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=ZTO010BSICGIINFANTM

Alerts

분유류 has constant value ""Constant
전체 has constant value ""Constant
전체.1 has constant value ""Constant
남양유업 아이엠마더 has constant value ""Constant
201810 is highly overall correlated with 30 and 2 other fieldsHigh correlation
MT is highly overall correlated with 30 and 2 other fieldsHigh correlation
2 is highly overall correlated with 30 and 2 other fieldsHigh correlation
202 is highly overall correlated with 15High correlation
15 is highly overall correlated with 202High correlation
30 is highly overall correlated with MT and 2 other fieldsHigh correlation
부산광역시 is highly overall correlated with 부산진구High correlation
부산진구 is highly overall correlated with 부산광역시High correlation
202 has 1 (1.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:42:28.823733
Analysis finished2023-12-10 06:42:31.392703
Duration2.57 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
70 
QU
29 

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 70
70.7%
QU 29
29.3%

Length

2023-12-10T15:42:31.502348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:31.695542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 70
70.7%
qu 29
29.3%

201810
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201810
58 
2018Q4
29 
201901
12 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201810
2nd row201810
3rd row201810
4th row201810
5th row201810

Common Values

ValueCountFrequency (%)
201810 58
58.6%
2018Q4 29
29.3%
201901 12
 
12.1%

Length

2023-12-10T15:42:31.852999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:32.012839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201810 58
58.6%
2018q4 29
29.3%
201901 12
 
12.1%

202
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.454545
Minimum0
Maximum292
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:42:32.209193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.6
Q161
median98
Q3114.5
95-th percentile190.8
Maximum292
Range292
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation51.44767
Coefficient of variation (CV)0.54468178
Kurtosis2.1022306
Mean94.454545
Median Absolute Deviation (MAD)32
Skewness0.95723172
Sum9351
Variance2646.8627
MonotonicityNot monotonic
2023-12-10T15:42:32.446274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 10
 
10.1%
61 3
 
3.0%
60 3
 
3.0%
84 3
 
3.0%
64 3
 
3.0%
44 2
 
2.0%
103 2
 
2.0%
65 2
 
2.0%
109 2
 
2.0%
170 2
 
2.0%
Other values (59) 67
67.7%
ValueCountFrequency (%)
0 1
1.0%
1 1
1.0%
5 2
2.0%
10 1
1.0%
14 1
1.0%
25 1
1.0%
27 1
1.0%
32 1
1.0%
33 1
1.0%
39 1
1.0%
ValueCountFrequency (%)
292 1
1.0%
253 1
1.0%
207 1
1.0%
200 1
1.0%
198 1
1.0%
190 1
1.0%
181 1
1.0%
170 2
2.0%
169 1
1.0%
156 1
1.0%

15
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.555556
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:42:32.756073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q112.5
median21
Q339.5
95-th percentile100
Maximum100
Range99
Interquartile range (IQR)27

Descriptive statistics

Standard deviation25.93761
Coefficient of variation (CV)0.87758832
Kurtosis1.3063704
Mean29.555556
Median Absolute Deviation (MAD)10
Skewness1.4143204
Sum2926
Variance672.75964
MonotonicityNot monotonic
2023-12-10T15:42:32.998384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
100 6
 
6.1%
12 6
 
6.1%
13 5
 
5.1%
16 5
 
5.1%
15 4
 
4.0%
24 4
 
4.0%
8 4
 
4.0%
5 4
 
4.0%
21 3
 
3.0%
19 3
 
3.0%
Other values (37) 55
55.6%
ValueCountFrequency (%)
1 3
3.0%
2 2
 
2.0%
3 2
 
2.0%
5 4
4.0%
6 1
 
1.0%
7 1
 
1.0%
8 4
4.0%
9 1
 
1.0%
11 1
 
1.0%
12 6
6.1%
ValueCountFrequency (%)
100 6
6.1%
80 1
 
1.0%
79 1
 
1.0%
74 1
 
1.0%
69 1
 
1.0%
67 2
 
2.0%
64 1
 
1.0%
58 2
 
2.0%
57 1
 
1.0%
52 1
 
1.0%

분유류
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분유류 99
100.0%

Length

2023-12-10T15:42:33.212232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:33.357682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분유류 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

2023-12-10T15:42:33.558768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:34.043795image/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

2023-12-10T15:42:34.167543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:34.308038image/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
2
70 
1
29 

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 70
70.7%
1 29
29.3%

Length

2023-12-10T15:42:34.443281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:34.584978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 70
70.7%
1 29
29.3%

30
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.121212
Minimum20
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-10T15:42:34.755651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q130
median40
Q355
95-th percentile70
Maximum70
Range50
Interquartile range (IQR)25

Descriptive statistics

Standard deviation15.470362
Coefficient of variation (CV)0.36728197
Kurtosis-0.90672882
Mean42.121212
Median Absolute Deviation (MAD)10
Skewness0.4129132
Sum4170
Variance239.3321
MonotonicityNot monotonic
2023-12-10T15:42:34.916640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
30 26
26.3%
40 26
26.3%
60 14
14.1%
20 12
12.1%
70 11
11.1%
50 10
 
10.1%
ValueCountFrequency (%)
20 12
12.1%
30 26
26.3%
40 26
26.3%
50 10
 
10.1%
60 14
14.1%
70 11
11.1%
ValueCountFrequency (%)
70 11
11.1%
60 14
14.1%
50 10
 
10.1%
40 26
26.3%
30 26
26.3%
20 12
12.1%

부산광역시
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
15 
울산광역시
10 
인천광역시
8 
광주광역시
8 
경상남도
8 
Other values (10)
50 

Length

Max length7
Median length5
Mean length4.3838384
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row부산광역시
2nd row대구광역시
3rd row대구광역시
4th row인천광역시
5th row인천광역시

Common Values

ValueCountFrequency (%)
경기도 15
15.2%
울산광역시 10
10.1%
인천광역시 8
8.1%
광주광역시 8
8.1%
경상남도 8
8.1%
제주특별자치도 8
8.1%
대구광역시 7
7.1%
전라북도 7
7.1%
서울특별시 7
7.1%
강원도 6
 
6.1%
Other values (5) 15
15.2%

Length

2023-12-10T15:42:35.122259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 15
15.2%
울산광역시 10
10.1%
인천광역시 8
8.1%
광주광역시 8
8.1%
경상남도 8
8.1%
제주특별자치도 8
8.1%
대구광역시 7
7.1%
전라북도 7
7.1%
서울특별시 7
7.1%
강원도 6
 
6.1%
Other values (5) 15
15.2%

부산진구
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
19 
서구
9 
북구
8 
전주시
 
4
서초구
 
4
Other values (25)
55 

Length

Max length4
Median length3
Mean length2.6262626
Min length2

Unique

Unique8 ?
Unique (%)8.1%

Sample

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

Common Values

ValueCountFrequency (%)
전체 19
19.2%
서구 9
 
9.1%
북구 8
 
8.1%
전주시 4
 
4.0%
서초구 4
 
4.0%
제주시 4
 
4.0%
창원시 4
 
4.0%
김포시 4
 
4.0%
구리시 3
 
3.0%
중구 3
 
3.0%
Other values (20) 37
37.4%

Length

2023-12-10T15:42:35.355519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 19
19.2%
서구 9
 
9.1%
북구 8
 
8.1%
전주시 4
 
4.0%
서초구 4
 
4.0%
제주시 4
 
4.0%
창원시 4
 
4.0%
김포시 4
 
4.0%
광산구 3
 
3.0%
춘천시 3
 
3.0%
Other values (20) 37
37.4%

남양유업 아이엠마더
Categorical

CONSTANT 

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

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남양유업 아이엠마더
2nd row남양유업 아이엠마더
3rd row남양유업 아이엠마더
4th row남양유업 아이엠마더
5th row남양유업 아이엠마더

Common Values

ValueCountFrequency (%)
남양유업 아이엠마더 99
100.0%

Length

2023-12-10T15:42:35.615056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:42:35.767117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남양유업 99
50.0%
아이엠마더 99
50.0%

Interactions

2023-12-10T15:42:30.493103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:29.543949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:30.037443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:30.658501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:29.701220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:30.195860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:30.783840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:29.872909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:42:30.333925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:42:35.860477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
MT20181020215230부산광역시부산진구
MT1.0001.0000.0000.4380.9990.9950.0000.000
2018101.0001.0000.3330.6691.0000.9990.0000.000
2020.0000.3331.0000.5160.0000.3250.1950.383
150.4380.6690.5161.0000.4380.4600.0000.657
20.9991.0000.0000.4381.0000.9950.0000.000
300.9950.9990.3250.4600.9951.0000.0000.000
부산광역시0.0000.0000.1950.0000.0000.0001.0000.994
부산진구0.0000.0000.3830.6570.0000.0000.9941.000
2023-12-10T15:42:36.043880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
201810MT부산광역시2부산진구
2018101.0000.9950.0000.9950.000
MT0.9951.0000.0000.9750.000
부산광역시0.0000.0001.0000.0000.757
20.9950.9750.0001.0000.000
부산진구0.0000.0000.7570.0001.000
2023-12-10T15:42:36.209290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2021530MT2018102부산광역시부산진구
2021.0000.5020.0240.0000.2020.0000.0600.100
150.5021.0000.3620.4220.3680.4220.0000.266
300.0240.3621.0000.9170.9520.9170.0000.000
MT0.0000.4220.9171.0000.9950.9750.0000.000
2018100.2020.3680.9520.9951.0000.9950.0000.000
20.0000.4220.9170.9750.9951.0000.0000.000
부산광역시0.0600.0000.0000.0000.0000.0001.0000.757
부산진구0.1000.2660.0000.0000.0000.0000.7571.000

Missing values

2023-12-10T15:42:31.006652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:42:31.278745image/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

MT20181020215분유류전체전체.1230부산광역시부산진구남양유업 아이엠마더
0MT2018105316분유류전체전체230부산광역시기장군남양유업 아이엠마더
1MT20181010012분유류전체전체230대구광역시북구남양유업 아이엠마더
2MT2018109240분유류전체전체230대구광역시수성구남양유업 아이엠마더
3MT201810145분유류전체전체230인천광역시중구남양유업 아이엠마더
4MT20181012221분유류전체전체230인천광역시서구남양유업 아이엠마더
5MT2018108612분유류전체전체230광주광역시서구남양유업 아이엠마더
6MT201810323분유류전체전체230광주광역시광산구남양유업 아이엠마더
7MT20181010119분유류전체전체230울산광역시전체남양유업 아이엠마더
8MT2018108923분유류전체전체230울산광역시북구남양유업 아이엠마더
9MT20181013922분유류전체전체230경기도구리시남양유업 아이엠마더
MT20181020215분유류전체전체.1230부산광역시부산진구남양유업 아이엠마더
89MT2019016015분유류전체전체220부산광역시기장군남양유업 아이엠마더
90MT20190120764분유류전체전체220대구광역시북구남양유업 아이엠마더
91MT2019012516분유류전체전체220인천광역시중구남양유업 아이엠마더
92MT201901101분유류전체전체220인천광역시서구남양유업 아이엠마더
93MT201901728분유류전체전체220광주광역시서구남양유업 아이엠마더
94MT201901579분유류전체전체220광주광역시광산구남양유업 아이엠마더
95MT201901275분유류전체전체220울산광역시전체남양유업 아이엠마더
96MT201901338분유류전체전체220울산광역시북구남양유업 아이엠마더
97MT2019016111분유류전체전체220경기도구리시남양유업 아이엠마더
98MT2019017113분유류전체전체220경기도김포시남양유업 아이엠마더