Overview

Dataset statistics

Number of variables26
Number of observations28
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory236.7 B

Variable types

Categorical9
Text1
Numeric16

Dataset

DescriptionSample
Author(주)어메이징푸드솔루션
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=AFS00000000000000029

Alerts

0 is highly imbalanced (77.8%)Imbalance
0.3 is highly imbalanced (77.8%)Imbalance
0.5 is highly imbalanced (77.8%)Imbalance
0.7 is highly imbalanced (62.8%)Imbalance
0.11 has 10 (35.7%) zerosZeros
0.1 has 19 (67.9%) zerosZeros
0.84 has 8 (28.6%) zerosZeros
4.8 has 7 (25.0%) zerosZeros
63.6 has 7 (25.0%) zerosZeros
213.6 has 7 (25.0%) zerosZeros
31.2 has 7 (25.0%) zerosZeros
0.2 has 15 (53.6%) zerosZeros
0.6 has 7 (25.0%) zerosZeros
0.4 has 20 (71.4%) zerosZeros
63 has 4 (14.3%) zerosZeros
0.96 has 9 (32.1%) zerosZeros
4.92 has 7 (25.0%) zerosZeros
1.32 has 9 (32.1%) zerosZeros

Reproduction

Analysis started2023-12-10 06:14:31.603410
Analysis finished2023-12-10 06:14:31.867460
Duration0.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

AF007020000001
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
AF007020000003
11 
AF007020000001
6 
AF007020000004
6 
AF007020000002
5 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAF007020000001
2nd rowAF007020000001
3rd rowAF007020000001
4th rowAF007020000001
5th rowAF007020000001

Common Values

ValueCountFrequency (%)
AF007020000003 11
39.3%
AF007020000001 6
21.4%
AF007020000004 6
21.4%
AF007020000002 5
17.9%

Length

2023-12-10T15:14:32.007293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:32.199893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
af007020000003 11
39.3%
af007020000001 6
21.4%
af007020000004 6
21.4%
af007020000002 5
17.9%

B002859
Text

Distinct14
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-10T15:14:32.468080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters196
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)17.9%

Sample

1st rowA004146
2nd rowA004019
3rd rowA000072
4th rowA003290
5th rowB001335
ValueCountFrequency (%)
a004146 3
10.7%
a000072 3
10.7%
a003742 3
10.7%
b002859 3
10.7%
a003747 3
10.7%
a003290 2
7.1%
b001335 2
7.1%
a003050 2
7.1%
a004491 2
7.1%
a004019 1
 
3.6%
Other values (4) 4
14.3%
2023-12-10T15:14:33.026908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71
36.2%
A 21
 
10.7%
4 17
 
8.7%
3 16
 
8.2%
7 13
 
6.6%
2 13
 
6.6%
9 12
 
6.1%
1 9
 
4.6%
5 9
 
4.6%
B 7
 
3.6%
Other values (2) 8
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
85.7%
Uppercase Letter 28
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71
42.3%
4 17
 
10.1%
3 16
 
9.5%
7 13
 
7.7%
2 13
 
7.7%
9 12
 
7.1%
1 9
 
5.4%
5 9
 
5.4%
6 5
 
3.0%
8 3
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
A 21
75.0%
B 7
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168
85.7%
Latin 28
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71
42.3%
4 17
 
10.1%
3 16
 
9.5%
7 13
 
7.7%
2 13
 
7.7%
9 12
 
7.1%
1 9
 
5.4%
5 9
 
5.4%
6 5
 
3.0%
8 3
 
1.8%
Latin
ValueCountFrequency (%)
A 21
75.0%
B 7
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71
36.2%
A 21
 
10.7%
4 17
 
8.7%
3 16
 
8.2%
7 13
 
6.6%
2 13
 
6.6%
9 12
 
6.1%
1 9
 
4.6%
5 9
 
4.6%
B 7
 
3.6%
Other values (2) 8
 
4.1%

0
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
27 
0.07
 
1

Length

Max length4
Median length3
Mean length3.0357143
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 27
96.4%
0.07 1
 
3.6%

Length

2023-12-10T15:14:33.364285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:33.518344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 27
96.4%
0.07 1
 
3.6%

0.11
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.30714286
Minimum0
Maximum4.24
Zeros10
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:33.661074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.01
Q30.1025
95-th percentile1.8225
Maximum4.24
Range4.24
Interquartile range (IQR)0.1025

Descriptive statistics

Standard deviation0.89566386
Coefficient of variation (CV)2.9161149
Kurtosis14.68607
Mean0.30714286
Median Absolute Deviation (MAD)0.01
Skewness3.7251927
Sum8.6
Variance0.80221376
MonotonicityNot monotonic
2023-12-10T15:14:33.834660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 10
35.7%
0.01 7
25.0%
0.11 3
 
10.7%
0.02 3
 
10.7%
0.41 1
 
3.6%
4.24 1
 
3.6%
2.12 1
 
3.6%
1.27 1
 
3.6%
0.1 1
 
3.6%
ValueCountFrequency (%)
0.0 10
35.7%
0.01 7
25.0%
0.02 3
 
10.7%
0.1 1
 
3.6%
0.11 3
 
10.7%
0.41 1
 
3.6%
1.27 1
 
3.6%
2.12 1
 
3.6%
4.24 1
 
3.6%
ValueCountFrequency (%)
4.24 1
 
3.6%
2.12 1
 
3.6%
1.27 1
 
3.6%
0.41 1
 
3.6%
0.11 3
 
10.7%
0.1 1
 
3.6%
0.02 3
 
10.7%
0.01 7
25.0%
0.0 10
35.7%

0.1
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.66892857
Minimum0
Maximum6.82
Zeros19
Zeros (%)67.9%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:33.985240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.18
95-th percentile2.1
Maximum6.82
Range6.82
Interquartile range (IQR)1.18

Descriptive statistics

Standard deviation1.4157928
Coefficient of variation (CV)2.1165082
Kurtosis13.317044
Mean0.66892857
Median Absolute Deviation (MAD)0
Skewness3.329183
Sum18.73
Variance2.0044692
MonotonicityNot monotonic
2023-12-10T15:14:34.159067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 19
67.9%
2.1 3
 
10.7%
1.4 2
 
7.1%
1.18 2
 
7.1%
0.45 1
 
3.6%
6.82 1
 
3.6%
ValueCountFrequency (%)
0.0 19
67.9%
0.45 1
 
3.6%
1.18 2
 
7.1%
1.4 2
 
7.1%
2.1 3
 
10.7%
6.82 1
 
3.6%
ValueCountFrequency (%)
6.82 1
 
3.6%
2.1 3
 
10.7%
1.4 2
 
7.1%
1.18 2
 
7.1%
0.45 1
 
3.6%
0.0 19
67.9%

0.02
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.01
12 
0.0
12 
0.02
3 
0.06
 
1

Length

Max length4
Median length4
Mean length3.5714286
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row0.01
2nd row0.0
3rd row0.01
4th row0.0
5th row0.01

Common Values

ValueCountFrequency (%)
0.01 12
42.9%
0.0 12
42.9%
0.02 3
 
10.7%
0.06 1
 
3.6%

Length

2023-12-10T15:14:34.330517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:34.453426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.01 12
42.9%
0.0 12
42.9%
0.02 3
 
10.7%
0.06 1
 
3.6%

0.01
Categorical

Distinct5
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
16 
0.01
6 
0.02
3 
0.49
2 
0.16
 
1

Length

Max length4
Median length3
Mean length3.4285714
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row0.01
2nd row0.0
3rd row0.49
4th row0.0
5th row0.02

Common Values

ValueCountFrequency (%)
0.0 16
57.1%
0.01 6
 
21.4%
0.02 3
 
10.7%
0.49 2
 
7.1%
0.16 1
 
3.6%

Length

2023-12-10T15:14:34.585803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:34.739723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 16
57.1%
0.01 6
 
21.4%
0.02 3
 
10.7%
0.49 2
 
7.1%
0.16 1
 
3.6%

0.36
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
20 
0.36
3 
0.01
3 
0.03
 
2

Length

Max length4
Median length3
Mean length3.2857143
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.03

Common Values

ValueCountFrequency (%)
0.0 20
71.4%
0.36 3
 
10.7%
0.01 3
 
10.7%
0.03 2
 
7.1%

Length

2023-12-10T15:14:34.926796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:35.086458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 20
71.4%
0.36 3
 
10.7%
0.01 3
 
10.7%
0.03 2
 
7.1%

0.84
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8339286
Minimum0
Maximum11.35
Zeros8
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:35.223044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.91
Q33.78
95-th percentile11.35
Maximum11.35
Range11.35
Interquartile range (IQR)3.78

Descriptive statistics

Standard deviation4.1337503
Coefficient of variation (CV)1.4586642
Kurtosis0.53502708
Mean2.8339286
Median Absolute Deviation (MAD)0.91
Skewness1.4577389
Sum79.35
Variance17.087891
MonotonicityNot monotonic
2023-12-10T15:14:35.394768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 8
28.6%
11.35 3
 
10.7%
0.84 3
 
10.7%
0.98 3
 
10.7%
10.8 2
 
7.1%
4.32 2
 
7.1%
2.2 2
 
7.1%
0.05 2
 
7.1%
3.6 1
 
3.6%
0.3 1
 
3.6%
ValueCountFrequency (%)
0.0 8
28.6%
0.05 2
 
7.1%
0.3 1
 
3.6%
0.84 3
 
10.7%
0.98 3
 
10.7%
1.2 1
 
3.6%
2.2 2
 
7.1%
3.6 1
 
3.6%
4.32 2
 
7.1%
10.8 2
 
7.1%
ValueCountFrequency (%)
11.35 3
10.7%
10.8 2
7.1%
4.32 2
7.1%
3.6 1
 
3.6%
2.2 2
7.1%
1.2 1
 
3.6%
0.98 3
10.7%
0.84 3
10.7%
0.3 1
 
3.6%
0.05 2
7.1%

4.8
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1496429
Minimum0
Maximum11.49
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:35.569355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.225
median3
Q37.65
95-th percentile11.49
Maximum11.49
Range11.49
Interquartile range (IQR)7.425

Descriptive statistics

Standard deviation4.0621993
Coefficient of variation (CV)0.97892744
Kurtosis-1.1153048
Mean4.1496429
Median Absolute Deviation (MAD)3
Skewness0.53281588
Sum116.19
Variance16.501463
MonotonicityNot monotonic
2023-12-10T15:14:35.725881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 7
25.0%
8.1 3
10.7%
4.8 3
10.7%
11.49 3
10.7%
7.5 2
 
7.1%
0.5 2
 
7.1%
3.0 2
 
7.1%
1.41 2
 
7.1%
2.5 1
 
3.6%
0.3 1
 
3.6%
Other values (2) 2
 
7.1%
ValueCountFrequency (%)
0.0 7
25.0%
0.3 1
 
3.6%
0.5 2
 
7.1%
1.41 2
 
7.1%
2.5 1
 
3.6%
3.0 2
 
7.1%
4.8 3
10.7%
6.0 1
 
3.6%
7.5 2
 
7.1%
8.1 3
10.7%
ValueCountFrequency (%)
11.49 3
10.7%
9.4 1
 
3.6%
8.1 3
10.7%
7.5 2
7.1%
6.0 1
 
3.6%
4.8 3
10.7%
3.0 2
7.1%
2.5 1
 
3.6%
1.41 2
7.1%
0.5 2
7.1%

63.6
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.176071
Minimum0
Maximum63.6
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:35.897723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.45
median5.3
Q39.775
95-th percentile63.6
Maximum63.6
Range63.6
Interquartile range (IQR)9.325

Descriptive statistics

Standard deviation21.600626
Coefficient of variation (CV)1.5237385
Kurtosis0.97065353
Mean14.176071
Median Absolute Deviation (MAD)5
Skewness1.5760095
Sum396.93
Variance466.58706
MonotonicityNot monotonic
2023-12-10T15:14:36.082626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 7
25.0%
3.5 3
10.7%
63.6 3
10.7%
5.95 3
10.7%
43.5 2
 
7.1%
8.2 2
 
7.1%
5.4 2
 
7.1%
0.84 2
 
7.1%
14.5 1
 
3.6%
0.6 1
 
3.6%
Other values (2) 2
 
7.1%
ValueCountFrequency (%)
0.0 7
25.0%
0.6 1
 
3.6%
0.84 2
 
7.1%
3.5 3
10.7%
5.2 1
 
3.6%
5.4 2
 
7.1%
5.95 3
10.7%
8.2 2
 
7.1%
14.5 1
 
3.6%
41.6 1
 
3.6%
ValueCountFrequency (%)
63.6 3
10.7%
43.5 2
7.1%
41.6 1
 
3.6%
14.5 1
 
3.6%
8.2 2
7.1%
5.95 3
10.7%
5.4 2
7.1%
5.2 1
 
3.6%
3.5 3
10.7%
0.84 2
7.1%

213.6
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean147.84036
Minimum0
Maximum1434.9
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:36.259473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median0.15
Q337.3875
95-th percentile1100.09
Maximum1434.9
Range1434.9
Interquartile range (IQR)37.3575

Descriptive statistics

Standard deviation379.71567
Coefficient of variation (CV)2.5684169
Kurtosis8.8985827
Mean147.84036
Median Absolute Deviation (MAD)0.15
Skewness3.0841773
Sum4139.53
Variance144183.99
MonotonicityNot monotonic
2023-12-10T15:14:36.424115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 7
25.0%
0.1 3
10.7%
213.6 3
10.7%
0.04 3
10.7%
1434.9 2
 
7.1%
0.15 2
 
7.1%
0.6 2
 
7.1%
0.23 2
 
7.1%
478.3 1
 
3.6%
1.05 1
 
3.6%
Other values (2) 2
 
7.1%
ValueCountFrequency (%)
0.0 7
25.0%
0.04 3
10.7%
0.1 3
10.7%
0.15 2
 
7.1%
0.23 2
 
7.1%
0.6 2
 
7.1%
0.8 1
 
3.6%
1.05 1
 
3.6%
146.4 1
 
3.6%
213.6 3
10.7%
ValueCountFrequency (%)
1434.9 2
7.1%
478.3 1
 
3.6%
213.6 3
10.7%
146.4 1
 
3.6%
1.05 1
 
3.6%
0.8 1
 
3.6%
0.6 2
7.1%
0.23 2
7.1%
0.15 2
7.1%
0.1 3
10.7%

120
Real number (ℝ)

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.285714
Minimum0.5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:36.588713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile0.675
Q15
median10
Q320
95-th percentile120
Maximum120
Range119.5
Interquartile range (IQR)15

Descriptive statistics

Standard deviation35.200597
Coefficient of variation (CV)1.5116821
Kurtosis4.6072414
Mean23.285714
Median Absolute Deviation (MAD)9.25
Skewness2.3888677
Sum652
Variance1239.082
MonotonicityNot monotonic
2023-12-10T15:14:36.755062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
20.0 7
25.0%
10.0 5
17.9%
5.0 4
14.3%
120.0 3
10.7%
1.0 3
10.7%
30.0 2
 
7.1%
0.5 2
 
7.1%
15.0 1
 
3.6%
3.0 1
 
3.6%
ValueCountFrequency (%)
0.5 2
 
7.1%
1.0 3
10.7%
3.0 1
 
3.6%
5.0 4
14.3%
10.0 5
17.9%
15.0 1
 
3.6%
20.0 7
25.0%
30.0 2
 
7.1%
120.0 3
10.7%
ValueCountFrequency (%)
120.0 3
10.7%
30.0 2
 
7.1%
20.0 7
25.0%
15.0 1
 
3.6%
10.0 5
17.9%
5.0 4
14.3%
3.0 1
 
3.6%
1.0 3
10.7%
0.5 2
 
7.1%

31.2
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.398571
Minimum0
Maximum144
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:36.941502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median12.06
Q331.2
95-th percentile119.36
Maximum144
Range144
Interquartile range (IQR)30.45

Descriptive statistics

Standard deviation38.056556
Coefficient of variation (CV)1.4983739
Kurtosis5.5873524
Mean25.398571
Median Absolute Deviation (MAD)12.06
Skewness2.3706554
Sum711.16
Variance1448.3015
MonotonicityNot monotonic
2023-12-10T15:14:37.162675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 7
25.0%
18.6 3
10.7%
31.2 3
10.7%
4.59 3
10.7%
144.0 2
 
7.1%
33.2 2
 
7.1%
29.0 2
 
7.1%
5.52 2
 
7.1%
48.0 1
 
3.6%
1.95 1
 
3.6%
Other values (2) 2
 
7.1%
ValueCountFrequency (%)
0.0 7
25.0%
1.0 1
 
3.6%
1.95 1
 
3.6%
4.59 3
10.7%
5.52 2
 
7.1%
18.6 3
10.7%
29.0 2
 
7.1%
31.2 3
10.7%
33.2 2
 
7.1%
48.0 1
 
3.6%
ValueCountFrequency (%)
144.0 2
7.1%
73.6 1
 
3.6%
48.0 1
 
3.6%
33.2 2
7.1%
31.2 3
10.7%
29.0 2
7.1%
18.6 3
10.7%
5.52 2
7.1%
4.59 3
10.7%
1.95 1
 
3.6%

0.2
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3071429
Minimum0
Maximum20.7
Zeros15
Zeros (%)53.6%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:37.360543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.775
95-th percentile15.87
Maximum20.7
Range20.7
Interquartile range (IQR)1.775

Descriptive statistics

Standard deviation5.4054622
Coefficient of variation (CV)2.3429248
Kurtosis9.0886631
Mean2.3071429
Median Absolute Deviation (MAD)0
Skewness3.1161406
Sum64.6
Variance29.219021
MonotonicityNot monotonic
2023-12-10T15:14:37.550054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 15
53.6%
2.3 3
 
10.7%
20.7 2
 
7.1%
1.25 2
 
7.1%
1.6 2
 
7.1%
6.9 1
 
3.6%
0.3 1
 
3.6%
0.4 1
 
3.6%
3.0 1
 
3.6%
ValueCountFrequency (%)
0.0 15
53.6%
0.3 1
 
3.6%
0.4 1
 
3.6%
1.25 2
 
7.1%
1.6 2
 
7.1%
2.3 3
 
10.7%
3.0 1
 
3.6%
6.9 1
 
3.6%
20.7 2
 
7.1%
ValueCountFrequency (%)
20.7 2
 
7.1%
6.9 1
 
3.6%
3.0 1
 
3.6%
2.3 3
 
10.7%
1.6 2
 
7.1%
1.25 2
 
7.1%
0.4 1
 
3.6%
0.3 1
 
3.6%
0.0 15
53.6%

0.6
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.175
Minimum0
Maximum0.6
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:37.768121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median0.1
Q30.1525
95-th percentile0.6
Maximum0.6
Range0.6
Interquartile range (IQR)0.1225

Descriptive statistics

Standard deviation0.21351555
Coefficient of variation (CV)1.2200888
Kurtosis0.14714509
Mean0.175
Median Absolute Deviation (MAD)0.06
Skewness1.3226771
Sum4.9
Variance0.045588889
MonotonicityNot monotonic
2023-12-10T15:14:38.080284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 7
25.0%
0.1 5
17.9%
0.6 4
14.3%
0.11 3
10.7%
0.49 2
 
7.1%
0.09 2
 
7.1%
0.04 2
 
7.1%
0.16 1
 
3.6%
0.12 1
 
3.6%
0.15 1
 
3.6%
ValueCountFrequency (%)
0.0 7
25.0%
0.04 2
 
7.1%
0.09 2
 
7.1%
0.1 5
17.9%
0.11 3
10.7%
0.12 1
 
3.6%
0.15 1
 
3.6%
0.16 1
 
3.6%
0.49 2
 
7.1%
0.6 4
14.3%
ValueCountFrequency (%)
0.6 4
14.3%
0.49 2
 
7.1%
0.16 1
 
3.6%
0.15 1
 
3.6%
0.12 1
 
3.6%
0.11 3
10.7%
0.1 5
17.9%
0.09 2
 
7.1%
0.04 2
 
7.1%
0.0 7
25.0%

0.3
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
27 
12.65
 
1

Length

Max length5
Median length3
Mean length3.0714286
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 27
96.4%
12.65 1
 
3.6%

Length

2023-12-10T15:14:38.437071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:38.625182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 27
96.4%
12.65 1
 
3.6%

0.4
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.16821429
Minimum0
Maximum1.42
Zeros20
Zeros (%)71.4%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:39.117095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.08
95-th percentile1.0075
Maximum1.42
Range1.42
Interquartile range (IQR)0.08

Descriptive statistics

Standard deviation0.37602259
Coefficient of variation (CV)2.2353785
Kurtosis4.8702167
Mean0.16821429
Median Absolute Deviation (MAD)0
Skewness2.3705581
Sum4.71
Variance0.14139299
MonotonicityNot monotonic
2023-12-10T15:14:39.378592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 20
71.4%
0.08 3
 
10.7%
0.78 1
 
3.6%
1.42 1
 
3.6%
0.71 1
 
3.6%
0.43 1
 
3.6%
1.13 1
 
3.6%
ValueCountFrequency (%)
0.0 20
71.4%
0.08 3
 
10.7%
0.43 1
 
3.6%
0.71 1
 
3.6%
0.78 1
 
3.6%
1.13 1
 
3.6%
1.42 1
 
3.6%
ValueCountFrequency (%)
1.42 1
 
3.6%
1.13 1
 
3.6%
0.78 1
 
3.6%
0.71 1
 
3.6%
0.43 1
 
3.6%
0.08 3
 
10.7%
0.0 20
71.4%

0.5
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
27 
0.02
 
1

Length

Max length4
Median length3
Mean length3.0357143
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 27
96.4%
0.02 1
 
3.6%

Length

2023-12-10T15:14:39.740980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:39.901765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 27
96.4%
0.02 1
 
3.6%

286.8
Real number (ℝ)

Distinct16
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.242143
Minimum1.53
Maximum286.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:40.071503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.53
5-th percentile1.9045
Q15.7
median28.71
Q364
95-th percentile286.8
Maximum286.8
Range285.27
Interquartile range (IQR)58.3

Descriptive statistics

Standard deviation85.644565
Coefficient of variation (CV)1.5503483
Kurtosis4.1284341
Mean55.242143
Median Absolute Deviation (MAD)23.31
Skewness2.2571754
Sum1546.78
Variance7334.9915
MonotonicityNot monotonic
2023-12-10T15:14:40.251827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2.6 3
10.7%
286.8 3
10.7%
5.8 3
10.7%
30.9 2
 
7.1%
64.0 2
 
7.1%
6.3 2
 
7.1%
44.2 2
 
7.1%
1.53 2
 
7.1%
5.4 2
 
7.1%
66.6 1
 
3.6%
Other values (6) 6
21.4%
ValueCountFrequency (%)
1.53 2
7.1%
2.6 3
10.7%
5.4 2
7.1%
5.8 3
10.7%
6.3 2
7.1%
10.3 1
 
3.6%
26.52 1
 
3.6%
30.9 2
7.1%
44.1 1
 
3.6%
44.2 2
7.1%
ValueCountFrequency (%)
286.8 3
10.7%
88.4 1
 
3.6%
69.8 1
 
3.6%
66.6 1
 
3.6%
64.0 2
7.1%
50.8 1
 
3.6%
44.2 2
7.1%
44.1 1
 
3.6%
30.9 2
7.1%
26.52 1
 
3.6%

63
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.268214
Minimum0
Maximum63
Zeros4
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:40.447102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2625
median1.42
Q312.6375
95-th percentile63
Maximum63
Range63
Interquartile range (IQR)12.375

Descriptive statistics

Standard deviation19.436044
Coefficient of variation (CV)1.8928359
Kurtosis4.2087947
Mean10.268214
Median Absolute Deviation (MAD)1.315
Skewness2.3054276
Sum287.51
Variance377.75982
MonotonicityNot monotonic
2023-12-10T15:14:40.627483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.0 4
14.3%
0.65 3
10.7%
63.0 3
10.7%
0.21 3
10.7%
4.96 2
7.1%
16.2 2
7.1%
1.5 2
7.1%
1.34 2
7.1%
0.28 2
7.1%
1.65 1
 
3.6%
Other values (4) 4
14.3%
ValueCountFrequency (%)
0.0 4
14.3%
0.21 3
10.7%
0.28 2
7.1%
0.65 3
10.7%
1.34 2
7.1%
1.5 2
7.1%
1.65 1
 
3.6%
1.87 1
 
3.6%
4.96 2
7.1%
11.96 1
 
3.6%
ValueCountFrequency (%)
63.0 3
10.7%
17.22 1
 
3.6%
16.2 2
7.1%
14.67 1
 
3.6%
11.96 1
 
3.6%
4.96 2
7.1%
1.87 1
 
3.6%
1.65 1
 
3.6%
1.5 2
7.1%
1.34 2
7.1%

0.7
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
25 
5.6
 
2
10.95
 
1

Length

Max length5
Median length3
Mean length3.0714286
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row5.6
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 25
89.3%
5.6 2
 
7.1%
10.95 1
 
3.6%

Length

2023-12-10T15:14:40.849287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:41.019142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 25
89.3%
5.6 2
 
7.1%
10.95 1
 
3.6%

0.96
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1096429
Minimum0
Maximum10
Zeros9
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:41.163298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.03
Q30.96
95-th percentile5
Maximum10
Range10
Interquartile range (IQR)0.96

Descriptive statistics

Standard deviation2.2737854
Coefficient of variation (CV)2.0491146
Kurtosis8.3531918
Mean1.1096429
Median Absolute Deviation (MAD)0.03
Skewness2.7679046
Sum31.07
Variance5.1700999
MonotonicityNot monotonic
2023-12-10T15:14:41.326026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 9
32.1%
0.03 3
 
10.7%
0.96 3
 
10.7%
0.54 3
 
10.7%
5.0 2
 
7.1%
0.01 2
 
7.1%
0.02 2
 
7.1%
10.0 1
 
3.6%
0.04 1
 
3.6%
3.0 1
 
3.6%
ValueCountFrequency (%)
0.0 9
32.1%
0.01 2
 
7.1%
0.02 2
 
7.1%
0.03 3
 
10.7%
0.04 1
 
3.6%
0.54 3
 
10.7%
0.96 3
 
10.7%
3.0 1
 
3.6%
3.38 1
 
3.6%
5.0 2
 
7.1%
ValueCountFrequency (%)
10.0 1
 
3.6%
5.0 2
7.1%
3.38 1
 
3.6%
3.0 1
 
3.6%
0.96 3
10.7%
0.54 3
10.7%
0.04 1
 
3.6%
0.03 3
10.7%
0.02 2
7.1%
0.01 2
7.1%

4.92
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.94071429
Minimum0
Maximum4.92
Zeros7
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:41.501004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.015
median0.17
Q30.4325
95-th percentile4.92
Maximum4.92
Range4.92
Interquartile range (IQR)0.4175

Descriptive statistics

Standard deviation1.6501065
Coefficient of variation (CV)1.7540995
Kurtosis1.6572372
Mean0.94071429
Median Absolute Deviation (MAD)0.16
Skewness1.7517826
Sum26.34
Variance2.7228513
MonotonicityNot monotonic
2023-12-10T15:14:41.653205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 7
25.0%
0.19 5
17.9%
0.15 3
10.7%
4.92 3
10.7%
2.75 2
 
7.1%
0.27 2
 
7.1%
0.06 2
 
7.1%
0.92 1
 
3.6%
0.03 1
 
3.6%
0.02 1
 
3.6%
ValueCountFrequency (%)
0.0 7
25.0%
0.02 1
 
3.6%
0.03 1
 
3.6%
0.06 2
 
7.1%
0.15 3
10.7%
0.19 5
17.9%
0.27 2
 
7.1%
0.92 1
 
3.6%
2.75 2
 
7.1%
3.05 1
 
3.6%
ValueCountFrequency (%)
4.92 3
10.7%
3.05 1
 
3.6%
2.75 2
 
7.1%
0.92 1
 
3.6%
0.27 2
 
7.1%
0.19 5
17.9%
0.15 3
10.7%
0.06 2
 
7.1%
0.03 1
 
3.6%
0.02 1
 
3.6%

1.32
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.26714286
Minimum0
Maximum1.32
Zeros9
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-10T15:14:41.837060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.12
Q30.29
95-th percentile1.32
Maximum1.32
Range1.32
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.39097084
Coefficient of variation (CV)1.4635272
Kurtosis4.0329734
Mean0.26714286
Median Absolute Deviation (MAD)0.12
Skewness2.207861
Sum7.48
Variance0.1528582
MonotonicityNot monotonic
2023-12-10T15:14:42.001161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 9
32.1%
0.12 5
17.9%
0.26 3
 
10.7%
1.32 3
 
10.7%
0.24 2
 
7.1%
0.29 2
 
7.1%
0.34 2
 
7.1%
0.08 1
 
3.6%
0.32 1
 
3.6%
ValueCountFrequency (%)
0.0 9
32.1%
0.08 1
 
3.6%
0.12 5
17.9%
0.24 2
 
7.1%
0.26 3
 
10.7%
0.29 2
 
7.1%
0.32 1
 
3.6%
0.34 2
 
7.1%
1.32 3
 
10.7%
ValueCountFrequency (%)
1.32 3
 
10.7%
0.34 2
 
7.1%
0.32 1
 
3.6%
0.29 2
 
7.1%
0.26 3
 
10.7%
0.24 2
 
7.1%
0.12 5
17.9%
0.08 1
 
3.6%
0.0 9
32.1%

0.8
Categorical

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
0.0
20 
12.92
3 
0.02
3 
0.11
 
2

Length

Max length5
Median length3
Mean length3.3928571
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12.92
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 20
71.4%
12.92 3
 
10.7%
0.02 3
 
10.7%
0.11 2
 
7.1%

Length

2023-12-10T15:14:42.207947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:42.382571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 20
71.4%
12.92 3
 
10.7%
0.02 3
 
10.7%
0.11 2
 
7.1%

Sample

AF007020000001B00285900.110.10.020.010.360.844.863.6213.612031.20.20.60.30.40.5286.8630.70.964.921.320.8
0AF007020000001A0041460.00.012.10.010.010.011.358.13.50.110.018.62.30.10.00.00.02.60.650.00.030.150.2612.92
1AF007020000001A0040190.00.410.00.00.00.00.00.00.00.05.00.00.00.00.00.780.044.20.00.05.00.00.00.0
2AF007020000001A0000720.00.010.00.010.490.010.87.543.51434.930.0144.020.70.490.00.00.030.94.960.00.02.750.240.0
3AF007020000001A0032900.00.00.00.00.00.00.00.00.00.020.00.00.00.00.00.00.064.016.25.60.00.00.00.0
4AF007020000001B0013350.00.01.40.010.020.034.320.58.20.155.033.21.250.090.00.00.06.31.50.00.00.270.290.0
5AF007020000001A0037420.04.240.00.00.00.00.00.00.00.010.00.00.00.00.01.420.088.40.00.010.00.00.00.0
6AF007020000002B0028590.00.110.00.020.010.360.844.863.6213.6120.031.20.00.60.00.00.0286.863.00.00.964.921.320.0
7AF007020000002A0037470.00.020.00.010.00.010.9811.495.950.041.04.590.00.110.00.080.05.80.210.00.540.190.120.02
8AF007020000002A0000720.00.00.00.00.160.03.62.514.5478.310.048.06.90.160.00.00.010.31.650.00.00.920.080.0
9AF007020000002B0006290.00.00.450.00.00.00.30.30.61.0515.01.950.30.120.00.00.044.111.9610.950.00.030.00.0
AF007020000001B00285900.110.10.020.010.360.844.863.6213.612031.20.20.60.30.40.5286.8630.70.964.921.320.8
18AF007020000003A0032900.00.00.00.00.00.00.00.00.00.020.00.00.00.00.00.00.064.016.25.60.00.00.00.0
19AF007020000003B0013350.00.01.40.010.020.034.320.58.20.155.033.21.250.090.00.00.06.31.50.00.00.270.290.0
20AF007020000003A0037420.01.270.00.00.00.00.00.00.00.03.00.00.00.00.00.430.026.520.00.03.00.00.00.0
21AF007020000003A0044910.00.010.00.00.00.00.051.410.840.230.55.520.00.10.00.00.01.530.280.00.020.060.120.11
22AF007020000004B0028590.00.110.00.020.010.360.844.863.6213.6120.031.20.00.60.00.00.0286.863.00.00.964.921.320.0
23AF007020000004A0044910.00.010.00.00.00.00.051.410.840.230.55.520.00.10.00.00.01.530.280.00.020.060.120.11
24AF007020000004A0037470.00.020.00.010.00.010.9811.495.950.041.04.590.00.110.00.080.05.80.210.00.540.190.120.02
25AF007020000004B0025990.070.16.820.060.020.01.26.041.6146.420.073.63.00.1512.651.130.0250.81.870.03.383.050.00.0
26AF007020000004A0030500.00.01.180.010.00.02.23.05.40.620.029.01.60.040.00.00.05.41.340.00.010.190.340.0
27AF007020000004A0041460.00.012.10.010.010.011.358.13.50.110.018.62.30.10.00.00.02.60.650.00.030.150.2612.92