JSON Stands for Java Script Object Notation. JSON is the most renowned and popular data format used for representing semi structure. Don’t get caught up with a JavaScript part of the name as it is independent of any programming language, it is used for storing information in an easy and organized manner and data is in the text format when exchanged between our server and a browser.

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Why do we use JSON over XML?

  1. JSON is less verbose, means JSON has a more compact style than XML, and it is often more readable. The lightweight approach of JSON can make significant improvements.


“Most of us need to listen to the music to understand how beautiful it is. But often that’s how we present statistics: we just show the notes, we don’t play the music.” — Hans Rosling

What is Data Visualization and Why we need Data Visualization?

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Source:Google

Why?

  1. So, imagine you work in an organization as Analyst and you have made certain analysis. Now you need to show that to your teammates or some client. Now you can understand it by looking at the excel sheets or numbers but the other person is not an analyst, he is not from technical background. So, What you need to do? You need to present your analysis or data in such a way that the other person can understand and How you can do that? …


From social media to IOT devices we generate immeasurable amount of data. Consider any service provider around you like zomato, ola, uber, etc. What makes them rich? Answer is Data. Data makes them very rich. Wait! But Is data enough to grow a business? NO, it isn’t. You must know how to use the data to draw useful insights and solve problems. This is where Data Science comes in.

In simple words, Data Science is the process of using data to find solutions/ to predict outcomes for a problem statement.

Data Science Life Cycle:

  1. Concept Study: It involves understanding the business problem, asking questions, get a good understanding of the business model, meet up with all the stakeholders, understand what kind of data is available, all that is part of the first step. …


DataFrames generally refers to a data structure, which is tabular in nature. It represents rows, each of which consists of a number of observations.DataFrames are nothing, but 2-dimensional data structures, similar to a SQL table or a spreadsheet.

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Today we’ll learn about creating dataframes in different ways.

To create Pandas DataFrame in Python, you can follow this general method:

import pandas as pd

data = {'First Column Name': ['First value', 'Second value',...],
'Second Column Name': ['First value', 'Second value',...],
....
}

df = pd.DataFrame (data, columns = ['First Column Name','Second Column Name',...])

df

Working with Different Files:

  1. Reading Data From CSV File : A CSV(Comma Separated Values) is a plain-text file format used to store tabular data such as a spreadsheet or a database. Python uses a CSV package which is a part of the standard library, so you need not install it. …


[pandas] is derived from the term “panel data”, an econometrics term for data sets that include observations over multiple time periods for the same individuals. — Wikipedia.

Pandas has so many uses that it might make sense to list the things it can’t do instead of what it can do. This tool is essentially your data’s home. Through pandas, you get acquainted with your data by cleaning, transforming, and analyzing it.

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For example, say you want to explore a dataset stored in a CSV on your computer. …


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Photo by Dstudio Bcn on Unsplash

In my last blog on decorators, I have discussed decorators, in which we learned about different types of decorators. We discussed examples of functions with parameters and functions without parameters.

Decorators are most often used to extend a function, by adding something either before or after it. Decorators dynamically alter the functionality of a function, method, or class without having to directly use subclasses or change the source code of the function being decorated. Using decorators in Python also ensures that your code is DRY(Don’t Repeat Yourself).


So, What exactly Pandas is?

Pandas is an open-source Python library that provides high-performance, easy-to-use data structure, and data analysis tools for the Python programming language.Python with pandas is used in a wide range of fields, including academics, retail, finance, economics, statistics, analytics, and many others.

Python pandas is well suited for different kinds of data, such as:

  • Ordered and unordered time series data
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Source: Google

Now, How to install pandas on your system? Just run this command

#on terminal or PyCharm
pip install pandas
#on Anaconda
conda install pandas

Let’s know more about very integral part of pandas, which are dataframes and series.The key data structures in pandas are…


It’s simply not enough to process your list data in your code. You need to be able to get your data into your programs with ease, too. It’s no surprise then that Python makes reading data from files easy. Which is great, until you consider what can go wrong when interacting with data external to your programs…and there are lots of things waiting to trip you up! When bad stuff happens, you need a strategy for getting out of trouble, and one such strategy is to deal with any exceptional situations using Python’s exception handling mechanism.

Data is external to your program

Most of your programs conform to the input-process-output model: data comes in, gets manipulated, and then is stored, displayed, printed, or transferred. …


Built-in Function: A function which is already defined in a program or programming framework with a set of statements, which together performs a task and it is called Build-in function. So users need not create this type of function and can use directly in their program or application.Many build in functions are available in most of the programs or programming frameworks and these differ from each other; each one is having its unique functionality.

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Source: Google

Python interpreter has various pre-defined functions that are readily available to use. We don’t have to define these functions to use them; we can directly call them.Few …


What is Error?

Simple Answer: An error is an action which is inaccurate or incorrect. In some usages, an error is synonymous with a mistake.Likewise, In statistics, “error” refers to the difference between the value which has been computed and the correct value. An error could result in failure or in a deviation from the intended performance or behaviour. Now come back to our programming language.The programmer should know the fact that there is very less chances that a program will run perfectly in first time. So the programmer has to make efforts to detect and rectify any kind of errors that are present in the
program. …

Aarti

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