Overview

Dataset statistics

Number of variables3
Number of observations7918
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory193.4 KiB
Average record size in memory25.0 B

Variable types

Numeric1
Text2

Dataset

Description출입국관리 시스템에서 사용하는 공항코드 및 공항명 데이터를 제공 (각 도시 또는 공항 이름을 기준으로 지정된 세자리 코드, 공항명은 전 세계 공항의 영문 공항명)
URLhttps://www.data.go.kr/data/15118509/fileData.do

Alerts

번호 has unique valuesUnique
공항코드 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:42:45.258545
Analysis finished2023-12-12 01:42:45.785935
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct7918
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3959.5
Minimum1
Maximum7918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.7 KiB
2023-12-12T10:42:45.893169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile396.85
Q11980.25
median3959.5
Q35938.75
95-th percentile7522.15
Maximum7918
Range7917
Interquartile range (IQR)3958.5

Descriptive statistics

Standard deviation2285.874
Coefficient of variation (CV)0.57731381
Kurtosis-1.2
Mean3959.5
Median Absolute Deviation (MAD)1979.5
Skewness0
Sum31351321
Variance5225220.2
MonotonicityStrictly increasing
2023-12-12T10:42:46.068630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5290 1
 
< 0.1%
5288 1
 
< 0.1%
5287 1
 
< 0.1%
5286 1
 
< 0.1%
5285 1
 
< 0.1%
5284 1
 
< 0.1%
5283 1
 
< 0.1%
5282 1
 
< 0.1%
5281 1
 
< 0.1%
Other values (7908) 7908
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
7918 1
< 0.1%
7917 1
< 0.1%
7916 1
< 0.1%
7915 1
< 0.1%
7914 1
< 0.1%
7913 1
< 0.1%
7912 1
< 0.1%
7911 1
< 0.1%
7910 1
< 0.1%
7909 1
< 0.1%

공항코드
Text

UNIQUE 

Distinct7918
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size62.0 KiB
2023-12-12T10:42:46.615656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters23754
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7918 ?
Unique (%)100.0%

Sample

1st rowYSQ
2nd rowYSR
3rd rowYSS
4th rowYST
5th rowYSV
ValueCountFrequency (%)
ysq 1
 
< 0.1%
sgr 1
 
< 0.1%
sgp 1
 
< 0.1%
sgo 1
 
< 0.1%
sgn 1
 
< 0.1%
sgm 1
 
< 0.1%
sgk 1
 
< 0.1%
sgj 1
 
< 0.1%
sgi 1
 
< 0.1%
sgh 1
 
< 0.1%
Other values (7908) 7908
99.9%
2023-12-12T10:42:47.280136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1355
 
5.7%
S 1309
 
5.5%
M 1263
 
5.3%
B 1222
 
5.1%
L 1163
 
4.9%
C 1119
 
4.7%
K 1101
 
4.6%
T 1089
 
4.6%
N 1069
 
4.5%
R 1031
 
4.3%
Other values (17) 12033
50.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 23746
> 99.9%
Space Separator 8
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1355
 
5.7%
S 1309
 
5.5%
M 1263
 
5.3%
B 1222
 
5.1%
L 1163
 
4.9%
C 1119
 
4.7%
K 1101
 
4.6%
T 1089
 
4.6%
N 1069
 
4.5%
R 1031
 
4.3%
Other values (16) 12025
50.6%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23746
> 99.9%
Common 8
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1355
 
5.7%
S 1309
 
5.5%
M 1263
 
5.3%
B 1222
 
5.1%
L 1163
 
4.9%
C 1119
 
4.7%
K 1101
 
4.6%
T 1089
 
4.6%
N 1069
 
4.5%
R 1031
 
4.3%
Other values (16) 12025
50.6%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1355
 
5.7%
S 1309
 
5.5%
M 1263
 
5.3%
B 1222
 
5.1%
L 1163
 
4.9%
C 1119
 
4.7%
K 1101
 
4.6%
T 1089
 
4.6%
N 1069
 
4.5%
R 1031
 
4.3%
Other values (17) 12033
50.7%

공항명
Text

Distinct7705
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size62.0 KiB
2023-12-12T10:42:47.646619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length9.6199798
Min length2

Characters and Unicode

Total characters76171
Distinct characters154
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7520 ?
Unique (%)95.0%

Sample

1st rowSpring Island
2nd rowNANISIVIK.NWT
3rd rowSlate Island
4th rowST.THERESE POINT MANI
5th rowSaglek
ValueCountFrequency (%)
island 152
 
1.4%
san 63
 
0.6%
bay 62
 
0.6%
lake 59
 
0.6%
airport 58
 
0.5%
city 57
 
0.5%
port 44
 
0.4%
fort 42
 
0.4%
de 38
 
0.4%
river 35
 
0.3%
Other values (8061) 9994
94.2%
2023-12-12T10:42:48.337042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5540
 
7.3%
A 5011
 
6.6%
e 3189
 
4.2%
o 3112
 
4.1%
n 2978
 
3.9%
i 2721
 
3.6%
2698
 
3.5%
r 2672
 
3.5%
N 2645
 
3.5%
I 2405
 
3.2%
Other values (144) 43200
56.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 36469
47.9%
Lowercase Letter 35420
46.5%
Space Separator 2698
 
3.5%
Other Punctuation 1167
 
1.5%
Other Letter 165
 
0.2%
Dash Punctuation 135
 
0.2%
Open Punctuation 56
 
0.1%
Close Punctuation 53
 
0.1%
Decimal Number 6
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
항 19
 
11.5%
공 17
 
10.3%
주 6
 
3.6%
스 5
 
3.0%
천 4
 
2.4%
산 4
 
2.4%
국 3
 
1.8%
제 3
 
1.8%
사 3
 
1.8%
이 3
 
1.8%
Other values (76) 98
59.4%
Lowercase Letter
ValueCountFrequency (%)
a 5540
15.6%
e 3189
 
9.0%
o 3112
 
8.8%
n 2978
 
8.4%
i 2721
 
7.7%
r 2672
 
7.5%
l 2078
 
5.9%
t 1758
 
5.0%
s 1653
 
4.7%
u 1646
 
4.6%
Other values (17) 8073
22.8%
Uppercase Letter
ValueCountFrequency (%)
A 5011
13.7%
N 2645
 
7.3%
I 2405
 
6.6%
S 2336
 
6.4%
O 2317
 
6.4%
E 2219
 
6.1%
R 2155
 
5.9%
L 2056
 
5.6%
T 1836
 
5.0%
M 1497
 
4.1%
Other values (16) 11992
32.9%
Other Punctuation
ValueCountFrequency (%)
. 1053
90.2%
/ 63
 
5.4%
' 41
 
3.5%
; 6
 
0.5%
, 2
 
0.2%
& 2
 
0.2%
Decimal Number
ValueCountFrequency (%)
4 3
50.0%
3 2
33.3%
7 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 55
98.2%
[ 1
 
1.8%
Space Separator
ValueCountFrequency (%)
2698
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 71889
94.4%
Common 4117
 
5.4%
Hangul 165
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
항 19
 
11.5%
공 17
 
10.3%
주 6
 
3.6%
스 5
 
3.0%
천 4
 
2.4%
산 4
 
2.4%
국 3
 
1.8%
제 3
 
1.8%
사 3
 
1.8%
이 3
 
1.8%
Other values (76) 98
59.4%
Latin
ValueCountFrequency (%)
a 5540
 
7.7%
A 5011
 
7.0%
e 3189
 
4.4%
o 3112
 
4.3%
n 2978
 
4.1%
i 2721
 
3.8%
r 2672
 
3.7%
N 2645
 
3.7%
I 2405
 
3.3%
S 2336
 
3.2%
Other values (43) 39280
54.6%
Common
ValueCountFrequency (%)
2698
65.5%
. 1053
 
25.6%
- 135
 
3.3%
/ 63
 
1.5%
( 55
 
1.3%
) 53
 
1.3%
' 41
 
1.0%
; 6
 
0.1%
4 3
 
0.1%
= 2
 
< 0.1%
Other values (5) 8
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76005
99.8%
Hangul 165
 
0.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 5540
 
7.3%
A 5011
 
6.6%
e 3189
 
4.2%
o 3112
 
4.1%
n 2978
 
3.9%
i 2721
 
3.6%
2698
 
3.5%
r 2672
 
3.5%
N 2645
 
3.5%
I 2405
 
3.2%
Other values (57) 43034
56.6%
Hangul
ValueCountFrequency (%)
항 19
 
11.5%
공 17
 
10.3%
주 6
 
3.6%
스 5
 
3.0%
천 4
 
2.4%
산 4
 
2.4%
국 3
 
1.8%
제 3
 
1.8%
사 3
 
1.8%
이 3
 
1.8%
Other values (76) 98
59.4%
None
ValueCountFrequency (%)
ı 1
100.0%

Interactions

2023-12-12T10:42:45.515014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T10:42:45.664317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:42:45.746457image/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

번호공항코드공항명
01YSQSpring Island
12YSRNANISIVIK.NWT
23YSSSlate Island
34YSTST.THERESE POINT MANI
45YSVSaglek
56YSWSalluit
67YSXShearwater
78YSYSACHS HARBOUR.NWT
89YSZSquirrel Cove
910YTBHartley Bay
번호공항코드공항명
79087909JGSJINGGANGSHAN
79097910HMIHAMI
79107911GOQGOLMUD
79117912DATDATONG
79127913CIHCHANGZHI
79137914AYNANYANG AIRPORT
79147915AQGANQING
79157916AOGANSHAN
79167917JDZJINGDEZHEN
79177918SBRDD