Introduction to Data Science in Python

This repository contains the topics that were taught in the coursera course Introduction to Data Science in Python, it contains the assignments as well. These topics and assignments are gathered into different directories, according to weekly aims. The datasets used in the course are located in the Datasets directory of every week. Then each weekly aim is:

First Week: Fundamentals of Data Manipulation with Python

Here we manipulate and select data using numpy, as well as apply regular expresion to string data, and learn how to properly match string patterns. (./Week_1/Assignment_1.ipynb)

Second Week: Basic Data Processing with Pandas

In this week we learn about the one of the most important python libraries, i.e., Pandas. Using this toolkit we can read in data into DataFrame structures, query these structures, and the details about such structures are indexed. (./Week_2/Assignment_2.ipynb)

Third Week: More Data Processing with Pandas

Now we deepen our knowlegde in Pandas by learning how to merge DataFrames, generate summary tables, group data into logical pieces, and manipulate dates. (./Week_3/Assignment_3.ipynb)

Fourth Week: Answering Questions with Messy Data

This week gathers previous knowlegdes in python pandas library, so taking into account that we introduced to a variety of statistical techniques such a distributions, sampling and t-tests, in order to get applied to datasets. (./Week_4/Assignment_4.ipynb)