NumPy and Pandas

NumPy and Pandas

NumPy basics: building an array from lists, basic statistics, converting to booleans, referencing the array, and taking slices

Pandas basics: building a dataframe from lists, and retrieving data from the dataframe using row and column index references

Pandas: basic statistics

Converting between NumPy and Pandas

Array maths in NumPy

Reading and writing CSV files using NumPy and Pandas

Applying user-defined functions to NumPy and Pandas

Adding more data to NumPy arrays and Pandas dataframes

Using Pandas to merge or lookup data

Sorting and ranking with Pandas

Using masks to filter data, and perform search and replace, in NumPy and Pandas

Summarising data by groups in Pandas using pivot_tables and groupby

Reshaping Pandas data with stack, unstack, pivot and melt

Subgrouping data in Pandas with groupby

Iterating through columns and rows in NumPy and Pandas

Removing duplicate data in NumPy and Pandas

Setting width and number of decimal places in NumPy print output

Using NumPy to generate random numbers, or shuffle arrays

Using ‘pop’ to remove a Pandas DataFrame column and transfer to new variable

Saving intact Pandas DataFrames using ‘pickle’