Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory76.3 B

Variable types

Categorical6
Text1
Numeric2

Dataset

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

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 BRTC_NMHigh correlation
BRTC_NM is highly overall correlated with BRTC_RATEHigh correlation

Reproduction

Analysis started2023-12-10 06:15:47.129448
Analysis finished2023-12-10 06:15:48.860868
Duration1.73 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

2023-12-10T15:15:48.957653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:49.108968image/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
모니터
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
모니터 100
100.0%

Length

2023-12-10T15:15:49.286728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:49.459587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
모니터 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

2023-12-10T15:15:49.610333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:49.748995image/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

2023-12-10T15:15:49.947957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:50.129397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20203q 100
100.0%

BRTC_NM
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기도
62 
강원도
38 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 62
62.0%
강원도 38
38.0%

Length

2023-12-10T15:15:50.311576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:50.482435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 62
62.0%
강원도 38
38.0%

PRDUCT_BRAND_NM
Categorical

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
LG전자
17 
삼성전자
15 
한성컴퓨터
12 
울트라기어
10 
크로스오버
5 
Other values (25)
41 

Length

Max length10
Median length7
Mean length4.38
Min length2

Unique

Unique15 ?
Unique (%)15.0%

Sample

1st row울트라기어
2nd rowLG전자
3rd rowLG전자
4th rowLG전자
5th row울트라기어

Common Values

ValueCountFrequency (%)
LG전자 17
17.0%
삼성전자 15
15.0%
한성컴퓨터 12
12.0%
울트라기어 10
 
10.0%
크로스오버 5
 
5.0%
필립스 4
 
4.0%
HP 3
 
3.0%
MSI 3
 
3.0%
AOC 3
 
3.0%
울트라 와이드 3
 
3.0%
Other values (20) 25
25.0%

Length

2023-12-10T15:15:50.700330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
lg전자 17
16.3%
삼성전자 15
14.4%
한성컴퓨터 12
11.5%
울트라기어 10
 
9.6%
크로스오버 5
 
4.8%
필립스 4
 
3.8%
hp 3
 
2.9%
msi 3
 
2.9%
aoc 3
 
2.9%
울트라 3
 
2.9%
Other values (22) 29
27.9%

PRDNM
Text

Distinct94
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T15:15:51.171564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length29
Mean length12.83
Min length4

Characters and Unicode

Total characters1283
Distinct characters100
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)88.0%

Sample

1st row34GN850
2nd row27UL650
3rd row40MB27HM
4th row32UK550
5th row27GN750
ValueCountFrequency (%)
hdr 17
 
7.2%
게이밍 12
 
5.1%
144 8
 
3.4%
리얼 7
 
3.0%
시력보호 6
 
2.5%
4k 6
 
2.5%
ips 5
 
2.1%
커브드 5
 
2.1%
프리싱크 4
 
1.7%
ultron 4
 
1.7%
Other values (131) 162
68.6%
2023-12-10T15:15:51.827252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
 
10.6%
2 82
 
6.4%
0 80
 
6.2%
4 60
 
4.7%
5 53
 
4.1%
3 51
 
4.0%
7 49
 
3.8%
1 45
 
3.5%
H 35
 
2.7%
D 35
 
2.7%
Other values (90) 657
51.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 474
36.9%
Uppercase Letter 432
33.7%
Other Letter 213
16.6%
Space Separator 136
 
10.6%
Lowercase Letter 22
 
1.7%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 21
 
9.9%
이 20
 
9.4%
게 12
 
5.6%
밍 12
 
5.6%
보 10
 
4.7%
스 9
 
4.2%
얼 9
 
4.2%
드 8
 
3.8%
시 7
 
3.3%
터 6
 
2.8%
Other values (41) 99
46.5%
Uppercase Letter
ValueCountFrequency (%)
H 35
 
8.1%
D 35
 
8.1%
G 33
 
7.6%
R 32
 
7.4%
F 30
 
6.9%
U 28
 
6.5%
T 23
 
5.3%
M 20
 
4.6%
K 19
 
4.4%
L 19
 
4.4%
Other values (16) 158
36.6%
Lowercase Letter
ValueCountFrequency (%)
i 4
18.2%
y 3
13.6%
e 3
13.6%
w 3
13.6%
l 2
9.1%
s 2
9.1%
h 1
 
4.5%
f 1
 
4.5%
a 1
 
4.5%
p 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
2 82
17.3%
0 80
16.9%
4 60
12.7%
5 53
11.2%
3 51
10.8%
7 49
10.3%
1 45
9.5%
6 21
 
4.4%
9 17
 
3.6%
8 16
 
3.4%
Space Separator
ValueCountFrequency (%)
136
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 616
48.0%
Latin 454
35.4%
Hangul 213
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 21
 
9.9%
이 20
 
9.4%
게 12
 
5.6%
밍 12
 
5.6%
보 10
 
4.7%
스 9
 
4.2%
얼 9
 
4.2%
드 8
 
3.8%
시 7
 
3.3%
터 6
 
2.8%
Other values (41) 99
46.5%
Latin
ValueCountFrequency (%)
H 35
 
7.7%
D 35
 
7.7%
G 33
 
7.3%
R 32
 
7.0%
F 30
 
6.6%
U 28
 
6.2%
T 23
 
5.1%
M 20
 
4.4%
K 19
 
4.2%
L 19
 
4.2%
Other values (27) 180
39.6%
Common
ValueCountFrequency (%)
136
22.1%
2 82
13.3%
0 80
13.0%
4 60
9.7%
5 53
 
8.6%
3 51
 
8.3%
7 49
 
8.0%
1 45
 
7.3%
6 21
 
3.4%
9 17
 
2.8%
Other values (2) 22
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1070
83.4%
Hangul 213
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
 
12.7%
2 82
 
7.7%
0 80
 
7.5%
4 60
 
5.6%
5 53
 
5.0%
3 51
 
4.8%
7 49
 
4.6%
1 45
 
4.2%
H 35
 
3.3%
D 35
 
3.3%
Other values (39) 444
41.5%
Hangul
ValueCountFrequency (%)
리 21
 
9.9%
이 20
 
9.4%
게 12
 
5.6%
밍 12
 
5.6%
보 10
 
4.7%
스 9
 
4.2%
얼 9
 
4.2%
드 8
 
3.8%
시 7
 
3.3%
터 6
 
2.8%
Other values (41) 99
46.5%

BRTC_RATE
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6723
Minimum0.2
Maximum12.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:15:52.047485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.629
Q10.72
median1.07
Q32.04
95-th percentile4.286
Maximum12.11
Range11.91
Interquartile range (IQR)1.32

Descriptive statistics

Standard deviation1.5559841
Coefficient of variation (CV)0.93044556
Kurtosis19.714225
Mean1.6723
Median Absolute Deviation (MAD)0.42
Skewness3.5386197
Sum167.23
Variance2.4210866
MonotonicityNot monotonic
2023-12-10T15:15:52.255061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7 9
 
9.0%
0.65 3
 
3.0%
0.67 3
 
3.0%
0.77 3
 
3.0%
1.18 2
 
2.0%
0.81 2
 
2.0%
1.05 2
 
2.0%
0.96 2
 
2.0%
1.93 2
 
2.0%
1.95 2
 
2.0%
Other values (61) 70
70.0%
ValueCountFrequency (%)
0.2 1
 
1.0%
0.31 1
 
1.0%
0.35 1
 
1.0%
0.55 1
 
1.0%
0.61 1
 
1.0%
0.63 2
2.0%
0.64 1
 
1.0%
0.65 3
3.0%
0.67 3
3.0%
0.68 1
 
1.0%
ValueCountFrequency (%)
12.11 1
1.0%
5.18 1
1.0%
4.84 1
1.0%
4.42 1
1.0%
4.4 1
1.0%
4.28 1
1.0%
4.13 1
1.0%
3.69 1
1.0%
3.67 1
1.0%
3.62 1
1.0%

TOTAL_PRDUCT_RATE
Real number (ℝ)

Distinct62
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5925
Minimum0.01
Maximum3.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:15:52.480721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.08
Q10.19
median0.35
Q30.695
95-th percentile2.274
Maximum3.27
Range3.26
Interquartile range (IQR)0.505

Descriptive statistics

Standard deviation0.66888778
Coefficient of variation (CV)1.1289245
Kurtosis4.5871365
Mean0.5925
Median Absolute Deviation (MAD)0.175
Skewness2.2008335
Sum59.25
Variance0.44741086
MonotonicityNot monotonic
2023-12-10T15:15:52.742921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.19 8
 
8.0%
0.2 4
 
4.0%
0.37 3
 
3.0%
0.21 3
 
3.0%
0.3 3
 
3.0%
0.35 3
 
3.0%
0.28 3
 
3.0%
2.0 2
 
2.0%
0.08 2
 
2.0%
0.26 2
 
2.0%
Other values (52) 67
67.0%
ValueCountFrequency (%)
0.01 1
1.0%
0.04 1
1.0%
0.05 1
1.0%
0.07 1
1.0%
0.08 2
2.0%
0.09 1
1.0%
0.1 1
1.0%
0.11 1
1.0%
0.12 1
1.0%
0.13 2
2.0%
ValueCountFrequency (%)
3.27 1
1.0%
2.75 2
2.0%
2.54 2
2.0%
2.26 1
1.0%
2.0 2
2.0%
1.5 1
1.0%
1.44 2
2.0%
1.35 1
1.0%
1.29 1
1.0%
1.2 1
1.0%

Interactions

2023-12-10T15:15:48.201902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:47.885301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:48.357236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:48.044991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:15:52.884578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BRTC_NMPRDUCT_BRAND_NMPRDNMBRTC_RATETOTAL_PRDUCT_RATE
BRTC_NM1.0000.1850.0000.8020.138
PRDUCT_BRAND_NM0.1851.0001.0000.0000.000
PRDNM0.0001.0001.0000.0001.000
BRTC_RATE0.8020.0000.0001.0000.770
TOTAL_PRDUCT_RATE0.1380.0001.0000.7701.000
2023-12-10T15:15:53.014259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BRTC_NMPRDUCT_BRAND_NM
BRTC_NM1.0000.112
PRDUCT_BRAND_NM0.1121.000
2023-12-10T15:15:53.123928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
BRTC_RATETOTAL_PRDUCT_RATEBRTC_NMPRDUCT_BRAND_NM
BRTC_RATE1.0000.1440.5940.000
TOTAL_PRDUCT_RATE0.1441.0000.1300.000
BRTC_NM0.5940.1301.0000.112
PRDUCT_BRAND_NM0.0000.0000.1121.000

Missing values

2023-12-10T15:15:48.548769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:15:48.766615image/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_NMPRDNMBRTC_RATETOTAL_PRDUCT_RATE
0컴퓨터모니터20200720203Q강원도울트라기어34GN85012.112.0
1컴퓨터모니터20200720203Q강원도LG전자27UL6504.840.86
2컴퓨터모니터20200720203Q강원도LG전자40MB27HM4.420.16
3컴퓨터모니터20200720203Q강원도LG전자32UK5504.42.54
4컴퓨터모니터20200720203Q강원도울트라기어27GN7504.281.44
5컴퓨터모니터20200720203Q강원도크로스오버400UK30 UHD 리얼 4K HDR4.130.15
6컴퓨터모니터20200720203Q강원도LG전자43MN59HM3.690.14
7컴퓨터모니터20200720203Q강원도주연테크캐리뷰 V15UPG3.670.13
8컴퓨터모니터20200720203Q강원도삼성전자LH43DCJPLGA3.620.42
9컴퓨터모니터20200720203Q강원도삼성전자S27F3503.590.34
PRDUCT_LCLAS_NMPRDUCT_MLSFC_NMYMQU_SE_VALUEBRTC_NMPRDUCT_BRAND_NMPRDNMBRTC_RATETOTAL_PRDUCT_RATE
90컴퓨터모니터20200720203Q경기도삼성전자S24D3000.670.4
91컴퓨터모니터20200720203Q경기도AOC24B1 보더리스 IPS 시력보호0.670.36
92컴퓨터모니터20200720203Q경기도AOC27B2 보더리스 75 시력보호0.670.3
93컴퓨터모니터20200720203Q경기도울트라 와이드34WK6500.650.74
94컴퓨터모니터20200720203Q경기도필립스243S IPS 시력보호 피벗 높낮이0.650.34
95컴퓨터모니터20200720203Q경기도AOC2777 IPS 75 프리싱크 시력보호0.650.17
96컴퓨터모니터20200720203Q경기도한성컴퓨터TFX133T DEX 포터블 HDR0.640.41
97컴퓨터모니터20200720203Q경기도인터픽셀IP27400.630.39
98컴퓨터모니터20200720203Q경기도LG전자32MN58HMW0.630.17
99컴퓨터모니터20200720203Q경기도크로스오버32UL980M HDR 4K 프리미엄 멀티0.610.16