Templates
Boost your programming skills with free Python, SQL, R, and Excel templates and create top-notch projects for your portfolio.Save hours of browsing through the Internet and accelerate your workflow with code-ready templates for your programming projects. Personally crafted by 365 Data Science instructors, these templates bring a surprising efficiency level to your work process.
15 Ways to Visualize Revenue
Our Excel revenue visualization template offers a comprehensive array of data visualization examples—perfect for understanding your data more intuitively. What is the Excel revenue visualization template? This template is an expansive tool for visualizing revenue data in Excel—providing 15 different visualization methods and examples tailored to diverse analytical needs and presentation styles. It includes all kinds of revenue graphs—from straightforward column and pie charts to more complex data visualization methods like waterfall and Pareto charts. Each revenue chart provides a unique perspective on data, making it a versatile tool for data science students, researchers, and enthusiasts needing to present or understand complex data comprehensively. Simply input your data into any of the following revenue charts to visualize your revenue in Excel. Column chart: Revenue development over time Sparklines chart: Revenue development over time Treemap chart: Revenue by product over time Stacked area chart: Demonstrate the contribution of revenue components Clustered column chart: Show revenue split by category and over time Pie chart: Revenue breakdown in a single period Doughnut chart with total: Revenue breakdown in a single period with total Waterfall chart: Compare annual revenue in a year-over-year growth chart Scatter plot: Plot revenue vs marketing spend Bubble chart: Compare the number of products by company and revenue Combo chart: Track revenue development and margins over time Pie of Pie: Provide a macro and a micro breakdown Map chart: Geographical distribution of revenue Pareto chart: Cumulative revenue contribution by revenue category Funnel chart: Website conversion rate You can choose the ideal method to visualize and extract valuable insights from your data, such as revenue growth charts or breakdowns according to categories like location.
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Data Science Shortcuts Cheat Sheet
Discover how to boost your productivity using this data science shortcuts cheat sheet with over 2,000 workarounds in Python IDEs, such as Jupyter, Spyder Rodeo, PyCharm, and Atom, compatible with various operating systems. Amplify your proficiency in R with R Studio shortcuts, streamline MATLAB operations, and manage databases efficiently with SQL shortcuts. Enhance data visualization in Tableau, easily manage Excel spreadsheets, and conduct statistical analyses seamlessly in SPSS and SAS. This data science shortcuts cheat sheet lets you speed up your everyday tasks while achieving your goals.
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Multi-Dimensional Dictionaries in Python
The following is a program implementing a multi-dimensional dictionary in Python. The notebook shows how to retrieve keys and values from the dictionary, how to create a new key:value pair and how to loop through the keys and the values using a for-loop. Some other related topics you might be interested in are One-Dimensional Dictionaries in Python, Dictionary Comprehension in Python, Using Counter - a Dictionary Subclass in Python. The Multi-Dimensional Dictionaries in Python free template is among the topics covered in detail in the 365 Program.
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Methods in Python - Functions Inside Classes in Python
In Python, we can design and create our own objects with the help of classes. In this free notebook, we will design a class and define two functions inside - two methods. In Python, methods are accessed through the dot-notation. They help interact with an object and are an essential part of a class. Some other related topics you might be interested in are Defining classes in Python, The Pass-Statement in Python, Creating a Constructor in Python - the INIT method, Class Variables in Python, Inheritance in Python. The Methods in Python – Functions Inside Classes in Python template is among the topics covered in detail in the 365 Program.
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Inheritance in Python
In Python, we can design and create our own objects. This is done with the help of classes. The design of these (parent) classes can be inherited by other classes. This allows classes to make use of the constructor and the methods of the parent class. In this notebook, we demonstrate how this can be done with a thorough example. Some other related topics you might be interested in are Defining classes in Python, The pass-statement in Python, Creating a constructor in Python - the INIT method, Class variables in Python, Methods in Python - functions inside classes. The Inheritance in Python template is among the topics covered in detail in the 365 Program.
Learn More![Yellow cover of Indexing with.iloc[] and .loc[] in Python. This template resource is from 365 Data Science.](https://365datascience.com/resources/resources/thumb@240_d39kb37f1qb-indexing-with-iloc-and-loc-in-python-365-data-science.jpg)
Indexing with.iloc[] and .loc[] in Python
The following template demonstrates how to perform indexing with the pandas methods iloc[] and loc[].Some other related topics you might be interested in are Data Selection in Python, Common Attributes for Working with DataFrames in Python, Attribute Chaining in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, and Converting Series into Arrays in Python. The Indexing with.iloc[] and .loc[] in Python template is among the topics covered in detail in the 365 Program.
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Data Selection in Python
The following template demonstrates how to extract elements, rows, columns, or just a subset from a DataFrame object. Some other related topics you might be interested in are Delivering an Array with the Unique Values from a Dataset in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, Attribute Chaining in Python, Common Attributes for Working with DataFrames in Python, Indexing with.iloc[] and .loc[] in Python. The Data Selection in Python template is among the topics covered in detail in the 365 Program.
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Common Attributes for Working with DataFrames in Python
The following template demonstrates the application of important pandas attributes when cleaning, preprocessing, and analyzing a dataset. Some other related topics you might be interested in are Data Selection in Python, Indexing with.iloc[] and .loc[] in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, and Using Pandas Methods for Working with Series Objects in Python. The Common Attributes for Working with DataFrames in Python template is among the topics covered in detail in the 365 Program.
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Attribute Chaining in Python
The following template demonstrates how to use several attributes at once. Some other related topics you might be interested in are Common Attributes for Working with DataFrames in Python, Data Selection in Python, Indexing with.iloc[] and .loc[] in Python, Converting Series into Arrays in Python, and Delivering an Array with the Unique Values from a Dataset in Python. The Attribute Chaining in Python template is among the topics covered in detail in the 365 Program.
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Ordering the Rows from a Data Table According to the Values in a Column in Python
The following template demonstrates how to convert Series objects into pandas and NumPy arrays. Some other related topics you might be interested in are Ordering the Rows from a Data Table According to the Values in a Column in Python, Attribute Chaining in Python, Common Attributes for Working with DataFrames in Python, Data Selection in Python, and Indexing with.iloc[] and .loc[] in Python. The Ordering the Rows from a Data Table According to the Values in a Column in Python template is among the topics covered in greater detail in the 365 Program.
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Converting Series into Arrays in Python
The following template demonstrates how to convert the pandas Series to a NumPy Array using this function. Despite being quite straightforward, this approach has a highly original premise. since we are aware that the Series' output has an index. In contrast, NumPy arrays simply contain their elements. Some other related topics you might be interested in are Ordering the Rows from a Data Table According to the Values in a Column in Python, Indexing with.iloc[] and .loc[] in Python, Data Selection in Python, Common Attributes for Working with DataFrames in Python. The Converting Series into Arrays in Python template is among the topics covered in detail in the 365 Program.
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Obtaining Descriptive Statistics about the Data in Python
The following template demonstrates how to obtain an overview about the dataset. It shows the application of the .describe() method on a pandas Series object. Some other related topics you might be interested in are Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, Data Selection in Python, and Common Attributes for Working with DataFrames in Python. The Obtaining Descriptive Statistics about the Data in Python template is among the topics covered in detail in the 365 Program.
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Creating DataFrames in Python
The following template demonstrates how to create a DataFrame from various datatypes. Some other related topics you might be interested in are Obtaining Descriptive Statistics about the Data in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, and Data Selection in Python. The Creating DataFrames in Python template is among the topics covered in detail in the 365 Program.
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Using Pandas Methods for Working with Series Objects in Python
The following template demonstrates the application of some of the most widely used pandas methods for working with Series objects. Some other related topics you might be interested in are Creating DataFrames in Python, Obtaining Descriptive Statistics about the Data in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, and Data Selection in Python. The Using Pandas Methods for Working with Series Objects in Python template is among the topics covered in detail in the 365 Program.
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Dealing with Indexing in Python
This template shows how to perform various operations regarding indexing in Python. Some other related topics you might be interested in are Using Pandas Methods for Working with Series Objects in Python, Creating DataFrames in Python, Obtaining Descriptive Statistics about the Data in Python, Delivering an Array with the Unique Values from a Dataset in Python, and Ordering the Rows from a Data Table According to the Values in a Column in Python. The Dealing with Indexing in Python template is among the topics covered in detail in the 365 Program.
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Position-Based and Label-Based Indexing in Python
This template shows the difference between position-based and label-based indexing in Python. It demonstrates its application on pandas Series. Some other related topics you might be interested in are Dealing with Indexing in Python, Creating a Series Object from a List in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python and Attribute Chaining in Python. The Position-Based and Label-Based Indexing in Python template is among the topics covered in detail in the 365 Program.
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Indexing in Pandas Python
This template demonstrated the concepts behind indexing in Python by giving pandas objects as an example. Some other related topics you might be interested in are Position-Based and Label-Based Indexing in Python, Dealing with Indexing in Python, Using Pandas Methods for Working with Series Objects in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, and Attribute Chaining in Python. The Indexing in Pandas Python template is among the topics covered in detail in the 365 Program.
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Using Attributes in Python
This template shows how to use attributes for gathering information about different Objects - in particular - pandas Series. Some other related topics you might be interested in are Using Pandas Methods for Working with Series Objects in Python, Creating DataFrames in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, and Ordering the Rows from a Data Table According to the Values in a Column in Python. The Using Attributes in Python template is among the topics covered in detail in the 365 Program.
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Creating a Series Object by Using a NumPy Array in Python
This template shows how to convert a NumPy array into a Series. First, you import the Pandas and NumPy libraries, after which you create an array containing four integer values. Then you turn the array into a series and finally you check the type of the object. Some other related topics you might be interested in are Using Attributes in Python, Indexing in Pandas Python, Position-Based and Label-Based Indexing in Python, and Dealing with Indexing in Python. The creating a Series Object by Using a NumPy Array in Python template is among the topics covered in detail in the 365 Program.
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Creating a Series Object from a List in Python
This template shows how to convert a list object into a Series in the popular Pandas library. Some other related topics you might be interested in are Creating a Series Object by Using a NumPy Array in Python, Using Pandas Methods for Working with Series Objects in Python, Obtaining Descriptive Statistics about the Data in Python, Delivering an Array with the Unique Values from a Dataset in Python, and Ordering the Rows from a Data Table According to the Values in a Column in Python. The Creating a Series Object from a list in Python template is among the topics covered in detail in the 365 Program.
Learn MoreCheck out our most helpful downloadable resources according to 365 Data Science students and our expert team of instructors.
Obtaining Descriptive Statistics about the Data in Python
The following template demonstrates how to obtain an overview about the dataset. It shows the application of the .describe() method on a pandas Series object. Some other related topics you might be interested in are Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, Data Selection in Python, and Common Attributes for Working with DataFrames in Python. The Obtaining Descriptive Statistics about the Data in Python template is among the topics covered in detail in the 365 Program.
Learn MoreData Science Shortcuts Cheat Sheet
Discover how to boost your productivity using this data science shortcuts cheat sheet with over 2,000 workarounds in Python IDEs, such as Jupyter, Spyder Rodeo, PyCharm, and Atom, compatible with various operating systems. Amplify your proficiency in R with R Studio shortcuts, streamline MATLAB operations, and manage databases efficiently with SQL shortcuts. Enhance data visualization in Tableau, easily manage Excel spreadsheets, and conduct statistical analyses seamlessly in SPSS and SAS. This data science shortcuts cheat sheet lets you speed up your everyday tasks while achieving your goals.
Learn MoreCommon Attributes for Working with DataFrames in Python
The following template demonstrates the application of important pandas attributes when cleaning, preprocessing, and analyzing a dataset. Some other related topics you might be interested in are Data Selection in Python, Indexing with.iloc[] and .loc[] in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, and Using Pandas Methods for Working with Series Objects in Python. The Common Attributes for Working with DataFrames in Python template is among the topics covered in detail in the 365 Program.
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Normal Distribution in Excel Template
This Normal Distribution in Excel template demonstrates that the sum of 2 randomly thrown dice is normally distributed. Open the .xlsx file with Microsoft Excel. Study the structure of the file and experiment with different values. Some other related topics you might be interested to explore are Positive Skew in Excel, Zero Skew in Excel, Negative Skew in Excel, Uniform Distribution in Excel, Standard Normal Distribution in Excel You can now download the Excel template for free. Normal Distribution in Excel is among the topics covered in detail in the 365 Data Science program
Learn MoreMost Popular Templates
Check out our most helpful downloadable resources according to 365 Data Science students and our expert team of instructors.
Obtaining Descriptive Statistics about the Data in Python
The following template demonstrates how to obtain an overview about the dataset. It shows the application of the .describe() method on a pandas Series object. Some other related topics you might be interested in are Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, Ordering the Rows from a Data Table According to the Values in a Column in Python, Data Selection in Python, and Common Attributes for Working with DataFrames in Python. The Obtaining Descriptive Statistics about the Data in Python template is among the topics covered in detail in the 365 Program.
Learn MoreData Science Shortcuts Cheat Sheet
Discover how to boost your productivity using this data science shortcuts cheat sheet with over 2,000 workarounds in Python IDEs, such as Jupyter, Spyder Rodeo, PyCharm, and Atom, compatible with various operating systems. Amplify your proficiency in R with R Studio shortcuts, streamline MATLAB operations, and manage databases efficiently with SQL shortcuts. Enhance data visualization in Tableau, easily manage Excel spreadsheets, and conduct statistical analyses seamlessly in SPSS and SAS. This data science shortcuts cheat sheet lets you speed up your everyday tasks while achieving your goals.
Learn MoreCommon Attributes for Working with DataFrames in Python
The following template demonstrates the application of important pandas attributes when cleaning, preprocessing, and analyzing a dataset. Some other related topics you might be interested in are Data Selection in Python, Indexing with.iloc[] and .loc[] in Python, Delivering an Array with the Unique Values from a Dataset in Python, Converting Series into Arrays in Python, and Using Pandas Methods for Working with Series Objects in Python. The Common Attributes for Working with DataFrames in Python template is among the topics covered in detail in the 365 Program.
Learn MoreNormal Distribution in Excel Template
This Normal Distribution in Excel template demonstrates that the sum of 2 randomly thrown dice is normally distributed. Open the .xlsx file with Microsoft Excel. Study the structure of the file and experiment with different values. Some other related topics you might be interested to explore are Positive Skew in Excel, Zero Skew in Excel, Negative Skew in Excel, Uniform Distribution in Excel, Standard Normal Distribution in Excel You can now download the Excel template for free. Normal Distribution in Excel is among the topics covered in detail in the 365 Data Science program
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