Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells300
Missing cells (%)37.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory69.3 B

Variable types

Categorical3
Text1
Numeric1
Unsupported3

Alerts

Survey_Base_Date_DE has constant value ""Constant
Country_CD has constant value ""Constant
Unnamed: 5 has 100 (100.0%) missing valuesMissing
FILE_NAME has 100 (100.0%) missing valuesMissing
BASE_YMD has 100 (100.0%) missing valuesMissing
Music_RN has unique valuesUnique
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
FILE_NAME is an unsupported type, check if it needs cleaning or further analysisUnsupported
BASE_YMD is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 10:00:43.270790
Analysis finished2023-12-10 10:00:44.449603
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Survey_Base_Date_DE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020-01-07
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-01-07
2nd row2020-01-07
3rd row2020-01-07
4th row2020-01-07
5th row2020-01-07

Common Values

ValueCountFrequency (%)
2020-01-07 100
100.0%

Length

2023-12-10T19:00:44.563996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:44.770012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-01-07 100
100.0%

Country_CD
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
id 100
100.0%

Length

2023-12-10T19:00:45.016097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:00:45.180895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
id 100
100.0%

Music_NM
Categorical

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
BTS
19 
BIGBANG
11 
BLACKPINK
8 
EXO
6 
IU
 
5
Other values (35)
51 

Length

Max length54
Median length17
Mean length7.05
Min length2

Unique

Unique28 ?
Unique (%)28.0%

Sample

1st rowYounha
2nd rowRed Velvet
3rd rowBTS
4th rowDavichi
5th rowATEEZ

Common Values

ValueCountFrequency (%)
BTS 19
19.0%
BIGBANG 11
 
11.0%
BLACKPINK 8
 
8.0%
EXO 6
 
6.0%
IU 5
 
5.0%
Girls' Generation 5
 
5.0%
TWICE 5
 
5.0%
2NE1 3
 
3.0%
Lyn 3
 
3.0%
TAEYEON 3
 
3.0%
Other values (30) 32
32.0%

Length

2023-12-10T19:00:45.359748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
bts 19
 
14.4%
bigbang 11
 
8.3%
blackpink 9
 
6.8%
exo 6
 
4.5%
girls 6
 
4.5%
iu 5
 
3.8%
generation 5
 
3.8%
twice 5
 
3.8%
5
 
3.8%
2ne1 3
 
2.3%
Other values (49) 58
43.9%

Artist_NM
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T19:00:46.015534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length24
Mean length12.18
Min length2

Characters and Unicode

Total characters1218
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st rowWinter Flower (feat. RM)
2nd rowPsycho
3rd rowBoy With Luv (feat. Halsey)
4th rowSunset
5th rowAnswer
ValueCountFrequency (%)
you 12
 
4.9%
love 8
 
3.3%
feat 7
 
2.8%
me 6
 
2.4%
i 5
 
2.0%
with 4
 
1.6%
my 4
 
1.6%
for 3
 
1.2%
it 3
 
1.2%
if 3
 
1.2%
Other values (155) 191
77.6%
2023-12-10T19:00:47.123051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
 
12.0%
e 77
 
6.3%
o 74
 
6.1%
i 51
 
4.2%
r 45
 
3.7%
t 42
 
3.4%
a 41
 
3.4%
n 36
 
3.0%
A 34
 
2.8%
l 31
 
2.5%
Other values (56) 641
52.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 594
48.8%
Uppercase Letter 412
33.8%
Space Separator 146
 
12.0%
Other Punctuation 23
 
1.9%
Decimal Number 14
 
1.1%
Open Punctuation 13
 
1.1%
Close Punctuation 12
 
1.0%
Dash Punctuation 4
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 34
 
8.3%
L 30
 
7.3%
O 28
 
6.8%
E 26
 
6.3%
B 25
 
6.1%
S 24
 
5.8%
M 23
 
5.6%
D 23
 
5.6%
I 23
 
5.6%
Y 21
 
5.1%
Other values (15) 155
37.6%
Lowercase Letter
ValueCountFrequency (%)
e 77
13.0%
o 74
12.5%
i 51
 
8.6%
r 45
 
7.6%
t 42
 
7.1%
a 41
 
6.9%
n 36
 
6.1%
l 31
 
5.2%
s 28
 
4.7%
u 28
 
4.7%
Other values (14) 141
23.7%
Decimal Number
ValueCountFrequency (%)
2 8
57.1%
0 1
 
7.1%
4 1
 
7.1%
6 1
 
7.1%
5 1
 
7.1%
9 1
 
7.1%
7 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 13
56.5%
, 4
 
17.4%
& 3
 
13.0%
' 3
 
13.0%
Open Punctuation
ValueCountFrequency (%)
( 11
84.6%
[ 2
 
15.4%
Close Punctuation
ValueCountFrequency (%)
) 10
83.3%
] 2
 
16.7%
Space Separator
ValueCountFrequency (%)
146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1006
82.6%
Common 212
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 77
 
7.7%
o 74
 
7.4%
i 51
 
5.1%
r 45
 
4.5%
t 42
 
4.2%
a 41
 
4.1%
n 36
 
3.6%
A 34
 
3.4%
l 31
 
3.1%
L 30
 
3.0%
Other values (39) 545
54.2%
Common
ValueCountFrequency (%)
146
68.9%
. 13
 
6.1%
( 11
 
5.2%
) 10
 
4.7%
2 8
 
3.8%
, 4
 
1.9%
- 4
 
1.9%
& 3
 
1.4%
' 3
 
1.4%
] 2
 
0.9%
Other values (7) 8
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1218
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
 
12.0%
e 77
 
6.3%
o 74
 
6.1%
i 51
 
4.2%
r 45
 
3.7%
t 42
 
3.4%
a 41
 
3.4%
n 36
 
3.0%
A 34
 
2.8%
l 31
 
2.5%
Other values (56) 641
52.6%

Music_RN
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:00:47.440060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T19:00:47.749738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

FILE_NAME
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

BASE_YMD
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

Interactions

2023-12-10T19:00:43.787259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:00:48.003903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Music_NMArtist_NMMusic_RN
Music_NM1.0001.0000.378
Artist_NM1.0001.0000.870
Music_RN0.3780.8701.000
2023-12-10T19:00:48.230797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Music_RNMusic_NM
Music_RN1.0000.083
Music_NM0.0831.000

Missing values

2023-12-10T19:00:44.112624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:00:44.360701image/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_Base_Date_DECountry_CDMusic_NMArtist_NMMusic_RNUnnamed: 5FILE_NAMEBASE_YMD
02020-01-07idYounhaWinter Flower (feat. RM)1<NA><NA><NA>
12020-01-07idRed VelvetPsycho2<NA><NA><NA>
22020-01-07idBTSBoy With Luv (feat. Halsey)3<NA><NA><NA>
32020-01-07idDavichiSunset4<NA><NA><NA>
42020-01-07idATEEZAnswer5<NA><NA><NA>
52020-01-07idIUBlueming6<NA><NA><NA>
62020-01-07idCrushBeautiful7<NA><NA><NA>
72020-01-07idEXOKo Ko Bop8<NA><NA><NA>
82020-01-07idBTSEuphoria9<NA><NA><NA>
92020-01-07idMAMAMOOHip10<NA><NA><NA>
Survey_Base_Date_DECountry_CDMusic_NMArtist_NMMusic_RNUnnamed: 5FILE_NAMEBASE_YMD
902020-01-07idLynMy Destiny91<NA><NA><NA>
912020-01-07idThe OneA Winter Story92<NA><NA><NA>
922020-01-07idIUPalette (feat. G-DRAGON)93<NA><NA><NA>
932020-01-07idTWICELike OOH-AHH94<NA><NA><NA>
942020-01-07id2NE1Falling In Love95<NA><NA><NA>
952020-01-07id2NE1Come Back Home96<NA><NA><NA>
962020-01-07idKim Tae Woo & BENDarling U (From Oh My Venus [Original Television Soundtrack]97<NA><NA><NA>
972020-01-07idSUPER JUNIORSorry, Sorry98<NA><NA><NA>
982020-01-07idCHEN, BAEKHYUN & XIUMINFor You99<NA><NA><NA>
992020-01-07idTAEYEONAll with You100<NA><NA><NA>