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The Supervised Learning Workshop

You're reading from   The Supervised Learning Workshop Predict outcomes from data by building your own powerful predictive models with machine learning in Python

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781800209046
Length 532 pages
Edition 2nd Edition
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Authors (4):
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Blaine Bateman Blaine Bateman
Author Profile Icon Blaine Bateman
Blaine Bateman
Ashish Ranjan Jha Ashish Ranjan Jha
Author Profile Icon Ashish Ranjan Jha
Ashish Ranjan Jha
Ishita Mathur Ishita Mathur
Author Profile Icon Ishita Mathur
Ishita Mathur
Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
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Toc

1. Fundamentals

Activity 1.01: Implementing Pandas Functions

  1. Open a new Jupyter notebook.
  2. Use pandas to load the Titanic dataset:
    import pandas as pd
    df = pd.read_csv(r'../Datasets/titanic.csv')
  3. Use the head function on the dataset as follows:
    # Have a look at the first 5 sample of the data
    df.head()

    The output will be as follows:

    Figure 1.26: First five rows

  4. Use the describe function as follows:
    df.describe(include='all')

    The output will be as follows:

    Figure 1.27: Output of describe()

  5. We do not need the Unnamed: 0 column. We can remove the column without using the del command, as follows:
    del df['Unnamed: 0']
    df = df[df.columns[1:]] # Use the columns
    df.head()

    The output will be as follows:

    Figure 1.28: First five rows after deleting the Unnamed: 0 column

  6. Compute the mean, standard deviation, minimum, and maximum values for the columns of the DataFrame without using describe:
    df.mean()

    The output will be as follows:

    Figure 1.29: Output...

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