Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory54.3 B

Variable types

Categorical4
Text1
Numeric1

Alerts

boost1 has constant value ""Constant
boost2 has constant value ""Constant
boost3 has constant value ""Constant
term has unique valuesUnique

Reproduction

Analysis started2023-12-10 09:48:15.462957
Analysis finished2023-12-10 09:48:16.338418
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

isbn13
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
9791191739015
49 
9791138007238
48 
9791165881320
 
3

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9791138007238
2nd row9791165881320
3rd row9791138007238
4th row9791138007238
5th row9791138007238

Common Values

ValueCountFrequency (%)
9791191739015 49
49.0%
9791138007238 48
48.0%
9791165881320 3
 
3.0%

Length

2023-12-10T18:48:16.425817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:16.577543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9791191739015 49
49.0%
9791138007238 48
48.0%
9791165881320 3
 
3.0%

term
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T18:48:16.997392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length3.03
Min length2

Characters and Unicode

Total characters303
Distinct characters182
Distinct categories4 ?
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 (%)100.0%

Sample

1st row셜록
2nd row희망
3rd row사건
4th row블로그
5th row셜록 SHERLOCK
ValueCountFrequency (%)
셜록 2
 
1.8%
집중 1
 
0.9%
장아찌 1
 
0.9%
맛내기 1
 
0.9%
가지 1
 
0.9%
채소 1
 
0.9%
한식대첩 1
 
0.9%
초보 1
 
0.9%
기본 1
 
0.9%
배추김치 1
 
0.9%
Other values (98) 98
89.9%
2023-12-10T18:48:17.754741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
3.3%
치 8
 
2.6%
스 8
 
2.6%
기 8
 
2.6%
김 6
 
2.0%
정 5
 
1.7%
한 5
 
1.7%
지 5
 
1.7%
명 5
 
1.7%
사 4
 
1.3%
Other values (172) 239
78.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 272
89.8%
Uppercase Letter 15
 
5.0%
Space Separator 10
 
3.3%
Lowercase Letter 6
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 8
 
2.9%
스 8
 
2.9%
기 8
 
2.9%
김 6
 
2.2%
정 5
 
1.8%
한 5
 
1.8%
지 5
 
1.8%
명 5
 
1.8%
사 4
 
1.5%
양 4
 
1.5%
Other values (153) 214
78.7%
Uppercase Letter
ValueCountFrequency (%)
P 2
13.3%
E 2
13.3%
N 2
13.3%
A 1
6.7%
J 1
6.7%
K 1
6.7%
C 1
6.7%
O 1
6.7%
L 1
6.7%
R 1
6.7%
Other values (2) 2
13.3%
Lowercase Letter
ValueCountFrequency (%)
v 1
16.7%
i 1
16.7%
d 1
16.7%
n 1
16.7%
y 1
16.7%
a 1
16.7%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 272
89.8%
Latin 21
 
6.9%
Common 10
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 8
 
2.9%
스 8
 
2.9%
기 8
 
2.9%
김 6
 
2.2%
정 5
 
1.8%
한 5
 
1.8%
지 5
 
1.8%
명 5
 
1.8%
사 4
 
1.5%
양 4
 
1.5%
Other values (153) 214
78.7%
Latin
ValueCountFrequency (%)
P 2
 
9.5%
E 2
 
9.5%
N 2
 
9.5%
v 1
 
4.8%
i 1
 
4.8%
d 1
 
4.8%
A 1
 
4.8%
n 1
 
4.8%
y 1
 
4.8%
a 1
 
4.8%
Other values (8) 8
38.1%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 272
89.8%
ASCII 31
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
32.3%
P 2
 
6.5%
E 2
 
6.5%
N 2
 
6.5%
v 1
 
3.2%
i 1
 
3.2%
d 1
 
3.2%
A 1
 
3.2%
n 1
 
3.2%
y 1
 
3.2%
Other values (9) 9
29.0%
Hangul
ValueCountFrequency (%)
치 8
 
2.9%
스 8
 
2.9%
기 8
 
2.9%
김 6
 
2.2%
정 5
 
1.8%
한 5
 
1.8%
지 5
 
1.8%
명 5
 
1.8%
사 4
 
1.5%
양 4
 
1.5%
Other values (153) 214
78.7%

freq
Real number (ℝ)

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.56
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T18:48:17.965286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum27
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.8152543
Coefficient of variation (CV)1.0997087
Kurtosis58.230916
Mean2.56
Median Absolute Deviation (MAD)1
Skewness6.8922617
Sum256
Variance7.9256566
MonotonicityNot monotonic
2023-12-10T18:48:18.118832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 44
44.0%
1 26
26.0%
3 15
 
15.0%
4 6
 
6.0%
5 6
 
6.0%
8 2
 
2.0%
27 1
 
1.0%
ValueCountFrequency (%)
1 26
26.0%
2 44
44.0%
3 15
 
15.0%
4 6
 
6.0%
5 6
 
6.0%
8 2
 
2.0%
27 1
 
1.0%
ValueCountFrequency (%)
27 1
 
1.0%
8 2
 
2.0%
5 6
 
6.0%
4 6
 
6.0%
3 15
 
15.0%
2 44
44.0%
1 26
26.0%

boost1
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T18:48:18.324636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:18.505158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

boost2
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T18:48:18.682275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:18.906726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

boost3
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T18:48:19.111482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T18:48:19.285201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

Interactions

2023-12-10T18:48:15.709579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T18:48:19.382451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
isbn13termfreq
isbn131.0001.0000.103
term1.0001.0001.000
freq0.1031.0001.000
2023-12-10T18:48:19.523839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
freqisbn13
freq1.0000.095
isbn130.0951.000

Missing values

2023-12-10T18:48:15.846651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T18:48:16.290192image/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

isbn13termfreqboost1boost2boost3
09791138007238셜록8000
19791165881320희망1000
29791138007238사건4000
39791138007238블로그4000
49791138007238셜록 SHERLOCK3000
59791138007238어벤져스3000
69791138007238닥터스트레인지3000
79791165881320치료1000
89791138007238Jay2000
99791138007238영상출판미디어 주2000
isbn13termfreqboost1boost2boost3
909791191739015무김치2000
919791191739015고추2000
929791191739015경험2000
939791191739015김치냉장고2000
949791191739015알토란2000
959791191739015실패2000
969791191739015활동2000
979791191739015비결2000
989791191739015한식2000
999791191739015빼기2000