python interview questions for data science pdf
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title: "mastering python interview questions for data science: a comprehensive guide with code examples"
introduction:
welcome to the world of python interview questions tailored specifically for data science roles! this tutorial aims to equip you with the knowledge and code examples necessary to ace your python interviews in the field of data science. whether you're a seasoned professional or a budding data scientist, this guide will help you navigate through common interview questions and showcase your python proficiency.
table of contents:
python basics for data science interviews
1.1 variables and data types
1.2 control flow (if statements, loops)
1.3 functions and modules
1.4 list comprehensions
numpy and pandas
2.1 introduction to numpy
array creation and manipulation
array indexing and slicing
2.2 introduction to pandas
dataframe creation and manipulation
data cleaning and preprocessing
data visualization with matplotlib and seaborn
3.1 basic plotting with matplotlib
line plots, scatter plots, histograms
3.2 advanced visualization with seaborn
heatmaps, pair plots, box plots
machine learning with scikit-learn
4.1 building and evaluating models
linear regression, decision trees
4.2 cross-validation and model tuning
gridsearchcv for hyperparameter tuning
sql for data science interviews
5.1 basic sql queries
select, where, group by
5.2 join operations
inner join, left join
web scraping with beautifulsoup
6.1 fetching data from html
parsing html elements
6.2 scraping dynamic websites
handling ajax requests
time series analysis with pandas
7.1 working with datetime objects
resampling and shifting
7.2 time series visualization
plotting trends and seasonality
conclusion:
congratulations! you've now covered a wide range of python topics relevant to data science interviews. remember to practice these concepts and code examples to strengthen your understanding. good luck with your interviews, and may your python skills shine bright in the wo ...
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