Overview

Dataset statistics

Number of variables4
Number of observations141
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory32.9 B

Variable types

Categorical2
Text2

Dataset

Description전라남도 순천시 대형폐기물 품목별 수수료에 대한 데이터로 대형폐기물 대분류, 품목, 규격, 금액 등의 항목을 제공합니다.
Author전라남도 순천시
URLhttps://www.data.go.kr/data/15084135/fileData.do

Reproduction

Analysis started2023-12-12 08:58:18.336983
Analysis finished2023-12-12 08:58:19.022035
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대분류
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
가전제품
49 
가구류
47 
기타
45 

Length

Max length4
Median length3
Mean length3.0283688
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가전제품 49
34.8%
가구류 47
33.3%
기타 45
31.9%

Length

2023-12-12T17:58:19.145699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:58:19.334173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가전제품 49
34.8%
가구류 47
33.3%
기타 45
31.9%

품목
Text

Distinct81
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T17:58:19.762259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length3.6099291
Min length2

Characters and Unicode

Total characters509
Distinct characters151
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)27.7%

Sample

1st row돌침대
2nd row돌침대
3rd row돌침대 받침
4th row돌침대 받침
5th row매트리스
ValueCountFrequency (%)
냉장고 5
 
3.3%
쇼파 5
 
3.3%
컴퓨터 4
 
2.6%
돌침대 4
 
2.6%
및 4
 
2.6%
전축(오디오 3
 
2.0%
침대 3
 
2.0%
가방 3
 
2.0%
보일러통 3
 
2.0%
에어컨 3
 
2.0%
Other values (75) 116
75.8%
2023-12-12T17:58:20.435012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 30
 
5.9%
장 24
 
4.7%
대 13
 
2.6%
13
 
2.6%
오 11
 
2.2%
고 10
 
2.0%
침 10
 
2.0%
) 10
 
2.0%
전 10
 
2.0%
가 10
 
2.0%
Other values (141) 368
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
93.3%
Space Separator 13
 
2.6%
Close Punctuation 10
 
2.0%
Open Punctuation 10
 
2.0%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 30
 
6.3%
장 24
 
5.1%
대 13
 
2.7%
오 11
 
2.3%
고 10
 
2.1%
침 10
 
2.1%
전 10
 
2.1%
가 10
 
2.1%
스 9
 
1.9%
이 8
 
1.7%
Other values (137) 340
71.6%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
93.3%
Common 34
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 30
 
6.3%
장 24
 
5.1%
대 13
 
2.7%
오 11
 
2.3%
고 10
 
2.1%
침 10
 
2.1%
전 10
 
2.1%
가 10
 
2.1%
스 9
 
1.9%
이 8
 
1.7%
Other values (137) 340
71.6%
Common
ValueCountFrequency (%)
13
38.2%
) 10
29.4%
( 10
29.4%
2 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
93.3%
ASCII 34
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 30
 
6.3%
장 24
 
5.1%
대 13
 
2.7%
오 11
 
2.3%
고 10
 
2.1%
침 10
 
2.1%
전 10
 
2.1%
가 10
 
2.1%
스 9
 
1.9%
이 8
 
1.7%
Other values (137) 340
71.6%
ASCII
ValueCountFrequency (%)
13
38.2%
) 10
29.4%
( 10
29.4%
2 1
 
2.9%

규격
Text

Distinct78
Distinct (%)55.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T17:58:20.855543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length5.6524823
Min length2

Characters and Unicode

Total characters797
Distinct characters121
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)48.9%

Sample

1st row2인용(받침 별도)
2nd row1인용(받침 별도)
3rd row2인용(돌침대 별도)
4th row1인용(돌침대 별도)
5th row1인용(침대 별도)
ValueCountFrequency (%)
개당 19
 
8.6%
대형 15
 
6.8%
모든 15
 
6.8%
규격 15
 
6.8%
소형 14
 
6.3%
이상 14
 
6.3%
미만 11
 
5.0%
별도 8
 
3.6%
1m 6
 
2.7%
중형 5
 
2.3%
Other values (72) 100
45.0%
2023-12-12T17:58:21.453220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
10.2%
형 41
 
5.1%
이 32
 
4.0%
0 31
 
3.9%
m 28
 
3.5%
대 26
 
3.3%
( 25
 
3.1%
) 25
 
3.1%
1 25
 
3.1%
상 23
 
2.9%
Other values (111) 460
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
60.6%
Decimal Number 109
 
13.7%
Space Separator 81
 
10.2%
Lowercase Letter 49
 
6.1%
Open Punctuation 25
 
3.1%
Close Punctuation 25
 
3.1%
Uppercase Letter 18
 
2.3%
Other Punctuation 4
 
0.5%
Other Symbol 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
형 41
 
8.5%
이 32
 
6.6%
대 26
 
5.4%
상 23
 
4.8%
개 20
 
4.1%
당 20
 
4.1%
인 19
 
3.9%
용 19
 
3.9%
소 17
 
3.5%
모 17
 
3.5%
Other values (81) 249
51.6%
Decimal Number
ValueCountFrequency (%)
0 31
28.4%
1 25
22.9%
2 12
 
11.0%
6 11
 
10.1%
3 10
 
9.2%
9 8
 
7.3%
5 6
 
5.5%
4 5
 
4.6%
7 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
27.8%
X 4
22.2%
D 2
 
11.1%
L 2
 
11.1%
E 1
 
5.6%
K 1
 
5.6%
F 1
 
5.6%
R 1
 
5.6%
P 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
m 28
57.1%
c 7
 
14.3%
g 4
 
8.2%
ℓ 4
 
8.2%
k 3
 
6.1%
x 3
 
6.1%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
, 2
50.0%
Space Separator
ValueCountFrequency (%)
81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
60.6%
Common 251
31.5%
Latin 63
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
형 41
 
8.5%
이 32
 
6.6%
대 26
 
5.4%
상 23
 
4.8%
개 20
 
4.1%
당 20
 
4.1%
인 19
 
3.9%
용 19
 
3.9%
소 17
 
3.5%
모 17
 
3.5%
Other values (81) 249
51.6%
Common
ValueCountFrequency (%)
81
32.3%
0 31
 
12.4%
( 25
 
10.0%
) 25
 
10.0%
1 25
 
10.0%
2 12
 
4.8%
6 11
 
4.4%
3 10
 
4.0%
9 8
 
3.2%
5 6
 
2.4%
Other values (6) 17
 
6.8%
Latin
ValueCountFrequency (%)
m 28
44.4%
c 7
 
11.1%
C 5
 
7.9%
X 4
 
6.3%
g 4
 
6.3%
k 3
 
4.8%
x 3
 
4.8%
D 2
 
3.2%
L 2
 
3.2%
E 1
 
1.6%
Other values (4) 4
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
60.6%
ASCII 307
38.5%
Letterlike Symbols 4
 
0.5%
CJK Compat 3
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
26.4%
0 31
 
10.1%
m 28
 
9.1%
( 25
 
8.1%
) 25
 
8.1%
1 25
 
8.1%
2 12
 
3.9%
6 11
 
3.6%
3 10
 
3.3%
9 8
 
2.6%
Other values (18) 51
16.6%
Hangul
ValueCountFrequency (%)
형 41
 
8.5%
이 32
 
6.6%
대 26
 
5.4%
상 23
 
4.8%
개 20
 
4.1%
당 20
 
4.1%
인 19
 
3.9%
용 19
 
3.9%
소 17
 
3.5%
모 17
 
3.5%
Other values (81) 249
51.6%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 4
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 3
100.0%

금액
Categorical

Distinct13
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2,000
37 
3,000
26 
4,000
21 
5,000
15 
10,000
9 
Other values (8)
33 

Length

Max length6
Median length5
Mean length5.1276596
Min length5

Unique

Unique3 ?
Unique (%)2.1%

Sample

1st row20,000
2nd row10,000
3rd row20,000
4th row10,000
5th row3,000

Common Values

ValueCountFrequency (%)
2,000 37
26.2%
3,000 26
18.4%
4,000 21
14.9%
5,000 15
10.6%
10,000 9
 
6.4%
8,000 9
 
6.4%
1,000 7
 
5.0%
6,000 6
 
4.3%
15,000 5
 
3.5%
20,000 3
 
2.1%
Other values (3) 3
 
2.1%

Length

2023-12-12T17:58:21.685818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2,000 37
26.2%
3,000 26
18.4%
4,000 21
14.9%
5,000 15
10.6%
10,000 9
 
6.4%
8,000 9
 
6.4%
1,000 7
 
5.0%
6,000 6
 
4.3%
15,000 5
 
3.5%
20,000 3
 
2.1%
Other values (3) 3
 
2.1%

Correlations

2023-12-12T17:58:21.802940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류품목규격금액
대분류1.0001.0000.5280.309
품목1.0001.0000.0000.000
규격0.5280.0001.0000.429
금액0.3090.0000.4291.000
2023-12-12T17:58:21.943910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류금액
대분류1.0000.175
금액0.1751.000
2023-12-12T17:58:22.068115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류금액
대분류1.0000.175
금액0.1751.000

Missing values

2023-12-12T17:58:18.822462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:58:18.972148image/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

대분류품목규격금액
0가구류돌침대2인용(받침 별도)20,000
1가구류돌침대1인용(받침 별도)10,000
2가구류돌침대 받침2인용(돌침대 별도)20,000
3가구류돌침대 받침1인용(돌침대 별도)10,000
4가구류매트리스1인용(침대 별도)3,000
5가구류매트리스2인용이상(침대 별도)5,000
6가구류문갑모든 규격3,000
7가구류문짝1m x 1m 미만2,000
8가구류문짝1m x 1m 이상4,000
9가구류비키니옷장개당2,000
대분류품목규격금액
131기타의류 및 이불묶음단위(100리터 봉투기준)2,000
132기타자전거개당3,000
133기타장판(카페트)1묶음(20Kg)2,000
134기타재봉틀개당3,000
135기타정수기개당3,000
136기타칸막이판넬개당2,000
137기타판유리(잡재물류)60kg 미만2,000
138기타판유리(잡재물류)60kg 이상3,000
139기타피아노그랜드15,000
140기타피아노어프라이트10,000