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| 0.Importing Data.webm |
9.01Мб |
| 0.Welcome.webm |
39.76Мб |
| 01. Accessing an API with Python.webm |
32.28Мб |
| 01. An Intelligent Spider.webm |
19.85Мб |
| 01. Cleaning A Spreadsheet.webm |
35.38Мб |
| 01. Complex Relationships.webm |
18.73Мб |
| 01. Controlling Conversion.webm |
19.70Мб |
| 01. Everyone Loves Charlotte.webm |
27.89Мб |
| 01. Examples and Features.webm |
12.81Мб |
| 01. Functions.webm |
30.28Мб |
| 01. Indexing.webm |
48.99Мб |
| 01. Installation and Creating Your First Notebook.webm |
17.66Мб |
| 01. Installing scikit-learn using Anaconda.webm |
18.02Мб |
| 01. Introducing Tuples.webm |
7.81Мб |
| 01. Iterate over Dictionaries.webm |
6.28Мб |
| 01. Iteration.webm |
11.04Мб |
| 01. Lets Chat About Sequences.webm |
11.60Мб |
| 01. Making Better Decisions with Data Analysis.webm |
22.24Мб |
| 01. Moving Forward.webm |
4.88Мб |
| 01. New Way of Thinking.webm |
55.23Мб |
| 01. Numeric.webm |
27.06Мб |
| 01. Our Data Set - Flower Power.webm |
19.09Мб |
| 01. Packing.webm |
13.49Мб |
| 01. Problem Discussion.webm |
13.14Мб |
| 01. Project Breakdown.webm |
17.06Мб |
| 01. Recap of Functions.webm |
11.44Мб |
| 01. Sequence Operations.webm |
7.81Мб |
| 01. Summarizing Data Maximum, Minimum, Range.webm |
17.91Мб |
| 01. The Application.webm |
18.62Мб |
| 01. The Project.webm |
17.47Мб |
| 01. Understanding Metrics.webm |
28.73Мб |
| 01. Welcome.webm |
35.87Мб |
| 01. Welcome.webm |
16.24Мб |
| 01. Welcome.webm |
46.30Мб |
| 01. Welcome.webm |
19.16Мб |
| 01. Welcome to Matplotlib.webm |
13.19Мб |
| 01. What Are Objects And Classes.webm |
29.96Мб |
| 01. What is a dictionary.webm |
15.55Мб |
| 01. What is Anaconda and why use it.webm |
21.77Мб |
| 01. What Is Cleaning Data.webm |
16.69Мб |
| 01. What is Data Scraping.webm |
31.01Мб |
| 01. What is Machine Learning.webm |
22.40Мб |
| 01. What Problems Does Netflix Have.webm |
29.49Мб |
| 01. Where is it Being Used.webm |
14.11Мб |
| 02. Add Items.webm |
10.15Мб |
| 02. Boolean Array Indexing.webm |
45.36Мб |
| 02. Characteristics of Big Data.webm |
10.04Мб |
| 02. Cleaning A Spreadsheet Part 2.webm |
21.28Мб |
| 02. Comparing and Combining Dice.webm |
17.75Мб |
| 02. Context.webm |
17.35Мб |
| 02. Creation.webm |
10.18Мб |
| 02. Data is Everywhere.webm |
25.82Мб |
| 02. Decision Process.webm |
20.41Мб |
| 02. Defining a Function.webm |
3.93Мб |
| 02. Defining Terms.webm |
20.44Мб |
| 02. Dictionary Syntax and KeyValue Pairs.webm |
12.19Мб |
| 02. Functions Recap and Cheat Sheet.md |
1.38Кб |
| 02. Gather Information.webm |
12.63Мб |
| 02. Gathering Weather Data.webm |
8.34Мб |
| 02. Getting Setup.webm |
17.49Мб |
| 02. Getting Started with Charting.webm |
10.19Мб |
| 02. How Does Netflix Apply Big Data Tools to Solve these Problems.webm |
17.38Мб |
| 02. Installing Anaconda.webm |
17.66Мб |
| 02. Installing Scrapy.webm |
11.90Мб |
| 02. Iterating with Basic For Loops.webm |
8.72Мб |
| 02. Labels and Classifiers.webm |
10.90Мб |
| 02. Lets Make a Class!.webm |
7.62Мб |
| 02. Loading a Dataset.webm |
14.41Мб |
| 02. Math.webm |
13.95Мб |
| 02. Mutability.webm |
14.51Мб |
| 02. Packing, a Practical Example.webm |
5.36Мб |
| 02. Packing with Dictionaries.webm |
6.16Мб |
| 02. Recap.webm |
8.99Мб |
| 02. Returning Values.webm |
24.82Мб |
| 02. Running Code in Cells.webm |
12.40Мб |
| 02. Running Scripts.webm |
14.24Мб |
| 02. Scatter Plot.webm |
17.23Мб |
| 02. Scraping APIs.webm |
22.92Мб |
| 02. Slices.webm |
6.99Мб |
| 02. Strings and Operators.webm |
14.02Мб |
| 02. Summarizing Data Mean, Median, Mode.webm |
9.26Мб |
| 02. Super-Duper!.webm |
16.84Мб |
| 02. Supervised and Unsupervised Learning.webm |
29.39Мб |
| 02. Types of Data.webm |
22.40Мб |
| 02. Universal Functions.webm |
42.94Мб |
| 02. Web Page Anatomy.webm |
18.79Мб |
| 03. Accessing Keys and Values.webm |
6.29Мб |
| 03. Addition.webm |
13.26Мб |
| 03. All About Returns.webm |
8.22Мб |
| 03. Analyzing Data Spread.webm |
9.54Мб |
| 03. Analyzing the Data.webm |
14.43Мб |
| 03. Bad Data Types.webm |
17.52Мб |
| 03. Beautiful Soup.webm |
27.18Мб |
| 03. Branch and Loop.webm |
19.29Мб |
| 03. Calling a Function.webm |
3.11Мб |
| 03. Calling the API.webm |
25.47Мб |
| 03. Cleaning A CSV.webm |
22.81Мб |
| 03. Crawling Spiders.webm |
19.59Мб |
| 03. Creating a Spreadsheet.webm |
17.91Мб |
| 03. Display the List.webm |
13.87Мб |
| 03. Domain Data Storage.webm |
34.58Мб |
| 03. Emulating Built-ins.webm |
24.24Мб |
| 03. Expecting Exceptions.webm |
18.57Мб |
| 03. Giving a Hand.webm |
19.73Мб |
| 03. Graphs and Charts.webm |
25.31Мб |
| 03. Histogram.webm |
18.01Мб |
| 03. Introducing Arrays.webm |
38.46Мб |
| 03. Iterating with Enumerate.webm |
7.08Мб |
| 03. Len, Min, and Max.webm |
4.42Мб |
| 03. Machine Learning Frameworks.webm |
18.93Мб |
| 03. Making Predictions with a Classifier.webm |
11.34Мб |
| 03. Methods.webm |
14.04Мб |
| 03. Multiple Superclasses.webm |
31.27Мб |
| 03. Problem Summary and Presentation.webm |
8.88Мб |
| 03. Routines in Action.webm |
38.46Мб |
| 03. Slicing.webm |
28.20Мб |
| 03. Split and Join.webm |
13.41Мб |
| 03. String Methods.webm |
13.39Мб |
| 03. The Importance of Big Data.webm |
22.77Мб |
| 03. The Legend of Charting.webm |
10.76Мб |
| 03. The Python Shell.webm |
20.53Мб |
| 03. Tuples vs. Lists.md |
2.06Кб |
| 03. Unpacking.webm |
4.50Мб |
| 03. Unpacking with Dictionaries.md |
1.16Кб |
| 03. Using conda to Install Packages.webm |
9.35Мб |
| 03. Using Scrapers for Site Testing.webm |
22.21Мб |
| 03. Wrapping Up.webm |
27.63Мб |
| 04. Arguments and Parameters.webm |
6.65Мб |
| 04. Booleans.webm |
17.58Мб |
| 04. Box Plot.webm |
14.64Мб |
| 04. Chart Types & Reasons to Use.webm |
18.92Мб |
| 04. Cleaning A CSV Part 2.webm |
24.40Мб |
| 04. Common Issues with Data Scraping.md |
1.67Кб |
| 04. Creating the Study Log.webm |
29.11Мб |
| 04. Domain Computations.webm |
29.31Мб |
| 04. Exploring Our New Problems.webm |
41.33Мб |
| 04. Family Tree.webm |
20.08Мб |
| 04. Getting Good Data is Hard.webm |
37.57Мб |
| 04. Handle Exceptions.webm |
19.96Мб |
| 04. Indexing.webm |
31.57Мб |
| 04. Is Our Data Normal.webm |
10.71Мб |
| 04. Iterating with Ranges.webm |
6.38Мб |
| 04. Lets Talk About Scope.webm |
10.96Мб |
| 04. Machine Learning Review.webm |
7.79Мб |
| 04. Manipulation.webm |
43.46Мб |
| 04. Membership Testing.webm |
4.12Мб |
| 04. Method Arguments.webm |
13.49Мб |
| 04. miniconda.webm |
20.41Мб |
| 04. More Soup in the Tureen.webm |
23.56Мб |
| 04. Multidimensional Lists.webm |
14.17Мб |
| 04. Other Languages.webm |
20.20Мб |
| 04. Plotting.webm |
38.74Мб |
| 04. Presenting Your Findings.webm |
30.37Мб |
| 04. Raising Exceptions.webm |
15.95Мб |
| 04. Saving the Data.webm |
22.30Мб |
| 04. Subclassing Built-ins.webm |
28.47Мб |
| 04. Syntax and Errors.webm |
23.06Мб |
| 04. The Endless Web.webm |
38.37Мб |
| 04. Tuple Syntax.md |
2.58Кб |
| 04. Unpacking, a Practical Example.webm |
5.00Мб |
| 04. Update and Mutate Dictionaries.webm |
6.29Мб |
| 04. Wrap Up.webm |
6.09Мб |
| 04. Yatzy Scoring.webm |
14.14Мб |
| 05. Being a Good Citizen.webm |
31.17Мб |
| 05. Cleaner Code Through Refactoring.webm |
21.10Мб |
| 05. Cleaning A CSV Part 3.webm |
23.96Мб |
| 05. Constructicons.webm |
19.30Мб |
| 05. Count and Index.webm |
6.86Мб |
| 05. Deletion.webm |
14.60Мб |
| 05. Design.webm |
31.53Мб |
| 05. Domain Infrastructure.webm |
17.49Мб |
| 05. Function Gotchas.md |
1.56Кб |
| 05. If, Else and Elif.webm |
22.88Мб |
| 05. Multidimensional Arrays.webm |
35.33Мб |
| 05. No Problem.webm |
17.91Мб |
| 05. Saving Your Work.webm |
12.02Мб |
| 05. Variables.webm |
20.28Мб |
| 05. Visualizing Data.webm |
15.99Мб |
| 05. Where to Now.webm |
15.72Мб |
| 05. While Loops.webm |
24.61Мб |
| 05. Wrapping Up.webm |
7.32Мб |
| 06. Charting Our Data Part 1.webm |
9.12Мб |
| 06. Cleaning A CSV Part 4.webm |
23.67Мб |
| 06. Code Challenges.md |
908б |
| 06. Code Samples Membership Testing, Count, and Index.md |
1.19Кб |
| 06. Comparisons.webm |
25.42Мб |
| 06. For Loops.webm |
11.23Мб |
| 06. Multiple Arguments and Parameters.webm |
5.99Мб |
| 06. Special Methods.webm |
19.91Мб |
| 06. Wrapping Up.webm |
18.82Мб |
| 07. Charting Our Data Part 2.webm |
12.63Мб |
| 07. Concatenation and Multiplication.webm |
4.42Мб |
| 07. Input and Coding Style.webm |
25.83Мб |
| 08. Sequence Operations Cheat Sheet.md |
2.70Кб |
| 1.Manipulation.webm |
5.47Мб |
| 1.Meet Series.webm |
11.99Мб |
| 2.Combining DataFrames.webm |
8.95Мб |
| 2.Vectorization and Broadcasting Review.webm |
13.69Мб |
| 3.Meet DataFrames.webm |
11.60Мб |
| 3.Until Next Time.webm |
13.71Мб |
| 4.Onwards.webm |
4.77Мб |
| About This Course.png |
300.66Кб |
| Accessing a DataFrame.png |
718.01Кб |
| Accessing a Series.png |
680.00Кб |
| Beginning Data Science.md |
6.65Кб |
| Combining DataFrames.png |
1.21Мб |
| Common Issues with Data Scraping.md |
1.67Кб |
| Creating a DataFrame.png |
465.05Кб |
| Creating a Series.png |
511.47Кб |
| Data Analysis Basics.md |
3.91Кб |
| Data from APIs.md |
1.02Кб |
| Exploration Methods.png |
1.22Мб |
| Functions, Packing, and Unpacking.md |
4.17Кб |
| Grouping.png |
945.93Кб |
| Handling Duplicated and Missing Data.png |
862.95Кб |
| intro_matplotlib.zip |
265.59Кб |
| intro_matplotlib.zip |
265.59Кб |
| intro_matplotlib.zip |
265.59Кб |
| Introducing Dictionaries.md |
2.89Кб |
| Introducing Lists.md |
3.54Кб |
| Introducing Tuples.md |
1.83Кб |
| Introduction to Anaconda.md |
1.13Кб |
| Introduction to Big Data.md |
4.20Кб |
| Introduction to Data Visualization with Matplotlib.md |
4.51Кб |
| Introduction to NumPy.md |
4.41Кб |
| Jupyter Notebooks.md |
1.24Кб |
| Learning SQL.md |
495б |
| Machine Learning Basics.md |
3.36Кб |
| Manipulating Text.png |
725.39Кб |
| Manipulation Techniques.png |
1.24Мб |
| marathon_results_2017.csv |
4.00Мб |
| ML-machine-learning-basics.zip |
614б |
| More Visualization.md |
1.01Кб |
| Object-Oriented+Python+2.zip |
130.13Кб |
| Object-Oriented+Python+2.zip |
130.13Кб |
| Object-Oriented+Python+2.zip |
130.13Кб |
| Object-Oriented+Python+2.zip |
130.13Кб |
| Object-Oriented Python.md |
7.13Кб |
| Optional Challenge #1 - Top Referrers.png |
393.99Кб |
| Optional Challenge #2 - Update Users.png |
399.39Кб |
| Optional Challenge #3 - Verified Email List.png |
419.33Кб |
| Preparing Data for Analysis.md |
2.31Кб |
| preparing-data-for-analysis-student.zip |
38.00Кб |
| Python Basics.md |
5.63Кб |
| python-introducing-pandas-1.2.0.zip |
88.32Кб |
| python-intro-to-numpy.zip |
57.71Кб |
| python-intro-to-numpy.zip |
57.71Кб |
| python-intro-to-numpy.zip |
57.71Кб |
| Python Sequences.md |
3.48Кб |
| README.txt |
2.25Кб |
| scraping_data_from_the_web.zip |
37.26Кб |
| scraping_data_from_the_web.zip |
37.26Кб |
| scraping_data_from_the_web.zip |
37.26Кб |
| Scraping Data From the Web.md |
4.08Кб |
| Selecting Data.png |
751.58Кб |
| Series Vectorization and Broadcasting.png |
553.42Кб |
| TeamTreehouse - Beginning Data Science (Track) [Thomas].jpg |
157.26Кб |
| TeamTreehouse - Beginning Data Science (Track) [Thomas].png |
1.02Мб |