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If you're starting Excel from scratch, focus on these topics.
- Understanding the Excel interface
- Workbook, worksheet, rows and columns
- Cells and cell references
- Creating, opening and saving workbooks
- Entering and editing data
- Copy, cut and paste
- Undo and redo
- Text, numbers and dates
- Font formatting
- Cell colors and borders
- Alignment
- Wrap Text
- Merge & Center
- Number formats
- Currency, percentage and date formats
Learn how Excel formulas work:
=A2+B2
=A2-B2
=A2*B2
=A2/B2
Also understand:
- Operators
- Formula bar
- Order of operations
- Relative references
- Absolute references
- Mixed references
Start with:
=SUM()
=AVERAGE()
=MIN()
=MAX()
=COUNT()
=COUNTA()
=COUNTBLANK()
=IF()
=AND()
=OR()
=NOT()
=IFS()
Example:
=IF(B2>=50,"Pass","Fail")
Very important for analysis:
=COUNTIF()
=COUNTIFS()
=SUMIF()
=SUMIFS()
=AVERAGEIF()
=AVERAGEIFS()
Learn these carefully:
=VLOOKUP()
=XLOOKUP()
=HLOOKUP()
=INDEX()
=MATCH()
=XMATCH()
Understand exact match, approximate match, lookup arrays and return arrays.
Useful for cleaning and manipulating data:
=LEFT()
=RIGHT()
=MID()
=LEN()
=TRIM()
=CLEAN()
=UPPER()
=LOWER()
=PROPER()
=CONCAT()
=TEXTJOIN()
=SUBSTITUTE()
Modern Excel:
=TEXTBEFORE()
=TEXTAFTER()
=TEXTSPLIT()
=TODAY()
=NOW()
=DATE()
=YEAR()
=MONTH()
=DAY()
=DATEDIF()
=EOMONTH()
=EDATE()
=NETWORKDAYS()
=WORKDAY()
- Sort A to Z
- Sort Z to A
- Multi-level sorting
- Custom sorting
- Filters
- Multiple filters
- Clear filters
- Filter by text, number and date
- Creating Tables
- Table styles
- Header rows
- Total Row
- Structured references
- Sorting and filtering tables
- Expanding tables automatically
- Drop-down lists
- Restricting data entry
- Number restrictions
- Date restrictions
- Input messages
- Error alerts
- Highlight cells
- Duplicate values
- Data bars
- Color scales
- Icon sets
- Formula-based formatting
Learn:
- Column charts
- Bar charts
- Line charts
- Pie charts
- Area charts
- Combo charts
Also learn:
- Chart titles
- Data labels
- Legends
- Axis formatting
One of the most important Excel skills.
Learn:
- Creating PivotTables
- Rows
- Columns
- Values
- Filters
- Grouping
- Sorting
- Calculated fields
- Slicers
- PivotCharts
Learn how to handle messy datasets using:
- Remove Duplicates
- Text to Columns
- Flash Fill
- Find & Replace
- TRIM
- CLEAN
- SUBSTITUTE
- Error handling
- Blank values
Understand:
#N/A
#VALUE!
#REF!
#DIV/0!
#NAME?
#NUM!
#SPILL!
And learn:
=IFERROR()
=IFNA()
Start with:
Ctrl + C โ Copy
Ctrl + V โ Paste
Ctrl + X โ Cut
Ctrl + Z โ Undo
Ctrl + S โ Save
Ctrl + F โ Find
Ctrl + H โ Replace
Ctrl + T โ Create Table
Ctrl + 1 โ Format Cells
Ctrl + Shift + L โ Filter
Ctrl + Arrow โ Navigate through data
Ctrl + Shift + Arrow โ Select data
- Page margins
- Orientation
- Paper size
- Print area
- Page breaks
- Headers and footers
- Print titles
- Scaling
Once you've learned the above, practice:
- Total sales
- Average sales
- Highest/lowest sales
- Sales by region
- Sales by product
- Monthly sales
- Employee performance
- Customer analysis
- Basic dashboards
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1. Pandas
Pandas is one of the most important libraries for data automation.
โข Read CSV and Excel files
โข Clean and transform data
โข Remove duplicates
โข Filter records
โข Merge datasets
โข Generate reports
2. OpenPyXL
OpenPyXL is useful for automating Excel files.
โข Update Excel files
โข Add formulas
โข Format cells
โข Create worksheets
โข Apply filters
โข Automate repetitive Excel tasks
3. XlsxWriter
XlsxWriter is useful for creating formatted Excel reports.
โข Create professional reports
โข Add charts
โข Add formulas
โข Format cells and worksheets
โข Create customized Excel outputs
4. pathlib
pathlib makes it easier to work with files and folders.
โข Find files automatically
โข Create folders
โข Move or rename files
โข Check whether files exist
โข Process multiple files
5. Requests
Requests is useful when your data comes from APIs.
โข Send API requests
โข Download data
โข Work with JSON responses
โข Automate data collection
โข Connect APIs with Pandas
6. SQLAlchemy
SQLAlchemy is useful for database automation.
โข Connect Python to databases
โข Run SQL queries
โข Read database data
โข Insert or update records
โข Build data pipelines
7. PyODBC
PyODBC helps Python connect to databases through ODBC.
โข Connect to SQL Server
โข Execute SQL queries
โข Read database records
โข Insert data
โข Automate database tasks
8. Schedule
Schedule helps you run Python tasks automatically.
โข Run scripts at specific times
โข Schedule daily tasks
โข Automate recurring reports
โข Run regular data processing jobs
9. Logging
Logging helps you monitor your automation scripts.
โข Track successful runs
โข Record errors
โข Monitor processes
โข Troubleshoot failures
โข Maintain execution logs
10. Selenium / Playwright
Selenium and Playwright are useful for browser automation.
โข Open websites automatically
โข Fill forms
โข Download files
โข Perform repetitive browser tasks
โข Automate web-based workflows
11. BeautifulSoup
BeautifulSoup is useful for extracting data from web pages.
โข Read HTML
โข Extract text
โข Extract links
โข Collect structured information
โข Combine web data with Pandas
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