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๐Ÿ‘ 1โค 1
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๐Ÿ‘ 9โค 2๐Ÿฅฐ 1
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โค 5
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๐Ÿ‘ 2โค 1
Important Pandas topics for a data analysis interviews ๐Ÿ‘‰ DataFrame and Series: Understand the fundamental data structures in pandas. A DataFrame is a 2-dimensional labeled data structure, while a Series is a 1-dimensional labeled array. ๐Ÿ‘‰ Data Cleaning and Manipulation: Be able to clean and preprocess data using functions like drop, fillna, replace, and apply. Know how to filter and select specific rows and columns using conditions. ๐Ÿ‘‰ Indexing and Slicing: Understand how to use various indexing techniques like label-based indexing (loc) and position-based indexing (iloc). Practice slicing data for specific rows and columns. ๐Ÿ‘‰ Grouping and Aggregation: Know how to use the groupby function to group data based on certain columns and perform aggregation functions like sum, mean, count, etc. ๐Ÿ‘‰ Merging and Joining: Be familiar with methods to combine multiple DataFrames using merge and join operations. Understand the different types of joins (inner, outer, left, right) and when to use them. ๐Ÿ‘‰ Reshaping Data: Learn about techniques to reshape data using functions like pivot, melt, and stack/unstack. Understand the concept of wide and long data formats. ๐Ÿ‘‰ Data Visualization: While not exclusive to pandas, you might need to use pandas to prepare data for visualization. Familiarize yourself with plotting functions and libraries like Matplotlib and Seaborn. ๐Ÿ‘‰ Handling Dates and Time: Be comfortable working with date and time data using pandas' datetime functionality. This includes date parsing, date arithmetic, and resampling time series data. ๐Ÿ‘‰ Handling Missing Data: Learn techniques to identify and handle missing data, such as using functions like isna, fillna, and considering strategies for imputation. ๐Ÿ‘‰ Performance Optimization: Understand ways to optimize performance when working with large datasets, such as using vectorized operations and avoiding unnecessary loops. ๐Ÿ‘‰ Reading and Writing Data: Know how to read data from various file formats (CSV, Excel, SQL databases) into pandas DataFrames and write DataFrame data back to these formats. ๐Ÿ‘‰ Exploratory Data Analysis (EDA): Practice using pandas to perform basic exploratory data analysis tasks like summarizing data, calculating basic statistics, and identifying trends or patterns. Free Resources to learn Pandas ๐Ÿ‘‡๐Ÿ‘‡ https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with-python-course https://t.me/DataAnalystInterview/55?single https://bit.ly/3LkLtLj https://bit.ly/3DFMgDY https://t.me/learndataanalysis/30 Remember, the depth of your understanding in each topic will depend on the specific requirements of the interview and the role you're applying for. Practice by working on real datasets and solving data analysis problems using pandas to build your proficiency in these areas. ENJOY LEARNING ๐Ÿ‘๐Ÿ‘
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๐Ÿ‘ 10โค 1
๐Ÿš€ Microsoft is offering some FREE courses ๐Ÿš€ 1๏ธโƒฃ AI for beginners Check this out ๐Ÿ‘‡ http://microsoft.github.io/AI-For-Beginners 2๏ธโƒฃ IOT Check this out ๐Ÿ‘‡ https://microsoft.github.io/IoT-For-Beginners 3๏ธโƒฃ Machine Learning Check this out๐Ÿ‘‡ http://microsoft.github.io/ML-For-Beginners/#/ 4๏ธโƒฃ Data Science Check this out๐Ÿ‘‡ http://microsoft.github.io/Data-Science-For-Beginners/#/ Free Coding Courses ๐Ÿ‘‡ https://t.me/programming_guide Few more courses โœ… ๐Ÿญ.๐——๐—ฎ๐˜๐—ฎ ๐—™๐˜‚๐—ป๐—ฑ๐—ฎ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐—น๐˜€ https://learn.microsoft.com/en-us/training/paths/azure-data-fundamentals-explore-non-relational-data/ ๐Ÿฎ.๐—ฆ๐—พ๐—น ๐—™๐˜‚๐—ป๐—ฑ๐—ฎ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐—น๐˜€ https://learn.microsoft.com/en-us/training/paths/azure-sql-fundamentals/ ๐Ÿฏ.๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—•๐—œ https://learn.microsoft.com/en-us/training/paths/create-use-analvtics-reports-power-bi/ ๐Ÿฐ.๐—”๐˜‡๐˜‚๐—ฟ๐—ฒ ๐—ฐ๐—ผ๐˜€๐—บ๐—ผ๐˜€ ๐——๐—• https://learn.microsoft.com/en-us/training/paths/create-use-analytics-reports-power-bi/ ๐Ÿฑ.๐—”๐—œ ๐—ณ๐˜‚๐—ป๐—ฑ๐—ฎ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐—น๐˜€ https://learn.microsoft.com/en-us/training/paths/create-no-code-predictive-models-azure-machine-learning/
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๐Ÿ‘ 7โค 1
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๐Ÿ‘ 9โค 5๐Ÿ‘ 2๐Ÿคฃ 2
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