Shayne  Bayer

Shayne Bayer


Python Pandas Tutorial (Part 2): DataFrame and Series Basics

In this video, we will be learning about the Pandas DataFrame and Series objects. This video is sponsored by Brilliant. Go to to si…

#python pandas #pandas #dataframe #series #programming

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Python Pandas Tutorial (Part 2): DataFrame and Series Basics
Ray  Patel

Ray Patel


top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Udit Vashisht


Python Pandas Objects - Pandas Series and Pandas Dataframe

In this post, we will learn about pandas’ data structures/objects. Pandas provide two type of data structures:-

Pandas Series

Pandas Series is a one dimensional indexed data, which can hold datatypes like integer, string, boolean, float, python object etc. A Pandas Series can hold only one data type at a time. The axis label of the data is called the index of the series. The labels need not to be unique but must be a hashable type. The index of the series can be integer, string and even time-series data. In general, Pandas Series is nothing but a column of an excel sheet with row index being the index of the series.

Pandas Dataframe

Pandas dataframe is a primary data structure of pandas. Pandas dataframe is a two-dimensional size mutable array with both flexible row indices and flexible column names. In general, it is just like an excel sheet or SQL table. It can also be seen as a python’s dict-like container for series objects.

#python #python-pandas #pandas-dataframe #pandas-series #pandas-tutorial

Shayne  Bayer

Shayne Bayer


Python Pandas Tutorial (Part 2): DataFrame and Series Basics

In this video, we will be learning about the Pandas DataFrame and Series objects. This video is sponsored by Brilliant. Go to to si…

#python pandas #pandas #dataframe #series #programming

Kennith  Blick

Kennith Blick


Understanding Pandas Series - Python Pandas Tutorial #2

Series is a crucial pandas data structure that you need to master in order to get information of your dataFrame. We will cover from the very basic to more advanced concepts in 15 minutes. We will go through different ways to create a series, how to access and set values, how to slice using index and label index, how to perform math operations and advanced selection using boolean filter.

0:00 - Intro
0:09 - Pandas data structures
0:25 - What is a pandas Series
1:23 - How to create series
4:11 - How to access and set elements to a pandas Series
6:26 - How to slice to a pandas Series
8:34 - Boolean filter selection
12:02 - Arithmetic operations on Series
14:20 - Notebooks on Github


• Learn how to use Jupyter Notebooks ➭
• NumPy ➭
• Matplotlib ➭
• Pandas ➭

• Beginner Python Tutorials ➭
• Intermediate Python Tutorials ➭

• LinkedIn ➭

#pandas #python #python pandas tutorial #pandas series

August  Larson

August Larson


Python for Beginners #2 — Importing files to python with pandas

Use pandas to upload CSV, TXT and Excel files

Story time before we begin

Learning Python isn’t the easiest thing to do. But consistency is really the key to arriving at a level that boosts your career.

We hear a lot about millennials wanting things to easy. In reality, there are a lot of young professionals who believe that they can do more for their companies but are being held back by the work cultures they are faced with at the onset of their careers.

Having been lucky enough to have found a job after my studies, I remember immediately feeling a wave of disappointment a very short while after starting my new job. I felt like a cog in a massive machine. I wasn’t really anything other than a ‘resource’. An extra 8–15 hours of daily man power depending on my boss’ whim.

The result, was the eventual disenchantment and lack of motivation simply because, for the most part, I was expected to be quiet and do my job in the hope of one day being senior enough to effect significant changes. And while the older generation would generally tell me to suck it up, I couldn’t see myself sucking it up for 5 years or more. I knew I’d get stale and afraid of change, much like those telling me to stay in my place.

For anyone in a similar situation,**_ do your best to improve on your skills _**and find an environment that works for you. That’s the whole purpose of these articles. To get you on your way to freedom.


For this demonstration, I’ll use data from this Kaggle competition. It’s a simple CSV file containing data on individuals in the Titanic and the different profiles i.e. (age, marital status etc.)

I want to import this file to python. I’ll show you how to do this alongside all the possible troubleshoots you may encounter.

Table of Contents

  1. Where should you put your files?
  2. Reading CSV and TXT files
  3. Reading excel (XLSX) files

#python #programming #pandas #python for beginners #importing files to python with pandas #python for beginners #2 — importing files to python with pandas