Explore puzzles designed to enhance your critical thinking and problem-solving skills using pandas. Gain insights into common pitfalls and sharpen your data manipulation techniques.

test.tar.gz

test

test2

Puzzles are a great way to practice your critical thinking and problem-solving skills. This course assumes a basic understanding of pandas.  The teasers and puzzles in this course are designed to help you practice what you already know and help avoid future mistakes.

Pandas Brain Teasers

# Try it yourself
Try executing the code below to see the result.

import pandas as pd

s = pd.Series(['Rick', 'Morty', 'Summer', 'Beth', 'Jerry'])
print(s.lower())

# Explanation
The `pandas.Series` has a lot of methods, like those listed below:
```py
In [1]: import pandas as pd
In [2]: sum(1 for attr in dir(pd.Series) if attr[0] != '_')
Out[2]: 207
```
But, `lower` is not one of them, as we can see below:
```py
In [3]: hasattr(pd.Series, 'lower')
Out[3]: False
```
Most of the time, people use pandas with numerical data. The pandas developers decided to move non-numerical methods out of the already big `pandas.Series` top-level API. To make the teaser code work, we can use the `.str` attribute.

The `pandas.Series` (and `pandas.DataFrame`) has several special attribute accessors, like those listed below:
* `.str` for string methods such as `lower` and `match`.
* `.dt` to work with date time and timestamp data (for example, `s.dt.year`).
* `.cat` to work with categorical data
* `.sparse` to work with sparse data

# Solution

Let's find out how to use lower with a pandas series.

Before We Begin

Puzzles

Wrapping Up

The lower() Method with Pandas Series

Try it yourself

Explanation