Pandas Basics

This book is intended for those who plan to become data scientists as well as anyone who needs to perform data cleaning tasks using Pandas and NumPy. --

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Bibliographic Details
Main Author: Campesato, Oswald.
Format: Electronic
Language: English
Published: Bloomfield : Mercury Learning & Information, 2022.
Subjects:
Data mining.
Python (Computer program language)
elektronické knihy
electronic books
ISBN: 9781683928256
1683928253
Physical Description: 1 online resource (215 p.)

Cover

Table of contents

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035 |a (OCoLC)1354205722  |z (OCoLC)1354515675 
100 1 |a Campesato, Oswald. 
245 1 0 |a Pandas Basics  |h [electronic resource]. 
260 |a Bloomfield :  |b Mercury Learning & Information,  |c 2022. 
300 |a 1 online resource (215 p.) 
500 |a Description based upon print version of record. 
505 0 |a Cover -- Title Page -- Copyright -- Dedication -- Contents -- Preface -- Chapter 1: Introduction to Python -- Tools for Python -- easy_install and pip -- virtualenv -- IPython -- Python Installation -- Setting the PATH Environment Variable (Windows Only) -- Launching Python on Your Machine -- The Python Interactive Interpreter -- Python Identifiers -- Lines, Indentation, and Multi-lines -- Quotations and Comments -- Saving Your Code in a Module -- Some Standard Modules -- The help() and dir() Functions -- Compile Time and Runtime Code Checking -- Simple Data Types -- Working with Numbers 
505 8 |a Working with Other Bases -- The chr() Function -- The round() Function -- Formatting Numbers -- Working with Fractions -- Unicode and UTF-8 -- Working with Unicode -- Working with Strings -- Comparing Strings -- Formatting Strings -- Uninitialized Variables and the Value None -- Slicing and Splicing Strings -- Testing for Digits and Alphabetic Characters -- Search and Replace a String in Other Strings -- Remove Leading and Trailing Characters -- Printing Text without NewLine Characters -- Text Alignment -- Working with Dates -- Converting Strings to Dates -- Exception Handling 
505 8 |a Handling User Input -- Command-line Arguments -- Summary -- Chapter 2: Working with Data -- Dealing with Data: What Can Go Wrong? -- What is Data Drift? -- What are Datasets? -- Data Preprocessing -- Data Types -- Preparing Datasets -- Discrete Data Versus Continuous Data -- Binning Continuous Data -- Scaling Numeric Data via Normalization -- Scaling Numeric Data via Standardization -- Scaling Numeric Data via Robust Standardization -- What to Look for in Categorical Data -- Mapping Categorical Data to Numeric Values -- Working with Dates -- Working with Currency 
505 8 |a Working with Outliers and Anomalies -- Outlier Detection/Removal -- Finding Outliers with NumPy -- Finding Outliers with Pandas -- Calculating Z-scores to Find Outliers -- Finding Outliers with SkLearn (Optional) -- Working with Missing Data -- Imputing Values: When is Zero a Valid Value? -- Dealing with Imbalanced Datasets -- What is SMOTE? -- SMOTE extensions -- The Bias-Variance Tradeoff -- Types of Bias in Data -- Analyzing Classifiers (Optional) -- What is LIME? -- What is ANOVA? -- Summary -- Chapter 3: Introduction to Probability and Statistics -- What is a Probability? 
505 8 |a Calculating the Expected Value -- Random Variables -- Discrete versus Continuous Random Variables -- Well-known Probability Distributions -- Fundamental Concepts in Statistics -- The Mean -- The Median -- The Mode -- The Variance and Standard Deviation -- Population, Sample, and Population Variance -- Chebyshev's Inequality -- What is a p-value? -- The Moments of a Function (Optional) -- What is Skewness? -- What is Kurtosis? -- Data and Statistics -- The Central Limit Theorem -- Correlation versus Causation -- Statistical Inferences -- Statistical Terms: RSS, TSS, R^2, and F1 Score 
500 |a What is an F1 score? 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book is intended for those who plan to become data scientists as well as anyone who needs to perform data cleaning tasks using Pandas and NumPy. --  |c Edited summary from book. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Data mining. 
650 0 |a Python (Computer program language) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Campesato, Oswald  |t Pandas Basics  |d Bloomfield : Mercury Learning & Information,c2022  |z 9781683928263 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpPB000023/pandas-basics?kpromoter=marc  |y Full text 

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