Course Outline

Introduction

Pandas Overview

  • What is Pandas?
  • Pandas features

Preparing the Development Environment

  • Installing and configuring Pandas

Dataframes

  • Loading a dataset
  • Preparing data
  • Using the Pandas API
  • Working with calculations

Data Structures

  • Working with series
  • Using regex
  • Binning data
  • Normalizing data

Data Visualization

  • Creating graphs with Matplotlib
  • Using Seaborn

Data Assembly

  • Concatenating data
  • Merging data

Predictive Analysis

  • Finding and replacing empty values
  • Using index values
  • Adding time series data
  • Working with frequencies

Summary and Conclusion

Requirements

  • An understanding of data analysis
  • Python programming experience

Audience

  • Data Scientists
 14 Hours

Number of participants



Price per participant

Related Courses

H2O AutoML

14 Hours

AutoML with Auto-sklearn

14 Hours

AutoML with Auto-Keras

14 Hours

Advanced Stable Diffusion: Deep Learning for Text-to-Image Generation

21 Hours

Introduction to Stable Diffusion for Text-to-Image Generation

21 Hours

AlphaFold

7 Hours

Edge AI with TensorFlow Lite

14 Hours

Optimizing AI Models for Edge Devices

14 Hours

TensorFlow Lite for Embedded Linux

21 Hours

TensorFlow Lite for Android

21 Hours

TensorFlow Lite for iOS

21 Hours

Tensorflow Lite for Microcontrollers

21 Hours

Deep Learning Neural Networks with Chainer

14 Hours

Distributed Deep Learning with Horovod

7 Hours

Accelerating Deep Learning with FPGA and OpenVINO

35 Hours

Related Categories