Seaborn

Basic Statistics and Data Visualization

/ RP / 1 Comment

Doing exploratory, diagnostic and descriptive statistics is the first and very crucial part of any data analytics project.

Here are some more details on each of the steps involved in Exploratory Data Analysis ( EDA)

Let’s now look at examples on how to accomplish these tasks in Python.

You can find all the inbuilt datasets in the seaborn library using the below command-

seaborn.get_dataset_names()

The following datasets are available-

[‘anscombe’,

‘attention’,

‘brain_networks’,

‘car_crashes’,

‘diamonds’,

‘dots’,

‘exercise’,

‘flights’,

‘fmri’,

‘gammas’,

‘iris’,

‘mpg’,

‘planets’,

‘tips’,

‘titanic’]

EDA1EDA2EDA3EDA4EDA5EDA6EDA7EDA8EDA9EDA10

EDA11EDA12EDA13EDA14EDA15EDA16EDA17EDA18EDA19EDA20EDA21EDA22EDA23EDA24EDA25EDA26EDA27EDA28

Cheers!

Install and check Python Packages

/ RP / 2 Comments

Here are some examples on how you can check that necessary packages are installed in the python environment and check their version before moving forward. These are some of the must have packages. If any of the packages are not installed, you can do the anaconda install using conda prompt.  Further directions are shown in the link 

You can search for any package in anaconda environment by using the following code-

anaconda search -t conda seaborn

Installing a package using anaconda prompt is as simple as the line shown below. In this case we are installing a package called Seaborn on anaconda prompt. You can go to the anaconda prompt by typing anaconda prompt in the search menu.

conda install seaborn

Please note that sometimes the anaconda prompt may not let you install new packages and display certain errors like “access denied“. In that case you need to right click on the anaconda prompt shortcut and start as an administrator.

If your conda prompt screen is getting too cluttered you can always clear the screen by typing the command “cls”

Python_version

Cheers!