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=ZTO010BSICGISANITAR

Alerts

MT has constant value ""Constant
생리대 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
깨끗한나라 릴리안 has constant value ""Constant
50 is highly overall correlated with 201802 and 1 other fieldsHigh correlation
201802 is highly overall correlated with 50High correlation
2 is highly overall correlated with 50High correlation
경기도 is highly overall correlated with 구리시High correlation
구리시 is highly overall correlated with 경기도High correlation
2 is highly imbalanced (52.8%)Imbalance
5 has 2 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:45:46.432972
Analysis finished2023-12-10 06:45:48.719128
Duration2.29 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

2023-12-10T15:45:48.789969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:48.890632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201802
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201802
70 
201808
29 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201802
2nd row201802
3rd row201802
4th row201802
5th row201802

Common Values

ValueCountFrequency (%)
201802 70
70.7%
201808 29
29.3%

Length

2023-12-10T15:45:49.016353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:49.139833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201802 70
70.7%
201808 29
29.3%

56
Real number (ℝ)

Distinct76
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.292929
Minimum17
Maximum221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:45:49.287308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile33.3
Q162.5
median100
Q3123
95-th percentile176.2
Maximum221
Range204
Interquartile range (IQR)60.5

Descriptive statistics

Standard deviation43.501408
Coefficient of variation (CV)0.44256905
Kurtosis-0.13934913
Mean98.292929
Median Absolute Deviation (MAD)30
Skewness0.33505046
Sum9731
Variance1892.3725
MonotonicityNot monotonic
2023-12-10T15:45:49.456536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98 4
 
4.0%
57 3
 
3.0%
104 3
 
3.0%
60 3
 
3.0%
134 3
 
3.0%
100 3
 
3.0%
115 2
 
2.0%
99 2
 
2.0%
101 2
 
2.0%
94 2
 
2.0%
Other values (66) 72
72.7%
ValueCountFrequency (%)
17 1
1.0%
22 1
1.0%
24 1
1.0%
25 1
1.0%
27 1
1.0%
34 1
1.0%
35 1
1.0%
38 1
1.0%
40 1
1.0%
42 1
1.0%
ValueCountFrequency (%)
221 1
1.0%
199 1
1.0%
193 1
1.0%
185 1
1.0%
178 1
1.0%
176 1
1.0%
167 1
1.0%
165 1
1.0%
162 1
1.0%
160 1
1.0%

5
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.060606
Minimum0
Maximum95
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:45:49.602605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.9
Q14
median7
Q312.5
95-th percentile23.3
Maximum95
Range95
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation11.444469
Coefficient of variation (CV)1.1375527
Kurtosis31.556537
Mean10.060606
Median Absolute Deviation (MAD)4
Skewness4.7840961
Sum996
Variance130.97588
MonotonicityNot monotonic
2023-12-10T15:45:49.745995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
7 12
12.1%
6 10
 
10.1%
2 9
 
9.1%
13 8
 
8.1%
11 7
 
7.1%
4 6
 
6.1%
3 6
 
6.1%
5 5
 
5.1%
12 4
 
4.0%
9 4
 
4.0%
Other values (16) 28
28.3%
ValueCountFrequency (%)
0 2
 
2.0%
1 3
 
3.0%
2 9
9.1%
3 6
6.1%
4 6
6.1%
5 5
5.1%
6 10
10.1%
7 12
12.1%
8 4
 
4.0%
9 4
 
4.0%
ValueCountFrequency (%)
95 1
1.0%
44 1
1.0%
42 1
1.0%
29 1
1.0%
26 1
1.0%
23 1
1.0%
20 2
2.0%
19 2
2.0%
18 2
2.0%
16 1
1.0%

생리대
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생리대 99
100.0%

Length

2023-12-10T15:45:49.882899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:49.992981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생리대 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

2023-12-10T15:45:50.108629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:50.207705image/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

2023-12-10T15:45:50.334122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:50.449195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전체 99
100.0%

2
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
89 
1
10 

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 89
89.9%
1 10
 
10.1%

Length

2023-12-10T15:45:50.564056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:50.689770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 89
89.9%
1 10
 
10.1%

50
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.686869
Minimum20
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:45:50.800753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q140
median50
Q360
95-th percentile70
Maximum99
Range79
Interquartile range (IQR)20

Descriptive statistics

Standard deviation17.667361
Coefficient of variation (CV)0.33532759
Kurtosis0.50538545
Mean52.686869
Median Absolute Deviation (MAD)10
Skewness0.20605193
Sum5216
Variance312.13564
MonotonicityNot monotonic
2023-12-10T15:45:50.927283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
40 25
25.3%
60 22
22.2%
70 20
20.2%
50 18
18.2%
20 10
 
10.1%
99 4
 
4.0%
ValueCountFrequency (%)
20 10
 
10.1%
40 25
25.3%
50 18
18.2%
60 22
22.2%
70 20
20.2%
99 4
 
4.0%
ValueCountFrequency (%)
99 4
 
4.0%
70 20
20.2%
60 22
22.2%
50 18
18.2%
40 25
25.3%
20 10
 
10.1%

경기도
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
15 
전라북도
9 
경상남도
9 
광주광역시
9 
강원도
8 
Other values (10)
49 

Length

Max length7
Median length5
Mean length4.2828283
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row경기도
3rd row경기도
4th row강원도
5th row강원도

Common Values

ValueCountFrequency (%)
경기도 15
15.2%
전라북도 9
9.1%
경상남도 9
9.1%
광주광역시 9
9.1%
강원도 8
8.1%
제주특별자치도 8
8.1%
인천광역시 7
7.1%
울산광역시 7
7.1%
서울특별시 6
 
6.1%
전체 5
 
5.1%
Other values (5) 16
16.2%

Length

2023-12-10T15:45:51.114431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 15
15.2%
전라북도 9
9.1%
경상남도 9
9.1%
광주광역시 9
9.1%
강원도 8
8.1%
제주특별자치도 8
8.1%
인천광역시 7
7.1%
울산광역시 7
7.1%
서울특별시 6
 
6.1%
전체 5
 
5.1%
Other values (5) 16
16.2%

구리시
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)24.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
18 
서구
8 
북구
6 
광산구
 
5
춘천시
 
5
Other values (19)
57 

Length

Max length4
Median length3
Mean length2.6767677
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row김포시
2nd row화성시
3rd row양주시
4th row춘천시
5th row원주시

Common Values

ValueCountFrequency (%)
전체 18
18.2%
서구 8
 
8.1%
북구 6
 
6.1%
광산구 5
 
5.1%
춘천시 5
 
5.1%
군산시 5
 
5.1%
화성시 4
 
4.0%
창원시 4
 
4.0%
제주시 4
 
4.0%
전주시 4
 
4.0%
Other values (14) 36
36.4%

Length

2023-12-10T15:45:51.278635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 18
18.2%
서구 8
 
8.1%
북구 6
 
6.1%
광산구 5
 
5.1%
춘천시 5
 
5.1%
군산시 5
 
5.1%
화성시 4
 
4.0%
창원시 4
 
4.0%
제주시 4
 
4.0%
전주시 4
 
4.0%
Other values (14) 36
36.4%

깨끗한나라 릴리안
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row깨끗한나라 릴리안
2nd row깨끗한나라 릴리안
3rd row깨끗한나라 릴리안
4th row깨끗한나라 릴리안
5th row깨끗한나라 릴리안

Common Values

ValueCountFrequency (%)
깨끗한나라 릴리안 99
100.0%

Length

2023-12-10T15:45:51.440984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:45:51.563225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
깨끗한나라 99
50.0%
릴리안 99
50.0%

Interactions

2023-12-10T15:45:48.056133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:47.339068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:47.682413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:48.166506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:47.459647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:47.825693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:48.276867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:47.557621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:45:47.944534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:45:51.637245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201802565250경기도구리시
2018021.0000.6030.2110.2320.9910.0000.000
560.6031.0000.2330.2220.3620.0000.000
50.2110.2331.0000.3950.5010.0000.861
20.2320.2220.3951.0001.0000.0000.000
500.9910.3620.5011.0001.0000.0000.000
경기도0.0000.0000.0000.0000.0001.0000.981
구리시0.0000.0000.8610.0000.0000.9811.000
2023-12-10T15:45:51.773966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201802경기도2구리시
2018021.0000.0000.1480.000
경기도0.0001.0000.0000.792
20.1480.0001.0000.000
구리시0.0000.7920.0001.000
2023-12-10T15:45:51.883186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
565502018022경기도구리시
561.0000.328-0.0940.4460.1600.0000.000
50.3281.0000.1150.1260.2650.0000.478
50-0.0940.1151.0000.8970.9790.0000.000
2018020.4460.1260.8971.0000.1480.0000.000
20.1600.2650.9790.1481.0000.0000.000
경기도0.0000.0000.0000.0000.0001.0000.792
구리시0.0000.4780.0000.0000.0000.7921.000

Missing values

2023-12-10T15:45:48.450670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:45:48.652683image/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

MT201802565생리대전체전체.1250경기도구리시깨끗한나라 릴리안
0MT2018021324생리대전체전체250경기도김포시깨끗한나라 릴리안
1MT2018029811생리대전체전체250경기도화성시깨끗한나라 릴리안
2MT20180215613생리대전체전체250경기도양주시깨끗한나라 릴리안
3MT201802382생리대전체전체250강원도춘천시깨끗한나라 릴리안
4MT201802802생리대전체전체250강원도원주시깨끗한나라 릴리안
5MT201802987생리대전체전체250충청남도천안시깨끗한나라 릴리안
6MT201802812생리대전체전체250전라북도전주시깨끗한나라 릴리안
7MT20180210712생리대전체전체250전라북도군산시깨끗한나라 릴리안
8MT201802494생리대전체전체250전라남도나주시깨끗한나라 릴리안
9MT201802743생리대전체전체250경상북도포항시깨끗한나라 릴리안
MT201802565생리대전체전체.1250경기도구리시깨끗한나라 릴리안
89MT20180817811생리대전체전체240전라남도나주시깨끗한나라 릴리안
90MT2018081996생리대전체전체240경상북도포항시깨끗한나라 릴리안
91MT2018081177생리대전체전체240경상남도전체깨끗한나라 릴리안
92MT2018081308생리대전체전체240경상남도창원시깨끗한나라 릴리안
93MT2018081346생리대전체전체240제주특별자치도전체깨끗한나라 릴리안
94MT2018081347생리대전체전체240제주특별자치도제주시깨끗한나라 릴리안
95MT2018081157생리대전체전체250전체전체깨끗한나라 릴리안
96MT20180810216생리대전체전체250서울특별시도봉구깨끗한나라 릴리안
97MT2018081264생리대전체전체250서울특별시서초구깨끗한나라 릴리안
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