Udemy - Excel Automation Using Python

seeders: 31
leechers: 15
updated:
Download torrent
Added by tutsnode in Other > Tutorials
Download Fast Safe Anonymous
movies, software, shows...
  • Downloads: 302
  • Language: English

Files

Excel Automation Using Python [TutsNode.com] - Excel Automation Using Python 3. Pandas Intro
  • 4. ImportingExporting Data from Excel Spreadsheet.mp4 (209.3 MB)
  • 7. Combining DataFrames (Concatenate, Merge & Join).srt (30.9 KB)
  • 4. ImportingExporting Data from Excel Spreadsheet.srt (30.4 KB)
  • 10. Numpy Assignment Solution.srt (22.7 KB)
  • 3. Pandas Dataframe.srt (21.4 KB)
  • 12. Pandas Assignment Solution.srt (18.8 KB)
  • 6. Handling NaN Values.srt (18.8 KB)
  • 8. Data AggregationSummarization using Groupby.srt (15.9 KB)
  • 5. Handling PythonDataframe Data Types.srt (15.9 KB)
  • 9.1 commute.xlsx (14.5 KB)
  • 1. The Power of Pandas (Teaser Video).srt (14.0 KB)
  • 2.1 pd_series.py (0.7 KB)
  • 3.2 pd_df_intro.py (0.9 KB)
  • 4.2 pd_df_impexp.py (0.9 KB)
  • 5.1 pd_df_dtype.py (0.8 KB)
  • 6.1 pd_df_nan.py (0.6 KB)
  • 7.1 pd_df_combine.py (1.0 KB)
  • 2. Pandas Series.srt (10.6 KB)
  • 8.1 pd_groupby.py (0.6 KB)
  • 10.1 np_assignment.py (0.8 KB)
  • 12.1 pd_assignment.py (0.8 KB)
  • 9. Numpy Assignment.srt (4.6 KB)
  • 11. Pandas Assignment.srt (3.1 KB)
  • 7. Combining DataFrames (Concatenate, Merge & Join).mp4 (201.1 MB)
  • 12. Pandas Assignment Solution.mp4 (142.2 MB)
  • 10. Numpy Assignment Solution.mp4 (130.4 MB)
  • 6. Handling NaN Values.mp4 (119.2 MB)
  • 3. Pandas Dataframe.mp4 (114.9 MB)
  • 8. Data AggregationSummarization using Groupby.mp4 (111.1 MB)
  • 5. Handling PythonDataframe Data Types.mp4 (108.0 MB)
  • 1. The Power of Pandas (Teaser Video).mp4 (79.3 MB)
  • 2. Pandas Series.mp4 (60.2 MB)
  • 11. Pandas Assignment.mp4 (37.9 MB)
  • 3.1 flight_data.csv (29.3 MB)
  • 9. Numpy Assignment.mp4 (28.3 MB)
  • 4.1 data.xlsx (2.1 MB)
  • 11.1 sales_data.xlsx (1.3 MB)
5. Implementing Excel Functions in Python
  • 1. Vlookup - I.srt (25.6 KB)
  • 4. Pivot Table - II.srt (13.0 KB)
  • 9. String Manipulation in Python.srt (11.3 KB)
  • 11. Assignment Solution - SUMIF(s) and COUNTIF(s).srt (11.2 KB)
  • 2. Vlookup - II.srt (10.8 KB)
  • 10. Assignment - SUMIF(s) and COUNTIF(s).srt (9.9 KB)
  • 8. Text Manipulation in Excel.srt (9.7 KB)
  • 5. Pivot Table - III.srt (6.5 KB)
  • 7. IF Function - II.srt (6.5 KB)
  • 6. IF Function - I.srt (5.5 KB)
  • 3. Pivot Table - I.srt (4.6 KB)
  • 5.1 pivot_tbl_pd.py (1.4 KB)
  • 4.1 pivot_tbl.py (1.1 KB)
  • 2.1 vlookup_fn.py (1.0 KB)
  • 1.2 vlookup.py (0.7 KB)
  • 11.1 sumif_countif.py (0.9 KB)
  • 9.1 string_fn.py (0.9 KB)
  • 7.1 if_fn.py (0.6 KB)
  • 1. Vlookup - I.mp4 (196.5 MB)
  • 8. Text Manipulation in Excel.mp4 (112.6 MB)
  • 10. Assignment - SUMIF(s) and COUNTIF(s).mp4 (105.6 MB)
  • 4. Pivot Table - II.mp4 (98.6 MB)
  • 11. Assignment Solution - SUMIF(s) and COUNTIF(s).mp4 (72.6 MB)
  • 9. String Manipulation in Python.mp4 (67.0 MB)
  • 2. Vlookup - II.mp4 (65.0 MB)
  • 6. IF Function - I.mp4 (58.7 MB)
  • 5. Pivot Table - III.mp4 (54.1 MB)
  • 3. Pivot Table - I.mp4 (41.0 MB)
  • 7. IF Function - II.mp4 (39.3 MB)
  • 1.1 zipcode_income.csv (4.8 MB)
6. Visualization
  • 12. Visualization Assignment 1 Solution - II.srt (23.2 KB)
  • 5. Hands on With Matplotlib OO Interface - I.srt (22.4 KB)
  • 14. Visualization Assignment 2 Solution.srt (21.9 KB)
  • 9. Combining Pandas Visualization with OO Capabilities - II.srt (21.1 KB)
  • 11. Visualization Assignment 1 Solution - I.srt (16.3 KB)
  • 8. Combining Pandas Visualization with OO Capabilities - I.srt (15.9 KB)
  • 7. Hands on With Matplotlib OO Interface - III.srt (14.9 KB)
  • 6. Hands on With Matplotlib OO Interface - II.srt (13.3 KB)
  • 3. Pandas Visualization.srt (13.0 KB)
  • 1. Excel Visualization.srt (9.3 KB)
  • 2. Python Visualization Intro.srt (7.1 KB)
  • 10. Visualization Assignment 1.srt (5.3 KB)
  • 4. Matplotlib Object Oriented Interface.srt (4.7 KB)
  • 13. Visualization Assignment 2.srt (2.2 KB)
  • 14.1 assignment2.py (1.4 KB)
  • 12.1 assignment1_2.py (1.3 KB)
  • 7.1 plt_oo_3.py (1.3 KB)
  • 9.1 df_plot_oo_2.py (1.1 KB)
  • 11.1 assignment1_1.py (1.0 KB)
  • 3.1 df_plot.py (0.9 KB)
  • 8.1 df_plot_oo_1.py (0.8 KB)
  • 6.1 plt_oo_2.py (0.6 KB)
  • 5.1 plt_oo_1.py (0.6 KB)
  • 12. Visualization Assignment 1 Solution - II.mp4 (184.8 MB)
  • 14. Visualization Assignment 2 Solution.mp4 (147.6 MB)
  • 9. Combining Pandas Visualization with OO Capabilities - II.mp4 (145.1 MB)
  • 11. Visualization Assignment 1 Solution - I.mp4 (114.4 MB)
  • 5. Hands on With Matplotlib OO Interface - I.mp4 (113.5 MB)
  • 7. Hands on With Matplotlib OO Interface - III.mp4 (102.4 MB)
  • 8. Combining Pandas Visualization with OO Capabilities - I.mp4 (97.6 MB)
  • 1. Excel Visualization.mp4 (80.9 MB)
  • 3. Pandas Visualization.mp4 (75.8 MB)
  • 6. Hands on With Matplotlib OO Interface - II.mp4 (70.5 MB)
  • 10. Visualization Assignment 1.mp4 (28.3 MB)
  • 2. Python Visualization Intro.mp4 (25.2 MB)
  • 4. Matplotlib Object Oriented Interface.mp4 (21.7 MB)
  • 13. Visualization Assignment 2.mp4 (8.4 MB)
2. Numpy Intro
  • 4. Numpy Operations.srt (20.9 KB)
  • 2.1 np_1d_array.py (0.6 KB)
  • 5. Indexing and Slicing.srt (17.6 KB)
  • 3.1 np_2d3d_array.py (0.8 KB)
  • 4.1 np_operations.py (1.0 KB)
  • 5.1 np_indexing.py (1.0 KB)
  • 2. Numpy 1d Arrays.srt (13.2 KB)
  • 3. Higher Dimensional Arrays.srt (11.3 KB)
  • 1. What & Why of Numpy and Pandas.srt (10.9 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



Download torrent
4.4 GB
seeders:31
leechers:15
Udemy - Excel Automation Using Python

Trackers

tracker name
udp://inferno.demonoid.pw:3391/announce
udp://tracker.openbittorrent.com:80/announce
udp://tracker.opentrackr.org:1337/announce
udp://torrent.gresille.org:80/announce
udp://glotorrents.pw:6969/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://tracker.pirateparty.gr:6969/announce
udp://tracker.coppersurfer.tk:6969/announce
udp://ipv4.tracker.harry.lu:80/announce
udp://9.rarbg.to:2710/announce
udp://shadowshq.yi.org:6969/announce
udp://tracker.zer0day.to:1337/announce
µTorrent compatible trackers list

Download torrent
4.4 GB
seeders:31
leechers:15
Udemy - Excel Automation Using Python

Torrent hash: 1B9BE2BD9B6E10F89A8FEB8565BB4DD18ED4471B