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

Categorical9
Numeric3

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO010BSICGIELECTRI

Alerts

전기레인지 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
리홈쿠첸 has constant value ""Constant
201804 is highly overall correlated with MTHigh correlation
MT is highly overall correlated with 201804High correlation
전체.2 is highly overall correlated with 전체.3High correlation
전체.3 is highly overall correlated with 전체.2High correlation
65 has 1 (1.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:15:55.621814
Analysis finished2023-12-10 06:15:57.967348
Duration2.35 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
MT
77 
QU
22 

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 77
77.8%
QU 22
 
22.2%

Length

2023-12-10T15:15:58.067054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:58.214915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 77
77.8%
qu 22
 
22.2%

201804
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
2018Q4
22 
201801
21 
201806
20 
201804
18 
201802
18 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201804
2nd row201804
3rd row201804
4th row201804
5th row201804

Common Values

ValueCountFrequency (%)
2018Q4 22
22.2%
201801 21
21.2%
201806 20
20.2%
201804 18
18.2%
201802 18
18.2%

Length

2023-12-10T15:15:58.368486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:15:58.547718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018q4 22
22.2%
201801 21
21.2%
201806 20
20.2%
201804 18
18.2%
201802 18
18.2%

65
Real number (ℝ)

ZEROS 

Distinct66
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.272727
Minimum0
Maximum188
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:15:58.733335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22.8
Q170
median100
Q3118
95-th percentile171.2
Maximum188
Range188
Interquartile range (IQR)48

Descriptive statistics

Standard deviation42.220224
Coefficient of variation (CV)0.43854812
Kurtosis-0.1765345
Mean96.272727
Median Absolute Deviation (MAD)25
Skewness0.0013864519
Sum9531
Variance1782.5473
MonotonicityNot monotonic
2023-12-10T15:15:58.963727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 26
26.3%
154 2
 
2.0%
133 2
 
2.0%
108 2
 
2.0%
117 2
 
2.0%
149 2
 
2.0%
52 2
 
2.0%
118 2
 
2.0%
47 2
 
2.0%
132 1
 
1.0%
Other values (56) 56
56.6%
ValueCountFrequency (%)
0 1
1.0%
8 1
1.0%
15 1
1.0%
17 1
1.0%
21 1
1.0%
23 1
1.0%
24 1
1.0%
32 1
1.0%
35 1
1.0%
37 1
1.0%
ValueCountFrequency (%)
188 1
1.0%
186 1
1.0%
183 1
1.0%
178 1
1.0%
173 1
1.0%
171 1
1.0%
168 1
1.0%
164 1
1.0%
161 1
1.0%
154 2
2.0%

6
Real number (ℝ)

Distinct53
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.060606
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:15:59.210434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q113
median36
Q391
95-th percentile100
Maximum100
Range99
Interquartile range (IQR)78

Descriptive statistics

Standard deviation37.301534
Coefficient of variation (CV)0.79262758
Kurtosis-1.5142881
Mean47.060606
Median Absolute Deviation (MAD)28
Skewness0.38852432
Sum4659
Variance1391.4045
MonotonicityNot monotonic
2023-12-10T15:15:59.802354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 22
22.2%
9 4
 
4.0%
8 3
 
3.0%
13 3
 
3.0%
11 3
 
3.0%
14 3
 
3.0%
47 3
 
3.0%
4 3
 
3.0%
36 2
 
2.0%
7 2
 
2.0%
Other values (43) 51
51.5%
ValueCountFrequency (%)
1 2
2.0%
2 1
 
1.0%
4 3
3.0%
5 1
 
1.0%
6 2
2.0%
7 2
2.0%
8 3
3.0%
9 4
4.0%
10 1
 
1.0%
11 3
3.0%
ValueCountFrequency (%)
100 22
22.2%
98 1
 
1.0%
94 1
 
1.0%
91 2
 
2.0%
89 1
 
1.0%
87 1
 
1.0%
86 1
 
1.0%
83 1
 
1.0%
79 1
 
1.0%
78 1
 
1.0%

전기레인지
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전기레인지 99
100.0%

Length

2023-12-10T15:16:00.005618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:00.155837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전기레인지 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

2023-12-10T15:16:00.310455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:00.461960image/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

2023-12-10T15:16:00.614588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:00.756145image/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
68 
1
31 

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 68
68.7%
1 31
31.3%

Length

2023-12-10T15:16:00.902872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:01.041089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 68
68.7%
1 31
31.3%

20
Real number (ℝ)

Distinct7
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.808081
Minimum20
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:16:01.175248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile29
Q130
median40
Q350
95-th percentile70
Maximum99
Range79
Interquartile range (IQR)20

Descriptive statistics

Standard deviation13.760841
Coefficient of variation (CV)0.3291431
Kurtosis1.9556405
Mean41.808081
Median Absolute Deviation (MAD)10
Skewness1.0396806
Sum4139
Variance189.36075
MonotonicityNot monotonic
2023-12-10T15:16:01.358391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
30 32
32.3%
40 26
26.3%
50 21
21.2%
60 9
 
9.1%
70 5
 
5.1%
20 5
 
5.1%
99 1
 
1.0%
ValueCountFrequency (%)
20 5
 
5.1%
30 32
32.3%
40 26
26.3%
50 21
21.2%
60 9
 
9.1%
70 5
 
5.1%
99 1
 
1.0%
ValueCountFrequency (%)
99 1
 
1.0%
70 5
 
5.1%
60 9
 
9.1%
50 21
21.2%
40 26
26.3%
30 32
32.3%
20 5
 
5.1%

전체.2
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
39 
서울특별시
12 
광주광역시
8 
전라북도
7 
경상남도
7 
Other values (11)
26 

Length

Max length7
Median length5
Mean length3.5959596
Min length2

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row전체
2nd row서울특별시
3rd row대구광역시
4th row충청남도
5th row전라북도

Common Values

ValueCountFrequency (%)
전체 39
39.4%
서울특별시 12
 
12.1%
광주광역시 8
 
8.1%
전라북도 7
 
7.1%
경상남도 7
 
7.1%
대구광역시 6
 
6.1%
울산광역시 5
 
5.1%
경상북도 3
 
3.0%
충청남도 2
 
2.0%
강원도 2
 
2.0%
Other values (6) 8
 
8.1%

Length

2023-12-10T15:16:01.577133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 39
39.4%
서울특별시 12
 
12.1%
광주광역시 8
 
8.1%
전라북도 7
 
7.1%
경상남도 7
 
7.1%
대구광역시 6
 
6.1%
울산광역시 5
 
5.1%
경상북도 3
 
3.0%
충청남도 2
 
2.0%
강원도 2
 
2.0%
Other values (6) 8
 
8.1%

전체.3
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)21.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
48 
북구
11 
도봉구
7 
전주시
5 
광산구
 
4
Other values (16)
24 

Length

Max length3
Median length2
Mean length2.3939394
Min length2

Unique

Unique10 ?
Unique (%)10.1%

Sample

1st row전체
2nd row도봉구
3rd row북구
4th row천안시
5th row전주시

Common Values

ValueCountFrequency (%)
전체 48
48.5%
북구 11
 
11.1%
도봉구 7
 
7.1%
전주시 5
 
5.1%
광산구 4
 
4.0%
포항시 3
 
3.0%
창원시 3
 
3.0%
군산시 2
 
2.0%
구리시 2
 
2.0%
천안시 2
 
2.0%
Other values (11) 12
 
12.1%

Length

2023-12-10T15:16:01.769656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 48
48.5%
북구 11
 
11.1%
도봉구 7
 
7.1%
전주시 5
 
5.1%
광산구 4
 
4.0%
포항시 3
 
3.0%
창원시 3
 
3.0%
천안시 2
 
2.0%
강남구 2
 
2.0%
구리시 2
 
2.0%
Other values (11) 12
 
12.1%

리홈쿠첸
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
리홈쿠첸 99
100.0%

Length

2023-12-10T15:16:01.961035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:02.097810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
리홈쿠첸 99
100.0%

Interactions

2023-12-10T15:15:56.960561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:56.227429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:56.549170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:57.114849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:56.324308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:56.696924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:57.262863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:56.424979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:15:56.818778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:16:02.197112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
MT201804656220전체.2전체.3
MT1.0001.0000.0000.0000.4830.3500.6280.422
2018041.0001.0000.0000.0000.2690.3180.2570.000
650.0000.0001.0000.6870.2370.1490.0000.000
60.0000.0000.6871.0000.0000.0000.6090.555
20.4830.2690.2370.0001.0000.1180.0000.000
200.3500.3180.1490.0000.1181.0000.3080.000
전체.20.6280.2570.0000.6090.0000.3081.0000.978
전체.30.4220.0000.0000.5550.0000.0000.9781.000
2023-12-10T15:16:02.384679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201804전체.32MT전체.2
2018041.0000.0000.3230.9840.119
전체.30.0001.0000.0000.3300.801
20.3230.0001.0000.3210.000
MT0.9840.3300.3211.0000.460
전체.20.1190.8010.0000.4601.000
2023-12-10T15:16:02.555350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
65620MT2018042전체.2전체.3
651.0000.390-0.0300.0000.0000.1710.0000.000
60.3901.000-0.1090.0000.0000.0000.2780.220
20-0.030-0.1091.0000.3640.2060.1210.1330.000
MT0.0000.0000.3641.0000.9840.3210.4600.330
2018040.0000.0000.2060.9841.0000.3230.1190.000
20.1710.0000.1210.3210.3231.0000.0000.000
전체.20.0000.2780.1330.4600.1190.0001.0000.801
전체.30.0000.2200.0000.3300.0000.0000.8011.000

Missing values

2023-12-10T15:15:57.614831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:15:57.873106image/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

MT201804656전기레인지전체전체.1220전체.2전체.3리홈쿠첸
0MT20180415424전기레인지전체전체230전체전체리홈쿠첸
1MT20180414965전기레인지전체전체230서울특별시도봉구리홈쿠첸
2MT201804168100전기레인지전체전체230대구광역시북구리홈쿠첸
3MT20180410866전기레인지전체전체230충청남도천안시리홈쿠첸
4MT201804100100전기레인지전체전체230전라북도전주시리홈쿠첸
5MT20180411713전기레인지전체전체240전체전체리홈쿠첸
6MT20180410019전기레인지전체전체240경상남도전체리홈쿠첸
7MT20180410513전기레인지전체전체250전체전체리홈쿠첸
8MT20180458100전기레인지전체전체250광주광역시광산구리홈쿠첸
9MT20180416111전기레인지전체전체260전체전체리홈쿠첸
MT201804656전기레인지전체전체.1220전체.2전체.3리홈쿠첸
89MT201802547전기레인지전체전체250전체전체리홈쿠첸
90MT2018027814전기레인지전체전체250경상남도전체리홈쿠첸
91MT2018028126전기레인지전체전체250경상남도창원시리홈쿠첸
92MT20180212527전기레인지전체전체130전체전체리홈쿠첸
93MT20180238100전기레인지전체전체130서울특별시도봉구리홈쿠첸
94MT20180215478전기레인지전체전체130광주광역시북구리홈쿠첸
95MT201802218전기레인지전체전체140전체전체리홈쿠첸
96MT201802438전기레인지전체전체150전체전체리홈쿠첸
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