Datacamp

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

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

2. Create a conda enviroment with environment.yml

conda env create -f environment.yml -n $ENV_NAME

Couses

These are the courses Im currently working on.

Data Types for Data Science

Start/finish: 1/30/18 - 2/1/18

• 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

Finish 2/14/18

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

---

Pandas Foundations

Finish 3/6/18

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

Manipulating DataFrames with pandas

Finish 03/08/18

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

Merging DataFrames with pandas

Finish 03/13/18

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

Cleaning Data in Python

finish 03/16/18

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

---

Python Data Science Toolbox (Part 2)

finish 03/17/18

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

Importing Data in Python (Part 1)

finish 03/17/18

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

Importing Data in Python (Part 2)

finish 03/18/18

• 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

finish 03/23/18

• 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