Overview

Dataset statistics

Number of variables5
Number of observations150
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.7%
Total size in memory6.0 KiB
Average record size in memory40.9 B

Variable types

Numeric4
Categorical1

Alerts

Dataset has 1 (0.7%) 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 distributedUniform

Reproduction

Analysis started2024-07-14 05:42:27.904794
Analysis finished2024-07-14 05:42:29.649817
Duration1.75 second
Software versionydata-profiling v4.8.3
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
2024-07-14T14:42:29.737136image/svg+xmlMatplotlib v3.8.4, 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
2024-07-14T14:42:29.863629image/svg+xmlMatplotlib v3.8.4, 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%
Mean3.0573333
Minimum2
Maximum4.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-07-14T14:42:29.981650image/svg+xmlMatplotlib v3.8.4, 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 deviation0.43586628
Coefficient of variation (CV)0.1425642
Kurtosis0.22824904
Mean3.0573333
Median Absolute Deviation (MAD)0.3
Skewness0.31896566
Sum458.6
Variance0.18997942
MonotonicityNot monotonic
2024-07-14T14:42:30.093538image/svg+xmlMatplotlib v3.8.4, 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%
3.4 12
 
8.0%
3.1 11
 
7.3%
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) 35
23.3%
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 4
 
2.7%
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%
Mean3.758
Minimum1
Maximum6.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-07-14T14:42:30.215082image/svg+xmlMatplotlib v3.8.4, 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 deviation1.7652982
Coefficient of variation (CV)0.46974407
Kurtosis-1.4021034
Mean3.758
Median Absolute Deviation (MAD)1.25
Skewness-0.27488418
Sum563.7
Variance3.1162779
MonotonicityNot monotonic
2024-07-14T14:42:30.338831image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1.4 13
 
8.7%
1.5 13
 
8.7%
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 13
8.7%
1.5 13
8.7%
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%
Mean1.1993333
Minimum0.1
Maximum2.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-07-14T14:42:30.456107image/svg+xmlMatplotlib v3.8.4, 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 deviation0.76223767
Coefficient of variation (CV)0.63555114
Kurtosis-1.340604
Mean1.1993333
Median Absolute Deviation (MAD)0.7
Skewness-0.10296675
Sum179.9
Variance0.58100626
MonotonicityNot monotonic
2024-07-14T14:42:30.570802image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.2 29
19.3%
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%
2.1 6
 
4.0%
Other values (12) 41
27.3%
ValueCountFrequency (%)
0.1 5
 
3.3%
0.2 29
19.3%
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
setosa
50 
versicolor
50 
virginica
50 

Length

Max length10
Median length9
Mean length8.3333333
Min length6

Characters and Unicode

Total characters1250
Distinct characters12
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 rowsetosa
2nd rowsetosa
3rd rowsetosa
4th rowsetosa
5th rowsetosa

Common Values

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

Length

2024-07-14T14:42:30.700998image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-14T14:42:30.822076image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
setosa 50
33.3%
versicolor 50
33.3%
virginica 50
33.3%

Most occurring characters

ValueCountFrequency (%)
i 200
16.0%
s 150
12.0%
o 150
12.0%
r 150
12.0%
e 100
8.0%
a 100
8.0%
v 100
8.0%
c 100
8.0%
t 50
 
4.0%
l 50
 
4.0%
Other values (2) 100
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1250
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 200
16.0%
s 150
12.0%
o 150
12.0%
r 150
12.0%
e 100
8.0%
a 100
8.0%
v 100
8.0%
c 100
8.0%
t 50
 
4.0%
l 50
 
4.0%
Other values (2) 100
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1250
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 200
16.0%
s 150
12.0%
o 150
12.0%
r 150
12.0%
e 100
8.0%
a 100
8.0%
v 100
8.0%
c 100
8.0%
t 50
 
4.0%
l 50
 
4.0%
Other values (2) 100
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1250
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 200
16.0%
s 150
12.0%
o 150
12.0%
r 150
12.0%
e 100
8.0%
a 100
8.0%
v 100
8.0%
c 100
8.0%
t 50
 
4.0%
l 50
 
4.0%
Other values (2) 100
8.0%

Interactions

2024-07-14T14:42:29.123415image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.020047image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.373897image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.706840image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:29.209681image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.118041image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.465876image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.795403image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:29.292960image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.200046image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.542390image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.880604image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:29.377968image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.286631image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.629960image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-07-14T14:42:28.962038image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-07-14T14:42:30.899475image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
petal_lengthpetal_widthsepal_lengthsepal_widthspecies
petal_length1.0000.9380.882-0.3100.890
petal_width0.9381.0000.834-0.2890.924
sepal_length0.8820.8341.000-0.1670.617
sepal_width-0.310-0.289-0.1671.0000.446
species0.8900.9240.6170.4461.000

Missing values

2024-07-14T14:42:29.483177image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-14T14:42:29.589185image/svg+xmlMatplotlib v3.8.4, 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
05.13.51.40.2setosa
14.93.01.40.2setosa
24.73.21.30.2setosa
34.63.11.50.2setosa
45.03.61.40.2setosa
55.43.91.70.4setosa
64.63.41.40.3setosa
75.03.41.50.2setosa
84.42.91.40.2setosa
94.93.11.50.1setosa
sepal_lengthsepal_widthpetal_lengthpetal_widthspecies
1406.73.15.62.4virginica
1416.93.15.12.3virginica
1425.82.75.11.9virginica
1436.83.25.92.3virginica
1446.73.35.72.5virginica
1456.73.05.22.3virginica
1466.32.55.01.9virginica
1476.53.05.22.0virginica
1486.23.45.42.3virginica
1495.93.05.11.8virginica

Duplicate rows

Most frequently occurring

sepal_lengthsepal_widthpetal_lengthpetal_widthspecies# duplicates
05.82.75.11.9virginica2