Overview

Dataset statistics

Number of variables7
Number of observations82
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory58.6 B

Variable types

Categorical4
Text1
Numeric1
DateTime1

Dataset

Description충청남도 공주시 배농가현황에 대한 데이터로 (읍면동, 재배지 위치, 재배면적(㎡),과종명,수확시기,데이터기준일) 등의 항목을 제공합니다,
Author충청남도 공주시
URLhttps://www.data.go.kr/data/15036538/fileData.do

Alerts

기관 has constant value ""Constant
과종명 has constant value ""Constant
수확시기 has constant value ""Constant
데이터기준일 has constant value ""Constant
재배면적(㎡) has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:01:43.375354
Analysis finished2023-12-12 07:01:43.900436
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
충청남도 공주시
82 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 공주시
2nd row충청남도 공주시
3rd row충청남도 공주시
4th row충청남도 공주시
5th row충청남도 공주시

Common Values

ValueCountFrequency (%)
충청남도 공주시 82
100.0%

Length

2023-12-12T16:01:43.967268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:01:44.063508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 82
50.0%
공주시 82
50.0%

읍면동
Categorical

Distinct15
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Memory size788.0 B
사곡면
32 
우성면
20 
계룡면
4 
신풍면
4 
유구읍
4 
Other values (10)
18 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)3.7%

Sample

1st row계룡면
2nd row계룡면
3rd row계룡면
4th row계룡면
5th row금학동

Common Values

ValueCountFrequency (%)
사곡면 32
39.0%
우성면 20
24.4%
계룡면 4
 
4.9%
신풍면 4
 
4.9%
유구읍 4
 
4.9%
정안면 3
 
3.7%
신관동 2
 
2.4%
옥룡동 2
 
2.4%
웅진동 2
 
2.4%
월송동 2
 
2.4%
Other values (5) 7
 
8.5%

Length

2023-12-12T16:01:44.146815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사곡면 32
39.0%
우성면 20
24.4%
계룡면 4
 
4.9%
신풍면 4
 
4.9%
유구읍 4
 
4.9%
정안면 3
 
3.7%
신관동 2
 
2.4%
옥룡동 2
 
2.4%
웅진동 2
 
2.4%
월송동 2
 
2.4%
Other values (5) 7
 
8.5%

재배지 위치
Text

Distinct81
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-12T16:01:44.398458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length20
Mean length15.890244
Min length7

Characters and Unicode

Total characters1303
Distinct characters119
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

Unique80 ?
Unique (%)97.6%

Sample

1st row공주시 계룡면 월암송정길 20-5
2nd row공주시 계룡면 호복동길 27-13
3rd row공주시 계룡면 금띠길 47
4th row공주시 계룡면 죽곡서당골길 28
5th row공주시 봉정안터길 72
ValueCountFrequency (%)
공주시 60
 
19.5%
사곡면 31
 
10.1%
우성면 20
 
6.5%
묵방길 8
 
2.6%
통천포길 7
 
2.3%
고순길 6
 
2.0%
아래안영골길 5
 
1.6%
국제길 4
 
1.3%
신풍면 4
 
1.3%
유구읍 4
 
1.3%
Other values (136) 158
51.5%
2023-12-12T16:01:44.800665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
225
 
17.3%
길 75
 
5.8%
면 68
 
5.2%
공 62
 
4.8%
주 60
 
4.6%
시 60
 
4.6%
1 50
 
3.8%
2 47
 
3.6%
- 36
 
2.8%
곡 32
 
2.5%
Other values (109) 588
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 757
58.1%
Decimal Number 269
 
20.6%
Space Separator 225
 
17.3%
Dash Punctuation 36
 
2.8%
Other Punctuation 6
 
0.5%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 75
 
9.9%
면 68
 
9.0%
공 62
 
8.2%
주 60
 
7.9%
시 60
 
7.9%
곡 32
 
4.2%
사 31
 
4.1%
우 20
 
2.6%
성 20
 
2.6%
골 16
 
2.1%
Other values (94) 313
41.3%
Decimal Number
ValueCountFrequency (%)
1 50
18.6%
2 47
17.5%
7 26
9.7%
3 25
9.3%
4 22
8.2%
6 22
8.2%
9 20
 
7.4%
0 20
 
7.4%
5 19
 
7.1%
8 18
 
6.7%
Space Separator
ValueCountFrequency (%)
225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 757
58.1%
Common 546
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 75
 
9.9%
면 68
 
9.0%
공 62
 
8.2%
주 60
 
7.9%
시 60
 
7.9%
곡 32
 
4.2%
사 31
 
4.1%
우 20
 
2.6%
성 20
 
2.6%
골 16
 
2.1%
Other values (94) 313
41.3%
Common
ValueCountFrequency (%)
225
41.2%
1 50
 
9.2%
2 47
 
8.6%
- 36
 
6.6%
7 26
 
4.8%
3 25
 
4.6%
4 22
 
4.0%
6 22
 
4.0%
9 20
 
3.7%
0 20
 
3.7%
Other values (5) 53
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 757
58.1%
ASCII 546
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
225
41.2%
1 50
 
9.2%
2 47
 
8.6%
- 36
 
6.6%
7 26
 
4.8%
3 25
 
4.6%
4 22
 
4.0%
6 22
 
4.0%
9 20
 
3.7%
0 20
 
3.7%
Other values (5) 53
 
9.7%
Hangul
ValueCountFrequency (%)
길 75
 
9.9%
면 68
 
9.0%
공 62
 
8.2%
주 60
 
7.9%
시 60
 
7.9%
곡 32
 
4.2%
사 31
 
4.1%
우 20
 
2.6%
성 20
 
2.6%
골 16
 
2.1%
Other values (94) 313
41.3%

재배면적(㎡)
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11495.256
Minimum1230
Maximum40460
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-12-12T16:01:44.948883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1230
5-th percentile1662.9
Q15179.5
median9137
Q314782.25
95-th percentile31637.85
Maximum40460
Range39230
Interquartile range (IQR)9602.75

Descriptive statistics

Standard deviation8973.8109
Coefficient of variation (CV)0.78065341
Kurtosis1.5309625
Mean11495.256
Median Absolute Deviation (MAD)4732.5
Skewness1.3903593
Sum942611
Variance80529282
MonotonicityNot monotonic
2023-12-12T16:01:45.132304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6460 1
 
1.2%
5433 1
 
1.2%
9093 1
 
1.2%
18596 1
 
1.2%
11641 1
 
1.2%
10501 1
 
1.2%
9778 1
 
1.2%
1474 1
 
1.2%
8639 1
 
1.2%
5241 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1230 1
1.2%
1474 1
1.2%
1510 1
1.2%
1600 1
1.2%
1643 1
1.2%
2041 1
1.2%
2049 1
1.2%
2050 1
1.2%
2188 1
1.2%
3071 1
1.2%
ValueCountFrequency (%)
40460 1
1.2%
35414 1
1.2%
35044 1
1.2%
32249 1
1.2%
31640 1
1.2%
31597 1
1.2%
29974 1
1.2%
29432 1
1.2%
24770 1
1.2%
22441 1
1.2%

과종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
배
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
배 82
100.0%

Length

2023-12-12T16:01:45.305416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:01:45.404850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
배 82
100.0%

수확시기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
10월
82 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10월
2nd row10월
3rd row10월
4th row10월
5th row10월

Common Values

ValueCountFrequency (%)
10월 82
100.0%

Length

2023-12-12T16:01:45.506083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:01:45.606501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10월 82
100.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2020-05-11 00:00:00
Maximum2020-05-11 00:00:00
2023-12-12T16:01:45.687028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:01:45.777640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T16:01:43.567365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:01:45.861273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동재배지 위치재배면적(㎡)
읍면동1.0001.0000.525
재배지 위치1.0001.0001.000
재배면적(㎡)0.5251.0001.000
2023-12-12T16:01:45.934272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재배면적(㎡)읍면동
재배면적(㎡)1.0000.211
읍면동0.2111.000

Missing values

2023-12-12T16:01:43.706224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:01:43.851579image/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

기관읍면동재배지 위치재배면적(㎡)과종명수확시기데이터기준일
0충청남도 공주시계룡면공주시 계룡면 월암송정길 20-56460배10월2020-05-11
1충청남도 공주시계룡면공주시 계룡면 호복동길 27-133614배10월2020-05-11
2충청남도 공주시계룡면공주시 계룡면 금띠길 473252배10월2020-05-11
3충청남도 공주시계룡면공주시 계룡면 죽곡서당골길 2810445배10월2020-05-11
4충청남도 공주시금학동공주시 봉정안터길 725159배10월2020-05-11
5충청남도 공주시반포면공주시 반포면 연정길 5-62050배10월2020-05-11
6충청남도 공주시사곡면공주시 사곡면 위안양골길 23-414444배10월2020-05-11
7충청남도 공주시사곡면공주시 사곡면 진밭양지편길 629181배10월2020-05-11
8충청남도 공주시사곡면공주시 사곡면 아래안영골길 108-222441배10월2020-05-11
9충청남도 공주시사곡면공주시 사곡면 고순길 2717611배10월2020-05-11
기관읍면동재배지 위치재배면적(㎡)과종명수확시기데이터기준일
72충청남도 공주시유구읍공주시 유구읍 산막1길 99-41510배10월2020-05-11
73충청남도 공주시유구읍공주시 유구읍 추동3길 6-1713544배10월2020-05-11
74충청남도 공주시의당면의당면 도신고복로 172041배10월2020-05-11
75충청남도 공주시의당면의당면 도신리 5623894배10월2020-05-11
76충청남도 공주시이인면공주시 이인면 새터2길 1511550배10월2020-05-11
77충청남도 공주시이인면공주시 이인면 새터2길 29-102188배10월2020-05-11
78충청남도 공주시정안면공주시 정안면 동오리길 4615000배10월2020-05-11
79충청남도 공주시정안면공주시 정안면 죽암리길 35-1618403배10월2020-05-11
80충청남도 공주시정안면공주시 정안면 장원길 326-54861배10월2020-05-11
81충청남도 공주시탄천면공주시 탄천면 평촌동촌길 88-324770배10월2020-05-11