Advanced Techniques for Exploring Data Sets with Pandas
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Advanced Techniques for Exploring Data Sets with Pandas

Explore popular datasets in R, while mastering advanced techniques used for them
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
0 students enrolled
Created by Packt Publishing
Last updated 8/2017
English
Curiosity Sale
Current price: $10 Original price: $125 Discount: 92% off
30-Day Money-Back Guarantee
Includes:
  • 2 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Learn how to read different kinds of data into pandas DataFrames for data analysis
  • Practice how to manipulate, transform and apply formulas on data imported into pandas DataFrames
  • Master analyzing and visualizing different kinds of data using pandas to gain real-world insights
  • Use pandas to make predictions using Machine Learning and Scikit-learn
  • Work with big data using pandas
  • Manipulate quantitative financial data and model time-series data, perform algorithmic trading, derive results on fixed and moving windows, and more
  • Advance to the next level in pandas by learning complex techniques
  • Take transformed data out of pandas DataFrames and into the formats your application expects
View Curriculum
Requirements
  • Some programming experience in Python will be helpful to get the most out of this course.
Description

In this course, you will learn how to start using pandas from end-to-end: from getting your data into pandas; using pandas to manipulate, transform, analyze, and visualize data; to ultimately taking your transformed data out of pandas into any number of formats.

This course will get you (or anyone who has never used pandas) started on using it as a complete end-to-end data analysis workflow. You will start by setting up Python, pandas, and Jupyter notebooks. You will learn how to use Jupyter notebooks to run Python code. We will then show how to get data into pandas and do some exploratory analysis. You will learn how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some cool visualizations for your audience. Finally, you will wrap-up your newly gained pandas knowledge by learning how to get data out of pandas into some popular file formats.

About the Author

Harish Garg is a Data Analyst, author, and Software Developer who is really passionate about Data Science and the Python programming language. He is a graduate from Udacity's Data Analyst Nanodegree program. He has 17 years of industry experience, which includes data analysis using Python, developing and testing enterprise and consumer software, managing projects and software teams, and creating training material and tutorials. Harish also worked for 11 years for Intel Security (previously McAfee, Inc.).

He regularly contributes articles and tutorials on data analysis and Python. He is also active in the open data community and is a contributing member of the Data4Democracy open data initiative. He has written data analysis pieces for think tan takshashila.

Who is the target audience?
  • If you are a budding data scientist looking to learn the popular pandas library, or a Python developer looking to step into the world of data analysis, this video is the ideal resource you need to get started.
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Curriculum For This Course
26 Lectures
01:45:01
+
Working with Different Kinds of Datasets
4 Lectures 19:06

This video provides an overview of the entire course.

Preview 04:36

Exploring pandas read CSV method to work with CSV-based datasets.

Using Advanced Options While Reading Data from CSV Files
04:26

Exploring ways to work with an Excel dataset in pandas.

Reading Data from Excel Files
05:02

Explore working with different kinds of datasets in pandas apart from CSV and Excel.

Reading Data from Some Other Popular Formats
05:02
+
Data Selection
8 Lectures 29:27

Learn techniques on how to select a subset of data in pandas as Series.

Preview 05:01

Explore methods to select multiple rows and columns from a dataset in pandas.

Selecting Multiple Rows and Columns from a Pandas DataFrame
04:56

Explore sorting techniques on a pandas DataFrame or a series.

Sorting a Pandas DataFrame or a Series
03:03

Learn various methods of filtering data in pandas.

Filtering Rows of a Pandas DataFrame by Column Value
03:15

Learn how to apply multiple filters to a pandas DataFrame.

Applying Multiple Filter Criteria to a Pandas DataFrame
04:02

Learn how to use the "axis" parameter in pandas.

Using the "axis" Parameter in Pandas
03:10

Learn how to use string methods on series data in Pandas.

Using String Methods in Pandas
02:38

Learn about how to change the datatype of a pandas series.

Changing the Data Type of a Pandas Series
03:22
+
Manipulating, Transforming, and Reshaping Data
10 Lectures 40:45

Learn about modifying a Pandas DataFrame original object.

Preview 04:08

Learn how to split and aggregate data in groups using the “groupby” method.

Using the "groupby" Method
04:13

Explore how we can use various Pandas techniques to handle the missing data from our datasets.

Handling Missing Values in Pandas
04:58

Explore how to set index and use it for data analysis in pandas.

Indexing in Pandas DataFrames
03:28

Learn various methods for renaming column labels in pandas.

Renaming Columns in a Pandas DataFrame
03:39

Learn how to remove columns or rows from a dataset in pandas.

Removing Columns from a Pandas DataFrame
03:36

Learn how to work with date and time series data in pandas.

Working with Dates and Times Data
04:33

Learn what is “SettingWithCopyWarning” and how to get around it.

Handling SettingWithCopyWarning
03:44

Learn how to apply prebuilt and your own functions to Pandas Data objects.

Applying a Function to a Pandas Series or DataFrame
03:20

Learn how to combine two or more DataFrames using Pandas merge and concat methods.

Merging and Concatenating Multiple DataFrames into One
05:06
+
Visualizing Data Like a Pro
4 Lectures 15:43

Learn how to get started with plotting and control plot aesthetics.

Preview 05:53

Learn how to change the colors of a plot and work with plot color palettes.

Choosing the Colors for the Plots
03:18

Learn how to plot categorical data with seaborn.

Plotting Categorical Data
02:49

Learn to plot with data aware with grids using seaborn.

Plotting with Data Aware Grids
03:43
About the Instructor
Packt Publishing
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Tech Knowledge in Motion

Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.