Quick Introduction to Pandas Library

-

Overview:

Pandas is a python library which provides very powerful tools to perform complex data manipulations and analysis. In this article, few of the commonly used operations are explained.

A common datastructure is a 'Dataframe'. Dataframe is a matrix type of datastructure with easy access to rows and columns.

Creation of Dataframe:




Accessing data from Dataframe:

Data in Dataframe could be accessed in various ways.


Data can also be accessed by slicing the dataframe instead of loops. It is the most efficient way of accessing data.

Creating Dataframe with Index:

We can create Dataframe with an index. Let us create a dataframe with date as index.


As we can see from above, the values are filled as NaN (Not a Number). We can replace NaN with zero using fillna() function. 

Comments

  1. AnonymousFebruary 14, 2026 at 12:02 AM


    In today's digital age, many entertainment options are just a click away. For those interested in visual performances, you can explore the görüntülü show to experience live and engaging content from the comfort of your home. These shows offer a wide variety of entertainment that caters to different tastes and preferences. Whether you're a fan of music, comedy, or drama, there is something for everyone. Check out the görüntülü show to find new ways to enjoy your leisure time.

    ReplyDelete
  2. AnonymousMay 23, 2026 at 12:21 PM

    5CD9F7DE
    esçort bayan amasya
    esçort bayan edirne
    karşıyaka esçort
    kuşadası esçort
    esçort balıkesir
    İzmir rus esçort
    diyarbakır esçort numaraları
    tokat esçort
    esçort maraş

    ReplyDelete
  3. AnonymousJune 28, 2026 at 4:42 AM

    298B5607
    Sinop Esçort
    Uşak Esçort
    Tokat Esçort
    Kırıkkale Esçort
    Gümüşhane Esçort
    Kayseri Esçort
    Ordu Esçort
    Adıyaman Esçort
    Kırşehir Esçort

    ReplyDelete

Post a Comment

Popular posts from this blog

Pivotal Cloud Foundry (PCF) Integration with Elastic Cloud Storage (ECS)

-
Recently, I was involved in integrating Pivotal Cloud Foundry with Elastic Cloud Storage (ECS), an object storage solution from EMC. In this post, I'm going to document the hiccups we faced during this integration and how did we resolve this, so that it is easier for other folks who would like to carry out this integration. References: We followed the blog post, https://blog.codedellemc.com/2016/01/05/emc-ecs-with-cloud-foundry/ and the service broker code from git hub, https://github.com/spiegela/ecs-cf-service-broker .  1. application.yml file Configuration: First task would be to update the application.yml file in the broker code to have the correct configuration. Note the spring profiles created in yml file. The active spring profile is defined in the build.gradle file to be 'development'. So based on that, we need to update the correct section in the yml file. Under the broker section: a) Provide a valid ECS namespace name (The namespa...
Read more

Restful code example using Spring MVC

-
In my previous blog, I talked about Restful webservices design. In this blog, I will provide sample code for the same using Spring MVC framework. Spring MVC 3.x supports annotation based controllers, which are Restful in nature.  Let us create a sample Spring web application for performing CRUD on User entity. Creating project: Create a Maven project with a archetype 'maven-archetype-webapp'. pom.xml <!-- version property --> <properties> <spring.version>3.1.2.RELEASE</spring.version> </properties> <!-- servlet dependency for compilation --> <dependency> <groupId>javax.servlet</groupId> <artifactId>servlet-api</artifactId> <version>2.5</version> <type>jar</type> <scope>compile</scope> </dependency> <!-- Spring MVC dependencies --> <dependency> <groupId>org.springframework</groupId> <artifactId...
Read more

Spring Integration - Bulk processing Example

-
Image
In this post, I'm going to share my experience in using Spring Integration for a bulk processing task. This was the first time I was using Spring Integration and it did not disappoint me. It was pretty robust in terms of error handling and definitely scalable. Disclaimer: The actual task being performed has been modified into a fictitious e – commerce domain task, since I cannot reveal the original task which is customer specific and confidential. However, the nature of the task in terms of processing of clob and xml remain the same and the complexity of the original task has been retained. Also, the views posted on this post are strictly personal. Objective: The objective is to work upon customer information from an ecommerce application and process it and save it into database as clob data. The task is to perform data processing by reading xml from a file in the file system and then store it as clob into a table. Following is the high level of tasks required t...
Read more