Pandas with Python Tutorial
4.2 (125 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
29,021 students enrolled

Pandas with Python Tutorial

This Python course will get you up and running with using Python for data analysis and visualization.
4.2 (125 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
29,021 students enrolled
Created by EDU CBA
Last updated 10/2018
English
English [Auto-generated]
Current price: $11.99 Original price: $99.99 Discount: 88% off
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This course includes
  • 6 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Learn about Reading data using Pandas, Series vs Data Frame and Basic Operations in Pandas
  • Understand Sorting, Filtering Data, Filtering Function, and Reading Selective Columns & Rows

Requirements
  • Basic understanding of Computer Programming terminologies.
  • Basic understanding of any of the programming languages is a plus.
Description

Pandas is an open-source, BSD-licensed Python library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. This Python course will get you up and running with using Python for data analysis and visualization.

The training will include the following;

  • Installing Jupyter

  • Jupyter Environment

  • Read data using Pandas

  • Series vs Data Frame

  • Basic Operations in Pandas

  • Analyze the imported data

  • Renaming Columns

  • Sorting

  • Filtering Data

  • Filtering Function

  • Read Selective Columns & Rows

  • And a lot other topics.

Who this course is for:
  • Anyone who wants to learn the basics and various functions of Pandas.
  • Developers
  • Data Visualizers
  • Students and Professionals from Data Analytics field
Course content
Expand all 59 lectures 06:09:45
+ Data Set
9 lectures 49:00
Reading the Data Set
09:10
Series and Data Frame
03:35
Operations in Data Set
03:55
More on Panda Functions
06:19
Column Names and Operation
09:01
Sorting Data Frame
03:02
Filtering Data
07:12
+ Data Analysis
32 lectures 03:15:21
Filter Multiple Criteria
05:49
Selective Columns and Rows
02:56
Data Frame and Series
02:06
Axis Parameter
02:50
String Methods in Pandas
03:55
Changing the Data Types
04:07
Example of Data Type Change
04:31
Group by Functions
04:07
Functions on Series
04:22
Plotting series in Pandas
03:44
Dealing with Null Values
06:03
Uses of Index
07:13
Column in Index
06:59
Output of Data
08:34
Functions of iX Method
09:35
InPlace Parameter
04:59
Inspecting the Space
05:26
Reducing the Space
10:25
Using in Country Series
04:15
Creating Manual Data Frame
06:59
Random Sampling with Pandas
03:42
Concept of Dummy Coding
11:31
Creating Dummified Values
11:31
Duplicates in Data Frame
08:50
Functions for Date and Time
09:10
Setting with Copy Warning
04:56
Example on Copy Warning
04:41
Changing the Display Option
04:29
Formatting the Data
06:57
Tricks for Display Options
07:10
Data with Rows and Columns
09:10
Converting Data Frame
04:19
+ Azure Data Lake
16 lectures 01:57:43
Introduction to Azure Data Lake
07:24
Merging Data Frames
08:32
Shaping a Data Frame
07:41
Filling NA Values
02:41
Importing Time Series Data
07:37
Working with Interpolate Method
09:38
Stacking and Unstacking
10:05
Stacking and Unstacking for 3 Levels
03:51
Concept of Crosstab
08:50
More on Crosstab
07:39
More Options with Crosstab
09:37
Functions of Pivot
03:52
Pivot Table Method
06:29
Example on Pivot Table
09:46
Data Frame to CSV File
06:30
Using Excel Functions
07:31
+ Summary
1 lecture 02:37
Summary on Pandas
02:37