Overview

Dataset statistics

Number of variables4
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory972.0 B
Average record size in memory40.5 B

Variable types

Numeric3
DateTime1

Dataset

Description소비자물가변동율에 따른 연금인상률에 대한 데이터입니다. 2000년부터 연도별로 데이터가 존재하며 소비자물가변동율이 적용된 연금인상률을 확인하실 수 있습니다. (물가변동고시일자는 매년 12.31.입니다.)
URLhttps://www.data.go.kr/data/15083845/fileData.do

Alerts

연금적용연도 is highly overall correlated with 소비자물가변동율 and 1 other fieldsHigh correlation
소비자물가변동율 is highly overall correlated with 연금적용연도 and 1 other fieldsHigh correlation
물가변동연도 is highly overall correlated with 연금적용연도 and 1 other fieldsHigh correlation
연금적용연도 has unique valuesUnique
물가변동연도 has unique valuesUnique
물가변동고시일자 has unique valuesUnique
소비자물가변동율 has 5 (20.8%) zerosZeros

Reproduction

Analysis started2023-12-12 23:15:02.710819
Analysis finished2023-12-12 23:15:04.057563
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연금적용연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.5
Minimum2000
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:15:04.128098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001.15
Q12005.75
median2011.5
Q32017.25
95-th percentile2021.85
Maximum2023
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.0035153208
Kurtosis-1.2
Mean2011.5
Median Absolute Deviation (MAD)6
Skewness0
Sum48276
Variance50
MonotonicityStrictly increasing
2023-12-13T08:15:04.245656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2000 1
 
4.2%
2013 1
 
4.2%
2023 1
 
4.2%
2022 1
 
4.2%
2021 1
 
4.2%
2020 1
 
4.2%
2019 1
 
4.2%
2018 1
 
4.2%
2017 1
 
4.2%
2016 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
2000 1
4.2%
2001 1
4.2%
2002 1
4.2%
2003 1
4.2%
2004 1
4.2%
2005 1
4.2%
2006 1
4.2%
2007 1
4.2%
2008 1
4.2%
2009 1
4.2%
ValueCountFrequency (%)
2023 1
4.2%
2022 1
4.2%
2021 1
4.2%
2020 1
4.2%
2019 1
4.2%
2018 1
4.2%
2017 1
4.2%
2016 1
4.2%
2015 1
4.2%
2014 1
4.2%

소비자물가변동율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.022916667
Minimum0
Maximum0.06
Zeros5
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:15:04.335516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.011
median0.024
Q30.0345
95-th percentile0.0495
Maximum0.06
Range0.06
Interquartile range (IQR)0.0235

Descriptive statistics

Standard deviation0.016797817
Coefficient of variation (CV)0.73299566
Kurtosis-0.39772691
Mean0.022916667
Median Absolute Deviation (MAD)0.0115
Skewness0.22438078
Sum0.55
Variance0.00028216667
MonotonicityNot monotonic
2023-12-13T08:15:04.443921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 5
20.8%
0.036 2
 
8.3%
0.022 2
 
8.3%
0.025 2
 
8.3%
0.013 2
 
8.3%
0.06 1
 
4.2%
0.029 1
 
4.2%
0.051 1
 
4.2%
0.005 1
 
4.2%
0.04 1
 
4.2%
Other values (6) 6
25.0%
ValueCountFrequency (%)
0.0 5
20.8%
0.005 1
 
4.2%
0.013 2
 
8.3%
0.02 1
 
4.2%
0.022 2
 
8.3%
0.023 1
 
4.2%
0.025 2
 
8.3%
0.027 1
 
4.2%
0.028 1
 
4.2%
0.029 1
 
4.2%
ValueCountFrequency (%)
0.06 1
4.2%
0.051 1
4.2%
0.041 1
4.2%
0.04 1
4.2%
0.036 2
8.3%
0.034 1
4.2%
0.029 1
4.2%
0.028 1
4.2%
0.027 1
4.2%
0.025 2
8.3%

물가변동연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.5
Minimum1999
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:15:04.565329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2000.15
Q12004.75
median2010.5
Q32016.25
95-th percentile2020.85
Maximum2022
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.0035170693
Kurtosis-1.2
Mean2010.5
Median Absolute Deviation (MAD)6
Skewness0
Sum48252
Variance50
MonotonicityStrictly increasing
2023-12-13T08:15:04.702005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1999 1
 
4.2%
2012 1
 
4.2%
2022 1
 
4.2%
2021 1
 
4.2%
2020 1
 
4.2%
2019 1
 
4.2%
2018 1
 
4.2%
2017 1
 
4.2%
2016 1
 
4.2%
2015 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1999 1
4.2%
2000 1
4.2%
2001 1
4.2%
2002 1
4.2%
2003 1
4.2%
2004 1
4.2%
2005 1
4.2%
2006 1
4.2%
2007 1
4.2%
2008 1
4.2%
ValueCountFrequency (%)
2022 1
4.2%
2021 1
4.2%
2020 1
4.2%
2019 1
4.2%
2018 1
4.2%
2017 1
4.2%
2016 1
4.2%
2015 1
4.2%
2014 1
4.2%
2013 1
4.2%

물가변동고시일자
Date

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
Minimum1999-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T08:15:04.819494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:04.975868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

Interactions

2023-12-13T08:15:03.633305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:02.824235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:03.049596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:03.701328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:02.901098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:03.429488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:03.828345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:02.981423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:15:03.526922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:15:05.056373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연금적용연도소비자물가변동율물가변동연도물가변동고시일자
연금적용연도1.0000.6701.0001.000
소비자물가변동율0.6701.0000.6701.000
물가변동연도1.0000.6701.0001.000
물가변동고시일자1.0001.0001.0001.000
2023-12-13T08:15:05.154405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연금적용연도소비자물가변동율물가변동연도
연금적용연도1.000-0.5571.000
소비자물가변동율-0.5571.000-0.557
물가변동연도1.000-0.5571.000

Missing values

2023-12-13T08:15:03.925770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:15:04.009140image/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

연금적용연도소비자물가변동율물가변동연도물가변동고시일자
020000.0619991999-12-31
120010.02320002000-12-31
220020.04120012001-12-31
320030.03420022002-12-31
420040.03620032003-12-31
520050.03620042004-12-31
620060.02720052005-12-31
720070.02220062006-12-31
820080.02520072007-12-31
920090.0220082008-12-31
연금적용연도소비자물가변동율물가변동연도물가변동고시일자
1420140.01320132013-12-31
1520150.01320142014-12-31
1620160.020152015-12-31
1720170.020162016-12-31
1820180.020172017-12-31
1920190.020182018-12-31
2020200.020192019-12-31
2120210.00520202020-12-31
2220220.02520212021-12-31
2320230.05120222022-12-31