Basic To Advance Python For Data Analysis Part2
Published 1/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.14 GB | Duration: 8h 48m
Data analysis using Pandas in python
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
Requirements
Core concept of Python you should know. I have taught all of it in Part1
Description
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 conversions
Overview
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 Project - Append data from every excel sheet
Lecture 16 Project for you- Append one data into other but with a condition
Lecture 17 Project continues -Now Get excel sheet names automatically
Lecture 18 How to lookup data - Merge function
Lecture 19 Project for you - Create a single lookup column after output is extracted
Lecture 20 Lookup on Two Columns combination -Explore more Merge function
Lecture 21 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 22 How to Filter a data
Lecture 23 Filter using between and isin methods
Lecture 24 How to solve the dates Filtering - Project for you
Lecture 25 Get rows - loc and iloc methods
Lecture 26 How to Lookup data from one table to another - Awesome project
Lecture 27 Remove or Drop Rows and Columns
Lecture 28 How to remove rows and columns using Drop method
Lecture 29 Get duplicates & Remove duplicates -drop duplicate & duplicated methods
Lecture 30 Surprise Test for you - Let us see how much you have learnt
Lecture 31 Remove or drop Nan values from data - Dropna
Python developers, excel data analysts, those who work on data day and night and look for creating automation in reports
Homepage
https://www.udemy.com/course/basic-to-advance-python-for-data-analysis-part2/Fikper
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