Intro to Pandas for Data Analysis

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.

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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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 and assign the result to a new series called `length_difference`

.

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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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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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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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Create a new series called `species_and_gener`

by concatenating the `species`

and `gender`

series, separated by a hyphen `(-)`

.

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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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Create a new series called `culmen_length_mm_sorted`

by sorting `culmen_length_mm`

in descending order.

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

.

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