Overview

Dataset statistics

Number of variables8
Number of observations38
Missing cells9
Missing cells (%)3.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory67.5 B

Variable types

Text6
Categorical1
DateTime1

Dataset

Description이 데이터는 광주광역시의 문화예술 관광지별(자치구) 방문자 수 통계 데이터로 2016년부터 2020년까지 주요 관광지 방문자수를 확인할 수 있습니다.
Author광주광역시
URLhttps://www.data.go.kr/data/15098091/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
2016년 has 5 (13.2%) missing valuesMissing
2017년 has 2 (5.3%) missing valuesMissing
2018년 has 1 (2.6%) missing valuesMissing
2019년 has 1 (2.6%) missing valuesMissing
방문지역 has unique valuesUnique
2020년 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:54:21.190202
Analysis finished2023-12-11 22:54:21.763156
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

방문지역
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T07:54:21.914239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.7631579
Min length3

Characters and Unicode

Total characters257
Distinct characters109
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

Unique38 ?
Unique (%)100.0%

Sample

1st row곰적골
2nd row동적골
3rd row장원봉제1진입로
4th row제1수원지
5th row제2수원지
ValueCountFrequency (%)
곰적골 1
 
2.6%
국립광주과학관 1
 
2.6%
국립5.18묘지 1
 
2.6%
이장우가옥 1
 
2.6%
포충사 1
 
2.6%
펭귄마을 1
 
2.6%
무등산국립공원(원효지구 1
 
2.6%
광주문화예술회관 1
 
2.6%
광주시민의숲야영장 1
 
2.6%
시립민속박물관 1
 
2.6%
Other values (28) 28
73.7%
2023-12-12T07:54:22.256738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 12
 
4.7%
관 10
 
3.9%
주 9
 
3.5%
광 7
 
2.7%
립 7
 
2.7%
지 7
 
2.7%
증 6
 
2.3%
장 6
 
2.3%
사 6
 
2.3%
1 6
 
2.3%
Other values (99) 181
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 235
91.4%
Decimal Number 13
 
5.1%
Close Punctuation 3
 
1.2%
Open Punctuation 3
 
1.2%
Other Punctuation 2
 
0.8%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 12
 
5.1%
관 10
 
4.3%
주 9
 
3.8%
광 7
 
3.0%
립 7
 
3.0%
지 7
 
3.0%
증 6
 
2.6%
장 6
 
2.6%
사 6
 
2.6%
심 6
 
2.6%
Other values (91) 159
67.7%
Decimal Number
ValueCountFrequency (%)
1 6
46.2%
2 3
23.1%
8 2
 
15.4%
5 2
 
15.4%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 235
91.4%
Common 22
 
8.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 12
 
5.1%
관 10
 
4.3%
주 9
 
3.8%
광 7
 
3.0%
립 7
 
3.0%
지 7
 
3.0%
증 6
 
2.6%
장 6
 
2.6%
사 6
 
2.6%
심 6
 
2.6%
Other values (91) 159
67.7%
Common
ValueCountFrequency (%)
1 6
27.3%
) 3
13.6%
2 3
13.6%
( 3
13.6%
. 2
 
9.1%
8 2
 
9.1%
5 2
 
9.1%
~ 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 235
91.4%
ASCII 22
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 12
 
5.1%
관 10
 
4.3%
주 9
 
3.8%
광 7
 
3.0%
립 7
 
3.0%
지 7
 
3.0%
증 6
 
2.6%
장 6
 
2.6%
사 6
 
2.6%
심 6
 
2.6%
Other values (91) 159
67.7%
ASCII
ValueCountFrequency (%)
1 6
27.3%
) 3
13.6%
2 3
13.6%
( 3
13.6%
. 2
 
9.1%
8 2
 
9.1%
5 2
 
9.1%
~ 1
 
4.5%

자치구
Categorical

Distinct5
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size436.0 B
동구
16 
북구
11 
남구
8 
서구
2 
광산구
 
1

Length

Max length3
Median length2
Mean length2.0263158
Min length2

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
동구 16
42.1%
북구 11
28.9%
남구 8
21.1%
서구 2
 
5.3%
광산구 1
 
2.6%

Length

2023-12-12T07:54:22.384227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:54:22.498583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동구 16
42.1%
북구 11
28.9%
남구 8
21.1%
서구 2
 
5.3%
광산구 1
 
2.6%

2016년
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing5
Missing (%)13.2%
Memory size436.0 B
2023-12-12T07:54:22.705043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5757576
Min length6

Characters and Unicode

Total characters217
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row202,365
2nd row17,344
3rd row77,438
4th row62,723
5th row56,981
ValueCountFrequency (%)
405,019 1
 
3.0%
539,536 1
 
3.0%
71,021 1
 
3.0%
128,540 1
 
3.0%
852,458 1
 
3.0%
202,647 1
 
3.0%
16,364 1
 
3.0%
666,502 1
 
3.0%
335,032 1
 
3.0%
202,365 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T07:54:23.084980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 33
15.2%
1 24
11.1%
2 23
10.6%
5 22
10.1%
3 22
10.1%
7 20
9.2%
8 18
8.3%
6 17
7.8%
0 15
6.9%
4 13
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 184
84.8%
Other Punctuation 33
 
15.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
13.0%
2 23
12.5%
5 22
12.0%
3 22
12.0%
7 20
10.9%
8 18
9.8%
6 17
9.2%
0 15
8.2%
4 13
7.1%
9 10
5.4%
Other Punctuation
ValueCountFrequency (%)
, 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 217
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 33
15.2%
1 24
11.1%
2 23
10.6%
5 22
10.1%
3 22
10.1%
7 20
9.2%
8 18
8.3%
6 17
7.8%
0 15
6.9%
4 13
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 33
15.2%
1 24
11.1%
2 23
10.6%
5 22
10.1%
3 22
10.1%
7 20
9.2%
8 18
8.3%
6 17
7.8%
0 15
6.9%
4 13
 
6.0%

2017년
Text

MISSING 

Distinct36
Distinct (%)100.0%
Missing2
Missing (%)5.3%
Memory size436.0 B
2023-12-12T07:54:23.278221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.5
Min length5

Characters and Unicode

Total characters234
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row32,951
2nd row238,704
3rd row20,346
4th row88,221
5th row40,926
ValueCountFrequency (%)
238,704 1
 
2.8%
20,346 1
 
2.8%
36,691 1
 
2.8%
96,001 1
 
2.8%
113,700 1
 
2.8%
782,402 1
 
2.8%
207,065 1
 
2.8%
31,796 1
 
2.8%
729,714 1
 
2.8%
178,867 1
 
2.8%
Other values (26) 26
72.2%
2023-12-12T07:54:23.597238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 36
15.4%
2 25
10.7%
0 25
10.7%
3 24
10.3%
1 24
10.3%
7 21
9.0%
6 21
9.0%
9 19
8.1%
4 15
6.4%
8 12
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 198
84.6%
Other Punctuation 36
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 25
12.6%
0 25
12.6%
3 24
12.1%
1 24
12.1%
7 21
10.6%
6 21
10.6%
9 19
9.6%
4 15
7.6%
8 12
6.1%
5 12
6.1%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 36
15.4%
2 25
10.7%
0 25
10.7%
3 24
10.3%
1 24
10.3%
7 21
9.0%
6 21
9.0%
9 19
8.1%
4 15
6.4%
8 12
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 36
15.4%
2 25
10.7%
0 25
10.7%
3 24
10.3%
1 24
10.3%
7 21
9.0%
6 21
9.0%
9 19
8.1%
4 15
6.4%
8 12
 
5.1%

2018년
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Memory size436.0 B
2023-12-12T07:54:23.804730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.4324324
Min length5

Characters and Unicode

Total characters238
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row40,573
2nd row214,557
3rd row12,420
4th row62,258
5th row36,957
ValueCountFrequency (%)
40,573 1
 
2.7%
39,510 1
 
2.7%
608,586 1
 
2.7%
80,730 1
 
2.7%
107,680 1
 
2.7%
22,814 1
 
2.7%
748,825 1
 
2.7%
207,254 1
 
2.7%
30,932 1
 
2.7%
855,385 1
 
2.7%
Other values (27) 27
73.0%
2023-12-12T07:54:24.117262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 37
15.5%
2 30
12.6%
5 29
12.2%
0 26
10.9%
3 24
10.1%
8 20
8.4%
4 15
6.3%
7 15
6.3%
9 15
6.3%
1 14
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
84.5%
Other Punctuation 37
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30
14.9%
5 29
14.4%
0 26
12.9%
3 24
11.9%
8 20
10.0%
4 15
7.5%
7 15
7.5%
9 15
7.5%
1 14
7.0%
6 13
6.5%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 37
15.5%
2 30
12.6%
5 29
12.2%
0 26
10.9%
3 24
10.1%
8 20
8.4%
4 15
6.3%
7 15
6.3%
9 15
6.3%
1 14
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 37
15.5%
2 30
12.6%
5 29
12.2%
0 26
10.9%
3 24
10.1%
8 20
8.4%
4 15
6.3%
7 15
6.3%
9 15
6.3%
1 14
 
5.9%

2019년
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing1
Missing (%)2.6%
Memory size436.0 B
2023-12-12T07:54:24.303481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.4324324
Min length5

Characters and Unicode

Total characters238
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row37,948
2nd row240,307
3rd row11,341
4th row48,015
5th row35,092
ValueCountFrequency (%)
37,948 1
 
2.7%
21,096 1
 
2.7%
605,901 1
 
2.7%
70,925 1
 
2.7%
102,200 1
 
2.7%
64,628 1
 
2.7%
717,942 1
 
2.7%
216,375 1
 
2.7%
34,680 1
 
2.7%
890,363 1
 
2.7%
Other values (27) 27
73.0%
2023-12-12T07:54:24.611953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 37
15.5%
1 28
11.8%
3 24
10.1%
0 24
10.1%
5 23
9.7%
2 22
9.2%
4 20
8.4%
7 19
8.0%
6 15
6.3%
9 13
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
84.5%
Other Punctuation 37
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28
13.9%
3 24
11.9%
0 24
11.9%
5 23
11.4%
2 22
10.9%
4 20
10.0%
7 19
9.5%
6 15
7.5%
9 13
6.5%
8 13
6.5%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 37
15.5%
1 28
11.8%
3 24
10.1%
0 24
10.1%
5 23
9.7%
2 22
9.2%
4 20
8.4%
7 19
8.0%
6 15
6.3%
9 13
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 37
15.5%
1 28
11.8%
3 24
10.1%
0 24
10.1%
5 23
9.7%
2 22
9.2%
4 20
8.4%
7 19
8.0%
6 15
6.3%
9 13
 
5.5%

2020년
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T07:54:24.792247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1315789
Min length5

Characters and Unicode

Total characters233
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row31,312
2nd row193,063
3rd row11,912
4th row38,196
5th row34,621
ValueCountFrequency (%)
31,312 1
 
2.6%
258,340 1
 
2.6%
230,246 1
 
2.6%
14,156 1
 
2.6%
46,710 1
 
2.6%
7,251 1
 
2.6%
611,605 1
 
2.6%
28,550 1
 
2.6%
14,772 1
 
2.6%
17,848 1
 
2.6%
Other values (28) 28
73.7%
2023-12-12T07:54:25.098082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 38
16.3%
1 35
15.0%
0 25
10.7%
2 23
9.9%
3 20
8.6%
6 18
7.7%
4 17
7.3%
7 16
6.9%
9 15
 
6.4%
8 15
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
83.7%
Other Punctuation 38
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 35
17.9%
0 25
12.8%
2 23
11.8%
3 20
10.3%
6 18
9.2%
4 17
8.7%
7 16
8.2%
9 15
7.7%
8 15
7.7%
5 11
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 233
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 38
16.3%
1 35
15.0%
0 25
10.7%
2 23
9.9%
3 20
8.6%
6 18
7.7%
4 17
7.3%
7 16
6.9%
9 15
 
6.4%
8 15
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 233
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 38
16.3%
1 35
15.0%
0 25
10.7%
2 23
9.9%
3 20
8.6%
6 18
7.7%
4 17
7.3%
7 16
6.9%
9 15
 
6.4%
8 15
 
6.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
Minimum2021-10-30 00:00:00
Maximum2021-10-30 00:00:00
2023-12-12T07:54:25.193548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:54:25.272857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T07:54:25.357950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
방문지역자치구2016년2017년2018년2019년2020년
방문지역1.0001.0001.0001.0001.0001.0001.000
자치구1.0001.0001.0001.0001.0001.0001.000
2016년1.0001.0001.0001.0001.0001.0001.000
2017년1.0001.0001.0001.0001.0001.0001.000
2018년1.0001.0001.0001.0001.0001.0001.000
2019년1.0001.0001.0001.0001.0001.0001.000
2020년1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T07:54:21.525366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:54:21.628681image/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.
2023-12-12T07:54:21.714741image/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

방문지역자치구2016년2017년2018년2019년2020년데이터기준일자
0곰적골동구<NA>32,95140,57337,94831,3122021-10-30
1동적골동구202,365238,704214,557240,307193,0632021-10-30
2장원봉제1진입로동구17,34420,34612,42011,34111,9122021-10-30
3제1수원지동구77,43888,22162,25848,01538,1962021-10-30
4제2수원지동구62,72340,92636,95735,09234,6212021-10-30
5주차장~옛길동구56,98162,95072,22887,88363,2382021-10-30
6증심사방향1동구157,827170,700132,173106,47581,4822021-10-30
7증심사방향2동구360,738389,402285,356272,017221,7472021-10-30
8증심사상가방향1동구55,99376,82383,47073,42647,9382021-10-30
9증심사상가방향2동구405,019420,418352,350335,559196,9042021-10-30
방문지역자치구2016년2017년2018년2019년2020년데이터기준일자
28시립미술관북구158,206178,867203,990212,33029,5802021-10-30
29시립민속박물관북구335,032324,777243,20853,01117,8482021-10-30
30우치공원(동물원)북구247,027369,261445,089481,091180,0302021-10-30
31우치공원(패밀리랜드)북구551,362386,469347,954334,041130,6632021-10-30
32국립광주박물관북구547,738567,401593,500567,04797,1982021-10-30
33광주호호수생태원북구<NA><NA><NA><NA>120,2722021-10-30
34전통문화관동구131,977147,549178,222178,51929,9272021-10-30
35광주김치타운남구138,215111,927101,732130,32626,7072021-10-30
36국립5.18묘지북구578,575703,612608,586605,901230,2462021-10-30
37월봉서원광산구29,19832,46338,30930,57116,1392021-10-30