Section 1 : Section 1 Installation and Setup
Section 2 : Section 2 BONUS Python Crash Course
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Lecture 1 | Intro to the Python Crash Course | 00:03:33 Duration |
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Lecture 2 | Comments | 00:03:18 Duration |
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Lecture 3 | Basic Data Types | 00:11:09 Duration |
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Lecture 4 | Operators | 00:15:38 Duration |
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Lecture 5 | Variables | 00:07:44 Duration |
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Lecture 6 | Built-in Functions | 00:10:27 Duration |
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Lecture 7 | Custom Functions | 00:16:30 Duration |
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Lecture 8 | String Methods | 00:20:45 Duration |
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Lecture 9 | Lists | 00:13:37 Duration |
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Lecture 10 | Index Positions and Slicing | 00:15:54 Duration |
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Lecture 11 | Dictionaries | 00:15:24 Duration |
Section 3 : Section 3 Series
Section 4 : Section 4 DataFrames I Introduction
Section 5 : Section 5 DataFrames II Filtering Data
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Lecture 1 | This Module's Dataset + Memory Optimization | 00:15:45 Duration |
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Lecture 2 | Filter a DataFrame Based on A Condition | 00:12:48 Duration |
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Lecture 3 | Filter DataFrame with More than One Condition (AND - &) | 00:04:39 Duration |
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Lecture 4 | Filter DataFrame with More than One Condition (OR - ) | 00:08:47 Duration |
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Lecture 5 | Check for Inclusion with the isin Method | 00:06:15 Duration |
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Lecture 6 | Check for Null and Present DataFrame Values with the isnull | 00:05:15 Duration |
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Lecture 7 | Check For Inclusion Within a Range of Values | 00:06:50 Duration |
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Lecture 8 | Check for Duplicate DataFrame Rows with the duplicated | 00:09:00 Duration |
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Lecture 9 | Delete Duplicate DataFrame Rows with the drop_duplicates | 00:08:13 Duration |
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Lecture 10 | Identify and Count Unique Values with the unique | 00:04:40 Duration |
Section 6 : Section 6 DataFrames III Data Extraction
Section 7 : Section 7 Working with Text Data
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Lecture 1 | Intro to the Working with Text Data Section | 00:06:23 Duration |
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Lecture 2 | Common String Methods - lower, upper, title, and len | 00:07:11 Duration |
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Lecture 3 | Use the str | 00:09:09 Duration |
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Lecture 4 | Filter a DataFrame's Rows with String Methods | 00:08:25 Duration |
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Lecture 5 | More DataFrame String Methods - strip, lstrip, and rstrip | 00:05:58 Duration |
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Lecture 6 | Invoke String Methods on DataFrame Index and Columns | 00:06:20 Duration |
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Lecture 7 | Split Strings by Characters with the str | 00:10:29 Duration |
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Lecture 8 | More Practice with the str | 00:08:33 Duration |
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Lecture 9 | Exploring the expand and n Parameters of the str | 00:08:44 Duration |
Section 8 : Section 8 MultiIndex
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Lecture 1 | Intro to the MultiIndex Module | 00:04:50 Duration |
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Lecture 2 | Create a MultiIndex on a DataFrame with the set_index | 00:10:36 Duration |
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Lecture 3 | Extract Index Level Values with the get_level_values Method | 00:04:17 Duration |
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Lecture 4 | Change Index Level Name with the set_names Method | 00:04:15 Duration |
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Lecture 5 | The sort_index Method on a MultiIndex DataFrame | 00:08:20 Duration |
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Lecture 6 | Extract Rows from a MultiIndex DataFrame | 00:10:54 Duration |
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Lecture 7 | The transpose Method on a MultiIndex DataFrame | 00:08:16 Duration |
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Lecture 8 | The | 00:03:30 Duration |
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Lecture 9 | The | 00:05:59 Duration |
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Lecture 10 | The | 00:03:37 Duration |
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Lecture 11 | The | 00:06:14 Duration |
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Lecture 12 | The | 00:05:08 Duration |
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Lecture 13 | The pivot Method | 00:06:43 Duration |
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Lecture 14 | Use the pivot_table method to create an aggregate | 00:06:43 Duration |
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Lecture 15 | Use the pd | 00:05:56 Duration |
Section 9 : Section 9 The GroupBy Object
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Lecture 1 | Intro to the Groupby Module | 00:07:44 Duration |
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Lecture 2 | First Operations with groupby Object | 00:09:30 Duration |
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Lecture 3 | Retrieve a group from a GroupBy object with the get_group | 00:03:46 Duration |
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Lecture 4 | Methods on the Groupby Object and DataFrame Columns | 00:08:43 Duration |
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Lecture 5 | Grouping by Multiple Columns | 00:04:38 Duration |
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Lecture 6 | The | 00:06:08 Duration |
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Lecture 7 | Iterating through Groups | 00:09:01 Duration |
Section 10 : Section 10 Merging, Joining, and Concatenating
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Lecture 1 | Intro to the Merging, Joining, and Concatenating Section | |
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Lecture 2 | The pd | 00:05:20 Duration |
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Lecture 3 | The pd | 00:07:09 Duration |
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Lecture 4 | Inner Joins, Part 1 | 00:09:26 Duration |
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Lecture 5 | Inner Joins, Part 2 | 00:09:05 Duration |
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Lecture 6 | Outer Joins | 00:12:43 Duration |
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Lecture 7 | Left Joins | 00:09:19 Duration |
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Lecture 8 | The left_on and right_on Parameters | 00:09:11 Duration |
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Lecture 9 | Merging by Indexes with the left_index and right_index | 00:11:04 Duration |
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Lecture 10 | The | 00:03:16 Duration |
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Lecture 11 | The pd | 00:03:07 Duration |
Section 11 : Section 11 Working with Dates and Times in Datasets
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Lecture 1 | Intro to the Working with Dates and Times Module | 00:04:21 Duration |
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Lecture 2 | Review of Python's datetime Module | 00:10:51 Duration |
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Lecture 3 | The pandas Timestamp Object | 00:07:50 Duration |
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Lecture 4 | The pandas DateTimeIndex Object | 00:05:40 Duration |
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Lecture 5 | The pd | 00:12:07 Duration |
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Lecture 6 | Create Range of Dates with the pd | 00:10:23 Duration |
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Lecture 7 | Create Range of Dates with the pd | 00:10:33 Duration |
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Lecture 8 | Create Range of Dates with the pd | 00:07:47 Duration |
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Lecture 9 | The | 00:07:29 Duration |
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Lecture 10 | Install pandas-datareader Library | 00:03:33 Duration |
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Lecture 11 | Import Financial Data Set with pandas_datareader Library | 00:07:56 Duration |
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Lecture 12 | Selecting Rows from a DataFrame with a DateTimeIndex | 00:12:28 Duration |
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Lecture 13 | Timestamp Object Attributes and Methods | 00:09:38 Duration |
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Lecture 14 | The pd | 00:06:50 Duration |
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Lecture 15 | Timeseries Offsets | 00:12:46 Duration |
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Lecture 16 | The Timedelta Object | 00:08:22 Duration |
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Lecture 17 | Timedeltas in a Dataset | 00:09:32 Duration |
Section 12 : Section 12 Input and Output in pandas
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Lecture 1 | Intro to the Input and Output Section | 00:01:27 Duration |
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Lecture 2 | Pass a URL to the pd | 00:04:25 Duration |
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Lecture 3 | Quick Object Conversions | 00:07:04 Duration |
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Lecture 4 | Export CSV File with the to_csv Method | 00:05:26 Duration |
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Lecture 5 | Install xlrd and openpyxl Libraries to Read and Write Excel | 00:04:11 Duration |
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Lecture 6 | Import Excel File into pandas with the read_excel Method | 00:09:44 Duration |
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Lecture 7 | Export Excel File with the to_excel Method | 00:07:44 Duration |
Section 13 : Section 13 Visualization
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Lecture 1 | Intro to Visualization Section | 00:04:48 Duration |
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Lecture 2 | Use the plot Method to Render a Line Chart | 00:07:53 Duration |
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Lecture 3 | Modifying Plot Aesthetics with matplotlib Templates | 00:04:45 Duration |
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Lecture 4 | Creating Bar Graphs to Show Counts | 00:05:57 Duration |
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Lecture 5 | Creating Pie Charts to Represent Proportions |
Section 14 : Section 14 Options and Settings in pandas
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Lecture 1 | Introduction to the Options and Settings Module | 00:01:45 Duration |
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Lecture 2 | Changing pandas Options with Attributes and Dot Syntax | 00:07:00 Duration |
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Lecture 3 | Changing pandas Options with Methods | 00:06:16 Duration |
Section 15 : Section 15 Conclusion
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Lecture 1 | INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM | |
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Lecture 2 | Conclusion | 00:01:41 Duration |