Section 1 : Section 1 Installation and Setup

Lecture 1 About Proctor Testing Pdf
Lecture 2 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 3 Completed Course Files Text
Lecture 4 MacOS - Download the Anaconda Distribution, our Python 4:20
Lecture 5 MacOS - Install Anaconda Distribution 10:36
Lecture 6 MacOS - Access the Terminal Application 8:30
Lecture 7 MacOS - Create conda Environment and Install pandas 13:4
Lecture 8 MacOS - Unpack Course Materials + The Start and Shutdown 12:27
Lecture 9 Windows - Download the Anaconda Distribution
Lecture 10 Windows - Install Anaconda Distribution 7:49
Lecture 11 Windows - Create conda Environment and Install pandas 18:4
Lecture 12 Windows - Unpack Course Materials + The Startdown 13:19
Lecture 13 Intro to the Jupyter Notebook Interface 9:50
Lecture 14 Cell Types and Cell Modes in Jupyter Notebook 7:34
Lecture 15 Code Cell Execution in Jupyter Notebook 3:13
Lecture 16 Popular Keyboard Shortcuts in Jupyter Notebook 3:38
Lecture 17 Import Libraries into Jupyter Notebook 8:26
Lecture 18 Troubleshooting Issues with Jupyter Notebook Text

Section 2 : Section 2 BONUS Python Crash Course

Lecture 19 Intro to the Python Crash Course 3:33
Lecture 20 Comments 3:18
Lecture 21 Basic Data Types 11:9
Lecture 22 Operators 15:38
Lecture 23 Variables 7:44
Lecture 24 Built-in Functions 10:27
Lecture 25 Custom Functions 16:30
Lecture 26 String Methods 20:45
Lecture 27 Lists 13:37
Lecture 28 Index Positions and Slicing 15:54
Lecture 29 Dictionaries 15:24

Section 3 : Section 3 Series

Lecture 30 Create Jupyter Notebook for the Series Module 2:15
Lecture 31 Create A Series Object from a Python List 10:58
Lecture 32 Create A Series Object from a Python Dictionary 3:6
Lecture 33 Coding Exercise SOLUTION Create a Series Object Text
Lecture 34 Intro to Attributes on a Series Object 7:17
Lecture 35 Intro to Methods on a Series Object 4:42
Lecture 36 Parameters and Arguments 10:10
Lecture 37 Create Series from Dataset with the pd 15:0
Lecture 38 Coding Exercise SOLUTION Import Series with the read_csv Text
Lecture 39 Use the head and tail Methods to Return Rows 3:41
Lecture 40 Passing pandas Objects to Python Built-In Functions 5:16
Lecture 41 Accessing More Series Attributes 6:8
Lecture 42 Use the sort_values method to sort a Series in ascending
Lecture 43 Use the inplace Parameter to permanently mutate a pandas 5:6
Lecture 44 Use the sort_index Method to Sort the Index of a pandas 4:41
Lecture 45 Coding Exercise SOLUTION The sort_values and sort_index Text
Lecture 46 Use Python's in Keyword to Check for Inclusion in Series
Lecture 47 Extract Series Values by Index Positiox 4:10
Lecture 48 Extract Series Values by Index Label 10:33
Lecture 49 Coding Exercise SOLUTION Extract Series Values by Index Text
Lecture 50 Use the get Method to Retrieve a Value for an index label 9:39
Lecture 51 Math Methods on Series Objects 5:40
Lecture 52 Use the idxmax and idxmin Methods to Find Index 3:12
Lecture 53 Use the value_counts Method to See Counts of Unique 3:37
Lecture 54 Use the apply Method to Invoke a Function on Every Series 6:44
Lecture 55 The Series#map Method 6:48

Section 4 : Section 4 DataFrames I Introduction

Lecture 56 Intro to DataFrames I Module 9:41
Lecture 57 Shared Methods and Attributes between Series 13:53
Lecture 58 Differences between Shared Methods 6:39
Lecture 59 Select One Column from a DataFrame 7:51
Lecture 60 Coding Exercise SOLUTION Select One Column from Text
Lecture 61 Select Two or More Columns from a DataFrame 5:10
Lecture 62 Coding Exercise SOLUTION Select Two or More Columns Text
Lecture 63 Add New Column to DataFrame 7:56
Lecture 64 Broadcasting Operations on DataFrames 9:5
Lecture 65 A Review of the value_counts Method 3:49
Lecture 66 Drop DataFrame Rows with Null Values with the dropna 6:36
Lecture 67 Coding Exercise SOLUTION Delete DataFrame Rows Text
Lecture 68 Fill in Null DataFrame Values with the fillna Method 4:23
Lecture 69 Convert DataFrame Column Types with the astype Method 10:34
Lecture 70 Sort a DataFrame with the sort_values Method, Part I 5:43
Lecture 71 Sort a DataFrame with the sort_values Method, Part II 4:9
Lecture 72 Coding Exercise SOLUTION The sort_values Method Text
Lecture 73 Sort DataFrame Indexwith the sort_index Method 2:54
Lecture 74 Rank Series Values with the rank Method 5:48

Section 5 : Section 5 DataFrames II Filtering Data

Lecture 75 This Module's Dataset + Memory Optimization 15:45
Lecture 76 Filter a DataFrame Based on A Condition 12:48
Lecture 77 Filter DataFrame with More than One Condition (AND - &) 4:39
Lecture 78 Filter DataFrame with More than One Condition (OR - ) 8:47
Lecture 79 Check for Inclusion with the isin Method 6:15
Lecture 80 Check for Null and Present DataFrame Values with the isnull 5:15
Lecture 81 Check For Inclusion Within a Range of Values 6:50
Lecture 82 Check for Duplicate DataFrame Rows with the duplicated 9:0
Lecture 83 Delete Duplicate DataFrame Rows with the drop_duplicates 8:13
Lecture 84 Identify and Count Unique Values with the unique 4:40

Section 6 : Section 6 DataFrames III Data Extraction

Lecture 85 Intro to the DataFrames III Module + Import Dataset 5:57
Lecture 86 Use the set_index and reset_index methods to define a new 9:25
Lecture 87 Retrieve Rows by Index Label with loc Accessor 17:8
Lecture 88 Retrieve Rows by Index Position with iloc Accessor 7:32
Lecture 89 Passing second arguments to the loc and iloc Accessors 9:10
Lecture 90 Set New Value for a Specific Cell or Cells In a Row 4:42
Lecture 91 Set Multiple Values in a DataFrame 6:13
Lecture 92 Rename Index Labels or Columns in a DataFrame 9:33
Lecture 93 Delete Rows or Columns from a DataFrame 7:40
Lecture 94 Create Random Sample with the sample Method 4:45
Lecture 95 Use the nsmallest nlargest methods to get rows 5:36
Lecture 96 Filter A DataFrame with the where method 5:1
Lecture 97 Filter A DataFrame with the query method 9:6
Lecture 98 A Review of the apply Method on a pandas Series Object 6:0
Lecture 99 Apply a Function to every DataFrame Row with the apply 7:11
Lecture 100 Create a Copy of a DataFrame with the copy Method 7:7

Section 7 : Section 7 Working with Text Data

Lecture 101 Intro to the Working with Text Data Section 6:23
Lecture 102 Common String Methods - lower, upper, title, and len 7:11
Lecture 103 Use the str 9:9
Lecture 104 Filter a DataFrame's Rows with String Methods 8:25
Lecture 105 More DataFrame String Methods - strip, lstrip, and rstrip 5:58
Lecture 106 Invoke String Methods on DataFrame Index and Columns 6:20
Lecture 107 Split Strings by Characters with the str 10:29
Lecture 108 More Practice with the str 8:33
Lecture 109 Exploring the expand and n Parameters of the str 8:44

Section 8 : Section 8 MultiIndex

Lecture 110 Intro to the MultiIndex Module 4:50
Lecture 111 Create a MultiIndex on a DataFrame with the set_index 10:36
Lecture 112 Extract Index Level Values with the get_level_values Method 4:17
Lecture 113 Change Index Level Name with the set_names Method 4:15
Lecture 114 The sort_index Method on a MultiIndex DataFrame 8:20
Lecture 115 Extract Rows from a MultiIndex DataFrame 10:54
Lecture 116 The transpose Method on a MultiIndex DataFrame 8:16
Lecture 117 The 3:30
Lecture 118 The 5:59
Lecture 119 The 3:37
Lecture 120 The 6:14
Lecture 121 The 5:8
Lecture 122 The pivot Method 6:43
Lecture 123 Use the pivot_table method to create an aggregate 6:43
Lecture 124 Use the pd 5:56

Section 9 : Section 9 The GroupBy Object

Lecture 125 Intro to the Groupby Module 7:44
Lecture 126 First Operations with groupby Object 9:30
Lecture 127 Retrieve a group from a GroupBy object with the get_group 3:46
Lecture 128 Methods on the Groupby Object and DataFrame Columns 8:43
Lecture 129 Grouping by Multiple Columns 4:38
Lecture 130 The 6:8
Lecture 131 Iterating through Groups 9:1

Section 10 : Section 10 Merging, Joining, and Concatenating

Lecture 132 Intro to the Merging, Joining, and Concatenating Section
Lecture 133 The pd 5:20
Lecture 134 The pd 7:9
Lecture 135 Inner Joins, Part 1 9:26
Lecture 136 Inner Joins, Part 2 9:5
Lecture 137 Outer Joins 12:43
Lecture 138 Left Joins 9:19
Lecture 139 The left_on and right_on Parameters 9:11
Lecture 140 Merging by Indexes with the left_index and right_index 11:4
Lecture 141 The 3:16
Lecture 142 The pd 3:7

Section 11 : Section 11 Working with Dates and Times in Datasets

Lecture 143 Intro to the Working with Dates and Times Module 4:21
Lecture 144 Review of Python's datetime Module 10:51
Lecture 145 The pandas Timestamp Object 7:50
Lecture 146 The pandas DateTimeIndex Object 5:40
Lecture 147 The pd 12:7
Lecture 148 Create Range of Dates with the pd 10:23
Lecture 149 Create Range of Dates with the pd 10:33
Lecture 150 Create Range of Dates with the pd 7:47
Lecture 151 The 7:29
Lecture 152 Install pandas-datareader Library 3:33
Lecture 153 Import Financial Data Set with pandas_datareader Library 7:56
Lecture 154 Selecting Rows from a DataFrame with a DateTimeIndex 12:28
Lecture 155 Timestamp Object Attributes and Methods 9:38
Lecture 156 The pd 6:50
Lecture 157 Timeseries Offsets 12:46
Lecture 158 The Timedelta Object 8:22
Lecture 159 Timedeltas in a Dataset 9:32

Section 12 : Section 12 Input and Output in pandas

Lecture 160 Intro to the Input and Output Section 1:27
Lecture 161 Pass a URL to the pd 4:25
Lecture 162 Quick Object Conversions 7:4
Lecture 163 Export CSV File with the to_csv Method 5:26
Lecture 164 Install xlrd and openpyxl Libraries to Read and Write Excel 4:11
Lecture 165 Import Excel File into pandas with the read_excel Method 9:44
Lecture 166 Export Excel File with the to_excel Method 7:44

Section 13 : Section 13 Visualization

Lecture 167 Intro to Visualization Section 4:48
Lecture 168 Use the plot Method to Render a Line Chart 7:53
Lecture 169 Modifying Plot Aesthetics with matplotlib Templates 4:45
Lecture 170 Creating Bar Graphs to Show Counts 5:57
Lecture 171 Creating Pie Charts to Represent Proportions

Section 14 : Section 14 Options and Settings in pandas

Lecture 172 Introduction to the Options and Settings Module 1:45
Lecture 173 Changing pandas Options with Attributes and Dot Syntax 7:0
Lecture 174 Changing pandas Options with Methods 6:16

Section 15 : Section 15 Conclusion

Lecture 175 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 176 Conclusion 1:41