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

nums = pd.Series([1, 2, 3, 4, 5, 6])
print(nums[(nums > 2) and (nums < 5)])

# Explanation
The result of `nums > 2` is the series of Boolean values listed below:
```py
In [1]: nums>2
Out[1]:
0 False
1 False
2 True
3 True
4 True
5 True
dtype: bool
```
We can use this Boolean series to select parts of other series that are the same size, including, of course, `nums`. The process, which is shown below, is known as **Boolean inexing**.
```py
In [2]: nums[nums>2]
Out[2]:
2 3
3 4
4 5
5 6
dtype: int64
```

We can combine two or more Boolean series to
create a more complex condition using Python's logical operators `and`, `or`, and `not`. This is what we're doing in the teaser `(nums > 2)` and `(nums < 5)`. However, these Python logical operators will call the built-in Boolean function on `nums > 2` and `nums < 5`.

Just like we saw in the first puzzle, [Rectified](https://www.educative.io/courses/pandas-brain-teasers/relational-operators-with-pandas-series), this will raise an error. To solve this, pandas and NumPy use the bitwise operators listed below:
* `&` instead of `and`
* `|` instead of `or`
*  `~` instead of `not`


Let's find out how to use relational operators to compare the values of a pandas series. 

Relational and Logical Operators with Pandas Series

Let's find out how to use relational operators to compare the values of a pandas series.

Before We Begin

Puzzles

Wrapping Up

Relational and Logical Operators with Pandas Series