10. Exploring the Iris Data Set#

How to do it#

  1. Import the plotly.express module as px

import plotly.express as px

  1. Load the data set and check its type

iris = px.data.iris()
type(iris)

pandas.core.frame.DataFrame

  1. Inspect the DataFrame using the method head and tail

iris.head()
sepal_length sepal_width petal_length petal_width species species_id
0 5.1 3.5 1.4 0.2 setosa 1
1 4.9 3.0 1.4 0.2 setosa 1
2 4.7 3.2 1.3 0.2 setosa 1
3 4.6 3.1 1.5 0.2 setosa 1
4 5.0 3.6 1.4 0.2 setosa 1 
iris.tail()
sepal_length sepal_width petal_length petal_width species species_id
145 6.7 3.0 5.2 2.3 virginica 3
146 6.3 2.5 5.0 1.9 virginica 3
147 6.5 3.0 5.2 2.0 virginica 3
148 6.2 3.4 5.4 2.3 virginica 3
149 5.9 3.0 5.1 1.8 virginica 3

  1. Use the method describe

iris.describe()
sepal_length sepal_width petal_length petal_width species_id
count 150.000000 150.000000 150.000000 150.000000 150.000000
mean 5.843333 3.054000 3.758667 1.198667 2.000000
std 0.828066 0.433594 1.764420 0.763161 0.819232
min 4.300000 2.000000 1.000000 0.100000 1.000000
25% 5.100000 2.800000 1.600000 0.300000 1.000000
50% 5.800000 3.000000 4.350000 1.300000 2.000000
75% 6.400000 3.300000 5.100000 1.800000 3.000000
max 7.900000 4.400000 6.900000 2.500000 3.000000

  1. Make a scatter plot to visualize the relationship between petal lenght and petal width

fig = px.scatter(iris, x='petal_length', y ='petal_width')
fig.show()

  1. Enhance the scatter plot by adding color the dots according to the species

fig = px.scatter(iris, x='petal_length', y='petal_width', color='species')
fig.show()

  1. Make a similar scatter plot to visualize the relationship between sepal lenght and sepal width by species

fig = px.scatter(iris, x='sepal_length', y='sepal_width', color='species')
fig.show()