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.
String Formatting in Python
In the following notebook template , you will find a series of examples that demonstrate the most important operations that one can perform on strings. From finding the length of a string all the way to creating a string storing a small poem and splitting it into separate words using the split() and strip() method. Some other related topics you might be interested in are User inputs in Python, Using Counter - a dictionary subclass in Python, Loops and if-statements, and Regular expressions in Python. The String Formatting in Python template is among the topics covered in detail in the 365 Data Science program
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User Inputs in Python
The following template is a program which demonstrates how to ask the user for an input and store that input either as a string, or as an integer, depending on the needs. Some other related topics you might be interested in are String formatting in Python, The if-else statement in Python, While-loops in Python, For-loops in Python. The User Inputs in Python template is among the topics covered in detail in the 365 Data Science program.
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Getting the Current Time in Python
This is a template demonstrating how to estimate the local time in the current time zone. It shows the application of the .now() method. Some other related topics you might be interested in are Converting Strings into Datetime Objects in Python, Replacing the Values of Datetime Objects in Python, Getting the Date of the Week in Python and Working with Format Codes in Python. The Getting the Current Time in Python template is among the topics covered in detail in the 365 Data Science program.
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Converting Strings into Datetime Objects in Python
This is a template demonstrating how to convert string values into datetime objects and display these values in a user-friendly form in Python. It includes the application of the .strptime() method from the datetime module. Some other related topics you might be interested in are Timestamps in Python, Converting Datetime Objects into Strings in Python, Replacing the Values of Datetime Objects in Python, and Working with Format Codes in Python. The Converting Strings into Datetime Objects in Python template is among the topics covered in detail in the 365 Data Science program.
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Working with Format Codes in Python
This template shows how to use the format codes. It demonstrates the combination of the Python .strftime() method and the format codes for indicating separate date and time elements. Other related topics you might be interested in are Timestamps in Python, Converting Datetime Objects into Strings in Python, Replacing the Values of Datetime Objects in Python, and Displaying Time Elements in Python. The Working with Format Codes in Python template is among the topics covered in detail in the 365 Data Science program.
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Timestamps in Python
This is a template demonstrating how to work with both date and time values in the form of a timestamp. Other related topics you might be interested in are Attributes of the Python Time class , Datetime Values in Python, Attributes of the Python Time Class, Working with Dates and Times Simultaneously and Converting Strings into Datetime Objects in Python. The Timestamps in Python template is among the topics covered in detail in the 365 Data Science program.
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Converting Datetime Objects into Strings in Python
This template shows how to convert datetime objects into strings. It demonstrates the application of the Python .strftime() method in a combination with the format codes. Other related topics you might be interested are Importing the Datetime Module in Python, Datetime Values in Python, Attributes of the Python Time Class, Estimating the Difference between Two Dates - timedelta Python, and Converting Strings into Datetime Objects in Python. The Converting Datetime Objects into Strings in Python template is among the topics covered in detail in the 365 Data Science program.
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Replacing the Values of Datetime Objects in Python
This template shows how to replace separate elements in a datetime object. It demonstrates the application of the .replace() method. Other related topics you might be interested in are Displaying Dates in Python, Datetime Values in Python, Getting the Date of the Week in Python, Displaying Time Elements in Python, Attributes of the Python Time Class, and Estimating the Difference between Two Dates - timedelta Python. The Replacing the Values of Datetime Objects in Python template is among the topics covered in detail in the 365 Data Science program.
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Working with Dates and Times Simultaneously in Python
This template shows how to use the 'datetime' class and manipulate date and time values simultaneously. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Displaying Dates in Python, Displaying Time in Python, Attributes of the Python Time Class, and Estimating the Difference between Two Dates - timedelta Python. The Working with Dates and Times Simultaneously in Python template is among the topics covered in detail in the 365 Data Science program.
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Displaying Time Elements in Python
This is a template that shows how can we display single elements from a time value using a function. Single elements can be microseconds, seconds, minutes, and hours. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Attributes of the Python Date Class, Displaying Time in Python, and Attributes of the Python Time Class. The Displaying Time Elements in Python template is among the topics covered in detail in the 365 Data Science program.
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Attributes of the Python Time Class
This is a template demonstrating the application of the 'time' class. It shows how to display time values with the attributes of the class and how to display time in a user-friendly form. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Attributes of the Python Date Class, Displaying Dates in Python and Estimating the Difference between Two Dates - timedelta Python. The Attributes of the Python Time Class template is among the topics covered in detail in the 365 Data Science program.
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Displaying Time in Python
This is a template demonstrating the implementation of the 'time' class and the way time values can be displayed like on a real clock. The 'time' class is part of the datetime module. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Attributes of the Python Date Class, Displaying Dates in Python and Estimating the Difference between Two Dates - timedelta Python. The Displaying Time in Python template is among the topics covered in detail in the 365 Data Science program.
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Getting the Date of the Week in Python
This is a template demonstrating how we can estimate the day of the week with the help of the .weekday() function - part of the date class from the datetime module. The function returns an integer corresponding to the day of the week. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Attributes of the Python Date Class, Displaying Time in Python. The Getting the Date of the Week in Python template is among the topics covered in detail in the 365 Data Science program.
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Estimating the Difference between Two Dates - timedelta Python
This is a template demonstrating how we can estimate the duration between two dates in Python. It introduces the use of the class 'timedelta'. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Displaying Dates in Python, Attributes of the Python Date Class. The Estimating the Difference between Two Dates template is among the topics covered in detail in the 365 Data Science program.
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Attributes of the Python Date Class
The Attributes of the Python Date Class demonstrates the use of the attributes of the date class from the datetime module. It shows how to display the separate date elements. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Displaying Dates in Python, Displaying Time in Python. The Attributes of the Python Date Class template is among the topics covered in detail in the 365 Data Science program.
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Displaying Dates in Python
This is a template demonstrating how to convert values into datetimes and display these values in a user-friendly form. It includes the application of the .strptime() method from the datetime module. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Displaying Dates in Python, Displaying Time in Python.The Displaying Dates in Python template is among the topics covered in detail in the 365 Data Science program.
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Importing the Datetime Module in Python
This template demonstrates the technique of importing the Python datetime module and its separate classes for working with dates and times. Other related topics you might be interested in are Datetime Values in Python, Displaying Dates in Python, Displaying Dates in Python, Displaying Time in Python. The Importing the Datetime Module in Python template is among the topics covered in detail in the 365 Data Science program.
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Bar and Line Chart with Matplotlib in Python
This template shows a combination chart, showing the frequency of Python users among participants from a KDNuggets annual survey across several consecutive years, represented with a bar and line chart in Python's matplotlib library. Some other related topics you might be interested in are Bar chart in matplotlib Python, Line chart in matplotlib Python, Regression scatter plot with seaborn matplotlib in Python, Regression Scatter Plot with seaborn regplot in Python. The Bar and Line Chart with Matplotlib in Python template is among the topics covered in detail in the 365 Data Science program.
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Model Accuracy in Python
In this template, we classify points using the logistic regression method provided by statsmodels. Afterwards, we create a confusion matrix that makes it easier to see the correctly and incorrectly classified classes. Some other related topics you might be interested in are Logistic Regression with statsmodels in Python, Confusion Matrix with statsmodels in Python, Logistic Regression Curve in Python. The Model Accuracy in Python template is among the topics covered in detail in the 365 Data Science program.
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Logistic Regression Curve in Python
In this template, we demonstrate how to create a logistic regression using statsmodels. Then, we plot the resulting regression curve onto the data points to visualize the result. Some other related topics you might be interested in are Logistic Regression with statsmodels in Python, Confusion Matrix with Statsmodels in Python, Model Accuracy in Python. You can now download the Python template for free. The Logistic Regression Curve in Python template is among the topics covered in detail in the 365 Data Science 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.
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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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Linear Regression with statsmodels in Python Template
The following Linear Regression with Statsmodels in Python free .ipynb template shows how to solve a simple linear regression problem using the Ordinary Least Squares statsmodels library. We are going to examine the causal relationship between the independent variable in the dataset - SAT score of a student, and the dependent variable -the GPA score. This database is read with the help of the pandas library. Download and unzip the .zip file in a new folder. Inside the folder you will find a .csv and a .ipynb file. The first one contains the database and the second one contains the Python code. Open the .ipynb file using Jupyter notebook.
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Confusion Matrix with statsmodels in Python Template
In this Confusion Matrix with statsmodels in Python template, we will show you how to solve a simple classification problem using the logistic regression algorithm. Then, we will create a python confusion matrix of the model using the statsmodels library and make the table more beautiful and readable with the help of the pandas library. Some other related topics you might be interested in are Logistic regression with statsmodels in Python, Logistic Regression Curve in Python, Model Accuracy in Python. You can now download the Python template for free. The Confusion Matrix with statsmodels in Python template 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 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 MoreLinear Regression with statsmodels in Python Template
The following Linear Regression with Statsmodels in Python free .ipynb template shows how to solve a simple linear regression problem using the Ordinary Least Squares statsmodels library. We are going to examine the causal relationship between the independent variable in the dataset - SAT score of a student, and the dependent variable -the GPA score. This database is read with the help of the pandas library. Download and unzip the .zip file in a new folder. Inside the folder you will find a .csv and a .ipynb file. The first one contains the database and the second one contains the Python code. Open the .ipynb file using Jupyter notebook.
Learn MoreConfusion Matrix with statsmodels in Python Template
In this Confusion Matrix with statsmodels in Python template, we will show you how to solve a simple classification problem using the logistic regression algorithm. Then, we will create a python confusion matrix of the model using the statsmodels library and make the table more beautiful and readable with the help of the pandas library. Some other related topics you might be interested in are Logistic regression with statsmodels in Python, Logistic Regression Curve in Python, Model Accuracy in Python. You can now download the Python template for free. The Confusion Matrix with statsmodels in Python template is among the topics covered in detail in the 365 Data Science program.
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