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

cities = pd.DataFrame([
  ('Vienna', 'Austria', 1_899_055),
  ('Sofia', 'Bulgaria', 1_238_438),
  ('Tekirdağ', 'Turkey', 1_055_412),
], columns=['City', 'Country', 'Population'])

def population_of(city):
  return cities[cities['City'] == city]['Population']

city = 'Tekirdağ'
print(population_of(city))

import React from 'react';
import { shallow, configure } from 'enzyme';
import Adapter from 'enzyme-adapter-react-16';

configure({ adapter: new Adapter() });

import HelloWorld from './app';

var TestResult = function() {
    this.succeeded = false;
    this.reason = "";
    this.input = "";
    this.expected_output = "";
    this.actual_output = "";
}

export const executeTests = function() {

  var results = [];

  result = new TestResult();
  result.input = 'HelloWorld Component';
  result.expected_output = "span containing text 'Hello World'"

  let wrapper = shallow(<HelloWorld />);

  // Call your Challenge function here.

  let type = wrapper.type();
  let testSuccessful = true;
  let failureReason;

  if (type !== 'span') {
    testSuccessful = false;
    failureReason = "You need to render exactly one span HTML element";
  } else if (wrapper.props().children != "Hello World") {
     testSuccessful = false;
     failureReason = "You have rendered wrong message in your span element";
  }

  result.actual_output = wrapper.html();

  if (testSuccessful) {
    result.succeeded = true;
    result.reason = "Succeeded"
  } else {
    result.succeeded = false;
    result.reason = failureReason;
  }

  results.push(result);

  return results;
}


React

Dart

GoJS React

Typescript React

Vue.js

# Explanation
The output is telling us that `Tekirdağ` couldn't be found in the `cities` DataFrame. But, it’s
clearly there!

Let’s investigate the code below:
```py
In [1]: city
Out[1]: 'Tekirdağ'
In [2]: city2 = cities.loc[2]['City']
In [3]: city2
Out[3]: 'Tekirdağ'
In [4]: city2 == city
Out[4]: False
In [5]: len(city)
Out[5]: 9
In [6]: len(city2)
Out[6]: 8
```

>**Note:** **Unicode** is a universal character encoding standard that assigns a code to every character and symbol of any language.

In the beginning, computers were primarily developed in English-speaking countries, namely, in the UK and the US. When early developers wanted to encode text in ways that computers could understand, they came out with the following scheme:
Use a `byte` (8 bits) to represent a character. For example, `a` is 97 (01100001), `b` is 98, and so on. One byte is enough for the English alphabet, which contains twenty-six lowercase letters, twenty-six uppercase letters, and ten digits.
There is even some space left for other special characters (for example, 9 for the "Tab" key). This scheme is known as **ASCII encoding**.

After a while, countries outside of the UK and the US needed support
for their own languages. ASCII wasn’t good enough, because a single byte can’t hold
all the numbers needed to represent larger alphabets. This led
to several different encoding schemes. The most common one is UTF-8.

Some of the characters in UTF-8 are control characters. In `city`, we have the character `g` at position 7. After that, we have a control character that indicates that a breve should be added to the previous character. This is why the length of the `city` is 9. This is also why `city2` from the `cities` DataFrame has `ğ` at location 7. These are known as Unicode normalization forms. We can use the `unicodedata`
module to normalize strings to the same format.

There might be times where we want to do case-insensitive searches for cities.
In those cases, involving Unicode, `str.lower` or `str.upper` methods won’t adequately do the job. Therefore, we use the `str.casefold` method instead.

Here’s a solution to this teaser incorporating all of these methods:


# Solution

Let's find out how a pandas DataFrames works along with Python functions.



Call Functions on Pandas DataFrames Values

Let's find out how a pandas DataFrames works along with Python functions.

Before We Begin

Puzzles

Wrapping Up

Call Functions on Pandas DataFrames Values

Try it yourself

Explanation