Book Image

Python Data Analysis - Third Edition

By : Avinash Navlani, Ivan Idris
5 (1)
Book Image

Python Data Analysis - Third Edition

5 (1)
By: Avinash Navlani, Ivan Idris

Overview of this book

Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you’ll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines. Starting with the essential statistical and data analysis fundamentals using Python, you’ll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You’ll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you’ll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you’ll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask. By the end of this data analysis book, you’ll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.
Table of Contents (20 chapters)
Section 1: Foundation for Data Analysis
Section 2: Exploratory Data Analysis and Data Cleaning
Section 3: Deep Dive into Machine Learning
Section 4: NLP, Image Analytics, and Parallel Computing

Changing the data type of NumPy arrays

As we have seen in the preceding sections, NumPy supports multiple data types, such as int, float, and complex numbers. The astype() function converts the data type of the array. Let's see an example of the astype() function:

# Create an array
print("Integer Array:",arr)

# Change datatype of array

# print array
print("Float Array:", arr)

# Check new data type of array
print("Changed Datatype:", arr.dtype)

In the preceding code, we have created one NumPy array and checked its data type using the dtype attribute.

Let's change the data type of an array using the astype() function:

# Change datatype of array

# Check new data type of array


In the preceding code, we have changed the column data type from integer to float using astype().

The tolist() function converts a NumPy array into a Python list. Let's see an...