Overview

Dataset statistics

Number of variables6
Number of observations480
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.0 KiB
Average record size in memory51.3 B

Variable types

Categorical3
DateTime1
Numeric2

Dataset

Description한국공항공사가 운영하는 주요 국제공항(김포, 김해, 제주, 청주, 양양, 무안 등) 시간대별 여객실적 정보에 대한 데이터 제공
URLhttps://www.data.go.kr/data/15002619/fileData.do

Alerts

연도 has constant value ""Constant
출발여객수 is highly overall correlated with 도착여객수High correlation
도착여객수 is highly overall correlated with 출발여객수High correlation
공항 is highly overall correlated with 노선High correlation
노선 is highly overall correlated with 공항High correlation
출발여객수 has 179 (37.3%) zerosZeros
도착여객수 has 171 (35.6%) zerosZeros

Reproduction

Analysis started2023-12-12 02:56:49.448079
Analysis finished2023-12-12 02:56:50.552263
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023
480 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 480
100.0%

Length

2023-12-12T11:56:50.666847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:50.792435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 480
100.0%

공항
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
김포
48 
김해
48 
제주
48 
대구
48 
청주
48 
Other values (9)
240 

Length

Max length4
Median length2
Mean length2.1
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row김포
2nd row김포
3rd row김포
4th row김포
5th row김포

Common Values

ValueCountFrequency (%)
김포 48
10.0%
김해 48
10.0%
제주 48
10.0%
대구 48
10.0%
청주 48
10.0%
양양 48
10.0%
광주 24
 
5.0%
여수 24
 
5.0%
울산 24
 
5.0%
원주 24
 
5.0%
Other values (4) 96
20.0%

Length

2023-12-12T11:56:50.943886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김포 48
10.0%
김해 48
10.0%
제주 48
10.0%
대구 48
10.0%
청주 48
10.0%
양양 48
10.0%
광주 24
 
5.0%
여수 24
 
5.0%
울산 24
 
5.0%
원주 24
 
5.0%
Other values (4) 96
20.0%

노선
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
국내선
312 
국제선
168 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국내선
2nd row국내선
3rd row국내선
4th row국내선
5th row국내선

Common Values

ValueCountFrequency (%)
국내선 312
65.0%
국제선 168
35.0%

Length

2023-12-12T11:56:51.135534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:56:51.283201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내선 312
65.0%
국제선 168
35.0%

시간
Date

Distinct24
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 23:00:00
2023-12-12T11:56:51.424650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:51.588543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

출발여객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct297
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45703.062
Minimum0
Maximum683173
Zeros179
Zeros (%)37.3%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-12T11:56:51.779029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1022.5
Q324947.75
95-th percentile347462.8
Maximum683173
Range683173
Interquartile range (IQR)24947.75

Descriptive statistics

Standard deviation116817.33
Coefficient of variation (CV)2.5560067
Kurtosis11.826309
Mean45703.062
Median Absolute Deviation (MAD)1022.5
Skewness3.4696507
Sum21937470
Variance1.3646289 × 1010
MonotonicityNot monotonic
2023-12-12T11:56:51.997894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 179
37.3%
157 2
 
0.4%
90 2
 
0.4%
5585 2
 
0.4%
365 2
 
0.4%
190 2
 
0.4%
10610 1
 
0.2%
33948 1
 
0.2%
1989 1
 
0.2%
17057 1
 
0.2%
Other values (287) 287
59.8%
ValueCountFrequency (%)
0 179
37.3%
9 1
 
0.2%
45 1
 
0.2%
46 1
 
0.2%
64 1
 
0.2%
71 1
 
0.2%
90 2
 
0.4%
91 1
 
0.2%
103 1
 
0.2%
104 1
 
0.2%
ValueCountFrequency (%)
683173 1
0.2%
651611 1
0.2%
621559 1
0.2%
595019 1
0.2%
563967 1
0.2%
550476 1
0.2%
545579 1
0.2%
543047 1
0.2%
526225 1
0.2%
522378 1
0.2%

도착여객수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct308
Distinct (%)64.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46201.619
Minimum0
Maximum628341
Zeros171
Zeros (%)35.6%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-12T11:56:52.213387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1092
Q323492.5
95-th percentile369078.65
Maximum628341
Range628341
Interquartile range (IQR)23492.5

Descriptive statistics

Standard deviation118043.62
Coefficient of variation (CV)2.5549673
Kurtosis10.911277
Mean46201.619
Median Absolute Deviation (MAD)1092
Skewness3.3771931
Sum22176777
Variance1.3934297 × 1010
MonotonicityNot monotonic
2023-12-12T11:56:52.441569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 171
35.6%
185 2
 
0.4%
191 2
 
0.4%
12441 1
 
0.2%
2060 1
 
0.2%
23895 1
 
0.2%
3778 1
 
0.2%
21518 1
 
0.2%
8553 1
 
0.2%
15889 1
 
0.2%
Other values (298) 298
62.1%
ValueCountFrequency (%)
0 171
35.6%
46 1
 
0.2%
47 1
 
0.2%
65 1
 
0.2%
79 1
 
0.2%
101 1
 
0.2%
144 1
 
0.2%
157 1
 
0.2%
158 1
 
0.2%
164 1
 
0.2%
ValueCountFrequency (%)
628341 1
0.2%
607258 1
0.2%
594706 1
0.2%
588224 1
0.2%
581318 1
0.2%
572380 1
0.2%
556223 1
0.2%
545248 1
0.2%
536049 1
0.2%
532665 1
0.2%

Interactions

2023-12-12T11:56:50.022368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:49.687549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:50.170013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:56:49.851998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:56:52.608336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공항노선시간출발여객수도착여객수
공항1.0000.7110.0000.5310.546
노선0.7111.0000.0000.1590.152
시간0.0000.0001.0000.0000.000
출발여객수0.5310.1590.0001.0000.890
도착여객수0.5460.1520.0000.8901.000
2023-12-12T11:56:52.756646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공항노선
공항1.0000.561
노선0.5611.000
2023-12-12T11:56:52.876915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출발여객수도착여객수공항노선
출발여객수1.0000.7780.2450.121
도착여객수0.7781.0000.2540.115
공항0.2450.2541.0000.561
노선0.1210.1150.5611.000

Missing values

2023-12-12T11:56:50.338020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:56:50.472455image/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

연도공항노선시간출발여객수도착여객수
02023김포국내선00:0001665
12023김포국내선01:0000
22023김포국내선02:0000
32023김포국내선03:0000
42023김포국내선04:0000
52023김포국내선05:0000
62023김포국내선06:00342648332
72023김포국내선07:0051168079975
82023김포국내선08:00426693216287
92023김포국내선09:00351373322572
연도공항노선시간출발여객수도착여객수
4702023무안국제선14:00468745
4712023무안국제선15:00912997
4722023무안국제선16:001225516
4732023무안국제선17:002123176
4742023무안국제선18:001136530
4752023무안국제선19:0014644714
4762023무안국제선20:0085542976
4772023무안국제선21:001162744
4782023무안국제선22:0026050
4792023무안국제선23:00268174