Diagnostic Analysis
■ Descriptive Analysis
Figure 3.1: Types of Data Analysis
Types of Data Analysis
What is Data Analysis
Data Analysis
Figure 3.2: Data Science Life Cycle
Data Analysis Process
Predictive and prescriptive analyses are more complex than descriptive and diagnostic ones, but they bring more added value and insights to a project.
Prescriptive Analysis
■ Predictive Analysis
Predictive Analysis
Figure 3.3: Types of Exploratory Data Analysis
Types of Exploratory Data Analysis
What is Exploratory Data Analysis
Exploratory Data Analysis
Data Analysis Tools
Figure 3.5: Multivariate graphical analysis
Figure 3.4: Univariate graphical analysis
Graphical Analysis
Non-Graphical Analysis
Table 3.1: Advantages and disadvantages of using code libraries
Python Libraries/Modules
Data Analysis with Python
Jupyter Notebook
In this unit you will use:
Table 3.2: Python libraries for data science
Python Libraries for Data Science
Python Standard Library
HISTORY The American mathematician John Tukey defined data analysis in 1961
To open Jupyter Notebook:
To create a new Jupyter Notebook:
INFORMATION
You can have as many different cells as you need in the same Notebook. Each cell contains its own code.
Figure 3.8: Create a program in Jupyter Notebook
To create a program in Jupyter Notebook:
You can run your program by pressing Shift + Enter
Now that your notebook is ready, it's time to write and run your first program in Jupyter Notebook.
Figure 3.9: Save your Notebook
When you are working, the Notebook is autosaved.
It's time to save your Notebook.