Part 2 of the Python Course for Data Scientists: 100 hands-on Python projects and source codes with useful resources for beginners.
This guide will help you build confidence in the Python learning journey, develop a specific application that helps you stand out in the job hunt, and have fun along the way.
Table of Contents
Setting Up Your Environment
Setting working directory YOURPATH import os os.chdir('YOURPATH') # Set working directory os. getcwd() You’ll need pandas and other Python libraries, which you can install with pip python3 -m pip install requests pandas matplotlib Within the Jupyter notebook, this command looks as follows !pip install requests pandas matplotlib You can also use the Conda package manager conda install requests pandas matplotlib Since we’re using the Anaconda distribution, then you’re good to go! Anaconda already comes with pandas and Jupyter notebook installed.
Download Datasets
Initial Pandas Data QC
Displaying Pandas Data Types
Showing Descriptive Statistics
Exploring the Dataset
Email Slicer
User Input & Type Conversion
Working with Lists
Practicing Loops
Calculator
Temperature Conversion
ADC Temperature Sensor
Sorting Numpy Arrays
Story Generator
Display Calendar
Invoice Generator
Using Strings
Guess a Word
Tip Calculator
Pizza Deliveries
Highest Score
Password Generator
Paint Area Calculator
Menu-Driven Program
Datetime Module
Counting Digits
Largest Number
Join Two Strings
Format Floating Point in the String
Raise a Number to a Power
Working with Boolean Types
If Else Statement
Using AND/OR Operators
Switch Case Statement
While Loop
Use of regex
Use of getpass
Use of Date Format
Add/Remove the Item from a List
Slice Data
Add and Search Data in the Set
Count Items in the List
Define and Call a Function
Using Try-Except Blocks
Read/Write Files
List Files in a Directory
Read/Write w/ pickle
Use of range Function
Use of map Function
Use of filter Function
Pandas First Program
Current Weather
Turtle Race Game
Must Watch Movie List
Digital Clock
BMI Calculator
YouTube Downloader
Factorial of a Number
Numpy Linear Algebra
Numpy/Matplotlib Images
Numpy Financial Module
Creating Pandas Data Objects
I/O Pandas DataFrames
Tkinter Sentiment Detector GUI
Tkinter/Pillow Slideshow
IceCream Debugger
Using Pandas DataFrames
Tkinter Calendar
Loan Calculator GUI
Weight Converter GUI
Age Calculator GUI
Create Dictionary from an Object
Check a Key in a Dictionary
Add a Key-Value Pair to the Dictionary
Iterate Over Dictionaries Using for Loop
Check the File Size
Working with Functions
Working with Dictionaries
Remove First N Characters from a String
Working with Classes
Define Class and Method
List Operations via Classes
Minimize Lateness
Compute a Polynomial Equation
Creating Linked Lists
CockTail Sort Algorithm
Binary Search via Recursion
Find Simple Interest
Probability Distributions in SciPy
Piecewise Linear 1-D Interpolation in Numpy
Cubic Spline 1-D Interpolation in Scipy
Interpolation with Radial Basis Function
SciPy T-Test
KS-Test
Statistical Description of Data
Exporting Data in Matlab Format
Import Data from Matlab Format
SciPy Optimizers
Working with Spatial Data
Python Coding Interview Q&A
Conclusions
The Road Ahead
Explore More
References