Intro to Pandas for Data Analysis

# Practicing Series Vectorized Operations with Penguins Data

In this project, you will be working with a dataset containing information about penguins. Each penguin is described by various attributes such as species, island, culmen length, culmen depth, flipper length, body mass, and gender. You will learn how to apply vectorized operations on the Pandas series derived from the dataset to perform various calculations and manipulations.

## Project Activities

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.

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### Add a constant value of 100 to the `body_mass_g` series

Create a new series called `body_mass_g_plus_100` by adding a constant value of 100 to the `body_mass_g` series.

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### Subtract the `culmen_length_mm` series from the `flipper_length_mm` series

Subtract the `culmen_length_mm` series from the `flipper_length_mm` series and assign the result to a new series called `length_difference`.

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### Multiply the `culmen_depth_mm` series by 2

Multiply the `culmen_depth_mm` series by 2 and assign the result to a new series called `double_culmen_depth_mm`.

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### Raise the `flipper_length_mm` series to the power of 2

Create a new series called `flipper_length_mm_squared` by raising the `flipper_length_mm` series to the power of 2.

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### Calculate the mean of the `culmen_length_mm` series and subtract it from each value in the series

Find the mean of the `culmen_length_mm` series and subtract it from each value in the series. Assign the result to a new series called `culmen_length_mm_mean_centered`.

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### Concatenate the `species` and `gender` series, separated by a hyphen `-`

Create a new series called `species_and_gener` by concatenating the `species` and `gender` series, separated by a hyphen `(-)`.

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### Perform element-wise addition of `culmen_length_mm` and `culmen_depth_mm`

Add `culmen_length_mm` and `culmen_depth_mm` together and assign the result to a new variable called `culmen_length_plus_depth_mm`.

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### Sort `culmen_length_mm` in descending order

Create a new series called `culmen_length_mm_sorted` by sorting `culmen_length_mm` in descending order.

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### Divide `flipper_length_mm` by `culmen_length_mm`

Find the ratio of each penguin's flipper length to its culmen length and assign the result to a new variable called `length_ratio`.

Author

#### Anurag Verma

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! 🗣️

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## Intro to Pandas for Data Analysis

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