All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.
All our activities include solutions with explanations on how they work and why we chose them.
Store the resulting series in the variable brand_avg_price.
Store the resulting series in the variable ram_type_warranty_counts.
Store the resulting dataframe in the variable os_avg_rating.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable warranty_min_price.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable touchscreen_proc_gnr_avg_rating.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable ssd_hdd_prices.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable weight_os_bit_avg_price_tot_reviews.
Your result should look similar to this dataframe:
Store the resulting series in the variable brand_price_deviations.
Store the resulting series in the variable weighted_avg_price.
Store the resulting series in the variable brand_ram_percentage.
In this task, you are asked to calculate the minimum, maximum, and the difference between these ratings for each laptop's processor brand and name combination. Store this information in an rating_stats named dataframe for easy reference and visualization. Your output should be similar to this provided example:
Your result should look similar to this dataframe:
Store the resulting series in the variable highest_avg_rating_without_warranty.
Store the resulting column with the name Price_Percentage in the original dataframe laptops_df.
What's up, friends! 👋 I'm a computer science student about to finish my last year of college. 🎓 I LOVE writing code! ❤️ It makes me so happy! 😄 Whether I'm goofing in notebooks 📓 or coding in Python 🐍, writing programs is a blast! 💥
