Overview

Dataset statistics

Number of variables6
Number of observations33
Missing cells160
Missing cells (%)80.8%
Duplicate rows1
Duplicate rows (%)3.0%
Total size in memory1.7 KiB
Average record size in memory53.0 B

Variable types

Categorical1
Text5

Dataset

Description경상북도 고령군에 신고 또는 허가되어있는 대기배출시설 사업장 중 보일러를 사용하면서 부생연료유 C9 사용업체 현황
Author경상북도 고령군
URLhttps://www.data.go.kr/data/15110396/fileData.do

Alerts

업체명 has constant value ""Constant
주소 has constant value ""Constant
전화번호 has constant value ""Constant
사용연료 has constant value ""Constant
사용량 has constant value ""Constant
Dataset has 1 (3.0%) duplicate rowsDuplicates
연번 is highly imbalanced (80.4%)Imbalance
업체명 has 32 (97.0%) missing valuesMissing
주소 has 32 (97.0%) missing valuesMissing
전화번호 has 32 (97.0%) missing valuesMissing
사용연료 has 32 (97.0%) missing valuesMissing
사용량 has 32 (97.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 22:56:37.510156
Analysis finished2023-12-12 22:56:38.029869
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
32 
1
 
1

Length

Max length4
Median length4
Mean length3.9090909
Min length1

Unique

Unique1 ?
Unique (%)3.0%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 32
97.0%
1 1
 
3.0%

Length

2023-12-13T07:56:38.437733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:56:38.547374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
97.0%
1 1
 
3.0%

업체명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-13T07:56:38.668171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row㈜효재산업
ValueCountFrequency (%)
㈜효재산업 1
100.0%
2023-12-13T07:56:38.941680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 1
20.0%
효 1
20.0%
재 1
20.0%
산 1
20.0%
업 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
80.0%
Other Symbol 1
 
20.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
효 1
25.0%
재 1
25.0%
산 1
25.0%
업 1
25.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 1
20.0%
효 1
20.0%
재 1
20.0%
산 1
20.0%
업 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
80.0%
None 1
 
20.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 1
100.0%
Hangul
ValueCountFrequency (%)
효 1
25.0%
재 1
25.0%
산 1
25.0%
업 1
25.0%

주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-13T07:56:39.085265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row고령군 다산면 다산산단2길 30
ValueCountFrequency (%)
고령군 1
25.0%
다산면 1
25.0%
다산산단2길 1
25.0%
30 1
25.0%
2023-12-13T07:56:39.380777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
17.6%
산 3
17.6%
다 2
11.8%
고 1
 
5.9%
령 1
 
5.9%
군 1
 
5.9%
면 1
 
5.9%
단 1
 
5.9%
2 1
 
5.9%
길 1
 
5.9%
Other values (2) 2
11.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11
64.7%
Space Separator 3
 
17.6%
Decimal Number 3
 
17.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 3
27.3%
다 2
18.2%
고 1
 
9.1%
령 1
 
9.1%
군 1
 
9.1%
면 1
 
9.1%
단 1
 
9.1%
길 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
0 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11
64.7%
Common 6
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 3
27.3%
다 2
18.2%
고 1
 
9.1%
령 1
 
9.1%
군 1
 
9.1%
면 1
 
9.1%
단 1
 
9.1%
길 1
 
9.1%
Common
ValueCountFrequency (%)
3
50.0%
2 1
 
16.7%
3 1
 
16.7%
0 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11
64.7%
ASCII 6
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3
50.0%
2 1
 
16.7%
3 1
 
16.7%
0 1
 
16.7%
Hangul
ValueCountFrequency (%)
산 3
27.3%
다 2
18.2%
고 1
 
9.1%
령 1
 
9.1%
군 1
 
9.1%
면 1
 
9.1%
단 1
 
9.1%
길 1
 
9.1%

전화번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-13T07:56:39.519086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row054-956-2044
ValueCountFrequency (%)
054-956-2044 1
100.0%
2023-12-13T07:56:39.813663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 3
25.0%
0 2
16.7%
5 2
16.7%
- 2
16.7%
9 1
 
8.3%
6 1
 
8.3%
2 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
83.3%
Dash Punctuation 2
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 3
30.0%
0 2
20.0%
5 2
20.0%
9 1
 
10.0%
6 1
 
10.0%
2 1
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 3
25.0%
0 2
16.7%
5 2
16.7%
- 2
16.7%
9 1
 
8.3%
6 1
 
8.3%
2 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 3
25.0%
0 2
16.7%
5 2
16.7%
- 2
16.7%
9 1
 
8.3%
6 1
 
8.3%
2 1
 
8.3%

사용연료
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-13T07:56:39.970394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
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

Unique1 ?
Unique (%)100.0%

Sample

1st row부생연료유2호
ValueCountFrequency (%)
부생연료유2호 1
100.0%
2023-12-13T07:56:40.243757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 1
14.3%
생 1
14.3%
연 1
14.3%
료 1
14.3%
유 1
14.3%
2 1
14.3%
호 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
85.7%
Decimal Number 1
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1
16.7%
생 1
16.7%
연 1
16.7%
료 1
16.7%
유 1
16.7%
호 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
85.7%
Common 1
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1
16.7%
생 1
16.7%
연 1
16.7%
료 1
16.7%
유 1
16.7%
호 1
16.7%
Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
85.7%
ASCII 1
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 1
16.7%
생 1
16.7%
연 1
16.7%
료 1
16.7%
유 1
16.7%
호 1
16.7%
ASCII
ValueCountFrequency (%)
2 1
100.0%

사용량
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing32
Missing (%)97.0%
Memory size396.0 B
2023-12-13T07:56:40.383815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters8
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row914.45ℓ/일
ValueCountFrequency (%)
914.45ℓ/일 1
100.0%
2023-12-13T07:56:40.635821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 2
22.2%
9 1
11.1%
1 1
11.1%
. 1
11.1%
5 1
11.1%
ℓ 1
11.1%
/ 1
11.1%
일 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
55.6%
Other Punctuation 2
 
22.2%
Lowercase Letter 1
 
11.1%
Other Letter 1
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 2
40.0%
9 1
20.0%
1 1
20.0%
5 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
/ 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
ℓ 1
100.0%
Other Letter
ValueCountFrequency (%)
일 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8
88.9%
Hangul 1
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 2
25.0%
9 1
12.5%
1 1
12.5%
. 1
12.5%
5 1
12.5%
ℓ 1
12.5%
/ 1
12.5%
Hangul
ValueCountFrequency (%)
일 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
77.8%
Letterlike Symbols 1
 
11.1%
Hangul 1
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 2
28.6%
9 1
14.3%
1 1
14.3%
. 1
14.3%
5 1
14.3%
/ 1
14.3%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 1
100.0%
Hangul
ValueCountFrequency (%)
일 1
100.0%

Missing values

2023-12-13T07:56:37.692394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:56:37.829463image/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.
2023-12-13T07:56:37.960837image/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

연번업체명주소전화번호사용연료사용량
01㈜효재산업고령군 다산면 다산산단2길 30054-956-2044부생연료유2호914.45ℓ/일
1<NA><NA><NA><NA><NA><NA>
2<NA><NA><NA><NA><NA><NA>
3<NA><NA><NA><NA><NA><NA>
4<NA><NA><NA><NA><NA><NA>
5<NA><NA><NA><NA><NA><NA>
6<NA><NA><NA><NA><NA><NA>
7<NA><NA><NA><NA><NA><NA>
8<NA><NA><NA><NA><NA><NA>
9<NA><NA><NA><NA><NA><NA>
연번업체명주소전화번호사용연료사용량
23<NA><NA><NA><NA><NA><NA>
24<NA><NA><NA><NA><NA><NA>
25<NA><NA><NA><NA><NA><NA>
26<NA><NA><NA><NA><NA><NA>
27<NA><NA><NA><NA><NA><NA>
28<NA><NA><NA><NA><NA><NA>
29<NA><NA><NA><NA><NA><NA>
30<NA><NA><NA><NA><NA><NA>
31<NA><NA><NA><NA><NA><NA>
32<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

연번업체명주소전화번호사용연료사용량# duplicates
0<NA><NA><NA><NA><NA><NA>32