Overview

Dataset statistics

Number of variables4
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory35.3 B

Variable types

Categorical2
Text1
Numeric1

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO033TURNOVER

Alerts

MT has constant value ""Constant
1.55 has 8 (8.1%) zerosZeros

Reproduction

Analysis started2023-12-10 06:36:31.492687
Analysis finished2023-12-10 06:36:32.230524
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

MT
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
MT
99 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
MT 99
100.0%

Length

2023-12-10T15:36:32.337739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:32.478052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201901
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201901
79 
201902
20 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201901
2nd row201901
3rd row201901
4th row201901
5th row201901

Common Values

ValueCountFrequency (%)
201901 79
79.8%
201902 20
 
20.2%

Length

2023-12-10T15:36:32.670215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:36:32.860842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201901 79
79.8%
201902 20
 
20.2%

맥주
Text

Distinct80
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-10T15:36:33.289055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.0606061
Min length1

Characters and Unicode

Total characters402
Distinct characters148
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

Unique61 ?
Unique (%)61.6%

Sample

1st row소주
2nd row전통주
3rd row와인
4th row양주
5th row커피
ValueCountFrequency (%)
소주 2
 
2.0%
흰우유 2
 
2.0%
분유류 2
 
2.0%
전통주 2
 
2.0%
가공유 2
 
2.0%
식품 2
 
2.0%
유아용 2
 
2.0%
아이스크림 2
 
2.0%
유제품 2
 
2.0%
발효유류 2
 
2.0%
Other values (71) 81
80.2%
2023-12-10T15:36:33.953061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 25
 
6.2%
품 20
 
5.0%
유 17
 
4.2%
류 15
 
3.7%
/ 13
 
3.2%
식 10
 
2.5%
주 10
 
2.5%
용 9
 
2.2%
제 8
 
2.0%
음 8
 
2.0%
Other values (138) 267
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 380
94.5%
Other Punctuation 13
 
3.2%
Uppercase Letter 7
 
1.7%
Space Separator 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 25
 
6.6%
품 20
 
5.3%
유 17
 
4.5%
류 15
 
3.9%
식 10
 
2.6%
주 10
 
2.6%
용 9
 
2.4%
제 8
 
2.1%
음 8
 
2.1%
료 8
 
2.1%
Other values (129) 250
65.8%
Uppercase Letter
ValueCountFrequency (%)
Y 1
14.3%
I 1
14.3%
D 1
14.3%
C 1
14.3%
V 1
14.3%
T 1
14.3%
P 1
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 13
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 380
94.5%
Common 15
 
3.7%
Latin 7
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 25
 
6.6%
품 20
 
5.3%
유 17
 
4.5%
류 15
 
3.9%
식 10
 
2.6%
주 10
 
2.6%
용 9
 
2.4%
제 8
 
2.1%
음 8
 
2.1%
료 8
 
2.1%
Other values (129) 250
65.8%
Latin
ValueCountFrequency (%)
Y 1
14.3%
I 1
14.3%
D 1
14.3%
C 1
14.3%
V 1
14.3%
T 1
14.3%
P 1
14.3%
Common
ValueCountFrequency (%)
/ 13
86.7%
2
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 380
94.5%
ASCII 22
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 25
 
6.6%
품 20
 
5.3%
유 17
 
4.5%
류 15
 
3.9%
식 10
 
2.6%
주 10
 
2.6%
용 9
 
2.4%
제 8
 
2.1%
음 8
 
2.1%
료 8
 
2.1%
Other values (129) 250
65.8%
ASCII
ValueCountFrequency (%)
/ 13
59.1%
2
 
9.1%
Y 1
 
4.5%
I 1
 
4.5%
D 1
 
4.5%
C 1
 
4.5%
V 1
 
4.5%
T 1
 
4.5%
P 1
 
4.5%

1.55
Real number (ℝ)

ZEROS 

Distinct81
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5008081
Minimum0
Maximum27.43
Zeros8
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:36:34.205445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.115
median0.74
Q32.215
95-th percentile9.749
Maximum27.43
Range27.43
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation4.3395412
Coefficient of variation (CV)1.7352556
Kurtosis12.108696
Mean2.5008081
Median Absolute Deviation (MAD)0.72
Skewness3.1028804
Sum247.58
Variance18.831618
MonotonicityNot monotonic
2023-12-10T15:36:34.438778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
8.1%
0.02 4
 
4.0%
0.04 3
 
3.0%
0.03 2
 
2.0%
0.11 2
 
2.0%
0.01 2
 
2.0%
0.12 2
 
2.0%
0.5 2
 
2.0%
0.72 2
 
2.0%
1.98 1
 
1.0%
Other values (71) 71
71.7%
ValueCountFrequency (%)
0.0 8
8.1%
0.01 2
 
2.0%
0.02 4
4.0%
0.03 2
 
2.0%
0.04 3
 
3.0%
0.06 1
 
1.0%
0.07 1
 
1.0%
0.09 1
 
1.0%
0.1 1
 
1.0%
0.11 2
 
2.0%
ValueCountFrequency (%)
27.43 1
1.0%
16.6 1
1.0%
15.34 1
1.0%
15.33 1
1.0%
10.1 1
1.0%
9.71 1
1.0%
8.79 1
1.0%
8.77 1
1.0%
8.65 1
1.0%
8.55 1
1.0%

Interactions

2023-12-10T15:36:31.849809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:36:34.612633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201901맥주1.55
2019011.0000.0000.135
맥주0.0001.0000.803
1.550.1350.8031.000
2023-12-10T15:36:34.755906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1.55201901
1.551.0000.138
2019010.1381.000

Missing values

2023-12-10T15:36:32.038797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:36:32.179018image/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

MT201901맥주1.55
0MT201901소주0.03
1MT201901전통주0.02
2MT201901와인1.13
3MT201901양주15.33
4MT201901커피0.7
5MT201901탄산음료0.0
6MT201901과채류음료0.22
7MT201901물0.04
8MT201901차0.36
9MT201901기능성음료2.07
MT201901맥주1.55
89MT201902기능성음료2.21
90MT201902두유0.02
91MT201902흰우유0.0
92MT201902가공유2.68
93MT201902발효유류1.83
94MT201902유제품0.45
95MT201902아이스크림0.13
96MT201902분유류0.0
97MT201902유아용 식품1.68
98MT201902냉장고0.71