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=ZTO010BSICGICOFFEEM

Alerts

MT has constant value ""Constant
커피머신 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
드롱기 has constant value ""Constant
전체.2 is highly overall correlated with 전체.3High correlation
전체.3 is highly overall correlated with 전체.2High correlation
1 has 2 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:31:56.332207
Analysis finished2023-12-10 06:31:59.131297
Duration2.8 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

2023-12-10T15:31:59.258479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:31:59.438281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201803
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201802
36 
201803
34 
201807
29 

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 (%)
201802 36
36.4%
201803 34
34.3%
201807 29
29.3%

Length

2023-12-10T15:31:59.617429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:31:59.776219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201802 36
36.4%
201803 34
34.3%
201807 29
29.3%

11
Real number (ℝ)

Distinct60
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.68687
Minimum7
Maximum466
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:31:59.955391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile12
Q180
median100
Q3132
95-th percentile297.7
Maximum466
Range459
Interquartile range (IQR)52

Descriptive statistics

Standard deviation82.991227
Coefficient of variation (CV)0.68765747
Kurtosis3.18089
Mean120.68687
Median Absolute Deviation (MAD)25
Skewness1.6045062
Sum11948
Variance6887.5438
MonotonicityNot monotonic
2023-12-10T15:32:00.180008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 30
30.3%
12 3
 
3.0%
59 3
 
3.0%
75 2
 
2.0%
313 2
 
2.0%
97 2
 
2.0%
112 2
 
2.0%
82 2
 
2.0%
208 2
 
2.0%
126 1
 
1.0%
Other values (50) 50
50.5%
ValueCountFrequency (%)
7 1
 
1.0%
8 1
 
1.0%
9 1
 
1.0%
12 3
3.0%
19 1
 
1.0%
22 1
 
1.0%
25 1
 
1.0%
27 1
 
1.0%
46 1
 
1.0%
47 1
 
1.0%
ValueCountFrequency (%)
466 1
1.0%
368 1
1.0%
326 1
1.0%
313 2
2.0%
296 1
1.0%
291 1
1.0%
266 1
1.0%
259 1
1.0%
252 1
1.0%
245 1
1.0%

1
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.343434
Minimum0
Maximum100
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:32:00.415540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q118
median31
Q380
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)62

Descriptive statistics

Standard deviation35.169317
Coefficient of variation (CV)0.77562093
Kurtosis-1.3058116
Mean45.343434
Median Absolute Deviation (MAD)23
Skewness0.50842368
Sum4489
Variance1236.8808
MonotonicityNot monotonic
2023-12-10T15:32:00.842936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 19
 
19.2%
25 4
 
4.0%
27 4
 
4.0%
22 4
 
4.0%
26 3
 
3.0%
24 3
 
3.0%
17 3
 
3.0%
3 3
 
3.0%
14 2
 
2.0%
80 2
 
2.0%
Other values (42) 52
52.5%
ValueCountFrequency (%)
0 2
2.0%
2 2
2.0%
3 3
3.0%
4 2
2.0%
5 1
 
1.0%
6 1
 
1.0%
7 1
 
1.0%
8 1
 
1.0%
9 1
 
1.0%
11 2
2.0%
ValueCountFrequency (%)
100 19
19.2%
93 1
 
1.0%
90 1
 
1.0%
88 1
 
1.0%
87 1
 
1.0%
85 1
 
1.0%
80 2
 
2.0%
78 1
 
1.0%
76 1
 
1.0%
71 1
 
1.0%

커피머신
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
커피머신 99
100.0%

Length

2023-12-10T15:32:01.494433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:32:01.757225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
커피머신 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

2023-12-10T15:32:01.985068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:32:02.157495image/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

2023-12-10T15:32:02.369062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:32:02.538214image/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
63 
1
36 

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 63
63.6%
1 36
36.4%

Length

2023-12-10T15:32:02.747993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:32:02.961810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 63
63.6%
1 36
36.4%

20
Real number (ℝ)

Distinct6
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.20202
Minimum20
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:32:03.150027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q130
median40
Q350
95-th percentile60
Maximum70
Range50
Interquartile range (IQR)20

Descriptive statistics

Standard deviation13.169213
Coefficient of variation (CV)0.32757589
Kurtosis-0.59656447
Mean40.20202
Median Absolute Deviation (MAD)10
Skewness0.29046102
Sum3980
Variance173.42816
MonotonicityNot monotonic
2023-12-10T15:32:03.361642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
30 28
28.3%
50 26
26.3%
40 21
21.2%
20 12
12.1%
60 8
 
8.1%
70 4
 
4.0%
ValueCountFrequency (%)
20 12
12.1%
30 28
28.3%
40 21
21.2%
50 26
26.3%
60 8
 
8.1%
70 4
 
4.0%
ValueCountFrequency (%)
70 4
 
4.0%
60 8
 
8.1%
50 26
26.3%
40 21
21.2%
30 28
28.3%
20 12
12.1%

전체.2
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
28 
서울특별시
27 
경기도
11 
경상남도
8 
전라북도
4 
Other values (9)
21 

Length

Max length7
Median length5
Mean length3.7878788
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row전체
2nd row서울특별시
3rd row서울특별시
4th row전체
5th row경기도

Common Values

ValueCountFrequency (%)
전체 28
28.3%
서울특별시 27
27.3%
경기도 11
 
11.1%
경상남도 8
 
8.1%
전라북도 4
 
4.0%
대구광역시 3
 
3.0%
광주광역시 3
 
3.0%
인천광역시 3
 
3.0%
울산광역시 3
 
3.0%
부산광역시 2
 
2.0%
Other values (4) 7
 
7.1%

Length

2023-12-10T15:32:03.652393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 28
28.3%
서울특별시 27
27.3%
경기도 11
 
11.1%
경상남도 8
 
8.1%
전라북도 4
 
4.0%
대구광역시 3
 
3.0%
광주광역시 3
 
3.0%
인천광역시 3
 
3.0%
울산광역시 3
 
3.0%
부산광역시 2
 
2.0%
Other values (4) 7
 
7.1%

전체.3
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
38 
도봉구
10 
강남구
10 
북구
5 
광명시
4 
Other values (17)
32 

Length

Max length4
Median length3
Mean length2.5454545
Min length2

Unique

Unique7 ?
Unique (%)7.1%

Sample

1st row전체
2nd row도봉구
3rd row서초구
4th row전체
5th row광명시

Common Values

ValueCountFrequency (%)
전체 38
38.4%
도봉구 10
 
10.1%
강남구 10
 
10.1%
북구 5
 
5.1%
광명시 4
 
4.0%
전주시 4
 
4.0%
구리시 3
 
3.0%
서초구 3
 
3.0%
양천구 3
 
3.0%
광주시 2
 
2.0%
Other values (12) 17
17.2%

Length

2023-12-10T15:32:03.892828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 38
38.4%
강남구 10
 
10.1%
도봉구 10
 
10.1%
북구 5
 
5.1%
광명시 4
 
4.0%
전주시 4
 
4.0%
구리시 3
 
3.0%
서초구 3
 
3.0%
양천구 3
 
3.0%
창원시 2
 
2.0%
Other values (12) 17
17.2%

드롱기
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
드롱기 99
100.0%

Length

2023-12-10T15:32:04.186084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:32:04.417104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
드롱기 99
100.0%

Interactions

2023-12-10T15:31:58.273647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:57.080323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:57.494017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:58.397554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:57.213696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:58.008861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:58.517650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:57.357130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:31:58.139179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:32:04.541295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201803111220전체.2전체.3
2018031.0000.5000.4000.1040.3590.0000.000
110.5001.0000.5680.0000.0000.0000.000
10.4000.5681.0000.2250.0000.0000.112
20.1040.0000.2251.0000.2690.0000.000
200.3590.0000.0000.2691.0000.3000.000
전체.20.0000.0000.0000.0000.3001.0000.974
전체.30.0000.0000.1120.0000.0000.9741.000
2023-12-10T15:32:04.735685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체.22전체.3201803
전체.21.0000.0000.7770.000
20.0001.0000.0000.171
전체.30.7770.0001.0000.000
2018030.0000.1710.0001.000
2023-12-10T15:32:04.922226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
111202018032전체.2전체.3
111.0000.3540.1370.2440.0000.0000.000
10.3541.0000.1150.2360.1970.0000.000
200.1370.1151.0000.1550.1880.1400.000
2018030.2440.2360.1551.0000.1710.0000.000
20.0000.1970.1880.1711.0000.0000.000
전체.20.0000.0000.1400.0000.0001.0000.777
전체.30.0000.0000.0000.0000.0000.7771.000

Missing values

2023-12-10T15:31:58.726646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:31:59.011976image/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

MT201803111커피머신전체전체.1220전체.2전체.3드롱기
0MT201803569커피머신전체전체230전체전체드롱기
1MT20180384커피머신전체전체230서울특별시도봉구드롱기
2MT201803100100커피머신전체전체230서울특별시서초구드롱기
3MT20180314623커피머신전체전체240전체전체드롱기
4MT20180320885커피머신전체전체240경기도광명시드롱기
5MT201803826커피머신전체전체240경상남도전체드롱기
6MT20180320525커피머신전체전체250전체전체드롱기
7MT2018032725커피머신전체전체250서울특별시도봉구드롱기
8MT20180310667커피머신전체전체250서울특별시서초구드롱기
9MT20180311278커피머신전체전체250서울특별시강남구드롱기
MT201803111커피머신전체전체.1220전체.2전체.3드롱기
89MT201802100100커피머신전체전체260세종특별자치시전체드롱기
90MT20180296100커피머신전체전체260전라북도전주시드롱기
91MT201802972커피머신전체전체120전체전체드롱기
92MT2018027511커피머신전체전체130전체전체드롱기
93MT201802711커피머신전체전체130서울특별시도봉구드롱기
94MT20180262100커피머신전체전체130서울특별시동작구드롱기
95MT2018029016커피머신전체전체130대구광역시북구드롱기
96MT20180210017커피머신전체전체130전라북도전주시드롱기
97MT201802100100커피머신전체전체130경상북도경주시드롱기
98MT2018027818커피머신전체전체140전체전체드롱기