Python Pandas Library Full Tutorial
4.1 (145 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.
19,223 students enrolled

Python Pandas Library Full Tutorial

Pandas Library
4.1 (145 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.
19,223 students enrolled
Created by Diptam Paul
Last updated 4/2020
English
English [Auto]
Current price: $16.99 Original price: $24.99 Discount: 32% off
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This course includes
  • 1 hour on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • pandas library
Course content
Expand all 32 lectures 01:14:01
+ Intermediate Level
19 lectures 38:47
Creating DF using Numpy
02:52
Data Type
02:03
Getting Index and Column
00:53
DF to Numpy
01:03
Transpose of DataFrame
00:43
Sorting
01:50
Is Dataframe combination of Series
01:18
loc in Pandas
03:35
What if you mistake a column name
02:29
Deleting Rows or Columns
01:19
Print Certain Amount of Rows and Columns
02:04
Print with Conditions
01:05
Print with Multiple Conditions
01:49
ILOC
03:09
Replace
02:12
Reset Index
02:20
IsNull( )
01:37
DropNA
03:25
Drop Duplicates
03:01
+ Miscellenious
6 lectures 17:23
For Loops
02:18
Adding a New Column
01:18
String Contains and REGEX
03:56
Conditional Changes
01:59
Chunksize
03:46
Requirements
  • numpy arrays
  • python
Description

pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. In this course, you'll learn a lot about this library. Basic knowledge of Numpy is required, as we will perform some tasks using NumPy.

[Note: In this course, we used Jupyter Notebook to write all the codings. in case if you don't have Jupyter Notebook or you don't how to use Jupyter Notebook, you can simply run these codes in any IDE, or even in Python Default IDLE.]

Who this course is for:
  • Beginner in Python
  • Who wants to learn Pandas Library