Offer: 17 Courses in 6999 Rs (550 Hrs).
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Python Advance Projects Hindi Part4

Python Advance Projects Hindi Part4

Created by Ajay Parmar

Course Description

 

  • Practical Business Scenarios – Covers real-world workflows like reconciling bank statements and allocating support tickets.

  • Data Cleaning & Preprocessing – Handling missing data, duplicates, and formatting for smooth analysis.

  • Excel-Python Integration – Using Python (Pandas) for logic while keeping outputs Excel-friendly.

  • Automation of Repetitive Tasks – Reconciling transactions or distributing tickets automatically instead of manually.

  • Conditional Logic Implementation – Applying rules (e.g., match debit vs credit in bank data, round-robin logic in ticket allocation).

  • Aggregation & Summarization – Grouping data (e.g., tickets per department, reconciled/unreconciled items).

  • Dashboards & Reporting – Preparing Excel reports with ticket summaries or reconciliation status.

  • Problem-Solving Skills – Tackling issues like unmatched transactions or uneven ticket distribution.

  • Hands-On with Pandas – Using groupby, merge, value_counts, filtering, etc., on real datasets.

  • End-to-End Mini Projects – From raw data input → processing → output in Excel reports.

  • File Automation – Reading 100s of Excel/CSV files from a folder automatically.

  • Python + OS Integration – Using os to dynamically fetch filenames and loop through files.

  • Data Merging – Consolidating all sales files into one master dataset with Pandas.

  • Error Handling – Managing missing or corrupt files while merging large volumes of data.

  • Data Cleaning at Scale – Removing nulls, correcting datatypes, formatting columns across files.

  • Dynamic Reporting – Generating summary sales reports (total, region-wise, product-wise).

  • Pivot Table Automation – Creating Excel pivot tables directly from Python using xlwings.

  • Visualization – Automated charts (sales trends, region performance) exported to Excel.

  • Reusable Code – Writing scripts that work for daily/monthly new files without manual changes.

  • Scalability – Designed to handle hundreds/thousands of files efficiently.

  • Time-Saving Automation – Reduces manual effort of copy-pasting data across files.

  • Business-Oriented Outcome – Produces consolidated sales dashboards useful for decision-making.

  • Excel Formatting with xlwings – Styling, formatting, and saving reports professionally.

Course Curriculum

Real Projects – Using Python

  • Project1 : Bank Reconcilation Part1
    00:00
  • Part2
    00:00

Ticket Allocation

Sales Project

Original price was: ₹3,100.00.Current price is: ₹1,499.00.
1,499.00 3,100.00

Python Advance Projects Hindi Part4

Original price was: ₹3,100.00.Current price is: ₹1,499.00.
1,499.00 3,100.00

Course Description

 

  • Practical Business Scenarios – Covers real-world workflows like reconciling bank statements and allocating support tickets.

  • Data Cleaning & Preprocessing – Handling missing data, duplicates, and formatting for smooth analysis.

  • Excel-Python Integration – Using Python (Pandas) for logic while keeping outputs Excel-friendly.

  • Automation of Repetitive Tasks – Reconciling transactions or distributing tickets automatically instead of manually.

  • Conditional Logic Implementation – Applying rules (e.g., match debit vs credit in bank data, round-robin logic in ticket allocation).

  • Aggregation & Summarization – Grouping data (e.g., tickets per department, reconciled/unreconciled items).

  • Dashboards & Reporting – Preparing Excel reports with ticket summaries or reconciliation status.

  • Problem-Solving Skills – Tackling issues like unmatched transactions or uneven ticket distribution.

  • Hands-On with Pandas – Using groupby, merge, value_counts, filtering, etc., on real datasets.

  • End-to-End Mini Projects – From raw data input → processing → output in Excel reports.

  • File Automation – Reading 100s of Excel/CSV files from a folder automatically.

  • Python + OS Integration – Using os to dynamically fetch filenames and loop through files.

  • Data Merging – Consolidating all sales files into one master dataset with Pandas.

  • Error Handling – Managing missing or corrupt files while merging large volumes of data.

  • Data Cleaning at Scale – Removing nulls, correcting datatypes, formatting columns across files.

  • Dynamic Reporting – Generating summary sales reports (total, region-wise, product-wise).

  • Pivot Table Automation – Creating Excel pivot tables directly from Python using xlwings.

  • Visualization – Automated charts (sales trends, region performance) exported to Excel.

  • Reusable Code – Writing scripts that work for daily/monthly new files without manual changes.

  • Scalability – Designed to handle hundreds/thousands of files efficiently.

  • Time-Saving Automation – Reduces manual effort of copy-pasting data across files.

  • Business-Oriented Outcome – Produces consolidated sales dashboards useful for decision-making.

  • Excel Formatting with xlwings – Styling, formatting, and saving reports professionally.

Course Curriculum

Real Projects – Using Python

  • Project1 : Bank Reconcilation Part1
    00:00
  • Part2
    00:00

Ticket Allocation

Sales Project