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

## Problem statement

The function `getMinMax(arr)` needs to be implemented. The `arr` is the multidimensional array on which operations are performed. The dimensions of the `NumPy` array are random, i.e., the number of rows and columns are not fixed. The elements of the array are also random. The task is to find the minimum and maximum value for each row of the multidimensional `NumPy` array and return all of them in a `list`.


### Input
The input to the function is a multidimensional array with random dimensions and data. The following is an example of how the input array should look.
```
[
[-3, 0, 5, -6]
[7, 2, -1, 9]
[12, -4, 3, 1]
]
```

### Output
The output is a list containing the minimum and maximum element from each row. First, the minimum element from each row should be stored, followed by the maximum element. The `list` should then be returned. The following is an example of what the output of the above input array should look like.

```
[-6, 5, -1, 9, -4, 12]
```

## Coding exercise

Write your code below. It is recommended​ that you try solving the exercise yourself before viewing the solution.


# Problem statement

The function `getMinMax(arr)` needs to be implemented. The `arr` is the multidimensional array on which operations are performed. The dimensions of the `NumPy` array are random, i.e., the number of rows and columns are not fixed. The elements of the array are also random. The task is to find the minimum and maximum value for each row of the multidimensional `NumPy` array and return all of them in a `list`.


## Input
The input to the function is a multidimensional array with random dimensions and data. The following is an example of how the input array should look.
```
[
[-3, 0, 5, -6]
[7, 2, -1, 9]
[12, -4, 3, 1]
]
```

## Output
The output is a list containing the minimum and maximum element from each row. First, the minimum element from each row should be stored, followed by the maximum element. The `list` should then be returned. The following is an example of what the output of the above input array should look like.

```
[-6, 5, -1, 9, -4, 12]
```

# Coding exercise

Write your code below. It is recommended​ that you try solving the exercise yourself before viewing the solution.


In this challenge, the minimum and maximum values need to be returned for each row of a 2-D Numpy array.

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

Challenge: Find Min and Max from a 2-D NumPy Array

Problem statement

Input

Output

Coding exercise