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Create Task 2

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	`1`	`+import seaborn as sns`
	`2`	`+import pandas as pd`
	`3`	`+import matplotlib.pyplot as plt`
	`4`	`+`
	`5`	`+# Load the Iris dataset from Seaborn`
	`6`	`+iris = sns.load_dataset("iris")`
	`7`	`+numeric_iris = iris.drop(columns='species')`
	`8`	`+`
	`9`	`+# Display the first few rows of the dataset`
	`10`	`+print("First few rows of the dataset:")`
	`11`	`+print(iris.head())`
	`12`	`+`
	`13`	`+# Summary statistics`
	`14`	`+print("\nSummary statistics:")`
	`15`	`+print(iris.describe())`
	`16`	`+`
	`17`	`+# Checking for missing values`
	`18`	`+print("\nMissing values:")`
	`19`	`+print(iris.isnull().sum())`
	`20`	`+`
	`21`	`+# Visualizations`
	`22`	`+# Pairplot`
	`23`	`+sns.pairplot(iris, hue="species")`
	`24`	`+plt.title("Pairplot of Iris Dataset")`
	`25`	`+plt.show()`
	`26`	`+`
	`27`	`+# Boxplot`
	`28`	`+plt.figure(figsize=(10, 6))`
	`29`	`+sns.boxplot(data=iris, orient="h")`
	`30`	`+plt.title("Boxplot of Iris Dataset")`
	`31`	`+plt.show()`
	`32`	`+`
	`33`	`+# Histograms`
	`34`	`+plt.figure(figsize=(10, 6))`
	`35`	`+iris.hist()`
	`36`	`+plt.suptitle("Histograms of Iris Dataset")`
	`37`	`+plt.show()`
	`38`	`+`
	`39`	`+# Correlation heatmap`
	`40`	`+plt.figure(figsize=(8, 6))`
	`41`	`+sns.heatmap(numeric_iris.corr(), annot=True, cmap="coolwarm")`
	`42`	`+plt.title("Correlation Heatmap of Iris Dataset")`
	`43`	`+plt.show()`

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