Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory771.5 KiB
Average record size in memory79.0 B

Variable types

Numeric4
Categorical4

Dataset

Description가축분뇨 전자인계관리시스템에서 관리하고 있는 데이터 중에 액비를 배출하는 배출자의 관리 대장에 대한 정보 입니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15041910/fileData.do

Alerts

비료구분 has constant value ""Constant
처리구분 has constant value ""Constant
대장등록타입 has constant value ""Constant
배출업체번호 is highly overall correlated with 운반업체번호High correlation
운반업체번호 is highly overall correlated with 배출업체번호High correlation
관리대장번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:22:08.588554
Analysis finished2023-12-12 15:22:12.391674
Duration3.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리대장번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean452647.02
Minimum382159
Maximum788783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:22:12.489470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum382159
5-th percentile384566.9
Q1394439.75
median431382.5
Q3509306.75
95-th percentile563407.2
Maximum788783
Range406624
Interquartile range (IQR)114867

Descriptive statistics

Standard deviation66446.69
Coefficient of variation (CV)0.14679582
Kurtosis0.3990478
Mean452647.02
Median Absolute Deviation (MAD)42518
Skewness0.85631312
Sum4.5264702 × 109
Variance4.4151626 × 109
MonotonicityNot monotonic
2023-12-13T00:22:12.712526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
397543 1
 
< 0.1%
436959 1
 
< 0.1%
405023 1
 
< 0.1%
385470 1
 
< 0.1%
538915 1
 
< 0.1%
390367 1
 
< 0.1%
450580 1
 
< 0.1%
400370 1
 
< 0.1%
404445 1
 
< 0.1%
563411 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
382159 1
< 0.1%
382160 1
< 0.1%
382161 1
< 0.1%
382162 1
< 0.1%
382165 1
< 0.1%
382181 1
< 0.1%
382184 1
< 0.1%
382188 1
< 0.1%
382194 1
< 0.1%
382197 1
< 0.1%
ValueCountFrequency (%)
788783 1
< 0.1%
788778 1
< 0.1%
788777 1
< 0.1%
788776 1
< 0.1%
788770 1
< 0.1%
788767 1
< 0.1%
788760 1
< 0.1%
788753 1
< 0.1%
764730 1
< 0.1%
764728 1
< 0.1%

배출업체번호
Real number (ℝ)

HIGH CORRELATION 

Distinct979
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0157826 × 109
Minimum2.0130001 × 109
Maximum2.0210005 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:22:12.934696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0130001 × 109
5-th percentile2.0130004 × 109
Q12.0150004 × 109
median2.0160016 × 109
Q32.016004 × 109
95-th percentile2.0180108 × 109
Maximum2.0210005 × 109
Range8000310
Interquartile range (IQR)1003605

Descriptive statistics

Standard deviation1469712.6
Coefficient of variation (CV)0.00072910273
Kurtosis1.4209399
Mean2.0157826 × 109
Median Absolute Deviation (MAD)998498
Skewness0.31671403
Sum2.0157826 × 1013
Variance2.1600552 × 1012
MonotonicityNot monotonic
2023-12-13T00:22:13.158484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2016000840 96
 
1.0%
2016000829 94
 
0.9%
2013000588 88
 
0.9%
2014000326 85
 
0.9%
2017000106 71
 
0.7%
2017000118 71
 
0.7%
2015000301 70
 
0.7%
2015000094 63
 
0.6%
2016000841 61
 
0.6%
2017000119 60
 
0.6%
Other values (969) 9241
92.4%
ValueCountFrequency (%)
2013000149 2
 
< 0.1%
2013000160 36
0.4%
2013000174 2
 
< 0.1%
2013000201 5
 
0.1%
2013000202 9
 
0.1%
2013000217 8
 
0.1%
2013000236 5
 
0.1%
2013000238 5
 
0.1%
2013000240 3
 
< 0.1%
2013000256 12
 
0.1%
ValueCountFrequency (%)
2021000459 2
 
< 0.1%
2021000392 1
 
< 0.1%
2021000385 1
 
< 0.1%
2021000372 2
 
< 0.1%
2021000309 9
0.1%
2021000222 3
 
< 0.1%
2021000190 2
 
< 0.1%
2021000188 2
 
< 0.1%
2021000157 7
0.1%
2021000155 1
 
< 0.1%

운반업체번호
Real number (ℝ)

HIGH CORRELATION 

Distinct375
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0156182 × 109
Minimum2.0130001 × 109
Maximum2.0210005 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:22:13.387745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0130001 × 109
5-th percentile2.0130004 × 109
Q12.0150003 × 109
median2.016001 × 109
Q32.0160035 × 109
95-th percentile2.0180106 × 109
Maximum2.0210005 × 109
Range8000310
Interquartile range (IQR)1003218

Descriptive statistics

Standard deviation1448008.9
Coefficient of variation (CV)0.00071839444
Kurtosis1.6702278
Mean2.0156182 × 109
Median Absolute Deviation (MAD)1000522
Skewness0.52129782
Sum2.0156182 × 1013
Variance2.0967299 × 1012
MonotonicityNot monotonic
2023-12-13T00:22:13.617807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2016001370 173
 
1.7%
2016003536 172
 
1.7%
2016000978 134
 
1.3%
2016000840 132
 
1.3%
2014000276 122
 
1.2%
2015000223 120
 
1.2%
2016001881 119
 
1.2%
2015000366 109
 
1.1%
2016000829 106
 
1.1%
2016003636 102
 
1.0%
Other values (365) 8711
87.1%
ValueCountFrequency (%)
2013000149 2
 
< 0.1%
2013000160 36
0.4%
2013000201 3
 
< 0.1%
2013000202 9
 
0.1%
2013000217 8
 
0.1%
2013000238 5
 
0.1%
2013000256 12
 
0.1%
2013000259 1
 
< 0.1%
2013000261 5
 
0.1%
2013000277 22
0.2%
ValueCountFrequency (%)
2021000459 1
 
< 0.1%
2021000384 1
 
< 0.1%
2021000025 3
 
< 0.1%
2021000007 66
0.7%
2020000737 13
 
0.1%
2020000645 14
 
0.1%
2020000642 48
0.5%
2020000530 5
 
0.1%
2020000476 19
 
0.2%
2020000413 13
 
0.1%

비료구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 10000
100.0%

Length

2023-12-13T00:22:13.829727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:22:13.960365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10000
100.0%

처리구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
C
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
C 10000
100.0%

Length

2023-12-13T00:22:14.084128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:22:14.207526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
c 10000
100.0%

처리방법
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
6532 
<NA>
3422 
2
 
46

Length

Max length4
Median length1
Mean length2.0266
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row<NA>
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 6532
65.3%
<NA> 3422
34.2%
2 46
 
0.5%

Length

2023-12-13T00:22:14.337927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:22:14.481694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 6532
65.3%
na 3422
34.2%
2 46
 
0.5%

배출량
Real number (ℝ)

Distinct1596
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.39228
Minimum0
Maximum2660
Zeros12
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T00:22:14.631493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15
Q135
median70
Q3138
95-th percentile297
Maximum2660
Range2660
Interquartile range (IQR)103

Descriptive statistics

Standard deviation108.11438
Coefficient of variation (CV)1.0456717
Kurtosis48.425257
Mean103.39228
Median Absolute Deviation (MAD)46
Skewness4.232711
Sum1033922.8
Variance11688.719
MonotonicityNot monotonic
2023-12-13T00:22:14.811829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.0 473
 
4.7%
46.0 303
 
3.0%
48.0 291
 
2.9%
23.0 281
 
2.8%
60.0 181
 
1.8%
96.0 180
 
1.8%
72.0 178
 
1.8%
120.0 172
 
1.7%
22.0 157
 
1.6%
15.0 154
 
1.5%
Other values (1586) 7630
76.3%
ValueCountFrequency (%)
0.0 12
0.1%
1.0 1
 
< 0.1%
2.0 1
 
< 0.1%
3.0 1
 
< 0.1%
4.0 6
 
0.1%
4.2 1
 
< 0.1%
5.0 19
0.2%
5.47 1
 
< 0.1%
5.5 1
 
< 0.1%
5.9 1
 
< 0.1%
ValueCountFrequency (%)
2660.0 1
< 0.1%
1512.149 1
< 0.1%
1250.7 1
< 0.1%
1248.7 1
< 0.1%
1248.2 1
< 0.1%
1228.2 1
< 0.1%
1203.8 1
< 0.1%
1119.0 1
< 0.1%
1104.0 2
< 0.1%
1044.0 1
< 0.1%

대장등록타입
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
5
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 10000
100.0%

Length

2023-12-13T00:22:14.967623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:22:15.078662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 10000
100.0%

Interactions

2023-12-13T00:22:11.164660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:09.423211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:09.982162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:10.579610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:11.659290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:09.562097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:10.118479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:10.731373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:11.797181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:09.722671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:10.274901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:10.863056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:11.955953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:09.872646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:10.442667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:11.030409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:22:15.150647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리대장번호배출업체번호운반업체번호처리방법배출량
관리대장번호1.0000.1900.1810.0000.005
배출업체번호0.1901.0000.9330.3240.136
운반업체번호0.1810.9331.0000.3630.156
처리방법0.0000.3240.3631.0000.000
배출량0.0050.1360.1560.0001.000
2023-12-13T00:22:15.289133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리대장번호배출업체번호운반업체번호배출량처리방법
관리대장번호1.000-0.013-0.022-0.0470.000
배출업체번호-0.0131.0000.712-0.1340.249
운반업체번호-0.0220.7121.000-0.0790.278
배출량-0.047-0.134-0.0791.0000.000
처리방법0.0000.2490.2780.0001.000

Missing values

2023-12-13T00:22:12.120155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:22:12.321969image/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

관리대장번호배출업체번호운반업체번호비료구분처리구분처리방법배출량대장등록타입
17033397543201600361320160035361C174.05
12116391271201400024620140002461C163.05
22045414856201600170220160017021C<NA>13.05
31240476437201700007320160018691C124.05
20824409790201600056820150003701C123.05
43246554014201300041120130004111C180.05
40771541722201500022720150004051C<NA>50.955
40716539128201600406620150003611C146.05
24199432049201300038420130003841C1370.05
5959390077201700144920170014491C<NA>126.25
관리대장번호배출업체번호운반업체번호비료구분처리구분처리방법배출량대장등록타입
39774730562201400003220140000321C<NA>30.05
15230398061201600080020150003531C122.05
30394471761201500038620150003861C140.05
30531473564201300037120130003711C<NA>265.05
27785454390201600205420170015511C<NA>21.05
20230406650201500031120150003111C1180.05
34354497636202100037220200006421C<NA>24.05
45874573220201600041220150002231C148.05
10055394633202100015720140002481C<NA>115.05
12649395115201500038120150003811C140.05