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Data Science with Python

Distributions and Aggregations in Data

Mihaela Danci

Mastering distributions and aggregations is essential for effective exploration, summarization, and analysis of datasets. This course will teach you how to analyze distributions and implement advanced data summarization techniques.

Distributions and aggregations are essential tools in data science enabling the exploration, summarization, and in-depth analysis of data to derive actionable insights.

In this course, Data Science with Python: Distributions and Aggregations in Data, you’ll gain the ability to explore complex datasets and extract meaningful information.

First, you’ll explore univariate and bivariate distributions using graphical techniques, with an emphasis on understanding the principles of correlation and causation.

Next, you’ll discover how to perform advanced data manipulation techniques, including grouping and aggregation.

Finally, you’ll learn how to reshape data using crosstabs and pivot tables for data summarization and analysis.

When you’re finished with this course, you’ll have the skills and knowledge of distributions and aggregations needed to explore, summarize, and analyze data with Python.

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What's inside

Syllabus

Course Overview

Analyzing Distributions

Exploring Data Summarization Techniques

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Students seeking advancement with Python advanced distribution and aggregation analysis

Those who wish to explore data deeply, summarize data effectively, and analyze datasets in-depth

Designed for those looking to build their expertise in data analysis using Python programming language

Teaches critical Python techniques to analyze distributions and implement advanced data summarization methods

Taught by Mihaela Danci, recognized for her work in data science

Involves hands-on exploration of complex datasets to extract valuable insights

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Career center

Learners who complete Data Science with Python: Distributions and Aggregations in Data will develop knowledge and skills that may be useful to these careers:

Research Analyst

Research Analysts use their research skills and expertise to analyze data and trends that can drive business decisions. They collect and interpret data from a variety of sources to identify patterns and insights. The Data Science with Python: Distributions and Aggregations in Data course can help Research Analysts build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Research Analysts.

See salaries and explore the career path for Research Analyst

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use statistical techniques to draw conclusions from data and communicate their findings to stakeholders. The Data Science with Python: Distributions and Aggregations in Data course can help Data Analysts build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Data Analysts.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their expertise in data analysis, statistics, and machine learning to solve complex business problems. They develop and implement data-driven solutions to improve decision-making and drive business value. The Data Science with Python: Distributions and Aggregations in Data course can help Data Scientists build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Data Scientists.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts use their analytical skills to identify and solve business problems. They work with stakeholders to gather requirements, analyze data, and develop solutions that improve business processes. The Data Science with Python: Distributions and Aggregations in Data course can help Business Analysts build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Business Analysts.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians use their expertise in statistical methods to analyze data and draw conclusions. They work in a variety of fields, including research, healthcare, and public policy. The Data Science with Python: Distributions and Aggregations in Data course can help Statisticians build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Statisticians.

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Quantitative Analyst

Quantitative Analysts use their mathematical and statistical skills to analyze financial data and develop trading strategies. They work in the financial industry, helping investment firms make informed decisions. The Data Science with Python: Distributions and Aggregations in Data course can help Quantitative Analysts build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Quantitative Analysts.

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Operations Research Analyst

Operations Research Analysts use their analytical skills to solve complex problems in a variety of industries, including manufacturing, transportation, and healthcare. They develop and implement mathematical models to optimize processes and improve efficiency. The Data Science with Python: Distributions and Aggregations in Data course can help Operations Research Analysts build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Operations Research Analysts.

See salaries and explore the career path for Operations Research Analyst

Market Researcher

Market Researchers use their analytical skills to understand consumer behavior and market trends. They conduct surveys, analyze data, and develop marketing strategies to help businesses reach their target audience. The Data Science with Python: Distributions and Aggregations in Data course can help Market Researchers build a strong foundation in data analysis techniques, which are essential for success in this role. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis, which are all valuable skills for Market Researchers.

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Data Engineer

Data Engineers design, build, and maintain data pipelines and systems. They work with data scientists and other stakeholders to ensure that data is accessible, reliable, and secure. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Data Engineers who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

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Database Administrator

Database Administrators design, implement, and maintain databases. They work with data engineers and other stakeholders to ensure that data is stored, organized, and accessible in a secure manner. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Database Administrators who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They work with stakeholders to gather requirements, design software solutions, and implement and test software code. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Software Engineers who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

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Computer Scientist

Computer Scientists conduct research and develop new computing technologies. They work in a variety of fields, including artificial intelligence, machine learning, and data science. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Computer Scientists who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

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Actuary

Actuaries use their mathematical and statistical skills to assess risk and uncertainty. They work in the insurance industry, helping companies to develop and price insurance products. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Actuaries who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

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Financial Analyst

Financial Analysts use their analytical skills to evaluate investment opportunities and make recommendations to clients. They work in the financial industry, helping individuals and organizations to make informed investment decisions. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Financial Analysts who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

See salaries and explore the career path for Financial Analyst

Epidemiologist

Epidemiologists investigate the causes of disease and develop strategies to prevent and control outbreaks. They work in public health agencies and research institutions, helping to protect the health of populations. The Data Science with Python: Distributions and Aggregations in Data course may be useful to Epidemiologists who want to build a stronger foundation in data analysis techniques. The course covers topics such as exploring data distributions, advanced data summarization techniques, and reshaping data for analysis.

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Reading list

We've selected 18 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Science with Python: Distributions and Aggregations in Data.

Python Data Science Handbook