Overview

Dataset statistics

Number of variables3
Number of observations878
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.3 KiB
Average record size in memory27.2 B

Variable types

Numeric2
Categorical1

Dataset

Description농가의 일일 영농활동(교육, 시비 작업 등), 생산, 판매 활동 등 기록 관리시스템으로 품목재배일련번호, 년도 비고 등을 제공합니다.
Author충청북도
URLhttps://www.data.go.kr/data/15050314/fileData.do

Alerts

비고 is highly imbalanced (98.7%)Imbalance

Reproduction

Analysis started2023-12-12 04:47:25.503911
Analysis finished2023-12-12 04:47:26.210687
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목재배 일련번호
Real number (ℝ)

Distinct722
Distinct (%)82.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11744.835
Minimum8
Maximum15605
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2023-12-12T13:47:26.276935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile2768
Q111131.75
median12799
Q314558.75
95-th percentile15358.4
Maximum15605
Range15597
Interquartile range (IQR)3427

Descriptive statistics

Standard deviation3658.9813
Coefficient of variation (CV)0.31153961
Kurtosis1.5227864
Mean11744.835
Median Absolute Deviation (MAD)1713
Skewness-1.4886887
Sum10311965
Variance13388144
MonotonicityIncreasing
2023-12-12T13:47:26.407512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14805 5
 
0.6%
14804 5
 
0.6%
14803 5
 
0.6%
15385 4
 
0.5%
11532 4
 
0.5%
15384 4
 
0.5%
13886 4
 
0.5%
15382 4
 
0.5%
15381 4
 
0.5%
15380 4
 
0.5%
Other values (712) 835
95.1%
ValueCountFrequency (%)
8 1
0.1%
10 1
0.1%
18 1
0.1%
19 1
0.1%
26 1
0.1%
337 1
0.1%
338 1
0.1%
588 1
0.1%
589 1
0.1%
697 1
0.1%
ValueCountFrequency (%)
15605 2
0.2%
15585 1
0.1%
15559 1
0.1%
15522 2
0.2%
15519 2
0.2%
15475 1
0.1%
15450 1
0.1%
15449 1
0.1%
15439 1
0.1%
15428 1
0.1%

년도
Real number (ℝ)

Distinct11
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.9351
Minimum2010
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.8 KiB
2023-12-12T13:47:26.557588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2015
Q12016
median2016
Q32016
95-th percentile2017
Maximum2020
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.88655197
Coefficient of variation (CV)0.00043977208
Kurtosis8.1066859
Mean2015.9351
Median Absolute Deviation (MAD)0
Skewness-1.1226873
Sum1769991
Variance0.7859744
MonotonicityNot monotonic
2023-12-12T13:47:26.671497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2016 565
64.4%
2017 133
 
15.1%
2015 130
 
14.8%
2014 19
 
2.2%
2018 9
 
1.0%
2012 8
 
0.9%
2013 6
 
0.7%
2020 3
 
0.3%
2019 3
 
0.3%
2011 1
 
0.1%
ValueCountFrequency (%)
2010 1
 
0.1%
2011 1
 
0.1%
2012 8
 
0.9%
2013 6
 
0.7%
2014 19
 
2.2%
2015 130
 
14.8%
2016 565
64.4%
2017 133
 
15.1%
2018 9
 
1.0%
2019 3
 
0.3%
ValueCountFrequency (%)
2020 3
 
0.3%
2019 3
 
0.3%
2018 9
 
1.0%
2017 133
 
15.1%
2016 565
64.4%
2015 130
 
14.8%
2014 19
 
2.2%
2013 6
 
0.7%
2012 8
 
0.9%
2011 1
 
0.1%

비고
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
<NA>
877 
1
 
1

Length

Max length4
Median length4
Mean length3.9965831
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 877
99.9%
1 1
 
0.1%

Length

2023-12-12T13:47:26.808451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:47:26.934839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 877
99.9%
1 1
 
0.1%

Interactions

2023-12-12T13:47:25.809182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:47:25.594573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:47:25.919917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:47:25.708925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:47:27.012778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목재배 일련번호년도
품목재배 일련번호1.0000.416
년도0.4161.000
2023-12-12T13:47:27.119936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목재배 일련번호년도비고
품목재배 일련번호1.0000.282NaN
년도0.2821.000NaN
비고NaNNaN1.000

Missing values

2023-12-12T13:47:26.097899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:47:26.179901image/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

품목재배 일련번호년도비고
0820161
1102016<NA>
2182016<NA>
3192016<NA>
4262016<NA>
53372016<NA>
63382016<NA>
75882016<NA>
85892016<NA>
96972016<NA>
품목재배 일련번호년도비고
868154502017<NA>
869154752017<NA>
870155192017<NA>
871155192016<NA>
872155222017<NA>
873155222016<NA>
874155592017<NA>
875155852017<NA>
876156052016<NA>
877156052017<NA>