Overview

Dataset statistics

Number of variables3
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory30.6 B

Variable types

Numeric3

Dataset

Description경찰청에서 제공하는 연도별 남성, 여성 운전면허 소지자 현황자료입니다.
Author경찰청
URLhttps://www.data.go.kr/data/15048417/fileData.do

Alerts

연도 is highly overall correlated with 남 and 1 other fieldsHigh correlation
남 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
여 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
연도 has unique valuesUnique
남 has unique valuesUnique
여 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:52:25.606733
Analysis finished2023-12-12 17:52:27.139815
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2003
Minimum1985
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T02:52:27.233029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1986.8
Q11994
median2003
Q32012
95-th percentile2019.2
Maximum2021
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.0054040715
Kurtosis-1.2
Mean2003
Median Absolute Deviation (MAD)9
Skewness0
Sum74111
Variance117.16667
MonotonicityStrictly increasing
2023-12-13T02:52:27.412760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1985 1
 
2.7%
2013 1
 
2.7%
2006 1
 
2.7%
2007 1
 
2.7%
2008 1
 
2.7%
2009 1
 
2.7%
2010 1
 
2.7%
2011 1
 
2.7%
2012 1
 
2.7%
2014 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1985 1
2.7%
1986 1
2.7%
1987 1
2.7%
1988 1
2.7%
1989 1
2.7%
1990 1
2.7%
1991 1
2.7%
1992 1
2.7%
1993 1
2.7%
1994 1
2.7%
ValueCountFrequency (%)
2021 1
2.7%
2020 1
2.7%
2019 1
2.7%
2018 1
2.7%
2017 1
2.7%
2016 1
2.7%
2015 1
2.7%
2014 1
2.7%
2013 1
2.7%
2012 1
2.7%

남
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13512257
Minimum3837129
Maximum19334997
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T02:52:27.606499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3837129
5-th percentile4766432.4
Q111904012
median14362104
Q316933257
95-th percentile18978020
Maximum19334997
Range15497868
Interquartile range (IQR)5029245

Descriptive statistics

Standard deviation4468941.8
Coefficient of variation (CV)0.33073243
Kurtosis-0.29718963
Mean13512257
Median Absolute Deviation (MAD)2571153
Skewness-0.77853035
Sum4.9995353 × 108
Variance1.9971441 × 1013
MonotonicityNot monotonic
2023-12-13T02:52:27.803644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
3837129 1
 
2.7%
17227765 1
 
2.7%
14992244 1
 
2.7%
15248126 1
 
2.7%
15554394 1
 
2.7%
15817223 1
 
2.7%
16074165 1
 
2.7%
16474240 1
 
2.7%
16933257 1
 
2.7%
17557803 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
3837129 1
2.7%
4337394 1
2.7%
4873692 1
2.7%
5627843 1
2.7%
6416386 1
2.7%
7503101 1
2.7%
8454630 1
2.7%
9733430 1
2.7%
10910128 1
2.7%
11904012 1
2.7%
ValueCountFrequency (%)
19334997 1
2.7%
19142665 1
2.7%
18936859 1
2.7%
18731410 1
2.7%
18495975 1
2.7%
18291984 1
2.7%
17920583 1
2.7%
17557803 1
2.7%
17227765 1
2.7%
16933257 1
2.7%

여
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7254210.9
Minimum251392
Maximum14394809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-13T02:52:27.973534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum251392
5-th percentile379536.2
Q12985750
median7950569
Q311330060
95-th percentile13779760
Maximum14394809
Range14143417
Interquartile range (IQR)8344310

Descriptive statistics

Standard deviation4682775.2
Coefficient of variation (CV)0.6455251
Kurtosis-1.3699722
Mean7254210.9
Median Absolute Deviation (MAD)4035873
Skewness-0.10880932
Sum2.684058 × 108
Variance2.1928384 × 1013
MonotonicityStrictly increasing
2023-12-13T02:52:28.155787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
251392 1
 
2.7%
11620275 1
 
2.7%
9095985 1
 
2.7%
9433314 1
 
2.7%
9713985 1
 
2.7%
10004926 1
 
2.7%
10328199 1
 
2.7%
10776913 1
 
2.7%
11330060 1
 
2.7%
11986442 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
251392 1
2.7%
314473 1
2.7%
395802 1
2.7%
563978 1
2.7%
774081 1
2.7%
1040802 1
2.7%
1389726 1
2.7%
1879870 1
2.7%
2391482 1
2.7%
2985750 1
2.7%
ValueCountFrequency (%)
14394809 1
2.7%
14047900 1
2.7%
13712725 1
2.7%
13429671 1
2.7%
13169418 1
2.7%
12898375 1
2.7%
12373038 1
2.7%
11986442 1
2.7%
11620275 1
2.7%
11330060 1
2.7%

Interactions

2023-12-13T02:52:26.545325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:25.694538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:26.076847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:26.662754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:25.805828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:26.244040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:26.806030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:25.930318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:52:26.388236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:52:28.248329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도남여
연도1.0000.9470.959
남0.9471.0000.917
여0.9590.9171.000
2023-12-13T02:52:28.348514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도남여
연도1.0000.9871.000
남0.9871.0000.987
여1.0000.9871.000

Missing values

2023-12-13T02:52:26.984770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:52:27.093986image/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

연도남여
019853837129251392
119864337394314473
219874873692395802
319885627843563978
419896416386774081
5199075031011040802
6199184546301389726
7199297334301879870
81993109101282391482
91994119040122985750
연도남여
2720121693325711330060
2820131722776511620275
2920141755780311986442
3020151792058312373038
3120161829198412898375
3220171849597513169418
3320181873141013429671
3420191893685913712725
3520201914266514047900
3620211933499714394809