Introduction to Python for Data Analysis

Course Content

Introduction to Python for Data Analysis

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

.loc Function

Pandas allows you to set specific conditions on the dataset without an if/else statement and loops. Look at the syntax:

DataFrame.loc[DataFrame['job_title'] == 'Data Scientist'].count()

So inside the .loc[] function, you just put the condition you need. Here you compare if 'job_title' is equal to 'Data Scientist'.

It compares each value of 'job_title' to the 'Data Scientist' string.

The ways of creating such conditions are the same as for if statements; you can use >, <, >=, =<, == with the same meaning.

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Section 3. Chapter 13

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