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Análise e Visualização de Dados em Python
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Intermediate
O currículo do track abrange um conjunto de cursos fundamentais que fornecem o conhecimento e as habilidades necessárias para uma jornada de sucesso no campo da ciência de dados. Esses cursos englobam o estudo aprofundado de conceitos-chave, ferramentas e metodologias essenciais para o domínio da análise e modelagem de dados. Mostre mais
python
Power BI
Tableau
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Try Codefinity TeamsWhat you will learn
- Gain a deep understanding of NumPy and learn how to efficiently manipulate arrays for data analysis
- Explore the fundamentals of pandas to clean, transform, and analyze tabular data with ease
- Master essential and advanced visualization techniques to create compelling and insightful charts using Python
- Learn to build interactive reports and dashboards in Power BI to effectively communicate data-driven insights
- Develop proficiency in Tableau to create dynamic visualizations and uncover hidden patterns in complex datasets
- 156 chapters
- 16 hours
- 150 tasks
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Learning track content
Module 1 / Ultimate NumPy
First of all, we will discuss the applications of NumPy and why it is popular. Afterwards you will learn various possible options to create different arrays in NumPy.
It's now time to learn how to use index notation to retrieve specific elements or subsets of data from arrays. You will also learn how to use indices to retrieve data based on certain conditions and handle missing values.
There are quite few of common operations on arrays which you may want to perform. Luckily, NumPy has built-in functions and methods for this purpose which you will learn here.
It's time to discover how to efficiently use mathematical operations on NumPy arrays and apply them in some real-world problems.
Module 2 / Pandas First Steps
In this section, we'll explore the fundamentals of Series and DataFrame structures. You'll also learn about the distinctions between these two types of structures.
- What is pandas?Preview
- SeriesPreview
- Challenge: Creating a SeriesPreview
- DataFramePreview
- Quiz: Creating a SeriesPreview
- Quiz: Creating a DataFramePreview
- Adding a New ColumnPreview
- Inserting a New ColumnPreview
- Deleting a Row/ColumnPreview
- Quiz: Matching the FunctionsPreview
- Working with ColumnsPreview
- Quiz: Extracting ColumnsPreview
- iloc BasicsPreview
- Challenge: Using ilocPreview
Data can be sourced in various formats, such as CSV, JSON, SQL, HTML, and more. With Pandas, you're not limited to a single format — you can work with data across a multitude of file types. In this chapter, we'll specifically focus on the CSV and TXT formats.
Here, you'll learn how to process raw data by removing extraneous information and managing null values in a dataset.
- Viewing the DataPreview
- Quiz: Using HeadPreview
- Quiz: Head, Tail, and SamplePreview
- Exploring the DatasetPreview
- Column Names and Data TypesPreview
- Finding Null ValuesPreview
- Quiz: Identifying Null ValuesPreview
- Challenge: Dropping Null ValuesPreview
- Challenge: Filling Null ValuesPreview
- Quiz: Null ValuesPreview
- Describing the DataPreview
- max() and min()Preview
- Quiz: Statistical OperationsPreview
- sum() and count()Preview
- Unique ValuesPreview
Module 3 / Ultimate Visualization with Python
First, we will discuss plotting applications, Matplotlib library, and its advantages. Afterwards you will create your first simple plot using Matplotlib.
Now you are ready to create various commonly used in practice plots. Without further ado, let's dive in right now!
Plotting and visualization is not only about creating a plot or several plots, it is also about making them clear, understandable and pleasant to look at. Time to learn plots customization in maplotlib, let's do it!
Seaborn is another powerful plotting library in Python built on top of matplotlib. Now that you are familiar with matplotlib, it's time to dive into visualization with seaborn.
Module 4 / Introduction to Power BI
Dive into the world of Power BI and build a solid foundation. You'll cover everything from installation and setup to connecting data sources and creating your first report.
Explore essential data preparation techniques, including cleaning, transforming, and combining multiple data sources. You'll also tackle handling missing values, data profiling, and various data manipulation methods.
Master the fundamentals of data modeling, from understanding data models and creating relationships to getting the hang of DAX basics. You'll also learn to create measures and calculated columns.
Discover various visualization techniques and customize visuals for better insights. You'll also explore advanced features like slicers, filters, and drill-down/drill-through capabilities to enhance your data analysis.
Boost the usability and storytelling power of your reports by using themes, configuring report pages, and leveraging advanced features like the Analyze feature and identifying outliers. You'll also create groups, bins, and clusters for deeper insights.
Module 5 / Tableau Fundamentals
This section lays the groundwork for mastering Tableau by guiding you through installation, navigation, and foundational operations. From performing joins and splitting columns to understanding filters, marks, and the data pane, you will be equipped with essential tools for data exploration and visualization.
- What You Will LearnPreview
- Tableau InstallationPreview
- First StepsPreview
- Field Operations and JoinsPreview
- Challenge: Joining Tables and Splitting ColumnsPreview
- Exploring the Data PanePreview
- Challenge: Identifying Top Performers by ProfitPreview
- Pages, Filters, and Marks OverviewPreview
- Challenge: Finding the Sub-Category with the Lowest SalesPreview
This section delves into Tableau's powerful tools for data organization, filtering, and customization. You'll learn to differentiate dimensions and measures, work with continuous and discrete fields, and create calculated fields and interactive dashboards. Through practical challenges, you'll apply these tools to analyze data, uncover insights, and enhance your visualizations.
- Dimensions and MeasuresPreview
- Challenge: Comparing Sales and Profit by StatePreview
- Continuous and Discrete FieldsPreview
- Challenge: Identifying the Month with Lowest SalesPreview
- Dimension FiltersPreview
- Measure FiltersPreview
- Challenge: Finding the Most Profitable Customer in ArtPreview
- Calculated FieldsPreview
- Challenge: Comparing California and New York to Other StatesPreview
- Interactive Dashboards with ParametersPreview
- Challenge: Finding the Sub-Category with the Most SalesPreview
- Working with SetsPreview
- Challenge: Analyzing Bookcase Profit ConcentrationPreview
- Sets ApplicationsPreview
This section focuses on creating impactful visualizations to uncover patterns and trends in your data. From heatmaps and scatter plots to treemaps and combination charts, you'll explore a variety of chart types tailored to different analytical needs.
- Visualizing Data with HeatmapsPreview
- Challenge: Identifying Top-Selling Sub-Category by RegionPreview
- Scatter PlotsPreview
- Challenge: Determining the Highest Sales and Profit by StatePreview
- TreemapsPreview
- Challenge: Analyzing the Least Profitable Sub-CategoryPreview
- Combination ChartsPreview
- Challenge: Comparing Sales and Profit Trends for PhonesPreview
- SparklinesPreview
This section introduces advanced visualization techniques to enhance data analysis and storytelling. You'll learn to create bullet graphs, stacked area charts, histograms, and box plots, enabling deeper insights into trends, distributions, and comparisons.
Requirements
- A computer with a browser - all browsers are supported.
- Your enthusiasm to enhance your tech skills.
- Everything else needed to start learning and practicing is already included in this course.
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Graças a eles, estou aprendendo muito mais rápido porque eles ajudam você a entender tudo desde o início. É o melhor site que ajuda pessoas sem conhecimento em TI...
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A Codefinity é uma ferramenta de aprendizagem abrangente que ajuda a desenvolver as suas habilidades como engenheiro de software ou cientista de dados. Os exercícios são divertidos...
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Bem desenhado para iniciantes totais
Bem desenhado para iniciantes totais, progresso incremental e faz-me sentir confiante....
_Gracy
é simplesmente muito bem explicado
é simplesmente perfeitamente bem explicado! Até agora, não tive qualquer dificuldade porque tudo é muito bem gerido...
Ruslan Kravchuk
O principal é aprender e não desistir
O material é bom, há muito a aprender, tudo para se tornar melhor e o principal é aprender o que você quer....
Matteo Comune
Graças a eles, estou aprendendo muito…
Graças a eles, estou aprendendo muito mais rápido porque eles ajudam você a entender tudo desde o início. É o melhor site que ajuda pessoas sem conhecimento em TI...
Yuliana Cadavid
óptimo curso para iniciantes
ótimo curso para iniciantes, eles testam o seu conhecimento em cada lição...
Elpunzon
Estou a gostar da minha experiência com a Codefinity…
Estou a gostar da minha experiência de aprendizagem do Python com a Codefinity. A forma de aprendizagem ao meu ritmo é óptima porque posso ajustá-la ao meu horário...
Alexandru Alexandru
É bom aprender com o Codefinity
É bom aprender com o Codefinity. É fácil e tem bons exemplos do que aprendi aqui...
jacob Templet
Easy to follow along with and provides…
É fácil seguir e proporciona desafios no meu dia-a-dia. O desafio mantém-me querendo aprender dia após dia...
Elan
A Codefinity é uma ferramenta de aprendizagem abrangente…
A Codefinity é uma ferramenta de aprendizagem abrangente que ajuda a desenvolver as suas habilidades como engenheiro de software ou cientista de dados. Os exercícios são divertidos...
Thibault
Primeira vez aprendendo a programar
Primeira vez a aprender a programar e conseguindo-o com sucesso com a Codefinity - obrigado...
Adrien Morel
Bem desenhado para iniciantes totais
Bem desenhado para iniciantes totais, progresso incremental e faz-me sentir confiante....
_Gracy
é simplesmente muito bem explicado
é simplesmente perfeitamente bem explicado! Até agora, não tive qualquer dificuldade porque tudo é muito bem gerido...
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