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structured data, to extract useful information and support business decision-making.\n\n* It includes tasks such as cleaning, organizing, calculating metrics, statistical analysis, and creating visualizations.\n* Its purpose is to answer specific questions and solve specific problems based on existing data.\n* It requires skills in statistics, database management, and tools such as Excel, SQL, and visualization tools.\n* It is more descriptive and exploratory, focusing on interpreting data to improve efficiency and support business operations.\n\n## Statistics\n\n## Programming\n\n**[Python](https://github.com/rosa-lpz/python/)**\n* Python for Data Cleaning, Processing and Analysis\n   * [NumPy](https://github.com/rosa-lpz/python/tree/main/numpy)\n   * [Pandas](https://github.com/rosa-lpz/python/tree/main/pandas)\n   * [PySpark](https://github.com/rosa-lpz/pyspark)\n* Python for Data Visualization\n  * [Matplotlib](https://github.com/rosa-lpz/python/tree/main/matplotlib)\n  * [Seaborn](https://github.com/rosa-lpz/python/tree/main/seaborn)\n  * [Bokeh](https://github.com/rosa-lpz/python/tree/main/bokeh)\n  * [Plotly](https://github.com/rosa-lpz/python/tree/main/plotly)\n\n**[SQL](https://github.com/rosa-lpz/sql)**\n\n\n## Data Analysis Software Tools\n- **[Power BI](power-bi/)**\n  - [Power Query M](power-bi/power-query-m/)\n    - [Functions](power-bi/power-query-m/functions/)\n      - [Table Functions](power-bi/power-query-m/functions/table/)\n  - [DAX](power-bi/dax/)\n    - [Filters](power-bi/dax/filters/)\n    - [Tables](power-bi/dax/tables/)\n  - [Documentation](power-bi/documentation/)\n- **[Tableau](tableau/)**\n- **[Google Data Studio / Looker](google-data-studio-looker/)**\n\n\n## References / Resources\n### [Resources for Data Science](https://github.com/rosa-lpz/resources-for-data-science)\n  * **Python**\n    * [PDF](dataquest_python-cheatsheet.pdf) | [Website](https://www.dataquest.io/cheat-sheet/python-cheat-sheet/Much) | DataQuest - Python Cheat Sheet\n    * [PDF](cheatsheets/dataquest_pandas-cheat-sheet.pdf) | [Website](https://www.dataquest.io/cheat-sheet/pandas-cheat-sheet/) | DataQuest - Pandas Cheat Sheet\n    * [Website](https://www.datacamp.com/tutorial/matplotlib-tutorial-python) | Datacamp - Introduction to Plotting with Matplotlib in Python\n  * **SQL**\n    * [PDF](cheatsheets/dataquest_sql-cheat-sheet.pdf)  | [Website](https://www.dataquest.io/cheat-sheet/sql-cheat-sheet/) | DataQuest - SQL Cheat Sheet\n  * **Power BI**\n    * [PDF](cheatsheets/dataquest_power-bi_cheat-sheet.pdf) |[Website](https://www.dataquest.io/cheat-sheet/power-bi-cheat-sheet/) | DataQuest - Power BI Cheat Sheet\n    * DataCamp\n      * [PDF](cheatsheets/datacamp_power-bi_cheat-sheet.pdf) | [Website](https://www.datacamp.com/cheat-sheet/power-bi-cheat-sheet) | Power BI \n      * [PDF](cheatsheets/datacamp_power-bi_tables-in-power-query-m.pdf) | [Website](https://www.datacamp.com/cheat-sheet/working-with-tables-in-power-query-m-in-power-bi) | Working with Tables in Power Query M  \n      * [PDF](cheatsheets/datacamp_power-bi_data-transformation_power-query-m.pdf) | [Website](https://www.datacamp.com/cheat-sheet/data-transformation-with-power-query-m-in-power-bi) | Data Transformation with Power Query M  \n      * [PDF](cheatsheets/datacamp_power-bi-formulas-in-DAX_cheat-sheet.pdf) | [Website](https://www.datacamp.com/cheat-sheet/dax-cheat-sheet) | Formulas-in-DAX","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frosa-lpz%2Fdata-analysis-handbook","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frosa-lpz%2Fdata-analysis-handbook","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frosa-lpz%2Fdata-analysis-handbook/lists"}