Overview

Dataset statistics

Number of variables7
Number of observations236
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory56.6 B

Variable types

Categorical5
Text2

Dataset

Description- 공동실험실습관의 분석기기 및 보유장비 제공
Author부경대학교
URLhttps://www.data.go.kr/data/3075173/fileData.do

Alerts

캠퍼스(건물명) is highly overall correlated with 분석연구원 and 1 other fieldsHigh correlation
분석연구원 is highly overall correlated with 캠퍼스(건물명) and 1 other fieldsHigh correlation
단위 is highly overall correlated with 캠퍼스(건물명) and 1 other fieldsHigh correlation
구분 is highly imbalanced (59.6%)Imbalance

Reproduction

Analysis started2023-12-12 05:19:13.368081
Analysis finished2023-12-12 05:19:14.303841
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

캠퍼스(건물명)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
대연캠퍼스(장영실관)
197 
용당캠퍼스(산학협력관)
39 

Length

Max length12
Median length11
Mean length11.165254
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대연캠퍼스(장영실관)
2nd row대연캠퍼스(장영실관)
3rd row대연캠퍼스(장영실관)
4th row대연캠퍼스(장영실관)
5th row대연캠퍼스(장영실관)

Common Values

ValueCountFrequency (%)
대연캠퍼스(장영실관) 197
83.5%
용당캠퍼스(산학협력관) 39
 
16.5%

Length

2023-12-12T14:19:14.394637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:19:14.497763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대연캠퍼스(장영실관 197
83.5%
용당캠퍼스(산학협력관 39
 
16.5%

기기
Text

Distinct66
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2023-12-12T14:19:14.740818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length106
Median length63
Mean length56.525424
Min length15

Characters and Unicode

Total characters13340
Distinct characters204
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)7.6%

Sample

1st row가스크로마토그래피 열전도도 검출기Gas Chromatography TCD
2nd row가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer
3rd row가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer
4th row가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer
5th row가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer
ValueCountFrequency (%)
spectrometer 63
 
3.8%
x-ray 47
 
2.9%
mhz 40
 
2.4%
electron 37
 
2.3%
system 35
 
2.1%
chromatography 33
 
2.0%
analyzer 30
 
1.8%
scanning 27
 
1.6%
400 26
 
1.6%
emission 25
 
1.5%
Other values (221) 1276
77.9%
2023-12-12T14:19:15.206586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1403
 
10.5%
e 917
 
6.9%
r 749
 
5.6%
o 612
 
4.6%
t 569
 
4.3%
a 538
 
4.0%
n 454
 
3.4%
c 425
 
3.2%
i 423
 
3.2%
s 392
 
2.9%
Other values (194) 6858
51.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6859
51.4%
Other Letter 2581
 
19.3%
Uppercase Letter 1676
 
12.6%
Space Separator 1403
 
10.5%
Decimal Number 218
 
1.6%
Open Punctuation 185
 
1.4%
Close Punctuation 185
 
1.4%
Dash Punctuation 175
 
1.3%
Other Punctuation 58
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 190
 
7.4%
분 163
 
6.3%
석 124
 
4.8%
자 84
 
3.3%
전 82
 
3.2%
광 75
 
2.9%
로 59
 
2.3%
피 58
 
2.2%
마 57
 
2.2%
선 54
 
2.1%
Other values (130) 1635
63.3%
Lowercase Letter
ValueCountFrequency (%)
e 917
13.4%
r 749
10.9%
o 612
8.9%
t 569
 
8.3%
a 538
 
7.8%
n 454
 
6.6%
c 425
 
6.2%
i 423
 
6.2%
s 392
 
5.7%
m 341
 
5.0%
Other values (16) 1439
21.0%
Uppercase Letter
ValueCountFrequency (%)
M 248
14.8%
S 212
12.6%
T 174
10.4%
F 143
8.5%
R 131
 
7.8%
X 110
 
6.6%
C 94
 
5.6%
E 84
 
5.0%
P 65
 
3.9%
N 62
 
3.7%
Other values (12) 353
21.1%
Decimal Number
ValueCountFrequency (%)
0 129
59.2%
4 26
 
11.9%
1 23
 
10.6%
6 14
 
6.4%
7 10
 
4.6%
8 10
 
4.6%
2 6
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/ 46
79.3%
& 8
 
13.8%
. 4
 
6.9%
Open Punctuation
ValueCountFrequency (%)
( 176
95.1%
[ 9
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 176
95.1%
] 9
 
4.9%
Space Separator
ValueCountFrequency (%)
1403
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8535
64.0%
Hangul 2581
 
19.3%
Common 2224
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 190
 
7.4%
분 163
 
6.3%
석 124
 
4.8%
자 84
 
3.3%
전 82
 
3.2%
광 75
 
2.9%
로 59
 
2.3%
피 58
 
2.2%
마 57
 
2.2%
선 54
 
2.1%
Other values (130) 1635
63.3%
Latin
ValueCountFrequency (%)
e 917
 
10.7%
r 749
 
8.8%
o 612
 
7.2%
t 569
 
6.7%
a 538
 
6.3%
n 454
 
5.3%
c 425
 
5.0%
i 423
 
5.0%
s 392
 
4.6%
m 341
 
4.0%
Other values (38) 3115
36.5%
Common
ValueCountFrequency (%)
1403
63.1%
( 176
 
7.9%
) 176
 
7.9%
- 175
 
7.9%
0 129
 
5.8%
/ 46
 
2.1%
4 26
 
1.2%
1 23
 
1.0%
6 14
 
0.6%
7 10
 
0.4%
Other values (6) 46
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10759
80.7%
Hangul 2581
 
19.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1403
 
13.0%
e 917
 
8.5%
r 749
 
7.0%
o 612
 
5.7%
t 569
 
5.3%
a 538
 
5.0%
n 454
 
4.2%
c 425
 
4.0%
i 423
 
3.9%
s 392
 
3.6%
Other values (54) 4277
39.8%
Hangul
ValueCountFrequency (%)
기 190
 
7.4%
분 163
 
6.3%
석 124
 
4.8%
자 84
 
3.3%
전 82
 
3.2%
광 75
 
2.9%
로 59
 
2.3%
피 58
 
2.2%
마 57
 
2.2%
선 54
 
2.1%
Other values (130) 1635
63.3%

분석연구원
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
서용수
35 
심규성
34 
황인자
31 
유영철
27 
강순배
26 
Other values (4)
83 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서용수 35
14.8%
심규성 34
14.4%
황인자 31
13.1%
유영철 27
11.4%
강순배 26
11.0%
류호정 25
10.6%
홍순혁 20
8.5%
이누리 19
8.1%
김동우 19
8.1%

Length

2023-12-12T14:19:15.371878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:19:15.509463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서용수 35
14.8%
심규성 34
14.4%
황인자 31
13.1%
유영철 27
11.4%
강순배 26
11.0%
류호정 25
10.6%
홍순혁 20
8.5%
이누리 19
8.1%
김동우 19
8.1%

구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
분석의뢰
217 
직접사용
 
19

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직접사용
2nd row분석의뢰
3rd row분석의뢰
4th row분석의뢰
5th row분석의뢰

Common Values

ValueCountFrequency (%)
분석의뢰 217
91.9%
직접사용 19
 
8.1%

Length

2023-12-12T14:19:15.677761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:19:15.770761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분석의뢰 217
91.9%
직접사용 19
 
8.1%

항목
Text

Distinct150
Distinct (%)64.1%
Missing2
Missing (%)0.8%
Memory size2.0 KiB
2023-12-12T14:19:16.108779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length23
Mean length8.7735043
Min length2

Characters and Unicode

Total characters2053
Distinct characters182
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)40.2%

Sample

1st row기본
2nd row정성분석
3rd row정량분석
4th rowlibrary search
5th row정량분석(5성분 이상 추가)
ValueCountFrequency (%)
기본 13
 
3.3%
전처리 9
 
2.3%
추가 8
 
2.1%
image 7
 
1.8%
file 7
 
1.8%
library 7
 
1.8%
이상 7
 
1.8%
이내 6
 
1.5%
기기이용 6
 
1.5%
1개월 6
 
1.5%
Other values (176) 313
80.5%
2023-12-12T14:19:16.644218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
 
7.5%
e 72
 
3.5%
분 63
 
3.1%
( 60
 
2.9%
) 60
 
2.9%
a 57
 
2.8%
i 56
 
2.7%
기 55
 
2.7%
시 48
 
2.3%
t 47
 
2.3%
Other values (172) 1380
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 862
42.0%
Lowercase Letter 574
28.0%
Uppercase Letter 235
 
11.4%
Space Separator 155
 
7.5%
Decimal Number 73
 
3.6%
Open Punctuation 60
 
2.9%
Close Punctuation 60
 
2.9%
Other Punctuation 22
 
1.1%
Dash Punctuation 9
 
0.4%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
분 63
 
7.3%
기 55
 
6.4%
시 48
 
5.6%
석 43
 
5.0%
이 36
 
4.2%
정 29
 
3.4%
료 21
 
2.4%
성 20
 
2.3%
간 20
 
2.3%
본 20
 
2.3%
Other values (114) 507
58.8%
Lowercase Letter
ValueCountFrequency (%)
e 72
12.5%
a 57
9.9%
i 56
9.8%
t 47
 
8.2%
r 47
 
8.2%
l 40
 
7.0%
o 39
 
6.8%
n 30
 
5.2%
p 27
 
4.7%
s 23
 
4.0%
Other values (12) 136
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 36
15.3%
D 31
13.2%
M 25
10.6%
C 21
8.9%
P 19
8.1%
H 14
 
6.0%
I 13
 
5.5%
E 13
 
5.5%
F 12
 
5.1%
T 10
 
4.3%
Other values (10) 41
17.4%
Decimal Number
ValueCountFrequency (%)
1 27
37.0%
5 14
19.2%
0 9
 
12.3%
2 8
 
11.0%
3 7
 
9.6%
6 3
 
4.1%
8 2
 
2.7%
9 2
 
2.7%
4 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
/ 13
59.1%
, 9
40.9%
Space Separator
ValueCountFrequency (%)
155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 862
42.0%
Latin 809
39.4%
Common 382
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
분 63
 
7.3%
기 55
 
6.4%
시 48
 
5.6%
석 43
 
5.0%
이 36
 
4.2%
정 29
 
3.4%
료 21
 
2.4%
성 20
 
2.3%
간 20
 
2.3%
본 20
 
2.3%
Other values (114) 507
58.8%
Latin
ValueCountFrequency (%)
e 72
 
8.9%
a 57
 
7.0%
i 56
 
6.9%
t 47
 
5.8%
r 47
 
5.8%
l 40
 
4.9%
o 39
 
4.8%
S 36
 
4.4%
D 31
 
3.8%
n 30
 
3.7%
Other values (32) 354
43.8%
Common
ValueCountFrequency (%)
155
40.6%
( 60
 
15.7%
) 60
 
15.7%
1 27
 
7.1%
5 14
 
3.7%
/ 13
 
3.4%
, 9
 
2.4%
0 9
 
2.4%
- 9
 
2.4%
2 8
 
2.1%
Other values (6) 18
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1191
58.0%
Hangul 862
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
 
13.0%
e 72
 
6.0%
( 60
 
5.0%
) 60
 
5.0%
a 57
 
4.8%
i 56
 
4.7%
t 47
 
3.9%
r 47
 
3.9%
l 40
 
3.4%
o 39
 
3.3%
Other values (48) 558
46.9%
Hangul
ValueCountFrequency (%)
분 63
 
7.3%
기 55
 
6.4%
시 48
 
5.6%
석 43
 
5.0%
이 36
 
4.2%
정 29
 
3.4%
료 21
 
2.4%
성 20
 
2.3%
간 20
 
2.3%
본 20
 
2.3%
Other values (114) 507
58.8%

단위
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
시료
46 
개
33 
시간
31 
회
21 
원
13 
Other values (29)
92 

Length

Max length18
Median length12
Mean length2.8135593
Min length1

Unique

Unique11 ?
Unique (%)4.7%

Sample

1st row시간
2nd row원
3rd row원
4th row원
5th row원/peak

Common Values

ValueCountFrequency (%)
시료 46
19.5%
개 33
14.0%
시간 31
13.1%
회 21
8.9%
원 13
 
5.5%
- 11
 
4.7%
30분 10
 
4.2%
EA 8
 
3.4%
원소 8
 
3.4%
원/시료 7
 
3.0%
Other values (24) 48
20.3%

Length

2023-12-12T14:19:16.802325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
시료 47
17.6%
개 33
12.4%
시간 31
11.6%
회 21
 
7.9%
17
 
6.4%
원 14
 
5.2%
30분 10
 
3.7%
ea 8
 
3.0%
원소 8
 
3.0%
file 8
 
3.0%
Other values (30) 70
26.2%

외부
Categorical

Distinct38
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
30,000
33 
6,000
22 
15,000
17 
20,000
14 
10,000
 
13
Other values (33)
137 

Length

Max length7
Median length6
Mean length5.8220339
Min length1

Unique

Unique8 ?
Unique (%)3.4%

Sample

1st row-
2nd row45,000
3rd row50,000
4th row6,000
5th row45,000

Common Values

ValueCountFrequency (%)
30,000 33
 
14.0%
6,000 22
 
9.3%
15,000 17
 
7.2%
20,000 14
 
5.9%
10,000 13
 
5.5%
12,000 11
 
4.7%
9,000 11
 
4.7%
50,000 10
 
4.2%
100,000 8
 
3.4%
45,000 8
 
3.4%
Other values (28) 89
37.7%

Length

2023-12-12T14:19:16.950819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30,000 33
 
14.0%
6,000 22
 
9.3%
15,000 17
 
7.2%
20,000 14
 
5.9%
10,000 13
 
5.5%
12,000 11
 
4.7%
9,000 11
 
4.7%
50,000 10
 
4.2%
90,000 8
 
3.4%
na 8
 
3.4%
Other values (28) 89
37.7%

Correlations

2023-12-12T14:19:17.041362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
캠퍼스(건물명)기기분석연구원구분단위외부
캠퍼스(건물명)1.0001.0001.0000.1400.8000.613
기기1.0001.0001.0000.8710.9400.000
분석연구원1.0001.0001.0000.3290.9100.711
구분0.1400.8710.3291.0000.3700.000
단위0.8000.9400.9100.3701.0000.882
외부0.6130.0000.7110.0000.8821.000
2023-12-12T14:19:17.166121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
캠퍼스(건물명)단위구분외부분석연구원
캠퍼스(건물명)1.0000.6570.0900.4800.985
단위0.6571.0000.2910.3730.601
구분0.0900.2911.0000.0000.323
외부0.4800.3730.0001.0000.325
분석연구원0.9850.6010.3230.3251.000
2023-12-12T14:19:17.274128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
캠퍼스(건물명)분석연구원구분단위외부
캠퍼스(건물명)1.0000.9850.0900.6570.480
분석연구원0.9851.0000.3230.6010.325
구분0.0900.3231.0000.2910.000
단위0.6570.6010.2911.0000.373
외부0.4800.3250.0000.3731.000

Missing values

2023-12-12T14:19:14.093957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:19:14.244672image/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

캠퍼스(건물명)기기분석연구원구분항목단위외부
0대연캠퍼스(장영실관)가스크로마토그래피 열전도도 검출기Gas Chromatography TCD서용수직접사용기본시간-
1대연캠퍼스(장영실관)가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer서용수분석의뢰정성분석원45,000
2대연캠퍼스(장영실관)가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer서용수분석의뢰정량분석원50,000
3대연캠퍼스(장영실관)가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer서용수분석의뢰library search원6,000
4대연캠퍼스(장영실관)가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer서용수분석의뢰정량분석(5성분 이상 추가)원/peak45,000
5대연캠퍼스(장영실관)가스크로마토그래피 질량분석기(유해분석용) Gas Chromatography Mass Spectrometer서용수분석의뢰기타 전처리 등원/시료10,000
6대연캠퍼스(장영실관)가스크로마토그래피 텐덤 질량분석기(유해분석용) Gas Chromatography Tandem Mass Spectrometer(QQQ)서용수분석의뢰정성분석원45,000
7대연캠퍼스(장영실관)가스크로마토그래피 텐덤 질량분석기(유해분석용) Gas Chromatography Tandem Mass Spectrometer(QQQ)서용수분석의뢰정량분석원50,000
8대연캠퍼스(장영실관)가스크로마토그래피 텐덤 질량분석기(유해분석용) Gas Chromatography Tandem Mass Spectrometer(QQQ)서용수분석의뢰library search(5성분이상)원6,000
9대연캠퍼스(장영실관)가스크로마토그래피 텐덤 질량분석기(유해분석용) Gas Chromatography Tandem Mass Spectrometer(QQQ)서용수분석의뢰정량추가분석(5성분이상)원36,000
캠퍼스(건물명)기기분석연구원구분항목단위외부
226용당캠퍼스(산학협력관)X-선 회절분석기 (용당) X-Ray Diffractometer (용당)김동우분석의뢰scintillation counter detector30분21,000
227용당캠퍼스(산학협력관)X-선 회절분석기 (용당) X-Ray Diffractometer (용당)김동우분석의뢰high speed detector30분21,000
228용당캠퍼스(산학협력관)X-선 회절분석기 (용당) X-Ray Diffractometer (용당)김동우분석의뢰scintillation counter detector(초과측정시간30분당)30분12,000
229용당캠퍼스(산학협력관)X-선 회절분석기 (용당) X-Ray Diffractometer (용당)김동우분석의뢰high speed detector(초과측정시간30분당)30분12,000
230용당캠퍼스(산학협력관)X-선 회절분석기 (용당) X-Ray Diffractometer (용당)김동우분석의뢰Data 검색-9,000
231용당캠퍼스(산학협력관)X-선 회절분석기 (용당) X-Ray Diffractometer (용당)김동우분석의뢰시료전처리(분말작업)시료6,000
232대연캠퍼스(장영실관)X-선 회절분석기(고분해능) X-Ray Diffractometer류호정분석의뢰시료전처리(분말작업)시료6,000
233대연캠퍼스(장영실관)X-선 회절분석기(고분해능) X-Ray Diffractometer류호정분석의뢰일반분석시료21,000
234대연캠퍼스(장영실관)X-선 회절분석기(고분해능) X-Ray Diffractometer류호정분석의뢰초과측정시간 30분당시료12,000
235대연캠퍼스(장영실관)X-선 회절분석기(고분해능) X-Ray Diffractometer류호정분석의뢰Data 검색시료9,000