Python Step by Step: Build a Data Analysis Program Premium class

Ardit Sulce, Python and GIS Expert, Founder of PythonHow.com

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49 Videos (4h 44m)
    • Course Introduction

      3:09
    • An Example of Using Python for Data Analysis and Visualization

      8:03
    • Installing Python and Python Libraries

      7:54
    • Python editors: Spyder and iPython

      3:21
    • Section intro

      1:22
    • Variables

      2:47
    • If, else, and indentation

      4:06
    • Strings and numbers

      4:25
    • Functions

      3:09
    • Collections

      3:28
    • Sequences

      2:57
    • Working with sequences and strings

      7:27
    • Iteratiing

      3:37
    • Working with files

      5:29
    • Handling files easily

      1:44
    • Working with directories

      3:50
    • Working with directory paths - advanced

      6:46
    • Iterating through files

      6:09
    • Storing Python code

      4:32
    • Navigating through FTP directory trees with Python

      7:00
    • Section Introduction

      1:34
    • Creating an FTP function

      2:29
    • Downloading an FTP Fille

      8:31
    • Practice No.1: Creating an FTP File Downloader

      13:42
    • Extracting ZIP, TAR, GZ and other Archive Formats

      3:41
    • Extracting RAR files

      1:57
    • Practice No.2: Creating a Batch Archive Extractor

      5:52
    • Section intro

      1:34
    • Reading delimited TXT and CSV files

      10:06
    • Exporting data from Python to files

      4:14
    • Reading Fixed Width Files

      1:58
    • Exporting data to HTML and other file formats

      1:02
    • Get started with Pandas

      6:16
    • Practice No.3: Calculating and Adding Columns to CSV Files

      4:57
    • Practical No.4: Concatenating multiple CSV files

      6:18
    • Practice No. 5: Joining Data Based on a Matching Column

      8:59
    • Practice No. 6: Pivoting Large Amounts of Data

      7:41
    • How to perform visualizations in Python

      11:31
    • Practice No. 7: Producing JGP files

      3:08
    • More visualization techniques

      12:23
    • Programmatically creating KML Google Earth files with Python

      4:37
    • Practice No, 8: creating KML Google Earth fIles from CSV data

      7:46
    • User interaction

      6:07
    • Practice No. 9: Polishing the Program, I

      5:00
    • Practice No. 10: Polishing the Program, II

      5:30
    • Practice No. 11: Creating a Python Module out of Your Program

      5:00
    • Getting started with Jupyter Notebooks

      12:10
    • Data cleaning project, Part I

      8:40
    • Data cleaning project, Part II

      20:18

About This Class

The class is based on real world examples focused on handling, analyzing and visualizing large amounts of data. The class assumes you know nothing about Python so it starts from Python basics and later progresses to learning data analysis and visualization with Python.

As you progress through the video lectures, you will be guided step by step on learning Python for data analysis and visualization and you will progressively build a program that uses real world data containing hundreds of files and millions of records. The sample data will be downloaded, extracted, cleaned, manipulated, analyzed, aggregated and visualized using Python only.

Apart from following the video screencasts, you will also be required to write your own Python scripts from scratch for cleaning, analyzing and visualizing census income data.

More specifically, you will learn to use various Python libraries such as ftplib, os, glob, pandas, numpy, patoolib, matplotlib, seaborn, simplekml and more.

2 of 2 students recommendSee All

I took this course just before landing a job on handling Toshiba customer base. Still not sure what to expect on the new job, but I am already feeling confident using Python for applying various operations on datasets. Excellent instructor!

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Ardit Sulce

Python and GIS Expert, Founder of PythonHow.com

Ardit comes from a tutoring experience in Elance and Upwork where he has built a reputable profile in the Python and GIS domains.

He is also the founder of PythonHow - a web portal for learning Python, targeted to people with no programming experience.

Ardit now teaches full time on several platforms creating high quality courses focused on practical learning with real world scenarios. He is also a facilitator helping his students solve their problems in Python and GIS.

Ardit has an educational background in geodetic engineering with a master degree in geospatial technologies and as he is a self-taught Python programmer.