Overview

Dataset statistics

Number of variables6
Number of observations64
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory52.1 B

Variable types

Categorical4
Numeric2

Dataset

Description국내, 국제공항 시간대별 운항실적 통계 자료에 대한 데이터로 공항별 시간대, 노선, 도착, 출발 운항편 실적 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15002642/fileData.do

Alerts

도착 is highly overall correlated with 출발 and 1 other fieldsHigh correlation
출발 is highly overall correlated with 도착 and 2 other fieldsHigh correlation
공항 is highly overall correlated with 출발 and 2 other fieldsHigh correlation
일자 is highly overall correlated with 공항 and 1 other fieldsHigh correlation
시간대 is highly overall correlated with 공항 and 1 other fieldsHigh correlation
노선 is highly overall correlated with 도착 and 1 other fieldsHigh correlation
도착 has 10 (15.6%) zerosZeros
출발 has 8 (12.5%) zerosZeros

Reproduction

Analysis started2023-12-12 05:12:39.514453
Analysis finished2023-12-12 05:12:40.432509
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공항
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size644.0 B
ICN
16 
GMP
16 
PUS
16 
CJU
16 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
ICN 16
25.0%
GMP 16
25.0%
PUS 16
25.0%
CJU 16
25.0%

Length

2023-12-12T14:12:40.509021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:12:40.643096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
icn 16
25.0%
gmp 16
25.0%
pus 16
25.0%
cju 16
25.0%

일자
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-06-11
 
4
2023-05-30
 
4
2023-07-24
 
2
2023-07-23
 
2
2023-06-25
 
2
Other values (25)
50 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-27
2nd row2023-05-18
3rd row2023-07-24
4th row2023-07-23
5th row2023-06-25

Common Values

ValueCountFrequency (%)
2023-06-11 4
 
6.2%
2023-05-30 4
 
6.2%
2023-07-24 2
 
3.1%
2023-07-23 2
 
3.1%
2023-06-25 2
 
3.1%
2023-07-12 2
 
3.1%
2023-07-30 2
 
3.1%
2023-07-22 2
 
3.1%
2023-05-02 2
 
3.1%
2023-06-03 2
 
3.1%
Other values (20) 40
62.5%

Length

2023-12-12T14:12:40.778541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-06-11 4
 
6.2%
2023-05-30 4
 
6.2%
2023-07-27 2
 
3.1%
2023-05-14 2
 
3.1%
2023-01-08 2
 
3.1%
2023-03-04 2
 
3.1%
2023-01-07 2
 
3.1%
2023-04-03 2
 
3.1%
2023-05-24 2
 
3.1%
2023-03-01 2
 
3.1%
Other values (20) 40
62.5%

시간대
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
16:00
12 
08:00
8 
18:00
8 
15:00
6 
11:00
6 
Other values (5)
24 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row08:00
2nd row08:00
3rd row15:00
4th row11:00
5th row15:00

Common Values

ValueCountFrequency (%)
16:00 12
18.8%
08:00 8
12.5%
18:00 8
12.5%
15:00 6
9.4%
11:00 6
9.4%
20:00 6
9.4%
09:00 6
9.4%
17:00 6
9.4%
13:00 4
 
6.2%
10:00 2
 
3.1%

Length

2023-12-12T14:12:40.967007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:12:41.128337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
16:00 12
18.8%
08:00 8
12.5%
18:00 8
12.5%
15:00 6
9.4%
11:00 6
9.4%
20:00 6
9.4%
09:00 6
9.4%
17:00 6
9.4%
13:00 4
 
6.2%
10:00 2
 
3.1%

노선
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
국내
32 
국제
32 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내 32
50.0%
국제 32
50.0%

Length

2023-12-12T14:12:41.279829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:12:41.374847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내 32
50.0%
국제 32
50.0%

도착
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.390625
Minimum0
Maximum41
Zeros10
Zeros (%)15.6%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T14:12:41.466019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q316.25
95-th percentile37.7
Maximum41
Range41
Interquartile range (IQR)14.25

Descriptive statistics

Standard deviation11.327193
Coefficient of variation (CV)1.0901359
Kurtosis0.89743364
Mean10.390625
Median Absolute Deviation (MAD)5
Skewness1.2888141
Sum665
Variance128.30531
MonotonicityNot monotonic
2023-12-12T14:12:41.581424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 10
15.6%
4 8
12.5%
18 7
10.9%
2 5
7.8%
5 5
7.8%
1 5
7.8%
15 4
 
6.2%
16 3
 
4.7%
6 3
 
4.7%
39 2
 
3.1%
Other values (12) 12
18.8%
ValueCountFrequency (%)
0 10
15.6%
1 5
7.8%
2 5
7.8%
3 1
 
1.6%
4 8
12.5%
5 5
7.8%
6 3
 
4.7%
8 1
 
1.6%
10 1
 
1.6%
11 1
 
1.6%
ValueCountFrequency (%)
41 1
 
1.6%
39 2
 
3.1%
38 1
 
1.6%
36 1
 
1.6%
32 1
 
1.6%
27 1
 
1.6%
26 1
 
1.6%
18 7
10.9%
17 1
 
1.6%
16 3
4.7%

출발
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.015625
Minimum0
Maximum40
Zeros8
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-12T14:12:41.699631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5.5
Q316.75
95-th percentile28.85
Maximum40
Range40
Interquartile range (IQR)15.75

Descriptive statistics

Standard deviation10.673349
Coefficient of variation (CV)1.0656698
Kurtosis0.51113204
Mean10.015625
Median Absolute Deviation (MAD)5.5
Skewness1.1302536
Sum641
Variance113.92039
MonotonicityNot monotonic
2023-12-12T14:12:41.832388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 12
18.8%
0 8
12.5%
19 6
 
9.4%
5 4
 
6.2%
8 3
 
4.7%
3 3
 
4.7%
2 3
 
4.7%
13 3
 
4.7%
11 2
 
3.1%
9 2
 
3.1%
Other values (14) 18
28.1%
ValueCountFrequency (%)
0 8
12.5%
1 12
18.8%
2 3
 
4.7%
3 3
 
4.7%
4 2
 
3.1%
5 4
 
6.2%
6 1
 
1.6%
7 1
 
1.6%
8 3
 
4.7%
9 2
 
3.1%
ValueCountFrequency (%)
40 1
 
1.6%
39 1
 
1.6%
36 1
 
1.6%
29 1
 
1.6%
28 2
 
3.1%
27 1
 
1.6%
26 1
 
1.6%
22 1
 
1.6%
21 1
 
1.6%
19 6
9.4%

Interactions

2023-12-12T14:12:40.018765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:12:39.808748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:12:40.108127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:12:39.897404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:12:41.945862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공항일자시간대노선도착출발
공항1.0000.9830.9120.0000.6850.827
일자0.9831.0000.9990.0000.2290.000
시간대0.9120.9991.0000.0000.5940.717
노선0.0000.0000.0001.0000.6030.735
도착0.6850.2290.5940.6031.0000.916
출발0.8270.0000.7170.7350.9161.000
2023-12-12T14:12:42.080807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시간대공항노선일자
시간대1.0000.7610.0000.744
공항0.7611.0000.0000.692
노선0.0000.0001.0000.000
일자0.7440.6920.0001.000
2023-12-12T14:12:42.224573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도착출발공항일자시간대노선
도착1.0000.9110.4940.0000.3140.571
출발0.9111.0000.6460.0000.3580.508
공항0.4940.6461.0000.6920.7610.000
일자0.0000.0000.6921.0000.7440.000
시간대0.3140.3580.7610.7441.0000.000
노선0.5710.5080.0000.0000.0001.000

Missing values

2023-12-12T14:12:40.240154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:12:40.385322image/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

공항일자시간대노선도착출발
0ICN2023-07-2708:00국내20
1ICN2023-05-1808:00국내11
2ICN2023-07-2415:00국내00
3ICN2023-07-2311:00국내00
4ICN2023-06-2515:00국내00
5ICN2023-07-1216:00국내00
6ICN2023-07-3015:00국내00
7ICN2023-07-2213:00국내00
8ICN2023-07-2708:00국제3236
9ICN2023-05-1808:00국제2639
공항일자시간대노선도착출발
54CJU2023-01-0816:00국내1621
55CJU2023-05-2016:00국내1819
56CJU2023-05-3017:00국제21
57CJU2023-03-0116:00국제11
58CJU2023-05-2417:00국제11
59CJU2023-04-0317:00국제10
60CJU2023-01-0716:00국제01
61CJU2023-03-0416:00국제01
62CJU2023-01-0816:00국제01
63CJU2023-05-2016:00국제01