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=ZTO010BSICGISPORTS

Alerts

MT has constant value ""Constant
스포츠/레저용품 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
2 has constant value ""Constant
대연엔터프라이즈 has constant value ""Constant
서울특별시 is highly overall correlated with 강북구High correlation
강북구 is highly overall correlated with 서울특별시High correlation

Reproduction

Analysis started2023-12-10 06:35:49.572147
Analysis finished2023-12-10 06:35:52.122263
Duration2.55 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

2023-12-10T15:35:52.260190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:52.521364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201801
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201801
54 
201803
45 

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 54
54.5%
201803 45
45.5%

Length

2023-12-10T15:35:52.726033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:52.915719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201801 54
54.5%
201803 45
45.5%

57
Real number (ℝ)

Distinct71
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.55556
Minimum39
Maximum247
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:35:53.150068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile56.6
Q1105.5
median133
Q3158
95-th percentile198.1
Maximum247
Range208
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation39.503868
Coefficient of variation (CV)0.30028278
Kurtosis0.14853947
Mean131.55556
Median Absolute Deviation (MAD)25
Skewness0.023241559
Sum13024
Variance1560.5556
MonotonicityNot monotonic
2023-12-10T15:35:53.492130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
158 4
 
4.0%
143 3
 
3.0%
159 3
 
3.0%
166 3
 
3.0%
125 3
 
3.0%
102 3
 
3.0%
97 2
 
2.0%
137 2
 
2.0%
103 2
 
2.0%
129 2
 
2.0%
Other values (61) 72
72.7%
ValueCountFrequency (%)
39 1
1.0%
49 1
1.0%
51 1
1.0%
52 1
1.0%
53 1
1.0%
57 1
1.0%
72 1
1.0%
75 1
1.0%
79 1
1.0%
81 1
1.0%
ValueCountFrequency (%)
247 1
1.0%
211 1
1.0%
202 1
1.0%
201 1
1.0%
199 1
1.0%
198 2
2.0%
191 1
1.0%
188 1
1.0%
187 1
1.0%
180 2
2.0%

100
Real number (ℝ)

Distinct60
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.111111
Minimum15
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:35:53.780840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile25
Q142.5
median59
Q376.5
95-th percentile97.3
Maximum100
Range85
Interquartile range (IQR)34

Descriptive statistics

Standard deviation22.287495
Coefficient of variation (CV)0.37704409
Kurtosis-0.89529182
Mean59.111111
Median Absolute Deviation (MAD)17
Skewness0.023092691
Sum5852
Variance496.73243
MonotonicityNot monotonic
2023-12-10T15:35:54.181738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 5
 
5.1%
44 5
 
5.1%
73 4
 
4.0%
55 4
 
4.0%
85 3
 
3.0%
78 3
 
3.0%
53 3
 
3.0%
32 3
 
3.0%
80 3
 
3.0%
62 2
 
2.0%
Other values (50) 64
64.6%
ValueCountFrequency (%)
15 1
1.0%
16 1
1.0%
17 1
1.0%
24 1
1.0%
25 2
2.0%
27 1
1.0%
28 1
1.0%
29 2
2.0%
30 1
1.0%
31 1
1.0%
ValueCountFrequency (%)
100 5
5.1%
97 1
 
1.0%
94 1
 
1.0%
93 1
 
1.0%
91 1
 
1.0%
89 2
 
2.0%
86 1
 
1.0%
85 3
3.0%
83 1
 
1.0%
82 1
 
1.0%

스포츠/레저용품
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
스포츠/레저용품
99 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row스포츠/레저용품
2nd row스포츠/레저용품
3rd row스포츠/레저용품
4th row스포츠/레저용품
5th row스포츠/레저용품

Common Values

ValueCountFrequency (%)
스포츠/레저용품 99
100.0%

Length

2023-12-10T15:35:54.491497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:54.709108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
스포츠/레저용품 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

2023-12-10T15:35:54.959000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:55.169299image/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

2023-12-10T15:35:55.361849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:55.517066image/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

2023-12-10T15:35:55.683665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:55.837509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 99
100.0%

20
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
30
32 
40
31 
20
29 
50
7 

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 (%)
30 32
32.3%
40 31
31.3%
20 29
29.3%
50 7
 
7.1%

Length

2023-12-10T15:35:55.979040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:56.145675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 32
32.3%
40 31
31.3%
20 29
29.3%
50 7
 
7.1%

서울특별시
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
24 
서울특별시
20 
대전광역시
12 
경상북도
11 
부산광역시
7 
Other values (4)
25 

Length

Max length5
Median length5
Mean length4.2929293
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 24
24.2%
서울특별시 20
20.2%
대전광역시 12
12.1%
경상북도 11
11.1%
부산광역시 7
 
7.1%
대구광역시 7
 
7.1%
광주광역시 7
 
7.1%
충청북도 6
 
6.1%
경상남도 5
 
5.1%

Length

2023-12-10T15:35:56.358015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:56.584808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 24
24.2%
서울특별시 20
20.2%
대전광역시 12
12.1%
경상북도 11
11.1%
부산광역시 7
 
7.1%
대구광역시 7
 
7.1%
광주광역시 7
 
7.1%
충청북도 6
 
6.1%
경상남도 5
 
5.1%

강북구
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
26 
동구
12 
은평구
7 
영등포구
7 
북구
7 
Other values (7)
40 

Length

Max length4
Median length3
Mean length2.6161616
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row은평구
2nd row영등포구
3rd row북구
4th row동구
5th row전체

Common Values

ValueCountFrequency (%)
전체 26
26.3%
동구 12
12.1%
은평구 7
 
7.1%
영등포구 7
 
7.1%
북구 7
 
7.1%
수원시 6
 
6.1%
성남시 6
 
6.1%
고양시 6
 
6.1%
시흥시 6
 
6.1%
강북구 6
 
6.1%
Other values (2) 10
 
10.1%

Length

2023-12-10T15:35:56.846118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 26
26.3%
동구 12
12.1%
은평구 7
 
7.1%
영등포구 7
 
7.1%
북구 7
 
7.1%
수원시 6
 
6.1%
성남시 6
 
6.1%
고양시 6
 
6.1%
시흥시 6
 
6.1%
강북구 6
 
6.1%
Other values (2) 10
 
10.1%

대연엔터프라이즈
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대연엔터프라이즈 99
100.0%

Length

2023-12-10T15:35:57.062596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:57.219296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대연엔터프라이즈 99
100.0%

Interactions

2023-12-10T15:35:50.969044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:50.729917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:51.117724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:50.850532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:35:57.321934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2018015710020서울특별시강북구
2018011.0000.0000.5670.2790.0000.000
570.0001.0000.4070.0620.0000.218
1000.5670.4071.0000.2720.0710.314
200.2790.0620.2721.0000.0000.000
서울특별시0.0000.0000.0710.0001.0000.935
강북구0.0000.2180.3140.0000.9351.000
2023-12-10T15:35:57.478526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201801강북구서울특별시20
2018011.0000.0000.0000.183
강북구0.0001.0000.7470.000
서울특별시0.0000.7471.0000.000
200.1830.0000.0001.000
2023-12-10T15:35:57.663610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
5710020180120서울특별시강북구
571.0000.2090.0000.0190.0000.085
1000.2091.0000.4220.1500.0900.134
2018010.0000.4221.0000.1830.0000.000
200.0190.1500.1831.0000.0000.000
서울특별시0.0000.0900.0000.0001.0000.747
강북구0.0850.1340.0000.0000.7471.000

Missing values

2023-12-10T15:35:51.538977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:35:51.962243image/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

MT20180157100스포츠/레저용품전체전체.1220서울특별시강북구대연엔터프라이즈
0MT201801160100스포츠/레저용품전체전체220서울특별시은평구대연엔터프라이즈
1MT2018018724스포츠/레저용품전체전체220서울특별시영등포구대연엔터프라이즈
2MT2018017555스포츠/레저용품전체전체220부산광역시북구대연엔터프라이즈
3MT20180110485스포츠/레저용품전체전체220대구광역시동구대연엔터프라이즈
4MT20180119885스포츠/레저용품전체전체220광주광역시전체대연엔터프라이즈
5MT20180118094스포츠/레저용품전체전체220대전광역시전체대연엔터프라이즈
6MT201801128100스포츠/레저용품전체전체220대전광역시동구대연엔터프라이즈
7MT2018018555스포츠/레저용품전체전체220경기도수원시대연엔터프라이즈
8MT20180111578스포츠/레저용품전체전체220경기도성남시대연엔터프라이즈
9MT2018013934스포츠/레저용품전체전체220경기도고양시대연엔터프라이즈
MT20180157100스포츠/레저용품전체전체.1220서울특별시강북구대연엔터프라이즈
89MT20180315936스포츠/레저용품전체전체240광주광역시전체대연엔터프라이즈
90MT20180315952스포츠/레저용품전체전체240대전광역시전체대연엔터프라이즈
91MT2018039053스포츠/레저용품전체전체240대전광역시동구대연엔터프라이즈
92MT20180314344스포츠/레저용품전체전체240경기도수원시대연엔터프라이즈
93MT20180315053스포츠/레저용품전체전체240경기도성남시대연엔터프라이즈
94MT20180316632스포츠/레저용품전체전체240경기도고양시대연엔터프라이즈
95MT20180317653스포츠/레저용품전체전체240경기도시흥시대연엔터프라이즈
96MT20180318065스포츠/레저용품전체전체240충청북도전체대연엔터프라이즈
97MT20180313552스포츠/레저용품전체전체240경상북도전체대연엔터프라이즈
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