Overview

Dataset statistics

Number of variables12
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.8 KiB
Average record size in memory101.3 B

Variable types

Categorical10
Numeric2

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGIDIY

Alerts

DIY용품 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
노루페인트 has constant value ""Constant
2 is highly overall correlated with 93 and 3 other fieldsHigh correlation
201803 is highly overall correlated with 93 and 3 other fieldsHigh correlation
MT is highly overall correlated with 93 and 3 other fieldsHigh correlation
20 is highly overall correlated with MT and 2 other fieldsHigh correlation
93 is highly overall correlated with 27 and 3 other fieldsHigh correlation
27 is highly overall correlated with 93High 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 06:37:50.158829
Analysis finished2023-12-10 06:37:52.252758
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

MT
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
QU
72 
MT
27 

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 (%)
QU 72
72.7%
MT 27
 
27.3%

Length

2023-12-10T15:37:52.406203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:52.548725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
qu 72
72.7%
mt 27
 
27.3%

201803
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2018Q3
72 
201803
27 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201803
2nd row201803
3rd row201803
4th row201803
5th row201803

Common Values

ValueCountFrequency (%)
2018Q3 72
72.7%
201803 27
 
27.3%

Length

2023-12-10T15:37:52.707310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:52.838957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018q3 72
72.7%
201803 27
 
27.3%

93
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.929293
Minimum11
Maximum266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:37:53.014146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile25.7
Q168.5
median93
Q3119.5
95-th percentile159
Maximum266
Range255
Interquartile range (IQR)51

Descriptive statistics

Standard deviation43.457287
Coefficient of variation (CV)0.45778585
Kurtosis1.9291236
Mean94.929293
Median Absolute Deviation (MAD)27
Skewness0.70243439
Sum9398
Variance1888.5358
MonotonicityNot monotonic
2023-12-10T15:37:53.230045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103 3
 
3.0%
59 3
 
3.0%
130 3
 
3.0%
79 2
 
2.0%
108 2
 
2.0%
86 2
 
2.0%
88 2
 
2.0%
101 2
 
2.0%
91 2
 
2.0%
95 2
 
2.0%
Other values (63) 76
76.8%
ValueCountFrequency (%)
11 2
2.0%
17 1
1.0%
22 1
1.0%
23 1
1.0%
26 2
2.0%
32 1
1.0%
33 1
1.0%
35 1
1.0%
43 1
1.0%
46 1
1.0%
ValueCountFrequency (%)
266 1
1.0%
215 1
1.0%
198 1
1.0%
169 1
1.0%
168 1
1.0%
158 1
1.0%
157 1
1.0%
155 1
1.0%
150 1
1.0%
149 1
1.0%

27
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.040404
Minimum3
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:37:53.447879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7
Q119
median27
Q334
95-th percentile55.2
Maximum89
Range86
Interquartile range (IQR)15

Descriptive statistics

Standard deviation14.832341
Coefficient of variation (CV)0.52896318
Kurtosis3.422529
Mean28.040404
Median Absolute Deviation (MAD)8
Skewness1.3336563
Sum2776
Variance219.99835
MonotonicityNot monotonic
2023-12-10T15:37:53.698701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
28 7
 
7.1%
26 5
 
5.1%
17 4
 
4.0%
35 4
 
4.0%
30 4
 
4.0%
23 4
 
4.0%
24 4
 
4.0%
29 4
 
4.0%
32 4
 
4.0%
33 3
 
3.0%
Other values (36) 56
56.6%
ValueCountFrequency (%)
3 1
 
1.0%
5 1
 
1.0%
6 1
 
1.0%
7 3
3.0%
8 2
2.0%
9 2
2.0%
10 1
 
1.0%
12 2
2.0%
13 1
 
1.0%
14 1
 
1.0%
ValueCountFrequency (%)
89 1
1.0%
79 1
1.0%
66 1
1.0%
65 1
1.0%
57 1
1.0%
55 1
1.0%
49 1
1.0%
48 1
1.0%
45 1
1.0%
44 2
2.0%

DIY용품
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
DIY용품 99
100.0%

Length

2023-12-10T15:37:53.903297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:54.042194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
diy용품 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

2023-12-10T15:37:54.226901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:54.378816image/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

2023-12-10T15:37:54.525612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:54.676600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
1
72 
2
27 

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 (%)
1 72
72.7%
2 27
 
27.3%

Length

2023-12-10T15:37:54.850824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:55.059843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 72
72.7%
2 27
 
27.3%

20
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
50
26 
60
24 
40
22 
20
21 
30
6 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
50 26
26.3%
60 24
24.2%
40 22
22.2%
20 21
21.2%
30 6
 
6.1%

Length

2023-12-10T15:37:55.240118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:55.436268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50 26
26.3%
60 24
24.2%
40 22
22.2%
20 21
21.2%
30 6
 
6.1%

전체.2
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
16 
인천광역시
9 
광주광역시
8 
울산광역시
8 
강원도
8 
Other values (10)
50 

Length

Max length7
Median length5
Mean length4.2929293
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row대구광역시
3rd row인천광역시
4th row인천광역시
5th row광주광역시

Common Values

ValueCountFrequency (%)
경기도 16
16.2%
인천광역시 9
9.1%
광주광역시 8
8.1%
울산광역시 8
8.1%
강원도 8
8.1%
전라북도 8
8.1%
경상남도 7
 
7.1%
제주특별자치도 6
 
6.1%
부산광역시 6
 
6.1%
서울특별시 5
 
5.1%
Other values (5) 18
18.2%

Length

2023-12-10T15:37:55.685242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 16
16.2%
인천광역시 9
9.1%
광주광역시 8
8.1%
울산광역시 8
8.1%
강원도 8
8.1%
전라북도 8
8.1%
경상남도 7
 
7.1%
제주특별자치도 6
 
6.1%
부산광역시 6
 
6.1%
서울특별시 5
 
5.1%
Other values (5) 18
18.2%

전체.3
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
14 
북구
9 
서구
8 
중구
 
5
원주시
 
4
Other values (17)
59 

Length

Max length4
Median length3
Mean length2.6666667
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row서초구
2nd row북구
3rd row중구
4th row서구
5th row서구

Common Values

ValueCountFrequency (%)
전체 14
 
14.1%
북구 9
 
9.1%
서구 8
 
8.1%
중구 5
 
5.1%
원주시 4
 
4.0%
광산구 4
 
4.0%
구리시 4
 
4.0%
김포시 4
 
4.0%
양평군 4
 
4.0%
양주시 4
 
4.0%
Other values (12) 39
39.4%

Length

2023-12-10T15:37:55.920681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 14
 
14.1%
북구 9
 
9.1%
서구 8
 
8.1%
중구 5
 
5.1%
양주시 4
 
4.0%
서초구 4
 
4.0%
춘천시 4
 
4.0%
군산시 4
 
4.0%
천안시 4
 
4.0%
전주시 4
 
4.0%
Other values (12) 39
39.4%

노루페인트
Categorical

CONSTANT 

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

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노루페인트 99
100.0%

Length

2023-12-10T15:37:56.152435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:37:56.294481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노루페인트 99
100.0%

Interactions

2023-12-10T15:37:51.562125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:37:50.918262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:37:51.698492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:37:51.407956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:37:56.386548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
MT2018039327220전체.2전체.3
MT1.0000.9990.5230.4960.9991.0000.0000.000
2018030.9991.0000.5230.4960.9991.0000.0000.000
930.5230.5231.0000.6210.5230.4380.2310.250
270.4960.4960.6211.0000.4960.5250.3620.452
20.9990.9990.5230.4961.0001.0000.0000.000
201.0001.0000.4380.5251.0001.0000.0000.000
전체.20.0000.0000.2310.3620.0000.0001.0000.980
전체.30.0000.0000.2500.4520.0000.0000.9801.000
2023-12-10T15:37:56.566745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2201803전체.2MT전체.320
21.0000.9740.0000.9740.0000.984
2018030.9741.0000.0000.9740.0000.984
전체.20.0000.0001.0000.0000.8090.000
MT0.9740.9740.0001.0000.0000.984
전체.30.0000.0000.8090.0001.0000.000
200.9840.9840.0000.9840.0001.000
2023-12-10T15:37:56.743069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
9327MT201803220전체.2전체.3
931.0000.5990.5020.5020.5020.2540.0830.075
270.5991.0000.3650.3650.3650.2360.1330.165
MT0.5020.3651.0000.9740.9740.9840.0000.000
2018030.5020.3650.9741.0000.9740.9840.0000.000
20.5020.3650.9740.9741.0000.9840.0000.000
200.2540.2360.9840.9840.9841.0000.0000.000
전체.20.0830.1330.0000.0000.0000.0001.0000.809
전체.30.0750.1650.0000.0000.0000.0000.8091.000

Missing values

2023-12-10T15:37:51.889647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:37:52.165713image/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

MT2018039327DIY용품전체전체.1220전체.2전체.3노루페인트
0MT20180314389DIY용품전체전체220서울특별시서초구노루페인트
1MT20180316939DIY용품전체전체220대구광역시북구노루페인트
2MT2018034341DIY용품전체전체220인천광역시중구노루페인트
3MT2018033519DIY용품전체전체220인천광역시서구노루페인트
4MT20180316845DIY용품전체전체220광주광역시서구노루페인트
5MT2018037816DIY용품전체전체220광주광역시광산구노루페인트
6MT2018033321DIY용품전체전체220울산광역시전체노루페인트
7MT201803237DIY용품전체전체220울산광역시북구노루페인트
8MT2018038579DIY용품전체전체220경기도구리시노루페인트
9MT2018032617DIY용품전체전체220경기도김포시노루페인트
MT2018039327DIY용품전체전체.1220전체.2전체.3노루페인트
89QU2018Q35557DIY용품전체전체160경기도양주시노루페인트
90QU2018Q38224DIY용품전체전체160경기도양평군노루페인트
91QU2018Q311929DIY용품전체전체160강원도춘천시노루페인트
92QU2018Q326621DIY용품전체전체160강원도원주시노루페인트
93QU2018Q313265DIY용품전체전체160충청남도천안시노루페인트
94QU2018Q313138DIY용품전체전체160전라북도전주시노루페인트
95QU2018Q310322DIY용품전체전체160전라북도군산시노루페인트
96QU2018Q39130DIY용품전체전체160전라남도나주시노루페인트
97QU2018Q35024DIY용품전체전체160경상북도포항시노루페인트
98QU2018Q38629DIY용품전체전체160경상남도전체노루페인트