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Index
Become a Python Data Analyst Title Page Copyright and Credits Become a Python Data Analyst Packt Upsell Why subscribe? Packt.com Contributor About the author Packt is searching for authors like you Table of Contents Preface Who this book is for What this book covers To get the most out of this book Download the example code files Download the color images Conventions used Get in touch Reviews The Anaconda Distribution and Jupyter Notebook The Anaconda distribution Installing Anaconda Jupyter Notebook Creating your own Jupyter Notebook Notebook user interfaces Using the Jupyter Notebook Running code in a code cell Running markdown syntax in a text cell Styles and formats Lists Useful keyboard shortcuts Summary Vectorizing Operations with NumPy Introduction to NumPy Problems and solutions  NumPy arrays Creating arrays in NumPy Creating arrays from lists Creating arrays from built-in NumPy functions Attributes of arrays Basic math with arrays Common manipulations with arrays Indexing arrays Slicing arrays Reshaping arrays Using NumPy for simulations Coin flips Simulating stock returns Summary Pandas - Everyone's Favorite Data Analysis Library Introduction to the pandas library Important objects in pandas Series Creating a pandas series DataFrames Creating a pandas DataFrame Anatomy of a DataFrame Operations and manipulations of pandas Inspection of data Selection, addition, and deletion of data Slicing DataFrames Selection by labels Answering simple questions about a dataset Total employees by department in the dataset Overall attrition rate Average hourly rate Average number of years Employees with the most number of years Overall employee satisfaction Answering further questions Employees with Low JobSatisfaction Employees with both Low JobSatisfaction and JobInvolvement Employee comparison Summary Visualization and Exploratory Data Analysis Introducing Matplotlib Terminologies in Matplotlib Introduction to pyplot Object-oriented interface Common customizations Colors Colornames Setting axis limits Setting ticks and tick labels Legend Annotations Producing grids, horizontal, and vertical lines EDA with seaborn and pandas Understanding the seaborn library Performing exploratory data analysis Key objectives when performing data analysis Types of variable Analyzing variables individually Understanding the main variable Numerical variables Categorical variables Relationships between variables Scatter plot Box plot Complex conditional plots Summary Statistical Computing with Python Introduction to SciPy Statistics subpackage  Confidence intervals Probability calculations Hypothesis testing Performing statistical tests  Summary Introduction to Predictive Analytics Models Predictive analytics and machine learning Understanding the scikit-learn library scikit-learn Building a regression model using scikit-learn Regression model to predict house prices Summary Other Books You May Enjoy Leave a review - let other readers know what you think
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