Overview

Dataset statistics

Number of variables10
Number of observations79
Missing cells462
Missing cells (%)58.5%
Duplicate rows4
Duplicate rows (%)5.1%
Total size in memory6.4 KiB
Average record size in memory82.7 B

Variable types

Unsupported9
Text1

Dataset

Description시도별 온실유형별(시설유형별, 규격시설별, 피복자재별 등)재배면적 현황
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220217000000002032

Alerts

Dataset has 4 (5.1%) duplicate rowsDuplicates
Unnamed: 0 has 79 (100.0%) missing valuesMissing
시설 has 35 (44.3%) missing valuesMissing
Unnamed: 2 has 39 (49.4%) missing valuesMissing
Unnamed: 3 has 47 (59.5%) missing valuesMissing
Unnamed: 4 has 40 (50.6%) missing valuesMissing
Unnamed: 5 has 39 (49.4%) missing valuesMissing
Unnamed: 6 has 47 (59.5%) missing valuesMissing
Unnamed: 7 has 39 (49.4%) missing valuesMissing
Unnamed: 8 has 48 (60.8%) missing valuesMissing
Unnamed: 9 has 49 (62.0%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 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
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 03:45:14.377362
Analysis finished2023-12-11 03:45:15.270317
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

시설
Text

MISSING 

Distinct41
Distinct (%)93.2%
Missing35
Missing (%)44.3%
Memory size764.0 B
2023-12-11T12:45:15.438034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length3
Mean length3.5
Min length1

Characters and Unicode

Total characters154
Distinct characters73
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

Unique38 ?
Unique (%)86.4%

Sample

1st row구 분
2nd row합 계
3rd row근채류
4th row무
5th row(봄)
ValueCountFrequency (%)
추 3
 
4.3%
가을 2
 
2.9%
2
 
2.9%
근 2
 
2.9%
박 2
 
2.9%
파 2
 
2.9%
봄 2
 
2.9%
고랭지 2
 
2.9%
오 1
 
1.4%
이 1
 
1.4%
Other values (50) 50
72.5%
2023-12-11T12:45:15.804396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
16.2%
) 9
 
5.8%
( 8
 
5.2%
채 6
 
3.9%
추 6
 
3.9%
고 4
 
2.6%
류 4
 
2.6%
수 3
 
1.9%
파 3
 
1.9%
가 3
 
1.9%
Other values (63) 83
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 110
71.4%
Space Separator 25
 
16.2%
Close Punctuation 9
 
5.8%
Open Punctuation 8
 
5.2%
Other Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
채 6
 
5.5%
추 6
 
5.5%
고 4
 
3.6%
류 4
 
3.6%
수 3
 
2.7%
파 3
 
2.7%
가 3
 
2.7%
토 3
 
2.7%
근 3
 
2.7%
양 3
 
2.7%
Other values (58) 72
65.5%
Other Punctuation
ValueCountFrequency (%)
* 1
50.0%
: 1
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 110
71.4%
Common 44
 
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
채 6
 
5.5%
추 6
 
5.5%
고 4
 
3.6%
류 4
 
3.6%
수 3
 
2.7%
파 3
 
2.7%
가 3
 
2.7%
토 3
 
2.7%
근 3
 
2.7%
양 3
 
2.7%
Other values (58) 72
65.5%
Common
ValueCountFrequency (%)
25
56.8%
) 9
 
20.5%
( 8
 
18.2%
* 1
 
2.3%
: 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 110
71.4%
ASCII 44
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
56.8%
) 9
 
20.5%
( 8
 
18.2%
* 1
 
2.3%
: 1
 
2.3%
Hangul
ValueCountFrequency (%)
채 6
 
5.5%
추 6
 
5.5%
고 4
 
3.6%
류 4
 
3.6%
수 3
 
2.7%
파 3
 
2.7%
가 3
 
2.7%
토 3
 
2.7%
근 3
 
2.7%
양 3
 
2.7%
Other values (58) 72
65.5%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)49.4%
Memory size764.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing47
Missing (%)59.5%
Memory size764.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing40
Missing (%)50.6%
Memory size764.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)49.4%
Memory size764.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing47
Missing (%)59.5%
Memory size764.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing39
Missing (%)49.4%
Memory size764.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)60.8%
Memory size764.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing49
Missing (%)62.0%
Memory size764.0 B

Missing values

2023-12-11T12:45:14.799613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:45:14.994350image/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.
2023-12-11T12:45:15.165930image/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: 0시설Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
0<NA>구 분2012NaNNaN2013NaNNaN증감율(%)NaN
1<NA><NA>면적단수생산량면적단수생산량면 적생산량
2<NA>합 계62908NaN266892360226NaN2545931.12-4.263369-4.608296
3<NA>근채류1112NaN454281138NaN44302.152.338129-2.478317
4<NA>무109741114509711273911440742.734731-2.268444
5<NA>(봄)109741114509711273911440742.734731-2.268444
6<NA>(고랭지)000000NaNNaN
7<NA>(가을)000000NaNNaN
8<NA>(월동)000000NaNNaN
9<NA>당 근000000NaNNaN
Unnamed: 0시설Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
69<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
70<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
71<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
72<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
73<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
74<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
75<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
76<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
77<NA><NA>NaNNaNNaNNaNNaNNaNNaNNaN
78<NA><NA>NaNNaNNaNNaNNaN83NaNNaN

Duplicate rows

Most frequently occurring

시설# duplicates
3<NA>35
0(가을)2
1(고랭지)2
2(봄)2