Overview

Dataset statistics

Number of variables4
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory888.0 B
Average record size in memory42.3 B

Variable types

Numeric4

Dataset

Description1999년부터 2019년까지 년도별 수송인원 형황자료(2019.12.31기준) 입니다.(연도, 수송인원, 승차인원, 유입인원)
URLhttps://www.data.go.kr/data/15051189/fileData.do

Alerts

연도 is highly overall correlated with 수송인원 and 2 other fieldsHigh correlation
수송인원 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
승차인원 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
유입인원 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
연도 has unique valuesUnique
수송인원 has unique valuesUnique
승차인원 has unique valuesUnique
유입인원 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:11:47.106645
Analysis finished2023-12-12 15:11:49.018509
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009
Minimum1999
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:11:49.077568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1999
5-th percentile2000
Q12004
median2009
Q32014
95-th percentile2018
Maximum2019
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.0030885201
Kurtosis-1.2
Mean2009
Median Absolute Deviation (MAD)5
Skewness0
Sum42189
Variance38.5
MonotonicityStrictly increasing
2023-12-13T00:11:49.561644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1999 1
 
4.8%
2000 1
 
4.8%
2019 1
 
4.8%
2018 1
 
4.8%
2017 1
 
4.8%
2016 1
 
4.8%
2015 1
 
4.8%
2014 1
 
4.8%
2013 1
 
4.8%
2012 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1999 1
4.8%
2000 1
4.8%
2001 1
4.8%
2002 1
4.8%
2003 1
4.8%
2004 1
4.8%
2005 1
4.8%
2006 1
4.8%
2007 1
4.8%
2008 1
4.8%
ValueCountFrequency (%)
2019 1
4.8%
2018 1
4.8%
2017 1
4.8%
2016 1
4.8%
2015 1
4.8%
2014 1
4.8%
2013 1
4.8%
2012 1
4.8%
2011 1
4.8%
2010 1
4.8%

수송인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89757759
Minimum11715832
Maximum1.6606709 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:11:49.712310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11715832
5-th percentile56355598
Q171493670
median76018947
Q31.0038763 × 108
95-th percentile1.6143977 × 108
Maximum1.6606709 × 108
Range1.5435126 × 108
Interquartile range (IQR)28893962

Descriptive statistics

Standard deviation36644398
Coefficient of variation (CV)0.40825883
Kurtosis1.01448
Mean89757759
Median Absolute Deviation (MAD)9934290
Skewness0.66066939
Sum1.8849129 × 109
Variance1.3428119 × 1015
MonotonicityNot monotonic
2023-12-13T00:11:49.839186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
11715832 1
 
4.8%
56355598 1
 
4.8%
166067091 1
 
4.8%
161439766 1
 
4.8%
156706992 1
 
4.8%
122044579 1
 
4.8%
100387632 1
 
4.8%
101972628 1
 
4.8%
98659697 1
 
4.8%
90615181 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
11715832 1
4.8%
56355598 1
4.8%
68942572 1
4.8%
69633615 1
4.8%
71236417 1
4.8%
71493670 1
4.8%
72827501 1
4.8%
73299905 1
4.8%
74305827 1
4.8%
75102847 1
4.8%
ValueCountFrequency (%)
166067091 1
4.8%
161439766 1
4.8%
156706992 1
4.8%
122044579 1
4.8%
101972628 1
4.8%
100387632 1
4.8%
98659697 1
4.8%
90615181 1
4.8%
85953237 1
4.8%
80133395 1
4.8%

승차인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64996002
Minimum8820082
Maximum1.1581474 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:11:49.985123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8820082
5-th percentile42477097
Q152629318
median56293216
Q371942784
95-th percentile1.1234431 × 108
Maximum1.1581474 × 108
Range1.0699466 × 108
Interquartile range (IQR)19313466

Descriptive statistics

Standard deviation24791904
Coefficient of variation (CV)0.38143737
Kurtosis1.1731034
Mean64996002
Median Absolute Deviation (MAD)7878920
Skewness0.47994268
Sum1.364916 × 109
Variance6.1463852 × 1014
MonotonicityNot monotonic
2023-12-13T00:11:50.119300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
8820082 1
 
4.8%
42477097 1
 
4.8%
115814738 1
 
4.8%
112344307 1
 
4.8%
109365960 1
 
4.8%
86459379 1
 
4.8%
71942784 1
 
4.8%
73054617 1
 
4.8%
70727958 1
 
4.8%
66603288 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
8820082 1
4.8%
42477097 1
4.8%
50774313 1
4.8%
51285782 1
4.8%
52319590 1
4.8%
52629318 1
4.8%
53838502 1
4.8%
54310398 1
4.8%
54526945 1
4.8%
55697490 1
4.8%
ValueCountFrequency (%)
115814738 1
4.8%
112344307 1
4.8%
109365960 1
4.8%
86459379 1
4.8%
73054617 1
4.8%
71942784 1
4.8%
70727958 1
4.8%
66603288 1
4.8%
64172136 1
4.8%
61458141 1
4.8%

유입인원
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24761757
Minimum2895750
Maximum50252353
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T00:11:50.252324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2895750
5-th percentile13878501
Q118859302
median19778882
Q328444848
95-th percentile49095459
Maximum50252353
Range47356603
Interquartile range (IQR)9585546

Descriptive statistics

Standard deviation11945076
Coefficient of variation (CV)0.4824002
Kurtosis0.80996519
Mean24761757
Median Absolute Deviation (MAD)2122092
Skewness0.97702874
Sum5.1999689 × 108
Variance1.4268485 × 1014
MonotonicityNot monotonic
2023-12-13T00:11:50.364967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2895750 1
 
4.8%
13878501 1
 
4.8%
50252353 1
 
4.8%
49095459 1
 
4.8%
47341032 1
 
4.8%
35585200 1
 
4.8%
28444848 1
 
4.8%
28918011 1
 
4.8%
27931739 1
 
4.8%
24011893 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
2895750 1
4.8%
13878501 1
4.8%
17656790 1
4.8%
18675254 1
4.8%
18809631 1
4.8%
18859302 1
4.8%
18864352 1
4.8%
18916827 1
4.8%
18988999 1
4.8%
18989507 1
4.8%
ValueCountFrequency (%)
50252353 1
4.8%
49095459 1
4.8%
47341032 1
4.8%
35585200 1
4.8%
28918011 1
4.8%
28444848 1
4.8%
27931739 1
4.8%
24011893 1
4.8%
21781101 1
4.8%
20321457 1
4.8%

Interactions

2023-12-13T00:11:48.461909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.196307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.700755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.086299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.549835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.303136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.817378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.179018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.632957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.413993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.907321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.283072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.720188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.532483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:47.998634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:11:48.372861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:11:50.444625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도수송인원승차인원유입인원
연도1.0000.8660.8200.783
수송인원0.8661.0000.9620.991
승차인원0.8200.9621.0000.961
유입인원0.7830.9910.9611.000
2023-12-13T00:11:50.550792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도수송인원승차인원유입인원
연도1.0000.9420.9450.865
수송인원0.9421.0000.9970.925
승차인원0.9450.9971.0000.912
유입인원0.8650.9250.9121.000

Missing values

2023-12-13T00:11:48.907927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:11:48.987673image/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

연도수송인원승차인원유입인원
019991171583288200822895750
12000563555984247709713878501
22001689425725128578217656790
32002760189475569749020321457
42003743058275452694519778882
52004712364175231959018916827
62005696336155077431318859302
72006714936705262931818864352
82007728275015383850218988999
92008732999055431039818989507
연도수송인원승차인원유입인원
112010801333956145814118675254
122011859532376417213621781101
132012906151816660328824011893
142013986596977072795827931739
1520141019726287305461728918011
1620151003876327194278428444848
1720161220445798645937935585200
18201715670699210936596047341032
19201816143976611234430749095459
20201916606709111581473850252353