The solutions to the five Dunder Data Pandas Challenges will be presented below. Try these challenges for yourself at python.dunderdata.com before looking at the solutions. Video solutions for all of the challenges are available on YouTube. The following two datasets are used for the challenges.
import pandas as pd
emp = pd.read_csv('../data/employee.csv', parse_dates=['hire_date'])
emp.head(3)
movie = pd.read_csv('../data/movie.csv', index_col='title')
movie.head(3)
The solutions to the five Dunder Data Python Challenges will be presented below. Try these challenges for yourself at python.dunderdata.com before looking at the solutions. Video solutions for all of the challenges are available on YouTube.
Given a list of integers. Return the difference between the largest and smallest values.
def exercise_1(a_list):
"""
Parameters
----------
a_list : a list of integers
Returns
-------
an integer
"""
# YOUR CODE HERE
...
I’m excited to announce Dunder Data Python and Pandas Challenges! One Python and one Pandas challenge will be released each weekday on python.dunderdata.com. They will vary in difficulty and cover a wide range of topics.
Video solutions for the Python Challenges will be available here with the Pandas Challenges available here. You’ll answer the challenges within your very own Jupyter...
I am excited to announce Python Pandas Certification Courses — a series of courses to help you become an expert at using the pandas library to analyze data, each with a challenging certification exam given at the end.
The main goal of the Python Pandas Certification series of courses is to provide you with a path to gain mastery of the pandas library so that you can use it confidently in a professional environment.
The first course in...
In this post, you'll learn about the different available matplotlib styles that can instantly change the appearance of the plot. Let's begin by making a simple line plot using the default style. This simple style is often the first (and sometimes only) style that many people encounter with matplotlib not realizing how easy it is to choose others.
import matplotlib.pyplot as plt import numpy as np x = np.arange(-2, 8, .1) y = .1 * x ** 3 - x ** 2 + 3 * x + 2 fig, ax...
I am very excited to announce the official release of jupyter_to_medium, a Python package that extends Jupyter Notebooks, allowing you to automate the process of publishing them as Medium blog posts.
I've published dozens of blog posts on Medium myself with all of them beginning as Jupyter Notebooks. Manually converting them to Medium posts was a fairly lengthy, painstaking process. One particularly painful process was inserting tables, which Medium does not support, into...
I'm excited to announce the official release of bar_chart_race
, a python package for creating bar chart races. In this post, I'll cover many of the major available options. Navigate to the official documentation for a full breakdown of all of the options.
Bar chart races have become very popular over the last year and no python package existed to create them. I also built some for my coronavirus dashboard.
Install with:
pip install...
In this tutorial, you'll learn how to create a bar chart race animation such as the one below using the matplotlib data visualization library in python.
bar_chart_race
python package¶Along with this tutorial is the release of the python package bar_chart_race that automates the process of making these animations. This post explains the procedure from scratch.
A bar chart race is an animated sequence of bars that show data values at different moments...
In this tutorial, you will learn how to create the new Tesla Cybertruck using matplotlib. I was inspired by the image below which was originally created by Lynn Fisher (without matplotlib).
Before going into detail, let’s jump to the results. Here is the completed recreation of the Tesla Cybertruck that drives off the screen.
A tutorial now follows containing all the steps that creates a Tesla Cybertruck that drives. It covers the following topics:
This article summarizes the very detailed guide presented in Minimally Sufficient Pandas.
Take my free Intro to Pandas course to begin your journey mastering data analysis with Python.
Upon registration, you'll get access to the following free courses: