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Part 2 of the Python Course for Data Scientists: 100 hands-on Python projects and source codes with useful resources for beginners.

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100-Basic-Python-Codes

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