Python Interviews

Python Functions

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Python String Methods

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You don't need to know everything about every data tool. Focus on what will help land you your job. For Excel: - IFS (all variations) - XLOOKUP - IMPORTRANGE (in GSheets) - Pivot Tables - Dynamic functions like TODAY() For SQL: - Sum - Group By - Window Functions - CTEs - Joins For Tableau: - Calculated Columns - Sets - Groups - Formatting For Power BI: - Power Query for data transformation - DAX (Data Analysis Expressions) for creating custom calculations - Relationships between tables - Creating interactive and dynamic dashboards - Utilizing slicers and filters effectively I have created 100-Day Roadmap & Resources for Data Analyst 👇👇 https://topmate.io/analyst/861634 Hope it helps :)

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𝗦𝗤𝗟 - How do you write a query to find duplicate rows in a table? - How would you perform a left join and filter out nulls in SQL? - What is a window function in SQL, and how do you use it for ranking data? - How do you calculate the cumulative sum for a column in SQL? - What is the difference between UNION and UNION ALL in SQL? 𝗣𝘆𝘁𝗵𝗼𝗻 - How do you import a CSV file into a pandas DataFrame, and how would you handle missing data? - How do you use list comprehensions to filter and transform data in Python? - What are the differences between the apply() and map() functions in pandas? - How do you visualize data using matplotlib or seaborn in Python? - How do you write a function to calculate the correlation between two numerical columns in a pandas DataFrame? 𝗘𝘅𝗰𝗲𝗹 - How would you use VLOOKUP or XLOOKUP to merge data between two Excel sheets? - What is the difference between absolute and relative cell references, and when would you use each? - How do you create a pivot table, and what types of data analysis can you perform with it? - How would you use conditional formatting to highlight cells that meet certain criteria? - How do you use the IF, AND, and OR functions together to create complex logical tests? 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 - How would you create and customize a calculated column in Power BI? - What is the difference between a slicer and a filter in Power BI, and when would you use each? - How do you create relationships between tables in Power BI, and how do they impact your data model? - How would you set up row-level security (RLS) to control access to sensitive data in Power BI? - What is the purpose of DAX functions like CALCULATE and FILTER, and how do you use them? 𝗧𝗮𝗯𝗹𝗲𝗮𝘂 - How do you create a calculated field in Tableau, and what types of calculations can you perform? - What is a parameter in Tableau, and how can it be used to create interactive dashboards? - How do you use a dual-axis chart in Tableau to show multiple measures in the same view? - How would you optimize a Tableau dashboard for performance when working with large datasets? - How do you create a custom date filter in Tableau to allow users to select specific date ranges? I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://topmate.io/analyst/861634 Like this post for more content like this 👍♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)

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❗️Java vs. Python❗️ ➡️ Python and Java are both popular and powerful programming languages, each with its own unique strengths. Python is known for its simplicity and readability, making it an excellent choice for beginners and rapid development. Its concise syntax allows developers to express concepts with fewer lines of code, promoting faster iteration and prototyping. Python's extensive library ecosystem empowers developers to access a wide range of pre-built tools for various tasks. ➡️ On the other hand, Java is recognized for its platform independence and robustness. It's a statically-typed language, which means errors can be caught at compile time, enhancing code reliability. Java's "write once, run anywhere" philosophy enables applications to run on different platforms without modification, thanks to the Java Virtual Machine (JVM). This also makes Java well-suited for building large-scale, performance-critical applications. ➡️ In summary, Python emphasizes simplicity, readability, and rapid development, while Java prioritizes platform independence, robustness, and performance. The choice between the two largely depends on the project's requirements and the developer's preferences. Share for more: https://t.me/programming_guide

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Python vs R for Machine Learning