Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells3237
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory576.2 KiB
Average record size in memory59.0 B

Variable types

Text3
Numeric3

Dataset

Description한국세라믹기술원 세라믹소재정보은행의 변화물성 정보입니다. 금속/화학/세라믹 통합사이트 주소: http://www.matcenter.org 담당자: 김경훈 수석
Author한국세라믹기술원
URLhttps://www.data.go.kr/data/15072089/fileData.do

Alerts

측정변수명 has 768 (7.7%) missing valuesMissing
측정단위 has 2411 (24.1%) missing valuesMissing
데이터 is highly skewed (γ1 = 59.66112684)Skewed
측정조건 has 109 (1.1%) zerosZeros

Reproduction

Analysis started2023-12-12 22:27:20.739289
Analysis finished2023-12-12 22:27:22.514637
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

물성시퀀스
Text

Distinct1258
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T07:27:22.665374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters140000
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique790 ?
Unique (%)7.9%

Sample

1st rowPRO-1000013394
2nd rowPRO-1000077169
3rd rowPRO-1000012047
4th rowPRO-1000017213
5th rowPRO-1000012102
ValueCountFrequency (%)
pro-1000076492 208
 
2.1%
pro-1000076559 186
 
1.9%
pro-1000076557 166
 
1.7%
pro-1000076558 166
 
1.7%
pro-1000013844 157
 
1.6%
pro-1000007626 156
 
1.6%
pro-1000009956 152
 
1.5%
pro-1000013808 151
 
1.5%
pro-1000012058 148
 
1.5%
pro-1000013463 147
 
1.5%
Other values (1248) 8363
83.6%
2023-12-13T07:27:22.979719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 48125
34.4%
1 16226
 
11.6%
P 10000
 
7.1%
R 10000
 
7.1%
O 10000
 
7.1%
- 10000
 
7.1%
7 7239
 
5.2%
9 4672
 
3.3%
2 4317
 
3.1%
8 4241
 
3.0%
Other values (4) 15180
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100000
71.4%
Uppercase Letter 30000
 
21.4%
Dash Punctuation 10000
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 48125
48.1%
1 16226
 
16.2%
7 7239
 
7.2%
9 4672
 
4.7%
2 4317
 
4.3%
8 4241
 
4.2%
5 4171
 
4.2%
4 3872
 
3.9%
3 3834
 
3.8%
6 3303
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
P 10000
33.3%
R 10000
33.3%
O 10000
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110000
78.6%
Latin 30000
 
21.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 48125
43.8%
1 16226
 
14.8%
- 10000
 
9.1%
7 7239
 
6.6%
9 4672
 
4.2%
2 4317
 
3.9%
8 4241
 
3.9%
5 4171
 
3.8%
4 3872
 
3.5%
3 3834
 
3.5%
Latin
ValueCountFrequency (%)
P 10000
33.3%
R 10000
33.3%
O 10000
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 140000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 48125
34.4%
1 16226
 
11.6%
P 10000
 
7.1%
R 10000
 
7.1%
O 10000
 
7.1%
- 10000
 
7.1%
7 7239
 
5.2%
9 4672
 
3.3%
2 4317
 
3.1%
8 4241
 
3.0%
Other values (4) 15180
 
10.8%

순번
Real number (ℝ)

Distinct3913
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5030.8289
Minimum1
Maximum37815
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T07:27:23.376286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q1197
median759
Q34666.25
95-th percentile21719.3
Maximum37815
Range37814
Interquartile range (IQR)4469.25

Descriptive statistics

Standard deviation8691.7997
Coefficient of variation (CV)1.7277073
Kurtosis3.3292176
Mean5030.8289
Median Absolute Deviation (MAD)654
Skewness1.9905288
Sum50308289
Variance75547382
MonotonicityNot monotonic
2023-12-13T07:27:23.527875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 298
 
3.0%
2 207
 
2.1%
3 173
 
1.7%
4 150
 
1.5%
5 127
 
1.3%
6 72
 
0.7%
7 58
 
0.6%
8 37
 
0.4%
9 30
 
0.3%
11 28
 
0.3%
Other values (3903) 8820
88.2%
ValueCountFrequency (%)
1 298
3.0%
2 207
2.1%
3 173
1.7%
4 150
1.5%
5 127
1.3%
6 72
 
0.7%
7 58
 
0.6%
8 37
 
0.4%
9 30
 
0.3%
10 17
 
0.2%
ValueCountFrequency (%)
37815 1
< 0.1%
37797 1
< 0.1%
37786 1
< 0.1%
37777 1
< 0.1%
37766 1
< 0.1%
37762 1
< 0.1%
37748 1
< 0.1%
37742 1
< 0.1%
37740 1
< 0.1%
37739 1
< 0.1%

데이터
Real number (ℝ)

SKEWED 

Distinct2988
Distinct (%)30.1%
Missing58
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean1.4866408 × 1015
Minimum-678.481
Maximum5.53 × 1018
Zeros67
Zeros (%)0.7%
Negative352
Negative (%)3.5%
Memory size166.0 KiB
2023-12-13T07:27:23.646974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-678.481
5-th percentile0.0063
Q120.8333
median58.3333
Q3162.51185
95-th percentile483.31635
Maximum5.53 × 1018
Range5.53 × 1018
Interquartile range (IQR)141.67855

Descriptive statistics

Standard deviation7.5120951 × 1016
Coefficient of variation (CV)50.530667
Kurtosis3885.5624
Mean1.4866408 × 1015
Median Absolute Deviation (MAD)51.881069
Skewness59.661127
Sum1.4780183 × 1019
Variance5.6431573 × 1033
MonotonicityNot monotonic
2023-12-13T07:27:23.762890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5 270
 
2.7%
45.8333 260
 
2.6%
33.3333 259
 
2.6%
50.0 248
 
2.5%
41.6667 234
 
2.3%
29.1667 230
 
2.3%
25.0 225
 
2.2%
54.1667 221
 
2.2%
58.3333 188
 
1.9%
20.8333 182
 
1.8%
Other values (2978) 7625
76.2%
ValueCountFrequency (%)
-678.481 1
< 0.1%
-621.7722 1
< 0.1%
-601.519 1
< 0.1%
-573.1646 1
< 0.1%
-520.5063 1
< 0.1%
-496.2025 1
< 0.1%
-484.0506 1
< 0.1%
-475.9494 1
< 0.1%
-431.3924 1
< 0.1%
-419.2405 1
< 0.1%
ValueCountFrequency (%)
5.53e+18 1
< 0.1%
4.04e+18 1
< 0.1%
1.91e+18 1
< 0.1%
1.9e+18 1
< 0.1%
1.4e+18 1
< 0.1%
95000000000000.0 1
< 0.1%
86000000000000.0 1
< 0.1%
1890000000000.0 1
< 0.1%
1000000000.0 1
< 0.1%
839733500.0 1
< 0.1%

측정변수명
Text

MISSING 

Distinct291
Distinct (%)3.2%
Missing768
Missing (%)7.7%
Memory size156.2 KiB
2023-12-13T07:27:23.965508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length2
Mean length4.7195624
Min length1

Characters and Unicode

Total characters43571
Distinct characters132
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)1.2%

Sample

1st row2Θ
2nd rowwavelength
3rd row2Θ
4th row2θ
5th row2Θ
ValueCountFrequency (%)
2θ 6228
60.1%
temperature 611
 
5.9%
capacity 521
 
5.0%
wavelength 373
 
3.6%
voltage 151
 
1.5%
조성 131
 
1.3%
℃ 123
 
1.2%
of 106
 
1.0%
frequency 101
 
1.0%
x 100
 
1.0%
Other values (295) 1925
 
18.6%
2023-12-13T07:27:24.362922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 6407
14.7%
Θ 5103
 
11.7%
e 4004
 
9.2%
t 2826
 
6.5%
a 2591
 
5.9%
r 1856
 
4.3%
n 1413
 
3.2%
p 1259
 
2.9%
1173
 
2.7%
i 1167
 
2.7%
Other values (122) 15772
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25310
58.1%
Uppercase Letter 7738
 
17.8%
Decimal Number 6837
 
15.7%
Space Separator 1173
 
2.7%
Other Letter 941
 
2.2%
Other Punctuation 458
 
1.1%
Open Punctuation 396
 
0.9%
Close Punctuation 395
 
0.9%
Other Symbol 228
 
0.5%
Dash Punctuation 44
 
0.1%
Other values (3) 51
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 133
14.1%
조 131
13.9%
량 107
11.4%
함 106
11.3%
도 60
 
6.4%
전 46
 
4.9%
온 46
 
4.9%
두 31
 
3.3%
께 31
 
3.3%
극 24
 
2.6%
Other values (43) 226
24.0%
Lowercase Letter
ValueCountFrequency (%)
e 4004
15.8%
t 2826
11.2%
a 2591
 
10.2%
r 1856
 
7.3%
n 1413
 
5.6%
p 1259
 
5.0%
i 1167
 
4.6%
θ 1125
 
4.4%
m 1103
 
4.4%
c 1100
 
4.3%
Other values (19) 6866
27.1%
Uppercase Letter
ValueCountFrequency (%)
Θ 5103
65.9%
T 772
 
10.0%
C 663
 
8.6%
O 220
 
2.8%
V 157
 
2.0%
N 147
 
1.9%
P 139
 
1.8%
A 111
 
1.4%
S 99
 
1.3%
B 69
 
0.9%
Other values (11) 258
 
3.3%
Decimal Number
ValueCountFrequency (%)
2 6407
93.7%
3 125
 
1.8%
0 105
 
1.5%
1 75
 
1.1%
5 57
 
0.8%
4 39
 
0.6%
7 17
 
0.2%
8 8
 
0.1%
9 4
 
0.1%
Other Punctuation
ValueCountFrequency (%)
% 223
48.7%
. 179
39.1%
/ 48
 
10.5%
: 6
 
1.3%
* 2
 
0.4%
Other Symbol
ValueCountFrequency (%)
℃ 206
90.4%
㎃ 11
 
4.8%
㎠ 11
 
4.8%
Open Punctuation
ValueCountFrequency (%)
( 394
99.5%
[ 2
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 393
99.5%
] 2
 
0.5%
Modifier Symbol
ValueCountFrequency (%)
^ 20
87.0%
˚ 3
 
13.0%
Other Number
ValueCountFrequency (%)
₂ 11
55.0%
₃ 9
45.0%
Math Symbol
ValueCountFrequency (%)
+ 7
87.5%
= 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1173
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26813
61.5%
Common 9582
 
22.0%
Greek 6235
 
14.3%
Hangul 941
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 133
14.1%
조 131
13.9%
량 107
11.4%
함 106
11.3%
도 60
 
6.4%
전 46
 
4.9%
온 46
 
4.9%
두 31
 
3.3%
께 31
 
3.3%
극 24
 
2.6%
Other values (43) 226
24.0%
Latin
ValueCountFrequency (%)
e 4004
14.9%
t 2826
 
10.5%
a 2591
 
9.7%
r 1856
 
6.9%
n 1413
 
5.3%
p 1259
 
4.7%
i 1167
 
4.4%
m 1103
 
4.1%
c 1100
 
4.1%
l 1032
 
3.8%
Other values (36) 8462
31.6%
Common
ValueCountFrequency (%)
2 6407
66.9%
1173
 
12.2%
( 394
 
4.1%
) 393
 
4.1%
% 223
 
2.3%
℃ 206
 
2.1%
. 179
 
1.9%
3 125
 
1.3%
0 105
 
1.1%
1 75
 
0.8%
Other values (19) 302
 
3.2%
Greek
ValueCountFrequency (%)
Θ 5103
81.8%
θ 1125
 
18.0%
μ 5
 
0.1%
λ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36144
83.0%
None 6255
 
14.4%
Hangul 941
 
2.2%
Letterlike Symbols 206
 
0.5%
CJK Compat 22
 
0.1%
Modifier Letters 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 6407
17.7%
e 4004
 
11.1%
t 2826
 
7.8%
a 2591
 
7.2%
r 1856
 
5.1%
n 1413
 
3.9%
p 1259
 
3.5%
1173
 
3.2%
i 1167
 
3.2%
m 1103
 
3.1%
Other values (59) 12345
34.2%
None
ValueCountFrequency (%)
Θ 5103
81.6%
θ 1125
 
18.0%
₂ 11
 
0.2%
₃ 9
 
0.1%
μ 5
 
0.1%
λ 2
 
< 0.1%
Letterlike Symbols
ValueCountFrequency (%)
℃ 206
100.0%
Hangul
ValueCountFrequency (%)
성 133
14.1%
조 131
13.9%
량 107
11.4%
함 106
11.3%
도 60
 
6.4%
전 46
 
4.9%
온 46
 
4.9%
두 31
 
3.3%
께 31
 
3.3%
극 24
 
2.6%
Other values (43) 226
24.0%
CJK Compat
ValueCountFrequency (%)
㎃ 11
50.0%
㎠ 11
50.0%
Modifier Letters
ValueCountFrequency (%)
˚ 3
100.0%

측정조건
Real number (ℝ)

ZEROS 

Distinct3082
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.310966
Minimum-40
Maximum30.86
Zeros109
Zeros (%)1.1%
Negative25
Negative (%)0.2%
Memory size166.0 KiB
2023-12-13T07:27:24.498205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-40
5-th percentile0.00345
Q16.839537
median16.33
Q324.3125
95-th percentile29.427601
Maximum30.86
Range70.86
Interquartile range (IQR)17.472963

Descriptive statistics

Standard deviation10.049731
Coefficient of variation (CV)0.65637471
Kurtosis-0.67334564
Mean15.310966
Median Absolute Deviation (MAD)8.417885
Skewness-0.30912069
Sum153109.66
Variance100.99709
MonotonicityNot monotonic
2023-12-13T07:27:24.620950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 109
 
1.1%
1.0 75
 
0.8%
10.0 58
 
0.6%
5.0 53
 
0.5%
20.0 45
 
0.4%
25.0 40
 
0.4%
6.0 37
 
0.4%
30.0 33
 
0.3%
2.0 33
 
0.3%
0.00347 31
 
0.3%
Other values (3072) 9486
94.9%
ValueCountFrequency (%)
-40.0 6
0.1%
-26.49 1
 
< 0.1%
-26.0 1
 
< 0.1%
-25.48 1
 
< 0.1%
-21.895 1
 
< 0.1%
-15.0 1
 
< 0.1%
-5.0 1
 
< 0.1%
-3.5 1
 
< 0.1%
-2.01005 1
 
< 0.1%
-2.0 1
 
< 0.1%
ValueCountFrequency (%)
30.86 1
 
< 0.1%
30.84 6
0.1%
30.82 6
0.1%
30.81313 1
 
< 0.1%
30.8125 4
< 0.1%
30.8 8
0.1%
30.7813 1
 
< 0.1%
30.78 7
0.1%
30.76 5
0.1%
30.75 4
< 0.1%

측정단위
Text

MISSING 

Distinct72
Distinct (%)0.9%
Missing2411
Missing (%)24.1%
Memory size156.2 KiB
2023-12-13T07:27:24.809506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters45534
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.2%

Sample

1st rowU01156
2nd rowU01276
3rd rowU01111
4th rowU01047
5th rowU09999
ValueCountFrequency (%)
u09999 3058
40.3%
u01276 1135
 
15.0%
u01111 576
 
7.6%
u01120 518
 
6.8%
u01084 505
 
6.7%
u01156 307
 
4.0%
u01049 253
 
3.3%
u01124 208
 
2.7%
u01311 131
 
1.7%
u09012 92
 
1.2%
Other values (62) 806
 
10.6%
2023-12-13T07:27:25.078309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 12953
28.4%
0 9849
21.6%
1 7745
17.0%
U 7589
16.7%
2 2312
 
5.1%
6 1530
 
3.4%
7 1309
 
2.9%
4 1044
 
2.3%
8 538
 
1.2%
5 409
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37945
83.3%
Uppercase Letter 7589
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 12953
34.1%
0 9849
26.0%
1 7745
20.4%
2 2312
 
6.1%
6 1530
 
4.0%
7 1309
 
3.4%
4 1044
 
2.8%
8 538
 
1.4%
5 409
 
1.1%
3 256
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
U 7589
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37945
83.3%
Latin 7589
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
9 12953
34.1%
0 9849
26.0%
1 7745
20.4%
2 2312
 
6.1%
6 1530
 
4.0%
7 1309
 
3.4%
4 1044
 
2.8%
8 538
 
1.4%
5 409
 
1.1%
3 256
 
0.7%
Latin
ValueCountFrequency (%)
U 7589
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45534
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 12953
28.4%
0 9849
21.6%
1 7745
17.0%
U 7589
16.7%
2 2312
 
5.1%
6 1530
 
3.4%
7 1309
 
2.9%
4 1044
 
2.3%
8 538
 
1.2%
5 409
 
0.9%

Interactions

2023-12-13T07:27:21.928613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:21.287894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:21.620862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:22.062297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:21.395114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:21.728037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:22.149552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:21.497474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:21.828373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:27:25.175564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번데이터측정조건측정단위
순번1.0000.0000.4000.609
데이터0.0001.0000.0000.788
측정조건0.4000.0001.0000.761
측정단위0.6090.7880.7611.000
2023-12-13T07:27:25.262107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번데이터측정조건
순번1.0000.0840.475
데이터0.0841.000-0.219
측정조건0.475-0.2191.000

Missing values

2023-12-13T07:27:22.277730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:27:22.374552image/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.
2023-12-13T07:27:22.461377image/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

물성시퀀스순번데이터측정변수명측정조건측정단위
66000PRO-100001339488095.83332Θ22.58<NA>
20073PRO-1000077169968231.0wavelength4.58093U01156
68501PRO-10000120479254.166672Θ23.48<NA>
83066PRO-100001721328095417.02θ27.38U01276
93046PRO-1000012102125933.33332Θ30.16<NA>
63619PRO-100001384483795.83332Θ21.72<NA>
9579PRO-1000076559744130.0699<NA>0.04661U01111
18237PRO-00000224313<NA>103/T2.5U01047
20809PRO-10000133944320.8332Θ5.06<NA>
33725PRO-10000138114062100.02Θ11.24<NA>
물성시퀀스순번데이터측정변수명측정조건측정단위
70133PRO-1000009265703125.02Θ24.04U09999
65295PRO-1000009769617854.1672Θ22.32U09999
70896PRO-100000234371230.8333조성24.22U01311
42145PRO-100001210245929.16672Θ14.16<NA>
55573PRO-1000009240447120.8332Θ18.92U09999
29346PRO-100000757514357112.52Θ9.8U09999
41269PRO-100000983444595.83332Θ13.88U09999
9980PRO-100007655949386.8032<NA>0.05526U01111
72336PRO-1000009808368200.0Temperature. ℃24.5625<NA>
36110PRO-100000994335275.02Θ12.02U09999