Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory45.9 B

Variable types

Text2
Categorical2
DateTime1

Dataset

Description경기도 업사이클플라자 보유 장비 목록
Author경기환경에너지진흥원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=HRK416ZVMFSRE9D5UKAX32811414&infSeq=1

Alerts

데이터기준일자 has constant value ""Constant
구분 has unique valuesUnique
장비명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:28:10.773548
Analysis finished2023-12-10 21:28:11.098947
Duration0.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T06:28:11.213334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.8518519
Min length3

Characters and Unicode

Total characters158
Distinct characters88
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowFDM 3D프린터
2nd rowDLP 3D 프린터
3rd rowCNC라우터
4th row레이저커팅기
5th row사절 미싱기
ValueCountFrequency (%)
미싱기 3
 
7.5%
fdm 1
 
2.5%
uv프린터 1
 
2.5%
테이블쏘 1
 
2.5%
밴드쏘 1
 
2.5%
스크롤쏘 1
 
2.5%
집진기 1
 
2.5%
컴퓨터 1
 
2.5%
자수기 1
 
2.5%
스캔앤컷 1
 
2.5%
Other values (28) 28
70.0%
2023-12-11T06:28:11.531079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
8.2%
기 8
 
5.1%
터 7
 
4.4%
스 5
 
3.2%
드 5
 
3.2%
프 5
 
3.2%
미 4
 
2.5%
린 4
 
2.5%
D 4
 
2.5%
크 3
 
1.9%
Other values (78) 100
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129
81.6%
Space Separator 13
 
8.2%
Uppercase Letter 13
 
8.2%
Decimal Number 3
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 8
 
6.2%
터 7
 
5.4%
스 5
 
3.9%
드 5
 
3.9%
프 5
 
3.9%
미 4
 
3.1%
린 4
 
3.1%
크 3
 
2.3%
팅 3
 
2.3%
싱 3
 
2.3%
Other values (66) 82
63.6%
Uppercase Letter
ValueCountFrequency (%)
D 4
30.8%
C 2
15.4%
V 1
 
7.7%
U 1
 
7.7%
F 1
 
7.7%
M 1
 
7.7%
L 1
 
7.7%
P 1
 
7.7%
N 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
3 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129
81.6%
Common 16
 
10.1%
Latin 13
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 8
 
6.2%
터 7
 
5.4%
스 5
 
3.9%
드 5
 
3.9%
프 5
 
3.9%
미 4
 
3.1%
린 4
 
3.1%
크 3
 
2.3%
팅 3
 
2.3%
싱 3
 
2.3%
Other values (66) 82
63.6%
Latin
ValueCountFrequency (%)
D 4
30.8%
C 2
15.4%
V 1
 
7.7%
U 1
 
7.7%
F 1
 
7.7%
M 1
 
7.7%
L 1
 
7.7%
P 1
 
7.7%
N 1
 
7.7%
Common
ValueCountFrequency (%)
13
81.2%
3 2
 
12.5%
1 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129
81.6%
ASCII 29
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
44.8%
D 4
 
13.8%
3 2
 
6.9%
C 2
 
6.9%
V 1
 
3.4%
U 1
 
3.4%
F 1
 
3.4%
1 1
 
3.4%
M 1
 
3.4%
L 1
 
3.4%
Other values (2) 2
 
6.9%
Hangul
ValueCountFrequency (%)
기 8
 
6.2%
터 7
 
5.4%
스 5
 
3.9%
드 5
 
3.9%
프 5
 
3.9%
미 4
 
3.1%
린 4
 
3.1%
크 3
 
2.3%
팅 3
 
2.3%
싱 3
 
2.3%
Other values (66) 82
63.6%

장비명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-11T06:28:11.720467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length11
Mean length9.4074074
Min length5

Characters and Unicode

Total characters254
Distinct characters63
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st rowULTIMAKER 3
2nd rowFabPro 1000
3rd rowMDX-50
4th rowSpeedy400
5th rowKM-640BL-7
ValueCountFrequency (%)
freejet 2
 
5.1%
ultimaker 1
 
2.6%
330tx 1
 
2.6%
220v 1
 
2.6%
△ 1
 
2.6%
1728[rpm 1
 
2.6%
pr1050x 1
 
2.6%
sdx-1200 1
 
2.6%
330uv 1
 
2.6%
수직강하형 1
 
2.6%
Other values (28) 28
71.8%
2023-12-11T06:28:12.044102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28
 
11.0%
1 14
 
5.5%
- 14
 
5.5%
2 13
 
5.1%
12
 
4.7%
4 11
 
4.3%
D 10
 
3.9%
5 9
 
3.5%
S 9
 
3.5%
P 9
 
3.5%
Other values (53) 125
49.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97
38.2%
Uppercase Letter 87
34.3%
Lowercase Letter 23
 
9.1%
Dash Punctuation 14
 
5.5%
Other Letter 14
 
5.5%
Space Separator 12
 
4.7%
Other Punctuation 4
 
1.6%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%
Other Symbol 1
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
D 10
 
11.5%
S 9
 
10.3%
P 9
 
10.3%
M 7
 
8.0%
B 5
 
5.7%
T 5
 
5.7%
L 4
 
4.6%
W 4
 
4.6%
U 4
 
4.6%
X 4
 
4.6%
Other values (13) 26
29.9%
Other Letter
ValueCountFrequency (%)
전 2
14.3%
직 1
 
7.1%
기 1
 
7.1%
성 1
 
7.1%
은 1
 
7.1%
스 1
 
7.1%
레 1
 
7.1%
프 1
 
7.1%
사 1
 
7.1%
형 1
 
7.1%
Other values (3) 3
21.4%
Lowercase Letter
ValueCountFrequency (%)
e 8
34.8%
r 3
 
13.0%
t 2
 
8.7%
j 2
 
8.7%
f 2
 
8.7%
p 1
 
4.3%
d 1
 
4.3%
y 1
 
4.3%
b 1
 
4.3%
o 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
0 28
28.9%
1 14
14.4%
2 13
13.4%
4 11
 
11.3%
5 9
 
9.3%
3 7
 
7.2%
6 5
 
5.2%
7 5
 
5.2%
8 4
 
4.1%
9 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Other Symbol
ValueCountFrequency (%)
△ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
51.2%
Latin 110
43.3%
Hangul 14
 
5.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
D 10
 
9.1%
S 9
 
8.2%
P 9
 
8.2%
e 8
 
7.3%
M 7
 
6.4%
B 5
 
4.5%
T 5
 
4.5%
L 4
 
3.6%
W 4
 
3.6%
U 4
 
3.6%
Other values (24) 45
40.9%
Common
ValueCountFrequency (%)
0 28
21.5%
1 14
10.8%
- 14
10.8%
2 13
10.0%
12
9.2%
4 11
 
8.5%
5 9
 
6.9%
3 7
 
5.4%
6 5
 
3.8%
7 5
 
3.8%
Other values (6) 12
9.2%
Hangul
ValueCountFrequency (%)
전 2
14.3%
직 1
 
7.1%
기 1
 
7.1%
성 1
 
7.1%
은 1
 
7.1%
스 1
 
7.1%
레 1
 
7.1%
프 1
 
7.1%
사 1
 
7.1%
형 1
 
7.1%
Other values (3) 3
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 239
94.1%
Hangul 14
 
5.5%
Geometric Shapes 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28
 
11.7%
1 14
 
5.9%
- 14
 
5.9%
2 13
 
5.4%
12
 
5.0%
4 11
 
4.6%
D 10
 
4.2%
5 9
 
3.8%
S 9
 
3.8%
P 9
 
3.8%
Other values (39) 110
46.0%
Hangul
ValueCountFrequency (%)
전 2
14.3%
직 1
 
7.1%
기 1
 
7.1%
성 1
 
7.1%
은 1
 
7.1%
스 1
 
7.1%
레 1
 
7.1%
프 1
 
7.1%
사 1
 
7.1%
형 1
 
7.1%
Other values (3) 3
21.4%
Geometric Shapes
ValueCountFrequency (%)
△ 1
100.0%

수량
Categorical

Distinct4
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
1
21 
2
3 
5
 
2
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.7%

Sample

1st row3
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 21
77.8%
2 3
 
11.1%
5 2
 
7.4%
3 1
 
3.7%

Length

2023-12-11T06:28:12.222157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:28:12.346691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
77.8%
2 3
 
11.1%
5 2
 
7.4%
3 1
 
3.7%

위치
Categorical

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
순환창작소
17 
창작의 광장
10 

Length

Max length6
Median length5
Mean length5.3703704
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row창작의 광장
2nd row창작의 광장
3rd row순환창작소
4th row순환창작소
5th row창작의 광장

Common Values

ValueCountFrequency (%)
순환창작소 17
63.0%
창작의 광장 10
37.0%

Length

2023-12-11T06:28:12.475856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:28:12.595349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
순환창작소 17
45.9%
창작의 10
27.0%
광장 10
27.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
Minimum2023-07-05 00:00:00
Maximum2023-07-05 00:00:00
2023-12-11T06:28:12.674626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:28:12.760137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-11T06:28:12.833687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분장비명수량위치
구분1.0001.0001.0001.000
장비명1.0001.0001.0001.000
수량1.0001.0001.0000.325
위치1.0001.0000.3251.000
2023-12-11T06:28:13.176624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위치수량
위치1.0000.198
수량0.1981.000
2023-12-11T06:28:13.248206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량위치
수량1.0000.198
위치0.1981.000

Missing values

2023-12-11T06:28:10.984082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:28:11.068028image/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

구분장비명수량위치데이터기준일자
0FDM 3D프린터ULTIMAKER 33창작의 광장2023-07-05
1DLP 3D 프린터FabPro 10001창작의 광장2023-07-05
2CNC라우터MDX-501순환창작소2023-07-05
3레이저커팅기Speedy4001순환창작소2023-07-05
4사절 미싱기KM-640BL-72창작의 광장2023-07-05
5가죽 미싱기DNU-15411창작의 광장2023-07-05
6오버로크 미싱기MO-6814S1창작의 광장2023-07-05
7범용밀링선반JWL-12211순환창작소2023-07-05
8컷팅플로터CE6000-120 PLUS1순환창작소2023-07-05
9슬라이딩 각도 절단기DWS7801순환창작소2023-07-05
구분장비명수량위치데이터기준일자
17컴퓨터 자수기PR1050X1창작의 광장2023-07-05
18스캔앤컷SDX-12001창작의 광장2023-07-05
19UV프린터freejet 330UV1창작의 광장2023-07-05
20잉크젯프린터freejet 330TX1창작의 광장2023-07-05
21평판 열프레스기수직강하형 450 전사프레스2창작의 광장2023-07-05
22우드버닝툴TBP-HM4015순환창작소2023-07-05
23드릴링머신TT-231순환창작소2023-07-05
24스파팅머신PDA3801순환창작소2023-07-05
25스팀다리미은성전기, ES-941순환창작소2023-07-05
26바큠보드DJB-21순환창작소2023-07-05