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=ZTO010BSICGIPURIFIER

Alerts

MT has constant value ""Constant
정수기 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
엘지전자 has constant value ""Constant
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 06:57:26.001124
Analysis finished2023-12-10 06:57:27.429214
Duration1.43 second
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

2023-12-10T15:57:27.489131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:27.581255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201808
Categorical

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
201808
35 
201801
33 
201802
15 
201806
13 
201804
 
3

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201808
2nd row201808
3rd row201808
4th row201808
5th row201808

Common Values

ValueCountFrequency (%)
201808 35
35.4%
201801 33
33.3%
201802 15
15.2%
201806 13
 
13.1%
201804 3
 
3.0%

Length

2023-12-10T15:57:27.680264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:27.789516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201808 35
35.4%
201801 33
33.3%
201802 15
15.2%
201806 13
 
13.1%
201804 3
 
3.0%

95
Real number (ℝ)

Distinct56
Distinct (%)56.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.62626
Minimum17
Maximum286
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:57:27.922036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile56.3
Q189.5
median100
Q3130
95-th percentile166.3
Maximum286
Range269
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation38.578726
Coefficient of variation (CV)0.3618126
Kurtosis4.2289386
Mean106.62626
Median Absolute Deviation (MAD)25
Skewness1.1839304
Sum10556
Variance1488.3181
MonotonicityNot monotonic
2023-12-10T15:57:28.068242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 22
22.2%
130 5
 
5.1%
151 4
 
4.0%
103 3
 
3.0%
99 2
 
2.0%
117 2
 
2.0%
43 2
 
2.0%
73 2
 
2.0%
118 2
 
2.0%
91 2
 
2.0%
Other values (46) 53
53.5%
ValueCountFrequency (%)
17 1
1.0%
38 1
1.0%
43 2
2.0%
50 1
1.0%
57 1
1.0%
58 1
1.0%
59 1
1.0%
64 2
2.0%
65 1
1.0%
66 2
2.0%
ValueCountFrequency (%)
286 1
 
1.0%
215 1
 
1.0%
193 1
 
1.0%
170 1
 
1.0%
169 1
 
1.0%
166 1
 
1.0%
160 1
 
1.0%
157 1
 
1.0%
153 1
 
1.0%
151 4
4.0%

36
Real number (ℝ)

Distinct28
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.262626
Minimum3
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:57:28.189742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile19.7
Q138.5
median100
Q3100
95-th percentile100
Maximum100
Range97
Interquartile range (IQR)61.5

Descriptive statistics

Standard deviation33.329091
Coefficient of variation (CV)0.46122169
Kurtosis-1.4848916
Mean72.262626
Median Absolute Deviation (MAD)0
Skewness-0.52013257
Sum7154
Variance1110.8283
MonotonicityNot monotonic
2023-12-10T15:57:28.309064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
100 56
56.6%
30 5
 
5.1%
21 4
 
4.0%
17 3
 
3.0%
68 2
 
2.0%
53 2
 
2.0%
20 2
 
2.0%
36 2
 
2.0%
47 2
 
2.0%
51 2
 
2.0%
Other values (18) 19
 
19.2%
ValueCountFrequency (%)
3 1
 
1.0%
15 1
 
1.0%
17 3
3.0%
20 2
 
2.0%
21 4
4.0%
27 1
 
1.0%
29 1
 
1.0%
30 5
5.1%
31 1
 
1.0%
32 1
 
1.0%
ValueCountFrequency (%)
100 56
56.6%
68 2
 
2.0%
63 1
 
1.0%
56 1
 
1.0%
54 1
 
1.0%
53 2
 
2.0%
52 1
 
1.0%
51 2
 
2.0%
47 2
 
2.0%
45 2
 
2.0%

정수기
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정수기 99
100.0%

Length

2023-12-10T15:57:28.416768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:28.504221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정수기 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

2023-12-10T15:57:28.598409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:28.706257image/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

2023-12-10T15:57:28.828000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:28.932683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
56 
1
43 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 56
56.6%
1 43
43.4%

Length

2023-12-10T15:57:29.038889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:29.140243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 56
56.6%
1 43
43.4%

60
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
2023-12-10T15:57:29.228586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q130
median40
Q345
95-th percentile60
Maximum70
Range50
Interquartile range (IQR)15

Descriptive statistics

Standard deviation11.298867
Coefficient of variation (CV)0.29908766
Kurtosis-0.23475374
Mean37.777778
Median Absolute Deviation (MAD)10
Skewness0.49452028
Sum3740
Variance127.6644
MonotonicityNot monotonic
2023-12-10T15:57:29.345009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
30 36
36.4%
40 28
28.3%
50 17
17.2%
20 10
 
10.1%
60 7
 
7.1%
70 1
 
1.0%
ValueCountFrequency (%)
20 10
 
10.1%
30 36
36.4%
40 28
28.3%
50 17
17.2%
60 7
 
7.1%
70 1
 
1.0%
ValueCountFrequency (%)
70 1
 
1.0%
60 7
 
7.1%
50 17
17.2%
40 28
28.3%
30 36
36.4%
20 10
 
10.1%

전체.2
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
28 
서울특별시
13 
경상남도
12 
경기도
11 
울산광역시
10 
Other values (6)
25 

Length

Max length5
Median length4
Mean length3.6767677
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산광역시
2nd row경상남도
3rd row경상남도
4th row전체
5th row서울특별시

Common Values

ValueCountFrequency (%)
전체 28
28.3%
서울특별시 13
13.1%
경상남도 12
12.1%
경기도 11
 
11.1%
울산광역시 10
 
10.1%
광주광역시 7
 
7.1%
충청남도 6
 
6.1%
부산광역시 4
 
4.0%
전라북도 3
 
3.0%
인천광역시 3
 
3.0%

Length

2023-12-10T15:57:29.483955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 28
28.3%
서울특별시 13
13.1%
경상남도 12
12.1%
경기도 11
 
11.1%
울산광역시 10
 
10.1%
광주광역시 7
 
7.1%
충청남도 6
 
6.1%
부산광역시 4
 
4.0%
전라북도 3
 
3.0%
인천광역시 3
 
3.0%

전체.3
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
42 
창원시
6 
천안시
6 
양천구
5 
서구
5 
Other values (18)
35 

Length

Max length4
Median length2
Mean length2.5050505
Min length2

Unique

Unique7 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
전체 42
42.4%
창원시 6
 
6.1%
천안시 6
 
6.1%
양천구 5
 
5.1%
서구 5
 
5.1%
도봉구 4
 
4.0%
북구 4
 
4.0%
파주시 4
 
4.0%
화성시 2
 
2.0%
광산구 2
 
2.0%
Other values (13) 19
19.2%

Length

2023-12-10T15:57:29.684235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 42
42.4%
천안시 6
 
6.1%
창원시 6
 
6.1%
양천구 5
 
5.1%
서구 5
 
5.1%
도봉구 4
 
4.0%
북구 4
 
4.0%
파주시 4
 
4.0%
부산진구 2
 
2.0%
원주시 2
 
2.0%
Other values (13) 19
19.2%

엘지전자
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
엘지전자 99
100.0%

Length

2023-12-10T15:57:29.838834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:57:29.929728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
엘지전자 99
100.0%

Interactions

2023-12-10T15:57:26.919460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:26.389414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:26.644110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:27.000444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:26.467590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:26.746624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:27.084356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:26.558038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:57:26.827573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:57:29.992412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018089536260전체.2전체.3
2018081.0000.0000.0000.3960.0000.0000.000
950.0001.0000.5450.0000.4930.0000.000
360.0000.5451.0000.1030.2100.5660.000
20.3960.0000.1031.0000.0000.0000.000
600.0000.4930.2100.0001.0000.0000.000
전체.20.0000.0000.5660.0000.0001.0000.977
전체.30.0000.0000.0000.0000.0000.9771.000
2023-12-10T15:57:30.116123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2전체.2전체.3201808
21.0000.0000.0000.475
전체.20.0001.0000.7890.000
전체.30.0000.7891.0000.000
2018080.4750.0000.0001.000
2023-12-10T15:57:30.211673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
9536602018082전체.2전체.3
951.0000.0590.0550.0000.0000.0000.000
360.0591.0000.0030.0000.0700.3030.000
600.0550.0031.0000.0000.0000.0000.000
2018080.0000.0000.0001.0000.4750.0000.000
20.0000.0700.0000.4751.0000.0000.000
전체.20.0000.3030.0000.0000.0001.0000.789
전체.30.0000.0000.0000.0000.0000.7891.000

Missing values

2023-12-10T15:57:27.203478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:57:27.359468image/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

MT2018089536정수기전체전체.1260전체.2전체.3엘지전자
0MT20180888100정수기전체전체260울산광역시전체엘지전자
1MT201808100100정수기전체전체260경상남도전체엘지전자
2MT201808100100정수기전체전체260경상남도창원시엘지전자
3MT2018087321정수기전체전체130전체전체엘지전자
4MT2018086741정수기전체전체130서울특별시도봉구엘지전자
5MT20180899100정수기전체전체130광주광역시북구엘지전자
6MT20180858100정수기전체전체130광주광역시광산구엘지전자
7MT20180866100정수기전체전체130경기도파주시엘지전자
8MT2018089729정수기전체전체140전체전체엘지전자
9MT20180810045정수기전체전체140서울특별시도봉구엘지전자
MT2018089536정수기전체전체.1260전체.2전체.3엘지전자
89MT201801101100정수기전체전체130경기도광명시엘지전자
90MT201801100100정수기전체전체130경기도화성시엘지전자
91MT2018017517정수기전체전체140전체전체엘지전자
92MT201801100100정수기전체전체140광주광역시서구엘지전자
93MT20180165100정수기전체전체140울산광역시전체엘지전자
94MT20180111668정수기전체전체140경상남도전체엘지전자
95MT20180110368정수기전체전체140경상남도창원시엘지전자
96MT20180410240정수기전체전체130전체전체엘지전자
97MT20180464100정수기전체전체130광주광역시광산구엘지전자
98MT201804121100정수기전체전체130울산광역시전체엘지전자