Overview

Brought to you by YData

Dataset statistics

Number of variables6
Number of observations150
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory48.9 B

Variable types

Numeric5
Categorical1

Alerts

Id is highly overall correlated with PetalLengthCm and 3 other fieldsHigh correlation
PetalLengthCm is highly overall correlated with Id and 3 other fieldsHigh correlation
PetalWidthCm is highly overall correlated with Id and 3 other fieldsHigh correlation
SepalLengthCm is highly overall correlated with Id and 3 other fieldsHigh correlation
Species is highly overall correlated with Id and 3 other fieldsHigh correlation
Id is uniformly distributedUniform
Species is uniformly distributedUniform
Id has unique valuesUnique

Reproduction

Analysis started2025-10-09 15:38:56.152303
Analysis finished2025-10-09 15:38:58.021258
Duration1.87 second
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

Id
Real number (ℝ)

High correlation  Uniform  Unique 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.5
Minimum1
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2025-10-09T09:38:58.086778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.45
Q138.25
median75.5
Q3112.75
95-th percentile142.55
Maximum150
Range149
Interquartile range (IQR)74.5

Descriptive statistics

Standard deviation43.445368
Coefficient of variation (CV)0.57543534
Kurtosis-1.2
Mean75.5
Median Absolute Deviation (MAD)37.5
Skewness0
Sum11325
Variance1887.5
MonotonicityStrictly increasing
2025-10-09T09:38:58.183297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
0.7%
21
 
0.7%
31
 
0.7%
41
 
0.7%
51
 
0.7%
61
 
0.7%
71
 
0.7%
81
 
0.7%
91
 
0.7%
101
 
0.7%
Other values (140)140
93.3%
ValueCountFrequency (%)
11
0.7%
21
0.7%
31
0.7%
41
0.7%
51
0.7%
61
0.7%
71
0.7%
81
0.7%
91
0.7%
101
0.7%
ValueCountFrequency (%)
1501
0.7%
1491
0.7%
1481
0.7%
1471
0.7%
1461
0.7%
1451
0.7%
1441
0.7%
1431
0.7%
1421
0.7%
1411
0.7%

SepalLengthCm
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
2025-10-09T09:38:58.266832image/svg+xmlMatplotlib v3.10.0, 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
2025-10-09T09:38:58.344359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
510
 
6.7%
6.39
 
6.0%
5.19
 
6.0%
6.78
 
5.3%
5.78
 
5.3%
6.47
 
4.7%
5.57
 
4.7%
5.87
 
4.7%
4.96
 
4.0%
66
 
4.0%
Other values (25)73
48.7%
ValueCountFrequency (%)
4.31
 
0.7%
4.43
 
2.0%
4.51
 
0.7%
4.64
 
2.7%
4.72
 
1.3%
4.85
3.3%
4.96
4.0%
510
6.7%
5.19
6.0%
5.24
 
2.7%
ValueCountFrequency (%)
7.91
 
0.7%
7.74
2.7%
7.61
 
0.7%
7.41
 
0.7%
7.31
 
0.7%
7.23
2.0%
7.11
 
0.7%
71
 
0.7%
6.94
2.7%
6.83
2.0%

SepalWidthCm
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
2025-10-09T09:38:58.414892image/svg+xmlMatplotlib v3.10.0, 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
2025-10-09T09:38:58.486673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
326
17.3%
2.814
9.3%
3.213
 
8.7%
3.412
 
8.0%
3.112
 
8.0%
2.910
 
6.7%
2.79
 
6.0%
2.58
 
5.3%
3.36
 
4.0%
3.56
 
4.0%
Other values (13)34
22.7%
ValueCountFrequency (%)
21
 
0.7%
2.23
 
2.0%
2.34
 
2.7%
2.43
 
2.0%
2.58
 
5.3%
2.65
 
3.3%
2.79
 
6.0%
2.814
9.3%
2.910
 
6.7%
326
17.3%
ValueCountFrequency (%)
4.41
 
0.7%
4.21
 
0.7%
4.11
 
0.7%
41
 
0.7%
3.92
 
1.3%
3.86
4.0%
3.73
 
2.0%
3.63
 
2.0%
3.56
4.0%
3.412
8.0%

PetalLengthCm
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
2025-10-09T09:38:58.558193image/svg+xmlMatplotlib v3.10.0, 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
2025-10-09T09:38:58.644720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1.514
 
9.3%
1.412
 
8.0%
4.58
 
5.3%
5.18
 
5.3%
1.37
 
4.7%
1.67
 
4.7%
5.66
 
4.0%
4.95
 
3.3%
45
 
3.3%
4.75
 
3.3%
Other values (33)73
48.7%
ValueCountFrequency (%)
11
 
0.7%
1.11
 
0.7%
1.22
 
1.3%
1.37
4.7%
1.412
8.0%
1.514
9.3%
1.67
4.7%
1.74
 
2.7%
1.92
 
1.3%
31
 
0.7%
ValueCountFrequency (%)
6.91
 
0.7%
6.72
1.3%
6.61
 
0.7%
6.41
 
0.7%
6.31
 
0.7%
6.13
2.0%
62
1.3%
5.92
1.3%
5.83
2.0%
5.73
2.0%

PetalWidthCm
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
2025-10-09T09:38:58.721243image/svg+xmlMatplotlib v3.10.0, 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
2025-10-09T09:38:58.792243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.228
18.7%
1.313
 
8.7%
1.512
 
8.0%
1.812
 
8.0%
1.48
 
5.3%
2.38
 
5.3%
0.47
 
4.7%
17
 
4.7%
0.37
 
4.7%
0.16
 
4.0%
Other values (12)42
28.0%
ValueCountFrequency (%)
0.16
 
4.0%
0.228
18.7%
0.37
 
4.7%
0.47
 
4.7%
0.51
 
0.7%
0.61
 
0.7%
17
 
4.7%
1.13
 
2.0%
1.25
 
3.3%
1.313
8.7%
ValueCountFrequency (%)
2.53
 
2.0%
2.43
 
2.0%
2.38
5.3%
2.23
 
2.0%
2.16
4.0%
26
4.0%
1.95
3.3%
1.812
8.0%
1.72
 
1.3%
1.64
 
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-setosa50
33.3%
Iris-versicolor50
33.3%
Iris-virginica50
33.3%

Length

2025-10-09T09:38:58.871775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-09T09:38:58.999803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
iris-setosa50
33.3%
iris-versicolor50
33.3%
iris-virginica50
33.3%

Most occurring characters

ValueCountFrequency (%)
i350
17.5%
r300
15.0%
s300
15.0%
I150
7.5%
-150
7.5%
o150
7.5%
e100
 
5.0%
a100
 
5.0%
v100
 
5.0%
c100
 
5.0%
Other values (4)200
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)2000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i350
17.5%
r300
15.0%
s300
15.0%
I150
7.5%
-150
7.5%
o150
7.5%
e100
 
5.0%
a100
 
5.0%
v100
 
5.0%
c100
 
5.0%
Other values (4)200
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i350
17.5%
r300
15.0%
s300
15.0%
I150
7.5%
-150
7.5%
o150
7.5%
e100
 
5.0%
a100
 
5.0%
v100
 
5.0%
c100
 
5.0%
Other values (4)200
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i350
17.5%
r300
15.0%
s300
15.0%
I150
7.5%
-150
7.5%
o150
7.5%
e100
 
5.0%
a100
 
5.0%
v100
 
5.0%
c100
 
5.0%
Other values (4)200
10.0%

Interactions

2025-10-09T09:38:57.565377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.245091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.566967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.893716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.199965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.626928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.314624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.634474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.958255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.262489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.692155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.383257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.698486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.019853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.327277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.750806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.444341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.763515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.078530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.386291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.812537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.506245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:56.829060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.140062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-09T09:38:57.503850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-10-09T09:38:59.047567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
IdPetalLengthCmPetalWidthCmSepalLengthCmSepalWidthCmSpecies
Id1.0000.8680.8790.734-0.4120.904
PetalLengthCm0.8681.0000.9360.881-0.3030.890
PetalWidthCm0.8790.9361.0000.834-0.2780.924
SepalLengthCm0.7340.8810.8341.000-0.1590.617
SepalWidthCm-0.412-0.303-0.278-0.1591.0000.437
Species0.9040.8900.9240.6170.4371.000

Missing values

2025-10-09T09:38:57.899126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-09T09:38:57.971647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

IdSepalLengthCmSepalWidthCmPetalLengthCmPetalWidthCmSpecies
015.13.51.40.2Iris-setosa
124.93.01.40.2Iris-setosa
234.73.21.30.2Iris-setosa
344.63.11.50.2Iris-setosa
455.03.61.40.2Iris-setosa
565.43.91.70.4Iris-setosa
674.63.41.40.3Iris-setosa
785.03.41.50.2Iris-setosa
894.42.91.40.2Iris-setosa
9104.93.11.50.1Iris-setosa
IdSepalLengthCmSepalWidthCmPetalLengthCmPetalWidthCmSpecies
1401416.73.15.62.4Iris-virginica
1411426.93.15.12.3Iris-virginica
1421435.82.75.11.9Iris-virginica
1431446.83.25.92.3Iris-virginica
1441456.73.35.72.5Iris-virginica
1451466.73.05.22.3Iris-virginica
1461476.32.55.01.9Iris-virginica
1471486.53.05.22.0Iris-virginica
1481496.23.45.42.3Iris-virginica
1491505.93.05.11.8Iris-virginica