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Datacamp Binder

My notes on Datacamp courses. They are markdown duplicates (on jupyter notebooks) of the lecutres along with my solution to each problem.

ko-fi

Getting Started

They can be viewed on github or download them.

Prerequisites

Only if are downloading them to your system.

  • Python enviroment
  • Jupyter notebook
  1. change directory
cd datacamp
  1. Create a conda enviroment with environment.yml
conda env create -f environment.yml -n $ENV_NAME

Courses

These are the courses Im currently working on.

Data Types for Data Science

  • Fundamental data types
  • Dictionaries - the root of Python
  • Meet the collections module
  • Handling Dates and Times
  • Answering Data Science Questions

Introduction to Data Visualization with Python

  • 01 Customizing plots
  • 02 Plotting 2D arrays
  • 03 Statistical plots with Seaborn
  • 04 Analyzing time series and images

Pandas Foundations

  • Data ingestion & instpection
  • Exploratory data analysis
  • Time series in pandas
  • Case Study - Sunlight in Austin

Manipulating DataFrames with pandas

  • Extracting and transforming data
  • Advanced indexing
  • Rearranging and reshaping data
  • Grouping data
  • Bringing it all together

Merging DataFrames with pandas

  • Preparing data
  • Concatenating data
  • Merging data
  • Case Study - Summer Olympics

Cleaning Data in Python

  • Exploring your data
  • Tidying data for analysis
  • Combining data for analysis
  • Cleaning data for analysis
  • Case study

Python Data Science Toolbox (Part 2)

  • Using iterators in PythonLand
  • List comprehensions and generators
  • Bringing it all together!

Importing Data in Python (Part 1)

  • Introduction and flat files
  • Importing data from other file types
  • Working with relational databases in Python

Importing Data in Python (Part 2)

  • Importing data from the Internet
  • Interacting with APIs to import data from the web
  • Diving deep into the Twitter API

Interactive Data Visualization with Bokeh

  • Basic plotting with Bokeh
  • Layouts, Interactions, and Annotations
  • Building interactive apps with Bokeh
  • Putting It All Together! A Case Study

Introduction to Databases in Python

  • Basics of Relational Databases
  • Applying Filtering, Ordering and Grouping to Queries
  • Advanced SQLAlchemy Queries
  • Creating and Manipulating your own Databases
  • Putting it all together!

Statistical Thinking in Python (Part 1)

  • Graphical exploratory data analysis
  • Quantitative exploratory data analysis
  • Thinking probabilistically-- Discrete variables
  • Work with Multiple Time Series
  • Thinking probabilistically-- Continuous variables

Statistical Thinking in Python (Part 1)

  • Parameter estimation by optimization
  • Bootstrap confidence intervals
  • Introduction to hypothesis testing
  • Hypothesis test examples
  • Putting it all together: a case study

Supervised Learning with scikit-learn

  • Classification
  • Regression
  • Fine-tuning your model
  • Preprocessing and pipelines

Visualizing Time Series Data in Python

  • Introduction
  • Summary Statistics and Diagnostics
  • Seasonality, Trend and Noise
  • Work with Multiple Time Series
  • Case Study

Intro to SQL for Data Science

  • Selecting Columns
  • Filtering rows
  • Aggregate Functions
  • Sortin, grouping and joins

Joining Data in SQL

  • Introduction to joins
  • Outer joins and cross joins
  • Set theory clauses
  • Subqueries