# 2.4 - Type of Plots

Last updated: February 16th, 2019

# Type of plots - Exercises¶

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

%matplotlib inline


### Exercise 1¶

Import the data/titanic.csv dataset.

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# your code goes here

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df = pd.read_csv('data/titanic.csv')



### Exercise 2¶

Draw a scatter plot showing Age vs Fare. Use alpha=0.5 to modify points opacity.

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# your code goes here

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plt.scatter(df['Age'], df['Fare'], alpha=0.5)


### Exercise 3¶

Draw a scatter plot showing Age vs Fare, using red dots for male and blue dots for female.

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# your code goes here

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colors = ['red' if x == 'male' else 'blue' for x in df['Sex']]

plt.scatter(df['Age'], df['Fare'], c=colors)


### Exercise 4¶

Draw a pie chart showing Sex proportion. Add the proportion number and sex labels within the plot.

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# your code goes here


To add proportion number use autopct parameter, to add sex labels use labels parameter.

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sex_count = df['Sex'].value_counts()

plt.pie(sex_count, autopct="%.2f%%", labels=sex_count.index)

plt.show()


### Exercise 5¶

Draw a histogram showing the Fare payed. Show 60 bins, and choose custom width and color.

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# your code goes here

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plt.hist(df['Fare'], bins=60, width=10, color='#3498db')

plt.show()


### Exercise 6¶

Draw a boxplot showing the Age of the passengers.

The Age column has some missing values, so before plotting remove them.

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# your code goes here

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plt.boxplot(df['Age'].dropna())

plt.show()


### Exercise 7¶

Draw a boxplot showing the Age of the passengers, grouped by Sex.

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# your code goes here

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df.boxplot(column='Age', by='Sex')