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.
Sending a GET Request in Python Template
This free .ipynb template demonstrates how to send an HTTP GET request in Python which is the backbone of the modern internet- the most popular one is the GET request. This type of request is the most basic form of request since it is sent to servers when opening web pages or accessing APIs. In this template, we have implemented a simple GET request using the Python library "requests".
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Stacked Area Chart Notebook in Matplotlib Python Template
In this free .ipynb template we have a stacked area chart, implemented in Python with the Pyplot module of Matplotlib. The chart shows the popularity of different engine types in automobiles across the span of several decades. In the stacked area chart each category is ‘stacked’ or ‘placed’ on top of the previous, presenting the totality of the data and avoiding overlap among categories.
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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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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.
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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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