Module 8: A Slice of NumPy and Advanced Data Wrangling¶

In this module you will about numpy arrays and more advanced wrangling techniques such as handling columns with dates and strings.

Module Learning Outcomes¶

By the end of the module, students are expected to:

Use NumPy to create ndarrays with np.array() and from functions such as np.arange(), np.linspace() and np.ones().
Describe the shape, dimension and size of an array.
Identify null values in a dataframe and manage them by removing them using .dropna() or replacing them using .fillna().
Manipulate non-standard date/time formats into standard Pandas datetime using pd.to_datetime().
Find, and replace text from a dataframe using verbs such as .replace() and .contains().