Overview

Dataset statistics

Number of variables7
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.9 KiB
Average record size in memory60.3 B

Variable types

Categorical6
Text1

Alerts

Survey_Date_YY has constant value ""Constant
Country_CD has constant value ""Constant
FILE_NAME has constant value ""Constant
BASE_YMD has constant value ""Constant

Reproduction

Analysis started2023-12-10 09:57:12.052137
Analysis finished2023-12-10 09:57:12.770447
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Survey_Date_YY
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2018
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 100
100.0%

Length

2023-12-10T18:57:12.897598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:13.078723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 100
100.0%

Country_CD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
au
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
au 100
100.0%

Length

2023-12-10T18:57:13.324392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:13.482925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
au 100
100.0%

Musuc_Info_NM
Categorical

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
monster
18 
bad boy
17 
icy
17 
growl
15 
daydream
12 
Other values (2)
21 

Length

Max length13
Median length9
Mean length7
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowreally really
2nd rowreally really
3rd rowreally really
4th rowreally really
5th rowreally really

Common Values

ValueCountFrequency (%)
monster 18
18.0%
bad boy 17
17.0%
icy 17
17.0%
growl 15
15.0%
daydream 12
12.0%
really really 11
11.0%
egotistic 10
10.0%

Length

2023-12-10T18:57:13.687707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:13.947785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
really 22
17.2%
monster 18
14.1%
bad 17
13.3%
boy 17
13.3%
icy 17
13.3%
growl 15
11.7%
daydream 12
9.4%
egotistic 10
7.8%

Country_Music_Info_KEY_W
Text

Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:57:14.508977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length5.73
Min length2

Characters and Unicode

Total characters573
Distinct characters40
Distinct categories2 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)66.0%

Sample

1st rowkpop
2nd rowlisten
3rd rowphone
4th rowfacetiousvera
5th rowfrroggi
ValueCountFrequency (%)
youtub 5
 
5.0%
video 5
 
5.0%
playlist 4
 
4.0%
bts 4
 
4.0%
kpop 3
 
3.0%
like 3
 
3.0%
facetiousvera 2
 
2.0%
midnoob 2
 
2.0%
monster 2
 
2.0%
next 2
 
2.0%
Other values (67) 68
68.0%
2023-12-10T18:57:15.266220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 60
 
10.5%
e 51
 
8.9%
i 42
 
7.3%
t 41
 
7.2%
a 34
 
5.9%
r 33
 
5.8%
n 28
 
4.9%
s 27
 
4.7%
l 25
 
4.4%
p 25
 
4.4%
Other values (30) 207
36.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 558
97.4%
Other Letter 15
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 60
 
10.8%
e 51
 
9.1%
i 42
 
7.5%
t 41
 
7.3%
a 34
 
6.1%
r 33
 
5.9%
n 28
 
5.0%
s 27
 
4.8%
l 25
 
4.5%
p 25
 
4.5%
Other values (15) 192
34.4%
Other Letter
ValueCountFrequency (%)
以 1
 
6.7%
씪 1
 
6.7%
깆 1
 
6.7%
諛 1
 
6.7%
떖 1
 
6.7%
묒 1
 
6.7%
쓬 1
 
6.7%
븙 1
 
6.7%
쟻 1
 
6.7%
대 1
 
6.7%
Other values (5) 5
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 558
97.4%
Hangul 11
 
1.9%
Han 4
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 60
 
10.8%
e 51
 
9.1%
i 42
 
7.5%
t 41
 
7.3%
a 34
 
6.1%
r 33
 
5.9%
n 28
 
5.0%
s 27
 
4.8%
l 25
 
4.5%
p 25
 
4.5%
Other values (15) 192
34.4%
Hangul
ValueCountFrequency (%)
씪 1
9.1%
깆 1
9.1%
떖 1
9.1%
묒 1
9.1%
쓬 1
9.1%
븙 1
9.1%
쟻 1
9.1%
대 1
9.1%
쑝 1
9.1%
냼 1
9.1%
Han
ValueCountFrequency (%)
以 1
25.0%
諛 1
25.0%
瑜 1
25.0%
紐 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 558
97.4%
Hangul 11
 
1.9%
CJK 3
 
0.5%
CJK Compat Ideographs 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 60
 
10.8%
e 51
 
9.1%
i 42
 
7.5%
t 41
 
7.3%
a 34
 
6.1%
r 33
 
5.9%
n 28
 
5.0%
s 27
 
4.8%
l 25
 
4.5%
p 25
 
4.5%
Other values (15) 192
34.4%
CJK
ValueCountFrequency (%)
以 1
33.3%
諛 1
33.3%
瑜 1
33.3%
Hangul
ValueCountFrequency (%)
씪 1
9.1%
깆 1
9.1%
떖 1
9.1%
묒 1
9.1%
쓬 1
9.1%
븙 1
9.1%
쟻 1
9.1%
대 1
9.1%
쑝 1
9.1%
냼 1
9.1%
CJK Compat Ideographs
ValueCountFrequency (%)
紐 1
100.0%

Keyword_FQ
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2
61 
1
21 
4
12 
3
 
4
8
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 61
61.0%
1 21
 
21.0%
4 12
 
12.0%
3 4
 
4.0%
8 2
 
2.0%

Length

2023-12-10T18:57:15.547154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:15.753916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 61
61.0%
1 21
 
21.0%
4 12
 
12.0%
3 4
 
4.0%
8 2
 
2.0%

FILE_NAME
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
KC_MUSIC_KEYWORD_2019
100 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKC_MUSIC_KEYWORD_2019
2nd rowKC_MUSIC_KEYWORD_2019
3rd rowKC_MUSIC_KEYWORD_2019
4th rowKC_MUSIC_KEYWORD_2019
5th rowKC_MUSIC_KEYWORD_2019

Common Values

ValueCountFrequency (%)
KC_MUSIC_KEYWORD_2019 100
100.0%

Length

2023-12-10T18:57:16.011461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:16.247801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kc_music_keyword_2019 100
100.0%

BASE_YMD
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2019
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 100
100.0%

Length

2023-12-10T18:57:16.461863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:57:16.654349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 100
100.0%

Correlations

2023-12-10T18:57:16.823003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Musuc_Info_NMCountry_Music_Info_KEY_WKeyword_FQ
Musuc_Info_NM1.0000.0000.432
Country_Music_Info_KEY_W0.0001.0000.000
Keyword_FQ0.4320.0001.000
2023-12-10T18:57:17.025946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Musuc_Info_NMKeyword_FQ
Musuc_Info_NM1.0000.290
Keyword_FQ0.2901.000
2023-12-10T18:57:17.264976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Musuc_Info_NMKeyword_FQ
Musuc_Info_NM1.0000.290
Keyword_FQ0.2901.000

Missing values

2023-12-10T18:57:12.362659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:57:12.673691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Survey_Date_YYCountry_CDMusuc_Info_NMCountry_Music_Info_KEY_WKeyword_FQFILE_NAMEBASE_YMD
02018aureally reallykpop4KC_MUSIC_KEYWORD_20192019
12018aureally reallylisten2KC_MUSIC_KEYWORD_20192019
22018aureally reallyphone2KC_MUSIC_KEYWORD_20192019
32018aureally reallyfacetiousvera2KC_MUSIC_KEYWORD_20192019
42018aureally reallyfrroggi2KC_MUSIC_KEYWORD_20192019
52018aureally reallymidnoob2KC_MUSIC_KEYWORD_20192019
62018aureally reallymonster2KC_MUSIC_KEYWORD_20192019
72018aureally reallyplaylist2KC_MUSIC_KEYWORD_20192019
82018aureally reallyvideo2KC_MUSIC_KEYWORD_20192019
92018aureally reallyyoutub2KC_MUSIC_KEYWORD_20192019
Survey_Date_YYCountry_CDMusuc_Info_NMCountry_Music_Info_KEY_WKeyword_FQFILE_NAMEBASE_YMD
902018audaydreamlike4KC_MUSIC_KEYWORD_20192019
912018audaydreamplaylist4KC_MUSIC_KEYWORD_20192019
922018audaydreamdaydream4KC_MUSIC_KEYWORD_20192019
932018audaydreamjhope4KC_MUSIC_KEYWORD_20192019
942018audaydreambtstwt3KC_MUSIC_KEYWORD_20192019
952018audaydream諛깆씪紐3KC_MUSIC_KEYWORD_20192019
962018audaydreambts2KC_MUSIC_KEYWORD_20192019
972018audaydreamimadaydream2KC_MUSIC_KEYWORD_20192019
982018audaydreamlukewaltham2KC_MUSIC_KEYWORD_20192019
992018audaydreamreaction2KC_MUSIC_KEYWORD_20192019