Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

DateTime1
Categorical4
Numeric2

Dataset

Description제주빅데이터센터 데이터를 활용하여 국가별 외국인 방문지 파악을 위한 유동인구 및 와이파이 이용현황 데이터 제공 - 방문인구는 해당 유동인구 수의 일별 합계 ※ 유동인구는 01~24시 해당 시간 정각 측정 인구 (머문 시간(분)/60분)
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/749

Alerts

데이터기준일자 has constant value ""Constant
시도명 is highly overall correlated with 읍면동명High correlation
읍면동명 is highly overall correlated with 시도명High correlation
방문인구 has 1819 (18.2%) zerosZeros
서비스 사용시간 has 1969 (19.7%) zerosZeros

Reproduction

Analysis started2023-12-11 20:13:06.629365
Analysis finished2023-12-11 20:13:07.586085
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

Distinct233
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-01-01 00:00:00
Maximum2019-12-31 00:00:00
2023-12-12T05:13:07.672879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:13:07.789985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제주시
6062 
서귀포시
3938 

Length

Max length4
Median length3
Mean length3.3938
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제주시
2nd row제주시
3rd row서귀포시
4th row제주시
5th row서귀포시

Common Values

ValueCountFrequency (%)
제주시 6062
60.6%
서귀포시 3938
39.4%

Length

2023-12-12T05:13:07.914273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:13:07.997816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 6062
60.6%
서귀포시 3938
39.4%

읍면동명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
화북동
 
269
한림읍
 
256
구좌읍
 
253
삼양동
 
247
예래동
 
247
Other values (38)
8728 

Length

Max length4
Median length3
Mean length3.1669
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한경면
2nd row구좌읍
3rd row효돈동
4th row한림읍
5th row대천동

Common Values

ValueCountFrequency (%)
화북동 269
 
2.7%
한림읍 256
 
2.6%
구좌읍 253
 
2.5%
삼양동 247
 
2.5%
예래동 247
 
2.5%
이도1동 245
 
2.5%
동홍동 245
 
2.5%
송산동 244
 
2.4%
우도면 244
 
2.4%
일도2동 243
 
2.4%
Other values (33) 7507
75.1%

Length

2023-12-12T05:13:08.091568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화북동 269
 
2.7%
한림읍 256
 
2.6%
구좌읍 253
 
2.5%
삼양동 247
 
2.5%
예래동 247
 
2.5%
이도1동 245
 
2.5%
동홍동 245
 
2.5%
송산동 244
 
2.4%
우도면 244
 
2.4%
일도2동 243
 
2.4%
Other values (33) 7507
75.1%

국적
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
인도
1049 
일본
1016 
싱가포르
1015 
홍콩
1011 
말레이시아
1003 
Other values (5)
4906 

Length

Max length5
Median length2
Mean length2.6009
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row싱가포르
2nd row타이
3rd row타이
4th row인도
5th row미국

Common Values

ValueCountFrequency (%)
인도 1049
10.5%
일본 1016
10.2%
싱가포르 1015
10.2%
홍콩 1011
10.1%
말레이시아 1003
10.0%
중국 1002
10.0%
기타 996
10.0%
미국 971
9.7%
베트남 970
9.7%
타이 967
9.7%

Length

2023-12-12T05:13:08.213224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:13:08.316622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인도 1049
10.5%
일본 1016
10.2%
싱가포르 1015
10.2%
홍콩 1011
10.1%
말레이시아 1003
10.0%
중국 1002
10.0%
기타 996
10.0%
미국 971
9.7%
베트남 970
9.7%
타이 967
9.7%

방문인구
Real number (ℝ)

ZEROS 

Distinct5700
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean637.29326
Minimum0
Maximum71835.401
Zeros1819
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:13:08.454922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110.96175
median83.183
Q3318.34025
95-th percentile2164.8202
Maximum71835.401
Range71835.401
Interquartile range (IQR)307.3785

Descriptive statistics

Standard deviation3029.961
Coefficient of variation (CV)4.7544218
Kurtosis200.64779
Mean637.29326
Median Absolute Deviation (MAD)83.183
Skewness12.696324
Sum6372932.6
Variance9180663.5
MonotonicityNot monotonic
2023-12-12T05:13:08.571695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1819
 
18.2%
3.135 18
 
0.2%
5.207999999999999 17
 
0.2%
1.211 16
 
0.2%
11.94 14
 
0.1%
10.416 13
 
0.1%
6.27 13
 
0.1%
1.841 12
 
0.1%
47.026 12
 
0.1%
36.455 11
 
0.1%
Other values (5690) 8055
80.5%
ValueCountFrequency (%)
0.0 1819
18.2%
0.303 4
 
< 0.1%
0.607 4
 
< 0.1%
0.91 2
 
< 0.1%
1.211 16
 
0.2%
1.255 1
 
< 0.1%
1.382 2
 
< 0.1%
1.3969999999999998 1
 
< 0.1%
1.406 2
 
< 0.1%
1.446 1
 
< 0.1%
ValueCountFrequency (%)
71835.401 1
< 0.1%
61621.756 1
< 0.1%
59697.416 1
< 0.1%
57490.597 1
< 0.1%
55713.046 1
< 0.1%
55002.96599999999 1
< 0.1%
53016.154 1
< 0.1%
53011.452000000005 1
< 0.1%
51238.603 1
< 0.1%
50961.155 1
< 0.1%

서비스 사용시간
Real number (ℝ)

ZEROS 

Distinct7485
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1417362.6
Minimum0
Maximum1.1960009 × 108
Zeros1969
Zeros (%)19.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T05:13:08.731826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1808.75
median15602
Q3133351.5
95-th percentile7104354
Maximum1.1960009 × 108
Range1.1960009 × 108
Interquartile range (IQR)132542.75

Descriptive statistics

Standard deviation6530115.5
Coefficient of variation (CV)4.6072299
Kurtosis82.889202
Mean1417362.6
Median Absolute Deviation (MAD)15602
Skewness8.1473216
Sum1.4173626 × 1010
Variance4.2642409 × 1013
MonotonicityNot monotonic
2023-12-12T05:13:08.878804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1969
 
19.7%
3686 12
 
0.1%
3671 10
 
0.1%
2 9
 
0.1%
3676 6
 
0.1%
3665 6
 
0.1%
3670 6
 
0.1%
3677 5
 
0.1%
3700 5
 
0.1%
3668 5
 
0.1%
Other values (7475) 7967
79.7%
ValueCountFrequency (%)
0 1969
19.7%
1 1
 
< 0.1%
2 9
 
0.1%
3 4
 
< 0.1%
4 1
 
< 0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
9 3
 
< 0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
119600088 1
< 0.1%
99571687 1
< 0.1%
96148238 1
< 0.1%
93296340 1
< 0.1%
91137644 1
< 0.1%
90606305 1
< 0.1%
89494189 1
< 0.1%
88487443 1
< 0.1%
83808025 1
< 0.1%
82347736 1
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2020-12-15
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-15
2nd row2020-12-15
3rd row2020-12-15
4th row2020-12-15
5th row2020-12-15

Common Values

ValueCountFrequency (%)
2020-12-15 10000
100.0%

Length

2023-12-12T05:13:09.055504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:13:09.164011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-15 10000
100.0%

Interactions

2023-12-12T05:13:07.216592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:13:07.045261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:13:07.305629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:13:07.131663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:13:09.217340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명읍면동명국적방문인구서비스 사용시간
시도명1.0001.0000.0140.0740.152
읍면동명1.0001.0000.0000.3860.340
국적0.0140.0001.0000.3500.518
방문인구0.0740.3860.3501.0000.041
서비스 사용시간0.1520.3400.5180.0411.000
2023-12-12T05:13:09.309095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명읍면동명국적
시도명1.0000.9980.011
읍면동명0.9981.0000.000
국적0.0110.0001.000
2023-12-12T05:13:09.421207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방문인구서비스 사용시간시도명읍면동명국적
방문인구1.0000.4860.0560.1430.114
서비스 사용시간0.4861.0000.1170.1240.182
시도명0.0560.1171.0000.9980.011
읍면동명0.1430.1240.9981.0000.000
국적0.1140.1820.0110.0001.000

Missing values

2023-12-12T05:13:07.413398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:13:07.516271image/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

일자시도명읍면동명국적방문인구서비스 사용시간데이터기준일자
396062019-01-01제주시한경면싱가포르50.024382020-12-15
954872019-05-11제주시구좌읍타이158.76785412020-12-15
596972019-02-16서귀포시효돈동타이0.002020-12-15
657932019-03-03제주시한림읍인도3.57102020-12-15
743682019-03-22서귀포시대천동미국22.93944092020-12-15
98522019-10-23서귀포시대륜동홍콩1786.028422020-12-15
827582019-04-11제주시아라동미국33.9022585952020-12-15
144822019-11-03서귀포시안덕면홍콩107.39821952020-12-15
630062019-02-24제주시노형동싱가포르190.359121572020-12-15
701452019-03-13제주시추자면말레이시아21.36502020-12-15
일자시도명읍면동명국적방문인구서비스 사용시간데이터기준일자
362092019-12-24제주시일도2동베트남0.01248472020-12-15
216942019-11-20제주시아라동일본17.9111942052020-12-15
384772019-12-29제주시오라동타이369.42936482020-12-15
827702019-04-11제주시연동중국45857.40830423822020-12-15
430552019-01-09제주시추자면말레이시아9.58202020-12-15
131852019-10-31서귀포시성산읍말레이시아1105.9551306262020-12-15
539062019-02-03제주시건입동싱가포르209.39520232020-12-15
41802019-10-10서귀포시송산동중국496.11510558272020-12-15
412762019-01-04서귀포시예래동싱가포르275.031332020-12-15
559762019-02-08제주시일도1동싱가포르0.079092020-12-15