Overview

Dataset statistics

Number of variables5
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory44.1 B

Variable types

Categorical2
DateTime1
Numeric2

Dataset

Description4차산업 원료광물의 국내 수급 리스크의 표준척도로서 수급위기(0~1&위기발생), 수급불안 (0~5), 수급주의 (5~20), 수급안정 (20~80), 공급과잉(80~100) 지수를 제공합니다. 수급안정화지수는 광종별 중장기 가격리스크, 세계 수급비율(공급/소비), 세계 공급(매장)편중도, 국내 수입증가율, 국내 수입국 편중도 등을 반영한 수급리스크의 표준척도 입니다.
URLhttps://www.data.go.kr/data/15104262/fileData.do

Alerts

광종 has constant value ""Constant
가격단위 has constant value ""Constant
수급안정화지수 is highly overall correlated with 실질가격(유럽 로테르담 기준)High correlation
실질가격(유럽 로테르담 기준) is highly overall correlated with 수급안정화지수High correlation
기간 has unique valuesUnique
수급안정화지수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:01:32.122302
Analysis finished2023-12-12 17:01:32.891501
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

광종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
코발트
63 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
코발트 63
100.0%

Length

2023-12-13T02:01:32.961657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:01:33.066603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
코발트 63
100.0%

기간
Date

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum2018-01-01 00:00:00
Maximum2023-03-01 00:00:00
2023-12-13T02:01:33.188823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:33.392073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수급안정화지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.352739
Minimum3.2785099
Maximum73.916652
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-13T02:01:33.574975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2785099
5-th percentile3.4262832
Q17.9704679
median39.400025
Q359.296577
95-th percentile65.998007
Maximum73.916652
Range70.638142
Interquartile range (IQR)51.32611

Descriptive statistics

Standard deviation24.191928
Coefficient of variation (CV)0.66547746
Kurtosis-1.5931537
Mean36.352739
Median Absolute Deviation (MAD)21.352729
Skewness-0.17410167
Sum2290.2225
Variance585.24939
MonotonicityNot monotonic
2023-12-13T02:01:33.766804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.529362115 1
 
1.6%
4.151129594 1
 
1.6%
59.07563109 1
 
1.6%
57.57362421 1
 
1.6%
44.76538711 1
 
1.6%
25.36476523 1
 
1.6%
18.06434942 1
 
1.6%
26.88832219 1
 
1.6%
35.27208713 1
 
1.6%
40.63973148 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
3.278509852 1
1.6%
3.359499082 1
1.6%
3.402339844 1
1.6%
3.417726422 1
1.6%
3.503294168 1
1.6%
3.504059394 1
1.6%
3.781825527 1
1.6%
3.973244602 1
1.6%
4.151129594 1
1.6%
4.529362115 1
1.6%
ValueCountFrequency (%)
73.91665187 1
1.6%
69.51523353 1
1.6%
67.96434761 1
1.6%
66.03007441 1
1.6%
65.70939565 1
1.6%
65.01683564 1
1.6%
64.58344072 1
1.6%
63.11054857 1
1.6%
61.92779033 1
1.6%
61.33438189 1
1.6%

실질가격(유럽 로테르담 기준)
Real number (ℝ)

HIGH CORRELATION 

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.80054
Minimum12.697461
Maximum45.242099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-13T02:01:33.955225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.697461
5-th percentile14.376337
Q116.307429
median22.819742
Q333.917151
95-th percentile41.824177
Maximum45.242099
Range32.544638
Interquartile range (IQR)17.609722

Descriptive statistics

Standard deviation9.5645328
Coefficient of variation (CV)0.38565825
Kurtosis-0.96002197
Mean24.80054
Median Absolute Deviation (MAD)6.8877495
Skewness0.60227186
Sum1562.434
Variance91.480288
MonotonicityNot monotonic
2023-12-13T02:01:34.131981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.17149268 2
 
3.2%
38.26106075 1
 
1.6%
15.209999 1
 
1.6%
15.28701166 1
 
1.6%
18.09282339 1
 
1.6%
22.83069841 1
 
1.6%
25.29560568 1
 
1.6%
22.52763605 1
 
1.6%
20.40619947 1
 
1.6%
20.99212005 1
 
1.6%
Other values (52) 52
82.5%
ValueCountFrequency (%)
12.69746119 1
1.6%
13.82377125 1
1.6%
13.95854339 1
1.6%
14.34360665 1
1.6%
14.67091043 1
1.6%
14.71904334 1
1.6%
15.15223951 1
1.6%
15.17149268 2
3.2%
15.209999 1
1.6%
15.23887875 1
1.6%
ValueCountFrequency (%)
45.24209891 1
1.6%
44.75529061 1
1.6%
42.76662692 1
1.6%
42.08302378 1
1.6%
39.49456029 1
1.6%
39.48326031 1
1.6%
39.15181636 1
1.6%
39.07694409 1
1.6%
38.26106075 1
1.6%
38.14227927 1
1.6%

가격단위
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
달러/파운드
63 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row달러/파운드
2nd row달러/파운드
3rd row달러/파운드
4th row달러/파운드
5th row달러/파운드

Common Values

ValueCountFrequency (%)
달러/파운드 63
100.0%

Length

2023-12-13T02:01:34.290922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:01:34.430237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달러/파운드 63
100.0%

Interactions

2023-12-13T02:01:32.466703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:32.243454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:32.584098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:01:32.363672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:01:34.504582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기간수급안정화지수실질가격(유럽 로테르담 기준)
기간1.0001.0001.000
수급안정화지수1.0001.0000.902
실질가격(유럽 로테르담 기준)1.0000.9021.000
2023-12-13T02:01:34.617743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수급안정화지수실질가격(유럽 로테르담 기준)
수급안정화지수1.000-0.955
실질가격(유럽 로테르담 기준)-0.9551.000

Missing values

2023-12-13T02:01:32.713586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:01:32.845780image/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

광종기간수급안정화지수실질가격(유럽 로테르담 기준)가격단위
0코발트2018-01-014.52936238.261061달러/파운드
1코발트2018-02-014.1511339.48326달러/파운드
2코발트2018-03-013.4023442.766627달러/파운드
3코발트2018-04-013.2785145.242099달러/파운드
4코발트2018-05-013.41772644.755291달러/파운드
5코발트2018-06-013.50405942.083024달러/파운드
6코발트2018-07-013.97324539.151816달러/파운드
7코발트2018-08-015.50659834.874118달러/파운드
8코발트2018-09-015.45663934.635893달러/파운드
9코발트2018-10-015.64248634.977694달러/파운드
광종기간수급안정화지수실질가격(유럽 로테르담 기준)가격단위
53코발트2022-06-0125.71166434.701917달러/파운드
54코발트2022-07-0139.40002528.755858달러/파운드
55코발트2022-08-0149.97703825.056972달러/파운드
56코발트2022-09-0136.5332126.170615달러/파운드
57코발트2022-10-0137.41230725.961807달러/파운드
58코발트2022-11-0143.70819124.172023달러/파운드
59코발트2022-12-0147.95891322.819742달러/파운드
60코발트2023-01-0158.44326419.949913달러/파운드
61코발트2023-02-0165.70939617.456173달러/파운드
62코발트2023-03-0165.01683617.632202달러/파운드