Overview

Dataset statistics

Number of variables5
Number of observations23
Missing cells49
Missing cells (%)42.6%
Duplicate rows1
Duplicate rows (%)4.3%
Total size in memory1.0 KiB
Average record size in memory46.7 B

Variable types

Unsupported3
Text2

Dataset

Description부산광역시 남구 2024년 소독의무대상시설 현황입니다. 소독의무대상시설의 종류 및 시설 현황을 알 수 있습니다.
Author부산광역시 남구
URLhttps://www.data.go.kr/data/15127384/fileData.do

Alerts

Unnamed: 4 has constant value ""Constant
Dataset has 1 (4.3%) duplicate rowsDuplicates
Unnamed: 0 has 23 (100.0%) missing valuesMissing
2024년 소독의무대상시설 현황 has 1 (4.3%) missing valuesMissing
Unnamed: 2 has 2 (8.7%) missing valuesMissing
Unnamed: 3 has 1 (4.3%) missing valuesMissing
Unnamed: 4 has 22 (95.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
2024년 소독의무대상시설 현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 08:54:33.021123
Analysis finished2024-04-06 08:54:33.824607
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

2024년 소독의무대상시설 현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.3%
Memory size316.0 B

Unnamed: 2
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing2
Missing (%)8.7%
Memory size316.0 B
2024-04-06T17:54:34.052742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length5.8095238
Min length2

Characters and Unicode

Total characters122
Distinct characters70
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

Unique21 ?
Unique (%)100.0%

Sample

1st row시설의 종류
2nd row숙박업소 및 관광숙박업소
3rd row식품접객업소
4th row버스 및 역무시설
5th row지하철
ValueCountFrequency (%)
및 4
 
12.5%
시설의 1
 
3.1%
기숙사 1
 
3.1%
공동주택(300세대 1
 
3.1%
건축물등 1
 
3.1%
유치원 1
 
3.1%
어린이집 1
 
3.1%
학원 1
 
3.1%
특수학교 1
 
3.1%
초등학교 1
 
3.1%
Other values (19) 19
59.4%
2024-04-06T17:54:35.007555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
9.0%
소 6
 
4.9%
학 6
 
4.9%
교 5
 
4.1%
및 4
 
3.3%
등 4
 
3.3%
숙 4
 
3.3%
업 4
 
3.3%
원 3
 
2.5%
식 3
 
2.5%
Other values (60) 72
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 106
86.9%
Space Separator 11
 
9.0%
Decimal Number 3
 
2.5%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 6
 
5.7%
학 6
 
5.7%
교 5
 
4.7%
및 4
 
3.8%
등 4
 
3.8%
숙 4
 
3.8%
업 4
 
3.8%
원 3
 
2.8%
식 3
 
2.8%
시 3
 
2.8%
Other values (55) 64
60.4%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 106
86.9%
Common 16
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 6
 
5.7%
학 6
 
5.7%
교 5
 
4.7%
및 4
 
3.8%
등 4
 
3.8%
숙 4
 
3.8%
업 4
 
3.8%
원 3
 
2.8%
식 3
 
2.8%
시 3
 
2.8%
Other values (55) 64
60.4%
Common
ValueCountFrequency (%)
11
68.8%
0 2
 
12.5%
( 1
 
6.2%
3 1
 
6.2%
) 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 106
86.9%
ASCII 16
 
13.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
68.8%
0 2
 
12.5%
( 1
 
6.2%
3 1
 
6.2%
) 1
 
6.2%
Hangul
ValueCountFrequency (%)
소 6
 
5.7%
학 6
 
5.7%
교 5
 
4.7%
및 4
 
3.8%
등 4
 
3.8%
숙 4
 
3.8%
업 4
 
3.8%
원 3
 
2.8%
식 3
 
2.8%
시 3
 
2.8%
Other values (55) 64
60.4%

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.3%
Memory size316.0 B

Unnamed: 4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing22
Missing (%)95.7%
Memory size316.0 B
2024-04-06T17:54:35.280476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories7 ?
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 row개 소(~24.12.31)
ValueCountFrequency (%)
개 1
50.0%
소(~24.12.31 1
50.0%
2024-04-06T17:54:35.786071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
14.3%
. 2
14.3%
1 2
14.3%
개 1
7.1%
1
7.1%
소 1
7.1%
( 1
7.1%
~ 1
7.1%
4 1
7.1%
3 1
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
42.9%
Other Punctuation 2
 
14.3%
Other Letter 2
 
14.3%
Space Separator 1
 
7.1%
Open Punctuation 1
 
7.1%
Math Symbol 1
 
7.1%
Close Punctuation 1
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
33.3%
1 2
33.3%
4 1
16.7%
3 1
16.7%
Other Letter
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
85.7%
Hangul 2
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
16.7%
. 2
16.7%
1 2
16.7%
1
8.3%
( 1
8.3%
~ 1
8.3%
4 1
8.3%
3 1
8.3%
) 1
8.3%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
85.7%
Hangul 2
 
14.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
16.7%
. 2
16.7%
1 2
16.7%
1
8.3%
( 1
8.3%
~ 1
8.3%
4 1
8.3%
3 1
8.3%
) 1
8.3%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Missing values

2024-04-06T17:54:33.310122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:54:33.532116image/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.
2024-04-06T17:54:33.709717image/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

Unnamed: 02024년 소독의무대상시설 현황Unnamed: 2Unnamed: 3Unnamed: 4
0<NA>NaN<NA>NaN<NA>
1<NA>순번시설의 종류개 소(24.1.1~)개 소(~24.12.31)
2<NA>1숙박업소 및 관광숙박업소39<NA>
3<NA>2식품접객업소71<NA>
4<NA>3버스 및 역무시설16<NA>
5<NA>4지하철6<NA>
6<NA>5대규모 점포 및 전통시장18<NA>
7<NA>6병원등20<NA>
8<NA>7집단급식소108<NA>
9<NA>8위탁급식영업소17<NA>
Unnamed: 02024년 소독의무대상시설 현황Unnamed: 2Unnamed: 3Unnamed: 4
13<NA>12고등학교15<NA>
14<NA>13중학교13<NA>
15<NA>14초등학교21<NA>
16<NA>15특수학교3<NA>
17<NA>16학원0<NA>
18<NA>17어린이집34<NA>
19<NA>18유치원25<NA>
20<NA>19건축물등125<NA>
21<NA>20공동주택(300세대 이상)62<NA>
22<NA>계<NA>608<NA>

Duplicate rows

Most frequently occurring

Unnamed: 2Unnamed: 4# duplicates
0<NA><NA>2