Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory51.3 B

Variable types

Numeric1
Categorical5

Dataset

Description임산물 양여에 관한 전반적인 정보(임산물 양여대상지)
Author산림청
URLhttps://www.data.go.kr/data/15069872/fileData.do

Alerts

경영계획구ID has constant value ""Constant
차기번호 has constant value ""Constant
임산물양여 가능 대상지(임산물생산)ID is highly overall correlated with 관리순번 and 1 other fieldsHigh correlation
임반ID is highly overall correlated with 관리순번 and 1 other fieldsHigh correlation
관리순번 is highly overall correlated with 임반ID and 1 other fieldsHigh correlation
관리순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:17:08.879187
Analysis finished2023-12-12 12:17:09.488796
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-12T21:17:09.597797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-12T21:17:09.783894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

경영계획구ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
춘천
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
춘천 100
100.0%

Length

2023-12-12T21:17:09.954318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:17:10.065937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
춘천 100
100.0%

임반ID
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
039-000
18 
040-000
18 
035-000
10 
037-000
10 
104-000
10 
Other values (11)
34 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row035-000
2nd row035-000
3rd row035-000
4th row035-000
5th row035-000

Common Values

ValueCountFrequency (%)
039-000 18
18.0%
040-000 18
18.0%
035-000 10
10.0%
037-000 10
10.0%
104-000 10
10.0%
038-000 8
8.0%
036-000 5
 
5.0%
058-000 3
 
3.0%
066-000 3
 
3.0%
103-000 3
 
3.0%
Other values (6) 12
12.0%

Length

2023-12-12T21:17:10.193971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
039-000 18
18.0%
040-000 18
18.0%
035-000 10
10.0%
037-000 10
10.0%
104-000 10
10.0%
038-000 8
8.0%
036-000 5
 
5.0%
058-000 3
 
3.0%
066-000 3
 
3.0%
103-000 3
 
3.0%
Other values (6) 12
12.0%

소반ID
Categorical

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
002-000
16 
001-000
15 
003-000
14 
004-000
12 
005-000
11 
Other values (7)
32 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row001-000
2nd row010-000
3rd row002-000
4th row003-000
5th row004-000

Common Values

ValueCountFrequency (%)
002-000 16
16.0%
001-000 15
15.0%
003-000 14
14.0%
004-000 12
12.0%
005-000 11
11.0%
006-000 10
10.0%
007-000 7
7.0%
008-000 6
 
6.0%
009-000 6
 
6.0%
010-000 1
 
1.0%
Other values (2) 2
 
2.0%

Length

2023-12-12T21:17:10.330082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
002-000 16
16.0%
001-000 15
15.0%
003-000 14
14.0%
004-000 12
12.0%
005-000 11
11.0%
006-000 10
10.0%
007-000 7
7.0%
008-000 6
 
6.0%
009-000 6
 
6.0%
010-000 1
 
1.0%
Other values (2) 2
 
2.0%

임산물양여 가능 대상지(임산물생산)ID
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
강원도 춘천시 사북면 오탄리
54 
강원도 춘천시 사북면 원평리
32 
강원도 화천군 간동면 간척리
11 
강원도 춘천시 사북면 고성리
 
3

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도 춘천시 사북면 원평리
2nd row강원도 춘천시 사북면 원평리
3rd row강원도 춘천시 사북면 원평리
4th row강원도 춘천시 사북면 원평리
5th row강원도 춘천시 사북면 원평리

Common Values

ValueCountFrequency (%)
강원도 춘천시 사북면 오탄리 54
54.0%
강원도 춘천시 사북면 원평리 32
32.0%
강원도 화천군 간동면 간척리 11
 
11.0%
강원도 춘천시 사북면 고성리 3
 
3.0%

Length

2023-12-12T21:17:10.460093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:17:10.583247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 100
25.0%
춘천시 89
22.2%
사북면 89
22.2%
오탄리 54
13.5%
원평리 32
 
8.0%
화천군 11
 
2.8%
간동면 11
 
2.8%
간척리 11
 
2.8%
고성리 3
 
0.8%

차기번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
8
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
8 100
100.0%

Length

2023-12-12T21:17:10.706312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:17:10.802464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 100
100.0%

Interactions

2023-12-12T21:17:09.123222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:17:10.874065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리순번임반ID소반ID임산물양여 가능 대상지(임산물생산)ID
관리순번1.0000.9410.0430.909
임반ID0.9411.0000.0001.000
소반ID0.0430.0001.0000.000
임산물양여 가능 대상지(임산물생산)ID0.9091.0000.0001.000
2023-12-12T21:17:10.968395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
임산물양여 가능 대상지(임산물생산)ID임반ID소반ID
임산물양여 가능 대상지(임산물생산)ID1.0000.9350.000
임반ID0.9351.0000.000
소반ID0.0000.0001.000
2023-12-12T21:17:11.065249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리순번임반ID소반ID임산물양여 가능 대상지(임산물생산)ID
관리순번1.0000.7310.0000.773
임반ID0.7311.0000.0000.935
소반ID0.0000.0001.0000.000
임산물양여 가능 대상지(임산물생산)ID0.7730.9350.0001.000

Missing values

2023-12-12T21:17:09.284070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:17:09.439009image/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

관리순번경영계획구ID임반ID소반ID임산물양여 가능 대상지(임산물생산)ID차기번호
01춘천035-000001-000강원도 춘천시 사북면 원평리8
12춘천035-000010-000강원도 춘천시 사북면 원평리8
23춘천035-000002-000강원도 춘천시 사북면 원평리8
34춘천035-000003-000강원도 춘천시 사북면 원평리8
45춘천035-000004-000강원도 춘천시 사북면 원평리8
56춘천035-000005-000강원도 춘천시 사북면 원평리8
67춘천035-000006-000강원도 춘천시 사북면 원평리8
78춘천035-000007-000강원도 춘천시 사북면 원평리8
89춘천035-000008-000강원도 춘천시 사북면 원평리8
910춘천035-000009-000강원도 춘천시 사북면 원평리8
관리순번경영계획구ID임반ID소반ID임산물양여 가능 대상지(임산물생산)ID차기번호
9091춘천104-000004-000강원도 춘천시 사북면 원평리8
9192춘천104-000005-000강원도 춘천시 사북면 원평리8
9293춘천104-000006-000강원도 춘천시 사북면 원평리8
9394춘천104-000007-000강원도 춘천시 사북면 원평리8
9495춘천104-000008-000강원도 춘천시 사북면 원평리8
9596춘천104-000008-001강원도 춘천시 사북면 원평리8
9697춘천104-000009-000강원도 춘천시 사북면 원평리8
9798춘천106-000001-000강원도 춘천시 사북면 고성리8
9899춘천106-000002-000강원도 춘천시 사북면 고성리8
99100춘천106-000003-000강원도 춘천시 사북면 고성리8