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

DateTime2
Categorical3
Numeric2

Dataset

Description제주 유동인구 데이터와 와이파이 이용현황 데이터를 활용한 국가별 외국인 방문지 파악 매쉬업 결과 정보입니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15074772/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
시도명 is highly overall correlated with 읍면동명High correlation
읍면동명 is highly overall correlated with 시도명High correlation
방문인구 has 2567 (25.7%) zerosZeros
서비스 사용시간 has 4190 (41.9%) zerosZeros

Reproduction

Analysis started2023-12-12 18:02:50.818862
Analysis finished2023-12-12 18:02:51.850858
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Date

Distinct222
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-31 00:00:00
2023-12-13T03:02:51.960693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:52.127431image/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
6049 
서귀포시
3951 

Length

Max length4
Median length3
Mean length3.3951
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 6049
60.5%
서귀포시 3951
39.5%

Length

2023-12-13T03:02:52.281549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:52.397001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 6049
60.5%
서귀포시 3951
39.5%

읍면동명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
이도2동
 
268
이호동
 
260
한경면
 
257
일도2동
 
257
성산읍
 
253
Other values (38)
8705 

Length

Max length4
Median length3
Mean length3.1659
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row용담1동
2nd row송산동
3rd row예래동
4th row아라동
5th row한경면

Common Values

ValueCountFrequency (%)
이도2동 268
 
2.7%
이호동 260
 
2.6%
한경면 257
 
2.6%
일도2동 257
 
2.6%
성산읍 253
 
2.5%
연동 252
 
2.5%
일도1동 251
 
2.5%
대천동 247
 
2.5%
이도1동 244
 
2.4%
조천읍 242
 
2.4%
Other values (33) 7469
74.7%

Length

2023-12-13T03:02:52.522174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
이도2동 268
 
2.7%
이호동 260
 
2.6%
한경면 257
 
2.6%
일도2동 257
 
2.6%
성산읍 253
 
2.5%
연동 252
 
2.5%
일도1동 251
 
2.5%
대천동 247
 
2.5%
이도1동 244
 
2.4%
노형동 242
 
2.4%
Other values (33) 7469
74.7%

국적
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
타이
1075 
싱가포르
1028 
홍콩
1027 
베트남
1004 
말레이시아
994 
Other values (5)
4872 

Length

Max length5
Median length2
Mean length2.6042
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row말레이시아
2nd row인도
3rd row중국
4th row일본
5th row싱가포르

Common Values

ValueCountFrequency (%)
타이 1075
10.8%
싱가포르 1028
10.3%
홍콩 1027
10.3%
베트남 1004
10.0%
말레이시아 994
9.9%
기타 992
9.9%
일본 983
9.8%
중국 980
9.8%
미국 970
9.7%
인도 947
9.5%

Length

2023-12-13T03:02:52.678753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:02:52.828701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
타이 1075
10.8%
싱가포르 1028
10.3%
홍콩 1027
10.3%
베트남 1004
10.0%
말레이시아 994
9.9%
기타 992
9.9%
일본 983
9.8%
중국 980
9.8%
미국 970
9.7%
인도 947
9.5%

방문인구
Real number (ℝ)

ZEROS 

Distinct5411
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean453.125
Minimum0
Maximum58704.118
Zeros2567
Zeros (%)25.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:02:53.013647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median62.9735
Q3254.9535
95-th percentile1636.1181
Maximum58704.118
Range58704.118
Interquartile range (IQR)254.9535

Descriptive statistics

Standard deviation2152.8157
Coefficient of variation (CV)4.7510416
Kurtosis246.238
Mean453.125
Median Absolute Deviation (MAD)62.9735
Skewness13.915229
Sum4531250
Variance4634615.6
MonotonicityNot monotonic
2023-12-13T03:02:53.164967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2567
 
25.7%
19.057 11
 
0.1%
9.933 11
 
0.1%
11.728 10
 
0.1%
23.0 10
 
0.1%
2.544 10
 
0.1%
27.783 9
 
0.1%
5.835 9
 
0.1%
2.487 9
 
0.1%
17.837 9
 
0.1%
Other values (5401) 7345
73.5%
ValueCountFrequency (%)
0.0 2567
25.7%
0.846 6
 
0.1%
1.132 6
 
0.1%
1.403 4
 
< 0.1%
1.411 2
 
< 0.1%
1.447 6
 
0.1%
1.553 3
 
< 0.1%
1.556 1
 
< 0.1%
1.61 5
 
0.1%
1.692 1
 
< 0.1%
ValueCountFrequency (%)
58704.118 1
< 0.1%
53111.97 1
< 0.1%
44825.216 1
< 0.1%
44392.814 1
< 0.1%
42457.092 1
< 0.1%
40980.6 1
< 0.1%
40918.733 1
< 0.1%
40379.279 1
< 0.1%
37328.974 1
< 0.1%
35117.183 1
< 0.1%

서비스 사용시간
Real number (ℝ)

ZEROS 

Distinct5165
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean459258.08
Minimum0
Maximum51755519
Zeros4190
Zeros (%)41.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T03:02:53.315650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median703.5
Q318273.25
95-th percentile2162037.2
Maximum51755519
Range51755519
Interquartile range (IQR)18273.25

Descriptive statistics

Standard deviation2396979.9
Coefficient of variation (CV)5.2192438
Kurtosis135.15751
Mean459258.08
Median Absolute Deviation (MAD)703.5
Skewness9.9432764
Sum4.5925808 × 109
Variance5.7455125 × 1012
MonotonicityNot monotonic
2023-12-13T03:02:53.505149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4190
41.9%
323 7
 
0.1%
377 6
 
0.1%
133 6
 
0.1%
1 5
 
0.1%
4 5
 
0.1%
126 5
 
0.1%
369 5
 
0.1%
399 5
 
0.1%
375 5
 
0.1%
Other values (5155) 5761
57.6%
ValueCountFrequency (%)
0 4190
41.9%
1 5
 
0.1%
2 4
 
< 0.1%
3 4
 
< 0.1%
4 5
 
0.1%
5 4
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
51755519 1
< 0.1%
51015158 1
< 0.1%
50261764 1
< 0.1%
45859430 1
< 0.1%
40704747 1
< 0.1%
35365805 1
< 0.1%
34897273 1
< 0.1%
34854704 1
< 0.1%
34512969 1
< 0.1%
32742344 1
< 0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-12-15 00:00:00
Maximum2020-12-15 00:00:00
2023-12-13T03:02:53.627014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:53.726298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:02:51.433828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:51.236723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:51.543216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:02:51.330873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:02:53.806144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명읍면동명국적방문인구서비스 사용시간
시도명1.0001.0000.0000.0370.102
읍면동명1.0001.0000.0000.2900.199
국적0.0000.0001.0000.2090.448
방문인구0.0370.2900.2091.0000.000
서비스 사용시간0.1020.1990.4480.0001.000
2023-12-13T03:02:53.932767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명읍면동명국적
시도명1.0000.9980.000
읍면동명0.9981.0000.000
국적0.0000.0001.000
2023-12-13T03:02:54.033889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방문인구서비스 사용시간시도명읍면동명국적
방문인구1.0000.4130.0360.1090.096
서비스 사용시간0.4131.0000.0780.0700.151
시도명0.0360.0781.0000.9980.000
읍면동명0.1090.0700.9981.0000.000
국적0.0960.1510.0000.0001.000

Missing values

2023-12-13T03:02:51.669204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:02:51.786944image/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
164752018-11-08제주시용담1동말레이시아97.96337262020-12-15
596532018-02-16서귀포시송산동인도0.022482020-12-15
442802018-01-11서귀포시예래동중국4157.79755782020-12-15
1942018-10-01제주시아라동일본273.892402552020-12-15
443362018-01-12제주시한경면싱가포르0.002020-12-15
472802018-01-18서귀포시중문동중국444.03598472020-12-15
255152018-11-29제주시용담2동말레이시아2213.967253042020-12-15
401192018-01-02제주시삼도2동베트남0.002020-12-15
568552018-02-10제주시이도1동말레이시아3.1502020-12-15
730952018-03-19서귀포시예래동말레이시아301.99285592020-12-15
일자시도명읍면동명국적방문인구서비스 사용시간데이터기준일자
446252018-01-12서귀포시중앙동말레이시아69.498295052020-12-15
753752018-03-25제주시삼도2동말레이시아1274.46102020-12-15
331492018-12-17제주시조천읍베트남0.096302020-12-15
161392018-11-07제주시노형동베트남1139.113594262020-12-15
714892018-03-16제주시이도2동베트남0.002020-12-15
339882018-12-19제주시애월읍미국417.18916842020-12-15
245922018-11-27제주시일도2동홍콩5.97902020-12-15
148352018-11-04제주시연동말레이시아1382.369226182020-12-15
472512018-01-18서귀포시서홍동기타1167.4768834432020-12-15
699792018-03-12서귀포시송산동베트남0.0141722020-12-15