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Introduction to Data Analysis in Python
course content

Course Content

Introduction to Data Analysis in Python

Introduction to Data Analysis in Python

1. Basics
What is Python?Hello, Python!CommentsChallengeMath SkillsVariablesNaming Rules and Conventions
2. Data Types
Data Types in PythonNumeric TypesWhat is a String?Multiline StringsConcatenationAccessing String ElementsWhat is a List?Updating Lists
3. Control Flow
Boolean TypeIf/else StatementsIndentationIf/elif/elseChallenge 1Challenge 2For LoopIncrementing and DecrementingWhile Loop
4. Functions and Modules
Built-in FunctionsImporting ModulesUsing ModulesChallengeDefining FunctionsChallengeLambda Functions
5. Introduction to NumPy
What is the NumPy?NumPy ArraysArrays OperationsAggregate Functions2-D ArraysAggregating in 2-D Arrays

bookAggregating in 2-D Arrays

All the aggregate functions learned in this section can be used along either columns, or rows. To do it, you need to specify the axis parameter within aggregate function.

For example, we can compute the sum of rows and columns elements separately.


              
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# Import the library
import numpy as np
# Creating array
arr = np.array([[5.2, 3.0, 4.5], [9.1, 0.1, 0.3]])
# Sum of rows and columns elements
print(arr.sum(axis = 0)) # columns
print(arr.sum(axis = 1)) # rows
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Section 5. Chapter 6
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