Overview

Dataset statistics

Number of variables13
Number of observations99
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.9 KiB
Average record size in memory112.3 B

Variable types

Categorical9
Numeric4

Dataset

DescriptionSample
Author(주)제로투원파트너스
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ZTO011TOTALCGIKIMCH

Alerts

MT has constant value ""Constant
201901 has constant value ""Constant
김치/절임식품 has constant value ""Constant
배추김치류 is highly overall correlated with 배추김치류.1 and 1 other fieldsHigh correlation
50 is highly overall correlated with 배추김치류 and 1 other fieldsHigh correlation
배추김치류.1 is highly overall correlated with 배추김치류 and 1 other fieldsHigh correlation
120 is highly overall correlated with 120.1High correlation
120.1 is highly overall correlated with 120High correlation
대구광역시 is highly overall correlated with 동구High correlation
동구 is highly overall correlated with 대구광역시High correlation
2 is highly imbalanced (91.9%)Imbalance

Reproduction

Analysis started2023-12-10 06:16:26.661858
Analysis finished2023-12-10 06:16:30.402533
Duration3.74 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

2023-12-10T15:16:30.507643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:30.646177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mt 99
100.0%

201901
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
201901
99 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201901
2nd row201901
3rd row201901
4th row201901
5th row201901

Common Values

ValueCountFrequency (%)
201901 99
100.0%

Length

2023-12-10T15:16:30.795288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:31.000572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201901 99
100.0%

120
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean284.68687
Minimum-580
Maximum11600
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)3.0%
Memory size1023.0 B
2023-12-10T15:16:31.211031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-580
5-th percentile18.6
Q185
median110
Q3161
95-th percentile728
Maximum11600
Range12180
Interquartile range (IQR)76

Descriptive statistics

Standard deviation1177.7427
Coefficient of variation (CV)4.1369759
Kurtosis89.366727
Mean284.68687
Median Absolute Deviation (MAD)31
Skewness9.2521759
Sum28184
Variance1387077.9
MonotonicityNot monotonic
2023-12-10T15:16:31.445344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 4
 
4.0%
128 3
 
3.0%
92 3
 
3.0%
95 3
 
3.0%
116 2
 
2.0%
125 2
 
2.0%
19 2
 
2.0%
93 2
 
2.0%
137 2
 
2.0%
94 2
 
2.0%
Other values (65) 74
74.7%
ValueCountFrequency (%)
-580 1
1.0%
-186 1
1.0%
-15 1
1.0%
10 1
1.0%
15 1
1.0%
19 2
2.0%
24 1
1.0%
28 2
2.0%
33 1
1.0%
37 1
1.0%
ValueCountFrequency (%)
11600 1
1.0%
1480 1
1.0%
1378 1
1.0%
1040 1
1.0%
962 1
1.0%
702 1
1.0%
631 1
1.0%
472 1
1.0%
437 1
1.0%
369 1
1.0%

80
Real number (ℝ)

Distinct78
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.48485
Minimum-391
Maximum1074
Zeros0
Zeros (%)0.0%
Negative5
Negative (%)5.1%
Memory size1023.0 B
2023-12-10T15:16:31.670422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-391
5-th percentile12.6
Q177.5
median99
Q3141.5
95-th percentile476.1
Maximum1074
Range1465
Interquartile range (IQR)64

Descriptive statistics

Standard deviation171.83965
Coefficient of variation (CV)1.2498806
Kurtosis12.225292
Mean137.48485
Median Absolute Deviation (MAD)32
Skewness2.7467407
Sum13611
Variance29528.865
MonotonicityNot monotonic
2023-12-10T15:16:32.249403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91 3
 
3.0%
89 3
 
3.0%
94 3
 
3.0%
106 2
 
2.0%
119 2
 
2.0%
210 2
 
2.0%
95 2
 
2.0%
107 2
 
2.0%
84 2
 
2.0%
140 2
 
2.0%
Other values (68) 76
76.8%
ValueCountFrequency (%)
-391 1
1.0%
-57 1
1.0%
-48 1
1.0%
-30 1
1.0%
-9 1
1.0%
15 1
1.0%
27 1
1.0%
35 1
1.0%
40 1
1.0%
41 1
1.0%
ValueCountFrequency (%)
1074 1
1.0%
779 1
1.0%
690 1
1.0%
659 1
1.0%
531 1
1.0%
470 1
1.0%
393 1
1.0%
339 1
1.0%
247 1
1.0%
229 1
1.0%

120.1
Real number (ℝ)

HIGH CORRELATION 

Distinct75
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean284.68687
Minimum-580
Maximum11600
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)3.0%
Memory size1023.0 B
2023-12-10T15:16:32.483135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-580
5-th percentile18.6
Q185
median110
Q3161
95-th percentile728
Maximum11600
Range12180
Interquartile range (IQR)76

Descriptive statistics

Standard deviation1177.7427
Coefficient of variation (CV)4.1369759
Kurtosis89.366727
Mean284.68687
Median Absolute Deviation (MAD)31
Skewness9.2521759
Sum28184
Variance1387077.9
MonotonicityNot monotonic
2023-12-10T15:16:32.691612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 4
 
4.0%
128 3
 
3.0%
92 3
 
3.0%
95 3
 
3.0%
116 2
 
2.0%
125 2
 
2.0%
19 2
 
2.0%
93 2
 
2.0%
137 2
 
2.0%
94 2
 
2.0%
Other values (65) 74
74.7%
ValueCountFrequency (%)
-580 1
1.0%
-186 1
1.0%
-15 1
1.0%
10 1
1.0%
15 1
1.0%
19 2
2.0%
24 1
1.0%
28 2
2.0%
33 1
1.0%
37 1
1.0%
ValueCountFrequency (%)
11600 1
1.0%
1480 1
1.0%
1378 1
1.0%
1040 1
1.0%
962 1
1.0%
702 1
1.0%
631 1
1.0%
472 1
1.0%
437 1
1.0%
369 1
1.0%

김치/절임식품
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row김치/절임식품
2nd row김치/절임식품
3rd row김치/절임식품
4th row김치/절임식품
5th row김치/절임식품

Common Values

ValueCountFrequency (%)
김치/절임식품 99
100.0%

Length

2023-12-10T15:16:32.901662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:33.033519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김치/절임식품 99
100.0%

배추김치류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
배추김치류
57 
전체
42 

Length

Max length5
Median length5
Mean length3.7272727
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
배추김치류 57
57.6%
전체 42
42.4%

Length

2023-12-10T15:16:33.188333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:33.352371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
배추김치류 57
57.6%
전체 42
42.4%

배추김치류.1
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
배추김치류
57 
전체
42 

Length

Max length5
Median length5
Mean length3.7272727
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
배추김치류 57
57.6%
전체 42
42.4%

Length

2023-12-10T15:16:33.521618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:33.661468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
배추김치류 57
57.6%
전체 42
42.4%

2
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2
98 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 98
99.0%
1 1
 
1.0%

Length

2023-12-10T15:16:33.800421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:33.943881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 98
99.0%
1 1
 
1.0%

50
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
20
38 
60
30 
50
23 
30
5 
99
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50
2nd row50
3rd row50
4th row50
5th row50

Common Values

ValueCountFrequency (%)
20 38
38.4%
60 30
30.3%
50 23
23.2%
30 5
 
5.1%
99 3
 
3.0%

Length

2023-12-10T15:16:34.095050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:16:34.257445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 38
38.4%
60 30
30.3%
50 23
23.2%
30 5
 
5.1%
99 3
 
3.0%

대구광역시
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size924.0 B
경기도
24 
서울특별시
22 
경상북도
10 
경상남도
8 
광주광역시
6 
Other values (8)
29 

Length

Max length7
Median length5
Mean length4.2424242
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row광주광역시
2nd row광주광역시
3rd row대전광역시
4th row대전광역시
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 24
24.2%
서울특별시 22
22.2%
경상북도 10
10.1%
경상남도 8
 
8.1%
광주광역시 6
 
6.1%
대전광역시 6
 
6.1%
부산광역시 5
 
5.1%
강원도 4
 
4.0%
전라남도 4
 
4.0%
충청북도 3
 
3.0%
Other values (3) 7
 
7.1%

Length

2023-12-10T15:16:34.448547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 24
24.2%
서울특별시 22
22.2%
경상북도 10
10.1%
경상남도 8
 
8.1%
광주광역시 6
 
6.1%
대전광역시 6
 
6.1%
부산광역시 5
 
5.1%
강원도 4
 
4.0%
전라남도 4
 
4.0%
충청북도 3
 
3.0%
Other values (3) 7
 
7.1%

동구
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)31.3%
Missing0
Missing (%)0.0%
Memory size924.0 B
전체
13 
동구
 
6
남구
 
6
고양시
 
4
동대문구
 
4
Other values (26)
66 

Length

Max length4
Median length3
Mean length2.8484848
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row전체
2nd row남구
3rd row전체
4th row동구
5th row수원시

Common Values

ValueCountFrequency (%)
전체 13
 
13.1%
동구 6
 
6.1%
남구 6
 
6.1%
고양시 4
 
4.0%
동대문구 4
 
4.0%
통영시 4
 
4.0%
김천시 3
 
3.0%
수원시 3
 
3.0%
성남시 3
 
3.0%
시흥시 3
 
3.0%
Other values (21) 50
50.5%

Length

2023-12-10T15:16:34.728258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 13
 
13.1%
남구 6
 
6.1%
동구 6
 
6.1%
고양시 4
 
4.0%
동대문구 4
 
4.0%
통영시 4
 
4.0%
평창군 3
 
3.0%
사천시 3
 
3.0%
서대문구 3
 
3.0%
은평구 3
 
3.0%
Other values (21) 50
50.5%

45
Real number (ℝ)

Distinct69
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.232323
Minimum-99
Maximum176
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)3.0%
Memory size1023.0 B
2023-12-10T15:16:34.991988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-99
5-th percentile14.6
Q145
median60
Q383.5
95-th percentile151.2
Maximum176
Range275
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation39.984137
Coefficient of variation (CV)0.61294976
Kurtosis3.644665
Mean65.232323
Median Absolute Deviation (MAD)21
Skewness-0.0154048
Sum6458
Variance1598.7312
MonotonicityNot monotonic
2023-12-10T15:16:35.279792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59 4
 
4.0%
57 4
 
4.0%
81 4
 
4.0%
52 3
 
3.0%
54 3
 
3.0%
45 3
 
3.0%
85 3
 
3.0%
38 3
 
3.0%
97 2
 
2.0%
47 2
 
2.0%
Other values (59) 68
68.7%
ValueCountFrequency (%)
-99 1
1.0%
-35 1
1.0%
-18 1
1.0%
10 1
1.0%
11 1
1.0%
15 1
1.0%
24 1
1.0%
27 1
1.0%
28 1
1.0%
29 2
2.0%
ValueCountFrequency (%)
176 1
1.0%
174 1
1.0%
168 1
1.0%
167 1
1.0%
153 1
1.0%
151 1
1.0%
138 1
1.0%
106 1
1.0%
104 1
1.0%
101 2
2.0%

Interactions

2023-12-10T15:16:29.316860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:27.556547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.185886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.751894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:29.447851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:27.718532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.325540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.891242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:29.639638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:27.882265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.488389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:29.027805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:29.777153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.045811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:28.627427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:16:29.191549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:16:35.448714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
12080120.1배추김치류배추김치류.1250대구광역시동구45
1201.0000.4171.0000.1470.1470.0000.1560.3630.4450.743
800.4171.0000.4170.0600.0600.0000.0680.0000.4830.492
120.11.0000.4171.0000.1470.1470.0000.1560.3630.4450.743
배추김치류0.1470.0600.1471.0000.9990.0000.8710.0000.0000.410
배추김치류.10.1470.0600.1470.9991.0000.0000.8710.0000.0000.410
20.0000.0000.0000.0000.0001.0000.0000.0000.0000.152
500.1560.0680.1560.8710.8710.0001.0000.0000.0000.482
대구광역시0.3630.0000.3630.0000.0000.0000.0001.0000.9530.000
동구0.4450.4830.4450.0000.0000.0000.0000.9531.0000.513
450.7430.4920.7430.4100.4100.1520.4820.0000.5131.000
2023-12-10T15:16:35.635349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배추김치류동구250배추김치류.1대구광역시
배추김치류1.0000.0000.0000.9640.9790.000
동구0.0001.0000.0000.0000.0000.631
20.0000.0001.0000.0000.0000.000
500.9640.0000.0001.0000.9640.000
배추김치류.10.9790.0000.0000.9641.0000.000
대구광역시0.0000.6310.0000.0000.0001.000
2023-12-10T15:16:35.810043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
12080120.145배추김치류배추김치류.1250대구광역시동구
1201.0000.2781.0000.4530.2430.2430.0000.1160.1860.166
800.2781.0000.2780.2650.0270.0270.0000.0000.1070.187
120.11.0000.2781.0000.4530.2430.2430.0000.1160.1860.166
450.4530.2650.4531.0000.4250.4250.1440.2260.0000.220
배추김치류0.2430.0270.2430.4251.0000.9790.0000.9640.0000.000
배추김치류.10.2430.0270.2430.4250.9791.0000.0000.9640.0000.000
20.0000.0000.0000.1440.0000.0001.0000.0000.0000.000
500.1160.0000.1160.2260.9640.9640.0001.0000.0000.000
대구광역시0.1860.1070.1860.0000.0000.0000.0000.0001.0000.631
동구0.1660.1870.1660.2200.0000.0000.0000.0000.6311.000

Missing values

2023-12-10T15:16:29.981681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:16:30.295605image/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

MT20190112080120.1김치/절임식품배추김치류배추김치류.1250대구광역시동구45
0MT201901116106116김치/절임식품배추김치류배추김치류250광주광역시전체59
1MT201901337533김치/절임식품배추김치류배추김치류250광주광역시남구35
2MT201901859185김치/절임식품배추김치류배추김치류250대전광역시전체59
3MT2019012810328김치/절임식품배추김치류배추김치류250대전광역시동구168
4MT2019019910499김치/절임식품배추김치류배추김치류250경기도수원시54
5MT2019018611486김치/절임식품배추김치류배추김치류250경기도성남시57
6MT201901908990김치/절임식품배추김치류배추김치류250경기도고양시45
7MT201901197229197김치/절임식품배추김치류배추김치류250경기도과천시174
8MT20190111799117김치/절임식품배추김치류배추김치류250경기도시흥시50
9MT20190115-915김치/절임식품배추김치류배추김치류250경기도하남시11
MT20190112080120.1김치/절임식품배추김치류배추김치류.1250대구광역시동구45
89MT201901958695김치/절임식품전체전체220경상북도경산시104
90MT20190112896128김치/절임식품전체전체220경상남도통영시84
91MT20190113164131김치/절임식품전체전체220경상남도사천시57
92MT2019016121061김치/절임식품전체전체220경상남도함양군36
93MT2019016833968김치/절임식품전체전체220제주특별자치도서귀포시59
94MT201901939893김치/절임식품전체전체230서울특별시동대문구85
95MT2019018114781김치/절임식품전체전체230서울특별시중랑구81
96MT2019018811588김치/절임식품전체전체230서울특별시강북구74
97MT201901161113161김치/절임식품전체전체230서울특별시은평구97
98MT201901949194김치/절임식품전체전체230서울특별시서대문구85