Applied Datascience with python

Week1:

Basic Python programs using strings, functions, lists, dictionaries, date/time features, and files

Use advanced Python features, including lambdas, list comprehensions and the numpy library

Week2:

Create Series and DataFrame Data Structures

Use pandas math functions, as well as broadcasting features

Employ the pandas library to import and manipulate data

Apply indexing and querying to DataFrames, and deal with missing values

Additional Resources: Python for data analysis by O'reilly, Learning the pandas library by Matt Harrison, dataskeptic podcast, planetpython

week3:

Apply merge and join on DataFrames

Employ slicing and indexing on DataFrames

Analyze data with groupby and understand categorical variables

Produce the entire process of data source to elucidation

Examine the data by manipulating, cutting, and applying aggregate functions to DataFrames

week4:

statistical techniques(distributions, sampling and t-tests)