Overview

Dataset statistics

Number of variables7
Number of observations126
Missing cells116
Missing cells (%)13.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory59.0 B

Variable types

Numeric2
Categorical2
Text3

Dataset

Description한국세라믹기술원 세라믹소재정보은행의 단위변환 정보입니다. 금속/화학/세라믹 통합사이트 주소: http://www.matcenter.org 담당자: 김경훈 수석
Author한국세라믹기술원
URLhttps://www.data.go.kr/data/15072085/fileData.do

Alerts

단위그룹명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
기준단위 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 is highly overall correlated with 기준단위 and 1 other fieldsHigh correlation
구분한글명 has 54 (42.9%) missing valuesMissing
구분영문명 has 58 (46.0%) missing valuesMissing
단위변환값 has 3 (2.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:21:13.135955
Analysis finished2023-12-12 20:21:14.323462
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct126
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.031746
Minimum1
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T05:21:14.413476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.25
Q135.25
median66.5
Q3101.75
95-th percentile126.75
Maximum133
Range132
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation38.789264
Coefficient of variation (CV)0.57016417
Kurtosis-1.2201498
Mean68.031746
Median Absolute Deviation (MAD)33.5
Skewness-0.026759148
Sum8572
Variance1504.607
MonotonicityNot monotonic
2023-12-13T05:21:14.591004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59 1
 
0.8%
19 1
 
0.8%
32 1
 
0.8%
31 1
 
0.8%
30 1
 
0.8%
29 1
 
0.8%
28 1
 
0.8%
27 1
 
0.8%
26 1
 
0.8%
25 1
 
0.8%
Other values (116) 116
92.1%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
133 1
0.8%
132 1
0.8%
131 1
0.8%
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%

기준단위
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Pa
19 
m
14 
ℓ
13 
m/s
12 
J
10 
Other values (11)
58 

Length

Max length6
Median length5
Mean length2.2222222
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowW/m·K
2nd rowg/cm³
3rd rowg/cm³
4th rowg/cm³
5th rowg/cm³

Common Values

ValueCountFrequency (%)
Pa 19
15.1%
m 14
11.1%
ℓ 13
10.3%
m/s 12
9.5%
J 10
7.9%
g 9
7.1%
N 9
7.1%
W/m·K 7
 
5.6%
m² 7
 
5.6%
g/cm³ 6
 
4.8%
Other values (6) 20
15.9%

Length

2023-12-13T05:21:14.766930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pa 19
15.1%
m 14
11.1%
ℓ 13
10.3%
m/s 12
9.5%
j 10
7.9%
g 9
7.1%
n 9
7.1%
w/m·k 7
 
5.6%
m² 7
 
5.6%
g/cm³ 6
 
4.8%
Other values (6) 20
15.9%

변환단위
Text

Distinct125
Distinct (%)100.0%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2023-12-13T05:21:15.116789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length3.792
Min length1

Characters and Unicode

Total characters474
Distinct characters55
Distinct categories7 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)100.0%

Sample

1st rowlbf/s·℉
2nd rowlb/ft³
3rd rowlb/in³
4th rowlb/Usgal
5th rowkg/m³
ValueCountFrequency (%)
a 2
 
1.6%
oz 2
 
1.6%
dyne/cm² 1
 
0.8%
torr 1
 
0.8%
bar 1
 
0.8%
atm 1
 
0.8%
hpa 1
 
0.8%
mpa 1
 
0.8%
kpa 1
 
0.8%
pa 1
 
0.8%
Other values (115) 115
90.6%
2023-12-13T05:21:15.668131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
m 45
 
9.5%
/ 41
 
8.6%
· 30
 
6.3%
g 25
 
5.3%
k 25
 
5.3%
l 24
 
5.1%
c 23
 
4.9%
a 23
 
4.9%
t 20
 
4.2%
s 19
 
4.0%
Other values (45) 199
42.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 312
65.8%
Other Punctuation 73
 
15.4%
Uppercase Letter 43
 
9.1%
Other Number 23
 
4.9%
Other Symbol 14
 
3.0%
Other Letter 7
 
1.5%
Space Separator 2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 45
14.4%
g 25
 
8.0%
k 25
 
8.0%
l 24
 
7.7%
c 23
 
7.4%
a 23
 
7.4%
t 20
 
6.4%
s 19
 
6.1%
f 19
 
6.1%
h 17
 
5.4%
Other values (13) 72
23.1%
Uppercase Letter
ValueCountFrequency (%)
P 7
16.3%
K 6
14.0%
C 5
11.6%
H 4
9.3%
W 4
9.3%
S 4
9.3%
N 3
7.0%
O 2
 
4.7%
J 2
 
4.7%
U 2
 
4.7%
Other values (3) 4
9.3%
Other Symbol
ValueCountFrequency (%)
° 5
35.7%
℉ 4
28.6%
㎡ 2
 
14.3%
㎗ 1
 
7.1%
㎖ 1
 
7.1%
㎤ 1
 
7.1%
Other Letter
ValueCountFrequency (%)
里 2
28.6%
홉 1
14.3%
돈 1
14.3%
海 1
14.3%
間 1
14.3%
尺 1
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 41
56.2%
· 30
41.1%
. 2
 
2.7%
Other Number
ValueCountFrequency (%)
² 13
56.5%
³ 8
34.8%
₂ 2
 
8.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 353
74.5%
Common 113
 
23.8%
Han 5
 
1.1%
Hangul 2
 
0.4%
Greek 1
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 45
 
12.7%
g 25
 
7.1%
k 25
 
7.1%
l 24
 
6.8%
c 23
 
6.5%
a 23
 
6.5%
t 20
 
5.7%
s 19
 
5.4%
f 19
 
5.4%
h 17
 
4.8%
Other values (24) 113
32.0%
Common
ValueCountFrequency (%)
/ 41
36.3%
· 30
26.5%
² 13
 
11.5%
³ 8
 
7.1%
° 5
 
4.4%
℉ 4
 
3.5%
㎡ 2
 
1.8%
₂ 2
 
1.8%
2
 
1.8%
. 2
 
1.8%
Other values (4) 4
 
3.5%
Han
ValueCountFrequency (%)
里 2
40.0%
海 1
20.0%
間 1
20.0%
尺 1
20.0%
Hangul
ValueCountFrequency (%)
홉 1
50.0%
돈 1
50.0%
Greek
ValueCountFrequency (%)
μ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 398
84.0%
None 59
 
12.4%
Letterlike Symbols 5
 
1.1%
CJK Compat 5
 
1.1%
CJK 5
 
1.1%
Hangul 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 45
 
11.3%
/ 41
 
10.3%
g 25
 
6.3%
k 25
 
6.3%
l 24
 
6.0%
c 23
 
5.8%
a 23
 
5.8%
t 20
 
5.0%
s 19
 
4.8%
f 19
 
4.8%
Other values (27) 134
33.7%
None
ValueCountFrequency (%)
· 30
50.8%
² 13
22.0%
³ 8
 
13.6%
° 5
 
8.5%
₂ 2
 
3.4%
μ 1
 
1.7%
Letterlike Symbols
ValueCountFrequency (%)
℉ 4
80.0%
ℓ 1
 
20.0%
CJK Compat
ValueCountFrequency (%)
㎡ 2
40.0%
㎗ 1
20.0%
㎖ 1
20.0%
㎤ 1
20.0%
CJK
ValueCountFrequency (%)
里 2
40.0%
海 1
20.0%
間 1
20.0%
尺 1
20.0%
Hangul
ValueCountFrequency (%)
홉 1
50.0%
돈 1
50.0%

구분한글명
Text

MISSING 

Distinct70
Distinct (%)97.2%
Missing54
Missing (%)42.9%
Memory size1.1 KiB
2023-12-13T05:21:15.976975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length3.3333333
Min length1

Characters and Unicode

Total characters240
Distinct characters79
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)94.4%

Sample

1st row절대온도
2nd row화씨온도
3rd row섭씨온도
4th row미터
5th row킬로미터
ValueCountFrequency (%)
톤 2
 
2.6%
파스칼 2
 
2.6%
온스 2
 
2.6%
새컨드 2
 
2.6%
주울 1
 
1.3%
밀리바 1
 
1.3%
파운드 1
 
1.3%
아르 1
 
1.3%
뉴턴 1
 
1.3%
에이커 1
 
1.3%
Other values (62) 62
81.6%
2023-12-13T05:21:16.432028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 14
 
5.8%
스 12
 
5.0%
미 11
 
4.6%
리 11
 
4.6%
제 10
 
4.2%
곱 10
 
4.2%
로 10
 
4.2%
트 7
 
2.9%
킬 7
 
2.9%
칼 7
 
2.9%
Other values (69) 141
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 236
98.3%
Space Separator 4
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 14
 
5.9%
스 12
 
5.1%
미 11
 
4.7%
리 11
 
4.7%
제 10
 
4.2%
곱 10
 
4.2%
로 10
 
4.2%
트 7
 
3.0%
킬 7
 
3.0%
칼 7
 
3.0%
Other values (68) 137
58.1%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 236
98.3%
Common 4
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 14
 
5.9%
스 12
 
5.1%
미 11
 
4.7%
리 11
 
4.7%
제 10
 
4.2%
곱 10
 
4.2%
로 10
 
4.2%
트 7
 
3.0%
킬 7
 
3.0%
칼 7
 
3.0%
Other values (68) 137
58.1%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 236
98.3%
ASCII 4
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 14
 
5.9%
스 12
 
5.1%
미 11
 
4.7%
리 11
 
4.7%
제 10
 
4.2%
곱 10
 
4.2%
로 10
 
4.2%
트 7
 
3.0%
킬 7
 
3.0%
칼 7
 
3.0%
Other values (68) 137
58.1%
ASCII
ValueCountFrequency (%)
4
100.0%

구분영문명
Text

MISSING 

Distinct66
Distinct (%)97.1%
Missing58
Missing (%)46.0%
Memory size1.1 KiB
2023-12-13T05:21:16.675199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length8.9852941
Min length1

Characters and Unicode

Total characters611
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)94.1%

Sample

1st rowKelvin
2nd rowFahrenheit
3rd rowCelsius
4th rowmeter
5th rowkilometer
ValueCountFrequency (%)
square 6
 
6.5%
cubic 6
 
6.5%
pascal 6
 
6.5%
centimeter 3
 
3.2%
yard 3
 
3.2%
meter 3
 
3.2%
inch 3
 
3.2%
foot 2
 
2.2%
per 2
 
2.2%
pound-force 2
 
2.2%
Other values (53) 57
61.3%
2023-12-13T05:21:17.128787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 78
12.8%
r 51
 
8.3%
i 46
 
7.5%
a 45
 
7.4%
c 41
 
6.7%
t 40
 
6.5%
o 39
 
6.4%
l 34
 
5.6%
28
 
4.6%
s 28
 
4.6%
Other values (28) 181
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 554
90.7%
Space Separator 28
 
4.6%
Uppercase Letter 24
 
3.9%
Dash Punctuation 4
 
0.7%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 78
14.1%
r 51
9.2%
i 46
 
8.3%
a 45
 
8.1%
c 41
 
7.4%
t 40
 
7.2%
o 39
 
7.0%
l 34
 
6.1%
s 28
 
5.1%
n 25
 
4.5%
Other values (14) 127
22.9%
Uppercase Letter
ValueCountFrequency (%)
P 9
37.5%
M 4
16.7%
C 2
 
8.3%
S 2
 
8.3%
T 1
 
4.2%
A 1
 
4.2%
N 1
 
4.2%
F 1
 
4.2%
L 1
 
4.2%
K 1
 
4.2%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 578
94.6%
Common 33
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 78
13.5%
r 51
 
8.8%
i 46
 
8.0%
a 45
 
7.8%
c 41
 
7.1%
t 40
 
6.9%
o 39
 
6.7%
l 34
 
5.9%
s 28
 
4.8%
n 25
 
4.3%
Other values (25) 151
26.1%
Common
ValueCountFrequency (%)
28
84.8%
- 4
 
12.1%
. 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 611
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 78
12.8%
r 51
 
8.3%
i 46
 
7.5%
a 45
 
7.4%
c 41
 
6.7%
t 40
 
6.5%
o 39
 
6.4%
l 34
 
5.6%
28
 
4.6%
s 28
 
4.6%
Other values (28) 181
29.6%

단위변환값
Real number (ℝ)

MISSING 

Distinct69
Distinct (%)56.1%
Missing3
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean81392558
Minimum1 × 10-9
Maximum1 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-13T05:21:17.301670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1 × 10-9
5-th percentile1 × 10-6
Q10.0023755
median1
Q33.45
95-th percentile10000
Maximum1 × 1010
Range1 × 1010
Interquartile range (IQR)3.4476245

Descriptive statistics

Standard deviation9.0166175 × 108
Coefficient of variation (CV)11.077938
Kurtosis122.99975
Mean81392558
Median Absolute Deviation (MAD)0.999
Skewness11.090519
Sum1.0011285 × 1010
Variance8.1299391 × 1017
MonotonicityNot monotonic
2023-12-13T05:21:17.511675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 27
21.4%
1000.0 7
 
5.6%
0.001 5
 
4.0%
10.0 4
 
3.2%
1e-06 4
 
3.2%
0.000238846 3
 
2.4%
0.1019716 3
 
2.4%
0.01 3
 
2.4%
39.370079 2
 
1.6%
3.28084 2
 
1.6%
Other values (59) 63
50.0%
(Missing) 3
 
2.4%
ValueCountFrequency (%)
1e-09 1
 
0.8%
1.02e-07 1
 
0.8%
2.78e-07 1
 
0.8%
3.72e-07 1
 
0.8%
1e-06 4
3.2%
9.87e-06 1
 
0.8%
1e-05 1
 
0.8%
1.0197e-05 2
1.6%
0.0001 1
 
0.8%
0.000145 1
 
0.8%
ValueCountFrequency (%)
10000000000.0 1
 
0.8%
10000000.0 1
 
0.8%
1000000.0 1
 
0.8%
141732.283 1
 
0.8%
100000.0 1
 
0.8%
11811.0236 1
 
0.8%
10000.0 2
 
1.6%
3600.0 1
 
0.8%
1000.0 7
5.6%
100.0 1
 
0.8%

단위그룹명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
압력
19 
길이
14 
부피
13 
속도
12 
열량·에너지
10 
Other values (11)
58 

Length

Max length6
Median length2
Mean length2.4285714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row열전도율
2nd row밀도
3rd row밀도
4th row밀도
5th row밀도

Common Values

ValueCountFrequency (%)
압력 19
15.1%
길이 14
11.1%
부피 13
10.3%
속도 12
9.5%
열량·에너지 10
7.9%
질량 9
7.1%
힘 9
7.1%
열전도율 7
 
5.6%
넓이 7
 
5.6%
밀도 6
 
4.8%
Other values (6) 20
15.9%

Length

2023-12-13T05:21:17.699372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
압력 19
15.1%
길이 14
11.1%
부피 13
10.3%
속도 12
9.5%
열량·에너지 10
7.9%
질량 9
7.1%
힘 9
7.1%
열전도율 7
 
5.6%
넓이 7
 
5.6%
밀도 6
 
4.8%
Other values (6) 20
15.9%

Interactions

2023-12-13T05:21:13.711120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:21:13.526668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:21:13.811211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:21:13.614869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:21:18.146572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번기준단위구분한글명구분영문명단위변환값단위그룹명
순번1.0000.9620.8560.9620.0000.962
기준단위0.9621.0000.9661.0000.0001.000
구분한글명0.8560.9661.0001.0001.0000.966
구분영문명0.9621.0001.0001.0001.0001.000
단위변환값0.0000.0001.0001.0001.0000.000
단위그룹명0.9621.0000.9661.0000.0001.000
2023-12-13T05:21:18.264927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단위그룹명기준단위
단위그룹명1.0001.000
기준단위1.0001.000
2023-12-13T05:21:18.358734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단위변환값기준단위단위그룹명
순번1.0000.0920.8010.801
단위변환값0.0921.0000.0000.000
기준단위0.8010.0001.0001.000
단위그룹명0.8010.0001.0001.000

Missing values

2023-12-13T05:21:13.974748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:21:14.118701image/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.
2023-12-13T05:21:14.248409image/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

순번기준단위변환단위구분한글명구분영문명단위변환값단위그룹명
059W/m·Klbf/s·℉<NA><NA>1.0열전도율
160g/cm³lb/ft³<NA><NA>1.0밀도
261g/cm³lb/in³<NA><NA>1.0밀도
362g/cm³lb/Usgal<NA><NA>1000.0밀도
463g/cm³kg/m³<NA><NA>62.42797밀도
564g/cm³g/l<NA><NA>0.036127밀도
665g/cm³g/㎤<NA><NA>1.0밀도
776°CK절대온도Kelvin<NA>온도
877°C℉화씨온도Fahrenheit<NA>온도
978°C°C섭씨온도Celsius<NA>온도
순번기준단위변환단위구분한글명구분영문명단위변환값단위그룹명
11649J/kg·Kcal/g·°C<NA><NA>0.000239비열
11750J/kg·Kkcal/kg·°C<NA><NA>0.000239비열
11851W/m²·KW/m²·K<NA><NA>1.0열전달계수
11952W/m²·Kkcal/h·m²·°C<NA><NA>0.859845열전달계수
12053W/m·KW/m·K<NA><NA>1.0열전도율
12154W/m·Kkcal/h·m·°C<NA><NA>0.859845열전도율
12255W/m·KBtu/h·ft·℉<NA><NA>0.5779열전도율
12356W/m·Kcal/s·cm·K<NA><NA>1.0열전도율
12457W/m·Kerg/s·cm·K<NA><NA>1.0열전도율
12558W/m·Kpdl/s·ft·℉<NA><NA>1.0열전도율