Overview

Dataset statistics

Number of variables5
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory44.6 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description보령시 관내 주요 배 농가 재배현황에 대한 데이터 입니다. 기관, 읍면동, 재배지 위치(지번 주소), 면적(㎡), 과종(배), 수확시기로 구성되어있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=417&beforeMenuCd=DOM_000000201001001000&publicdatapk=15039676

Alerts

과종 has constant value ""Constant
수확시기 has constant value ""Constant
위치 has unique valuesUnique
면적 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:58:53.773293
Analysis finished2024-01-09 22:58:54.139788
Duration0.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct5
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size428.0 B
남포면
13 
청라면
12 
웅천읍
주산면
주포면
 
1

Length

Max length4
Median length4
Mean length3.5675676
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
남포면 13
35.1%
청라면 12
32.4%
웅천읍 8
21.6%
주산면 3
 
8.1%
주포면 1
 
2.7%

Length

2024-01-10T07:58:54.199910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:58:54.294723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남포면 13
35.1%
청라면 12
32.4%
웅천읍 8
21.6%
주산면 3
 
8.1%
주포면 1
 
2.7%

위치
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-01-10T07:58:54.476452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length17.72973
Min length16

Characters and Unicode

Total characters656
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row충청남도 보령시 성동리 593-8
2nd row충청남도 보령시 성동리593-12
3rd row충청남도 보령시 성동리 505-5
4th row충청남도 보령시 성동리 505-30
5th row충청남도 보령시 성동리 21-1
ValueCountFrequency (%)
충청남도 37
25.2%
보령시 37
25.2%
나원리 7
 
4.8%
봉덕리 7
 
4.8%
성동리 7
 
4.8%
의평리 5
 
3.4%
신흥리 5
 
3.4%
주야리 3
 
2.0%
554-2 1
 
0.7%
180-9 1
 
0.7%
Other values (37) 37
25.2%
2024-01-10T07:58:54.779125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
110
16.8%
37
 
5.6%
37
 
5.6%
37
 
5.6%
37
 
5.6%
37
 
5.6%
37
 
5.6%
37
 
5.6%
37
 
5.6%
- 32
 
4.9%
Other values (25) 218
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 370
56.4%
Decimal Number 144
 
22.0%
Space Separator 110
 
16.8%
Dash Punctuation 32
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
9
 
2.4%
8
 
2.2%
Other values (13) 57
15.4%
Decimal Number
ValueCountFrequency (%)
2 28
19.4%
1 25
17.4%
9 17
11.8%
5 14
9.7%
0 13
9.0%
7 12
8.3%
4 11
 
7.6%
3 9
 
6.2%
6 9
 
6.2%
8 6
 
4.2%
Space Separator
ValueCountFrequency (%)
110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 370
56.4%
Common 286
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
9
 
2.4%
8
 
2.2%
Other values (13) 57
15.4%
Common
ValueCountFrequency (%)
110
38.5%
- 32
 
11.2%
2 28
 
9.8%
1 25
 
8.7%
9 17
 
5.9%
5 14
 
4.9%
0 13
 
4.5%
7 12
 
4.2%
4 11
 
3.8%
3 9
 
3.1%
Other values (2) 15
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 370
56.4%
ASCII 286
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
110
38.5%
- 32
 
11.2%
2 28
 
9.8%
1 25
 
8.7%
9 17
 
5.9%
5 14
 
4.9%
0 13
 
4.5%
7 12
 
4.2%
4 11
 
3.8%
3 9
 
3.1%
Other values (2) 15
 
5.2%
Hangul
ValueCountFrequency (%)
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
37
10.0%
9
 
2.4%
8
 
2.2%
Other values (13) 57
15.4%

면적
Real number (ℝ)

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3320.7838
Minimum62
Maximum13300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-01-10T07:58:54.901160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile204.8
Q11150
median2500
Q34301
95-th percentile9647.6
Maximum13300
Range13238
Interquartile range (IQR)3151

Descriptive statistics

Standard deviation3130.6604
Coefficient of variation (CV)0.94274745
Kurtosis2.7367238
Mean3320.7838
Median Absolute Deviation (MAD)1352
Skewness1.6777709
Sum122869
Variance9801034.8
MonotonicityNot monotonic
2024-01-10T07:58:55.020000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
3252 1
 
2.7%
2624 1
 
2.7%
4301 1
 
2.7%
1340 1
 
2.7%
7633 1
 
2.7%
5587 1
 
2.7%
4825 1
 
2.7%
1148 1
 
2.7%
4383 1
 
2.7%
2357 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
62 1
2.7%
112 1
2.7%
228 1
2.7%
309 1
2.7%
483 1
2.7%
500 1
2.7%
583 1
2.7%
873 1
2.7%
1148 1
2.7%
1150 1
2.7%
ValueCountFrequency (%)
13300 1
2.7%
11598 1
2.7%
9160 1
2.7%
8514 1
2.7%
7633 1
2.7%
5587 1
2.7%
4825 1
2.7%
4641 1
2.7%
4383 1
2.7%
4301 1
2.7%

과종
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
37 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
37
100.0%

Length

2024-01-10T07:58:55.137978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:58:55.221742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
37
100.0%

수확시기
Categorical

CONSTANT 

Distinct1
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size428.0 B
9-10월
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9-10월
2nd row9-10월
3rd row9-10월
4th row9-10월
5th row9-10월

Common Values

ValueCountFrequency (%)
9-10월 37
100.0%

Length

2024-01-10T07:58:55.309640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:58:55.391339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9-10월 37
100.0%

Interactions

2024-01-10T07:58:53.906010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:58:55.442870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동위치면적
읍면동1.0001.0000.000
위치1.0001.0001.000
면적0.0001.0001.000
2024-01-10T07:58:55.516520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적읍면동
면적1.0000.000
읍면동0.0001.000

Missing values

2024-01-10T07:58:54.023318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:58:54.104993image/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

읍면동위치면적과종수확시기
0웅천읍충청남도 보령시 성동리 593-832529-10월
1웅천읍충청남도 보령시 성동리593-12115989-10월
2웅천읍충청남도 보령시 성동리 505-521849-10월
3웅천읍충청남도 보령시 성동리 505-303099-10월
4웅천읍충청남도 보령시 성동리 21-14839-10월
5웅천읍충청남도 보령시 성동리 514-685149-10월
6웅천읍충청남도 보령시 성동리 514-1191609-10월
7웅천읍충청남도 보령시 성동리 527-4629-10월
8청라면충청남도 보령시 나원리 97-15009-10월
9청라면충청남도 보령시 나원리 792-1133009-10월
읍면동위치면적과종수확시기
27남포면충청남도 보령시 신흥리 697-443839-10월
28남포면충청남도 보령시 봉덕리 521-126249-10월
29남포면충청남도 보령시 봉덕리 21023579-10월
30남포면충청남도 보령시 봉덕리 270-42289-10월
31남포면충청남도 보령시 봉덕리 26833609-10월
32남포면충청남도 보령시 봉덕리 269-122309-10월
33주산면충청남도 보령시 주야리 628-223879-10월
34주산면충청남도 보령시 주야리 628-421129-10월
35주산면충청남도 보령시 주야리 554-233569-10월
36주포면충청남도 보령시 연지리 7105839-10월