Overview

Dataset statistics

Number of variables7
Number of observations87
Missing cells99
Missing cells (%)16.3%
Duplicate rows1
Duplicate rows (%)1.1%
Total size in memory4.9 KiB
Average record size in memory57.5 B

Variable types

Text5
Categorical2

Dataset

Description지역축제관광객현황공개자료2015
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202317

Alerts

Dataset has 1 (1.1%) duplicate rowsDuplicates
Unnamed: 6 is highly imbalanced (57.8%)Imbalance
2015년 지역축제 관광객 현황 has 47 (54.0%) missing valuesMissing
Unnamed: 1 has 12 (13.8%) missing valuesMissing
Unnamed: 2 has 15 (17.2%) missing valuesMissing
Unnamed: 3 has 13 (14.9%) missing valuesMissing
Unnamed: 5 has 12 (13.8%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:25:20.238842
Analysis finished2024-03-14 02:25:20.958766
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2015년 지역축제 관광객 현황
Text

MISSING 

Distinct32
Distinct (%)80.0%
Missing47
Missing (%)54.0%
Memory size828.0 B
2024-03-14T11:25:21.070836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.55
Min length1

Characters and Unicode

Total characters142
Distinct characters56
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)65.0%

Sample

1st row□ 연도별 현황
2nd row구분
3rd row2015
4th row2014
5th row2013
ValueCountFrequency (%)
2 4
 
8.2%
4 3
 
6.1%
3 3
 
6.1%
1 2
 
4.1%
구분 2
 
4.1%
현황 2
 
4.1%
□ 2
 
4.1%
2
 
4.1%
무주군 1
 
2.0%
진안군 1
 
2.0%
Other values (27) 27
55.1%
2024-03-14T11:25:21.328080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 15
 
10.6%
) 15
 
10.6%
10
 
7.0%
군 10
 
7.0%
2 7
 
4.9%
시 7
 
4.9%
1 6
 
4.2%
3 4
 
2.8%
4 4
 
2.8%
주 3
 
2.1%
Other values (46) 61
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68
47.9%
Decimal Number 28
19.7%
Open Punctuation 15
 
10.6%
Close Punctuation 15
 
10.6%
Space Separator 10
 
7.0%
Other Punctuation 4
 
2.8%
Other Symbol 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 10
 
14.7%
시 7
 
10.3%
주 3
 
4.4%
안 2
 
2.9%
구 2
 
2.9%
별 2
 
2.9%
현 2
 
2.9%
창 2
 
2.9%
황 2
 
2.9%
제 2
 
2.9%
Other values (31) 34
50.0%
Decimal Number
ValueCountFrequency (%)
2 7
25.0%
1 6
21.4%
3 4
14.3%
4 4
14.3%
0 3
10.7%
5 2
 
7.1%
7 1
 
3.6%
9 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
' 2
50.0%
? 1
25.0%
* 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Symbol
ValueCountFrequency (%)
□ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
52.1%
Hangul 68
47.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 10
 
14.7%
시 7
 
10.3%
주 3
 
4.4%
안 2
 
2.9%
구 2
 
2.9%
별 2
 
2.9%
현 2
 
2.9%
창 2
 
2.9%
황 2
 
2.9%
제 2
 
2.9%
Other values (31) 34
50.0%
Common
ValueCountFrequency (%)
( 15
20.3%
) 15
20.3%
10
13.5%
2 7
9.5%
1 6
 
8.1%
3 4
 
5.4%
4 4
 
5.4%
0 3
 
4.1%
□ 2
 
2.7%
' 2
 
2.7%
Other values (5) 6
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
50.7%
Hangul 68
47.9%
Geometric Shapes 2
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 15
20.8%
) 15
20.8%
10
13.9%
2 7
9.7%
1 6
 
8.3%
3 4
 
5.6%
4 4
 
5.6%
0 3
 
4.2%
' 2
 
2.8%
5 2
 
2.8%
Other values (4) 4
 
5.6%
Hangul
ValueCountFrequency (%)
군 10
 
14.7%
시 7
 
10.3%
주 3
 
4.4%
안 2
 
2.9%
구 2
 
2.9%
별 2
 
2.9%
현 2
 
2.9%
창 2
 
2.9%
황 2
 
2.9%
제 2
 
2.9%
Other values (31) 34
50.0%
Geometric Shapes
ValueCountFrequency (%)
□ 2
100.0%

Unnamed: 1
Text

MISSING 

Distinct61
Distinct (%)81.3%
Missing12
Missing (%)13.8%
Memory size828.0 B
2024-03-14T11:25:21.528547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.9333333
Min length3

Characters and Unicode

Total characters445
Distinct characters160
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)80.0%

Sample

1st row축제 수
2nd row56개
3rd row47개
4th row55개
5th row축제개요
ValueCountFrequency (%)
소 15
 
16.3%
계 15
 
16.3%
부안마실축제 1
 
1.1%
필봉마을굿축제 1
 
1.1%
하소백련축제 1
 
1.1%
삼례딸기축제 1
 
1.1%
와일드푸드축제 1
 
1.1%
홍삼&마이문화제 1
 
1.1%
마을축제 1
 
1.1%
운장산고로쇠축제 1
 
1.1%
Other values (54) 54
58.7%
2024-03-14T11:25:21.983031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 55
 
12.4%
축 38
 
8.5%
소 20
 
4.5%
17
 
3.8%
계 17
 
3.8%
산 9
 
2.0%
화 8
 
1.8%
장 6
 
1.3%
봉 6
 
1.3%
사 6
 
1.3%
Other values (150) 263
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 417
93.7%
Space Separator 17
 
3.8%
Decimal Number 8
 
1.8%
Other Punctuation 2
 
0.4%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 55
 
13.2%
축 38
 
9.1%
소 20
 
4.8%
계 17
 
4.1%
산 9
 
2.2%
화 8
 
1.9%
장 6
 
1.4%
봉 6
 
1.4%
사 6
 
1.4%
개 6
 
1.4%
Other values (142) 246
59.0%
Decimal Number
ValueCountFrequency (%)
5 4
50.0%
6 1
 
12.5%
4 1
 
12.5%
7 1
 
12.5%
2 1
 
12.5%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 417
93.7%
Common 27
 
6.1%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 55
 
13.2%
축 38
 
9.1%
소 20
 
4.8%
계 17
 
4.1%
산 9
 
2.2%
화 8
 
1.9%
장 6
 
1.4%
봉 6
 
1.4%
사 6
 
1.4%
개 6
 
1.4%
Other values (142) 246
59.0%
Common
ValueCountFrequency (%)
17
63.0%
5 4
 
14.8%
& 2
 
7.4%
6 1
 
3.7%
4 1
 
3.7%
7 1
 
3.7%
2 1
 
3.7%
Latin
ValueCountFrequency (%)
N 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 417
93.7%
ASCII 28
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 55
 
13.2%
축 38
 
9.1%
소 20
 
4.8%
계 17
 
4.1%
산 9
 
2.2%
화 8
 
1.9%
장 6
 
1.4%
봉 6
 
1.4%
사 6
 
1.4%
개 6
 
1.4%
Other values (142) 246
59.0%
ASCII
ValueCountFrequency (%)
17
60.7%
5 4
 
14.3%
& 2
 
7.1%
N 1
 
3.6%
6 1
 
3.6%
4 1
 
3.6%
7 1
 
3.6%
2 1
 
3.6%

Unnamed: 2
Text

MISSING 

Distinct56
Distinct (%)77.8%
Missing15
Missing (%)17.2%
Memory size828.0 B
2024-03-14T11:25:22.149984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.2222222
Min length1

Characters and Unicode

Total characters448
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)72.2%

Sample

1st row방문객 수
2nd row계
3rd row6,184,966
4th row6,190,450
5th row9,076,160
ValueCountFrequency (%)
14
 
17.9%
8.14~16 2
 
2.6%
10.7~11 2
 
2.6%
8 2
 
2.6%
10.30~11.1 2
 
2.6%
7 2
 
2.6%
8.29~30 1
 
1.3%
10.8~10 1
 
1.3%
7.17~19 1
 
1.3%
5.1~5.3 1
 
1.3%
Other values (50) 50
64.1%
2024-03-14T11:25:22.447042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 84
18.8%
. 74
16.5%
~ 45
10.0%
0 39
8.7%
2 38
8.5%
5 30
 
6.7%
20
 
4.5%
3 18
 
4.0%
8 18
 
4.0%
9 15
 
3.3%
Other values (12) 67
15.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 282
62.9%
Other Punctuation 94
 
21.0%
Math Symbol 45
 
10.0%
Space Separator 20
 
4.5%
Other Letter 7
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 84
29.8%
0 39
13.8%
2 38
13.5%
5 30
 
10.6%
3 18
 
6.4%
8 18
 
6.4%
9 15
 
5.3%
4 15
 
5.3%
6 13
 
4.6%
7 12
 
4.3%
Other Letter
ValueCountFrequency (%)
계 1
14.3%
기 1
14.3%
간 1
14.3%
방 1
14.3%
문 1
14.3%
객 1
14.3%
수 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 74
78.7%
? 14
 
14.9%
, 6
 
6.4%
Math Symbol
ValueCountFrequency (%)
~ 45
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441
98.4%
Hangul 7
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 84
19.0%
. 74
16.8%
~ 45
10.2%
0 39
8.8%
2 38
8.6%
5 30
 
6.8%
20
 
4.5%
3 18
 
4.1%
8 18
 
4.1%
9 15
 
3.4%
Other values (5) 60
13.6%
Hangul
ValueCountFrequency (%)
계 1
14.3%
기 1
14.3%
간 1
14.3%
방 1
14.3%
문 1
14.3%
객 1
14.3%
수 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
98.4%
Hangul 7
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 84
19.0%
. 74
16.8%
~ 45
10.2%
0 39
8.8%
2 38
8.6%
5 30
 
6.8%
20
 
4.5%
3 18
 
4.1%
8 18
 
4.1%
9 15
 
3.4%
Other values (5) 60
13.6%
Hangul
ValueCountFrequency (%)
계 1
14.3%
기 1
14.3%
간 1
14.3%
방 1
14.3%
문 1
14.3%
객 1
14.3%
수 1
14.3%

Unnamed: 3
Text

MISSING 

Distinct66
Distinct (%)89.2%
Missing13
Missing (%)14.9%
Memory size828.0 B
2024-03-14T11:25:22.648628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length9
Mean length6.3108108
Min length1

Characters and Unicode

Total characters467
Distinct characters26
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

Unique60 ?
Unique (%)81.1%

Sample

1st row외국인
2nd row61,804
3rd row72,697
4th row123,052
5th row2015년도 관광객 현황(명)
ValueCountFrequency (%)
5,000 4
 
5.3%
216,365 2
 
2.6%
10,000 2
 
2.6%
6,000 2
 
2.6%
43,000 2
 
2.6%
170,000 2
 
2.6%
133,196 1
 
1.3%
58,852 1
 
1.3%
2,800 1
 
1.3%
252,319 1
 
1.3%
Other values (58) 58
76.3%
2024-03-14T11:25:22.964062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 132
28.3%
, 72
15.4%
1 45
 
9.6%
5 35
 
7.5%
6 32
 
6.9%
2 31
 
6.6%
4 25
 
5.4%
3 21
 
4.5%
7 20
 
4.3%
9 19
 
4.1%
Other values (16) 35
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 379
81.2%
Other Punctuation 72
 
15.4%
Other Letter 12
 
2.6%
Space Separator 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
외 1
8.3%
국 1
8.3%
계 1
8.3%
명 1
8.3%
관 1
8.3%
황 1
8.3%
현 1
8.3%
객 1
8.3%
광 1
8.3%
도 1
8.3%
Other values (2) 2
16.7%
Decimal Number
ValueCountFrequency (%)
0 132
34.8%
1 45
 
11.9%
5 35
 
9.2%
6 32
 
8.4%
2 31
 
8.2%
4 25
 
6.6%
3 21
 
5.5%
7 20
 
5.3%
9 19
 
5.0%
8 19
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 455
97.4%
Hangul 12
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 132
29.0%
, 72
15.8%
1 45
 
9.9%
5 35
 
7.7%
6 32
 
7.0%
2 31
 
6.8%
4 25
 
5.5%
3 21
 
4.6%
7 20
 
4.4%
9 19
 
4.2%
Other values (4) 23
 
5.1%
Hangul
ValueCountFrequency (%)
외 1
8.3%
국 1
8.3%
계 1
8.3%
명 1
8.3%
관 1
8.3%
황 1
8.3%
현 1
8.3%
객 1
8.3%
광 1
8.3%
도 1
8.3%
Other values (2) 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 455
97.4%
Hangul 12
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 132
29.0%
, 72
15.8%
1 45
 
9.9%
5 35
 
7.7%
6 32
 
7.0%
2 31
 
6.8%
4 25
 
5.5%
3 21
 
4.6%
7 20
 
4.4%
9 19
 
4.2%
Other values (4) 23
 
5.1%
Hangul
ValueCountFrequency (%)
외 1
8.3%
국 1
8.3%
계 1
8.3%
명 1
8.3%
관 1
8.3%
황 1
8.3%
현 1
8.3%
객 1
8.3%
광 1
8.3%
도 1
8.3%
Other values (2) 2
16.7%

Unnamed: 4
Categorical

Distinct29
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size828.0 B
?
40 
<NA>
14 
-
 
2
568
 
2
1,572
 
2
Other values (24)
27 

Length

Max length9
Median length6
Mean length3.2413793
Min length1

Unique

Unique21 ?
Unique (%)24.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row내국인
5th row6,123,162

Common Values

ValueCountFrequency (%)
? 40
46.0%
<NA> 14
 
16.1%
- 2
 
2.3%
568 2
 
2.3%
1,572 2
 
2.3%
2,185 2
 
2.3%
113 2
 
2.3%
100 2
 
2.3%
61,804 1
 
1.1%
890 1
 
1.1%
Other values (19) 19
21.8%

Length

2024-03-14T11:25:23.089036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
42
48.3%
na 14
 
16.1%
568 2
 
2.3%
1,572 2
 
2.3%
2,185 2
 
2.3%
113 2
 
2.3%
100 2
 
2.3%
33,161 1
 
1.1%
10,000 1
 
1.1%
3,000 1
 
1.1%
Other values (18) 18
20.7%

Unnamed: 5
Text

MISSING 

Distinct69
Distinct (%)92.0%
Missing12
Missing (%)13.8%
Memory size828.0 B
2024-03-14T11:25:23.289708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.28
Min length3

Characters and Unicode

Total characters471
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)86.7%

Sample

1st row(단위 : 명, %)
2nd row증감률
3rd row(전년 동기 대비)
4th row△0.09%
5th row△31.8%
ValueCountFrequency (%)
5,000 4
 
5.0%
214,180 2
 
2.5%
170,000 2
 
2.5%
6,000 2
 
2.5%
2
 
2.5%
100,852 1
 
1.2%
253,547 1
 
1.2%
663,870 1
 
1.2%
638,970 1
 
1.2%
30,000 1
 
1.2%
Other values (63) 63
78.8%
2024-03-14T11:25:23.626253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 128
27.2%
, 70
14.9%
1 38
 
8.1%
5 35
 
7.4%
2 31
 
6.6%
4 25
 
5.3%
8 25
 
5.3%
6 23
 
4.9%
3 22
 
4.7%
7 20
 
4.2%
Other values (23) 54
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 366
77.7%
Other Punctuation 78
 
16.6%
Other Letter 15
 
3.2%
Space Separator 5
 
1.1%
Other Symbol 3
 
0.6%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 1
 
6.7%
비 1
 
6.7%
단 1
 
6.7%
률 1
 
6.7%
감 1
 
6.7%
증 1
 
6.7%
인 1
 
6.7%
대 1
 
6.7%
기 1
 
6.7%
동 1
 
6.7%
Other values (5) 5
33.3%
Decimal Number
ValueCountFrequency (%)
0 128
35.0%
1 38
 
10.4%
5 35
 
9.6%
2 31
 
8.5%
4 25
 
6.8%
8 25
 
6.8%
6 23
 
6.3%
3 22
 
6.0%
7 20
 
5.5%
9 19
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 70
89.7%
% 4
 
5.1%
. 3
 
3.8%
: 1
 
1.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Symbol
ValueCountFrequency (%)
△ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
96.8%
Hangul 15
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 128
28.1%
, 70
15.4%
1 38
 
8.3%
5 35
 
7.7%
2 31
 
6.8%
4 25
 
5.5%
8 25
 
5.5%
6 23
 
5.0%
3 22
 
4.8%
7 20
 
4.4%
Other values (8) 39
 
8.6%
Hangul
ValueCountFrequency (%)
위 1
 
6.7%
비 1
 
6.7%
단 1
 
6.7%
률 1
 
6.7%
감 1
 
6.7%
증 1
 
6.7%
인 1
 
6.7%
대 1
 
6.7%
기 1
 
6.7%
동 1
 
6.7%
Other values (5) 5
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 453
96.2%
Hangul 15
 
3.2%
Geometric Shapes 3
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 128
28.3%
, 70
15.5%
1 38
 
8.4%
5 35
 
7.7%
2 31
 
6.8%
4 25
 
5.5%
8 25
 
5.5%
6 23
 
5.1%
3 22
 
4.9%
7 20
 
4.4%
Other values (7) 36
 
7.9%
Geometric Shapes
ValueCountFrequency (%)
△ 3
100.0%
Hangul
ValueCountFrequency (%)
위 1
 
6.7%
비 1
 
6.7%
단 1
 
6.7%
률 1
 
6.7%
감 1
 
6.7%
증 1
 
6.7%
인 1
 
6.7%
대 1
 
6.7%
기 1
 
6.7%
동 1
 
6.7%
Other values (5) 5
33.3%

Unnamed: 6
Categorical

IMBALANCE 

Distinct7
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size828.0 B
?
65 
<NA>
16 
공동 개최
 
2
(단위 : 명)
 
1
전년대비
 
1
Other values (2)
 
2

Length

Max length9
Median length2
Mean length2.6551724
Min length2

Unique

Unique4 ?
Unique (%)4.6%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
? 65
74.7%
<NA> 16
 
18.4%
공동 개최 2
 
2.3%
(단위 : 명) 1
 
1.1%
전년대비 1
 
1.1%
증감율(%) 1
 
1.1%
수산물축제와 통합 1
 
1.1%

Length

2024-03-14T11:25:23.743134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:25:23.868076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
66
71.7%
na 16
 
17.4%
공동 2
 
2.2%
개최 2
 
2.2%
단위 1
 
1.1%
명 1
 
1.1%
전년대비 1
 
1.1%
증감율 1
 
1.1%
수산물축제와 1
 
1.1%
통합 1
 
1.1%

Correlations

2024-03-14T11:25:24.014992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015년 지역축제 관광객 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
2015년 지역축제 관광객 현황1.0000.0000.0000.9610.8670.9640.295
Unnamed: 10.0001.0001.0000.5660.0000.9001.000
Unnamed: 20.0001.0001.0000.0000.0000.5390.955
Unnamed: 30.9610.5660.0001.0000.9921.0001.000
Unnamed: 40.8670.0000.0000.9921.0000.9980.263
Unnamed: 50.9640.9000.5391.0000.9981.0001.000
Unnamed: 60.2951.0000.9551.0000.2631.0001.000
2024-03-14T11:25:24.408774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 6
Unnamed: 41.0000.078
Unnamed: 60.0781.000
2024-03-14T11:25:24.489470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 4Unnamed: 6
Unnamed: 41.0000.078
Unnamed: 60.0781.000

Missing values

2024-03-14T11:25:20.690704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:25:20.786619image/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.
2024-03-14T11:25:20.886017image/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

2015년 지역축제 관광객 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA><NA><NA><NA><NA><NA><NA>
1□ 연도별 현황<NA><NA><NA><NA>(단위 : 명, %)<NA>
2구분축제 수방문객 수<NA><NA>증감률<NA>
3<NA><NA>계외국인내국인(전년 동기 대비)<NA>
4201556개6,184,96661,8046,123,162△0.09%<NA>
5201447개6,190,45072,6976,117,753△31.8%<NA>
6201355개9,076,160123,0528,953,108△9.7%<NA>
7<NA><NA><NA><NA><NA><NA><NA>
8□ 시군별 현황<NA><NA><NA><NA><NA><NA>
9* 1일 이상 지역축제 포함<NA><NA><NA><NA><NA>(단위 : 명)
2015년 지역축제 관광객 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
77<NA>고창갯벌체험축제5.23~25105,000?105,000수산물축제와 통합
78부안군소 계?182,795700182,095?
79(2)부안마실축제5.1~5.3122,795550122,245?
80<NA>곰소젓갈축제10.9~10.1160,00015059,850?
81<NA><NA><NA><NA><NA><NA><NA>
82<NA><NA><NA><NA><NA><NA><NA>
83<NA><NA><NA><NA><NA><NA><NA>
84<NA><NA><NA><NA><NA><NA><NA>
85<NA><NA><NA><NA><NA><NA><NA>
86<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

2015년 지역축제 관광객 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6# duplicates
0<NA><NA><NA><NA><NA><NA><NA>8