Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

Numeric1
Categorical3
DateTime1
Text1

Dataset

Description축산관계자 출국신고의 출입국일, 신고방법, 이용항만 등 제공
Author농림축산검역본부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20211015000000001647

Alerts

출발항 is highly imbalanced (63.0%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-16 06:34:01.363172
Analysis finished2023-12-16 06:34:03.388717
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50122.205
Minimum6
Maximum99992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-16T06:34:03.788131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile5070.95
Q125435.25
median50214
Q374926.75
95-th percentile95315.05
Maximum99992
Range99986
Interquartile range (IQR)49491.5

Descriptive statistics

Standard deviation28713.926
Coefficient of variation (CV)0.57287836
Kurtosis-1.1846702
Mean50122.205
Median Absolute Deviation (MAD)24734.5
Skewness-0.0024823106
Sum5.0122205 × 108
Variance8.2448956 × 108
MonotonicityNot monotonic
2023-12-16T06:34:04.685719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9945 1
 
< 0.1%
75571 1
 
< 0.1%
78690 1
 
< 0.1%
50871 1
 
< 0.1%
37599 1
 
< 0.1%
46166 1
 
< 0.1%
10898 1
 
< 0.1%
572 1
 
< 0.1%
44319 1
 
< 0.1%
72849 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
6 1
< 0.1%
14 1
< 0.1%
17 1
< 0.1%
20 1
< 0.1%
22 1
< 0.1%
41 1
< 0.1%
44 1
< 0.1%
90 1
< 0.1%
95 1
< 0.1%
99 1
< 0.1%
ValueCountFrequency (%)
99992 1
< 0.1%
99981 1
< 0.1%
99980 1
< 0.1%
99962 1
< 0.1%
99955 1
< 0.1%
99944 1
< 0.1%
99942 1
< 0.1%
99925 1
< 0.1%
99913 1
< 0.1%
99911 1
< 0.1%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
6348 
여
3652 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row남
3rd row남
4th row남
5th row여

Common Values

ValueCountFrequency (%)
남 6348
63.5%
여 3652
36.5%

Length

2023-12-16T06:34:05.246699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T06:34:05.679825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 6348
63.5%
여 3652
36.5%

출국일시
Date

Distinct354
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-12-01 00:00:00
Maximum2023-11-19 00:00:00
2023-12-16T06:34:06.385788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-16T06:34:07.810724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

귀국예정일
Text

Distinct405
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-16T06:34:09.350737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.7963
Min length3

Characters and Unicode

Total characters97963
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)0.3%

Sample

1st row2023-02-07
2nd row2023-01-28
3rd row2023-01-13
4th row2023-10-18
5th row2023-08-26
ValueCountFrequency (%)
미기재 283
 
2.8%
2023-11-10 57
 
0.6%
2023-02-25 57
 
0.6%
2023-06-23 57
 
0.6%
2023-10-01 51
 
0.5%
2023-02-24 51
 
0.5%
2023-02-09 50
 
0.5%
2023-07-07 50
 
0.5%
2023-10-02 49
 
0.5%
2023-04-14 49
 
0.5%
Other values (395) 9246
92.5%
2023-12-16T06:34:11.596006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 25729
26.3%
0 21798
22.3%
- 19378
19.8%
3 11455
11.7%
1 8214
 
8.4%
8 1850
 
1.9%
7 1844
 
1.9%
6 1729
 
1.8%
9 1726
 
1.8%
4 1717
 
1.8%
Other values (4) 2523
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77736
79.4%
Dash Punctuation 19378
 
19.8%
Other Letter 849
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 25729
33.1%
0 21798
28.0%
3 11455
14.7%
1 8214
 
10.6%
8 1850
 
2.4%
7 1844
 
2.4%
6 1729
 
2.2%
9 1726
 
2.2%
4 1717
 
2.2%
5 1674
 
2.2%
Other Letter
ValueCountFrequency (%)
미 283
33.3%
기 283
33.3%
재 283
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 19378
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97114
99.1%
Hangul 849
 
0.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 25729
26.5%
0 21798
22.4%
- 19378
20.0%
3 11455
11.8%
1 8214
 
8.5%
8 1850
 
1.9%
7 1844
 
1.9%
6 1729
 
1.8%
9 1726
 
1.8%
4 1717
 
1.8%
Hangul
ValueCountFrequency (%)
미 283
33.3%
기 283
33.3%
재 283
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97114
99.1%
Hangul 849
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 25729
26.5%
0 21798
22.4%
- 19378
20.0%
3 11455
11.8%
1 8214
 
8.5%
8 1850
 
1.9%
7 1844
 
1.9%
6 1729
 
1.8%
9 1726
 
1.8%
4 1717
 
1.8%
Hangul
ValueCountFrequency (%)
미 283
33.3%
기 283
33.3%
재 283
33.3%

출발항
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인천공항
7256 
김해공항
1552 
대구공항
 
379
무안국제공항
 
340
청주국제공항
 
167
Other values (9)
 
306

Length

Max length6
Median length4
Mean length4.0936
Min length3

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row김해공항
2nd row인천공항
3rd row인천공항
4th row인천공항
5th row인천공항

Common Values

ValueCountFrequency (%)
인천공항 7256
72.6%
김해공항 1552
 
15.5%
대구공항 379
 
3.8%
무안국제공항 340
 
3.4%
청주국제공항 167
 
1.7%
김포공항 125
 
1.2%
부산항 107
 
1.1%
제주공항 46
 
0.5%
양양국제공항 19
 
0.2%
군산항 5
 
0.1%
Other values (4) 4
 
< 0.1%

Length

2023-12-16T06:34:12.662990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천공항 7256
72.6%
김해공항 1552
 
15.5%
대구공항 379
 
3.8%
무안국제공항 340
 
3.4%
청주국제공항 167
 
1.7%
김포공항 125
 
1.2%
부산항 107
 
1.1%
제주공항 46
 
0.5%
양양국제공항 19
 
0.2%
군산항 5
 
< 0.1%
Other values (4) 4
 
< 0.1%

구분
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전화
3865 
신고함
2994 
모바일
1556 
방문
769 
개인
438 
Other values (2)
 
378

Length

Max length5
Median length2
Mean length2.4966
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신고함
2nd row모바일
3rd row모바일
4th row모바일
5th row전화

Common Values

ValueCountFrequency (%)
전화 3865
38.6%
신고함 2994
29.9%
모바일 1556
15.6%
방문 769
 
7.7%
개인 438
 
4.4%
대행사 359
 
3.6%
여행자협회 19
 
0.2%

Length

2023-12-16T06:34:13.778988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-16T06:34:14.780878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전화 3865
38.6%
신고함 2994
29.9%
모바일 1556
15.6%
방문 769
 
7.7%
개인 438
 
4.4%
대행사 359
 
3.6%
여행자협회 19
 
0.2%

Interactions

2023-12-16T06:34:02.159985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-16T06:34:15.174589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번성별출발항구분
순번1.0000.0610.1450.161
성별0.0611.0000.0000.053
출발항0.1450.0001.0000.700
구분0.1610.0530.7001.000
2023-12-16T06:34:15.559455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별출발항구분
성별1.0000.0000.057
출발항0.0001.0000.336
구분0.0570.3361.000
2023-12-16T06:34:16.123049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번성별출발항구분
순번1.0000.0460.0590.082
성별0.0461.0000.0000.057
출발항0.0590.0001.0000.336
구분0.0820.0570.3361.000

Missing values

2023-12-16T06:34:02.619363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T06:34:03.116128image/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

순번성별출국일시귀국예정일출발항구분
99449945남2023-01-082023-02-07김해공항신고함
1479514796남2023-01-252023-01-28인천공항모바일
75977598남2022-12-302023-01-13인천공항모바일
8971289713남2023-10-142023-10-18인천공항모바일
7508675087여2023-08-222023-08-26인천공항전화
9477994780여2023-11-032023-11-06인천공항전화
19081909남2022-12-072022-12-12인천공항전화
7735077351남2023-08-302023-09-05인천공항전화
61976198남2022-12-232022-12-27인천공항전화
3672036721남2023-03-292023-04-03인천공항모바일
순번성별출국일시귀국예정일출발항구분
7891078911남2023-09-042023-10-07인천공항전화
5178451785여2023-06-022023-06-06인천공항신고함
70167017여2022-12-272023-01-02인천공항전화
1476114762여2023-01-252023-01-28인천공항모바일
2623426235남2023-02-242023-03-02인천공항전화
2839928400여2023-03-032023-03-13인천공항모바일
24922493남2022-12-092022-12-12인천공항신고함
9478394784남2023-11-032023-11-07김해공항개인
4177541776남2023-04-192023-04-23김해공항신고함
85828583남2023-01-042023-04-28인천공항방문