Showing posts with label Python. Show all posts
Showing posts with label Python. Show all posts

Sunday, 4 February 2018

Multiple Plots into One Figure in Python MatplotLib

Lets learn, How to plot multiple charts into one Figure. Embedding a jupyter notebook here with the examples.

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Saturday, 3 February 2018

Jupyter Lab Env - Quick Start Script

Every Data Analyst, who is working in Python, is very well aware of Jupyter or Jupyter Lab. 

Sometime it seems little annoying, to lazy person like me, to start the Command Prompt, go to your working code directory and type jupyter command to start the notebook.

To avoid this burden I have wrote a small batch script which will do the task for me in one click. Sharing here the same, Lazy Programmers, please share this post if you like it :-)

For Better View, Click on "View Raw"

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Tuesday, 16 January 2018

Python Pickle - to save your efforts

This tutorial is for Python beginners who just started getting dirty in Python :-) Lots of time when we are working on some data set and completed lots of cleaning and pre-processing steps, It's advisable from GURUs to save that intermediary dataset to avoid the re-do all the steps if something unexpected happen with Python, Jupyter notebook or your system for rebooted without your permission, weird though :-/

So, let's learn how to save any dataset or variable with Pickle library -

To Import:

To Save: 

To Read:

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Tuesday, 2 January 2018

Conda Commands

Sharing some CONDA commands which fasten the administration of different python environment. All these commands are available on Anaconda Site 

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Thursday, 13 July 2017

How to Run Python Code in NotePad++

Can you run the python code from NotePad++ ?? Question seems to be little odd but we can tweak our notepad++ settings and configure it that way. Let's see how -

1. Write few line as your python code, You can use below lines-

print("Today we are going to learn how to use notepad++ to run the python code")
print("As first step, we have to write few python code line")

input("Press Enter to Exit..........")

2. Save this file, in my case, it is saved as ""
3. Check the python executable path in your system. In my case it is - C:\tools\Anaconda3\python.exe  (It can be different as per your python installation)

4. Now go to Run menu or Press F5. This will open a run window as below -

5. Python below code in 'the program to run' -
Python_Executable_Path $(FULL_CURRENT_PATH)
C:\tools\Anaconda3\python.exe $(FULL_CURRENT_PATH)

6. Save this Run configuration by clicking on Save button on same window

7. Choose Run button combination (can use Ctrl + Alt + Shift + Key) and Save.

8. You can see this combination under Run Menu.

9. Now, You can run the Python code by pressing the combination buttons (My case - F9)

Things to Remember:
1. This tweak is not replacement for Python IDE :-) such as PyCharm, Spider or many others.
2. Always put the  input("Press Enter to Exit..........")at very last line of your code else you will not able to see the python code output.

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Saturday, 25 March 2017

Check if Python Pandas DataFrame Column is having NaN or NULL

Before implementing any algorithm on the given data, It is a best practice to explore it first so that you can get an idea about the data. Today, we will learn how to check for missing/Nan/NULL values in data.

1. Reading the data
Reading the csv data into storing it into a pandas dataframe.

2. Exploring data
Checking out the data, how it looks by using head command which fetch me some top rows from dataframe.

3. Checking NULLs
Pandas is proving two methods to check NULLs - isnull() and notnull()
These two returns TRUE and FALSE respectively if the value is NULL. So let's check what it will return for our data

isnull() test

notnull() test

Check 0th row, LoanAmount Column - In isnull() test it is TRUE and in notnull() test it is FALSE. It mean, this row/column is holding null.

But we will not prefer this way for large dataset, as this will return TRUE/FALSE matrix for each data point, instead we would interested to know the counts or a simple check if dataset is holding NULL or not.

Use any()
Python also provide any() method which returns TRUE if there is at least single data point which is true for checked condition.

Use all()
Returns TRUE if all the data points follow the condition.

Now, as we know that there are some nulls/NaN values in our data frame, let's check those out - 

data.isnull().sum() - this will return the count of NULLs/NaN values in each column.

If you want to get total no of NaN values, need to take sum once again -


If you want to get any particular column's NaN calculations - 

Here, I have attached the complete Jupyter Notebook for you -

If you want to download the data, You can get it from HERE.

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Friday, 3 February 2017

Learning Matplotlib #2

Thursday, 2 February 2017

Plotting in Python - Learning Matplotlib #1

Saturday, 14 January 2017

Learning Numpy #2

Thursday, 12 January 2017

Learning Numpy #1

Numpy is a python library used for numerical calculations and this is better performant than pure python. In this notebook, I have shared some basics of Numpy and will share more in next few posts. I hope you find these useful.

Click Here for Next Tutorial ~

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Wednesday, 11 January 2017

My Learning Path for Machine Learning

I am a Python Lover guy so my way includes lots of Python points. If you dont know the basics of this wonderful language, start it from HERE else you can follow the links which I am going to share.

Learning ML is not only studying ML algorithms, it includes Basic Algebra, Statistics, Algorithms, Programming and lot more. But no need to afraid as such :-) we need to start from somewhere.....

This is my github repo, you can fork it and follow me with these 2 links --

Fork Fork
Follow - Follow @atulsingh0
I am still updating this list and welcome you to update this as well.

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Friday, 6 January 2017

10 minutes with pandas library

Thursday, 5 January 2017

Learning Pandas #5 - read & write data from file

Wednesday, 4 January 2017

Learning Pandas #4 - Hierarchical Indexing

Sunday, 1 January 2017

Learning Pandas #3 - Working on Summary & MissingData

Saturday, 31 December 2016

Learning Pandas - DataFrame #2

Friday, 30 December 2016

Learning Pandas - Series #1

Monday, 12 September 2016

Python Points #15 - Exceptions

Tuesday, 14 June 2016

Python Points #14 - Code a childhood game

Level : Intermediate

Try to code this famous childhood game played in india, known as "Raja, Mantri, Chor, Sipahi", in python by seeing the game output shared below -

Little bit about Game:
Chits are made for Raja/King(100 points), Mantri/Minister(80 points),Chor/Thief(0 points) and Sipahi/Insprector(50 points). These chits are then thrown in the middle and 4 players pick one each. Raja/King then exclaims ‘Mera Manrti kaun?’ (Who is my minister?){In my game/code, King is so smart and asked directly to Mantri/Minister} Mantri/Minister responds and s/he is then asked to identify the Chor/Thief (Who stole my Queen's neckless ). If he guesses correctly then the points are retained if s/he is incorrect that he has to surrender the points to the Chor/Thief. The player with highest point wins in the end.

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Tuesday, 31 May 2016

Python Points #13 - Comprehensions