Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory68.3 B

Variable types

Categorical5
Text1
Numeric2

Dataset

DescriptionSample
Author써머스플랫폼
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=SMPBRANDAREA

Alerts

PRDUCT_LCLAS_NM has constant value ""Constant
PRDUCT_MLSFC_NM has constant value ""Constant
YM has constant value ""Constant
QU_SE_VALUE has constant value ""Constant
BRTC_RATE is highly overall correlated with TOTAL_BRAND_RATEHigh correlation
TOTAL_BRAND_RATE is highly overall correlated with BRTC_RATEHigh correlation

Reproduction

Analysis started2023-12-10 06:46:05.915286
Analysis finished2023-12-10 06:46:07.028397
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

PRDUCT_LCLAS_NM
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
컴퓨터 100
100.0%

Length

2023-12-10T15:46:07.138903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:46:07.249526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
컴퓨터 100
100.0%

PRDUCT_MLSFC_NM
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노트북 100
100.0%

Length

2023-12-10T15:46:07.395092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:46:07.505445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노트북 100
100.0%

YM
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
202007
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row202007
2nd row202007
3rd row202007
4th row202007
5th row202007

Common Values

ValueCountFrequency (%)
202007 100
100.0%

Length

2023-12-10T15:46:07.619606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:46:07.730765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
202007 100
100.0%

QU_SE_VALUE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20203Q
100 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20203Q
2nd row20203Q
3rd row20203Q
4th row20203Q
5th row20203Q

Common Values

ValueCountFrequency (%)
20203Q 100
100.0%

Length

2023-12-10T15:46:07.878088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:46:08.002053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20203q 100
100.0%

BRTC_NM
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
61 
경상남도
23 
강원도
16 

Length

Max length4
Median length3
Mean length3.23
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 61
61.0%
경상남도 23
 
23.0%
강원도 16
 
16.0%

Length

2023-12-10T15:46:08.116445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:46:08.258059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 61
61.0%
경상남도 23
 
23.0%
강원도 16
 
16.0%

PRDUCT_BRAND_NM
Text

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T15:46:08.518119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length6
Min length2

Characters and Unicode

Total characters600
Distinct characters113
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

Unique42 ?
Unique (%)42.0%

Sample

1st row갤럭시북 플렉스
2nd row게이밍
3rd rowROG
4th rowROG STRIX G
5th row파빌리온 게이밍
ValueCountFrequency (%)
2020 12
 
8.5%
갤럭시북 8
 
5.6%
플렉스 7
 
4.9%
rog 6
 
4.2%
울트라pc 4
 
2.8%
게이밍 3
 
2.1%
vivobook 3
 
2.1%
맥북프로 3
 
2.1%
15 3
 
2.1%
laptop 3
 
2.1%
Other values (60) 90
63.4%
2023-12-10T15:46:09.018819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
7.0%
2 27
 
4.5%
0 26
 
4.3%
북 24
 
4.0%
O 22
 
3.7%
이 18
 
3.0%
G 16
 
2.7%
스 15
 
2.5%
시 13
 
2.2%
5 12
 
2.0%
Other values (103) 385
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
47.7%
Uppercase Letter 148
24.7%
Decimal Number 86
 
14.3%
Space Separator 42
 
7.0%
Lowercase Letter 38
 
6.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 24
 
8.4%
이 18
 
6.3%
스 15
 
5.2%
시 13
 
4.5%
리 12
 
4.2%
트 9
 
3.1%
어 9
 
3.1%
플 8
 
2.8%
럭 8
 
2.8%
갤 8
 
2.8%
Other values (57) 162
56.6%
Uppercase Letter
ValueCountFrequency (%)
O 22
14.9%
G 16
 
10.8%
S 11
 
7.4%
R 11
 
7.4%
I 9
 
6.1%
P 9
 
6.1%
L 8
 
5.4%
V 7
 
4.7%
E 6
 
4.1%
T 6
 
4.1%
Other values (12) 43
29.1%
Lowercase Letter
ValueCountFrequency (%)
p 7
18.4%
t 5
13.2%
o 4
10.5%
a 4
10.5%
e 3
7.9%
i 3
7.9%
y 2
 
5.3%
s 2
 
5.3%
l 2
 
5.3%
w 1
 
2.6%
Other values (5) 5
13.2%
Decimal Number
ValueCountFrequency (%)
2 27
31.4%
0 26
30.2%
5 12
14.0%
1 12
14.0%
3 3
 
3.5%
7 3
 
3.5%
9 2
 
2.3%
4 1
 
1.2%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
47.7%
Latin 186
31.0%
Common 128
21.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 24
 
8.4%
이 18
 
6.3%
스 15
 
5.2%
시 13
 
4.5%
리 12
 
4.2%
트 9
 
3.1%
어 9
 
3.1%
플 8
 
2.8%
럭 8
 
2.8%
갤 8
 
2.8%
Other values (57) 162
56.6%
Latin
ValueCountFrequency (%)
O 22
 
11.8%
G 16
 
8.6%
S 11
 
5.9%
R 11
 
5.9%
I 9
 
4.8%
P 9
 
4.8%
L 8
 
4.3%
V 7
 
3.8%
p 7
 
3.8%
E 6
 
3.2%
Other values (27) 80
43.0%
Common
ValueCountFrequency (%)
42
32.8%
2 27
21.1%
0 26
20.3%
5 12
 
9.4%
1 12
 
9.4%
3 3
 
2.3%
7 3
 
2.3%
9 2
 
1.6%
4 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 314
52.3%
Hangul 286
47.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
 
13.4%
2 27
 
8.6%
0 26
 
8.3%
O 22
 
7.0%
G 16
 
5.1%
5 12
 
3.8%
1 12
 
3.8%
S 11
 
3.5%
R 11
 
3.5%
I 9
 
2.9%
Other values (36) 126
40.1%
Hangul
ValueCountFrequency (%)
북 24
 
8.4%
이 18
 
6.3%
스 15
 
5.2%
시 13
 
4.5%
리 12
 
4.2%
트 9
 
3.1%
어 9
 
3.1%
플 8
 
2.8%
럭 8
 
2.8%
갤 8
 
2.8%
Other values (57) 162
56.6%

BRTC_RATE
Real number (ℝ)

HIGH CORRELATION 

Distinct92
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9694
Minimum0.07
Maximum14.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:46:09.179767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.07
5-th percentile0.2385
Q10.785
median1.67
Q34.2025
95-th percentile8.869
Maximum14.14
Range14.07
Interquartile range (IQR)3.4175

Descriptive statistics

Standard deviation2.9245557
Coefficient of variation (CV)0.98489785
Kurtosis2.1745137
Mean2.9694
Median Absolute Deviation (MAD)1.28
Skewness1.5160617
Sum296.94
Variance8.5530259
MonotonicityNot monotonic
2023-12-10T15:46:09.388265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.67 3
 
3.0%
0.79 2
 
2.0%
1.45 2
 
2.0%
2.5 2
 
2.0%
1.18 2
 
2.0%
0.18 2
 
2.0%
0.69 2
 
2.0%
0.58 1
 
1.0%
0.19 1
 
1.0%
0.21 1
 
1.0%
Other values (82) 82
82.0%
ValueCountFrequency (%)
0.07 1
1.0%
0.18 2
2.0%
0.19 1
1.0%
0.21 1
1.0%
0.24 1
1.0%
0.29 1
1.0%
0.32 1
1.0%
0.33 1
1.0%
0.34 1
1.0%
0.35 1
1.0%
ValueCountFrequency (%)
14.14 1
1.0%
11.35 1
1.0%
11.23 1
1.0%
10.62 1
1.0%
9.04 1
1.0%
8.86 1
1.0%
8.3 1
1.0%
8.24 1
1.0%
7.77 1
1.0%
7.1 1
1.0%

TOTAL_BRAND_RATE
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.921
Minimum0.05
Maximum7.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:46:09.584799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile0.119
Q10.5175
median1.335
Q32.83
95-th percentile5.6345
Maximum7.51
Range7.46
Interquartile range (IQR)2.3125

Descriptive statistics

Standard deviation1.8558842
Coefficient of variation (CV)0.96610316
Kurtosis1.1698642
Mean1.921
Median Absolute Deviation (MAD)1.015
Skewness1.3101012
Sum192.1
Variance3.4443061
MonotonicityNot monotonic
2023-12-10T15:46:09.748335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.6 4
 
4.0%
2.7 4
 
4.0%
4.51 3
 
3.0%
7.51 3
 
3.0%
1.05 3
 
3.0%
0.45 3
 
3.0%
3.87 3
 
3.0%
0.52 3
 
3.0%
1.59 3
 
3.0%
0.16 3
 
3.0%
Other values (46) 68
68.0%
ValueCountFrequency (%)
0.05 1
 
1.0%
0.06 1
 
1.0%
0.09 2
2.0%
0.1 1
 
1.0%
0.12 1
 
1.0%
0.16 3
3.0%
0.18 1
 
1.0%
0.19 2
2.0%
0.2 1
 
1.0%
0.23 1
 
1.0%
ValueCountFrequency (%)
7.51 3
3.0%
6.29 2
2.0%
5.6 2
2.0%
5.03 2
2.0%
4.51 3
3.0%
4.13 2
2.0%
3.87 3
3.0%
3.36 2
2.0%
3.3 3
3.0%
3.22 3
3.0%

Interactions

2023-12-10T15:46:06.469619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:46:06.188421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:46:06.602485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:46:06.316016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:46:09.890211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BRTC_NMPRDUCT_BRAND_NMBRTC_RATETOTAL_BRAND_RATE
BRTC_NM1.0000.0000.5980.000
PRDUCT_BRAND_NM0.0001.0000.0001.000
BRTC_RATE0.5980.0001.0000.706
TOTAL_BRAND_RATE0.0001.0000.7061.000
2023-12-10T15:46:10.004288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BRTC_RATETOTAL_BRAND_RATEBRTC_NM
BRTC_RATE1.0000.6920.425
TOTAL_BRAND_RATE0.6921.0000.000
BRTC_NM0.4250.0001.000

Missing values

2023-12-10T15:46:06.773015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:46:06.952051image/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

PRDUCT_LCLAS_NMPRDUCT_MLSFC_NMYMQU_SE_VALUEBRTC_NMPRDUCT_BRAND_NMBRTC_RATETOTAL_BRAND_RATE
0컴퓨터노트북20200720203Q강원도갤럭시북 플렉스14.144.51
1컴퓨터노트북20200720203Q강원도게이밍11.231.6
2컴퓨터노트북20200720203Q강원도ROG10.623.3
3컴퓨터노트북20200720203Q강원도ROG STRIX G9.042.7
4컴퓨터노트북20200720203Q강원도파빌리온 게이밍8.30.23
5컴퓨터노트북20200720203Q강원도아스파이어57.11.4
6컴퓨터노트북20200720203Q강원도LEGION5.943.22
7컴퓨터노트북20200720203Q강원도씽크패드5.882.43
8컴퓨터노트북20200720203Q강원도아이디어패드4.97.51
9컴퓨터노트북20200720203Q강원도모던시리즈4.680.19
PRDUCT_LCLAS_NMPRDUCT_MLSFC_NMYMQU_SE_VALUEBRTC_NMPRDUCT_BRAND_NMBRTC_RATETOTAL_BRAND_RATE
90컴퓨터노트북20200720203Q경상남도LEGION3.183.22
91컴퓨터노트북20200720203Q경상남도ROG2.713.3
92컴퓨터노트북20200720203Q경상남도2020 맥북에어2.531.65
93컴퓨터노트북20200720203Q경상남도갤럭시북 이온2.382.7
94컴퓨터노트북20200720203Q경상남도아스파이어51.661.4
95컴퓨터노트북20200720203Q경상남도언더케이지1.480.76
96컴퓨터노트북20200720203Q경상남도HP1.471.59
97컴퓨터노트북20200720203Q경상남도파빌리온1.40.73
98컴퓨터노트북20200720203Q경상남도플렉스 51.320.45
99컴퓨터노트북20200720203Q경상남도노트북 플러스1.181.19