Publications by Alex Yarosh
Introduction to Data Visualization with ggplot2
Introduction to Data Visualization with ggplot2 1 Introduction 1.1 Drawing your first plot 1.2 Data columns types affect plot types 1.3 Mapping data columns to aesthetics 1.4 Adding geometries 1.5 Changing one geom or every geom 1.6 Saving plots as variables 2 Aesthetics 2.1 All about aesthetics: color, shape and size 2.2 All about aesthetics: ...
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Introduction to the Tidyverse
Introduction to the Tidyverse 1 Data wrangling 1.1 Loading the gapminder and dplyr packages 1.2 Filtering for one year 1.3 Filtering for one country and one year 1.4 Arranging observations by life expectancy 1.5 Filtering and arranging 1.6 Using mutate to change or create a column 1.7 Combining filter, mutate, and arrange 2 Data visualization 2...
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Intermediate Data Visualization with Seaborn
Intermediate Data Visualization with Seaborn 1 Seaborn Introduction 1.1 Reading a csv file 1.2 Comparing a histogram and displot 1.3 Plot a histogram 1.4 Rug plot and kde shading 1.5 Create a regression plot 1.6 Plotting multiple variables 1.7 Facetting multiple regressions 2 Customizing Seaborn Plots 2.1 Setting the default style 2.2 Comparing...
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Introduction to Data Visualization with Seaborn
Introduction to Data Visualization with Seaborn 1 Introduction to Seaborn 1.1 Making a scatter plot with lists 1.2 Making a count plot with a list 1.3 “Tidy” vs. “untidy” data 1.4 Making a count plot with a DataFrame 1.5 Hue and scatter plots 1.6 Hue and count plots 2 Visualizing Two Quantitative Variables 2.1 Creating subplots with co...
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Life Expectancy - 2021/12/31
Life Expectancy - 2021/12/31 1 Get Life Tables 2 Visualize Data for the U.S.A 2.1 Mortality Rate and Age by Gender (U.S.A., 2019) 2.2 Mortality Rate and Age by Year and Gender (U.S.A., 1933-2021) 2.3 Log Mortality Rate and Age by Gender (U.S.A., 2019) 2.4 Log Mortality Rate and Age by Year and Gender (U.S.A., 1933-2021) 2.5 Survival Probability a...
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Introduction to Data Visualization with Matplotlib
Introduction to Data Visualization with Matplotlib 1 Introduction to Matplotlib 1.1 Using the matplotlib.pyplot interface 1.2 Adding data to an Axes object 1.3 Customizing data appearance 1.4 Customizing axis labels and adding titles 1.5 Creating small multiples with plt.subplots 1.6 Small multiples with shared y axis 2 Plotting time-series 2.1...
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Document
LeetCode 217. Contains Duplicate Given an integer array nums, return true if any value appears at least twice in the array, and return false if every element is distinct. Example 1: Input: nums = [1,2,3,1] Output: true Example 2: Input: nums = [1,2,3,4] Output: false Example 3: Input: nums = [1,1,1,3,3,4,3,2,4,2] Output: true 217. Contains Duplic...
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Object-Oriented Programming in Python
Course Description Object-oriented programming (OOP) is a widely used programming paradigm that reduces development times—making it easier to read, reuse, and maintain your code. OOP shifts the focus from thinking about code as a sequence of actions to looking at your program as a collection of objects that interact with each other. In this cours...
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Introduction to SQL
Course Description The role of a data scientist is to turn raw data into actionable insights. Much of the world’s raw data—from electronic medical records to customer transaction histories—lives in organized collections of tables called relational databases. To be an effective data scientist, you must know how to wrangle and extract data from...
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Writing Functions in Python
Course Description You’ve done your analysis, built your report, and trained a model. What’s next? Well, if you want to deploy your model into production, your code will need to be more reliable than exploratory scripts in a Jupyter notebook. Writing Functions in Python will give you a strong foundation in writing complex and beautiful function...
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