Overview

Dataset statistics

Number of variables5
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory49.7 B

Variable types

Text1
Numeric2
Categorical2

Dataset

Description경상북도의 농수산,축산 정보입니다.(경상북도 시군의 기본형, 경관보전 직접직불제 지급면적, 지원액 현황입니다.)
Author경상북도
URLhttps://www.data.go.kr/data/15044811/fileData.do

Alerts

경관보전직접지불제 지급면적(ha) is highly overall correlated with 기본형공익직접지불제 지급면적(ha) and 1 other fieldsHigh correlation
경관보전직접지불제 지원액(천원) is highly overall correlated with 기본형공익직접지불제 지급면적(ha) and 2 other fieldsHigh correlation
기본형공익직접지불제 지급면적(ha) is highly overall correlated with 기본형공익직접지불제 지원액(천원) and 2 other fieldsHigh correlation
기본형공익직접지불제 지원액(천원) is highly overall correlated with 기본형공익직접지불제 지급면적(ha) and 1 other fieldsHigh correlation
경관보전직접지불제 지원액(천원) is highly imbalanced (51.3%)Imbalance
구 분 has unique valuesUnique
기본형공익직접지불제 지급면적(ha) has unique valuesUnique
기본형공익직접지불제 지원액(천원) has unique valuesUnique

Reproduction

Analysis started2023-12-23 07:41:55.613862
Analysis finished2023-12-23 07:41:59.068874
Duration3.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-23T07:41:59.565309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters69
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row포항시
2nd row경주시
3rd row김천시
4th row안동시
5th row구미시
ValueCountFrequency (%)
포항시 1
 
4.3%
청송군 1
 
4.3%
울진군 1
 
4.3%
봉화군 1
 
4.3%
예천군 1
 
4.3%
칠곡군 1
 
4.3%
성주군 1
 
4.3%
고령군 1
 
4.3%
청도군 1
 
4.3%
영덕군 1
 
4.3%
Other values (13) 13
56.5%
2023-12-23T07:42:01.482790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 14
20.3%
시 10
14.5%
주 4
 
5.8%
영 4
 
5.8%
경 3
 
4.3%
천 3
 
4.3%
청 2
 
2.9%
울 2
 
2.9%
성 2
 
2.9%
포 1
 
1.4%
Other values (24) 24
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 14
20.3%
시 10
14.5%
주 4
 
5.8%
영 4
 
5.8%
경 3
 
4.3%
천 3
 
4.3%
청 2
 
2.9%
울 2
 
2.9%
성 2
 
2.9%
포 1
 
1.4%
Other values (24) 24
34.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 14
20.3%
시 10
14.5%
주 4
 
5.8%
영 4
 
5.8%
경 3
 
4.3%
천 3
 
4.3%
청 2
 
2.9%
울 2
 
2.9%
성 2
 
2.9%
포 1
 
1.4%
Other values (24) 24
34.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 14
20.3%
시 10
14.5%
주 4
 
5.8%
영 4
 
5.8%
경 3
 
4.3%
천 3
 
4.3%
청 2
 
2.9%
울 2
 
2.9%
성 2
 
2.9%
포 1
 
1.4%
Other values (24) 24
34.8%

기본형공익직접지불제 지급면적(ha)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7993.6957
Minimum368
Maximum19656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-23T07:42:02.591480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum368
5-th percentile3017.6
Q14024
median7851
Q310484.5
95-th percentile15738.9
Maximum19656
Range19288
Interquartile range (IQR)6460.5

Descriptive statistics

Standard deviation4743.0404
Coefficient of variation (CV)0.59334763
Kurtosis0.20924887
Mean7993.6957
Median Absolute Deviation (MAD)3673
Skewness0.73051518
Sum183855
Variance22496432
MonotonicityNot monotonic
2023-12-23T07:42:03.283590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
8587 1
 
4.3%
12435 1
 
4.3%
368 1
 
4.3%
3023 1
 
4.3%
8157 1
 
4.3%
13956 1
 
4.3%
3017 1
 
4.3%
6728 1
 
4.3%
3631 1
 
4.3%
6120 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
368 1
4.3%
3017 1
4.3%
3023 1
4.3%
3631 1
4.3%
3828 1
4.3%
3870 1
4.3%
4178 1
4.3%
4806 1
4.3%
5745 1
4.3%
6120 1
4.3%
ValueCountFrequency (%)
19656 1
4.3%
15937 1
4.3%
13956 1
4.3%
13515 1
4.3%
12435 1
4.3%
10777 1
4.3%
10192 1
4.3%
8912 1
4.3%
8587 1
4.3%
8566 1
4.3%

기본형공익직접지불제 지원액(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17097488
Minimum632318
Maximum40404506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-23T07:42:04.083249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum632318
5-th percentile7494820.4
Q19722057.5
median15426930
Q321682580
95-th percentile32905664
Maximum40404506
Range39772188
Interquartile range (IQR)11960522

Descriptive statistics

Standard deviation9535786.5
Coefficient of variation (CV)0.55773026
Kurtosis0.26472596
Mean17097488
Median Absolute Deviation (MAD)6253076
Skewness0.68269611
Sum3.9324222 × 108
Variance9.0931224 × 1013
MonotonicityNot monotonic
2023-12-23T07:42:04.903871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20088424 1
 
4.3%
28332931 1
 
4.3%
632318 1
 
4.3%
7808800 1
 
4.3%
14918316 1
 
4.3%
27817068 1
 
4.3%
7640606 1
 
4.3%
15426930 1
 
4.3%
8788867 1
 
4.3%
14598732 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
632318 1
4.3%
7478622 1
4.3%
7640606 1
4.3%
7808800 1
4.3%
8788867 1
4.3%
9173854 1
4.3%
10270261 1
4.3%
10848972 1
4.3%
11386184 1
4.3%
14598732 1
4.3%
ValueCountFrequency (%)
40404506 1
4.3%
33413746 1
4.3%
28332931 1
4.3%
27817068 1
4.3%
26456429 1
4.3%
22834756 1
4.3%
20530404 1
4.3%
20088424 1
4.3%
19332541 1
4.3%
17739763 1
4.3%

경관보전직접지불제 지급면적(ha)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
17 
54
2 
3
2 
12
 
1
14
 
1

Length

Max length4
Median length4
Mean length3.3913043
Min length1

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row54
2nd row<NA>
3rd row3
4th row54
5th row12

Common Values

ValueCountFrequency (%)
<NA> 17
73.9%
54 2
 
8.7%
3 2
 
8.7%
12 1
 
4.3%
14 1
 
4.3%

Length

2023-12-23T07:42:05.955937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:42:06.791661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
73.9%
54 2
 
8.7%
3 2
 
8.7%
12 1
 
4.3%
14 1
 
4.3%

경관보전직접지불제 지원액(천원)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
18 
71030
 
1
1366
 
1
24558
 
1
6504
 
1

Length

Max length5
Median length4
Mean length4.0434783
Min length3

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st row71030
2nd row<NA>
3rd row1366
4th row24558
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
78.3%
71030 1
 
4.3%
1366 1
 
4.3%
24558 1
 
4.3%
6504 1
 
4.3%
181 1
 
4.3%

Length

2023-12-23T07:42:07.389733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T07:42:07.990816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
78.3%
71030 1
 
4.3%
1366 1
 
4.3%
24558 1
 
4.3%
6504 1
 
4.3%
181 1
 
4.3%

Interactions

2023-12-23T07:41:57.437459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:41:56.149831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:41:57.812326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:41:56.778805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T07:42:08.443596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분기본형공익직접지불제 지급면적(ha)기본형공익직접지불제 지원액(천원)경관보전직접지불제 지급면적(ha)경관보전직접지불제 지원액(천원)
구 분1.0001.0001.0001.0001.000
기본형공익직접지불제 지급면적(ha)1.0001.0000.8461.0001.000
기본형공익직접지불제 지원액(천원)1.0000.8461.0000.5731.000
경관보전직접지불제 지급면적(ha)1.0001.0000.5731.0001.000
경관보전직접지불제 지원액(천원)1.0001.0001.0001.0001.000
2023-12-23T07:42:08.785279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경관보전직접지불제 지급면적(ha)경관보전직접지불제 지원액(천원)
경관보전직접지불제 지급면적(ha)1.0001.000
경관보전직접지불제 지원액(천원)1.0001.000
2023-12-23T07:42:09.373762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본형공익직접지불제 지급면적(ha)기본형공익직접지불제 지원액(천원)경관보전직접지불제 지급면적(ha)경관보전직접지불제 지원액(천원)
기본형공익직접지불제 지급면적(ha)1.0000.9851.0001.000
기본형공익직접지불제 지원액(천원)0.9851.0000.0001.000
경관보전직접지불제 지급면적(ha)1.0000.0001.0001.000
경관보전직접지불제 지원액(천원)1.0001.0001.0001.000

Missing values

2023-12-23T07:41:58.337416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:41:58.902970image/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

구 분기본형공익직접지불제 지급면적(ha)기본형공익직접지불제 지원액(천원)경관보전직접지불제 지급면적(ha)경관보전직접지불제 지원액(천원)
0포항시8587200884245471030
1경주시1243528332931<NA><NA>
2김천시107772283475631366
3안동시13515264564295424558
4구미시78511731919412<NA>
5영주시1019219332541<NA><NA>
6영천시891220530404<NA><NA>
7상주시1965640404506146504
8문경시856617739763<NA><NA>
9경산시417810270261<NA><NA>
구 분기본형공익직접지불제 지급면적(ha)기본형공익직접지불제 지원액(천원)경관보전직접지불제 지급면적(ha)경관보전직접지불제 지원액(천원)
13영양군38287478622<NA><NA>
14영덕군38709173854<NA><NA>
15청도군612014598732<NA><NA>
16고령군363187888673181
17성주군672815426930<NA><NA>
18칠곡군30177640606<NA><NA>
19예천군1395627817068<NA><NA>
20봉화군815714918316<NA><NA>
21울진군30237808800<NA><NA>
22울릉군368632318<NA><NA>