Basic to Advance Python for Data Analysis Part2 (11 hrs)

Name: Basic to Advance Python for Data Analysis Part2 (11 hrs)
Rating: 4.9 (7 reviews)

Data analysis using Pandas in python - Everything you need to know

Created byajay parmar

Last updated 2/2023

English

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

Course content

6 sections • 37 lectures • 10h 45m total length

Introduction to Pandas library7:30
Learn how the pandas library supports data analysis in Python, enabling data structuring, cleaning, filtering, and pivot reports and charts from Excel, CSV, or databases.
Pip Concept14:09
Read CSV Files10:54
Read Excel files data6:26
Excel table headers Customization6:40

Extract Columns,Head, tail12:10
Learn to extract single or multiple columns from Excel data with pandas, using dot or bracket notation, and use head and tail to view top or bottom rows.
Rename Columns and Inplace parameter importance13:53
Learn how to rename data frame columns in Python using the rename method, rename multiple columns, avoid spaces in headers, and use the in-place parameter to apply changes directly.
Delete Columns from your data -Drop/Del/Pop methods9:51
Insert a New Column in your data - Insert method and other ways19:42
Learn how to add new columns in pandas dataframes using brackets and the insert method, including handling length-matched lists, inserting at different positions, and avoiding the dot notation.
Convert Data types using Astype & to_datetime functions- How and Why?24:08
Discover how to convert data types in python dataframes, including integers, floats, and objects, and use to_datetime for date handling and arithmetic.
Reduce data size techniques8:39
Learn how to assess data size with info and shrink memory usage by converting object columns to category in big data; avoid creating new columns through spelling errors.

Concatenate function - Combine the Data from multiple sources36:43
Explore using pandas concatenate to merge data from multiple sources in Python, choosing axis for column-wise or row-wise joins, while preserving headers and managing index with ignore_index.
Show every column Header in Pycharm - for too many Columns5:14
width = 430
pd.set_option('display.width', width)
pd.set_option('display.max_columns',10)
Project - Append data from every excel sheet12:00
Learn to append data to every excel sheet using python by converting a dictionary to a dataframe, looping through sheets x1, x2, x3, and concatenating data while handling header mismatches.
Project for you- Append one data into other but with a condition26:59
Learn to append data from one Excel file to another under a condition using Python loops, filtering by click > 20, collecting rows, converting to a DataFrame, and concatenating.
Project continues -Now Get excel sheet names automatically5:10
Learn to automate Excel sheet name retrieval with openpyxl by loading a workbook and extracting sheet_names, making your Python data analysis dynamic and up-to-date.
How to lookup data - Merge function19:55
Project for you - Create a single lookup column after output is extracted10:35
Learn to consolidate duplicate lookup IDs after an outer join by creating a single id column, filling blanks from another column, and selecting/excluding headers using pandas data frame operations.
Lookup on Two Columns combination -Explore more Merge function6:22
Merge - Left index and Right index and what is a Set Index10:13

How to Filter a data10:33
Learn how to filter a data frame using criteria, build single and multi condition filters with and/or, and extract east zone or item sold greater than 99 records.
Filter using between and isin methods4:30
How to solve the dates Filtering - Project for you5:08
Acquire skills to filter data by date ranges in Python, converting start and end dates from strings to datetime, and ensuring correct data types for 2004 filtering.
Get rows - loc and iloc methods37:07
Learn to select DataFrame rows with loc and iloc. Use index labels or set_index for campaigns, and understand loc's inclusive end and iloc's position-based access.
How to Lookup data from one table to another - Awesome project29:56
Master the pandas loc method to lookup data between dataframes by label and index, selecting specific rows, columns, or ranges for campaign name, serial number, open, and click.
Remove or Drop Rows and Columns33:20
Learn to delete data in pandas by dropping rows and columns with the drop method, using in place updates and axis settings, and leveraging locator methods for precise range selections.
How to remove rows and columns using Drop method19:58
Apply nested loops and dataframe lookups to match campaigns across multiple excel outputs and populate missing click counts in a combined dataset.
Get duplicates & Remove duplicates -drop duplicate & duplicated methods26:51
Learn to find and remove duplicate rows in a dataset using pandas duplicated and drop_duplicates, with control over subset columns and keep options.
Surprise Test for you - Let us see how much you have learnt25:10
Practice a surprise test on Python data analysis with Pandas, covering reading Excel data, indexing with iloc/loc, selecting columns, merging tables, inserting computed columns, and filtering results.
Remove or drop Nan values from data - Dropna37:19
Drop nan values in a pandas data frame with dropna by rows or columns, using any, all, thresh, and subset for in-place edits.

How to change values inside a data17:09
Basic functions -Sum Count, Unique,nlargest, n smallest & Value Count28:16
Apply basic Python data analysis functions—count, sum, value count, unique, min, max, and n smallest/largest—to data frames with zone filters and percentage contributions.
Group by - Powerful and useful to generate reports47:25
Master the group by technique in Python for data analysis, computing totals, averages, and other aggregates by zone and category. Create multi-level reports, top/bottom selections, and cumulative sums.
Loops in Groupby - more study on it17:59
Demonstrate looping through a group by data frame to process each category and extract the top two rows per group.
My other Courses details1:56
(Python Courses)
Basic to Advance Python for Data Analysis – Part1
https://www.udemy.com/course/basic-to-advance-python-for-data-analysis-part1/?referralCode=83C0824C488AF586740E

Basic to Advance Python for Data Analysis – Part2
https://www.udemy.com/course/basic-to-advance-python-for-data-analysis-part2/?referralCode=32B9BCA458012F5DA4D3

· (Excel Course)
Basic to Advance Excel Part1 (13 hrs)
(Vlookup, Hlookups, Match, Xlookup ,IF, INDEX, Error Handlers, Text functions)
https://www.udemy.com/complete-vlookup-match-cell-referencing-if-discussion/?couponCode=AJAYLOOKUP

Basic to Advance Excel Part2 (21 hrs)
(Count and Sum family ,Indirect,AdvanceFilters, Conditional Formatting,Date Time,Arrays,Offset,Charts)
https://www.udemy.com/course/excel-mis-analytics-training-series3/?referralCode=54E5A03098A3819A6275

Excel Pivots & Dashboards (Basic to Super Advance)
(This course has 6 sections - Pls check course description section - Complete training)
https://www.udemy.com/course/excel-pivots-dashboards-basic-to-super-advance/?referralCode=EC55CB06D2064F025509
·Solved Advance Excel Assignments for Interviews & Confidence
https://www.udemy.com/course/advance-excel-solved-assignments-interview-preparation/?referralCode=204865297D48FA198547

(Excel VBA Course)
Excel VBA Basic to Super Advance level (20 hours plus Course) Part1
It is divided into 5 sections - Introduction, Variables, Loops with IF, Collection Loops with Classes, Arrays & Functions - Basic to Super Advance
https://www.udemy.com/course/excel-vba-basic-to-super-advance-level-20-plus-hrs-course/?referralCode=D859044607839176824F

Excel VBA Basic to Super Advance level (16 hours plus Course) Part2
It is divided into 3 sections – File & folders using scripting library, UserForms, Error Handlers - Basic to Super Advance
https://www.udemy.com/course/excel-vba-basic-to-super-advance-part2/?referralCode=968EF1EA0A59AAA4F462

Excel VBA Basic to Super Advance level (4 hours Course) Part3
https://www.udemy.com/course/excel-vba-basic-to-super-advance-part3/?referralCode=A0617A0A1256E4C96D37
It is divided into 2 sections – CHARTS AND PIVOTS – Everything you can automate now

Excel VBA Connecting Outlook application
https://www.udemy.com/excel-vba-connecting-outlook-application/?couponCode=AJAYOUTLOOK001

Excel VBA Connecting PowerPoint application
https://www.udemy.com/excel-vba-connecting-powerpoint-application-series-13/?couponCode=AJAYPOWERPOINT

Excel VBA Connecting MS Access database
https://www.udemy.com/excel-vba-connect-with-ms-access-series-14/?couponCode=AJAYCONNECTACCESS

Excel & Access VBA Dashboard and Projects
https://www.udemy.com/advance-excel-access-dashboards-vba/?couponCode=AJAYAUTOMATION

Google Sheets (Basic to Advance with Practicals 15 hours) (New)
(This course will educate you about how to work with Google sheets. It has 14 sections as on date covering every minute detail about Sheets)
https://www.udemy.com/course/google-sheets-basic-to-super-advance-with-practicals/?referralCode=21FB7576F528DC634784

POWERPIVOT WITH DAX – PART1
https://www.udemy.com/course/powerpivot-with-dax-part12/?referralCode=3BA481C5ECE51F3D552D

POWERPIVOT WITH DAX – PART2
https://www.udemy.com/course/powerpivot-with-dax-part-22/?referralCode=500EC715F64356090F26

LEARN DAX IN POWERBI DESKTOP – Part 1
https://www.udemy.com/course/learn-dax-in-powerbi-desktop-part-12/?referralCode=CB26F423D30C292EA63D
LEARN DAX IN POWERBI DESKTOP – Part 2
https://www.udemy.com/course/learn-dax-in-powerbi-desktop-part-22/?referralCode=7725602651C8945E7191

POWER BI -BASIC TO ADVANCE PART1 (2022 updated)
https://www.udemy.com/course/basic-to-advance-training-on-microsoft-power-bi-part1-of-2/?referralCode=DF159B91A97C0D976E7F

POWER BI -BASIC TO ADVANCE PART2 (2022 updated)
https://www.udemy.com/course/basic-to-advance-training-on-microsoft-power-bi-part2-of-2/?referralCode=F2930133D2B694C7DE54

Excel Power Query
https://www.udemy.com/course/excel-power-query/?referralCode=B0FCF6BB5ADC2146FEB5

Excel Power Query M Code Programming – Part 1
https://www.udemy.com/course/draft/2684324/?referralCode=D6214BC0E4BFEA7BD5B5

Excel Power Query M Code Programming – Part 2
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Excel Power Query M Code Programming – Part 3
https://www.udemy.com/course/powerquery-m-code-language-part-3/?referralCode=A25E70CD163E89E64738

Excel Power Query M Code Programming – Part 4
https://www.udemy.com/course/powerquery-m-code-language-part4/?referralCode=9EEE9E455E5FCD0CC16E

Web Scraping Using Excel VBA
https://www.udemy.com/draft/2540898/?couponCode=AJAYWEB

(WebScraping Courses)
VBA Web Selenium Web Scraping Part 1
https://www.udemy.com/course/vba-selenium-web-scraping-part-12/?referralCode=251DACD1FE9851322A7B
VBA Web Selenium Web Scraping Part 2
https://www.udemy.com/course/vba-selenium-web-scraping-part-22/?referralCode=D1F35DAB8320D99EE469

· [MS Access VBA Courses]

Access VBA Introduction Series 1
https://www.udemy.com/access-vba-introduction-series1/?couponCode=AJAYACCESSINTRO001
Access VBA Arrays and Functions Series 2
https://www.udemy.com/access-vba-arrays-and-functions-series-2/?couponCode=AJAYACCESSARRAY001
Access Userform and SQL Series 3
https://www.udemy.com/access-vba-series-3/?couponCode=AJAYACCESSFORMS001
Access VBA File Handling and Error Handlers Series4
https://www.udemy.com/access-vba-filefolder-handling-error-handler-s-series-4/?couponCode=AJAYFILES001
Connection Set-Up AccessVBA & Security (ADODB &DAO Series-5)
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Connect Excel & Outlook Access VBA & Collection Loops Series 7
https://www.udemy.com/connect-excel-using-access-vba-collection-loops-series-7/?couponCode=AJAYOUTLOOKEXCELAUTO

· [MS Access front (without VBA)]

Introduction to Tables & Queries Series 1
https://www.udemy.com/ms-access-table-and-queries-series-1/?couponCode=AJAYACCESSINTRO
Sub Queries ,JOINS & Functions Series 2
https://www.udemy.com/ms-access-sub-queries-joins-functions-series2/?couponCode=AJAYFUNCTIONS
MS Access Forms Series 3
https://www.udemy.com/ms-access-forms-series-3/?couponCode=AJAYFORMS
MS Access Macros Series 4
https://www.udemy.com/ms-access-macros-series-4/?couponCode=AJAYMACROS

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 role
How 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 sheets
How to do changes in the data headers
How 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 data
How to filter the data rows and columns
How to use set index and how it changes the concept
How to use loc and iloc methods to pull the no of rows and columns
How to apply Vlookup in your data using Merge function
How to join multiple data from excel sheets using Conct function
How to find out the duplicate rows or remove the duplicate rows based on different criterias
How to use for loops in your data
Many practical projects for you with solutions
How to do data conversions
How to use Group by
How to create Pivot reports

Who this course is for:

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

Basic to Advance Python for Data Analysis Part2 (11 hrs)

What you'll learn

Explore related topics

Course content

Introduction - Pandas library5 lectures • 46min

Retrieve/Insert/Rename Columns6 lectures • 1hr 28min

Loops to use in real data2 lectures • 36min

How to LookUp Fields in Data9 lectures • 2hr 13min

Filter/ Vlookup/Remove and Extract Rows & Columns of your Data10 lectures • 3hr 50min

Change Values with Groupby and basic functions like sum count unique etc5 lectures • 1hr 53min

Requirements

Description

Who this course is for: