Overview

Dataset statistics

Number of variables6
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory53.6 B

Variable types

Numeric2
Categorical3
Text1

Dataset

Description경상남도 농작물진단처방 기타항목 데이터입니다.
Author경상남도
URLhttps://www.data.go.kr/data/15049543/fileData.do

Alerts

분류코드(대) is highly overall correlated with 분류코드(소) and 3 other fieldsHigh correlation
분석기준 is highly overall correlated with 분류코드(소) and 3 other fieldsHigh correlation
분류코드(소) is highly overall correlated with 비용 and 2 other fieldsHigh correlation
비용 is highly overall correlated with 분류코드(소) and 3 other fieldsHigh correlation
단위 is highly overall correlated with 비용 and 2 other fieldsHigh correlation
분류코드(소) has unique valuesUnique

Reproduction

Analysis started2024-04-20 23:02:38.376348
Analysis finished2024-04-20 23:02:40.269880
Duration1.89 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류코드(소)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.638889
Minimum1
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-04-21T08:02:40.459249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.75
Q19.75
median19.5
Q329.25
95-th percentile36.25
Maximum38
Range37
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.319144
Coefficient of variation (CV)0.57636376
Kurtosis-1.2442776
Mean19.638889
Median Absolute Deviation (MAD)10
Skewness-0.027061858
Sum707
Variance128.12302
MonotonicityStrictly increasing
2024-04-21T08:02:40.867887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 1
 
2.8%
21 1
 
2.8%
24 1
 
2.8%
25 1
 
2.8%
26 1
 
2.8%
27 1
 
2.8%
28 1
 
2.8%
29 1
 
2.8%
30 1
 
2.8%
31 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1 1
2.8%
2 1
2.8%
3 1
2.8%
4 1
2.8%
5 1
2.8%
6 1
2.8%
7 1
2.8%
8 1
2.8%
9 1
2.8%
10 1
2.8%
ValueCountFrequency (%)
38 1
2.8%
37 1
2.8%
36 1
2.8%
35 1
2.8%
34 1
2.8%
33 1
2.8%
32 1
2.8%
31 1
2.8%
30 1
2.8%
29 1
2.8%

분류코드(대)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size416.0 B
E
15 
A
11 
C
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
E 15
41.7%
A 11
30.6%
C 10
27.8%

Length

2024-04-21T08:02:41.250170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:02:41.428846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e 15
41.7%
a 11
30.6%
c 10
27.8%

항목명
Text

Distinct33
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-04-21T08:02:41.999272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length3.3055556
Min length1

Characters and Unicode

Total characters119
Distinct characters67
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)83.3%

Sample

1st row규소(Si)
2nd row철(Fe)
3rd row망간(Mn)
4th row아연(Zn)
5th row비소
ValueCountFrequency (%)
질소 3
 
7.7%
망간 2
 
5.1%
크롬 2
 
5.1%
철 2
 
5.1%
규소(si 1
 
2.6%
석회 1
 
2.6%
염산불용해물 1
 
2.6%
인산 1
 
2.6%
칼리 1
 
2.6%
고토 1
 
2.6%
Other values (24) 24
61.5%
2024-04-21T08:02:43.053895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 8
 
6.7%
질 6
 
5.0%
산 5
 
4.2%
( 4
 
3.4%
) 4
 
3.4%
망 3
 
2.5%
리 3
 
2.5%
3
 
2.5%
간 3
 
2.5%
분 3
 
2.5%
Other values (57) 77
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 100
84.0%
Open Punctuation 4
 
3.4%
Close Punctuation 4
 
3.4%
Lowercase Letter 4
 
3.4%
Uppercase Letter 4
 
3.4%
Space Separator 3
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 8
 
8.0%
질 6
 
6.0%
산 5
 
5.0%
망 3
 
3.0%
리 3
 
3.0%
간 3
 
3.0%
분 3
 
3.0%
규 3
 
3.0%
철 3
 
3.0%
회 2
 
2.0%
Other values (47) 61
61.0%
Uppercase Letter
ValueCountFrequency (%)
Z 1
25.0%
S 1
25.0%
M 1
25.0%
F 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
n 2
50.0%
i 1
25.0%
e 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 100
84.0%
Common 11
 
9.2%
Latin 8
 
6.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 8
 
8.0%
질 6
 
6.0%
산 5
 
5.0%
망 3
 
3.0%
리 3
 
3.0%
간 3
 
3.0%
분 3
 
3.0%
규 3
 
3.0%
철 3
 
3.0%
회 2
 
2.0%
Other values (47) 61
61.0%
Latin
ValueCountFrequency (%)
n 2
25.0%
Z 1
12.5%
S 1
12.5%
i 1
12.5%
M 1
12.5%
F 1
12.5%
e 1
12.5%
Common
ValueCountFrequency (%)
( 4
36.4%
) 4
36.4%
3
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 100
84.0%
ASCII 19
 
16.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 8
 
8.0%
질 6
 
6.0%
산 5
 
5.0%
망 3
 
3.0%
리 3
 
3.0%
간 3
 
3.0%
분 3
 
3.0%
규 3
 
3.0%
철 3
 
3.0%
회 2
 
2.0%
Other values (47) 61
61.0%
ASCII
ValueCountFrequency (%)
( 4
21.1%
) 4
21.1%
3
15.8%
n 2
10.5%
Z 1
 
5.3%
S 1
 
5.3%
i 1
 
5.3%
M 1
 
5.3%
F 1
 
5.3%
e 1
 
5.3%

비용
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13833.333
Minimum8500
Maximum30400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-04-21T08:02:43.414116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8500
5-th percentile8500
Q18500
median13000
Q314300
95-th percentile29000
Maximum30400
Range21900
Interquartile range (IQR)5800

Descriptive statistics

Standard deviation6442.892
Coefficient of variation (CV)0.46575123
Kurtosis1.2894203
Mean13833.333
Median Absolute Deviation (MAD)3700
Skewness1.4375862
Sum498000
Variance41510857
MonotonicityNot monotonic
2024-04-21T08:02:43.767355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8500 11
30.6%
14300 10
27.8%
9900 4
 
11.1%
9600 2
 
5.6%
30200 1
 
2.8%
17000 1
 
2.8%
30400 1
 
2.8%
20500 1
 
2.8%
22900 1
 
2.8%
16000 1
 
2.8%
Other values (3) 3
 
8.3%
ValueCountFrequency (%)
8500 11
30.6%
9600 2
 
5.6%
9900 4
 
11.1%
11700 1
 
2.8%
14300 10
27.8%
16000 1
 
2.8%
17000 1
 
2.8%
20500 1
 
2.8%
22900 1
 
2.8%
25400 1
 
2.8%
ValueCountFrequency (%)
30400 1
 
2.8%
30200 1
 
2.8%
28600 1
 
2.8%
25400 1
 
2.8%
22900 1
 
2.8%
20500 1
 
2.8%
17000 1
 
2.8%
16000 1
 
2.8%
14300 10
27.8%
11700 1
 
2.8%

분석기준
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size416.0 B
농촌진흥청고시 제2017-19
15 
수질오염공정시험기준
11 
농촌진흥청토양및식물체분석법
9 
토양오염공정시험기준
 
1

Length

Max length16
Median length14
Mean length13.5
Min length10

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
농촌진흥청고시 제2017-19 15
41.7%
수질오염공정시험기준 11
30.6%
농촌진흥청토양및식물체분석법 9
25.0%
토양오염공정시험기준 1
 
2.8%

Length

2024-04-21T08:02:44.159523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:02:44.498781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농촌진흥청고시 15
29.4%
제2017-19 15
29.4%
수질오염공정시험기준 11
21.6%
농촌진흥청토양및식물체분석법 9
17.6%
토양오염공정시험기준 1
 
2.0%

단위
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size416.0 B
%
13 
mg/L
11 
mg/kg
9 
kg/10a
 
1
cmolc/kg
 
1

Length

Max length8
Median length6
Mean length3.3333333
Min length1

Unique

Unique3 ?
Unique (%)8.3%

Sample

1st rowmg/L
2nd rowmg/L
3rd rowmg/L
4th rowmg/L
5th rowmg/L

Common Values

ValueCountFrequency (%)
% 13
36.1%
mg/L 11
30.6%
mg/kg 9
25.0%
kg/10a 1
 
2.8%
cmolc/kg 1
 
2.8%
<NA> 1
 
2.8%

Length

2024-04-21T08:02:44.896028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:02:45.247891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13
36.1%
mg/l 11
30.6%
mg/kg 9
25.0%
kg/10a 1
 
2.8%
cmolc/kg 1
 
2.8%
na 1
 
2.8%

Interactions

2024-04-21T08:02:39.243570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:02:38.755005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:02:39.490056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:02:39.008344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T08:02:45.487212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류코드(소)분류코드(대)항목명비용분석기준단위
분류코드(소)1.0000.9360.7250.6440.8930.874
분류코드(대)0.9361.0000.0000.8291.0000.838
항목명0.7250.0001.0000.9640.0000.973
비용0.6440.8290.9641.0000.8690.793
분석기준0.8931.0000.0000.8691.0000.746
단위0.8740.8380.9730.7930.7461.000
2024-04-21T08:02:45.755232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단위분류코드(대)분석기준
단위1.0000.8440.678
분류코드(대)0.8441.0000.985
분석기준0.6780.9851.000
2024-04-21T08:02:46.010867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류코드(소)비용분류코드(대)분석기준단위
분류코드(소)1.0000.6520.8140.6910.494
비용0.6521.0000.5780.7100.523
분류코드(대)0.8140.5781.0000.9850.844
분석기준0.6910.7100.9851.0000.678
단위0.4940.5230.8440.6781.000

Missing values

2024-04-21T08:02:39.799079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T08:02:40.139000image/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

분류코드(소)분류코드(대)항목명비용분석기준단위
01A규소(Si)8500수질오염공정시험기준mg/L
12A철(Fe)8500수질오염공정시험기준mg/L
23A망간(Mn)8500수질오염공정시험기준mg/L
34A아연(Zn)8500수질오염공정시험기준mg/L
45A비소8500수질오염공정시험기준mg/L
56A니켈8500수질오염공정시험기준mg/L
67A카드뮴8500수질오염공정시험기준mg/L
78A구리8500수질오염공정시험기준mg/L
89A크롬8500수질오염공정시험기준mg/L
910A수은8500수질오염공정시험기준mg/L
분류코드(소)분류코드(대)항목명비용분석기준단위
2629E규산14300농촌진흥청고시 제2017-19%
2730E붕소14300농촌진흥청고시 제2017-19%
2831E망간14300농촌진흥청고시 제2017-19mg/kg
2932E철14300농촌진흥청고시 제2017-19mg/kg
3033E알카리분14300농촌진흥청고시 제2017-19%
3134E분말도9600농촌진흥청고시 제2017-19%
3235E입상9600농촌진흥청고시 제2017-19%
3336E붕괴도25400농촌진흥청고시 제2017-19%
3437E유기물대질소비28600농촌진흥청고시 제2017-19<NA>
3538C크롬11700토양오염공정시험기준mg/kg