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Udemy - Excel Automation Using Python

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Added 5 years ago by tutsnode in Other
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Udemy - Excel Automation Using Python (Size: 4.39 GB)
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  TutsNode.com.txt 63 B
  [TGx]Downloaded from torrentgalaxy.to .txt 585 B
  [TutsNode.com] - Excel Automation Using Python
  1. Introduction
  1. Excel vs Python.mp4 45.9 MB
  1. Excel vs Python.srt 9.99 KB
  2. Course Objectives & Prerequisites.mp4 26.41 MB
  2. Course Objectives & Prerequisites.srt 8.27 KB
  3. Anaconda Distribution Introduction.mp4 56.75 MB
  3. Anaconda Distribution Introduction.srt 12.11 KB
  4. Creating Virtual Environment (Optional).mp4 80.82 MB
  4. Creating Virtual Environment (Optional).srt 12.78 KB
  2. Numpy Intro
  1. What & Why of Numpy and Pandas.mp4 62.68 MB
  1. What & Why of Numpy and Pandas.srt 10.91 KB
  2. Numpy 1d Arrays.mp4 68.02 MB
  2. Numpy 1d Arrays.srt 13.19 KB
  2.1 np_1d_array.py 655 B
  3. Higher Dimensional Arrays.mp4 66.36 MB
  3. Higher Dimensional Arrays.srt 11.35 KB
  3.1 np_2d3d_array.py 788 B
  4. Numpy Operations.mp4 111.35 MB
  4. Numpy Operations.srt 20.94 KB
  4.1 np_operations.py 1.02 KB
  5. Indexing and Slicing.mp4 88.24 MB
  5. Indexing and Slicing.srt 17.58 KB
  5.1 np_indexing.py 1.03 KB
  3. Pandas Intro
  1. The Power of Pandas (Teaser Video).mp4 79.28 MB
  1. The Power of Pandas (Teaser Video).srt 14.02 KB
  10. Numpy Assignment Solution.mp4 130.39 MB
  10. Numpy Assignment Solution.srt 22.67 KB
  10.1 np_assignment.py 814 B
  11. Pandas Assignment.mp4 37.86 MB
  11. Pandas Assignment.srt 3.07 KB
  11.1 sales_data.xlsx 1.33 MB
  12. Pandas Assignment Solution.mp4 142.17 MB
  12. Pandas Assignment Solution.srt 18.85 KB
  12.1 pd_assignment.py 868 B
  2. Pandas Series.mp4 60.17 MB
  2. Pandas Series.srt 10.6 KB
  2.1 pd_series.py 751 B
  3. Pandas Dataframe.mp4 114.85 MB
  3. Pandas Dataframe.srt 21.38 KB
  3.1 flight_data.csv 29.34 MB
  3.2 pd_df_intro.py 935 B
  4. ImportingExporting Data from Excel Spreadsheet.mp4 209.26 MB
  4. ImportingExporting Data from Excel Spreadsheet.srt 30.4 KB
  4.1 data.xlsx 2.11 MB
  4.2 pd_df_impexp.py 954 B
  5. Handling PythonDataframe Data Types.mp4 107.96 MB
  5. Handling PythonDataframe Data Types.srt 15.89 KB
  5.1 pd_df_dtype.py 816 B
  6. Handling NaN Values.mp4 119.21 MB
  6. Handling NaN Values.srt 18.83 KB
  6.1 pd_df_nan.py 629 B
  7. Combining DataFrames (Concatenate, Merge & Join).mp4 201.12 MB
  7. Combining DataFrames (Concatenate, Merge & Join).srt 30.93 KB
  7.1 pd_df_combine.py 1.03 KB
  8. Data AggregationSummarization using Groupby.mp4 111.1 MB
  8. Data AggregationSummarization using Groupby.srt 15.91 KB
  8.1 pd_groupby.py 646 B
  9. Numpy Assignment.mp4 28.34 MB
  9. Numpy Assignment.srt 4.56 KB
  9.1 commute.xlsx 14.5 KB
  4. OS Interaction Using Python
  1. How Do We Interact With OS.mp4 43.02 MB
  1. How Do We Interact With OS.srt 5.39 KB
  2. Python OS Library.mp4 54.28 MB
  2. Python OS Library.srt 11.26 KB
  2.1 os_intro.py 633 B
  3. File Handling using Python.mp4 70.34 MB
  3. File Handling using Python.srt 11.44 KB
  3.1 file_handling.py 1.16 KB
  4. Python Glob Library and Handling Filenames.mp4 34.54 MB
  4. Python Glob Library and Handling Filenames.srt 6.3 KB
  4.1 glob_intro.py 562 B
  5. Assignment - Organize Your Files Using Python.mp4 13.98 MB
  5. Assignment - Organize Your Files Using Python.srt 1.98 KB
  6. Assignment Solution - Organizing Files.mp4 77.84 MB
  6. Assignment Solution - Organizing Files.srt 14.7 KB
  6.1 assignment1.py 515 B
  7. Assignment - Consolidate Numerous Files from Various Locations.mp4 5.1 MB
  7. Assignment - Consolidate Numerous Files from Various Locations.srt 1.31 KB
  8. Assignment Solution - Consolidating files.mp4 51.22 MB
  8. Assignment Solution - Consolidating files.srt 8.73 KB
  8.1 assignment2.py 582 B
  5. Implementing Excel Functions in Python
  1. Vlookup - I.mp4 196.54 MB
  1. Vlookup - I.srt 25.62 KB
  1.1 zipcode_income.csv 4.8 MB
  1.2 vlookup.py 689 B
  10. Assignment - SUMIF(s) and COUNTIF(s).mp4 105.6 MB
  10. Assignment - SUMIF(s) and COUNTIF(s).srt 9.88 KB
  11. Assignment Solution - SUMIF(s) and COUNTIF(s).mp4 72.61 MB
  11. Assignment Solution - SUMIF(s) and COUNTIF(s).srt 11.17 KB
  11.1 sumif_countif.py 922 B
  2. Vlookup - II.mp4 64.99 MB
  2. Vlookup - II.srt 10.8 KB
  2.1 vlookup_fn.py 1.05 KB
  3. Pivot Table - I.mp4 41.04 MB
  3. Pivot Table - I.srt 4.56 KB
  4. Pivot Table - II.mp4 98.6 MB
  4. Pivot Table - II.srt 13.02 KB
  4.1 pivot_tbl.py 1.13 KB
  5. Pivot Table - III.mp4 54.15 MB
  5. Pivot Table - III.srt 6.51 KB
  5.1 pivot_tbl_pd.py 1.41 KB
  6. IF Function - I.mp4 58.7 MB
  6. IF Function - I.srt 5.48 KB
  7. IF Function - II.mp4 39.32 MB
  7. IF Function - II.srt 6.5 KB
  7.1 if_fn.py 647 B
  8. Text Manipulation in Excel.mp4 112.56 MB
  8. Text Manipulation in Excel.srt 9.74 KB
  9. String Manipulation in Python.mp4 67.04 MB
  9. String Manipulation in Python.srt 11.28 KB
  9.1 string_fn.py 896 B
  6. Visualization
  1. Excel Visualization.mp4 80.86 MB
  1. Excel Visualization.srt 9.31 KB
  10. Visualization Assignment 1.mp4 28.25 MB
  10. Visualization Assignment 1.srt 5.34 KB
  11. Visualization Assignment 1 Solution - I.mp4 114.4 MB
  11. Visualization Assignment 1 Solution - I.srt 16.26 KB
  11.1 assignment1_1.py 985 B
  12. Visualization Assignment 1 Solution - II.mp4 184.76 MB
  12. Visualization Assignment 1 Solution - II.srt 23.25 KB
  12.1 assignment1_2.py 1.33 KB
  13. Visualization Assignment 2.mp4 8.44 MB
  13. Visualization Assignment 2.srt 2.21 KB
  14. Visualization Assignment 2 Solution.mp4 147.64 MB
  14. Visualization Assignment 2 Solution.srt 21.87 KB
  14.1 assignment2.py 1.42 KB
  2. Python Visualization Intro.mp4 25.2 MB
  2. Python Visualization Intro.srt 7.12 KB
  3. Pandas Visualization.mp4 75.83 MB
  3. Pandas Visualization.srt 12.96 KB
  3.1 df_plot.py 955 B
  4. Matplotlib Object Oriented Interface.mp4 21.69 MB
  4. Matplotlib Object Oriented Interface.srt 4.69 KB
  5. Hands on With Matplotlib OO Interface - I.mp4 113.51 MB
  5. Hands on With Matplotlib OO Interface - I.srt 22.36 KB
  5.1 plt_oo_1.py 625 B
  6. Hands on With Matplotlib OO Interface - II.mp4 70.55 MB
  6. Hands on With Matplotlib OO Interface - II.srt 13.25 KB
  6.1 plt_oo_2.py 631 B
  7. Hands on With Matplotlib OO Interface - III.mp4 102.38 MB
  7. Hands on With Matplotlib OO Interface - III.srt 14.9 KB
  7.1 plt_oo_3.py 1.28 KB
  8. Combining Pandas Visualization with OO Capabilities - I.mp4 97.57 MB
  8. Combining Pandas Visualization with OO Capabilities - I.srt 15.91 KB
  8.1 df_plot_oo_1.py 811 B
  9. Combining Pandas Visualization with OO Capabilities - II.mp4 145.08 MB
  9. Combining Pandas Visualization with OO Capabilities - II.srt 21.1 KB
  9.1 df_plot_oo_2.py 1.14 KB

Description



Description

Excel spreadsheets are ubiquitous and no corporate job is possible without them. Like you, I have been working with them since I started my career. However, I rarely use excel now since I have automated most of my excel based tasks using python which has done wonders to my productivity and I want to help you do the same. I have created this course to help you automate your excel spreadsheets based tasks using python and improve your productivity manifold.

#############################################################################################

Are you someone whose day job requires a lot of manual handling of buggy macros and working on voluminous excel files?
Are you fed up with the tyranny of vlookups, Sumifs, pivot tables and excel dashboards and looking to upskill?
Are you the type of person who would prefer the convenience of python over the unsightliness of VBA code?

If the answer to any of the above questions is yes then you should consider this course. This course will start from the basics and will help you automate reasonably sophisticated excel based tasks. The course will also provide you with enough preparation to explore more advanced topics pertaining to automation/data analysis.

The course covers following topics

Creating python environment
Importing excel into python
Aggregating data from multiple files
Splitting data into multiple files
Interacting with your OS programmatically
Automating popular excel functions such as vlookup, sumif, countif, iserror etc
Automating pivot tables
Automating dashboards

#############################################################################################

Important note – Course prerequisites:

Please note that this course requires basic python proficiency. At the minimum, you should be comfortable with:

basic python data types and format
basic python data structures such as list, dictionary, tuple etc.
how to create python functions
how to implement loops in python

#############################################################################################
Who this course is for:

Heavy users of excel curious about automating their work using python
People who are tired of working with buggy macros and voluminous spreadsheets

Requirements

Python basics (data types, loops, functions etc.)

Last Updated 12/2020

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