Overview

Dataset statistics

Number of variables19
Number of observations505
Missing cells1432
Missing cells (%)14.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.6 KiB
Average record size in memory157.3 B

Variable types

Numeric4
Categorical8
Text6
DateTime1

Dataset

Description전라남도 관광자원 360VR 파일 데이터는 전남관광재단(http://www.namdoskyview.or.kr/openapi) 홈페이지에서 관리되는 전라남도 관광/랜드마크/축제 자원 데이터를, 전남관광재단에서 운영하는 데이터 클라우드 서버 에서 고화질 360VR 을 다운로드 할 수 있는 다운로드 URL 제공
Author재단법인전라남도관광재단
URLhttps://www.data.go.kr/data/15098248/fileData.do

Alerts

홈페이지 is highly overall correlated with No and 10 other fieldsHigh correlation
분류2 is highly overall correlated with 추천 and 2 other fieldsHigh correlation
추천 is highly overall correlated with No and 10 other fieldsHigh correlation
분류1 is highly overall correlated with 추천 and 2 other fieldsHigh correlation
코드 is highly overall correlated with No and 5 other fieldsHigh correlation
주차장 is highly overall correlated with No and 5 other fieldsHigh correlation
전화 is highly overall correlated with No and 10 other fieldsHigh correlation
시군명 is highly overall correlated with No and 5 other fieldsHigh correlation
No is highly overall correlated with 시군명 and 5 other fieldsHigh correlation
대분류코드 is highly overall correlated with 소분류코드 and 3 other fieldsHigh correlation
중분류코드 is highly overall correlated with 소분류코드 and 3 other fieldsHigh correlation
소분류코드 is highly overall correlated with 대분류코드 and 4 other fieldsHigh correlation
분류1 is highly imbalanced (71.7%)Imbalance
대분류 has 7 (1.4%) missing valuesMissing
중분류 has 136 (26.9%) missing valuesMissing
중분류코드 has 67 (13.3%) missing valuesMissing
소분류 has 467 (92.5%) missing valuesMissing
소분류코드 has 475 (94.1%) missing valuesMissing
키워드 has 35 (6.9%) missing valuesMissing
주소 has 243 (48.1%) missing valuesMissing
360VR(URL) has unique valuesUnique
대분류코드 has 74 (14.7%) zerosZeros

Reproduction

Analysis started2023-12-12 13:50:44.902619
Analysis finished2023-12-12 13:50:48.835069
Duration3.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

No
Real number (ℝ)

HIGH CORRELATION 

Distinct500
Distinct (%)99.4%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean270.84095
Minimum1
Maximum528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T22:50:48.899920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27.1
Q1134.5
median278
Q3402.5
95-th percentile502.9
Maximum528
Range527
Interquartile range (IQR)268

Descriptive statistics

Standard deviation153.09592
Coefficient of variation (CV)0.56526134
Kurtosis-1.1958853
Mean270.84095
Median Absolute Deviation (MAD)133
Skewness-0.07703709
Sum136233
Variance23438.361
MonotonicityNot monotonic
2023-12-12T22:50:49.020363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
278 2
 
0.4%
277 2
 
0.4%
279 2
 
0.4%
6 1
 
0.2%
360 1
 
0.2%
373 1
 
0.2%
372 1
 
0.2%
371 1
 
0.2%
370 1
 
0.2%
369 1
 
0.2%
Other values (490) 490
97.0%
(Missing) 2
 
0.4%
ValueCountFrequency (%)
1 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
11 1
0.2%
ValueCountFrequency (%)
528 1
0.2%
527 1
0.2%
526 1
0.2%
525 1
0.2%
524 1
0.2%
523 1
0.2%
522 1
0.2%
521 1
0.2%
520 1
0.2%
519 1
0.2%

시군명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
나주시
87 
신안군
62 
목포시
53 
함평군
50 
무안군
48 
Other values (16)
205 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
나주시 87
17.2%
신안군 62
12.3%
목포시 53
10.5%
함평군 50
9.9%
무안군 48
9.5%
진도군 42
8.3%
해남군 32
 
6.3%
강진군 20
 
4.0%
영암군 19
 
3.8%
순천시 15
 
3.0%
Other values (11) 77
15.2%

Length

2023-12-12T22:50:49.145713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
나주시 87
17.2%
신안군 62
12.3%
목포시 53
10.5%
함평군 50
9.9%
무안군 48
9.5%
진도군 42
8.3%
해남군 32
 
6.3%
강진군 20
 
4.0%
영암군 19
 
3.8%
순천시 15
 
3.0%
Other values (11) 77
15.2%

코드
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Naju_si
87 
Shinan_gun
62 
Mokpo_si
53 
Hampyeong_gun
50 
Muan_gun
48 
Other values (16)
205 

Length

Max length14
Median length12
Mean length9.5188119
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Naju_si 87
17.2%
Shinan_gun 62
12.3%
Mokpo_si 53
10.5%
Hampyeong_gun 50
9.9%
Muan_gun 48
9.5%
Jindo_gun 42
8.3%
Haenam_gun 32
 
6.3%
Gangjin_gun 20
 
4.0%
Yeongam_gun 19
 
3.8%
Suncheon_si 15
 
3.0%
Other values (11) 77
15.2%

Length

2023-12-12T22:50:49.256962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
naju_si 87
17.2%
shinan_gun 62
12.3%
mokpo_si 53
10.5%
hampyeong_gun 50
9.9%
muan_gun 48
9.5%
jindo_gun 42
8.3%
haenam_gun 32
 
6.3%
gangjin_gun 20
 
4.0%
yeongam_gun 19
 
3.8%
suncheon_si 15
 
3.0%
Other values (11) 77
15.2%

대분류
Text

MISSING 

Distinct233
Distinct (%)46.8%
Missing7
Missing (%)1.4%
Memory size4.1 KiB
2023-12-12T22:50:49.487583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length5.3232932
Min length2

Characters and Unicode

Total characters2651
Distinct characters286
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)20.1%

Sample

1st row사의재
2nd row금릉경포대
3rd row금릉경포대
4th row한국민화뮤지엄
5th row한국민화뮤지엄
ValueCountFrequency (%)
근대문화역사거리 14
 
2.6%
신안 12
 
2.2%
신안군 8
 
1.5%
진도군 7
 
1.3%
목포시 7
 
1.3%
함평자연생태공원 7
 
1.3%
축제 7
 
1.3%
동별 6
 
1.1%
진도개테마파크 6
 
1.1%
가거도 5
 
0.9%
Other values (237) 458
85.3%
2023-12-12T22:50:49.873735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 98
 
3.7%
사 76
 
2.9%
원 62
 
2.3%
산 57
 
2.2%
대 47
 
1.8%
군 47
 
1.8%
관 41
 
1.5%
41
 
1.5%
_ 40
 
1.5%
포 40
 
1.5%
Other values (276) 2102
79.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2529
95.4%
Space Separator 41
 
1.5%
Connector Punctuation 40
 
1.5%
Decimal Number 13
 
0.5%
Uppercase Letter 11
 
0.4%
Other Punctuation 7
 
0.3%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 98
 
3.9%
사 76
 
3.0%
원 62
 
2.5%
산 57
 
2.3%
대 47
 
1.9%
군 47
 
1.9%
관 41
 
1.6%
포 40
 
1.6%
문 39
 
1.5%
공 39
 
1.5%
Other values (264) 1983
78.4%
Decimal Number
ValueCountFrequency (%)
5 4
30.8%
1 4
30.8%
2 3
23.1%
0 2
15.4%
Uppercase Letter
ValueCountFrequency (%)
C 9
81.8%
R 1
 
9.1%
P 1
 
9.1%
Space Separator
ValueCountFrequency (%)
41
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2529
95.4%
Common 111
 
4.2%
Latin 11
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 98
 
3.9%
사 76
 
3.0%
원 62
 
2.5%
산 57
 
2.3%
대 47
 
1.9%
군 47
 
1.9%
관 41
 
1.6%
포 40
 
1.6%
문 39
 
1.5%
공 39
 
1.5%
Other values (264) 1983
78.4%
Common
ValueCountFrequency (%)
41
36.9%
_ 40
36.0%
, 7
 
6.3%
) 5
 
4.5%
( 5
 
4.5%
5 4
 
3.6%
1 4
 
3.6%
2 3
 
2.7%
0 2
 
1.8%
Latin
ValueCountFrequency (%)
C 9
81.8%
R 1
 
9.1%
P 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2529
95.4%
ASCII 122
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 98
 
3.9%
사 76
 
3.0%
원 62
 
2.5%
산 57
 
2.3%
대 47
 
1.9%
군 47
 
1.9%
관 41
 
1.6%
포 40
 
1.6%
문 39
 
1.5%
공 39
 
1.5%
Other values (264) 1983
78.4%
ASCII
ValueCountFrequency (%)
41
33.6%
_ 40
32.8%
C 9
 
7.4%
, 7
 
5.7%
) 5
 
4.1%
( 5
 
4.1%
5 4
 
3.3%
1 4
 
3.3%
2 3
 
2.5%
0 2
 
1.6%
Other values (2) 2
 
1.6%

대분류코드
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct75
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.493069
Minimum0
Maximum800
Zeros74
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T22:50:50.051839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median24
Q349
95-th percentile71
Maximum800
Range800
Interquartile range (IQR)43

Descriptive statistics

Standard deviation88.095572
Coefficient of variation (CV)2.2886087
Kurtosis64.329085
Mean38.493069
Median Absolute Deviation (MAD)21
Skewness7.7440426
Sum19439
Variance7760.8298
MonotonicityNot monotonic
2023-12-12T22:50:50.195090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 74
 
14.7%
2 18
 
3.6%
52 16
 
3.2%
1 14
 
2.8%
27 14
 
2.8%
24 12
 
2.4%
23 12
 
2.4%
100 12
 
2.4%
22 11
 
2.2%
10 11
 
2.2%
Other values (65) 311
61.6%
ValueCountFrequency (%)
0 74
14.7%
1 14
 
2.8%
2 18
 
3.6%
3 7
 
1.4%
4 5
 
1.0%
5 6
 
1.2%
6 4
 
0.8%
7 9
 
1.8%
8 11
 
2.2%
9 1
 
0.2%
ValueCountFrequency (%)
800 6
1.2%
200 3
 
0.6%
100 12
2.4%
80 2
 
0.4%
73 2
 
0.4%
71 2
 
0.4%
70 2
 
0.4%
69 3
 
0.6%
68 2
 
0.4%
67 9
1.8%

중분류
Text

MISSING 

Distinct206
Distinct (%)55.8%
Missing136
Missing (%)26.9%
Memory size4.1 KiB
2023-12-12T22:50:50.501434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length4.9457995
Min length2

Characters and Unicode

Total characters1825
Distinct characters280
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)27.4%

Sample

1st row사의재
2nd row월출산 경포대
3rd row월출산 경포대
4th row한국민화뮤지엄
5th row한국민화뮤지엄
ValueCountFrequency (%)
풍경 12
 
3.1%
목포근대문화거리 10
 
2.6%
시군청 6
 
1.5%
보성녹차밭 5
 
1.3%
보성_장도 5
 
1.3%
곤봉수목원 5
 
1.3%
영산강황포돛배,영산포등대 4
 
1.0%
진도아리랑회관 4
 
1.0%
강진만 4
 
1.0%
순천만국가정원 3
 
0.8%
Other values (208) 333
85.2%
2023-12-12T22:50:51.014227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 85
 
4.7%
사 42
 
2.3%
산 41
 
2.2%
리 40
 
2.2%
대 38
 
2.1%
포 36
 
2.0%
해 34
 
1.9%
문 30
 
1.6%
화 29
 
1.6%
목 28
 
1.5%
Other values (270) 1422
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1750
95.9%
Space Separator 22
 
1.2%
Connector Punctuation 21
 
1.2%
Uppercase Letter 17
 
0.9%
Other Punctuation 4
 
0.2%
Decimal Number 4
 
0.2%
Lowercase Letter 3
 
0.2%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 85
 
4.9%
사 42
 
2.4%
산 41
 
2.3%
리 40
 
2.3%
대 38
 
2.2%
포 36
 
2.1%
해 34
 
1.9%
문 30
 
1.7%
화 29
 
1.7%
목 28
 
1.6%
Other values (256) 1347
77.0%
Uppercase Letter
ValueCountFrequency (%)
C 13
76.5%
F 1
 
5.9%
Z 1
 
5.9%
P 1
 
5.9%
R 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
o 2
66.7%
m 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1750
95.9%
Common 55
 
3.0%
Latin 20
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 85
 
4.9%
사 42
 
2.4%
산 41
 
2.3%
리 40
 
2.3%
대 38
 
2.2%
포 36
 
2.1%
해 34
 
1.9%
문 30
 
1.7%
화 29
 
1.7%
목 28
 
1.6%
Other values (256) 1347
77.0%
Common
ValueCountFrequency (%)
22
40.0%
_ 21
38.2%
, 4
 
7.3%
2 2
 
3.6%
1 2
 
3.6%
) 2
 
3.6%
( 2
 
3.6%
Latin
ValueCountFrequency (%)
C 13
65.0%
o 2
 
10.0%
F 1
 
5.0%
Z 1
 
5.0%
m 1
 
5.0%
P 1
 
5.0%
R 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1750
95.9%
ASCII 75
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 85
 
4.9%
사 42
 
2.4%
산 41
 
2.3%
리 40
 
2.3%
대 38
 
2.2%
포 36
 
2.1%
해 34
 
1.9%
문 30
 
1.7%
화 29
 
1.7%
목 28
 
1.6%
Other values (256) 1347
77.0%
ASCII
ValueCountFrequency (%)
22
29.3%
_ 21
28.0%
C 13
17.3%
, 4
 
5.3%
o 2
 
2.7%
2 2
 
2.7%
1 2
 
2.7%
) 2
 
2.7%
( 2
 
2.7%
F 1
 
1.3%
Other values (4) 4
 
5.3%

중분류코드
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct15
Distinct (%)3.4%
Missing67
Missing (%)13.3%
Infinite0
Infinite (%)0.0%
Mean2.4726027
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T22:50:51.167023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile8
Maximum22
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.9007895
Coefficient of variation (CV)1.1731725
Kurtosis19.360911
Mean2.4726027
Median Absolute Deviation (MAD)0
Skewness3.852069
Sum1083
Variance8.4145795
MonotonicityNot monotonic
2023-12-12T22:50:51.282597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 245
48.5%
3 68
 
13.5%
2 53
 
10.5%
4 25
 
5.0%
10 11
 
2.2%
6 10
 
2.0%
7 7
 
1.4%
5 6
 
1.2%
8 4
 
0.8%
9 2
 
0.4%
Other values (5) 7
 
1.4%
(Missing) 67
 
13.3%
ValueCountFrequency (%)
1 245
48.5%
2 53
 
10.5%
3 68
 
13.5%
4 25
 
5.0%
5 6
 
1.2%
6 10
 
2.0%
7 7
 
1.4%
8 4
 
0.8%
9 2
 
0.4%
10 11
 
2.2%
ValueCountFrequency (%)
22 2
 
0.4%
21 2
 
0.4%
20 1
 
0.2%
12 1
 
0.2%
11 1
 
0.2%
10 11
2.2%
9 2
 
0.4%
8 4
 
0.8%
7 7
1.4%
6 10
2.0%

소분류
Text

MISSING 

Distinct31
Distinct (%)81.6%
Missing467
Missing (%)92.5%
Memory size4.1 KiB
2023-12-12T22:50:51.484151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length4.3421053
Min length2

Characters and Unicode

Total characters165
Distinct characters79
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)68.4%

Sample

1st row곡성읍
2nd row광양시청
3rd row구레군
4th row목포시립도서관
5th row목포빛과소금교회
ValueCountFrequency (%)
특정도서 3
 
7.0%
삼학도 3
 
7.0%
군도 2
 
4.7%
무안군 2
 
4.7%
온금동 2
 
4.7%
구레군 1
 
2.3%
튤립축제 1
 
2.3%
해남군청 1
 
2.3%
화순군청 1
 
2.3%
해변 1
 
2.3%
Other values (26) 26
60.5%
2023-12-12T22:50:51.832682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 10
 
6.1%
군 10
 
6.1%
포 6
 
3.6%
시 6
 
3.6%
목 6
 
3.6%
청 6
 
3.6%
서 5
 
3.0%
5
 
3.0%
동 5
 
3.0%
해 3
 
1.8%
Other values (69) 103
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158
95.8%
Space Separator 5
 
3.0%
Close Punctuation 1
 
0.6%
Open Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10
 
6.3%
군 10
 
6.3%
포 6
 
3.8%
시 6
 
3.8%
목 6
 
3.8%
청 6
 
3.8%
서 5
 
3.2%
동 5
 
3.2%
해 3
 
1.9%
정 3
 
1.9%
Other values (66) 98
62.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158
95.8%
Common 7
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10
 
6.3%
군 10
 
6.3%
포 6
 
3.8%
시 6
 
3.8%
목 6
 
3.8%
청 6
 
3.8%
서 5
 
3.2%
동 5
 
3.2%
해 3
 
1.9%
정 3
 
1.9%
Other values (66) 98
62.0%
Common
ValueCountFrequency (%)
5
71.4%
) 1
 
14.3%
( 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158
95.8%
ASCII 7
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 10
 
6.3%
군 10
 
6.3%
포 6
 
3.8%
시 6
 
3.8%
목 6
 
3.8%
청 6
 
3.8%
서 5
 
3.2%
동 5
 
3.2%
해 3
 
1.9%
정 3
 
1.9%
Other values (66) 98
62.0%
ASCII
ValueCountFrequency (%)
5
71.4%
) 1
 
14.3%
( 1
 
14.3%

소분류코드
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)33.3%
Missing475
Missing (%)94.1%
Infinite0
Infinite (%)0.0%
Mean4.1666667
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T22:50:51.947738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q36
95-th percentile9.55
Maximum23
Range22
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.6467143
Coefficient of variation (CV)1.1152114
Kurtosis8.5063008
Mean4.1666667
Median Absolute Deviation (MAD)2
Skewness2.5400163
Sum125
Variance21.591954
MonotonicityNot monotonic
2023-12-12T22:50:52.047481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 12
 
2.4%
3 6
 
1.2%
9 3
 
0.6%
6 2
 
0.4%
2 2
 
0.4%
10 1
 
0.2%
8 1
 
0.2%
4 1
 
0.2%
7 1
 
0.2%
23 1
 
0.2%
(Missing) 475
94.1%
ValueCountFrequency (%)
1 12
2.4%
2 2
 
0.4%
3 6
1.2%
4 1
 
0.2%
6 2
 
0.4%
7 1
 
0.2%
8 1
 
0.2%
9 3
 
0.6%
10 1
 
0.2%
23 1
 
0.2%
ValueCountFrequency (%)
23 1
 
0.2%
10 1
 
0.2%
9 3
 
0.6%
8 1
 
0.2%
7 1
 
0.2%
6 2
 
0.4%
4 1
 
0.2%
3 6
1.2%
2 2
 
0.4%
1 12
2.4%

촬영일자
Date

Distinct167
Distinct (%)33.1%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Minimum2010-10-28 00:00:00
Maximum2021-12-20 00:00:00
2023-12-12T22:50:52.173583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:52.588411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

분류1
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
360vr
421 
360VR
78 
361vr
 
3
362vr
 
1
363vr
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st row360vr
2nd row360vr
3rd row360vr
4th row360vr
5th row360vr

Common Values

ValueCountFrequency (%)
360vr 421
83.4%
360VR 78
 
15.4%
361vr 3
 
0.6%
362vr 1
 
0.2%
363vr 1
 
0.2%
386vr 1
 
0.2%

Length

2023-12-12T22:50:52.734758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:52.840576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
360vr 499
98.8%
361vr 3
 
0.6%
362vr 1
 
0.2%
363vr 1
 
0.2%
386vr 1
 
0.2%

분류2
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
관광지
342 
랜드마크
84 
축제
51 
기타
 
24
<NA>
 
4

Length

Max length4
Median length3
Mean length3.0257426
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관광지
2nd row관광지
3rd row관광지
4th row랜드마크
5th row랜드마크

Common Values

ValueCountFrequency (%)
관광지 342
67.7%
랜드마크 84
 
16.6%
축제 51
 
10.1%
기타 24
 
4.8%
<NA> 4
 
0.8%

Length

2023-12-12T22:50:53.018421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:53.147173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광지 342
67.7%
랜드마크 84
 
16.6%
축제 51
 
10.1%
기타 24
 
4.8%
na 4
 
0.8%

키워드
Text

MISSING 

Distinct277
Distinct (%)58.9%
Missing35
Missing (%)6.9%
Memory size4.1 KiB
2023-12-12T22:50:53.368393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length10.480851
Min length3

Characters and Unicode

Total characters4926
Distinct characters304
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)34.5%

Sample

1st row강진군,사의재
2nd row강진군,금릉경포대
3rd row강진군,금릉경포대
4th row강진군,한국민화뮤지엄
5th row강진군,한국민화뮤지엄
ValueCountFrequency (%)
목포시,근대문화역사거리 13
 
2.6%
함평군,자연생태공원 7
 
1.4%
진도군,진도개테마파크 6
 
1.2%
보성군,장도,전라남도_가보고싶은섬 5
 
1.0%
보성군,보성녹차밭,전남으뜸경관10선 5
 
1.0%
영암군,왕인박사유적지 5
 
1.0%
순천시,순천만국가정원,전남으뜸경관10선 4
 
0.8%
신안군,퍼플교,퍼플섬 4
 
0.8%
함평군,엑스포공원 4
 
0.8%
나주시,영산강황포돛배,영산포등대 4
 
0.8%
Other values (283) 440
88.5%
2023-12-12T22:50:53.816922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 620
 
12.6%
군 300
 
6.1%
도 190
 
3.9%
시 170
 
3.5%
주 112
 
2.3%
나 106
 
2.2%
진 99
 
2.0%
안 97
 
2.0%
남 87
 
1.8%
포 83
 
1.7%
Other values (294) 3062
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4190
85.1%
Other Punctuation 620
 
12.6%
Decimal Number 66
 
1.3%
Space Separator 27
 
0.5%
Uppercase Letter 14
 
0.3%
Connector Punctuation 7
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 300
 
7.2%
도 190
 
4.5%
시 170
 
4.1%
주 112
 
2.7%
나 106
 
2.5%
진 99
 
2.4%
안 97
 
2.3%
남 87
 
2.1%
포 83
 
2.0%
사 66
 
1.6%
Other values (278) 2880
68.7%
Decimal Number
ValueCountFrequency (%)
1 30
45.5%
0 23
34.8%
5 5
 
7.6%
2 5
 
7.6%
3 1
 
1.5%
4 1
 
1.5%
8 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
C 11
78.6%
F 1
 
7.1%
R 1
 
7.1%
P 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 620
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4190
85.1%
Common 722
 
14.7%
Latin 14
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 300
 
7.2%
도 190
 
4.5%
시 170
 
4.1%
주 112
 
2.7%
나 106
 
2.5%
진 99
 
2.4%
안 97
 
2.3%
남 87
 
2.1%
포 83
 
2.0%
사 66
 
1.6%
Other values (278) 2880
68.7%
Common
ValueCountFrequency (%)
, 620
85.9%
1 30
 
4.2%
27
 
3.7%
0 23
 
3.2%
_ 7
 
1.0%
5 5
 
0.7%
2 5
 
0.7%
) 1
 
0.1%
( 1
 
0.1%
3 1
 
0.1%
Other values (2) 2
 
0.3%
Latin
ValueCountFrequency (%)
C 11
78.6%
F 1
 
7.1%
R 1
 
7.1%
P 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4190
85.1%
ASCII 736
 
14.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 620
84.2%
1 30
 
4.1%
27
 
3.7%
0 23
 
3.1%
C 11
 
1.5%
_ 7
 
1.0%
5 5
 
0.7%
2 5
 
0.7%
) 1
 
0.1%
( 1
 
0.1%
Other values (6) 6
 
0.8%
Hangul
ValueCountFrequency (%)
군 300
 
7.2%
도 190
 
4.5%
시 170
 
4.1%
주 112
 
2.7%
나 106
 
2.5%
진 99
 
2.4%
안 97
 
2.3%
남 87
 
2.1%
포 83
 
2.0%
사 66
 
1.6%
Other values (278) 2880
68.7%

360VR(URL)
Text

UNIQUE 

Distinct505
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T22:50:54.112081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length90
Median length86
Mean length73.118812
Min length57

Characters and Unicode

Total characters36925
Distinct characters53
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique505 ?
Unique (%)100.0%

Sample

1st rowhttp://open.namdogeo.com:9090/Gangjin_gun/21/21_01_20210806/360VR/360VR1.JPG
2nd rowhttp://open.namdogeo.com:9090/Gangjin_gun/20/20_01_20210806/360VR/360VR2.JPG
3rd rowhttp://open.namdogeo.com:9090/Gangjin_gun/20/20_01_20210806/360VR/360VR1.JPG
4th rowhttp://open.namdogeo.com:9090/Gangjin_gun/19/19_01_20210629/360VR/360VR2.JPG
5th rowhttp://open.namdogeo.com:9090/Gangjin_gun/19/19_01_20210629/360VR/360VR1.JPG
ValueCountFrequency (%)
http://open.namdogeo.com:9090/gangjin_gun/21/21_01_20210806/360vr/360vr1.jpg 1
 
0.2%
http://open.namdogeo.com:9090\meta\sky360\jindo\360vr2.jpg 1
 
0.2%
http://open.namdogeo.com:9090\meta\sky360\yeongam\360vr2.jpg 1
 
0.2%
http://open.namdogeo.com:9090\meta\sky360\yeongam\360vr1.jpg 1
 
0.2%
http://open.namdogeo.com:9090\jangseong-gun\24\24_02_20201030\360vr\360vr1.jpg 1
 
0.2%
http://open.namdogeo.com:9090\meta\sky360\jindo\360vr8.jpg 1
 
0.2%
http://open.namdogeo.com:9090\yeosu_si\49\49_02_20210930\360vr\360vr1.jpg 1
 
0.2%
http://open.namdogeo.com:9090\wando_gun\37\37_01_20211204\360vr\360vr1.jpg 1
 
0.2%
http://open.namdogeo.com:9090\meta\sky360\wando\360vr2.jpg 1
 
0.2%
http://open.namdogeo.com:9090\meta\sky360\wando\360vr1.jpg 1
 
0.2%
Other values (496) 496
98.0%
2023-12-12T22:50:54.547609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3813
 
10.3%
/ 2442
 
6.6%
o 2326
 
6.3%
n 1780
 
4.8%
2 1594
 
4.3%
1 1590
 
4.3%
. 1514
 
4.1%
_ 1443
 
3.9%
3 1358
 
3.7%
6 1232
 
3.3%
Other values (43) 17833
48.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13720
37.2%
Decimal Number 11892
32.2%
Other Punctuation 6054
16.4%
Uppercase Letter 3805
 
10.3%
Connector Punctuation 1443
 
3.9%
Dash Punctuation 7
 
< 0.1%
Other Letter 3
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 2326
17.0%
n 1780
13.0%
e 1230
9.0%
p 1165
8.5%
m 1120
8.2%
t 1048
7.6%
g 1017
7.4%
a 940
6.9%
h 594
 
4.3%
d 557
 
4.1%
Other values (10) 1943
14.2%
Uppercase Letter
ValueCountFrequency (%)
R 970
25.5%
V 970
25.5%
G 502
13.2%
J 490
12.9%
P 452
11.9%
M 134
 
3.5%
N 87
 
2.3%
H 86
 
2.3%
S 61
 
1.6%
Y 28
 
0.7%
Other values (3) 25
 
0.7%
Decimal Number
ValueCountFrequency (%)
0 3813
32.1%
2 1594
13.4%
1 1590
13.4%
3 1358
 
11.4%
6 1232
 
10.4%
9 1194
 
10.0%
4 295
 
2.5%
7 284
 
2.4%
8 281
 
2.4%
5 251
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 2442
40.3%
. 1514
25.0%
\ 1088
18.0%
: 1010
16.7%
Other Letter
ValueCountFrequency (%)
새 1
33.3%
폴 1
33.3%
더 1
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 1443
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19397
52.5%
Latin 17525
47.5%
Hangul 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 2326
13.3%
n 1780
 
10.2%
e 1230
 
7.0%
p 1165
 
6.6%
m 1120
 
6.4%
t 1048
 
6.0%
g 1017
 
5.8%
R 970
 
5.5%
V 970
 
5.5%
a 940
 
5.4%
Other values (23) 4959
28.3%
Common
ValueCountFrequency (%)
0 3813
19.7%
/ 2442
12.6%
2 1594
8.2%
1 1590
8.2%
. 1514
 
7.8%
_ 1443
 
7.4%
3 1358
 
7.0%
6 1232
 
6.4%
9 1194
 
6.2%
\ 1088
 
5.6%
Other values (7) 2129
11.0%
Hangul
ValueCountFrequency (%)
새 1
33.3%
폴 1
33.3%
더 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36922
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3813
 
10.3%
/ 2442
 
6.6%
o 2326
 
6.3%
n 1780
 
4.8%
2 1594
 
4.3%
1 1590
 
4.3%
. 1514
 
4.1%
_ 1443
 
3.9%
3 1358
 
3.7%
6 1232
 
3.3%
Other values (40) 17830
48.3%
Hangul
ValueCountFrequency (%)
새 1
33.3%
폴 1
33.3%
더 1
33.3%

추천
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
0
335 
<NA>
170 

Length

Max length4
Median length1
Mean length2.009901
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 335
66.3%
<NA> 170
33.7%

Length

2023-12-12T22:50:54.695342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:54.807450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 335
66.3%
na 170
33.7%

주소
Text

MISSING 

Distinct143
Distinct (%)54.6%
Missing243
Missing (%)48.1%
Memory size4.1 KiB
2023-12-12T22:50:55.114996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length18.961832
Min length8

Characters and Unicode

Total characters4968
Distinct characters189
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)25.2%

Sample

1st row전라남도 강진군 강진읍 사의재길 27
2nd row전라남도 강진군 성전면 월남리 1229-1
3rd row전라남도 강진군 성전면 월남리 1229-1
4th row전라남도 강진군 대구면 청자촌길 61-5
5th row전라남도 강진군 대구면 청자촌길 61-5
ValueCountFrequency (%)
전라남도 260
 
22.1%
나주시 82
 
7.0%
해남군 28
 
2.4%
무안군 21
 
1.8%
목포시 21
 
1.8%
신안군 19
 
1.6%
강진군 14
 
1.2%
순천시 13
 
1.1%
영산로 13
 
1.1%
19번길6 13
 
1.1%
Other values (306) 695
58.9%
2023-12-12T22:50:55.577504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
917
18.5%
도 318
 
6.4%
남 314
 
6.3%
전 265
 
5.3%
라 260
 
5.2%
1 153
 
3.1%
군 143
 
2.9%
시 136
 
2.7%
길 124
 
2.5%
면 117
 
2.4%
Other values (179) 2221
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3290
66.2%
Space Separator 917
 
18.5%
Decimal Number 691
 
13.9%
Dash Punctuation 66
 
1.3%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 318
 
9.7%
남 314
 
9.5%
전 265
 
8.1%
라 260
 
7.9%
군 143
 
4.3%
시 136
 
4.1%
길 124
 
3.8%
면 117
 
3.6%
로 90
 
2.7%
주 87
 
2.6%
Other values (165) 1436
43.6%
Decimal Number
ValueCountFrequency (%)
1 153
22.1%
2 94
13.6%
3 90
13.0%
4 64
9.3%
6 55
 
8.0%
0 53
 
7.7%
7 51
 
7.4%
8 47
 
6.8%
9 45
 
6.5%
5 39
 
5.6%
Space Separator
ValueCountFrequency (%)
917
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3290
66.2%
Common 1678
33.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 318
 
9.7%
남 314
 
9.5%
전 265
 
8.1%
라 260
 
7.9%
군 143
 
4.3%
시 136
 
4.1%
길 124
 
3.8%
면 117
 
3.6%
로 90
 
2.7%
주 87
 
2.6%
Other values (165) 1436
43.6%
Common
ValueCountFrequency (%)
917
54.6%
1 153
 
9.1%
2 94
 
5.6%
3 90
 
5.4%
- 66
 
3.9%
4 64
 
3.8%
6 55
 
3.3%
0 53
 
3.2%
7 51
 
3.0%
8 47
 
2.8%
Other values (4) 88
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3290
66.2%
ASCII 1678
33.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
917
54.6%
1 153
 
9.1%
2 94
 
5.6%
3 90
 
5.4%
- 66
 
3.9%
4 64
 
3.8%
6 55
 
3.3%
0 53
 
3.2%
7 51
 
3.0%
8 47
 
2.8%
Other values (4) 88
 
5.2%
Hangul
ValueCountFrequency (%)
도 318
 
9.7%
남 314
 
9.5%
전 265
 
8.1%
라 260
 
7.9%
군 143
 
4.3%
시 136
 
4.1%
길 124
 
3.8%
면 117
 
3.6%
로 90
 
2.7%
주 87
 
2.6%
Other values (165) 1436
43.6%

주차장
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
O
185 
X
172 
<NA>
148 

Length

Max length4
Median length1
Mean length1.8792079
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
O 185
36.6%
X 172
34.1%
<NA> 148
29.3%

Length

2023-12-12T22:50:55.708146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:55.810526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 185
36.6%
x 172
34.1%
na 148
29.3%

전화
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
X
357 
<NA>
148 

Length

Max length4
Median length1
Mean length1.8792079
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 357
70.7%
<NA> 148
29.3%

Length

2023-12-12T22:50:55.913953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:56.016162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 357
70.7%
na 148
29.3%

홈페이지
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
X
357 
<NA>
148 

Length

Max length4
Median length1
Mean length1.8792079
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
X 357
70.7%
<NA> 148
29.3%

Length

2023-12-12T22:50:56.113128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:50:56.214747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
x 357
70.7%
na 148
29.3%

Interactions

2023-12-12T22:50:47.834465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:46.675652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.060390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.482199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.910529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:46.797905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.144949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.576597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.990667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:46.896770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.248815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.684572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:48.058517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:46.984825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.371929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:50:47.759129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:50:56.283681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No시군명코드대분류코드중분류코드소분류소분류코드분류1분류2주차장
No1.0000.8960.8960.3670.4461.0000.6120.6300.6940.701
시군명0.8961.0001.0000.3930.5660.9900.0000.5630.5130.699
코드0.8961.0001.0000.3930.5660.9900.0000.5630.5130.699
대분류코드0.3670.3930.3931.0000.3351.0000.9140.0000.7820.212
중분류코드0.4460.5660.5660.3351.0001.0000.7550.0600.2280.174
소분류1.0000.9900.9901.0001.0001.0001.000NaN1.0001.000
소분류코드0.6120.0000.0000.9140.7551.0001.0000.0000.2770.740
분류10.6300.5630.5630.0000.060NaN0.0001.0000.1430.000
분류20.6940.5130.5130.7820.2281.0000.2770.1431.0000.133
주차장0.7010.6990.6990.2120.1741.0000.7400.0000.1331.000
2023-12-12T22:50:56.411260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
홈페이지분류2추천분류1코드주차장전화시군명
홈페이지1.0001.0001.0001.0001.0001.0001.0001.000
분류21.0001.0001.0000.0920.2960.0881.0000.296
추천1.0001.0001.0001.0001.0001.0001.0001.000
분류11.0000.0921.0001.0000.2880.0001.0000.288
코드1.0000.2961.0000.2881.0000.6101.0001.000
주차장1.0000.0881.0000.0000.6101.0001.0000.610
전화1.0001.0001.0001.0001.0001.0001.0001.000
시군명1.0000.2961.0000.2881.0000.6101.0001.000
2023-12-12T22:50:56.519238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
No대분류코드중분류코드소분류코드시군명코드분류1분류2추천주차장전화홈페이지
No1.000-0.1910.133-0.3220.6030.6030.3940.4931.0000.5301.0001.000
대분류코드-0.1911.000-0.0870.6030.2000.2000.0000.4341.0000.1461.0001.000
중분류코드0.133-0.0871.0000.6830.2440.2440.0380.1571.0000.1841.0001.000
소분류코드-0.3220.6030.6831.0000.0000.0000.0000.1561.0000.4961.0001.000
시군명0.6030.2000.2440.0001.0001.0000.2880.2961.0000.6101.0001.000
코드0.6030.2000.2440.0001.0001.0000.2880.2961.0000.6101.0001.000
분류10.3940.0000.0380.0000.2880.2881.0000.0921.0000.0001.0001.000
분류20.4930.4340.1570.1560.2960.2960.0921.0001.0000.0881.0001.000
추천1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주차장0.5300.1460.1840.4960.6100.6100.0000.0881.0001.0001.0001.000
전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
홈페이지1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T22:50:48.170734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:50:48.446801image/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.
2023-12-12T22:50:48.704181image/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

No시군명코드대분류대분류코드중분류중분류코드소분류소분류코드촬영일자분류1분류2키워드360VR(URL)추천주소주차장전화홈페이지
01강진군Gangjin_gun사의재21사의재1<NA><NA>2021-08-06360vr관광지강진군,사의재http://open.namdogeo.com:9090/Gangjin_gun/21/21_01_20210806/360VR/360VR1.JPG0전라남도 강진군 강진읍 사의재길 27OXX
13강진군Gangjin_gun금릉경포대20월출산 경포대1<NA><NA>2021-08-06360vr관광지강진군,금릉경포대http://open.namdogeo.com:9090/Gangjin_gun/20/20_01_20210806/360VR/360VR2.JPG0전라남도 강진군 성전면 월남리 1229-1OXX
24강진군Gangjin_gun금릉경포대20월출산 경포대1<NA><NA>2021-08-06360vr관광지강진군,금릉경포대http://open.namdogeo.com:9090/Gangjin_gun/20/20_01_20210806/360VR/360VR1.JPG0전라남도 강진군 성전면 월남리 1229-1OXX
35강진군Gangjin_gun한국민화뮤지엄19한국민화뮤지엄1<NA><NA>2021-06-29360vr랜드마크강진군,한국민화뮤지엄http://open.namdogeo.com:9090/Gangjin_gun/19/19_01_20210629/360VR/360VR2.JPG0전라남도 강진군 대구면 청자촌길 61-5OXX
46강진군Gangjin_gun한국민화뮤지엄19한국민화뮤지엄1<NA><NA>2021-06-29360vr랜드마크강진군,한국민화뮤지엄http://open.namdogeo.com:9090/Gangjin_gun/19/19_01_20210629/360VR/360VR1.JPG0전라남도 강진군 대구면 청자촌길 61-5OXX
57강진군Gangjin_gun강진만생태공원13강진만3<NA><NA>2018-09-28360vr관광지강진군,강진만생태공원,강진만http://open.namdogeo.com:9090/Gangjin_gun/13/13_03_20180928/360VR/360VR1.JPG0전라남도 강진군 강진읍 남포리 510OXX
68강진군Gangjin_gun고려청자박물관4고려청자박물관1<NA><NA>2021-06-29360vr랜드마크강진군, 고려청자박물관http://open.namdogeo.com:9090/Gangjin_gun/4/4_01_20210629/360VR/360VR2.jpg0전라남도 강진군 대구면 청자촌길 33OXX
79강진군Gangjin_gun고려청자박물관4고려청자박물관1<NA><NA>2021-06-29360vr랜드마크강진군, 고려청자박물관http://open.namdogeo.com:9090/Gangjin_gun/4/4_01_20210629/360VR/360VR1.jpg0전라남도 강진군 대구면 청자촌길 33OXX
810강진군Gangjin_gun가우도1가우도4<NA><NA>2021-08-06360vr관광지강진군,가우도http://open.namdogeo.com:9090/Gangjin_gun/1/1_04_20210806/360VR/360VR1.jpg0전라남도 강진군 도암면 월곶로 473XXX
911강진군Gangjin_gun가우도1가우도 청자타워 출렁다리3<NA><NA>2021-05-19360vr관광지강진군,가우도http://open.namdogeo.com:9090/Gangjin_gun/1/1_03_20210519/360VR/360VR2.jpg0전라남도 강진군 도암면 월곶로 473XXX
No시군명코드대분류대분류코드중분류중분류코드소분류소분류코드촬영일자분류1분류2키워드360VR(URL)추천주소주차장전화홈페이지
495521영암군Yeongam_gun왕인박사유적지8<NA>3<NA><NA>2021-12-20360vr관광지영암군,왕인박사유적지http://open.namdogeo.com:9090\Yeongam_gun\8\8_03_20211220\360VR\360VR2.JPG<NA><NA><NA><NA><NA>
496522영암군Yeongam_gun왕인박사유적지8<NA>3<NA><NA>2021-12-20360vr관광지영암군,왕인박사유적지http://open.namdogeo.com:9090\Yeongam_gun\8\8_03_20211220\360VR\360VR3.JPG<NA><NA><NA><NA><NA>
497523영암군Yeongam_gun왕인박사유적지8<NA>3<NA><NA>2021-12-20360vr관광지영암군,왕인박사유적지http://open.namdogeo.com:9090\Yeongam_gun\8\8_03_20211220\360VR\360VR4.JPG<NA><NA><NA><NA><NA>
498524영암군Yeongam_gun무영대교14<NA>3<NA><NA>2021-12-20360vr관광지영암군,무영대교http://open.namdogeo.com:9090\Yeongam_gun\14\14_03_20211220\360VR\360VR1.JPG<NA><NA><NA><NA><NA>
499525영암군Yeongam_gun무영대교14<NA>3<NA><NA>2021-12-20360vr관광지영암군,무영대교http://open.namdogeo.com:9090\Yeongam_gun\14\14_03_20211220\360VR\360VR2.JPG<NA><NA><NA><NA><NA>
500526무안군Muan_gun남악수변공원7<NA>3<NA><NA>2021-12-20360vr관광지무안군,남악,수변공원http://open.namdogeo.com:9090\Muan_gun\7\7_03_20211220\360VR\360VR1.JPG<NA><NA><NA><NA><NA>
501527무안군Muan_gun남악수변공원7<NA>3<NA><NA>2021-12-20360vr관광지무안군,남악,수변공원http://open.namdogeo.com:9090\Muan_gun\7\7_03_20211220\360VR\360VR2.JPG<NA><NA><NA><NA><NA>
502528무안군Muan_gun남악수변공원7<NA>3<NA><NA>2021-12-20360vr관광지무안군,남악,수변공원http://open.namdogeo.com:9090\Muan_gun\7\7_03_20211220\360VR\360VR3.JPG<NA><NA><NA><NA><NA>
503<NA>영암군Yeongam_gun왕인박사유적지8왕인박사유적지2<NA><NA>2021-08-05360vr관광지영암군,왕인박사유적지http://open.namdogeo.com:9090/Yeongam_gun/8/8_02_20210805/360VR/360VR1.JPG0전라남도 영암군 군서면 왕인로 440OXX
504<NA>무안군Muan_gun홀통해수욕장8홀통해수욕장2<NA><NA>2021-06-27360vr관광지무안군, 홀통해수욕장http://open.namdogeo.com:9090/Muan_gun/8/8_02_20210627/360VR/360VR2.JPG0전라남도 무안군 현경면 홀통길 198-1OXX