Overview

Brought to you by YData

Dataset statistics

Number of variables5
Number of observations150
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)1.3%
Total size in memory6.0 KiB
Average record size in memory40.9 B

Variable types

Numeric4
Categorical1

Alerts

Dataset has 2 (1.3%) duplicate rowsDuplicates
petal_length is highly overall correlated with petal_width and 2 other fieldsHigh correlation
petal_width is highly overall correlated with petal_length and 2 other fieldsHigh correlation
sepal_length is highly overall correlated with petal_length and 2 other fieldsHigh correlation
species is highly overall correlated with petal_length and 2 other fieldsHigh correlation
species is uniformly distributed Uniform

Reproduction

Analysis started2025-03-13 15:29:57.582949
Analysis finished2025-03-13 15:29:59.043868
Duration1.46 second
Software versionydata-profiling vv4.14.0
Download configurationconfig.json

Variables

sepal_length
Real number (ℝ)

High correlation 

Distinct35
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8433333
Minimum4.3
Maximum7.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2025-03-13T11:29:59.105184image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum4.3
5-th percentile4.6
Q15.1
median5.8
Q36.4
95-th percentile7.255
Maximum7.9
Range3.6
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation0.82806613
Coefficient of variation (CV)0.14171126
Kurtosis-0.55206404
Mean5.8433333
Median Absolute Deviation (MAD)0.7
Skewness0.31491096
Sum876.5
Variance0.68569351
MonotonicityNot monotonic
2025-03-13T11:29:59.195851image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5 10
 
6.7%
5.1 9
 
6.0%
6.3 9
 
6.0%
5.7 8
 
5.3%
6.7 8
 
5.3%
5.8 7
 
4.7%
5.5 7
 
4.7%
6.4 7
 
4.7%
4.9 6
 
4.0%
5.4 6
 
4.0%
Other values (25) 73
48.7%
ValueCountFrequency (%)
4.3 1
 
0.7%
4.4 3
 
2.0%
4.5 1
 
0.7%
4.6 4
 
2.7%
4.7 2
 
1.3%
4.8 5
3.3%
4.9 6
4.0%
5 10
6.7%
5.1 9
6.0%
5.2 4
 
2.7%
ValueCountFrequency (%)
7.9 1
 
0.7%
7.7 4
2.7%
7.6 1
 
0.7%
7.4 1
 
0.7%
7.3 1
 
0.7%
7.2 3
2.0%
7.1 1
 
0.7%
7 1
 
0.7%
6.9 4
2.7%
6.8 3
2.0%

sepal_width
Real number (ℝ)

Distinct23
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.054
Minimum2
Maximum4.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2025-03-13T11:29:59.291680image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2.345
Q12.8
median3
Q33.3
95-th percentile3.8
Maximum4.4
Range2.4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.43359431
Coefficient of variation (CV)0.14197587
Kurtosis0.29078106
Mean3.054
Median Absolute Deviation (MAD)0.25
Skewness0.33405266
Sum458.1
Variance0.18800403
MonotonicityNot monotonic
2025-03-13T11:29:59.395955image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3 26
17.3%
2.8 14
9.3%
3.2 13
 
8.7%
3.1 12
 
8.0%
3.4 12
 
8.0%
2.9 10
 
6.7%
2.7 9
 
6.0%
2.5 8
 
5.3%
3.5 6
 
4.0%
3.3 6
 
4.0%
Other values (13) 34
22.7%
ValueCountFrequency (%)
2 1
 
0.7%
2.2 3
 
2.0%
2.3 4
 
2.7%
2.4 3
 
2.0%
2.5 8
 
5.3%
2.6 5
 
3.3%
2.7 9
 
6.0%
2.8 14
9.3%
2.9 10
 
6.7%
3 26
17.3%
ValueCountFrequency (%)
4.4 1
 
0.7%
4.2 1
 
0.7%
4.1 1
 
0.7%
4 1
 
0.7%
3.9 2
 
1.3%
3.8 6
4.0%
3.7 3
 
2.0%
3.6 3
 
2.0%
3.5 6
4.0%
3.4 12
8.0%

petal_length
Real number (ℝ)

High correlation 

Distinct43
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7586667
Minimum1
Maximum6.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2025-03-13T11:29:59.498775image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q11.6
median4.35
Q35.1
95-th percentile6.1
Maximum6.9
Range5.9
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation1.7644204
Coefficient of variation (CV)0.46942721
Kurtosis-1.4019208
Mean3.7586667
Median Absolute Deviation (MAD)1.25
Skewness-0.27446425
Sum563.8
Variance3.1131794
MonotonicityNot monotonic
2025-03-13T11:29:59.587742image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1.5 14
 
9.3%
1.4 12
 
8.0%
5.1 8
 
5.3%
4.5 8
 
5.3%
1.6 7
 
4.7%
1.3 7
 
4.7%
5.6 6
 
4.0%
4.7 5
 
3.3%
4.9 5
 
3.3%
4 5
 
3.3%
Other values (33) 73
48.7%
ValueCountFrequency (%)
1 1
 
0.7%
1.1 1
 
0.7%
1.2 2
 
1.3%
1.3 7
4.7%
1.4 12
8.0%
1.5 14
9.3%
1.6 7
4.7%
1.7 4
 
2.7%
1.9 2
 
1.3%
3 1
 
0.7%
ValueCountFrequency (%)
6.9 1
 
0.7%
6.7 2
1.3%
6.6 1
 
0.7%
6.4 1
 
0.7%
6.3 1
 
0.7%
6.1 3
2.0%
6 2
1.3%
5.9 2
1.3%
5.8 3
2.0%
5.7 3
2.0%

petal_width
Real number (ℝ)

High correlation 

Distinct22
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1986667
Minimum0.1
Maximum2.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2025-03-13T11:29:59.685260image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.3
median1.3
Q31.8
95-th percentile2.3
Maximum2.5
Range2.4
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation0.76316074
Coefficient of variation (CV)0.6366747
Kurtosis-1.3397542
Mean1.1986667
Median Absolute Deviation (MAD)0.7
Skewness-0.10499656
Sum179.8
Variance0.58241432
MonotonicityNot monotonic
2025-03-13T11:29:59.793072image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.2 28
18.7%
1.3 13
 
8.7%
1.8 12
 
8.0%
1.5 12
 
8.0%
1.4 8
 
5.3%
2.3 8
 
5.3%
1 7
 
4.7%
0.4 7
 
4.7%
0.3 7
 
4.7%
0.1 6
 
4.0%
Other values (12) 42
28.0%
ValueCountFrequency (%)
0.1 6
 
4.0%
0.2 28
18.7%
0.3 7
 
4.7%
0.4 7
 
4.7%
0.5 1
 
0.7%
0.6 1
 
0.7%
1 7
 
4.7%
1.1 3
 
2.0%
1.2 5
 
3.3%
1.3 13
8.7%
ValueCountFrequency (%)
2.5 3
 
2.0%
2.4 3
 
2.0%
2.3 8
5.3%
2.2 3
 
2.0%
2.1 6
4.0%
2 6
4.0%
1.9 5
3.3%
1.8 12
8.0%
1.7 2
 
1.3%
1.6 4
 
2.7%

species
Categorical

High correlation  Uniform 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Iris-setosa
50 
Iris-versicolor
50 
Iris-virginica
50 

Length

Max length15
Median length14
Mean length13.333333
Min length11

Characters and Unicode

Total characters2000
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIris-setosa
2nd rowIris-setosa
3rd rowIris-setosa
4th rowIris-setosa
5th rowIris-setosa

Common Values

ValueCountFrequency (%)
Iris-setosa 50
33.3%
Iris-versicolor 50
33.3%
Iris-virginica 50
33.3%

Length

2025-03-13T11:29:59.916392image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-13T11:30:00.034106image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
ValueCountFrequency (%)
iris-setosa 50
33.3%
iris-versicolor 50
33.3%
iris-virginica 50
33.3%

Most occurring characters

ValueCountFrequency (%)
i 350
17.5%
r 300
15.0%
s 300
15.0%
I 150
7.5%
- 150
7.5%
o 150
7.5%
e 100
 
5.0%
a 100
 
5.0%
v 100
 
5.0%
c 100
 
5.0%
Other values (4) 200
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 350
17.5%
r 300
15.0%
s 300
15.0%
I 150
7.5%
- 150
7.5%
o 150
7.5%
e 100
 
5.0%
a 100
 
5.0%
v 100
 
5.0%
c 100
 
5.0%
Other values (4) 200
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 350
17.5%
r 300
15.0%
s 300
15.0%
I 150
7.5%
- 150
7.5%
o 150
7.5%
e 100
 
5.0%
a 100
 
5.0%
v 100
 
5.0%
c 100
 
5.0%
Other values (4) 200
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 350
17.5%
r 300
15.0%
s 300
15.0%
I 150
7.5%
- 150
7.5%
o 150
7.5%
e 100
 
5.0%
a 100
 
5.0%
v 100
 
5.0%
c 100
 
5.0%
Other values (4) 200
10.0%

Interactions

2025-03-13T11:29:58.617450image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:57.669185image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:57.957810image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.232471image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.688440image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:57.763438image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.033597image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.303616image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.752894image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:57.836260image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.096996image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.373271image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.829626image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:57.897324image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.166993image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-03-13T11:29:58.442698image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Correlations

2025-03-13T11:30:00.110098image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
petal_lengthpetal_widthsepal_lengthsepal_widthspecies
petal_length1.0000.9360.881-0.3030.890
petal_width0.9361.0000.834-0.2780.924
sepal_length0.8810.8341.000-0.1590.617
sepal_width-0.303-0.278-0.1591.0000.437
species0.8900.9240.6170.4371.000

Missing values

2025-03-13T11:29:58.921495image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-13T11:29:58.999950image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

sepal_lengthsepal_widthpetal_lengthpetal_widthspecies
05.13.51.40.2Iris-setosa
14.93.01.40.2Iris-setosa
24.73.21.30.2Iris-setosa
34.63.11.50.2Iris-setosa
45.03.61.40.2Iris-setosa
55.43.91.70.4Iris-setosa
64.63.41.40.3Iris-setosa
75.03.41.50.2Iris-setosa
84.42.91.40.2Iris-setosa
94.93.11.50.1Iris-setosa
sepal_lengthsepal_widthpetal_lengthpetal_widthspecies
1406.73.15.62.4Iris-virginica
1416.93.15.12.3Iris-virginica
1425.82.75.11.9Iris-virginica
1436.83.25.92.3Iris-virginica
1446.73.35.72.5Iris-virginica
1456.73.05.22.3Iris-virginica
1466.32.55.01.9Iris-virginica
1476.53.05.22.0Iris-virginica
1486.23.45.42.3Iris-virginica
1495.93.05.11.8Iris-virginica

Duplicate rows

Most frequently occurring

sepal_lengthsepal_widthpetal_lengthpetal_widthspecies# duplicates
04.93.11.50.1Iris-setosa3
15.82.75.11.9Iris-virginica2