Overview

Dataset statistics

Number of variables4
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory38.4 B

Variable types

Categorical3
Numeric1

Dataset

Description비철 금속의 종류인 니켈, 동, 아연, 알루미늄, 연, 주석의 2013~2017연도별 생산량 합계를 제공합니다.
URLhttps://www.data.go.kr/data/15117822/fileData.do

Alerts

광종 is highly overall correlated with 단위High correlation
단위 is highly overall correlated with 광종High correlation
생산량 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:18:24.628005
Analysis finished2023-12-12 14:18:25.117016
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광종
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
니켈
5 
동
5 
아연
5 
알루미늄
5 
연
5 

Length

Max length4
Median length3
Mean length2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
니켈 5
16.7%
동 5
16.7%
아연 5
16.7%
알루미늄 5
16.7%
연 5
16.7%
주석 5
16.7%

Length

2023-12-12T23:18:25.192919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:18:25.306832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
니켈 5
16.7%
동 5
16.7%
아연 5
16.7%
알루미늄 5
16.7%
연 5
16.7%
주석 5
16.7%

연도
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2013
6 
2014
6 
2015
6 
2016
6 
2017
6 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013
2nd row2014
3rd row2015
4th row2016
5th row2017

Common Values

ValueCountFrequency (%)
2013 6
20.0%
2014 6
20.0%
2015 6
20.0%
2016 6
20.0%
2017 6
20.0%

Length

2023-12-12T23:18:25.420611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:18:25.549687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2013 6
20.0%
2014 6
20.0%
2015 6
20.0%
2016 6
20.0%
2017 6
20.0%

생산량
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61739.368
Minimum289.2
Maximum299114.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-12T23:18:25.678054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum289.2
5-th percentile298.2
Q11353.925
median8196.5
Q312134.175
95-th percentile252029.81
Maximum299114.1
Range298824.9
Interquartile range (IQR)10780.25

Descriptive statistics

Standard deviation104197.85
Coefficient of variation (CV)1.6877051
Kurtosis4.1573212 × 10-5
Mean61739.368
Median Absolute Deviation (MAD)6836.65
Skewness1.3765815
Sum1852181
Variance1.0857192 × 1010
MonotonicityNot monotonic
2023-12-12T23:18:25.809993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1909.8 1
 
3.3%
218908.9 1
 
3.3%
317.9 1
 
3.3%
304.8 1
 
3.3%
289.2 1
 
3.3%
312.0 1
 
3.3%
292.8 1
 
3.3%
7352.8 1
 
3.3%
7468.7 1
 
3.3%
6459.4 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
289.2 1
3.3%
292.8 1
3.3%
304.8 1
3.3%
312.0 1
3.3%
317.9 1
3.3%
1219.0 1
3.3%
1221.5 1
3.3%
1348.0 1
3.3%
1371.7 1
3.3%
1909.8 1
3.3%
ValueCountFrequency (%)
299114.1 1
3.3%
253421.8 1
3.3%
250328.5 1
3.3%
242751.9 1
3.3%
231426.8 1
3.3%
226391.2 1
3.3%
218908.9 1
3.3%
12193.8 1
3.3%
11955.3 1
3.3%
11585.1 1
3.3%

단위
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
천톤
25 
톤
5 

Length

Max length2
Median length2
Mean length1.8333333
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
천톤 25
83.3%
톤 5
 
16.7%

Length

2023-12-12T23:18:25.938705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:18:26.047944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천톤 25
83.3%
톤 5
 
16.7%

Interactions

2023-12-12T23:18:24.787187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:18:26.117261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
광종연도생산량단위
광종1.0000.0000.6461.000
연도0.0001.0000.0000.000
생산량0.6460.0001.0000.000
단위1.0000.0000.0001.000
2023-12-12T23:18:26.209507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
광종연도단위
광종1.0000.0000.926
연도0.0001.0000.000
단위0.9260.0001.000
2023-12-12T23:18:26.293011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생산량광종연도단위
생산량1.0000.4580.0000.000
광종0.4581.0000.0000.926
연도0.0000.0001.0000.000
단위0.0000.9260.0001.000

Missing values

2023-12-12T23:18:24.998412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:18:25.084204image/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

광종연도생산량단위
0니켈20131909.8천톤
1니켈20141348.0천톤
2니켈20151371.7천톤
3니켈20161221.5천톤
4니켈20171219.0천톤
5동201311072.0천톤
6동201411249.0천톤
7동201511585.1천톤
8동201612193.8천톤
9동201711955.3천톤
광종연도생산량단위
20연20136982.143톤
21연20147386.6톤
22연20156459.4톤
23연20167468.7톤
24연20177352.8톤
25주석2013292.8천톤
26주석2014312.0천톤
27주석2015289.2천톤
28주석2016304.8천톤
29주석2017317.9천톤