Data Analysis with Pandas and Python

Installation and Setup
1 Introduction to the Course
2 Mac OS – Download the Anaconda Distribution
3 Mac OS – Install Anaconda Distribution
4 Mac OS – Access the Terminal
5 Mac OS – Update Anaconda Libraries
6 Mac OS – Unpack Course Materials + The Startdown and Shutdown Process
7 Windows – Download the Anaconda Distribution
8 Windows – Install Anaconda Distribution
9 Windows – Access the Command Prompt and Update Anaconda Libraries
10 Windows – Unpack Course Materials + The Startdown and Shutdown Process
11 Intro to the Jupyter Notebook Interface
12 Cell Types and Cell Modes
13 Code Cell Execution
14 Popular Keyboard Shortcuts
15 Import Libraries into Jupyter Notebook
16 Python Crash Course, Part 1 – Data Types and Variables
17 Python Crash Course, Part 2 – Lists
18 Python Crash Course, Part 3 – Dictionaries
19 Python Crash Course, Part 4 – Operators
20 Python Crash Course, Part 5 – Functions

Series
21 Create Jupyter Notebook for the Series Module
22 Create A Series Object from a Python List
23 Create A Series Object from a Python Dictionary
24 Intro to Attributes
25 Intro to Methods
26 Parameters and Arguments
27 Import Series with the .read_csv() Method
28 The .head() and .tail() Methods
29 Python Built-In Functions
31 The .sort_values() Method
32 The inplace Parameter
33 The .sort_index() Method
34 Python’s in Keyword
35 Extract Series Values by Index Position
36 Extract Series Values by Index Label
37 The .get() Method on a Series
38 Math Methods on Series Objects
39 The .idxmax() and .idxmin() Methods
40 The .value_counts() Method
41 The .apply() Method
42 The .map() Method

DataFrames I
43 Intro to DataFrames I Module
44 Shared Methods and Attributes between Series and DataFrames
45 Differences between Shared Methods
46 Select One Column from a DataFrame
47 Select Two or More Columns from a DataFrame
48 Add New Column to DataFrame
49 Broadcasting Operations
50 A Review of the .value_counts() Method
51 Drop Rows with Null Values
52 Fill in Null Values with the .fillna() Method
53 The .astype() Method
54 Sort a DataFrame with the .sort_values() Method, Part I
55 Sort a DataFrame with the .sort_values() Method, Part II
56 Sort DataFrame with the .sort_index() Method

DataFrames II
57 This Module’s Dataset + Memory Optimization
58 Filter a DataFrame Based on A Condition
59 Filter with More than One Condition (AND)
60 Filter with More than One Condition (OR)
61 The .isin() Method
62 The .isnull() and .notnull() Methods
63 The .between() Method
64 The .duplicated() Method
65 The .drop_duplicates() Method
66 The .unique() and .nunique() Methods

DataFrames III
67 Intro to the DataFrames III Module + Import Dataset
68 The .set_index() and .reset_index() Methods
69 Retrieve Rows by Index Label with .loc[]
71 The Catch-All .ix[] Method
72 Second Arguments to .loc[], .iloc[], and .ix[] Methods
73 Set New Values for a Specific Cell or Row
74 Set Multiple Values in DataFrame
75 Rename Index Labels or Columns in a DataFrame
76 Delete Rows or Columns from a DataFrame
77 Create Random Sample with the .sample() Method
78 The .nsmallest() and .nlargest() Methods
79 Filtering with the .where() Method
80 The .query() Method
81 A Review of the .apply() Method on Single Columns
82 The .apply() Method with Row Values
83 The .copy() Method

Working with Text Data#
84 Intro to the Working with Text Data Module
85 Common String Methods – lower, upper, title, and len
86 The .str.replace() Method
87 Filtering with String Methods
88 More String Methods – strip, lstrip, and rstrip
89 String Methods on Index and Columns
90 Split Strings by Characters with .str.split() Method
91 More Practice with Splits
92 The expand and n Parameters of the .str.split() Method

MultiIndex
93 Intro to the MultiIndex Module
94 Create a MultiIndex with the set_index() Method
95 The .get_level_values() Method
96 The .set_names() Method
97 The sort_index() Method
98 Extract Rows from a MultiIndex DataFrame
99 The .transpose() Method and MultiIndex on Column Level
100 The .swaplevel() Method
101 The .stack() Method
102 The .unstack() Method, Part 1
103 The .unstack() Method, Part 2
104 The .unstack() Method, Part 3
105 The .pivot() Method
106 The .pivot_table() Method
107 The pd.melt() Method

GroupBy
108 Intro to the Groupby Module
109 First Operations with groupby Object
110 Retrieve A Group with the .get_group() Method
111 Methods on the Groupby Object and DataFrame Columns
112 Grouping by Multiple Columns
113 The .agg() Method
114 Iterating through Groups

Merging, Joining, and Concatenating#
115 Intro to the Merging, Joining, and Concatenating Module
116 The pd.concat() Method, Part 1
117 The pd.concat() Method, Part 2
118 The .append() Method on a DataFrame
119 Inner Joins, Part 1
120 Inner Joins, Part 2
121 Outer Joins
122 Left Joins
123 The left_on and right_on Parameters
124 Merging by Indexes with the left_index and right_index Parameters
125 The .join() Method
126 The pd.merge() Method

Working with Dates and Times#
127 Intro to the Working with Dates and Times Module
128 Review of Python’s datetime Module
129 The Pandas Timestamp Object
130 The Pandas DateTimeIndex Object
131 The pd.to_datetime() Method
132 Create Range of Dates with the pd.date_range() Method, Part 1
133 Create Range of Dates with the pd.date_range() Method, Part 2
134 Create Range of Dates with the pd.date_range() Method, Part 3
135 The .dt Accessor
136 Install Pandas-datareader Library
137 Import Financial Data Set with Pandas_datareader Library
138 Selecting Rows from a DataFrame with a DateTimeIndex
139 Timestamp Object Attributes
140 The .truncate() Method
141 pd.DateOffset Objects
142 More Fun with pd.DateOffset Objects
143 The Pandas Timedelta Object
144 Timedeltas in a Dataset

Panels
145 Intro to the Module + Fetch Panel Dataset from Google Finance
146 The Axes of a Panel Object
147 Panel Attributes
148 Use Bracket Notation to Extract a DataFrame from a Panel
149 Extracting with the .loc, .iloc, and .ix Methods
150 Convert Panel to a MultiIndex DataFrame (and Vice Versa)
151 The .major_xs() Method
152 The .minor_xs() Method
153 Transpose a Panel with the .transpose() Method
154 The .swapaxes() Method

Input and Output#
155 Intro to the Input and Output Module
156 Feed pd.read_csv() Method a URL Argument
157 Quick Object Conversions
158 Export DataFrame to CSV File with the .to_csv() Method
159 Install xlrd and openpyxl Libraries to Read and Write Excel Files
160 Import Excel File into Pandas
161 Export Excel File

Visualization
162 Intro to Visualization Module
163 The .plot() Method
164 Modifying Aesthetics with Templates
165 Bar Graphs
166 Pie Charts
167 Histograms

Options and Settings
168 Introduction to the Options and Settings Module
169 Changing Pandas Options with Attributes and Dot Syntax
170 Changing Pandas Options with Methods
171 The precision Option

Conclusion
172 Conclusion