 9
 
4.0%
젠 9
 
4.0%
산 8
 
3.6%
부 7
 
3.1%
Other values (46) 118
52.9%
Uppercase Letter
ValueCountFrequency (%)
C 37
12.6%
O 31
10.6%
N 24
 
8.2%
T 23
 
7.8%
D 21
 
7.2%
M 20
 
6.8%
S 19
 
6.5%
H 18
 
6.1%
E 15
 
5.1%
P 13
 
4.4%
Other values (14) 72
24.6%
Lowercase Letter
ValueCountFrequency (%)
n 21
11.9%
i 19
10.7%
e 18
10.2%
a 15
 
8.5%
p 13
 
7.3%
m 10
 
5.6%
l 10
 
5.6%
d 10
 
5.6%
t 10
 
5.6%
b 8
 
4.5%
Other values (9) 43
24.3%
Decimal Number
ValueCountFrequency (%)
2 25
45.5%
3 11
20.0%
1 8
 
14.5%
4 7
 
12.7%
0 2
 
3.6%
5 2
 
3.6%
Other Number
ValueCountFrequency (%)
₃ 3
42.9%
₄ 2
28.6%
₂ 2
28.6%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
* 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 470
58.0%
Hangul 223
27.5%
Common 117
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탄 19
 
8.5%
펜 13
 
5.8%
도 13
 
5.8%
벤 9
 
4.0%
틸 9
 
4.0%
강 9
 
4.0%
우 9
 
4.0%
젠 9
 
4.0%
산 8
 
3.6%
부 7
 
3.1%
Other values (46) 118
52.9%
Latin
ValueCountFrequency (%)
C 37
 
7.9%
O 31
 
6.6%
N 24
 
5.1%
T 23
 
4.9%
D 21
 
4.5%
n 21
 
4.5%
M 20
 
4.3%
S 19
 
4.0%
i 19
 
4.0%
H 18
 
3.8%
Other values (33) 237
50.4%
Common
ValueCountFrequency (%)
- 47
40.2%
2 25
21.4%
3 11
 
9.4%
1 8
 
6.8%
4 7
 
6.0%
5
 
4.3%
* 3
 
2.6%
₃ 3
 
2.6%
₄ 2
 
1.7%
0 2
 
1.7%
Other values (2) 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 580
71.6%
Hangul 223
 
27.5%
None 7
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 47
 
8.1%
C 37
 
6.4%
O 31
 
5.3%
2 25
 
4.3%
N 24
 
4.1%
T 23
 
4.0%
D 21
 
3.6%
n 21
 
3.6%
M 20
 
3.4%
S 19
 
3.3%
Other values (42) 312
53.8%
Hangul
ValueCountFrequency (%)
탄 19
 
8.5%
펜 13
 
5.8%
도 13
 
5.8%
벤 9
 
4.0%
틸 9
 
4.0%
강 9
 
4.0%
우 9
 
4.0%
젠 9
 
4.0%
산 8
 
3.6%
부 7
 
3.1%
Other values (46) 118
52.9%
None
ValueCountFrequency (%)
₃ 3
42.9%
₄ 2
28.6%
₂ 2
28.6%

관리항목명
Text

MISSING 

Distinct155
Distinct (%)77.1%
Missing6
Missing (%)2.9%
Memory size1.7 KiB
2023-12-12T21:10:46.209112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length6.119403
Min length1

Characters and Unicode

Total characters1230
Distinct characters146
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)58.7%

Sample

1st rowO3
2nd rowNO2
3rd rowNO
4th rowNOX
5th rowSO2
ValueCountFrequency (%)
풍속 4
 
2.0%
전기전도도 4
 
2.0%
풍향 3
 
1.5%
납 3
 
1.5%
황화수소 3
 
1.5%
암모니아 3
 
1.5%
화학적산소요구량 3
 
1.5%
알루미늄 2
 
1.0%
팔라듐 2
 
1.0%
바나듐 2
 
1.0%
Other values (148) 176
85.9%
2023-12-12T21:10:46.744483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 148
 
12.0%
n 94
 
7.6%
t 64
 
5.2%
- 45
 
3.7%
a 37
 
3.0%
l 35
 
2.8%
h 34
 
2.8%
y 34
 
2.8%
p 31
 
2.5%
m 24
 
2.0%
Other values (136) 684
55.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 641
52.1%
Other Letter 339
27.6%
Uppercase Letter 134
 
10.9%
Decimal Number 51
 
4.1%
Dash Punctuation 45
 
3.7%
Other Punctuation 16
 
1.3%
Space Separator 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 22
 
6.5%
도 18
 
5.3%
온 15
 
4.4%
산 13
 
3.8%
이 13
 
3.8%
수 11
 
3.2%
우 9
 
2.7%
강 9
 
2.7%
전 8
 
2.4%
륨 8
 
2.4%
Other values (84) 213
62.8%
Lowercase Letter
ValueCountFrequency (%)
e 148
23.1%
n 94
14.7%
t 64
10.0%
a 37
 
5.8%
l 35
 
5.5%
h 34
 
5.3%
y 34
 
5.3%
p 31
 
4.8%
m 24
 
3.7%
o 23
 
3.6%
Other values (11) 117
18.3%
Uppercase Letter
ValueCountFrequency (%)
O 20
14.9%
C 13
 
9.7%
T 13
 
9.7%
I 11
 
8.2%
N 10
 
7.5%
D 8
 
6.0%
E 7
 
5.2%
H 5
 
3.7%
S 5
 
3.7%
L 5
 
3.7%
Other values (11) 37
27.6%
Decimal Number
ValueCountFrequency (%)
2 23
45.1%
3 9
 
17.6%
1 8
 
15.7%
4 7
 
13.7%
0 2
 
3.9%
5 2
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 15
93.8%
* 1
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 775
63.0%
Hangul 339
27.6%
Common 116
 
9.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 22
 
6.5%
도 18
 
5.3%
온 15
 
4.4%
산 13
 
3.8%
이 13
 
3.8%
수 11
 
3.2%
우 9
 
2.7%
강 9
 
2.7%
전 8
 
2.4%
륨 8
 
2.4%
Other values (84) 213
62.8%
Latin
ValueCountFrequency (%)
e 148
19.1%
n 94
 
12.1%
t 64
 
8.3%
a 37
 
4.8%
l 35
 
4.5%
h 34
 
4.4%
y 34
 
4.4%
p 31
 
4.0%
m 24
 
3.1%
o 23
 
3.0%
Other values (32) 251
32.4%
Common
ValueCountFrequency (%)
- 45
38.8%
2 23
19.8%
, 15
 
12.9%
3 9
 
7.8%
1 8
 
6.9%
4 7
 
6.0%
4
 
3.4%
0 2
 
1.7%
5 2
 
1.7%
* 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 891
72.4%
Hangul 339
 
27.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 148
16.6%
n 94
 
10.5%
t 64
 
7.2%
- 45
 
5.1%
a 37
 
4.2%
l 35
 
3.9%
h 34
 
3.8%
y 34
 
3.8%
p 31
 
3.5%
m 24
 
2.7%
Other values (42) 345
38.7%
Hangul
ValueCountFrequency (%)
소 22
 
6.5%
도 18
 
5.3%
온 15
 
4.4%
산 13
 
3.8%
이 13
 
3.8%
수 11
 
3.2%
우 9
 
2.7%
강 9
 
2.7%
전 8
 
2.4%
륨 8
 
2.4%
Other values (84) 213
62.8%

통신기호
Text

MISSING 

Distinct165
Distinct (%)80.9%
Missing3
Missing (%)1.4%
Memory size1.7 KiB
2023-12-12T21:10:47.122793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length4
Mean length3.877451
Min length2

Characters and Unicode

Total characters791
Distinct characters41
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)64.7%

Sample

1st rowO3b
2nd rowNO2
3rd rowNOb
4th rowNOX
5th rowSO2
ValueCountFrequency (%)
tmp 5
 
2.5%
kbbb 3
 
1.5%
phb 3
 
1.5%
cabb 3
 
1.5%
h2s 3
 
1.5%
nibb 2
 
1.0%
cdbb 2
 
1.0%
crbb 2
 
1.0%
cubb 2
 
1.0%
febb 2
 
1.0%
Other values (152) 177
86.8%
2023-12-12T21:10:47.971881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
b 214
27.1%
V 61
 
7.7%
O 35
 
4.4%
C 34
 
4.3%
N 32
 
4.0%
S 30
 
3.8%
2 24
 
3.0%
P 22
 
2.8%
3 22
 
2.8%
H 22
 
2.8%
Other values (31) 295
37.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 434
54.9%
Lowercase Letter 214
27.1%
Decimal Number 129
 
16.3%
Other Punctuation 5
 
0.6%
Space Separator 4
 
0.5%
Other Letter 4
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
V 61
14.1%
O 35
 
8.1%
C 34
 
7.8%
N 32
 
7.4%
S 30
 
6.9%
P 22
 
5.1%
H 22
 
5.1%
T 21
 
4.8%
D 21
 
4.8%
A 21
 
4.8%
Other values (14) 135
31.1%
Decimal Number
ValueCountFrequency (%)
2 24
18.6%
3 22
17.1%
4 19
14.7%
1 16
12.4%
0 14
10.9%
5 13
10.1%
6 6
 
4.7%
7 5
 
3.9%
9 5
 
3.9%
8 5
 
3.9%
Other Letter
ValueCountFrequency (%)
수 2
50.0%
심 1
25.0%
위 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
b 214
100.0%
Other Punctuation
ValueCountFrequency (%)
* 5
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 648
81.9%
Common 139
 
17.6%
Hangul 4
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
b 214
33.0%
V 61
 
9.4%
O 35
 
5.4%
C 34
 
5.2%
N 32
 
4.9%
S 30
 
4.6%
P 22
 
3.4%
H 22
 
3.4%
T 21
 
3.2%
D 21
 
3.2%
Other values (15) 156
24.1%
Common
ValueCountFrequency (%)
2 24
17.3%
3 22
15.8%
4 19
13.7%
1 16
11.5%
0 14
10.1%
5 13
9.4%
6 6
 
4.3%
7 5
 
3.6%
* 5
 
3.6%
9 5
 
3.6%
Other values (3) 10
7.2%
Hangul
ValueCountFrequency (%)
수 2
50.0%
심 1
25.0%
위 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 787
99.5%
Hangul 4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
b 214
27.2%
V 61
 
7.8%
O 35
 
4.4%
C 34
 
4.3%
N 32
 
4.1%
S 30
 
3.8%
2 24
 
3.0%
P 22
 
2.8%
3 22
 
2.8%
H 22
 
2.8%
Other values (28) 291
37.0%
Hangul
ValueCountFrequency (%)
수 2
50.0%
심 1
25.0%
위 1
25.0%

단위
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
ppb
60 
ng/㎥
47 
ug/m3
24 
ppm
15 
<NA>
11 
Other values (25)
50 

Length

Max length5
Median length4
Mean length3.4975845
Min length1

Unique

Unique13 ?
Unique (%)6.3%

Sample

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

Common Values

ValueCountFrequency (%)
ppb 60
29.0%
ng/㎥ 47
22.7%
ug/m3 24
 
11.6%
ppm 15
 
7.2%
<NA> 11
 
5.3%
℃ 7
 
3.4%
mg/L 6
 
2.9%
deg 4
 
1.9%
m/s 4
 
1.9%
uS/cm 2
 
1.0%
Other values (20) 27
13.0%

Length

2023-12-12T21:10:48.165562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ppb 60
29.0%
ng/㎥ 47
22.7%
ug/m3 24
 
11.6%
ppm 15
 
7.2%
na 11
 
5.3%
℃ 7
 
3.4%
mg/l 6
 
2.9%
deg 4
 
1.9%
m/s 4
 
1.9%
3
 
1.4%
Other values (19) 26
12.6%

측정주기
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
60
129 
5
61 
<NA>
14 
1
 
3

Length

Max length4
Median length2
Mean length1.826087
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
60 129
62.3%
5 61
29.5%
<NA> 14
 
6.8%
1 3
 
1.4%

Length

2023-12-12T21:10:48.301022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:10:48.406452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
60 129
62.3%
5 61
29.5%
na 14
 
6.8%
1 3
 
1.4%

사용구분
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size339.0 B
True
197 
False
 
10
ValueCountFrequency (%)
True 197
95.2%
False 10
 
4.8%
2023-12-12T21:10:48.499121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

측정값 유효자리수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.057971
Minimum0
Maximum5
Zeros23
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T21:10:48.584291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5411891
Coefficient of variation (CV)0.50399075
Kurtosis-0.54436436
Mean3.057971
Median Absolute Deviation (MAD)1
Skewness-0.7727877
Sum633
Variance2.3752638
MonotonicityNot monotonic
2023-12-12T21:10:48.696761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4 82
39.6%
3 39
18.8%
5 27
 
13.0%
0 23
 
11.1%
1 19
 
9.2%
2 17
 
8.2%
ValueCountFrequency (%)
0 23
 
11.1%
1 19
 
9.2%
2 17
 
8.2%
3 39
18.8%
4 82
39.6%
5 27
 
13.0%
ValueCountFrequency (%)
5 27
 
13.0%
4 82
39.6%
3 39
18.8%
2 17
 
8.2%
1 19
 
9.2%
0 23
 
11.1%

나미스 코드
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)89.5%
Missing188
Missing (%)90.8%
Infinite0
Infinite (%)0.0%
Mean13215.737
Minimum10001
Maximum20008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T21:10:48.812424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10001
5-th percentile10001.9
Q110004.5
median10009
Q320001.5
95-th percentile20006.2
Maximum20008
Range10007
Interquartile range (IQR)9997

Descriptive statistics

Standard deviation4743.5241
Coefficient of variation (CV)0.35892998
Kurtosis-1.4214347
Mean13215.737
Median Absolute Deviation (MAD)7
Skewness0.85463867
Sum251099
Variance22501021
MonotonicityNot monotonic
2023-12-12T21:10:48.937421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
10002 2
 
1.0%
10007 2
 
1.0%
20002 1
 
0.5%
20008 1
 
0.5%
20004 1
 
0.5%
10009 1
 
0.5%
10010 1
 
0.5%
10011 1
 
0.5%
20006 1
 
0.5%
10003 1
 
0.5%
Other values (7) 7
 
3.4%
(Missing) 188
90.8%
ValueCountFrequency (%)
10001 1
0.5%
10002 2
1.0%
10003 1
0.5%
10004 1
0.5%
10005 1
0.5%
10006 1
0.5%
10007 2
1.0%
10009 1
0.5%
10010 1
0.5%
10011 1
0.5%
ValueCountFrequency (%)
20008 1
0.5%
20006 1
0.5%
20004 1
0.5%
20003 1
0.5%
20002 1
0.5%
20001 1
0.5%
11008 1
0.5%
10011 1
0.5%
10010 1
0.5%
10009 1
0.5%

나미스 전송여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)2.4%
Missing124
Missing (%)59.9%
Memory size546.0 B
False
57 
True
26 
(Missing)
124 
ValueCountFrequency (%)
False 57
27.5%
True 26
 
12.6%
(Missing) 124
59.9%
2023-12-12T21:10:49.045639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Interactions

2023-12-12T21:10:43.760785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.154307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.450222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.856981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.257154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.565590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.971828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.366476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:10:43.663545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:10:49.129006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정항목 코드프로그램 코드단위측정주기사용구분측정값 유효자리수나미스 코드나미스 전송여부
측정항목 코드1.0000.7810.8040.6400.0580.828NaNNaN
프로그램 코드0.7811.0000.8860.9980.4510.8450.0000.984
단위0.8040.8861.0000.8630.8360.8980.7360.935
측정주기0.6400.9980.8631.0000.0940.832NaN0.992
사용구분0.0580.4510.8360.0941.0000.744NaNNaN
측정값 유효자리수0.8280.8450.8980.8320.7441.0000.2530.841
나미스 코드NaN0.0000.736NaNNaN0.2531.0000.052
나미스 전송여부NaN0.9840.9350.992NaN0.8410.0521.000
2023-12-12T21:10:49.257056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정주기단위사용구분프로그램 코드나미스 전송여부
측정주기1.0000.6470.1550.9320.918
단위0.6471.0000.6970.5610.847
사용구분0.1550.6971.0000.4431.000
프로그램 코드0.9320.5610.4431.0000.863
나미스 전송여부0.9180.8471.0000.8631.000
2023-12-12T21:10:49.349514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정항목 코드측정값 유효자리수나미스 코드프로그램 코드단위측정주기사용구분나미스 전송여부
측정항목 코드1.0000.6170.7940.4790.5590.3030.0961.000
측정값 유효자리수0.6171.000-0.4860.6110.6260.5150.5470.630
나미스 코드0.794-0.4861.0000.0000.5691.0001.0000.099
프로그램 코드0.4790.6110.0001.0000.5610.9320.4430.863
단위0.5590.6260.5690.5611.0000.6470.6970.847
측정주기0.3030.5151.0000.9320.6471.0000.1550.918
사용구분0.0960.5471.0000.4430.6970.1551.0001.000
나미스 전송여부1.0000.6300.0990.8630.8470.9181.0001.000

Missing values

2023-12-12T21:10:44.103634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:10:44.253626image/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.
2023-12-12T21:10:44.368171image/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

측정항목 코드프로그램 코드측정항목명관리항목명통신기호단위측정주기사용구분측정값 유효자리수나미스 코드나미스 전송여부
01TMSAO3O3O3bppm5Y410003Y
12TMSANO2NO2NO2ppm5Y410006Y
23TMSANONONObppm5Y410005Y
34TMSANOXNOXNOXppm5Y410004Y
45TMSASO2SO2SO2ppm5Y410001Y
56TMSACOCOCObppm5Y210002Y
67TMSAPM10PM10PMbug/m35Y010007Y
78TMSAPM25PM25TSPug/m35Y011008Y
89TMSA시정거리시정거리PBbkm5Y3<NA><NA>
910TMSA온도온도TMP℃5Y120003Y
측정항목 코드프로그램 코드측정항목명관리항목명통신기호단위측정주기사용구분측정값 유효자리수나미스 코드나미스 전송여부
19778151TMSVp-E톨루엔p-ethyltolueneV47bppb60Y4<NA><NA>
19878161TMSV135-TM벤젠1,3,5-trimethylbenzeneV48bppb60Y4<NA><NA>
19978171TMSVo-E톨루엔o-ethyltolueneV49bppb60Y4<NA><NA>
20078181TMSV124-TM벤젠1,2,4-trimethylbenzeneV50bppb60Y4<NA><NA>
20178191TMSV123-TM벤젠1,2,3-trimethylbenzeneV52bppb60Y4<NA><NA>
20279111TMSVn-데칸n-decaneV51bppb60Y4<NA><NA>
20379121TMSVm-DE벤젠m-diethylbenzeneV53bppb60Y4<NA><NA>
20479131TMSVp-DE벤젠p-diethylbenzeneV54bppb60Y4<NA><NA>
20579141TMSVn-언데칸n-undecaneV55bppb60Y4<NA><NA>
20679151TMSVn-도데칸n-dodecaneV56bppb60Y4<NA><NA>