Data Analytics With Pandas Training

Course Duration : 14 Weeks

Level : All Levels

Instructor-Led Training : Yes

Live Classroom: Yes

Live-Online : Yes

Data Analytics With Pandas

Master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool.

By the end of this course, you’ll have not only have grasped the fundamental concepts of data analysis, but through using Python to analyse and manipulate your data, you’ll have gained a highly specific and much in demand skill set that you can put to a variety of practical used for just about any business in the world

Master Data Analysis with Pandas

Vetted curriculum by Industry experts

Real-Time Experienced Trainers

Extensive Career support

Master Data Analytics with Pandas! Unlock the power of data manipulation and analysis. Learn key functions through hands-on exercises and real-world examples. Enrol today to elevate your data skills!

Weeks Duration

Hr/Week Therory

Hr/Week Lab

Students

Data Analysis Intro

Starting Data Analysis

Data analysis fundamentals
Collecting Data

Data wrangling

Exploratory data analysis (EDA)

Drawing conclusions
Basic Statistics
Sampling

Descriptive statistics

Prediction and forecasting

Inferential statistics

Pandas DataFrames

Setting up a virtual environment
Virtual environments

Installing Python packages

Why choose pandas?

Jupyte
Pandas data structures
A Python object

A file

A database

An API
Creating a DataFrame from…
Inspecting a DataFrame
Examining the data

Describing and summarizing the data
Grabbing subsets of the data
Indexing

Selecting columns

Slicing

Filtering
Adding and removing data
Creating new data & adding data

Removing/deleting unwanted data

Data Wrangling

What is data wrangling
Cleaning data

Transforming data

Data enrichment
Cleaning data
Renaming DataFrame columns

Type conversion of DataFrame columns

Reordering, reindexing, and sorting data of DataFrame

Handling duplicate, missing, or invalid data
Finding the problematic/corrupt data

Handling the issues in data
Reshaping data
Transposing DataFrames

Pivoting DataFrames

Melting DataFrames

Aggregating Data Frames

Performing database-style operations
Using DataFrame operations to improve the quality of data
Arithmetic and statistics

Binning

Using functions on DataFrames

Window calculations

Pipes
Aggregating data
Summarizing DataFrames

Aggregating by group

Pivot tables and crosstabs
Time series data
Time-based selection and filtering

Shifting for lagged data

Differenced data

Resampling data

Merging time series data

Pandas and Matplotlib for Data Visualization

Matplotlib
Introduction

Plot components

More options
Pandas for plotting
Chart to show evolution over time

Chart to show relationships between variables

Charts for different distributions

Counts and frequencies
The pandas plotting module
Scatter matrices
Lag plots

Autocorrelation plots

Bootstrap plots

Seaborn for plotting and Customization Techniques

Seaborn for advanced plotting
Representing categorical data
Representing correlations and heatmaps
Regression plots
Faceting
Formatting plots with matplotlib
Chart titles and labels

Chart legends

Formatting chart axes
Customizing the visualizations
Adding reference lines to the graph

Shading chart regions

Annotations

Colors

Textures

Rule-Based Anomaly Detection

Simulating login attempts
Presuppositions

The login_attempt_simulator package

Simulating from the command line
Exploratory data analysis Implementing rule-based anomaly detection
Percent difference

Tukey fence

Z-score

Evaluating performance

Testimonial's

The instructor is so knowledgeable about the program and goes into detailed explanations, explaining why you would do something, where etc… The method of going deep into the fundamentals (such as parameters, arguments, dataframes are made of series and etc) is what inspires me the most to a strong foundation.

D. Shaurya

I always tried to avoid programming, most courses and videos were too hard or boring for me to follow… This is first time that I have actually enjoyed learning python and could complete a course, THANK YOU

M. Viraj

Highly recommended for those wanting to learn python data analytics without any coding background.

L. Aayush

Highly recommended for those wanting to learn python data analytics without any coding background.

J. Amith

I did my Python Training in Hyderabad at Invictus. The Python Training Programme was good. My Python Mentor at Invictus gave us an in-depth training of the Python programming language and its application. Overall a very good training platform for the Python course. I will recommend Invictus to my friends.

Arya

This is a very comprehensive training. it deserves 5 stars. To anyone who wants to get this course, I totally recommend it. It was a brilliant presentation that explicitly focused on time-series analysis

Isaac

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