Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells11660
Missing cells (%)23.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

Text4
Numeric1

Dataset

Description한국세라믹기술원 세라믹소재정보은행의 시편 정보입니다. 금속/화학/세라믹 통합사이트 주소: http://www.matcenter.org 담당자: 김경훈 수석
Author한국세라믹기술원
URLhttps://www.data.go.kr/data/15072086/fileData.do

Alerts

샘플타입 has 4050 (40.5%) missing valuesMissing
샘플형상 has 1089 (10.9%) missing valuesMissing
샘플표본수 has 4977 (49.8%) missing valuesMissing
샘플치수 has 1544 (15.4%) missing valuesMissing
샘플표본수 is highly skewed (γ1 = 70.6547473)Skewed
물성시퀀스 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:26:31.301037
Analysis finished2023-12-12 19:26:32.186073
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

물성시퀀스
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T04:26:32.351064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.999
Min length4

Characters and Unicode

Total characters139990
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowPRO-1000000514
2nd rowPRO-1000047426
3rd rowPRO-0000018319
4th rowPRO-0000011411
5th rowPRO-0000015478
ValueCountFrequency (%)
pro-1000000514 1
 
< 0.1%
pro-0000008696 1
 
< 0.1%
pro-0000024785 1
 
< 0.1%
pro-0000008356 1
 
< 0.1%
pro-0000017529 1
 
< 0.1%
pro-0000019647 1
 
< 0.1%
pro-1000072785 1
 
< 0.1%
pro-0000007400 1
 
< 0.1%
pro-0000021345 1
 
< 0.1%
pro-0000005768 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-13T04:26:32.709340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 53191
38.0%
1 10775
 
7.7%
P 9999
 
7.1%
R 9999
 
7.1%
O 9999
 
7.1%
- 9999
 
7.1%
2 5660
 
4.0%
4 4937
 
3.5%
3 4587
 
3.3%
7 4316
 
3.1%
Other values (8) 16528
 
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99990
71.4%
Uppercase Letter 29997
 
21.4%
Dash Punctuation 9999
 
7.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53191
53.2%
1 10775
 
10.8%
2 5660
 
5.7%
4 4937
 
4.9%
3 4587
 
4.6%
7 4316
 
4.3%
8 4220
 
4.2%
5 4174
 
4.2%
6 4108
 
4.1%
9 4022
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
d 1
25.0%
i 1
25.0%
s 1
25.0%
k 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
P 9999
33.3%
R 9999
33.3%
O 9999
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 9999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109989
78.6%
Latin 30001
 
21.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 53191
48.4%
1 10775
 
9.8%
- 9999
 
9.1%
2 5660
 
5.1%
4 4937
 
4.5%
3 4587
 
4.2%
7 4316
 
3.9%
8 4220
 
3.8%
5 4174
 
3.8%
6 4108
 
3.7%
Latin
ValueCountFrequency (%)
P 9999
33.3%
R 9999
33.3%
O 9999
33.3%
d 1
 
< 0.1%
i 1
 
< 0.1%
s 1
 
< 0.1%
k 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139990
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 53191
38.0%
1 10775
 
7.7%
P 9999
 
7.1%
R 9999
 
7.1%
O 9999
 
7.1%
- 9999
 
7.1%
2 5660
 
4.0%
4 4937
 
3.5%
3 4587
 
3.3%
7 4316
 
3.1%
Other values (8) 16528
 
11.8%

샘플타입
Text

MISSING 

Distinct115
Distinct (%)1.9%
Missing4050
Missing (%)40.5%
Memory size156.2 KiB
2023-12-13T04:26:33.003076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length4
Mean length5.4139496
Min length1

Characters and Unicode

Total characters32213
Distinct characters106
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)0.9%

Sample

1st rowBulk
2nd rowBulk
3rd rowBulk
4th rowBulk
5th rowBulk
ValueCountFrequency (%)
bulk 4351
63.3%
powder 377
 
5.5%
layer 237
 
3.4%
disk 226
 
3.3%
coating 193
 
2.8%
coated 174
 
2.5%
flim 141
 
2.1%
film 130
 
1.9%
pellet 92
 
1.3%
glass 91
 
1.3%
Other values (141) 865
 
12.6%
2023-12-13T04:26:33.354858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 5208
16.2%
k 4621
14.3%
u 4417
13.7%
B 4370
13.6%
e 1408
 
4.4%
i 1158
 
3.6%
1120
 
3.5%
a 964
 
3.0%
o 916
 
2.8%
t 866
 
2.7%
Other values (96) 7165
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23911
74.2%
Uppercase Letter 6515
 
20.2%
Space Separator 1120
 
3.5%
Decimal Number 371
 
1.2%
Other Punctuation 104
 
0.3%
Other Letter 62
 
0.2%
Open Punctuation 49
 
0.2%
Close Punctuation 49
 
0.2%
Dash Punctuation 24
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 6
 
9.7%
다 4
 
6.5%
조 3
 
4.8%
구 3
 
4.8%
에 2
 
3.2%
언 2
 
3.2%
급 2
 
3.2%
없 2
 
3.2%
류 2
 
3.2%
음 2
 
3.2%
Other values (31) 34
54.8%
Lowercase Letter
ValueCountFrequency (%)
l 5208
21.8%
k 4621
19.3%
u 4417
18.5%
e 1408
 
5.9%
i 1158
 
4.8%
a 964
 
4.0%
o 916
 
3.8%
t 866
 
3.6%
r 819
 
3.4%
d 602
 
2.5%
Other values (15) 2932
12.3%
Uppercase Letter
ValueCountFrequency (%)
B 4370
67.1%
P 522
 
8.0%
C 402
 
6.2%
F 276
 
4.2%
D 239
 
3.7%
L 198
 
3.0%
S 136
 
2.1%
T 107
 
1.6%
W 99
 
1.5%
G 91
 
1.4%
Other values (7) 75
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 152
41.0%
0 69
18.6%
3 50
 
13.5%
1 43
 
11.6%
5 28
 
7.5%
6 9
 
2.4%
4 7
 
1.9%
7 7
 
1.9%
8 3
 
0.8%
9 3
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 44
42.3%
# 38
36.5%
/ 11
 
10.6%
% 5
 
4.8%
: 4
 
3.8%
& 1
 
1.0%
; 1
 
1.0%
Space Separator
ValueCountFrequency (%)
1120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 5
100.0%
Modifier Letter
ValueCountFrequency (%)
ⁿ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30429
94.5%
Common 1722
 
5.3%
Hangul 62
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 5208
17.1%
k 4621
15.2%
u 4417
14.5%
B 4370
14.4%
e 1408
 
4.6%
i 1158
 
3.8%
a 964
 
3.2%
o 916
 
3.0%
t 866
 
2.8%
r 819
 
2.7%
Other values (33) 5682
18.7%
Hangul
ValueCountFrequency (%)
층 6
 
9.7%
다 4
 
6.5%
조 3
 
4.8%
구 3
 
4.8%
에 2
 
3.2%
언 2
 
3.2%
급 2
 
3.2%
없 2
 
3.2%
류 2
 
3.2%
음 2
 
3.2%
Other values (31) 34
54.8%
Common
ValueCountFrequency (%)
1120
65.0%
2 152
 
8.8%
0 69
 
4.0%
3 50
 
2.9%
( 49
 
2.8%
) 49
 
2.8%
. 44
 
2.6%
1 43
 
2.5%
# 38
 
2.2%
5 28
 
1.6%
Other values (12) 80
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32148
99.8%
Hangul 62
 
0.2%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 5208
16.2%
k 4621
14.4%
u 4417
13.7%
B 4370
13.6%
e 1408
 
4.4%
i 1158
 
3.6%
1120
 
3.5%
a 964
 
3.0%
o 916
 
2.8%
t 866
 
2.7%
Other values (54) 7100
22.1%
Hangul
ValueCountFrequency (%)
층 6
 
9.7%
다 4
 
6.5%
조 3
 
4.8%
구 3
 
4.8%
에 2
 
3.2%
언 2
 
3.2%
급 2
 
3.2%
없 2
 
3.2%
류 2
 
3.2%
음 2
 
3.2%
Other values (31) 34
54.8%
None
ValueCountFrequency (%)
ⁿ 3
100.0%

샘플형상
Text

MISSING 

Distinct186
Distinct (%)2.1%
Missing1089
Missing (%)10.9%
Memory size156.2 KiB
2023-12-13T04:26:33.661396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length161
Median length4
Mean length6.3839075
Min length2

Characters and Unicode

Total characters56887
Distinct characters186
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)0.5%

Sample

1st rowDisk
2nd rowthin film
3rd rowDisk
4th rowSheet
5th rowporosity hard body
ValueCountFrequency (%)
disk 4432
40.2%
pellet 652
 
5.9%
bulk 552
 
5.0%
powder 453
 
4.1%
bar 429
 
3.9%
platy 357
 
3.2%
structure 357
 
3.2%
film 343
 
3.1%
of 173
 
1.6%
crystal 171
 
1.5%
Other values (217) 3117
28.2%
2023-12-13T04:26:34.122063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 6051
 
10.6%
s 5781
 
10.2%
k 5047
 
8.9%
l 3958
 
7.0%
e 3878
 
6.8%
r 3108
 
5.5%
t 3106
 
5.5%
D 2892
 
5.1%
d 2541
 
4.5%
a 2451
 
4.3%
Other values (176) 18074
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47513
83.5%
Uppercase Letter 5130
 
9.0%
Space Separator 2130
 
3.7%
Other Letter 866
 
1.5%
Decimal Number 470
 
0.8%
Other Punctuation 455
 
0.8%
Close Punctuation 121
 
0.2%
Open Punctuation 121
 
0.2%
Dash Punctuation 33
 
0.1%
Other Number 32
 
0.1%
Other values (2) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 64
 
7.4%
기 55
 
6.4%
코 53
 
6.1%
팅 51
 
5.9%
판 35
 
4.0%
형 34
 
3.9%
필 25
 
2.9%
름 23
 
2.7%
실 20
 
2.3%
재 20
 
2.3%
Other values (104) 486
56.1%
Lowercase Letter
ValueCountFrequency (%)
i 6051
12.7%
s 5781
12.2%
k 5047
10.6%
l 3958
8.3%
e 3878
 
8.2%
r 3108
 
6.5%
t 3106
 
6.5%
d 2541
 
5.3%
a 2451
 
5.2%
o 1736
 
3.7%
Other values (15) 9856
20.7%
Uppercase Letter
ValueCountFrequency (%)
D 2892
56.4%
B 713
 
13.9%
P 568
 
11.1%
S 304
 
5.9%
F 201
 
3.9%
T 134
 
2.6%
O 106
 
2.1%
C 45
 
0.9%
R 36
 
0.7%
E 30
 
0.6%
Other values (11) 101
 
2.0%
Decimal Number
ValueCountFrequency (%)
0 111
23.6%
3 97
20.6%
1 71
15.1%
5 59
12.6%
4 59
12.6%
2 58
12.3%
8 11
 
2.3%
7 3
 
0.6%
6 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 244
53.6%
: 96
 
21.1%
* 89
 
19.6%
. 21
 
4.6%
& 3
 
0.7%
% 2
 
0.4%
Other Symbol
ValueCountFrequency (%)
㎛ 6
50.0%
℃ 4
33.3%
㎝ 2
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 92
76.0%
] 29
 
24.0%
Open Punctuation
ValueCountFrequency (%)
( 92
76.0%
[ 29
 
24.0%
Space Separator
ValueCountFrequency (%)
2130
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Other Number
ValueCountFrequency (%)
₂ 32
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52643
92.5%
Common 3378
 
5.9%
Hangul 866
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 64
 
7.4%
기 55
 
6.4%
코 53
 
6.1%
팅 51
 
5.9%
판 35
 
4.0%
형 34
 
3.9%
필 25
 
2.9%
름 23
 
2.7%
실 20
 
2.3%
재 20
 
2.3%
Other values (104) 486
56.1%
Latin
ValueCountFrequency (%)
i 6051
11.5%
s 5781
11.0%
k 5047
 
9.6%
l 3958
 
7.5%
e 3878
 
7.4%
r 3108
 
5.9%
t 3106
 
5.9%
D 2892
 
5.5%
d 2541
 
4.8%
a 2451
 
4.7%
Other values (36) 13830
26.3%
Common
ValueCountFrequency (%)
2130
63.1%
/ 244
 
7.2%
0 111
 
3.3%
3 97
 
2.9%
: 96
 
2.8%
) 92
 
2.7%
( 92
 
2.7%
* 89
 
2.6%
1 71
 
2.1%
5 59
 
1.7%
Other values (16) 297
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55976
98.4%
Hangul 866
 
1.5%
None 33
 
0.1%
CJK Compat 8
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 6051
 
10.8%
s 5781
 
10.3%
k 5047
 
9.0%
l 3958
 
7.1%
e 3878
 
6.9%
r 3108
 
5.6%
t 3106
 
5.5%
D 2892
 
5.2%
d 2541
 
4.5%
a 2451
 
4.4%
Other values (57) 17163
30.7%
Hangul
ValueCountFrequency (%)
층 64
 
7.4%
기 55
 
6.4%
코 53
 
6.1%
팅 51
 
5.9%
판 35
 
4.0%
형 34
 
3.9%
필 25
 
2.9%
름 23
 
2.7%
실 20
 
2.3%
재 20
 
2.3%
Other values (104) 486
56.1%
None
ValueCountFrequency (%)
₂ 32
97.0%
Ø 1
 
3.0%
CJK Compat
ValueCountFrequency (%)
㎛ 6
75.0%
㎝ 2
 
25.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 4
100.0%

샘플표본수
Real number (ℝ)

MISSING  SKEWED 

Distinct29
Distinct (%)0.6%
Missing4977
Missing (%)49.8%
Infinite0
Infinite (%)0.0%
Mean5.5902847
Minimum1
Maximum12321
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:26:34.313286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile10
Maximum12321
Range12320
Interquartile range (IQR)3

Descriptive statistics

Standard deviation173.9834
Coefficient of variation (CV)31.122459
Kurtosis5002.033
Mean5.5902847
Median Absolute Deviation (MAD)0
Skewness70.654747
Sum28080
Variance30270.225
MonotonicityNot monotonic
2023-12-13T04:26:34.440514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 3179
31.8%
5 381
 
3.8%
3 339
 
3.4%
4 298
 
3.0%
10 222
 
2.2%
6 130
 
1.3%
2 128
 
1.3%
7 103
 
1.0%
8 80
 
0.8%
16 49
 
0.5%
Other values (19) 114
 
1.1%
(Missing) 4977
49.8%
ValueCountFrequency (%)
1 3179
31.8%
2 128
 
1.3%
3 339
 
3.4%
4 298
 
3.0%
5 381
 
3.8%
6 130
 
1.3%
7 103
 
1.0%
8 80
 
0.8%
9 9
 
0.1%
10 222
 
2.2%
ValueCountFrequency (%)
12321 1
 
< 0.1%
456 1
 
< 0.1%
123 1
 
< 0.1%
88 1
 
< 0.1%
44 14
0.1%
36 2
 
< 0.1%
35 2
 
< 0.1%
31 1
 
< 0.1%
30 14
0.1%
25 1
 
< 0.1%

샘플치수
Text

MISSING 

Distinct363
Distinct (%)4.3%
Missing1544
Missing (%)15.4%
Memory size156.2 KiB
2023-12-13T04:26:34.686327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length117
Median length1
Mean length6.1552744
Min length1

Characters and Unicode

Total characters52049
Distinct characters73
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)1.3%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
mm 1336
 
16.6%
x 475
 
5.9%
dia.=24mm_thick 357
 
4.4%
2.5mm 357
 
4.4%
237
 
2.9%
3*4*30 183
 
2.3%
1.2mm 161
 
2.0%
dia_12mm 155
 
1.9%
diameter 150
 
1.9%
cm 139
 
1.7%
Other values (420) 4511
56.0%
2023-12-13T04:26:35.241901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9531
18.3%
m 8779
16.9%
1 2910
 
5.6%
. 2717
 
5.2%
2 2373
 
4.6%
5 2136
 
4.1%
i 2126
 
4.1%
0 1983
 
3.8%
3 1449
 
2.8%
* 1446
 
2.8%
Other values (63) 16599
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21444
41.2%
Decimal Number 13104
25.2%
Space Separator 9531
18.3%
Other Punctuation 4517
 
8.7%
Math Symbol 1108
 
2.1%
Connector Punctuation 955
 
1.8%
Uppercase Letter 691
 
1.3%
Open Punctuation 217
 
0.4%
Close Punctuation 217
 
0.4%
Other Symbol 211
 
0.4%
Other values (3) 54
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 8779
40.9%
i 2126
 
9.9%
t 1351
 
6.3%
a 1211
 
5.6%
d 1186
 
5.5%
c 1095
 
5.1%
h 1008
 
4.7%
e 935
 
4.4%
k 865
 
4.0%
x 763
 
3.6%
Other values (15) 2125
 
9.9%
Uppercase Letter
ValueCountFrequency (%)
X 288
41.7%
D 97
 
14.0%
L 70
 
10.1%
Φ 66
 
9.6%
Ø 58
 
8.4%
O 39
 
5.6%
I 15
 
2.2%
T 11
 
1.6%
R 10
 
1.4%
H 9
 
1.3%
Other values (5) 28
 
4.1%
Decimal Number
ValueCountFrequency (%)
1 2910
22.2%
2 2373
18.1%
5 2136
16.3%
0 1983
15.1%
3 1449
11.1%
4 1091
 
8.3%
6 375
 
2.9%
7 315
 
2.4%
8 301
 
2.3%
9 171
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 2717
60.2%
* 1446
32.0%
: 252
 
5.6%
/ 96
 
2.1%
; 4
 
0.1%
& 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 966
87.2%
× 77
 
6.9%
~ 64
 
5.8%
> 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
㎜ 100
47.4%
㎝ 96
45.5%
㎛ 15
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 216
99.5%
[ 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 216
99.5%
] 1
 
0.5%
Other Number
ValueCountFrequency (%)
³ 14
93.3%
² 1
 
6.7%
Space Separator
ValueCountFrequency (%)
9531
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 955
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Other Letter
ValueCountFrequency (%)
개 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29913
57.5%
Latin 22006
42.3%
Greek 129
 
0.2%
Hangul 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 8779
39.9%
i 2126
 
9.7%
t 1351
 
6.1%
a 1211
 
5.5%
d 1186
 
5.4%
c 1095
 
5.0%
h 1008
 
4.6%
e 935
 
4.2%
k 865
 
3.9%
x 763
 
3.5%
Other values (26) 2687
 
12.2%
Common
ValueCountFrequency (%)
9531
31.9%
1 2910
 
9.7%
. 2717
 
9.1%
2 2373
 
7.9%
5 2136
 
7.1%
0 1983
 
6.6%
3 1449
 
4.8%
* 1446
 
4.8%
4 1091
 
3.6%
= 966
 
3.2%
Other values (22) 3311
 
11.1%
Greek
ValueCountFrequency (%)
Φ 66
51.2%
φ 52
40.3%
π 6
 
4.7%
μ 5
 
3.9%
Hangul
ValueCountFrequency (%)
개 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51558
99.1%
None 279
 
0.5%
CJK Compat 211
 
0.4%
Hangul 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9531
18.5%
m 8779
17.0%
1 2910
 
5.6%
. 2717
 
5.3%
2 2373
 
4.6%
5 2136
 
4.1%
i 2126
 
4.1%
0 1983
 
3.8%
3 1449
 
2.8%
* 1446
 
2.8%
Other values (51) 16108
31.2%
CJK Compat
ValueCountFrequency (%)
㎜ 100
47.4%
㎝ 96
45.5%
㎛ 15
 
7.1%
None
ValueCountFrequency (%)
× 77
27.6%
Φ 66
23.7%
Ø 58
20.8%
φ 52
18.6%
³ 14
 
5.0%
π 6
 
2.2%
μ 5
 
1.8%
² 1
 
0.4%
Hangul
ValueCountFrequency (%)
개 1
100.0%

Interactions

2023-12-13T04:26:31.745803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T04:26:31.884862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:26:32.000618image/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.
2023-12-13T04:26:32.121352image/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

물성시퀀스샘플타입샘플형상샘플표본수샘플치수
6650PRO-1000000514BulkDisk7
26146PRO-1000047426<NA>thin film<NA><NA>
10961PRO-0000018319BulkDisk1
5620PRO-0000011411<NA>Sheet<NA>
14945PRO-0000015478Bulkporosity hard body1
2026PRO-0000017657BulkDisk1
14225PRO-0000015889BulkBulk<NA>3*4*30 mm
16590PRO-0000016806BulkDisk1
11752PRO-0000018538BulkDisk5
2703PRO-0000005867BulkBulk1
물성시퀀스샘플타입샘플형상샘플표본수샘플치수
2037PRO-0000017668BulkDisk1
21227PRO-1000067985<NA>bulk320*20*5mm
26628PRO-1000054620<NA>chip<NA>3.2*1.6mm*3um
3715PRO-00000056493Disk<NA>
15179PRO-1000002474BulkDisk<NA>dia. 13 mm
13455PRO-0000020413BulkBar<NA>3x4x40 mm
13290PRO-0000020206BulkDisk1
18392PRO-1000012003<NA>Plate<NA><NA>
26536PRO-1000048870<NA>platy structure<NA><NA>
15269PRO-0000013635Bulkcircle shape<NA>