Gain insights into performing predictive data analysis using Python. Learn about tools like NumPy, Pandas, Matplotlib, and Seaborn, and applying techniques to real-world financial and advertisement projects.

seaborn.tar.gz

seaborn

In this course, you will learn how to perform predictive data analysis using Python. The ideal audience is those who want to start their careers as data analysts. The main goal of this course is to show you how to use statistics to draw useful insights from data which can help in predicting future behavior or patterns.

Beyond that, you’ll learn all the tools of the trade that data scientists use everyday including: NumPy, Pandas, Matplotlib, and Seaborn. You’ll learn not only how to extract meaningful insights from data, but you’ll also learn how to create stunning visualizations that you can use for reports.

Various datasets of real-world scenarios are used in each lesson to get you accustomed to handling any type of data. At the end of the course, you will work on two real-world projects that demonstrate how data analysis techniques are being used in the financial and advertisement sector to generate revenue.

Predictive Data Analysis with Python

# What is customer behavior?

The decisions and instincts that make a customer buy a certain product or service can be described as *customer behavior*.

With the advent of targeted marketing, traditional marketing techniques are getting obsolete with every new day. The rise of digital marketing, where every customer is shown advertisements particular to their interests and habits, has taken over the world.

This insight into customer's interests and habits is obtained through an extensive *customer behavior analysis* approach. We will try to implement a very basic level of this approach that will include finding the products that are selling more and at which time of the day. Then we will group the customers according to their buying habits.


## Why is it important?

Do you know that the average attention span of a person is at an all-time low? This means that an average advertiser or salesperson has only **seven seconds** to grasp a customer's attention before they move to another product as there are so many options available for them to choose from. 

A customer will only be interested in your product if they somehow get convinced that it aligns with their interests and habits.

## The dataset

The dataset used in this project was made by collecting information from an e-commerce store with products in multiple categories. The data is only for the months of *October* and *November* for the year **2019**.
The dataset description can be found [here](https://www.kaggle.com/mkechinov/ecommerce-behavior-data-from-multi-category-store).

The ***October*** dataset can be downloaded from [here](https://www.kaggle.com/mkechinov/ecommerce-behavior-data-from-multi-category-store/download/FAH9d0ulvNiH3S9wVMMr%2Fversions%2FQKmiBnpOADqv1OZIHWvX%2Ffiles%2F2019-Oct.csv?datasetVersionNumber=8) and
the ***November*** dataset can be downloaded from [here](https://www.kaggle.com/mkechinov/ecommerce-behavior-data-from-multi-category-store/download/FAH9d0ulvNiH3S9wVMMr%2Fversions%2FQKmiBnpOADqv1OZIHWvX%2Ffiles%2F2019-Nov.csv?datasetVersionNumber=8). As the datasets are available on Kaggle, it might require you to log in before the datasets can be downloaded.

# Results?

We will try to provide promising results for the following queries:

1. Do users prefer the products of a specific brand?

2. What is the user's activity(view, cart, buy) throughout the day?

3. Items from which brands and categories are most preferred by users?

4. Can we effectively conduct targeted marketing?

___
In the next lesson, we explore the data along with some other analysis.

In this lesson, you will learn about customer behavior and what analysis can we draw from its data.

Getting Started

Numpy for Python

Pandas for Python

Statistics for Data Analysis

Data Wrangling

Visualizing the Data

Data Scraping

Project #1

Project #2

Conclusion

Predictive Data Analysis Exam

Customer Behavior Analysis

What is customer behavior?