Overview

Dataset statistics

Number of variables12
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory102.3 B

Variable types

Categorical9
Numeric3

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGIWINE

Alerts

MT has constant value ""Constant
201801 has constant value ""Constant
와인 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
금양인터내셔널 1865 has constant value ""Constant
2 is highly imbalanced (52.8%)Imbalance

Reproduction

Analysis started2023-12-10 06:44:20.242005
Analysis finished2023-12-10 06:44:22.358009
Duration2.12 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

2023-12-10T15:44:22.513082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:22.645810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201801
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201801
99 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201801
2nd row201801
3rd row201801
4th row201801
5th row201801

Common Values

ValueCountFrequency (%)
201801 99
100.0%

Length

2023-12-10T15:44:22.798831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:22.943730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201801 99
100.0%

141
Real number (ℝ)

Distinct63
Distinct (%)63.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.878788
Minimum11
Maximum245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:44:23.103710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile17.9
Q138
median64
Q396
95-th percentile140.6
Maximum245
Range234
Interquartile range (IQR)58

Descriptive statistics

Standard deviation44.227213
Coefficient of variation (CV)0.64210208
Kurtosis2.8933489
Mean68.878788
Median Absolute Deviation (MAD)30
Skewness1.3853403
Sum6819
Variance1956.0464
MonotonicityNot monotonic
2023-12-10T15:44:23.340967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 5
 
5.1%
19 4
 
4.0%
38 4
 
4.0%
44 4
 
4.0%
26 3
 
3.0%
65 3
 
3.0%
138 2
 
2.0%
50 2
 
2.0%
101 2
 
2.0%
67 2
 
2.0%
Other values (53) 68
68.7%
ValueCountFrequency (%)
11 1
 
1.0%
14 1
 
1.0%
15 1
 
1.0%
16 1
 
1.0%
17 1
 
1.0%
18 2
2.0%
19 4
4.0%
22 1
 
1.0%
24 1
 
1.0%
25 2
2.0%
ValueCountFrequency (%)
245 1
1.0%
229 1
1.0%
173 1
1.0%
166 1
1.0%
146 1
1.0%
140 1
1.0%
138 2
2.0%
127 1
1.0%
126 1
1.0%
118 1
1.0%

38
Real number (ℝ)

Distinct42
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.828283
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:44:23.552280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q19
median17
Q324
95-th percentile64.5
Maximum100
Range99
Interquartile range (IQR)15

Descriptive statistics

Standard deviation18.475599
Coefficient of variation (CV)0.8870438
Kurtosis4.090822
Mean20.828283
Median Absolute Deviation (MAD)8
Skewness1.8806125
Sum2062
Variance341.34776
MonotonicityNot monotonic
2023-12-10T15:44:23.795087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
10 8
 
8.1%
18 6
 
6.1%
19 6
 
6.1%
24 5
 
5.1%
9 5
 
5.1%
6 4
 
4.0%
2 4
 
4.0%
17 4
 
4.0%
8 4
 
4.0%
41 3
 
3.0%
Other values (32) 50
50.5%
ValueCountFrequency (%)
1 1
 
1.0%
2 4
4.0%
3 3
 
3.0%
4 3
 
3.0%
5 2
 
2.0%
6 4
4.0%
7 3
 
3.0%
8 4
4.0%
9 5
5.1%
10 8
8.1%
ValueCountFrequency (%)
100 1
 
1.0%
77 1
 
1.0%
75 1
 
1.0%
69 2
2.0%
64 1
 
1.0%
51 1
 
1.0%
49 1
 
1.0%
48 1
 
1.0%
41 3
3.0%
40 1
 
1.0%

와인
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
와인 99
100.0%

Length

2023-12-10T15:44:23.991731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:24.135613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
와인 99
100.0%

전체
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 99
100.0%

Length

2023-12-10T15:44:24.278383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:24.407854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

전체.1
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전체 99
100.0%

Length

2023-12-10T15:44:24.558800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:24.697143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
89 
1
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 89
89.9%
1 10
 
10.1%

Length

2023-12-10T15:44:24.851281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:25.014871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 89
89.9%
1 10
 
10.1%

20
Real number (ℝ)

Distinct6
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.777778
Minimum20
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:44:25.178032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q130
median30
Q340
95-th percentile60
Maximum70
Range50
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.478067
Coefficient of variation (CV)0.3038312
Kurtosis0.51491882
Mean37.777778
Median Absolute Deviation (MAD)10
Skewness0.94462647
Sum3740
Variance131.74603
MonotonicityNot monotonic
2023-12-10T15:44:25.330226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
30 45
45.5%
40 25
25.3%
50 14
 
14.1%
20 6
 
6.1%
60 6
 
6.1%
70 3
 
3.0%
ValueCountFrequency (%)
20 6
 
6.1%
30 45
45.5%
40 25
25.3%
50 14
 
14.1%
60 6
 
6.1%
70 3
 
3.0%
ValueCountFrequency (%)
70 3
 
3.0%
60 6
 
6.1%
50 14
 
14.1%
40 25
25.3%
30 45
45.5%
20 6
 
6.1%

충청북도
Categorical

Distinct12
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
23 
서울특별시
16 
부산광역시
12 
경상남도
8 
광주광역시
8 
Other values (7)
32 

Length

Max length5
Median length5
Mean length4.2727273
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도
2nd row경상남도
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
경기도 23
23.2%
서울특별시 16
16.2%
부산광역시 12
12.1%
경상남도 8
 
8.1%
광주광역시 8
 
8.1%
충청북도 8
 
8.1%
대전광역시 6
 
6.1%
대구광역시 5
 
5.1%
경상북도 4
 
4.0%
전라북도 4
 
4.0%
Other values (2) 5
 
5.1%

Length

2023-12-10T15:44:25.496409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 23
23.2%
서울특별시 16
16.2%
부산광역시 12
12.1%
경상남도 8
 
8.1%
광주광역시 8
 
8.1%
충청북도 8
 
8.1%
대전광역시 6
 
6.1%
대구광역시 5
 
5.1%
경상북도 4
 
4.0%
전라북도 4
 
4.0%
Other values (2) 5
 
5.1%

전체.2
Categorical

Distinct40
Distinct (%)40.4%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
29 
수원시
6 
북구
 
5
동구
 
4
통영시
 
4
Other values (35)
51 

Length

Max length4
Median length3
Mean length2.6262626
Min length2

Unique

Unique24 ?
Unique (%)24.2%

Sample

1st row전체
2nd row통영시
3rd row동대문구
4th row강북구
5th row은평구

Common Values

ValueCountFrequency (%)
전체 29
29.3%
수원시 6
 
6.1%
북구 5
 
5.1%
동구 4
 
4.0%
통영시 4
 
4.0%
시흥시 4
 
4.0%
중구 3
 
3.0%
성남시 3
 
3.0%
고양시 3
 
3.0%
강서구 2
 
2.0%
Other values (30) 36
36.4%

Length

2023-12-10T15:44:25.737167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 29
29.3%
수원시 6
 
6.1%
북구 5
 
5.1%
동구 4
 
4.0%
통영시 4
 
4.0%
시흥시 4
 
4.0%
중구 3
 
3.0%
성남시 3
 
3.0%
고양시 3
 
3.0%
영등포구 2
 
2.0%
Other values (30) 36
36.4%

금양인터내셔널 1865
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
금양인터내셔널 1865
99 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row금양인터내셔널 1865
2nd row금양인터내셔널 1865
3rd row금양인터내셔널 1865
4th row금양인터내셔널 1865
5th row금양인터내셔널 1865

Common Values

ValueCountFrequency (%)
금양인터내셔널 1865 99
100.0%

Length

2023-12-10T15:44:25.951040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:44:26.107491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금양인터내셔널 99
50.0%
1865 99
50.0%

Interactions

2023-12-10T15:44:21.607621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:20.765656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:21.176437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:21.733633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:20.895890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:21.303453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:21.856487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:21.032238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:44:21.452164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:44:26.213374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
14138220충청북도전체.2
1411.0000.4670.0000.0000.1490.761
380.4671.0000.1860.4550.4870.774
20.0000.1861.0000.3760.0000.000
200.0000.4550.3761.0000.0000.000
충청북도0.1490.4870.0000.0001.0000.886
전체.20.7610.7740.0000.0000.8861.000
2023-12-10T15:44:26.381709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충청북도2전체.2
충청북도1.0000.0000.428
20.0001.0000.000
전체.20.4280.0001.000
2023-12-10T15:44:26.529214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
14138202충청북도전체.2
1411.0000.393-0.0550.0000.0510.304
380.3931.000-0.0470.1770.2240.328
20-0.055-0.0471.0000.2640.0000.000
20.0000.1770.2641.0000.0000.000
충청북도0.0510.2240.0000.0001.0000.428
전체.20.3040.3280.0000.0000.4281.000

Missing values

2023-12-10T15:44:22.030991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:44:22.275042image/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

MT20180114138와인전체전체.1220충청북도전체.2금양인터내셔널 1865
0MT2018012524와인전체전체220경상북도전체금양인터내셔널 1865
1MT2018017969와인전체전체220경상남도통영시금양인터내셔널 1865
2MT2018017914와인전체전체230서울특별시동대문구금양인터내셔널 1865
3MT201801496와인전체전체230서울특별시강북구금양인터내셔널 1865
4MT201801712와인전체전체230서울특별시은평구금양인터내셔널 1865
5MT2018017634와인전체전체230서울특별시금천구금양인터내셔널 1865
6MT201801162와인전체전체230서울특별시영등포구금양인터내셔널 1865
7MT201801159와인전체전체230부산광역시북구금양인터내셔널 1865
8MT201801100100와인전체전체230부산광역시수영구금양인터내셔널 1865
9MT2018016830와인전체전체230광주광역시전체금양인터내셔널 1865
MT20180114138와인전체전체.1220충청북도전체.2금양인터내셔널 1865
89MT201801539와인전체전체240서울특별시용산구금양인터내셔널 1865
90MT2018011008와인전체전체240서울특별시성북구금양인터내셔널 1865
91MT2018017310와인전체전체240서울특별시노원구금양인터내셔널 1865
92MT201801174와인전체전체240서울특별시강서구금양인터내셔널 1865
93MT2018018718와인전체전체240서울특별시송파구금양인터내셔널 1865
94MT2018013810와인전체전체240부산광역시전체금양인터내셔널 1865
95MT2018015341와인전체전체240부산광역시중구금양인터내셔널 1865
96MT2018011912와인전체전체240부산광역시동래구금양인터내셔널 1865
97MT20180110117와인전체전체240대구광역시전체금양인터내셔널 1865
98MT201801398와인전체전체240인천광역시전체금양인터내셔널 1865