2023 Python Data Analysis & Visualization Masterclass
- Description
- Curriculum
- FAQ
- Reviews
Welcome to (what I think is) the web’s best course on Pandas, Matplotlib, Seaborn, and more! This course will level up your data skills to help you grow your career in Data Science, Machine Learning, Finance, Web Development, or any tech-adjacent field.
This is a tightly structured course that covers a ton, but it’s all broken down into human-sized pieces rather than an overwhelming reference manual that throws everything at you at once. After each and every new topic, you’ll have the chance to practice what you’re learning and challenge yourself with exercises and projects. We work with dozens of fun and real-world datasets including Amazon bestsellers, Rivian stock prices, Presidential Tweets, Bitcoin historic data, and UFO sightings.
If you’re still reading, let me tell you a little about the curriculum.. In the course, you’ll learn how to:
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Work with Jupyter Notebooks
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Use Pandas to read and manipulate datasets
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Work with DataFrames and Series objects
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Organize, filter, clean, aggregate, and analyze DataFrames
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Extract and manipulate date, time, and textual information from data
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Master Hierarchical Indexing
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Merge datasets together in Pandas
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Create complex visualizations with Matplotlib
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Use Seaborn to craft stunning and meaningful visualizations
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Create line, bar, box, scatter, pie, violin, rug, swarm, strip, and other plots!
What makes this course different from other courses on the same topics? First and foremost, this course integrates visualizations as soon as possible rather than tacking it on at the end, as many other courses do. You’ll be creating your first plots within the first couple of sections! Additionally, we start using real datasets from the get go, unlike most other courses which spend hours working with dull, fake data (colors, animals, etc) before you ever see your first real dataset. With all of that said, I feel bad trash talking my competitors, as there are quite a few great courses on the platform 🙂
I think that about wraps it up! The topics in this courses are extremely visual and immediate, which makes them a joy to teach (and hopefully for you to learn). If you have even a passing interest in these topics, you’ll likely enjoy the course and tear through it quickly. This stuff might seem intimidating, but it’s actually really approachable and fun! I’m not kidding when I say this is my favorite course I’ve ever made. I hope you enjoy it too.
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10Creating Notebooks & Running CellsVideo lesson
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11Shutting Down The Notebook ServerVideo lesson
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12How Cell Output WorksVideo lesson
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13Command Mode ShortcutsVideo lesson
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14Cell Types: Markdown Time!Video lesson
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15Restarting The KernelVideo lesson
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16Viewing The Docs Inside A NotebookVideo lesson
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17EXERCISE: Jupyter NotebookVideo lesson
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18SOLUTION: Jupyter NotebookVideo lesson
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19Datasets & CSVVideo lesson
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20pd.read_csv & DataFramesVideo lesson
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21Inspecting DataFrames: head(), tail(), etc.Video lesson
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22DataTypes and info()Video lesson
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23The House Sales Dataset WalkthroughVideo lesson
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24The Titanic Passenger Dataset WalkthroughVideo lesson
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25Non-comma Separators: Netflix DatasetVideo lesson
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26Overriding Headers: Country Population DatasetVideo lesson
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27EXERCISE: DataFrames & DatasetsVideo lesson
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28SOLUTION: DataFrames & DatasetsVideo lesson
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36Selecting A Single ColumnVideo lesson
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37A Closer Look At SeriesVideo lesson
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38Important Series MethodsVideo lesson
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39unique & nuniqueVideo lesson
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40nlargest & nsmallestVideo lesson
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41Selecting Multiple ColumnsVideo lesson
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42The powerful value_counts() methodVideo lesson
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43Using plot() to visualize!Video lesson
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44EXERCISE: Series & PlottingVideo lesson
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45SOLUTION: Series & PlottingVideo lesson
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46Set_Index BasicsVideo lesson
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47set_index: The World Happiness Index DatasetVideo lesson
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48setting index with read_csvVideo lesson
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49sort_values introVideo lesson
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50sorting by multiple columnsVideo lesson
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51sorting text columnsVideo lesson
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52sort_indexVideo lesson
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53Sorting and Plotting!Video lesson
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54locVideo lesson
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55ilocVideo lesson
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56loc & iloc with SeriesVideo lesson
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57EXERCISE: Indexes & SortingVideo lesson
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58SOLUTION: Indexes & SortingVideo lesson
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59Filtering DataFrames With A Boolean SeriesVideo lesson
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60Filtering With Comparison OperatorsVideo lesson
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61The Between MethodVideo lesson
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62The isin() MethodVideo lesson
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63Combining Conditions Using AND (&)Video lesson
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64Combining Conditions Using OR (|)Video lesson
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65Bitwise NegationVideo lesson
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66isna() and notna() MethodsVideo lesson
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67Filtering + Plotting ExamplesVideo lesson
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68EXERCISE: FilteringVideo lesson
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69SOLUTION: Filtering ExerciseVideo lesson
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70Dropping ColumnsVideo lesson
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71Dropping RowsVideo lesson
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72Adding Static ColumnsVideo lesson
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73Creating New "Dynamic" ColumnsVideo lesson
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74Finding The Highest price/sqft homesVideo lesson
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75Finding Largest Bitcoin Price ChangesVideo lesson
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76EXERCISE: Adding/Removing Columns & RowsVideo lesson
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77SOLUTION: Adding/Removing Columns & RowsVideo lesson
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78Renaming Columns and Index LabelsVideo lesson
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79The replace() methodVideo lesson
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80Updating Values Using loc[]Video lesson
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81Updating Multiple Values Using loc[]Video lesson
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82Making Updates With loc[] and Boolean MasksVideo lesson
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83EXERCISE: Updating ValuesVideo lesson
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84SOLUTION: Updating Values ExerciseVideo lesson
