Overview

Dataset statistics

Number of variables5
Number of observations23
Missing cells4
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory50.7 B

Variable types

Numeric2
Categorical3

Dataset

Description연도별 철강(철재류, 냉연 등) 수송실적 입니다.
Author한국철도공사
URLhttps://www.data.go.kr/data/15068403/fileData.do

Alerts

열연(톤) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
냉연(톤) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
기타철재(톤) is highly overall correlated with 연도 and 2 other fieldsHigh correlation
연도 is highly overall correlated with 철재류(톤) and 3 other fieldsHigh correlation
철재류(톤) is highly overall correlated with 연도High correlation
냉연(톤) is highly imbalanced (56.3%)Imbalance
열연(톤) is highly imbalanced (56.3%)Imbalance
기타철재(톤) is highly imbalanced (56.3%)Imbalance
철재류(톤) has 4 (17.4%) missing valuesMissing
연도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:25:33.034624
Analysis finished2023-12-12 21:25:33.939175
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007
Minimum1996
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:25:33.995833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1996
5-th percentile1997.1
Q12001.5
median2007
Q32012.5
95-th percentile2016.9
Maximum2018
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.0033793373
Kurtosis-1.2
Mean2007
Median Absolute Deviation (MAD)6
Skewness0
Sum46161
Variance46
MonotonicityStrictly increasing
2023-12-13T06:25:34.135205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1996 1
 
4.3%
1997 1
 
4.3%
2018 1
 
4.3%
2017 1
 
4.3%
2016 1
 
4.3%
2015 1
 
4.3%
2014 1
 
4.3%
2013 1
 
4.3%
2012 1
 
4.3%
2011 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1996 1
4.3%
1997 1
4.3%
1998 1
4.3%
1999 1
4.3%
2000 1
4.3%
2001 1
4.3%
2002 1
4.3%
2003 1
4.3%
2004 1
4.3%
2005 1
4.3%
ValueCountFrequency (%)
2018 1
4.3%
2017 1
4.3%
2016 1
4.3%
2015 1
4.3%
2014 1
4.3%
2013 1
4.3%
2012 1
4.3%
2011 1
4.3%
2010 1
4.3%
2009 1
4.3%

철재류(톤)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing4
Missing (%)17.4%
Infinite0
Infinite (%)0.0%
Mean1159851.6
Minimum421180
Maximum2383816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T06:25:34.263113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum421180
5-th percentile429701.2
Q1505027.5
median1087633
Q31688805
95-th percentile2323627.6
Maximum2383816
Range1962636
Interquartile range (IQR)1183777.5

Descriptive statistics

Standard deviation709627.48
Coefficient of variation (CV)0.61182609
Kurtosis-1.1860579
Mean1159851.6
Median Absolute Deviation (MAD)591609
Skewness0.5116727
Sum22037181
Variance5.0357116 × 1011
MonotonicityNot monotonic
2023-12-13T06:25:34.400487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
434808 1
 
4.3%
2383816 1
 
4.3%
2316940 1
 
4.3%
2280864 1
 
4.3%
1842085 1
 
4.3%
1627562 1
 
4.3%
981174 1
 
4.3%
1750048 1
 
4.3%
1596500 1
 
4.3%
496024 1
 
4.3%
Other values (9) 9
39.1%
(Missing) 4
17.4%
ValueCountFrequency (%)
421180 1
4.3%
430648 1
4.3%
434808 1
4.3%
448574 1
4.3%
496024 1
4.3%
514031 1
4.3%
514949 1
4.3%
587523 1
4.3%
981174 1
4.3%
1087633 1
4.3%
ValueCountFrequency (%)
2383816 1
4.3%
2316940 1
4.3%
2280864 1
4.3%
1842085 1
4.3%
1750048 1
4.3%
1627562 1
4.3%
1596500 1
4.3%
1169962 1
4.3%
1152860 1
4.3%
1087633 1
4.3%

냉연(톤)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
19 
1070941
 
1
1025377
 
1
1030393
 
1
935282
 
1

Length

Max length7
Median length4
Mean length4.4782609
Min length4

Unique

Unique4 ?
Unique (%)17.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
82.6%
1070941 1
 
4.3%
1025377 1
 
4.3%
1030393 1
 
4.3%
935282 1
 
4.3%

Length

2023-12-13T06:25:34.559210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:34.697109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
82.6%
1070941 1
 
4.3%
1025377 1
 
4.3%
1030393 1
 
4.3%
935282 1
 
4.3%

열연(톤)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
19 
1277939
 
1
1166991
 
1
1371126
 
1
1271882
 
1

Length

Max length7
Median length4
Mean length4.5217391
Min length4

Unique

Unique4 ?
Unique (%)17.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
82.6%
1277939 1
 
4.3%
1166991 1
 
4.3%
1371126 1
 
4.3%
1271882 1
 
4.3%

Length

2023-12-13T06:25:34.842865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:35.002216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
82.6%
1277939 1
 
4.3%
1166991 1
 
4.3%
1371126 1
 
4.3%
1271882 1
 
4.3%

기타철재(톤)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
19 
363944
 
1
103624
 
1
84074
 
1
148462
 
1

Length

Max length6
Median length4
Mean length4.3043478
Min length4

Unique

Unique4 ?
Unique (%)17.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
82.6%
363944 1
 
4.3%
103624 1
 
4.3%
84074 1
 
4.3%
148462 1
 
4.3%

Length

2023-12-13T06:25:35.176861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:35.311675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
82.6%
363944 1
 
4.3%
103624 1
 
4.3%
84074 1
 
4.3%
148462 1
 
4.3%

Interactions

2023-12-13T06:25:33.512003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:33.274858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:33.623248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:33.383629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:25:35.386299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도철재류(톤)냉연(톤)열연(톤)기타철재(톤)
연도1.0000.6441.0001.0001.000
철재류(톤)0.6441.000NaNNaNNaN
냉연(톤)1.000NaN1.0001.0001.000
열연(톤)1.000NaN1.0001.0001.000
기타철재(톤)1.000NaN1.0001.0001.000
2023-12-13T06:25:35.506139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
열연(톤)냉연(톤)기타철재(톤)
열연(톤)1.0001.0001.000
냉연(톤)1.0001.0001.000
기타철재(톤)1.0001.0001.000
2023-12-13T06:25:35.599862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도철재류(톤)냉연(톤)열연(톤)기타철재(톤)
연도1.0000.8931.0001.0001.000
철재류(톤)0.8931.0000.0000.0000.000
냉연(톤)1.0000.0001.0001.0001.000
열연(톤)1.0000.0001.0001.0001.000
기타철재(톤)1.0000.0001.0001.0001.000

Missing values

2023-12-13T06:25:33.788742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:25:33.903587image/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

연도철재류(톤)냉연(톤)열연(톤)기타철재(톤)
01996496024<NA><NA><NA>
11997434808<NA><NA><NA>
21998514949<NA><NA><NA>
31999514031<NA><NA><NA>
42000421180<NA><NA><NA>
52001448574<NA><NA><NA>
62002430648<NA><NA><NA>
72003587523<NA><NA><NA>
820041152860<NA><NA><NA>
920051169962<NA><NA><NA>
연도철재류(톤)냉연(톤)열연(톤)기타철재(톤)
132009981174<NA><NA><NA>
1420101627562<NA><NA><NA>
1520111842085<NA><NA><NA>
1620122280864<NA><NA><NA>
1720132316940<NA><NA><NA>
1820142383816<NA><NA><NA>
192015<NA>10709411277939363944
202016<NA>10253771166991103624
212017<NA>1030393137112684074
222018<NA>9352821271882148462