Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells856
Missing cells (%)2.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory410.2 KiB
Average record size in memory42.0 B

Variable types

Numeric2
Categorical2

Dataset

Description- 국내 공항별로 월별, 도착출발별 이용자 수 통계를 제공합니다. - 데이터 제공처: KOSIS 국가통계포털
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/787

Alerts

이용자수(명) has 856 (8.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 19:45:27.314423
Analysis finished2023-12-11 19:45:28.531135
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일(월)
Real number (ℝ)

Distinct222
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201378.63
Minimum200501
Maximum202306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:45:28.632795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200501
5-th percentile200512
Q1200908
median201403
Q3201810.25
95-th percentile202207
Maximum202306
Range1805
Interquartile range (IQR)902.25

Descriptive statistics

Standard deviation532.75712
Coefficient of variation (CV)0.0026455494
Kurtosis-1.1957148
Mean201378.63
Median Absolute Deviation (MAD)493
Skewness0.0066841955
Sum2.0137863 × 109
Variance283830.15
MonotonicityNot monotonic
2023-12-12T04:45:28.875453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201610 51
 
0.5%
201106 51
 
0.5%
201202 50
 
0.5%
201901 50
 
0.5%
201210 50
 
0.5%
201306 49
 
0.5%
201607 49
 
0.5%
202102 49
 
0.5%
201301 49
 
0.5%
200909 49
 
0.5%
Other values (212) 9503
95.0%
ValueCountFrequency (%)
200501 47
0.5%
200502 47
0.5%
200503 44
0.4%
200504 43
0.4%
200505 45
0.4%
200506 47
0.5%
200507 46
0.5%
200508 44
0.4%
200509 45
0.4%
200510 42
0.4%
ValueCountFrequency (%)
202306 43
0.4%
202305 39
0.4%
202304 43
0.4%
202303 44
0.4%
202302 43
0.4%
202301 41
0.4%
202212 39
0.4%
202211 43
0.4%
202210 45
0.4%
202209 41
0.4%

공항
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
울산
 
603
여수
 
595
무안
 
593
합계
 
593
광주
 
592
Other values (13)
7024 

Length

Max length4
Median length2
Mean length2.0132
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광주
2nd row합계
3rd row포항
4th row사천
5th row울산

Common Values

ValueCountFrequency (%)
울산 603
 
6.0%
여수 595
 
5.9%
무안 593
 
5.9%
합계 593
 
5.9%
광주 592
 
5.9%
김포 591
 
5.9%
인천 590
 
5.9%
사천 589
 
5.9%
청주 589
 
5.9%
군산 588
 
5.9%
Other values (8) 4077
40.8%

Length

2023-12-12T04:45:29.111993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
울산 603
 
6.0%
여수 595
 
5.9%
무안 593
 
5.9%
합계 593
 
5.9%
광주 592
 
5.9%
김포 591
 
5.9%
인천 590
 
5.9%
사천 589
 
5.9%
청주 589
 
5.9%
원주 588
 
5.9%
Other values (8) 4077
40.8%

도착출발구분
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
계
3340 
출발
3337 
도착
3323 

Length

Max length2
Median length2
Mean length1.666
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계
2nd row출발
3rd row도착
4th row계
5th row도착

Common Values

ValueCountFrequency (%)
계 3340
33.4%
출발 3337
33.4%
도착 3323
33.2%

Length

2023-12-12T04:45:29.299823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T04:45:29.429514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계 3340
33.4%
출발 3337
33.4%
도착 3323
33.2%

이용자수(명)
Real number (ℝ)

MISSING 

Distinct8808
Distinct (%)96.3%
Missing856
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean703126.83
Minimum0
Maximum13569860
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T04:45:29.586790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2483.45
Q110932.75
median53178
Q3633690.75
95-th percentile3735745.2
Maximum13569860
Range13569860
Interquartile range (IQR)622758

Descriptive statistics

Standard deviation1598063.3
Coefficient of variation (CV)2.2727952
Kurtosis18.712037
Mean703126.83
Median Absolute Deviation (MAD)49085
Skewness3.8840457
Sum6.4293918 × 109
Variance2.5538063 × 1012
MonotonicityNot monotonic
2023-12-12T04:45:29.778962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
932 4
 
< 0.1%
3683 3
 
< 0.1%
1222 3
 
< 0.1%
3483 3
 
< 0.1%
4699 3
 
< 0.1%
3293 3
 
< 0.1%
3873 3
 
< 0.1%
3178 3
 
< 0.1%
2263 3
 
< 0.1%
12762 3
 
< 0.1%
Other values (8798) 9113
91.1%
(Missing) 856
 
8.6%
ValueCountFrequency (%)
0 1
< 0.1%
32 1
< 0.1%
39 1
< 0.1%
46 1
< 0.1%
51 1
< 0.1%
54 1
< 0.1%
63 1
< 0.1%
66 1
< 0.1%
78 1
< 0.1%
86 1
< 0.1%
ValueCountFrequency (%)
13569860 1
< 0.1%
13484287 1
< 0.1%
13450302 1
< 0.1%
13298391 1
< 0.1%
13219221 1
< 0.1%
13209511 1
< 0.1%
13034574 1
< 0.1%
13018518 1
< 0.1%
12880754 1
< 0.1%
12802171 1
< 0.1%

Interactions

2023-12-12T04:45:27.993984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:45:27.660548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:45:28.150305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T04:45:27.827617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T04:45:29.925454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일(월)공항도착출발구분이용자수(명)
기준일(월)1.0000.1660.0000.296
공항0.1661.0000.0000.678
도착출발구분0.0000.0001.0000.241
이용자수(명)0.2960.6780.2411.000
2023-12-12T04:45:30.059222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공항도착출발구분
공항1.0000.000
도착출발구분0.0001.000
2023-12-12T04:45:30.213116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일(월)이용자수(명)공항도착출발구분
기준일(월)1.0000.0820.0640.000
이용자수(명)0.0821.0000.3370.148
공항0.0640.3371.0000.000
도착출발구분0.0000.1480.0001.000

Missing values

2023-12-12T04:45:28.343655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T04:45:28.468418image/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

기준일(월)공항도착출발구분이용자수(명)
9459202006광주계160655
665200602합계출발2530604
2227200808포항도착9277
1260200701사천계16446
1252200701울산도착50656
1911200802광주계113735
4471201204포항도착10729
9390202005김해계432974
8707201903사천도착8413
5261201308김해출발436124
기준일(월)공항도착출발구분이용자수(명)
7274201611여수출발25381
5779201406대구도착57830
5180201306울산출발19363
132200503여수계48962
3720201101목포계<NA>
6491201508청주출발94579
10421202201광주도착99825
2990200911여수출발27031
3886201105제주도착822701
11005202301군산계24765