github code link: If you are working on data science, you must know about pandas python module. Pandas and python makes data science and analytics extremely easy and effective. In this tutorial we will cover, 1) What is data science or data analytics? 2) What is pandas? 3) Walk through some basic functionality to show the power of pandas 4) Pandas installation Website: Facebook: Twitter: Google +:


In this tutorial, I explain decorators in a very simple way by going over how to measure execution time of function using decorators. They serve as a wrapper to original function but does a wonderful job of avoiding code duplication and not cluttering original code with additional logic. Code in this tutorial is available here: Website: Facebook: Twitter: Google +: Patreon:


This tutorial covers what is multi-threading and then shows how to create multiple threads in python program. Code used in this tutorial: Website: Facebook: Twitter: Google +: Patreon:


In this git github tutorial, we will learn what is pull request and step by step guide on how to create and merge pull request. Pull requests have become very famous as github popularity is touching the sky. It provides a way to contribute to other people's code. Website: Facebook: Twitter: Google +: Patreon:


In this tutorial we will cover basics of multiprocessing. We will create two processes (each performing different tasks) using multiprocessing module. Code used in this tutorial: Live code: Website: Facebook: Twitter: Google +: Patreon:


Pandas melt function provides a way to transform and reshape dataframe code used in this tutorial: Website: Facebook: Twitter: Google +:


Git is a version control system that allow you to store your code or program on cloud. It also offers features that makes it easy for multiple people to work on same code base. Git today is the most popular version control system and has already surpassed other VCS systems such as SVN. Website: Facebook: Twitter: Google +: Patreon:


In this python pandas tutorial you will learn how groupby method can be used to group your dataset based on some criteria and then apply analytics on each of the groups. This is similar to SQL group by. It is also called split apply combine strategy in data science. Link for code and data used in this tutorial: Website: Facebook: Twitter: Google +:


This tutorial goes over how multiprocessing pool can be used to divide the work among multiple cores of your computer. Also it covers simple explanation of map reduce concept. Link for code: Website: Facebook: Twitter: Google +: Patreon:


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This git tutorial covers the purpose of.gitignore file. It can be used to ignore specific file extensions from being included in git working copy. Website: Facebook: Twitter: Google +: Patreon:


Step by step process on how to install python on windows. Visit my website (link below) for all tutorials and answers on exercises. Website: Facebook: Twitter: Google +: Patreon:


Pandas merge function provides functionality similar to database joins. You can merge two data frames using a column column. One can perform left, right, outer or inner joins on these dataframes. This tutorial also covers indicator and suffixes flags in pandas.merge function. notebook/code used in this tutorial: Website: Facebook: Twitter: Google +:


Learn how to deal with JSON objects in python. JSON (Javascript Object Notation) is a data exchange format (like XML) but it is much light weight. Visit my website for complete list of programming tutorials. Link for code: Website: Facebook: Twitter: Google +: Patreon:


This tutorial goes over how to share data between two different processes using multiprocessing module's queue facility. Multiprocessing queue is different then queue module itself and I have explained the differences in the tutorial. Code used in this tutorial: Website: Facebook: Twitter: Google +: Patreon:


Pandas stack method is used to transpose innermost level of columns in a dataframe. unstack() is used to perform a reverse operation. This tutorial explains stack/unstack using nice visualizations. code: Website: Facebook: Twitter: Google +:


Time series analysis is crucial in financial data analysis space. Pandas has in built support of time series functionality that makes analyzing time serieses extremely efficient. In this tutorial we are going to start time series analysis tutorials with DatetimeIndex and Resample functionality. code: Website: Facebook: Twitter: Google +:


This video covers what is anaconda and how to install it? By installing Anaconda you are also installing jupyter notebook. Anaconda is a bundle of popular python packages such as numpy, scipy, nltk, scikit-learn, jupyter etc. It also comes with package manager called conda (similar to pip) Website: Facebook: Twitter: Google +:


Code used in this tutorial: This tutorial covers pivot and pivot table functionality in pandas. Pivot is used to transform or reshape dataframe into a different format. Pivot table is used to summarize and aggregate data inside dataframe. Website: Facebook: Twitter: Google +:


In this tutorial we will learn why everyone should learn python. If you are a newbie just starting out with programming then python is probably the best place to start. Also for experienced programmers it makes sense to learn python because code development speed is very good and one can to fast prototyping. Python is used heavily in data science, machine learning, scientific computing due to its rich set of libraries (modules). So come and learn python with me :) Website: Facebook: Twitter: Google +:


This tutorial covers how to share data between processes using python's multiprocessing module facilities such as value and array. Code used in this tutorial: Website: Facebook: Twitter: Google +: Patreon:


Learn how you can combine multiple python unit tests into one by using pytest parameters. Link for code in this tutorial: Website: Facebook: Twitter: Google +: Patreon:


This tutorial explains what is jupyter or ipython notebook. Jupyter or ipython notebook is a web application that allows you to run live code, embed visualizations and explanatory text all in one place. Website: Facebook: Twitter: Google +:


This tutorial covers powerful feature in pytest framework called fixtures. It leverages dependency injection concept for setup and teardown of your unit tests. It is preferred over traditional xunit style setup/teardown methods. You can find code used in this tutorial here: Website: Facebook: Twitter: Google +: Patreon:


This tutorial covers array operations such as slicing, indexing, stacking. We will also go over how to index one array with another boolean array. Website: Facebook: Twitter: Google +:


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Learn how to install julia programming language on windows Website: Facebook: Twitter: Google +: Patreon:


In this git tutorial we will learn how to commit a code change locally using git commit and how to upload it to remote using git push. Website: Facebook: Twitter: Google +: Patreon:


This tutorial walks through why locks are needed in multiprocessing environment. It also demonstrates use of Python multiprocessing module's lock. Code used in this tutorial: Website: Facebook: Twitter: Google +: Patreon:


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Code: This pandas tutorial covers basics on dataframe. DataFrame is a main object of pandas. It is used to represent tabular data (with rows and columns). This tutorial will go over, 1) What is dataframe? 2) Create dataframe from csv file and python dictionary 3) Dealing with rows and columns 4) Operations: mean, max, std, describe 5) Conditional selection 6) set_index function and usefulness of it Website: Facebook: Twitter: Google +:


In this tutorial we are covering difference between multiprocessing and multi-threading. The major difference between the two is that in multithreading threads are being executed in one process sharing common address space whereas in multi processing different processes have different address space. Thus creating multiple processes is costly compare to threads. Website: Facebook: Twitter: Google +: Patreon:


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nditer can be used to iterate through numpy array in variety of ways. C style and F style iteration is possible using flags in nditer. You can also iterate two broadcastable arrays concurrently using nditer Website: Facebook: Twitter: Google +:


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PyCharm is a free code editor for python with bunch of rich features that makes it number 1 editor for python code writing. Website: Facebook: Twitter: Google +: Patreon:


code/data link: This tutorial covers 5 different ways of creating pandas dataframe. Pandas is a popular python library especially used in data science and data analytics. Website: Facebook: Twitter: Google +:


In this tutorial, we will cover how to undo or revert a code change. Also I will show you how to reset your git branch to any previous commit id. Website: Facebook: Twitter: Google +: Patreon:


Generators are functions that can be used as iterators. Learn more about them in this tutorial. Code used in this tutorial: Website: Facebook: Twitter: Google +: Patreon:


Introduction on machine learning to begin machine learning with python tutorial series. This video describes what is machine learning, deep learning, machine learning application in real life. In next tutorial we will start writing python code to solve a simple problem using machine learning Website: Facebook: Twitter: Google +:


Crosstab (also known as contingency table or cross tabulation) is a table showing frequency distribution of one variable in rows and another on columns. pandas crosstab method can be used to generate these contingency tables that are extremely useful in survey and business analytics. code: Website: Facebook: Twitter: Google +:


Code link: In this tutorial we'll learn how to handle missing data in pandas using fillna, interpolate and dropna methods. You can fill missing values using a value or list of values or use one of the interpolation methods. Website: Facebook: Twitter: Google +:


In this tutorial, I'll cover a very powerful feature of git called branch. I will show you how you can manage alternate versions of your code by creating separate branches, how to merge branches and delete them. Website: Facebook: Twitter: Google +: Patreon:


This tutorial covers various operations around array object in numpy such as array properties (ndim,shape,itemsize,size etc.), math operations (min,max,sqrt,std etc.), arange, reshape etc. Please give thumbs up/subscribe/comment if you like this tutorial. Website: Facebook: Twitter: Google +:


This tutorial covers introduction to numpy python module. We'll see why numpy is very popular and talk about its main feature n dimensional array. It is memory efficient, fast and convenient compared to python native list. Website: Facebook: Twitter: Google +:


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Shifting and lagging is used to shift or lag the values in a time series back and forward in time. shift and tshift methods can be called on datadframe and timeseries both to either shift values or datetimes. Website: Facebook: Twitter: Google +:


This tutorial covers list (and set/dict) comprehensions which can be used to construct a list, set or dict in a dynamic mathematical way. Website: Facebook: Twitter: Google +: Patreon:


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