Basic to Advance Python for Data Analysis Part2 11 hrs

Data analysis using Pandas in python – Everything you need to know
Basic to Advance Python for Data Analysis Part2 11 hrs
File Size :
4.97 GB
Total length :
10h 45m



ajay parmar


Last update




Basic to Advance Python for Data Analysis Part2 11 hrs

What you’ll learn

You shall learn how to use Pandas library in python using pycharm IDLE to do data analysis
Using the excel sheets and text files or CSV files
You shall learn functions like insert, merge, conctx to lookup the inforamtion like a vlookup in excel does
How to insert new data, append the data, do the updates, do the changes in your data etc
How to filter the data, use the loops in your data, use the previously learnt lists and dictionaries on real time data
Practical projects also shared for you to monitor your progress

Basic to Advance Python for Data Analysis Part2 11 hrs


Core concept of Python you should know. I have taught all of it in Part1


This is Part2 and now after learning python core concepts in pycharm,we are heading towards using the excel and csv files data and using pandas library we will learn how to work with real data.What is a panada library and how to use it for data analysis.Pip – What is it and what is its roleHow to import excel and csv files or text file data and work on it from different locations.How to read the data from files especially if its excel. Read any data from any specific excel sheetsHow to do changes in the data headersHow to extract top or bottom data Learn about inplace parameter How to insert columns and rename existing columns How to remove the blanks or rows /columns from your dataHow to filter the data rows and columnsHow to use set index and how it changes the concept How to use loc and iloc methods to pull the no of rows and columnsHow to apply Vlookup in your data using Merge functionHow to join multiple data from excel sheets using Conct functionHow to find out the duplicate rows or remove the duplicate rows based on different criteriasHow to use for loops in your dataMany practical projects for you with solutions How to do data conversionsHow to use Group byHow to create Pivot reports


Section 1: Introduction – Pandas library

Lecture 1 Introduction to Pandas library

Lecture 2 Pip Concept

Lecture 3 Read CSV Files

Lecture 4 Read Excel files data

Lecture 5 Excel table headers Customization

Section 2: Retrieve/Insert/Rename Columns

Lecture 6 Extract Columns,Head, tail

Lecture 7 Rename Columns and Inplace parameter importance

Lecture 8 Delete Columns from your data -Drop/Del/Pop methods

Lecture 9 Insert a New Column in your data – Insert method and other ways

Lecture 10 Convert Data types using Astype & to_datetime functions- How and Why?

Lecture 11 Reduce data size techniques

Section 3: Loops to use in real data

Lecture 12 For Loops in DataFrame

Lecture 13 Range Loops with series and dataframe concepts

Section 4: How to LookUp Fields in Data

Lecture 14 Concatenate function – Combine the Data from multiple sources

Lecture 15 Show every column Header in Pycharm – for too many Columns

Lecture 16 Project – Append data from every excel sheet

Lecture 17 Project for you- Append one data into other but with a condition

Lecture 18 Project continues -Now Get excel sheet names automatically

Lecture 19 How to lookup data – Merge function

Lecture 20 Project for you – Create a single lookup column after output is extracted

Lecture 21 Lookup on Two Columns combination -Explore more Merge function

Lecture 22 Merge – Left index and Right index and what is a Set Index

Section 5: Filter/ Vlookup/Remove and Extract Rows & Columns of your Data

Lecture 23 How to Filter a data

Lecture 24 Filter using between and isin methods

Lecture 25 How to solve the dates Filtering – Project for you

Lecture 26 Get rows – loc and iloc methods

Lecture 27 How to Lookup data from one table to another – Awesome project

Lecture 28 Remove or Drop Rows and Columns

Lecture 29 How to remove rows and columns using Drop method

Lecture 30 Get duplicates & Remove duplicates -drop duplicate & duplicated methods

Lecture 31 Surprise Test for you – Let us see how much you have learnt

Lecture 32 Remove or drop Nan values from data – Dropna

Section 6: Change Values with Groupby and basic functions like sum count unique etc

Lecture 33 How to change values inside a data

Lecture 34 Basic functions -Sum Count, Unique,nlargest, n smallest & Value Count

Lecture 35 Group by – Powerful and useful to generate reports

Lecture 36 Loops in Groupby – more study on it

Lecture 37 My other Courses details

Python developers, excel data analysts, those who work on data day and night and look for creating automation in reports

Course Information:

Udemy | English | 10h 45m | 4.97 GB
Created by: ajay parmar

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