  # Box plot and histogram study on iris data

NumPy | Python Methods and Functions

` Attribute Information: - & gt; sepal length in cm - & gt; sepal width in cm - & gt; petal length in cm - & gt; petal width in cm - & gt; class: Iris Setosa Iris Versicolour Iris Virginica Number of Instances: 150 Summary Statistics: Min Max Mean SD Class Correlation sepal length: 4.3 7.9 5.84 0.83 0.7826 sepal width: 2.0 4.4 3.05 0.43 -0.4194 petal length: 1.0 6.9 3.76 1.76 0.9490 (high! ) petal width: 0.1 2.5 1.20 0.76 0.9565 (high!) Class Distribution: 33.3% for each of 3 classes. `

 ` import ` ` numpy as np ` ` import ` ` pandas as pd ` ` import ` ` matplotlib.pyplot as plt `

 ` data ` ` = ` ` pd.read_csv (` `" Iris.csv "` `) `   ` print ` < code class = "plain"> (data.head ( ` 10 ` `)) `

Exit:

Description

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` data.describe () `

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Information

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` data.info () `

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Exit: Code # 1: divider length histogram

 ` plt.figure (figsize ` ` = ` ` (` ` 10 ` `, ` ` 7 ` `)) ` ` x ` ` = ` ` data [` ` "SepalLengthCm" ` `] `   ` plt.hist (x, bins ` ` = ` ` 20 ` `, color ` ` = ` ` "green" ` `) ` ` plt.title (` ` "Sepal Length in cm" ` `) `` plt.xlabel ( "Sepal_Length_cm" ) plt.ylabel ( "Count" ) `

Exit:

Code no. 2: divider width histogram

 ` plt.figure (figsize ` ` = ` ` (` ` 10 ` `, ` ` 7 )) `` x = data.SepalWidthCm   plt.hist (x, bins = 20 , color = "green" ) plt.title ( " Sepal Width in cm " ) plt.xlabel ( "Sepal_Width_cm" ) plt.ylabel ( "Count" )   plt.show () `

Output:

Code # 3: Petal length histogram

 ` plt.figure (figsize ` ` = ` ` (` ` 10 ` `, ` ` 7 ` `)) ` ` x ` ` = ` ` data.PetalLengthCm `   ` plt.hist (x, bins ` ` = 20 , color = " green " ) `` plt.title ( "Petal Length in cm" ) `` plt.xlabel ( "Petal_Length_cm" ` `) ` ` plt.ylabel (` ` "Count" ` `) `   ` plt.show () `

Exit:

Code # 4: histogram for petal width

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 ` plt.figure (figsize ` ` = ` ` (` ` 10 ` ` , ` ` 7 ` `)) ` ` x ` ` = ` ` data.PetalWidthC m `   ` plt.hist (x, bins = 20 , color = "green" ) `` plt.title ( "Petal Width in cm" ) plt.xlabel ( "Petal_Width_cm" ) plt.ylabel ( " Count " )    plt.show () `
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Exit :

Code # 5:  Preparing data for the site

 ` # remove column ID ` ` new_data ` ` = ` ` data [[` ` "SepalLengthCm" ` `, ` ` "SepalWidthCm" ` `, ` ` "PetalLengthCm" ` `, ` ` "PetalWidthCm" ` `]] ` ` print ` ` (new_data.head ()) `

Output:

Code # 6: field for iris data

 ` plt .figure (figsize ` ` = ` ` (` ` 10 ` `, ` ` 7 ` `)) ` ` new_data.boxplot () `

Exit: