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
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
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
statistical techniques(distributions, sampling and t-tests)