Overview

Dataset statistics

Number of variables9
Number of observations2338
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory171.4 KiB
Average record size in memory75.1 B

Variable types

DateTime2
Categorical4
Numeric3

Dataset

Description제주도 내 중국인 관광객 타겟 마케팅을 위한 활용 데이터 매쉬업 결과 정보입니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15074780/fileData.do

Alerts

이용자 구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
읍면동명 is highly overall correlated with 시도명High correlation
시도명 is highly overall correlated with 읍면동명High correlation
이용자수 is highly overall correlated with 이용금액High correlation
이용금액 is highly overall correlated with 이용자수High correlation

Reproduction

Analysis started2024-04-17 18:38:55.844637
Analysis finished2024-04-17 18:38:57.004594
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
Minimum2018-01-01 00:00:00
Maximum2018-12-01 00:00:00
2024-04-18T03:38:57.038179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:57.113479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

이용자 구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
중국인관광객
2338 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중국인관광객 2338
100.0%

Length

2024-04-18T03:38:57.203003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:38:57.285717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중국인관광객 2338
100.0%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
제주시
1363 
서귀포시
975 

Length

Max length4
Median length3
Mean length3.4170231
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 1363
58.3%
서귀포시 975
41.7%

Length

2024-04-18T03:38:57.375405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:38:57.446788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 1363
58.3%
서귀포시 975
41.7%

읍면동명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
송산동
 
87
천지동
 
86
안덕면
 
84
연동
 
81
노형동
 
75
Other values (37)
1925 

Length

Max length4
Median length3
Mean length3.1565441
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대륜동
2nd row대륜동
3rd row대륜동
4th row대륜동
5th row대천동

Common Values

ValueCountFrequency (%)
송산동 87
 
3.7%
천지동 86
 
3.7%
안덕면 84
 
3.6%
연동 81
 
3.5%
노형동 75
 
3.2%
정방동 71
 
3.0%
이도2동 71
 
3.0%
예래동 70
 
3.0%
애월읍 69
 
3.0%
성산읍 68
 
2.9%
Other values (32) 1576
67.4%

Length

2024-04-18T03:38:57.535935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송산동 87
 
3.7%
천지동 86
 
3.7%
안덕면 84
 
3.6%
연동 81
 
3.5%
노형동 75
 
3.2%
정방동 71
 
3.0%
이도2동 71
 
3.0%
예래동 70
 
3.0%
애월읍 69
 
3.0%
성산읍 68
 
2.9%
Other values (32) 1576
67.4%

업종
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
쇼핑
520 
식음료
502 
소매
402 
숙박
356 
문화/레져
256 
Other values (2)
302 

Length

Max length5
Median length2
Mean length2.5431993
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row소매
2nd row쇼핑
3rd row숙박
4th row식음료
5th row쇼핑

Common Values

ValueCountFrequency (%)
쇼핑 520
22.2%
식음료 502
21.5%
소매 402
17.2%
숙박 356
15.2%
문화/레져 256
10.9%
교통 225
9.6%
유흥 77
 
3.3%

Length

2024-04-18T03:38:57.666132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:38:57.772074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
쇼핑 520
22.2%
식음료 502
21.5%
소매 402
17.2%
숙박 356
15.2%
문화/레져 256
10.9%
교통 225
9.6%
유흥 77
 
3.3%

방문인구
Real number (ℝ)

Distinct501
Distinct (%)21.5%
Missing3
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean113982.45
Minimum912.409
Maximum1507187.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-04-18T03:38:57.870035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum912.409
5-th percentile6498.927
Q120045.766
median41622.982
Q3105553.49
95-th percentile517800.17
Maximum1507187.3
Range1506274.9
Interquartile range (IQR)85507.721

Descriptive statistics

Standard deviation210294.28
Coefficient of variation (CV)1.8449706
Kurtosis16.955076
Mean113982.45
Median Absolute Deviation (MAD)29219.378
Skewness3.8703488
Sum2.6614903 × 108
Variance4.4223682 × 1010
MonotonicityNot monotonic
2024-04-18T03:38:57.976608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49646.056 9
 
0.4%
34298.709 9
 
0.4%
46485.453 8
 
0.3%
89048.892 8
 
0.3%
113194.389 8
 
0.3%
206259.432 8
 
0.3%
23789.745 8
 
0.3%
55400.954 8
 
0.3%
46047.451 8
 
0.3%
53617.975 8
 
0.3%
Other values (491) 2253
96.4%
ValueCountFrequency (%)
912.409 2
0.1%
1032.567 3
0.1%
1498.604 1
 
< 0.1%
1697.471 2
0.1%
1992.564 1
 
< 0.1%
2136.545 2
0.1%
2259.71 2
0.1%
2332.337 2
0.1%
2504.51 2
0.1%
2514.878 2
0.1%
ValueCountFrequency (%)
1507187.284 7
0.3%
1405892.507 7
0.3%
1293214.782 7
0.3%
1152313.229 7
0.3%
1023131.17 7
0.3%
999944.935 7
0.3%
951313.251 6
0.3%
910100.552 5
0.2%
861602.514 7
0.3%
836774.018 6
0.3%

이용자수
Real number (ℝ)

HIGH CORRELATION 

Distinct380
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean314.72327
Minimum1
Maximum48859
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-04-18T03:38:58.088480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median12
Q355
95-th percentile586.35
Maximum48859
Range48858
Interquartile range (IQR)52

Descriptive statistics

Standard deviation2298.0555
Coefficient of variation (CV)7.301829
Kurtosis195.416
Mean314.72327
Median Absolute Deviation (MAD)11
Skewness13.036246
Sum735823
Variance5281059
MonotonicityNot monotonic
2024-04-18T03:38:58.188996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 349
 
14.9%
2 186
 
8.0%
3 121
 
5.2%
4 114
 
4.9%
5 80
 
3.4%
7 61
 
2.6%
6 55
 
2.4%
9 53
 
2.3%
8 49
 
2.1%
11 44
 
1.9%
Other values (370) 1226
52.4%
ValueCountFrequency (%)
1 349
14.9%
2 186
8.0%
3 121
 
5.2%
4 114
 
4.9%
5 80
 
3.4%
6 55
 
2.4%
7 61
 
2.6%
8 49
 
2.1%
9 53
 
2.3%
10 33
 
1.4%
ValueCountFrequency (%)
48859 1
< 0.1%
36129 1
< 0.1%
32313 1
< 0.1%
32221 1
< 0.1%
30850 1
< 0.1%
27707 1
< 0.1%
27517 1
< 0.1%
27069 1
< 0.1%
25817 1
< 0.1%
23604 1
< 0.1%

이용금액
Real number (ℝ)

HIGH CORRELATION 

Distinct1972
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77907214
Minimum1000
Maximum1.2246302 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.7 KiB
2024-04-18T03:38:58.289130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile20000
Q1124892.5
median647030
Q33798912.5
95-th percentile1.6757641 × 108
Maximum1.2246302 × 1010
Range1.2246301 × 1010
Interquartile range (IQR)3674020

Descriptive statistics

Standard deviation6.0301895 × 108
Coefficient of variation (CV)7.7402196
Kurtosis197.33383
Mean77907214
Median Absolute Deviation (MAD)607030
Skewness13.293218
Sum1.8214707 × 1011
Variance3.6363185 × 1017
MonotonicityNot monotonic
2024-04-18T03:38:58.401941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 16
 
0.7%
30000 12
 
0.5%
60000 9
 
0.4%
20000 9
 
0.4%
40000 8
 
0.3%
44000 8
 
0.3%
80000 7
 
0.3%
48000 7
 
0.3%
38000 7
 
0.3%
90000 6
 
0.3%
Other values (1962) 2249
96.2%
ValueCountFrequency (%)
1000 2
0.1%
1100 1
 
< 0.1%
2000 3
0.1%
2100 1
 
< 0.1%
2900 1
 
< 0.1%
3000 4
0.2%
4000 1
 
< 0.1%
4100 2
0.1%
4300 1
 
< 0.1%
4400 2
0.1%
ValueCountFrequency (%)
12246302010 1
< 0.1%
9573213155 1
< 0.1%
9251702503 1
< 0.1%
8379724635 1
< 0.1%
8340831155 1
< 0.1%
7911147195 1
< 0.1%
7596446641 1
< 0.1%
7152316376 1
< 0.1%
7047358041 1
< 0.1%
6411996858 1
< 0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.4 KiB
Minimum2020-12-15 00:00:00
Maximum2020-12-15 00:00:00
2024-04-18T03:38:58.486758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:58.826970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-18T03:38:56.612829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.177727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.399456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.690119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.255140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.474942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.760773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.325343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:38:56.539765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T03:38:58.881402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년월시도명읍면동명업종방문인구이용자수이용금액
기준년월1.0000.0000.0000.0000.3300.0000.000
시도명0.0001.0001.0000.0000.2740.1030.034
읍면동명0.0001.0001.0000.2930.8250.3020.369
업종0.0000.0000.2931.0000.0000.0880.193
방문인구0.3300.2740.8250.0001.0000.4530.454
이용자수0.0000.1030.3020.0880.4531.0000.910
이용금액0.0000.0340.3690.1930.4540.9101.000
2024-04-18T03:38:58.967814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종읍면동명시도명
업종1.0000.1140.000
읍면동명0.1141.0000.989
시도명0.0000.9891.000
2024-04-18T03:38:59.037186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방문인구이용자수이용금액시도명읍면동명업종
방문인구1.0000.3550.3910.2100.4550.000
이용자수0.3551.0000.8740.0770.1190.047
이용금액0.3910.8741.0000.0370.1470.068
시도명0.2100.0770.0371.0000.9890.000
읍면동명0.4550.1190.1470.9891.0000.114
업종0.0000.0470.0680.0000.1141.000

Missing values

2024-04-18T03:38:56.858435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:38:56.962101image/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

기준년월이용자 구분시도명읍면동명업종방문인구이용자수이용금액데이터기준일자
02018-01중국인관광객서귀포시대륜동소매22743.84616000002020-12-15
12018-01중국인관광객서귀포시대륜동쇼핑22743.846110115588102020-12-15
22018-01중국인관광객서귀포시대륜동숙박22743.84644186002020-12-15
32018-01중국인관광객서귀포시대륜동식음료22743.84631878402020-12-15
42018-01중국인관광객서귀포시대천동쇼핑7274.67541984302020-12-15
52018-01중국인관광객서귀포시대천동숙박7274.6751300002020-12-15
62018-01중국인관광객서귀포시동홍동교통17931.53643410002020-12-15
72018-01중국인관광객서귀포시송산동교통20638.98143410002020-12-15
82018-01중국인관광객서귀포시동홍동쇼핑17931.5368965333602020-12-15
92018-01중국인관광객서귀포시송산동쇼핑20638.9818965333602020-12-15
기준년월이용자 구분시도명읍면동명업종방문인구이용자수이용금액데이터기준일자
23282018-12중국인관광객제주시이호동소매30139.8011801966495002020-12-15
23292018-12중국인관광객서귀포시성산읍숙박116738.552622488807132020-12-15
23302018-12중국인관광객서귀포시예래동쇼핑72995.2746742569633402020-12-15
23312018-12중국인관광객제주시한림읍숙박99600.896342754407982020-12-15
23322018-12중국인관광객제주시한림읍문화/레져99600.896213273263542020-12-15
23332018-12중국인관광객제주시용담2동쇼핑632161.50144786397042242020-12-15
23342018-12중국인관광객제주시연동소매1293214.78245918514246732020-12-15
23352018-12중국인관광객제주시노형동숙박283032.199708531359632020-12-15
23362018-12중국인관광객서귀포시남원읍숙박75153.799222254851492020-12-15
23372018-12중국인관광객제주시연동쇼핑1293214.7822751795732131552020-12-15