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

df1 = pd.DataFrame({
  'id': [1, 2, 3],
  'name': ['Clark Kent', 'Diana Prince', 'Bruce Wayne'],
})

df2 = pd.DataFrame({
  'id': [2, 1, 4],
  'hero': ['Wonder Woman', 'Superman', 'Aquaman'],
})

df = pd.merge(df1, df2, on='id')
print(df)

# Explanation
A pandas `merge` gets a sequence of `pandas.DataFrame` to merge plus an optional column to merge on. If the column is not provided, pandas will use the index of each DataFrame for merging.

The question is, what happens when one merge column has values that the
other doesn’t? This old question is rooted in relational databases and their join operator. There are several types of joins, and each
defines a different behavior. The pandas `merge` function mimics these operators
as well.
Looking at `pandas.merge` documentation, we’ll see a `how` parameter, like this:

*`how {‘left’, ‘right’, ‘outer’, ‘inner’}, default ‘inner’`*

Here are short definitions of the types of merges that can be performed.
* The **`left`** merge uses only keys from the left frame, similar to a SQL left outer join. This merge preserves key order.
* The **`right`** merge uses only keys from the right frame, similar to a SQL right outer join. This merge also preserves key order.
* The **`outer`** merge uses a union of keys from both frames, similar to a SQL full outer join. This merge sorts keys lexicographically.
* The **`inner`** merge uses the intersection of keys from both frames, similar to a SQL inner join. This merge preserves the order of the left keys.

Understand how to merge the Pandas DataFrames.

Before We Begin

Puzzles

Wrapping Up

Merge the Values of Two DataFrames

Try it yourself

Explanation