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.
Note that you have to modify the original dataframe.
Note that you have to modify the original dataframe.
Note that you have to modify the original dataframe.
Store the resulting dataframe in the variable certification_counts
.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable count_by_release_year
.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable average_duration_imdb_score
.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable genre_counts
.
Note: you have to explode the genres
column first.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable imdb_score_std
.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable TMDB_popularity
.
Note: you have to explode the production_countries
column first.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable genres_votes_scores
.
Note: you have to explode the genres
column first.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable genre_avg_deviation
.
Note: you have to explode the genres
column first.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable titles_df
with a new column called standardized_tmdb_popularity
.
Refer to this link for more information about the standardized score formula: https://en.wikipedia.org/wiki/Standard_score
Store the resulting dataframe in the variable min_max_year
.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable genre_year_scores
.
Note: you have to explode the genres
column first.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable genre_average_length
.
Note: you have to explode the genres
column first.
Your result should look similar to this dataframe:
Store the resulting dataframe in the variable certification_stats
.
Your result should look similar to this dataframe:
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! 💥 When I'm not geeking out over AI 🤖 with my classmates or building neural networks, 🧠 you can find me buried in statistics textbooks. 📚 I know, what a nerd! 🤓 I'm always down to learn new ways to speak human 🫂 and computer 💻. Making tech more fun is my jam! 🍇 If you want a cheery data buddy 😎 who can make difficult things easy-peasy 🥝 and learning a party 🎉, I'm your guy! 🙋♂️ Let's chat codes 👨💻, numbers 🧮, and machines 🤖 over coffee! ☕ I'd love to meet more techy humans. 💁♂️ Can't wait to talk! 🗣️
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! 💥 When I'm not geeking out over AI 🤖 with my classmates or building neural networks, 🧠 you can find me buried in statistics textbooks. 📚 I know, what a nerd! 🤓 I'm always down to learn new ways to speak human 🫂 and computer 💻. Making tech more fun is my jam! 🍇 If you want a cheery data buddy 😎 who can make difficult things easy-peasy 🥝 and learning a party 🎉, I'm your guy! 🙋♂️ Let's chat codes 👨💻, numbers 🧮, and machines 🤖 over coffee! ☕ I'd love to meet more techy humans. 💁♂️ Can't wait to talk! 🗣️