Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

Numeric2
Text5
DateTime1

Dataset

Description한국나노기술원에서 진행한 내부과제 장비활용 내역입니다.(접수번호, 공정순번, 장비명, 공정명 등) * 장비 상세 정보 : 한국나노기술원_나노소자팹서비스 및 연구공정장비 정보(https://www.data.go.kr/data/15037530/fileData.do)에서 확인 가능합니다.
URLhttps://www.data.go.kr/data/15086986/fileData.do

Reproduction

Analysis started2023-12-12 05:54:19.036753
Analysis finished2023-12-12 05:54:20.394582
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

접수번호
Real number (ℝ)

Distinct2503
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0152078 × 1010
Minimum2.0100311 × 1010
Maximum2.0210831 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T14:54:20.481869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0100311 × 1010
5-th percentile2.0100901 × 1010
Q12.0111125 × 1010
median2.0150713 × 1010
Q32.0190514 × 1010
95-th percentile2.0210401 × 1010
Maximum2.0210831 × 1010
Range1.1052 × 108
Interquartile range (IQR)79388997

Descriptive statistics

Standard deviation37312046
Coefficient of variation (CV)0.0018515235
Kurtosis-1.4424343
Mean2.0152078 × 1010
Median Absolute Deviation (MAD)39604999
Skewness0.098589635
Sum2.0152078 × 1014
Variance1.3921888 × 1015
MonotonicityNot monotonic
2023-12-12T14:54:20.664154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110711001 37
 
0.4%
20110512006 35
 
0.4%
20200924002 35
 
0.4%
20160822002 34
 
0.3%
20110512003 33
 
0.3%
20111125005 32
 
0.3%
20110512004 31
 
0.3%
20191104002 31
 
0.3%
20110804001 31
 
0.3%
20201118001 30
 
0.3%
Other values (2493) 9671
96.7%
ValueCountFrequency (%)
20100311001 1
< 0.1%
20100311002 1
< 0.1%
20100311005 1
< 0.1%
20100311008 1
< 0.1%
20100311010 1
< 0.1%
20100312001 1
< 0.1%
20100312003 1
< 0.1%
20100312004 2
< 0.1%
20100312006 2
< 0.1%
20100312007 1
< 0.1%
ValueCountFrequency (%)
20210831001 15
0.1%
20210830002 9
0.1%
20210830001 1
 
< 0.1%
20210826002 1
 
< 0.1%
20210824001 1
 
< 0.1%
20210823001 9
0.1%
20210819001 1
 
< 0.1%
20210818003 1
 
< 0.1%
20210818002 7
0.1%
20210818001 1
 
< 0.1%

제품번호
Text

Distinct2503
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:54:21.011240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.6991
Min length5

Characters and Unicode

Total characters116991
Distinct characters28
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

Unique1377 ?
Unique (%)13.8%

Sample

1st rowI20190114001
2nd rowVL1007-02
3rd rowI20141030001
4th rowI20131105003
5th rowI20130416002
ValueCountFrequency (%)
vl 190
 
1.8%
lve 75
 
0.7%
ml 62
 
0.6%
stj 54
 
0.5%
1012-01 49
 
0.5%
1011-01 47
 
0.5%
stj1107-01 37
 
0.4%
stj1104-02 35
 
0.3%
i20200924002 35
 
0.3%
i20160822002 34
 
0.3%
Other values (2495) 9763
94.0%
2023-12-12T14:54:21.450858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40787
34.9%
1 23098
19.7%
2 18835
16.1%
I 8585
 
7.3%
3 4335
 
3.7%
4 2847
 
2.4%
6 2665
 
2.3%
9 2662
 
2.3%
7 2613
 
2.2%
5 2599
 
2.2%
Other values (18) 7965
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102812
87.9%
Uppercase Letter 12180
 
10.4%
Dash Punctuation 1618
 
1.4%
Space Separator 381
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
I 8585
70.5%
L 1117
 
9.2%
V 669
 
5.5%
T 429
 
3.5%
J 378
 
3.1%
S 299
 
2.5%
E 227
 
1.9%
N 110
 
0.9%
A 93
 
0.8%
B 73
 
0.6%
Other values (6) 200
 
1.6%
Decimal Number
ValueCountFrequency (%)
0 40787
39.7%
1 23098
22.5%
2 18835
18.3%
3 4335
 
4.2%
4 2847
 
2.8%
6 2665
 
2.6%
9 2662
 
2.6%
7 2613
 
2.5%
5 2599
 
2.5%
8 2371
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 1618
100.0%
Space Separator
ValueCountFrequency (%)
381
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104811
89.6%
Latin 12180
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
I 8585
70.5%
L 1117
 
9.2%
V 669
 
5.5%
T 429
 
3.5%
J 378
 
3.1%
S 299
 
2.5%
E 227
 
1.9%
N 110
 
0.9%
A 93
 
0.8%
B 73
 
0.6%
Other values (6) 200
 
1.6%
Common
ValueCountFrequency (%)
0 40787
38.9%
1 23098
22.0%
2 18835
18.0%
3 4335
 
4.1%
4 2847
 
2.7%
6 2665
 
2.5%
9 2662
 
2.5%
7 2613
 
2.5%
5 2599
 
2.5%
8 2371
 
2.3%
Other values (2) 1999
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 116991
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40787
34.9%
1 23098
19.7%
2 18835
16.1%
I 8585
 
7.3%
3 4335
 
3.7%
4 2847
 
2.4%
6 2665
 
2.3%
9 2662
 
2.3%
7 2613
 
2.2%
5 2599
 
2.2%
Other values (18) 7965
 
6.8%

공정순번
Real number (ℝ)

Distinct81
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.4978
Minimum1
Maximum96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T14:54:21.634331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median9
Q321
95-th percentile41
Maximum96
Range95
Interquartile range (IQR)18

Descriptive statistics

Standard deviation13.290969
Coefficient of variation (CV)0.9846767
Kurtosis2.0624401
Mean13.4978
Median Absolute Deviation (MAD)7.5
Skewness1.3959103
Sum134978
Variance176.64986
MonotonicityNot monotonic
2023-12-12T14:54:21.783228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1706
 
17.1%
2 711
 
7.1%
3 577
 
5.8%
4 444
 
4.4%
5 389
 
3.9%
6 359
 
3.6%
7 291
 
2.9%
8 289
 
2.9%
10 269
 
2.7%
9 263
 
2.6%
Other values (71) 4702
47.0%
ValueCountFrequency (%)
1 1706
17.1%
2 711
7.1%
3 577
 
5.8%
4 444
 
4.4%
5 389
 
3.9%
6 359
 
3.6%
7 291
 
2.9%
8 289
 
2.9%
9 263
 
2.6%
10 269
 
2.7%
ValueCountFrequency (%)
96 1
 
< 0.1%
95 1
 
< 0.1%
89 1
 
< 0.1%
79 1
 
< 0.1%
77 5
0.1%
76 2
 
< 0.1%
75 1
 
< 0.1%
74 1
 
< 0.1%
73 2
 
< 0.1%
72 2
 
< 0.1%

장비코드
Text

Distinct151
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:54:22.110660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length7.0001
Min length7

Characters and Unicode

Total characters70001
Distinct characters29
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

Unique20 ?
Unique (%)0.2%

Sample

1st rowFE-MC50
2nd rowFR-SF10
3rd rowFC-FI10
4th rowFR-WB40
5th rowFC-AM20
ValueCountFrequency (%)
fl-tr10 1566
 
15.7%
fr-wb10 562
 
5.6%
fl-ca10 455
 
4.5%
fr-wb30 436
 
4.4%
fl-tr30 365
 
3.6%
ff-mw12 347
 
3.5%
ff-eb20 335
 
3.4%
fr-wb40 278
 
2.8%
ff-mw11 275
 
2.8%
fl-ca20 271
 
2.7%
Other values (141) 5110
51.1%
2023-12-12T14:54:22.641688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 12449
17.8%
- 10000
14.3%
0 9378
13.4%
1 6169
8.8%
R 5580
8.0%
L 4024
 
5.7%
W 2672
 
3.8%
T 2626
 
3.8%
B 2599
 
3.7%
C 2131
 
3.0%
Other values (19) 12373
17.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 40001
57.1%
Decimal Number 20000
28.6%
Dash Punctuation 10000
 
14.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 12449
31.1%
R 5580
13.9%
L 4024
 
10.1%
W 2672
 
6.7%
T 2626
 
6.6%
B 2599
 
6.5%
C 2131
 
5.3%
E 1758
 
4.4%
M 1603
 
4.0%
S 1508
 
3.8%
Other values (11) 3051
 
7.6%
Decimal Number
ValueCountFrequency (%)
0 9378
46.9%
1 6169
30.8%
2 2114
 
10.6%
3 1673
 
8.4%
4 455
 
2.3%
5 193
 
1.0%
6 18
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40001
57.1%
Common 30000
42.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 12449
31.1%
R 5580
13.9%
L 4024
 
10.1%
W 2672
 
6.7%
T 2626
 
6.6%
B 2599
 
6.5%
C 2131
 
5.3%
E 1758
 
4.4%
M 1603
 
4.0%
S 1508
 
3.8%
Other values (11) 3051
 
7.6%
Common
ValueCountFrequency (%)
- 10000
33.3%
0 9378
31.3%
1 6169
20.6%
2 2114
 
7.0%
3 1673
 
5.6%
4 455
 
1.5%
5 193
 
0.6%
6 18
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 12449
17.8%
- 10000
14.3%
0 9378
13.4%
1 6169
8.8%
R 5580
8.0%
L 4024
 
5.7%
W 2672
 
3.8%
T 2626
 
3.8%
B 2599
 
3.7%
C 2131
 
3.0%
Other values (19) 12373
17.7%

장비명
Text

Distinct149
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:54:23.051124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length32
Mean length20.1361
Min length3

Characters and Unicode

Total characters201361
Distinct characters73
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

Unique20 ?
Unique (%)0.2%

Sample

1st rowMOCVD V(epi)
2nd rowSurface Scan/Profiler
3rd rowFIB I
4th rowLiftoff Wet-Bench(R&D)
5th rowAFM III
ValueCountFrequency (%)
i 3220
 
10.5%
inch 2289
 
7.5%
track 2269
 
7.4%
2-3 1566
 
5.1%
wet-bench(r&d 1384
 
4.5%
ii 1012
 
3.3%
aligner 980
 
3.2%
contact 979
 
3.2%
e-beam 862
 
2.8%
acid 855
 
2.8%
Other values (181) 15306
49.8%
2023-12-12T14:54:23.617918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20722
 
10.3%
a 11945
 
5.9%
e 10899
 
5.4%
c 10899
 
5.4%
r 10738
 
5.3%
n 10375
 
5.2%
I 10349
 
5.1%
i 8606
 
4.3%
t 8470
 
4.2%
o 7883
 
3.9%
Other values (63) 90475
44.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 112760
56.0%
Uppercase Letter 38601
 
19.2%
Space Separator 20722
 
10.3%
Open Punctuation 7880
 
3.9%
Close Punctuation 7880
 
3.9%
Dash Punctuation 5396
 
2.7%
Decimal Number 4833
 
2.4%
Other Punctuation 3228
 
1.6%
Other Letter 48
 
< 0.1%
Letter Number 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 11945
10.6%
e 10899
9.7%
c 10899
9.7%
r 10738
9.5%
n 10375
9.2%
i 8606
 
7.6%
t 8470
 
7.5%
o 7883
 
7.0%
h 5549
 
4.9%
u 3787
 
3.4%
Other values (14) 23609
20.9%
Uppercase Letter
ValueCountFrequency (%)
I 10349
26.8%
D 3800
 
9.8%
A 3159
 
8.2%
R 2764
 
7.2%
T 2616
 
6.8%
M 2572
 
6.7%
C 2204
 
5.7%
W 2114
 
5.5%
B 1710
 
4.4%
P 1463
 
3.8%
Other values (12) 5850
15.2%
Decimal Number
ValueCountFrequency (%)
3 1606
33.2%
2 1589
32.9%
6 707
14.6%
4 704
14.6%
0 148
 
3.1%
9 38
 
0.8%
8 33
 
0.7%
1 4
 
0.1%
5 3
 
0.1%
7 1
 
< 0.1%
Other Letter
ValueCountFrequency (%)
통 13
27.1%
합 13
27.1%
으 10
20.8%
로 10
20.8%
변 1
 
2.1%
경 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
& 2356
73.0%
: 622
 
19.3%
/ 247
 
7.7%
, 2
 
0.1%
. 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20722
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7880
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7880
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5396
100.0%
Letter Number
ValueCountFrequency (%)
Ⅵ 12
100.0%
Math Symbol
ValueCountFrequency (%)
> 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 151373
75.2%
Common 49940
 
24.8%
Hangul 48
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 11945
 
7.9%
e 10899
 
7.2%
c 10899
 
7.2%
r 10738
 
7.1%
n 10375
 
6.9%
I 10349
 
6.8%
i 8606
 
5.7%
t 8470
 
5.6%
o 7883
 
5.2%
h 5549
 
3.7%
Other values (37) 55660
36.8%
Common
ValueCountFrequency (%)
20722
41.5%
( 7880
 
15.8%
) 7880
 
15.8%
- 5396
 
10.8%
& 2356
 
4.7%
3 1606
 
3.2%
2 1589
 
3.2%
6 707
 
1.4%
4 704
 
1.4%
: 622
 
1.2%
Other values (10) 478
 
1.0%
Hangul
ValueCountFrequency (%)
통 13
27.1%
합 13
27.1%
으 10
20.8%
로 10
20.8%
변 1
 
2.1%
경 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201301
> 99.9%
Hangul 48
 
< 0.1%
Number Forms 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20722
 
10.3%
a 11945
 
5.9%
e 10899
 
5.4%
c 10899
 
5.4%
r 10738
 
5.3%
n 10375
 
5.2%
I 10349
 
5.1%
i 8606
 
4.3%
t 8470
 
4.2%
o 7883
 
3.9%
Other values (56) 90415
44.9%
Hangul
ValueCountFrequency (%)
통 13
27.1%
합 13
27.1%
으 10
20.8%
로 10
20.8%
변 1
 
2.1%
경 1
 
2.1%
Number Forms
ValueCountFrequency (%)
Ⅵ 12
100.0%

공정코드
Text

Distinct243
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:54:24.015452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.8593
Min length4

Characters and Unicode

Total characters58593
Distinct characters21
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

Unique26 ?
Unique (%)0.3%

Sample

1st rowE1B005
2nd row92100
3rd rowC3A019
4th rowR1B004
5th rowC3A001
ValueCountFrequency (%)
l1a001 864
 
8.6%
l1b001 643
 
6.4%
l1b002 539
 
5.4%
f2b001 472
 
4.7%
r1b001 450
 
4.5%
f4a002 350
 
3.5%
f4a003 346
 
3.5%
r1b003 309
 
3.1%
r1b004 276
 
2.8%
r2a001 255
 
2.5%
Other values (233) 5496
55.0%
2023-12-12T14:54:24.591806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19866
33.9%
1 10453
17.8%
B 4655
 
7.9%
A 3928
 
6.7%
2 3428
 
5.9%
L 3158
 
5.4%
R 2425
 
4.1%
3 2178
 
3.7%
4 2030
 
3.5%
F 1734
 
3.0%
Other values (11) 4738
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41301
70.5%
Uppercase Letter 17292
29.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 4655
26.9%
A 3928
22.7%
L 3158
18.3%
R 2425
14.0%
F 1734
 
10.0%
C 838
 
4.8%
E 320
 
1.9%
D 187
 
1.1%
S 28
 
0.2%
M 18
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 19866
48.1%
1 10453
25.3%
2 3428
 
8.3%
3 2178
 
5.3%
4 2030
 
4.9%
5 1162
 
2.8%
9 1039
 
2.5%
6 495
 
1.2%
7 383
 
0.9%
8 267
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 41301
70.5%
Latin 17292
29.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 4655
26.9%
A 3928
22.7%
L 3158
18.3%
R 2425
14.0%
F 1734
 
10.0%
C 838
 
4.8%
E 320
 
1.9%
D 187
 
1.1%
S 28
 
0.2%
M 18
 
0.1%
Common
ValueCountFrequency (%)
0 19866
48.1%
1 10453
25.3%
2 3428
 
8.3%
3 2178
 
5.3%
4 2030
 
4.9%
5 1162
 
2.8%
9 1039
 
2.5%
6 495
 
1.2%
7 383
 
0.9%
8 267
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58593
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19866
33.9%
1 10453
17.8%
B 4655
 
7.9%
A 3928
 
6.7%
2 3428
 
5.9%
L 3158
 
5.4%
R 2425
 
4.1%
3 2178
 
3.7%
4 2030
 
3.5%
F 1734
 
3.0%
Other values (11) 4738
 
8.1%

공정명
Text

Distinct219
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:54:24.978010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length38
Mean length19.1388
Min length2

Characters and Unicode

Total characters191388
Distinct characters118
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.2%

Sample

1st rowMOCVD V (epi)
2nd rowMetal Thickness Inspection
3rd rowFIB(TEM Preparation)
4th rowMetal Liftoff
5th rowAFM
ValueCountFrequency (%)
pr 3182
 
9.7%
2189
 
6.6%
5마이크로 1883
 
5.7%
이하 1749
 
5.3%
track 1677
 
5.1%
metal 1317
 
4.0%
i 1239
 
3.8%
coating 1226
 
3.7%
wet 1177
 
3.6%
process 1066
 
3.2%
Other values (254) 16244
49.3%
2023-12-12T14:54:25.589215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23341
 
12.2%
e 12263
 
6.4%
a 10627
 
5.6%
o 8803
 
4.6%
t 8655
 
4.5%
i 8125
 
4.2%
n 7776
 
4.1%
r 7268
 
3.8%
c 6404
 
3.3%
s 6358
 
3.3%
Other values (108) 91768
47.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 104761
54.7%
Uppercase Letter 37881
 
19.8%
Space Separator 23341
 
12.2%
Other Letter 11919
 
6.2%
Close Punctuation 3570
 
1.9%
Open Punctuation 3570
 
1.9%
Decimal Number 2373
 
1.2%
Dash Punctuation 2263
 
1.2%
Other Punctuation 1571
 
0.8%
Math Symbol 113
 
0.1%
Other values (2) 26
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3782
31.7%
마 1883
15.8%
크 1883
15.8%
로 1883
15.8%
하 1749
14.7%
상 150
 
1.3%
원 40
 
0.3%
면 27
 
0.2%
터 24
 
0.2%
센 24
 
0.2%
Other values (41) 474
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 12263
11.7%
a 10627
10.1%
o 8803
 
8.4%
t 8655
 
8.3%
i 8125
 
7.8%
n 7776
 
7.4%
r 7268
 
6.9%
c 6404
 
6.1%
s 6358
 
6.1%
l 4921
 
4.7%
Other values (14) 23561
22.5%
Uppercase Letter
ValueCountFrequency (%)
P 5254
13.9%
I 4490
11.9%
R 4445
11.7%
M 3286
8.7%
E 3093
8.2%
D 2821
7.4%
T 2416
 
6.4%
A 2137
 
5.6%
C 2131
 
5.6%
O 1372
 
3.6%
Other values (13) 6436
17.0%
Decimal Number
ValueCountFrequency (%)
5 1891
79.7%
2 270
 
11.4%
3 117
 
4.9%
0 33
 
1.4%
1 18
 
0.8%
4 17
 
0.7%
8 16
 
0.7%
6 9
 
0.4%
7 2
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 889
56.6%
/ 470
29.9%
& 185
 
11.8%
. 27
 
1.7%
Space Separator
ValueCountFrequency (%)
23341
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3570
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3570
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2263
100.0%
Math Symbol
ValueCountFrequency (%)
~ 113
100.0%
Letter Number
ValueCountFrequency (%)
Ⅵ 24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 142666
74.5%
Common 36803
 
19.2%
Hangul 11919
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3782
31.7%
마 1883
15.8%
크 1883
15.8%
로 1883
15.8%
하 1749
14.7%
상 150
 
1.3%
원 40
 
0.3%
면 27
 
0.2%
터 24
 
0.2%
센 24
 
0.2%
Other values (41) 474
 
4.0%
Latin
ValueCountFrequency (%)
e 12263
 
8.6%
a 10627
 
7.4%
o 8803
 
6.2%
t 8655
 
6.1%
i 8125
 
5.7%
n 7776
 
5.5%
r 7268
 
5.1%
c 6404
 
4.5%
s 6358
 
4.5%
P 5254
 
3.7%
Other values (38) 61133
42.9%
Common
ValueCountFrequency (%)
23341
63.4%
) 3570
 
9.7%
( 3570
 
9.7%
- 2263
 
6.1%
5 1891
 
5.1%
, 889
 
2.4%
/ 470
 
1.3%
2 270
 
0.7%
& 185
 
0.5%
3 117
 
0.3%
Other values (9) 237
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 179445
93.8%
Hangul 11919
 
6.2%
Number Forms 24
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23341
 
13.0%
e 12263
 
6.8%
a 10627
 
5.9%
o 8803
 
4.9%
t 8655
 
4.8%
i 8125
 
4.5%
n 7776
 
4.3%
r 7268
 
4.1%
c 6404
 
3.6%
s 6358
 
3.5%
Other values (56) 79825
44.5%
Hangul
ValueCountFrequency (%)
이 3782
31.7%
마 1883
15.8%
크 1883
15.8%
로 1883
15.8%
하 1749
14.7%
상 150
 
1.3%
원 40
 
0.3%
면 27
 
0.2%
터 24
 
0.2%
센 24
 
0.2%
Other values (41) 474
 
4.0%
Number Forms
ValueCountFrequency (%)
Ⅵ 24
100.0%

등록일
Date

Distinct1398
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2010-03-11 00:00:00
Maximum2021-08-31 00:00:00
2023-12-12T14:54:25.924550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:54:26.328992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T14:54:19.896112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:54:19.586756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:54:20.043439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:54:19.749190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:54:26.580203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수번호공정순번
접수번호1.0000.306
공정순번0.3061.000
2023-12-12T14:54:26.766294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수번호공정순번
접수번호1.0000.102
공정순번0.1021.000

Missing values

2023-12-12T14:54:20.201486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:54:20.330303image/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

접수번호제품번호공정순번장비코드장비명공정코드공정명등록일
1777220190114001I201901140011FE-MC50MOCVD V(epi)E1B005MOCVD V (epi)2019-01-14
67620100716004VL1007-0211FR-SF10Surface Scan/Profiler92100Metal Thickness Inspection2010-07-16
1129920141030001I201410300011FC-FI10FIB IC3A019FIB(TEM Preparation)2014-10-30
984820131105003I201311050039FR-WB40Liftoff Wet-Bench(R&D)R1B004Metal Liftoff2013-11-05
894120130416002I201304160021FC-AM20AFM IIIC3A001AFM2013-04-16
1449020161213003I2016121300333FL-TR20Track II (4-6 inch)L1B004PR Development(Track II) - 5마이크로 이하2016-12-13
671920120313001I2012031300114FR-WB10Acid Wet-Bench(R&D)R1B001Acid Wet Process2012-03-13
1729320181026001I201810260017FL-TR10Track I (2-3 inch)L1B015LOR Coating2018-10-26
1056620140428001I201404280011FC-SM10FE SEM IC3A002FE SEM2014-04-28
2114620200727002I202007270027FR-EB20E-beam evaporator II (R&D)R2A001Metal Evaporation2020-07-27
접수번호제품번호공정순번장비코드장비명공정코드공정명등록일
71420100716004VL1007-0247FR-SF10Surface Scan/Profiler92200Isolation Pattern Inspection2010-07-16
568920111101002I201111010021FC-FI10FIB IC3A018FIB(Imaging)2011-11-01
1582220171027001I201710270011FE-MC50MOCVD V(epi)E1B005MOCVD V (epi)2017-10-27
1281220160113002I201601130023FL-TR10Track I (2-3 inch)L1B001PR Coating (Track I) - 5마이크로 이하2016-01-13
1719720181022001I2018102200110FF-MW12Microwave asher (foundry): DualF4A003PR Descum2018-10-22
2281120210310004I202103100041FB-DI20Dicing Machine IIB1A007Dicing (Si, Glass)2021-03-10
799120121016003I201210160035FC-FI10FIB IC3A019FIB(TEM Preparation)2012-10-16
2126720200807002I2020080700226FR-WB40Liftoff Wet-Bench(R&D)R1B004Metal Liftoff2020-08-07
1884020190919002I2019091900219FL-WB10Develop Wet-bench(Litho)L3A002PR Development2019-09-19
173420101125004VL-1010-0133FR-WS20Alkali Wet-station(R&D)79200KOH Etch2010-11-25