• Introduction to Data Analysis with Pandas and Python

• About Me

• Completed Course Files

• MacOS - Download the Anaconda Distribution, our Python development environment

• MacOS - Install Anaconda Distribution

• MacOS - Access the Terminal Application

• Introduction to Pandas Preview

• MacOS - Create conda Environment and Install pandas and Jupyter Notebook

• Windows - Install Anaconda Distribution

• Windows - Create conda Environment and Install pandas and Jupyter Notebook

• Windows - Unpack Course Materials + The Startdown and Shutdown Process

• Intro to the Jupyter Notebook Interface

• Cell Types and Cell Modes in Jupyter Notebook

• Code Cell Execution in Jupyter Notebook

• Import Libraries into Jupyter Notebook

• Troubleshooting Issues with Jupyter Notebook

• Intro to the Python Crash Course Preview

• Comments

• Basic Data Types

• Operators

• Variables

• Built-in Functions

• Custom Functions

• String Methods

• Lists

• Index Positions and Slicing

• Dictionaries

• Create Jupyter Notebook for the Series Module

• Create A Series Object from a Python List

• Create a Series Object

• Intro to Attributes on a Series Object

• Intro to Methods on a Series Object

• Parameters and Arguments

• Create Series from Dataset with the pd.read_csv Method

• Import Series with the read_csv Method

• Use the head and tail Methods to Return Rows from Beginning and End of Dataset

• Passing pandas Objects to Python Built-In Functions

• Accessing More Series Attributes

• Use the sort_values method to sort a Series in ascending or descending order

• Use the inplace Parameter to permanently mutate a pandas data structure

• Use the sort_index Method to Sort the Index of a pandas Series object

• The sort_values and sort_index Methods

• Use Python's in Keyword to Check for Inclusion in Series values or index

• Extract Series Values by Index Positiox

• Extract Series Values by Index Label

• Extract Series Values by Index Position or Index Label

• Use the get Method to Retrieve a Value for an index label in a Series

• Math Methods on Series Objects

• Use the idxmax and idxmin Methods to Find Index of Greatest or Smallest Value

• Use the value_counts Method to See Counts of Unique Values within a Series

• Use the apply Method to Invoke a Function on Every Series Values

• The Series#map Method

• A Review of the Series Module

• Intro to DataFrames I Module

• Shared Methods and Attributes between Series and DataFrames

• Differences between Shared Methods

• Select One Column from a DataFrame Preview

• Select One Column from a DataFrame

• Select Two or More Columns from a DataFrame

• Select Two or More Columns from a DataFrame

• Add New Column to DataFrame

• Broadcasting Operations on DataFrames

• A Review of the value_counts Method

• Drop DataFrame Rows with Null Values with the dropna Method

• Delete DataFrame Rows with Missing Values

• Fill in Null DataFrame Values with the fillna Method

• Convert DataFrame Column Types with the astype Method

• Sort a DataFrame with the sort_values Method, Part I Preview

• Sort a DataFrame with the sort_values Method, Part II

• The sort_values Method on a DataFrame

• Sort DataFrameIndexwith the sort_index Method

• Rank Series Values with the rank Method

• This Module's Dataset + Memory Optimization

• Filter a DataFrame Based on A Condition Preview

• Filter DataFrame with More than One Condition (AND - &)

• Filter DataFrame with More than One Condition (OR - |)

• Check for Inclusion with the isin Method

• Check for Null and Present DataFrame Values with the isnull and notnull Methods

• Check For Inclusion Within a Range of Values with the between Method

• Check for Duplicate DataFrame Rows with the duplicated Method

• Delete Duplicate DataFrame Rows with the drop_duplicates Method

• Identify and Count Unique Values with the unique and nunique Methods

• Intro to the DataFrames III Module + Import Dataset

• Use the set_index and reset_index methods to define a new DataFrame index

• Retrieve Rows by Index Label with loc Accessor

• Retrieve Rows by Index Position with iloc Accessor

• Passing second arguments to the loc and iloc Accessors

• Set New Value for a Specific Cell or Cells In a Row

• Set Multiple Values in a DataFrame

• Rename Index Labels or Columns in a DataFrame Preview

• Delete Rows or Columns from a DataFrame

• Create Random Sample with the sample Method

• Use the nsmallest / nlargest methods to get rows with smallest / largest values.

• Filter A DataFrame with the where method

• Filter A DataFrame with the query method

• A Review of the apply Method on a pandas Series Object

• Apply a Function to every DataFrame Row with the apply Method

• Create a Copy of a DataFrame with the copy Method

• Intro to the Working with Text Data Section

• Common String Methods - lower, upper, title, and len Preview

• Use the str.replace method to replace all occurrences of character with another

• Filter a DataFrame's Rows with String Methods

• More DataFrame String Methods - strip, lstrip, and rstrip

• Invoke String Methods on DataFrame Index and Columns

• Split Strings by Characters with the str.split Method

• More Practice with the str.split method on a Series

• Exploring the expand and n Parameters of the str.split Method

• Intro to the MultiIndex Module

• Create a MultiIndex on a DataFrame with the set_index Method

• Extract Index Level Values with the get_level_values Method

• Change Index Level Name with the set_names Method

• The sort_index Method on a MultiIndexDataFrame

• Extract Rows from a MultiIndexDataFrame

• The transpose Method on a MultiIndexDataFrame

• The .swaplevel() Method

• The .stack() Method Preview

• The .unstack() Method, Part 1

• The .unstack() Method, Part 2

• The .unstack() Method, Part 3

• The pivot Method

• Use the pivot_table method to create an aggregate summary of a DataFrame

• Use the pd.melt method to create a narrow dataset from a wide one Preview

• Intro to the Groupby Module

• First Operations with groupby Object

• Retrieve a group from a GroupBy object with the get_group Method

• Methods on the Groupby Object and DataFrame Columns

• Grouping by Multiple Columns

• Iterating through Groups