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

Categorical10
Numeric2

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGICLEANER

Alerts

MT has constant value ""Constant
청소기 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
2 has constant value ""Constant
다이슨 has constant value ""Constant
20 is highly overall correlated with 201801High correlation
201801 is highly overall correlated with 20High correlation
전체.2 is highly overall correlated with 전체.3High correlation
전체.3 is highly overall correlated with 전체.2High correlation

Reproduction

Analysis started2023-12-10 06:55:38.391292
Analysis finished2023-12-10 06:55:39.317118
Duration0.93 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

2023-12-10T15:55:39.377974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:39.461061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201801
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201801
63 
201806
36 

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 63
63.6%
201806 36
36.4%

Length

2023-12-10T15:55:39.552177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:39.649315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201801 63
63.6%
201806 36
36.4%

104
Real number (ℝ)

Distinct82
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.85859
Minimum23
Maximum361
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:55:39.756942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile38.9
Q166
median89
Q3139
95-th percentile229.9
Maximum361
Range338
Interquartile range (IQR)73

Descriptive statistics

Standard deviation65.188739
Coefficient of variation (CV)0.59883874
Kurtosis3.4163748
Mean108.85859
Median Absolute Deviation (MAD)33
Skewness1.6377485
Sum10777
Variance4249.5716
MonotonicityNot monotonic
2023-12-10T15:55:39.899836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71 3
 
3.0%
85 2
 
2.0%
80 2
 
2.0%
131 2
 
2.0%
60 2
 
2.0%
81 2
 
2.0%
41 2
 
2.0%
65 2
 
2.0%
180 2
 
2.0%
64 2
 
2.0%
Other values (72) 78
78.8%
ValueCountFrequency (%)
23 1
1.0%
29 1
1.0%
33 1
1.0%
34 1
1.0%
38 1
1.0%
39 1
1.0%
41 2
2.0%
43 1
1.0%
45 1
1.0%
48 1
1.0%
ValueCountFrequency (%)
361 1
1.0%
356 1
1.0%
297 1
1.0%
252 1
1.0%
238 1
1.0%
229 1
1.0%
214 1
1.0%
199 1
1.0%
193 1
1.0%
191 1
1.0%

45
Real number (ℝ)

Distinct60
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.939394
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:55:40.068629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile15.8
Q130
median44
Q363.5
95-th percentile94.5
Maximum100
Range90
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation23.3504
Coefficient of variation (CV)0.47712892
Kurtosis-0.4351976
Mean48.939394
Median Absolute Deviation (MAD)16
Skewness0.53826273
Sum4845
Variance545.24119
MonotonicityNot monotonic
2023-12-10T15:55:40.202214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 5
 
5.1%
100 4
 
4.0%
41 4
 
4.0%
28 3
 
3.0%
40 3
 
3.0%
43 3
 
3.0%
52 3
 
3.0%
60 3
 
3.0%
29 3
 
3.0%
20 3
 
3.0%
Other values (50) 65
65.7%
ValueCountFrequency (%)
10 1
 
1.0%
11 1
 
1.0%
12 2
2.0%
14 1
 
1.0%
16 1
 
1.0%
19 1
 
1.0%
20 3
3.0%
21 2
2.0%
24 1
 
1.0%
25 1
 
1.0%
ValueCountFrequency (%)
100 4
4.0%
99 1
 
1.0%
94 1
 
1.0%
92 1
 
1.0%
88 2
2.0%
87 1
 
1.0%
86 1
 
1.0%
81 2
2.0%
77 1
 
1.0%
74 1
 
1.0%

청소기
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청소기 99
100.0%

Length

2023-12-10T15:55:40.323915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:40.410151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소기 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

2023-12-10T15:55:40.502063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:40.584736image/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

2023-12-10T15:55:40.672052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:40.757137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
99 

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 99
100.0%

Length

2023-12-10T15:55:40.843248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:40.938649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 99
100.0%

20
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
30
41 
50
35 
20
22 
40
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row20
2nd row20
3rd row20
4th row20
5th row20

Common Values

ValueCountFrequency (%)
30 41
41.4%
50 35
35.4%
20 22
22.2%
40 1
 
1.0%

Length

2023-12-10T15:55:41.038481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:41.139845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 41
41.4%
50 35
35.4%
20 22
22.2%
40 1
 
1.0%

전체.2
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
17 
서울특별시
13 
인천광역시
7 
광주광역시
7 
울산광역시
7 
Other values (11)
48 

Length

Max length7
Median length5
Mean length4.4141414
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row부산광역시

Common Values

ValueCountFrequency (%)
경기도 17
17.2%
서울특별시 13
13.1%
인천광역시 7
 
7.1%
광주광역시 7
 
7.1%
울산광역시 7
 
7.1%
강원도 7
 
7.1%
대구광역시 6
 
6.1%
충청남도 6
 
6.1%
부산광역시 5
 
5.1%
제주특별자치도 5
 
5.1%
Other values (6) 19
19.2%

Length

2023-12-10T15:55:41.247542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 17
17.2%
서울특별시 13
13.1%
인천광역시 7
 
7.1%
광주광역시 7
 
7.1%
울산광역시 7
 
7.1%
강원도 7
 
7.1%
대구광역시 6
 
6.1%
충청남도 6
 
6.1%
부산광역시 5
 
5.1%
제주특별자치도 5
 
5.1%
Other values (6) 19
19.2%

전체.3
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
12 
서구
 
6
북구
 
6
화성시
 
3
서초구
 
3
Other values (33)
69 

Length

Max length4
Median length3
Mean length2.7676768
Min length2

Unique

Unique8 ?
Unique (%)8.1%

Sample

1st row도봉구
2nd row양천구
3rd row서초구
4th row강남구
5th row부산진구

Common Values

ValueCountFrequency (%)
전체 12
 
12.1%
서구 6
 
6.1%
북구 6
 
6.1%
화성시 3
 
3.0%
서초구 3
 
3.0%
강남구 3
 
3.0%
부산진구 3
 
3.0%
수성구 3
 
3.0%
구리시 3
 
3.0%
광산구 3
 
3.0%
Other values (28) 54
54.5%

Length

2023-12-10T15:55:41.376934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 12
 
12.1%
북구 6
 
6.1%
서구 6
 
6.1%
광산구 3
 
3.0%
도봉구 3
 
3.0%
양천구 3
 
3.0%
제주시 3
 
3.0%
천안시 3
 
3.0%
양주시 3
 
3.0%
원주시 3
 
3.0%
Other values (28) 54
54.5%

다이슨
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다이슨 99
100.0%

Length

2023-12-10T15:55:41.505578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:55:41.588636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다이슨 99
100.0%

Interactions

2023-12-10T15:55:38.917157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:38.765252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:38.997931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:55:38.842540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:55:41.644975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018011044520전체.2전체.3
2018011.0000.0740.3121.0000.0000.000
1040.0741.0000.2900.0000.1930.544
450.3120.2901.0000.3630.0000.000
201.0000.0000.3631.0000.0000.000
전체.20.0000.1930.0000.0001.0000.975
전체.30.0000.5440.0000.0000.9751.000
2023-12-10T15:55:41.765278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
20201801전체.3전체.2
201.0000.9900.0000.000
2018010.9901.0000.0000.000
전체.30.0000.0001.0000.661
전체.20.0000.0000.6611.000
2023-12-10T15:55:41.876377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1044520180120전체.2전체.3
1041.0000.4540.0650.0000.0660.180
450.4541.0000.2080.1900.0000.000
2018010.0650.2081.0000.9900.0000.000
200.0000.1900.9901.0000.0000.000
전체.20.0660.0000.0000.0001.0000.661
전체.30.1800.0000.0000.0000.6611.000

Missing values

2023-12-10T15:55:39.107980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:55:39.263608image/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

MT20180110445청소기전체전체.1220전체.2전체.3다이슨
0MT2018014560청소기전체전체220서울특별시도봉구다이슨
1MT20180116663청소기전체전체220서울특별시양천구다이슨
2MT20180110188청소기전체전체220서울특별시서초구다이슨
3MT2018012374청소기전체전체220서울특별시강남구다이슨
4MT20180123892청소기전체전체220부산광역시부산진구다이슨
5MT2018019047청소기전체전체220대구광역시북구다이슨
6MT2018017771청소기전체전체220대구광역시수성구다이슨
7MT20180110668청소기전체전체220인천광역시중구다이슨
8MT20180110630청소기전체전체220인천광역시서구다이슨
9MT20180152100청소기전체전체220광주광역시서구다이슨
MT20180110445청소기전체전체.1220전체.2전체.3다이슨
89MT2018068864청소기전체전체250강원도원주시다이슨
90MT2018065830청소기전체전체250강원도속초시다이슨
91MT2018068033청소기전체전체250충청북도증평군다이슨
92MT20180615544청소기전체전체250충청남도천안시다이슨
93MT20180614481청소기전체전체250충청남도보령시다이슨
94MT2018066030청소기전체전체250전라북도전주시다이슨
95MT2018069131청소기전체전체250전라북도군산시다이슨
96MT2018068041청소기전체전체250경상북도포항시다이슨
97MT20180619352청소기전체전체250경상북도경주시다이슨
98MT2018069829청소기전체전체250경상북도안동시다이슨