Course Content

Introduction to Python for Data Analysis

1. Introduction to Python 1/2

First Step in Programming Deal with Variables Practice Math Skills Challenge Deal with Percents How to Attract One User?Challenge Learn Numbers Boolean Numbers Challenge Work with Strings Get Familiar with Lists How to Append New Element?

2. Introduction to Python 2/2

If/Else Challenge If/Elif/Else Challenge For Loop While Loop Challenge

3. Explore Dataset

Data Study Operations with the File How to Explore the Data Sorting Data Max, min, mean, median Challenge Group Data Dive Deeper into Grouping Data Group Data 2.0 Introduction to NumPy Pivot Tables Recall Loops .loc Function Deal with Several Conditions Challenge Visualization: First Steps Dive Deeper into Visualization

4. Becoming an Analyst

Data Study Examine Dataset Challenge СAC 1/2 CAC 2/2 Costly Customers Organic Traffic How Much Do We Earn Is Our Project Profitable? ROI 1/2 ROI 2/2 Visualize ROI

Introduction to NumPy

NumPy is another crucial library to work with numbers especially. In this chapter, we will learn how to use NumPy to find mean, median or mode values. But to use this library, you must first import it; the alias for NumPy is usually np. Look at the example: import numpy as np.

Imagine that we work with this simple list while learning functions:

data = [1, 12, 14, 50]

Function title	Implementation	Result
`np.mean(data)`	Finds the mean value of list	`19.25`
`np.median(data)`	Finds the median value of list	`13.0`
`np.sum(data)`	Finds the sum of all values in list	`77`
`np.size(data)`	Finds the amount of values in list	`4`
`np.min(data)`	Finds the minimum value of all values in list	`1`
`np.max(data)`	Finds the maximim value of all values in list	`50`

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Everything was clear?

Section 3. Chapter 10

Introduction to NumPy

Imagine that we work with this simple list while learning functions:

data = [1, 12, 14, 50]

Function title	Implementation	Result
`np.mean(data)`	Finds the mean value of list	`19.25`
`np.median(data)`	Finds the median value of list	`13.0`
`np.sum(data)`	Finds the sum of all values in list	`77`
`np.size(data)`	Finds the amount of values in list	`4`
`np.min(data)`	Finds the minimum value of all values in list	`1`
`np.max(data)`	Finds the maximim value of all values in list	`50`

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Everything was clear?

Section 3. Chapter 10

Introduction to NumPy

Imagine that we work with this simple list while learning functions:

data = [1, 12, 14, 50]

Function title	Implementation	Result
`np.mean(data)`	Finds the mean value of list	`19.25`
`np.median(data)`	Finds the median value of list	`13.0`
`np.sum(data)`	Finds the sum of all values in list	`77`
`np.size(data)`	Finds the amount of values in list	`4`
`np.min(data)`	Finds the minimum value of all values in list	`1`
`np.max(data)`	Finds the maximim value of all values in list	`50`

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Everything was clear?

Imagine that we work with this simple list while learning functions:

data = [1, 12, 14, 50]

Function title	Implementation	Result
`np.mean(data)`	Finds the mean value of list	`19.25`
`np.median(data)`	Finds the median value of list	`13.0`
`np.sum(data)`	Finds the sum of all values in list	`77`
`np.size(data)`	Finds the amount of values in list	`4`
`np.min(data)`	Finds the minimum value of all values in list	`1`
`np.max(data)`	Finds the maximim value of all values in list	`50`

Task

Your tasks here are to find the number of users, figure out the maximum and the minimum possible values of price column, and then find the median value of the price.

Follow the algorithm:

Import the numpy with the np alias.
In the column 'user_id' find the size.
In the column 'price' find max and min values.
In the column 'price' find median value.

Section 3. Chapter 10

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