Overview

Dataset statistics

Number of variables10
Number of observations400
Missing cells474
Missing cells (%)11.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.7 KiB
Average record size in memory86.3 B

Variable types

Categorical3
Text1
Numeric6

Dataset

Description시군별, 연도별 경남방문 관광객(내국인, 외국인) 현황자료 안내입니다. 2013년부터 2016년까지의 내국인관광객수, 외국인관광객 수를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3034241

Alerts

시도 has constant value ""Constant
2017년 is highly overall correlated with 2018년 and 4 other fieldsHigh correlation
2018년 is highly overall correlated with 2017년 and 4 other fieldsHigh correlation
2019년 is highly overall correlated with 2017년 and 4 other fieldsHigh correlation
2020년 is highly overall correlated with 2017년 and 4 other fieldsHigh correlation
2021년 is highly overall correlated with 2017년 and 4 other fieldsHigh correlation
2022년 is highly overall correlated with 2017년 and 4 other fieldsHigh correlation
2017년 has 125 (31.2%) missing valuesMissing
2018년 has 111 (27.8%) missing valuesMissing
2019년 has 71 (17.8%) missing valuesMissing
2020년 has 62 (15.5%) missing valuesMissing
2021년 has 58 (14.5%) missing valuesMissing
2022년 has 47 (11.8%) missing valuesMissing
2017년 has 78 (19.5%) zerosZeros
2018년 has 65 (16.2%) zerosZeros
2019년 has 62 (15.5%) zerosZeros
2020년 has 68 (17.0%) zerosZeros
2021년 has 76 (19.0%) zerosZeros
2022년 has 71 (17.8%) zerosZeros

Reproduction

Analysis started2023-12-11 00:50:19.420880
Analysis finished2023-12-11 00:50:23.415284
Duration3.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
경상남도
400 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 400
100.0%

Length

2023-12-11T09:50:23.491330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:50:23.573121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 400
100.0%

시군
Categorical

Distinct18
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
거제시
66 
김해시
40 
통합창원시
37 
통영시
33 
양산시
31 
Other values (13)
193 

Length

Max length5
Median length3
Mean length3.185
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
거제시 66
16.5%
김해시 40
10.0%
통합창원시 37
9.2%
통영시 33
8.2%
양산시 31
 
7.8%
남해군 25
 
6.2%
밀양시 24
 
6.0%
진주시 24
 
6.0%
거창군 23
 
5.8%
창녕군 17
 
4.2%
Other values (8) 80
20.0%

Length

2023-12-11T09:50:23.674275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
거제시 66
16.5%
김해시 40
10.0%
통합창원시 37
9.2%
통영시 33
8.2%
양산시 31
 
7.8%
남해군 25
 
6.2%
밀양시 24
 
6.0%
진주시 24
 
6.0%
거창군 23
 
5.8%
창녕군 17
 
4.2%
Other values (8) 80
20.0%

관광지
Text

Distinct279
Distinct (%)69.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-11T09:50:23.900225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length7.285
Min length2

Characters and Unicode

Total characters2914
Distinct characters336
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

Unique158 ?
Unique (%)39.5%

Sample

1st row3.15아트
2nd row3.15아트
3rd row군항문화탐방
4th row도립미술관
5th row도립미술관
ValueCountFrequency (%)
컨트리클럽 9
 
1.8%
코스 6
 
1.2%
매물도 4
 
0.8%
박물관 4
 
0.8%
얼음골 3
 
0.6%
에덴밸리 3
 
0.6%
씨라인 2
 
0.4%
이순신영상관 2
 
0.4%
원예예술촌 2
 
0.4%
오션베이 2
 
0.4%
Other values (327) 456
92.5%
2023-12-11T09:50:24.252176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 93
 
3.2%
93
 
3.2%
원 82
 
2.8%
산 73
 
2.5%
물 56
 
1.9%
도 53
 
1.8%
공 50
 
1.7%
마 49
 
1.7%
해 48
 
1.6%
양 47
 
1.6%
Other values (326) 2270
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2736
93.9%
Space Separator 93
 
3.2%
Open Punctuation 27
 
0.9%
Close Punctuation 27
 
0.9%
Decimal Number 8
 
0.3%
Other Punctuation 7
 
0.2%
Math Symbol 6
 
0.2%
Lowercase Letter 4
 
0.1%
Uppercase Letter 4
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 93
 
3.4%
원 82
 
3.0%
산 73
 
2.7%
물 56
 
2.0%
도 53
 
1.9%
공 50
 
1.8%
마 49
 
1.8%
해 48
 
1.8%
양 47
 
1.7%
리 47
 
1.7%
Other values (310) 2138
78.1%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
H 1
25.0%
L 1
25.0%
G 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
. 2
28.6%
· 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
3 3
37.5%
1 3
37.5%
5 2
25.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2736
93.9%
Common 170
 
5.8%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 93
 
3.4%
원 82
 
3.0%
산 73
 
2.7%
물 56
 
2.0%
도 53
 
1.9%
공 50
 
1.8%
마 49
 
1.8%
해 48
 
1.8%
양 47
 
1.7%
리 47
 
1.7%
Other values (310) 2138
78.1%
Common
ValueCountFrequency (%)
93
54.7%
( 27
 
15.9%
) 27
 
15.9%
~ 6
 
3.5%
, 4
 
2.4%
3 3
 
1.8%
1 3
 
1.8%
5 2
 
1.2%
- 2
 
1.2%
. 2
 
1.2%
Latin
ValueCountFrequency (%)
c 4
50.0%
C 1
 
12.5%
H 1
 
12.5%
L 1
 
12.5%
G 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2736
93.9%
ASCII 177
 
6.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 93
 
3.4%
원 82
 
3.0%
산 73
 
2.7%
물 56
 
2.0%
도 53
 
1.9%
공 50
 
1.8%
마 49
 
1.8%
해 48
 
1.8%
양 47
 
1.7%
리 47
 
1.7%
Other values (310) 2138
78.1%
ASCII
ValueCountFrequency (%)
93
52.5%
( 27
 
15.3%
) 27
 
15.3%
~ 6
 
3.4%
c 4
 
2.3%
, 4
 
2.3%
3 3
 
1.7%
1 3
 
1.7%
5 2
 
1.1%
- 2
 
1.1%
Other values (5) 6
 
3.4%
None
ValueCountFrequency (%)
· 1
100.0%

내외국인 구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
내국인
279 
외국인
121 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row내국인
2nd row외국인
3rd row내국인
4th row내국인
5th row외국인

Common Values

ValueCountFrequency (%)
내국인 279
69.8%
외국인 121
30.2%

Length

2023-12-11T09:50:24.380373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:50:24.468667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내국인 279
69.8%
외국인 121
30.2%

2017년
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct195
Distinct (%)70.9%
Missing125
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean139546.96
Minimum0
Maximum3439296
Zeros78
Zeros (%)19.5%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-11T09:50:24.578803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17301
Q3152226.5
95-th percentile553947.1
Maximum3439296
Range3439296
Interquartile range (IQR)152226.5

Descriptive statistics

Standard deviation326954.27
Coefficient of variation (CV)2.3429695
Kurtosis45.632775
Mean139546.96
Median Absolute Deviation (MAD)17301
Skewness5.7665069
Sum38375414
Variance1.0689909 × 1011
MonotonicityNot monotonic
2023-12-11T09:50:24.724639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 78
19.5%
179 2
 
0.5%
40 2
 
0.5%
20 2
 
0.5%
529153 1
 
0.2%
135990 1
 
0.2%
112497 1
 
0.2%
194102 1
 
0.2%
180183 1
 
0.2%
237356 1
 
0.2%
Other values (185) 185
46.2%
(Missing) 125
31.2%
ValueCountFrequency (%)
0 78
19.5%
7 1
 
0.2%
19 1
 
0.2%
20 2
 
0.5%
40 2
 
0.5%
47 1
 
0.2%
57 1
 
0.2%
62 1
 
0.2%
65 1
 
0.2%
73 1
 
0.2%
ValueCountFrequency (%)
3439296 1
0.2%
2231752 1
0.2%
1625471 1
0.2%
1396275 1
0.2%
1260059 1
0.2%
1032975 1
0.2%
949450 1
0.2%
915128 1
0.2%
879310 1
0.2%
756684 1
0.2%

2018년
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct224
Distinct (%)77.5%
Missing111
Missing (%)27.8%
Infinite0
Infinite (%)0.0%
Mean127959.49
Minimum0
Maximum2394699
Zeros65
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-11T09:50:24.886484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q141
median22135
Q3139452
95-th percentile525099.2
Maximum2394699
Range2394699
Interquartile range (IQR)139411

Descriptive statistics

Standard deviation270939
Coefficient of variation (CV)2.117381
Kurtosis33.650864
Mean127959.49
Median Absolute Deviation (MAD)22135
Skewness5.0446937
Sum36980294
Variance7.3407944 × 1010
MonotonicityNot monotonic
2023-12-11T09:50:25.038447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65
 
16.2%
6 2
 
0.5%
280 1
 
0.2%
120366 1
 
0.2%
304941 1
 
0.2%
208417 1
 
0.2%
199964 1
 
0.2%
708 1
 
0.2%
63843 1
 
0.2%
41 1
 
0.2%
Other values (214) 214
53.5%
(Missing) 111
27.8%
ValueCountFrequency (%)
0 65
16.2%
1 1
 
0.2%
4 1
 
0.2%
6 2
 
0.5%
20 1
 
0.2%
28 1
 
0.2%
40 1
 
0.2%
41 1
 
0.2%
50 1
 
0.2%
52 1
 
0.2%
ValueCountFrequency (%)
2394699 1
0.2%
2246502 1
0.2%
1727640 1
0.2%
1064698 1
0.2%
1059483 1
0.2%
834570 1
0.2%
767812 1
0.2%
723607 1
0.2%
708465 1
0.2%
662920 1
0.2%

2019년
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct267
Distinct (%)81.2%
Missing71
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean121153.34
Minimum0
Maximum2157228
Zeros62
Zeros (%)15.5%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-11T09:50:25.180141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1250
median28836
Q3134836
95-th percentile531551.6
Maximum2157228
Range2157228
Interquartile range (IQR)134586

Descriptive statistics

Standard deviation244949.71
Coefficient of variation (CV)2.0218155
Kurtosis30.483724
Mean121153.34
Median Absolute Deviation (MAD)28836
Skewness4.7282743
Sum39859450
Variance6.0000358 × 1010
MonotonicityNot monotonic
2023-12-11T09:50:25.333655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 62
 
15.5%
7 2
 
0.5%
62865 1
 
0.2%
127016 1
 
0.2%
198891 1
 
0.2%
5445 1
 
0.2%
2070398 1
 
0.2%
319853 1
 
0.2%
63 1
 
0.2%
211894 1
 
0.2%
Other values (257) 257
64.2%
(Missing) 71
 
17.8%
ValueCountFrequency (%)
0 62
15.5%
1 1
 
0.2%
7 2
 
0.5%
10 1
 
0.2%
20 1
 
0.2%
23 1
 
0.2%
28 1
 
0.2%
29 1
 
0.2%
31 1
 
0.2%
35 1
 
0.2%
ValueCountFrequency (%)
2157228 1
0.2%
2070398 1
0.2%
1591169 1
0.2%
1069185 1
0.2%
891202 1
0.2%
804066 1
0.2%
799246 1
0.2%
745828 1
0.2%
741161 1
0.2%
702693 1
0.2%

2020년
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct269
Distinct (%)79.6%
Missing62
Missing (%)15.5%
Infinite0
Infinite (%)0.0%
Mean74951.565
Minimum0
Maximum1266366
Zeros68
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-11T09:50:25.456158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1136.75
median14284.5
Q382869.5
95-th percentile370004.9
Maximum1266366
Range1266366
Interquartile range (IQR)82732.75

Descriptive statistics

Standard deviation144058.42
Coefficient of variation (CV)1.9220201
Kurtosis19.811557
Mean74951.565
Median Absolute Deviation (MAD)14284.5
Skewness3.7294149
Sum25333629
Variance2.0752827 × 1010
MonotonicityNot monotonic
2023-12-11T09:50:25.595925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68
 
17.0%
4 2
 
0.5%
6 2
 
0.5%
37910 1
 
0.2%
127 1
 
0.2%
51040 1
 
0.2%
66863 1
 
0.2%
137458 1
 
0.2%
33 1
 
0.2%
20668 1
 
0.2%
Other values (259) 259
64.8%
(Missing) 62
 
15.5%
ValueCountFrequency (%)
0 68
17.0%
2 1
 
0.2%
4 2
 
0.5%
5 1
 
0.2%
6 2
 
0.5%
18 1
 
0.2%
25 1
 
0.2%
30 1
 
0.2%
33 1
 
0.2%
34 1
 
0.2%
ValueCountFrequency (%)
1266366 1
0.2%
963775 1
0.2%
714024 1
0.2%
600359 1
0.2%
579540 1
0.2%
540992 1
0.2%
534310 1
0.2%
492551 1
0.2%
447544 1
0.2%
434015 1
0.2%

2021년
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct266
Distinct (%)77.8%
Missing58
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean86703.564
Minimum0
Maximum1367603
Zeros76
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-11T09:50:25.755950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q116
median19225
Q3106970.75
95-th percentile431945.4
Maximum1367603
Range1367603
Interquartile range (IQR)106954.75

Descriptive statistics

Standard deviation162970.41
Coefficient of variation (CV)1.8796275
Kurtosis20.312027
Mean86703.564
Median Absolute Deviation (MAD)19225
Skewness3.8065667
Sum29652619
Variance2.6559353 × 1010
MonotonicityNot monotonic
2023-12-11T09:50:25.895496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 76
 
19.0%
5 2
 
0.5%
120682 1
 
0.2%
8 1
 
0.2%
17915 1
 
0.2%
19 1
 
0.2%
47579 1
 
0.2%
219250 1
 
0.2%
13 1
 
0.2%
34024 1
 
0.2%
Other values (256) 256
64.0%
(Missing) 58
 
14.5%
ValueCountFrequency (%)
0 76
19.0%
1 1
 
0.2%
2 1
 
0.2%
4 1
 
0.2%
5 2
 
0.5%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
13 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
1367603 1
0.2%
1242867 1
0.2%
783919 1
0.2%
783457 1
0.2%
670684 1
0.2%
577548 1
0.2%
541090 1
0.2%
537594 1
0.2%
525636 1
0.2%
499027 1
0.2%

2022년
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct282
Distinct (%)79.9%
Missing47
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean101925.95
Minimum0
Maximum1210831
Zeros71
Zeros (%)17.8%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-11T09:50:26.021822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1748
median39277
Q3126465
95-th percentile458356.6
Maximum1210831
Range1210831
Interquartile range (IQR)125717

Descriptive statistics

Standard deviation167701.03
Coefficient of variation (CV)1.6453222
Kurtosis11.317882
Mean101925.95
Median Absolute Deviation (MAD)39277
Skewness2.9807099
Sum35979859
Variance2.8123634 × 1010
MonotonicityNot monotonic
2023-12-11T09:50:26.179367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71
 
17.8%
10 2
 
0.5%
61935 1
 
0.2%
4796 1
 
0.2%
126465 1
 
0.2%
58313 1
 
0.2%
27 1
 
0.2%
88292 1
 
0.2%
217605 1
 
0.2%
81493 1
 
0.2%
Other values (272) 272
68.0%
(Missing) 47
 
11.8%
ValueCountFrequency (%)
0 71
17.8%
1 1
 
0.2%
2 1
 
0.2%
10 2
 
0.5%
12 1
 
0.2%
27 1
 
0.2%
30 1
 
0.2%
36 1
 
0.2%
54 1
 
0.2%
56 1
 
0.2%
ValueCountFrequency (%)
1210831 1
0.2%
1027844 1
0.2%
940677 1
0.2%
814383 1
0.2%
801175 1
0.2%
618855 1
0.2%
611355 1
0.2%
604395 1
0.2%
566813 1
0.2%
563391 1
0.2%

Interactions

2023-12-11T09:50:22.618325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:19.862271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.351340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.832790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.347830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.126461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.699400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:19.942657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.434345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.918124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.427421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.213169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.775011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.018250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.506224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.999170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.514146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.294137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.848305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.087013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.574664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.084583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.608420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.365355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.928583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.175424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.665519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.183630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.950828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.451901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:23.009207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.253074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:20.758576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:21.271324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.049981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:50:22.534837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:50:26.543420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군내외국인 구분2017년2018년2019년2020년2021년2022년
시군1.0000.2100.0000.2110.0630.1650.1420.000
내외국인 구분0.2101.0000.2490.2800.2500.3730.2550.411
2017년0.0000.2491.0000.9750.9710.8170.8570.849
2018년0.2110.2800.9751.0000.9890.8420.8620.846
2019년0.0630.2500.9710.9891.0000.8280.8640.857
2020년0.1650.3730.8170.8420.8281.0000.8650.933
2021년0.1420.2550.8570.8620.8640.8651.0000.882
2022년0.0000.4110.8490.8460.8570.9330.8821.000
2023-12-11T09:50:26.652153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군내외국인 구분
시군1.0000.162
내외국인 구분0.1621.000
2023-12-11T09:50:26.749946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2017년2018년2019년2020년2021년2022년시군내외국인 구분
2017년1.0000.9680.9590.9340.8990.9340.0000.264
2018년0.9681.0000.9810.9360.8930.9410.0920.296
2019년0.9590.9811.0000.9380.8900.9340.0250.265
2020년0.9340.9360.9381.0000.9680.9560.0680.278
2021년0.8990.8930.8900.9681.0000.9630.0610.271
2022년0.9340.9410.9340.9560.9631.0000.0000.312
시군0.0000.0920.0250.0680.0610.0001.0000.162
내외국인 구분0.2640.2960.2650.2780.2710.3120.1621.000

Missing values

2023-12-11T09:50:23.116150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:50:23.247498image/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.
2023-12-11T09:50:23.344589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시도시군관광지내외국인 구분2017년2018년2019년2020년2021년2022년
0경상남도통합창원시3.15아트내국인16132715922116772052014106167145497
1경상남도통합창원시3.15아트외국인017023051
2경상남도통합창원시군항문화탐방내국인12108121441051837202832
3경상남도통합창원시도립미술관내국인1195268389791582155243537078689
4경상남도통합창원시도립미술관외국인981371895867330
5경상남도통합창원시돝섬유원지내국인1241491077821732396794791385106407
6경상남도통합창원시돝섬유원지외국인0489826000
7경상남도통합창원시로봇랜드내국인<NA><NA><NA>173332323608496503
8경상남도통합창원시문신미술관내국인26517231422505188391091821298
9경상남도통합창원시문신미술관외국인738068413054
시도시군관광지내외국인 구분2017년2018년2019년2020년2021년2022년
390경상남도합천군대장경 테마파크내국인<NA><NA><NA>45931128187107002
391경상남도합천군영암사지내국인<NA><NA><NA>287732267012731
392경상남도합천군오도산자연휴양림내국인583623935234635613099886895120
393경상남도합천군오도산자연휴양림외국인040000
394경상남도합천군합천박물관내국인31941299913114373541236622427
395경상남도합천군합천박물관외국인40690040
396경상남도합천군합천영상테마파크내국인547168409665417043178764217690237724
397경상남도합천군합천영상테마파크외국인6410104300
398경상남도합천군황매산군립공원내국인529153292401799246343543541090618855
399경상남도합천군회양 관광지내국인<NA><NA><NA>447544120682172872