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 will bring a surprising level of efficiency to your work process.
Removing Missing Values with pandas in Python Template
The Removing Missing Values with pandas in Python shows how to detect and remove samples from a dataset that contain missing values. Some other related topics you might be interested are Removing Outliers with pandas in Python, Dummy Variables with pandas in Python, Feature Selection through p-values with sklearn in Python, Feature Selection through standardization with sklearn in Python, Linear Regression Model in Python – residuals. You can now download the Python template for free. The Removing Missing Values with pandas in Python template is among the topics covered in detail in the 365 Data Science program.
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Train and Test Split with sklearn in Python Template
The Train and Test Split with sklearn in Python template shows how to prevent overtraining of the machine learning algorithm by using the convenient train_test_split() method provided by sklearn to split a database into two parts - a training and a testing dataset. Some other related topics you might be interested are Regression Summary Table with sklearn in Python, Feature Selection through p-values with sklearn in Python, Feature Selection through Standardization with sklearn in Python, Predictions with Standardized Coefficients with sklearn in Python. You can now download the Python template for free. The Train and Test Split with sklearn in Python template is among the topics covered in detail in the 365 Data Science program.
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Predictions with Standardized Coefficients with sklearn in Python Template
The Predictions with Standardized Coefficients with sklearn in Python shows how to predict values using a model that was fit on standardized inputs. First, we solve a multiple linear regression problem with two continuous features using the machine learning package sklearn, after which we apply standardization. Some other related topics you might be interested are Predictions with statsmodels in Python, Feature Selection through Standardization with sklearn in Python, Visualizing Linear Regressions with matplotlib in Python. You can now download the Python template for free. The Predictions with Standardized Coefficients with sklearn in Python template is among the topics covered in detail in the 365 Data Science program.
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Correlation in Excel Template
The Correlation in Excel template demonstrates how the correlation coefficient can be calculated in Excel. Some other related topics you might be interested in are Calculating the Variance in Excel, Standard Deviation in Excel, Coefficient of Variation in Excel, Covariance in Excel. You can now download the Excel template for free. The Correlation in Excel template is among the topics covered in detail in the 365 Data Science program.
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Covariance in Excel Template
The Covariance in Excel template demonstrates how the covariance metric can be calculated in Excel. Some other related topics you might be interested in are Calculating the Variance in Excel, Standard Deviation in Excel, Coefficient of Variation in Excel, Correlation in Excel You can now download the Excel template for free. The Covariance in Excel template is among the topics covered in detail in the 365 Data Science program.
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Standard Deviation in Excel Template
The following Standard Deviation in Excel template introduces the relevant Excel syntax for calculating sample standard deviation. Some other related topics you might be interested in are Calculating the variance in Excel, Coefficient of Variation in Excel, Covariance in Excel, Correlation in Excel You can now download the Excel template for free. Standard Deviation in Excel template is among the topics covered in detail in the 365 Data Science program.
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Calculating the Variance in Excel Template
The following Calculating the Variance in Excel template demonstrates the difference between sample variance and population variance. It introduces the relevant Excel syntax for calculating these 2 metrics. Some other related topics you might be interested in are Standard Deviation in Excel, Coefficient of Variation in Excel, Covariance in Excel, Correlation in Excel. You can now download the Excel template for free. Calculating the Variance in Excel template is among the topics covered in detail in the 365 Data Science program.
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Negative Skew in Excel Template
The following Negative Skew in Excel template includes a sample dataset resulting in a negatively (left) skewed frequency distribution graph. Some other related topics you might be interested in are Positive Skew in Excel, Zero Skew in Excel, Normal Distribution in Excel, Standard Normal Distribution in Excel. You can now download the Excel template for free. Negative Skew in Excel template is among the topics covered in detail in the 365 Data Science program.
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Zero Skew in Excel Template
The following Zero Skew in Excel template includes a sample dataset resulting in a zero skewed (no skew) frequency distribution graph Some other related topics you might be interested in are Positive Skew in Excel, Negative Skew in Excel, Normal Distribution in Excel, Standard Normal Distribution in Excel. You can now download the Excel template for free. Zero Skew in Excel template is among the topics covered in detail in the 365 Data Science program.
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Positive Skew in Excel Template
The Positive Skew in Excel template includes a sample dataset resulting in a positively (right) skewed frequency distribution graph. Some other related topics you might be interested in are Zero Skew in Excel, Negative Skew in Excel, Normal Distribution in Excel, Standard Normal Distribution in Excel. You can now download the Excel template for free. Positive Skew in Excel template is among the topics covered in detail in the 365 Data Science program.
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Calculating the Mode in Excel Template
The Calculating the Mode in Excel template shows how to apply the Excel function corresponding to finding the mode of a set of numbers. Some other related topics you might be interested in are Calculating the Mean in Excel, Calculating the Median in Excel, Covariance in Excel, and Correlation in Excel. You can now download the Excel template for free. Calculating the Mode in Excel template is among the topics covered in detail in the 365 Data Science program.
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Calculating the Median in Excel Template
The Calculating the Median in Excel template shows how to apply the Excel function corresponding to finding the median of a set of numbers. Some other related topics you might be interested in are Calculating the Mean in Excel, Calculating the Mode in Excel, Covariance in Excel, and Correlation in Excel.
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Calculating the Mean in Excel Template
The Calculating the Mean in Excel template shows how to apply the Excel function corresponding to finding the mean of a set of numbers. Some other related topics you might be interested in are Pareto Diagram in Excel, Side-by-Side Bar Chart in Excel, Normal Distribution in Excel, Stacked Area Chart in matplotlib Python, Bar and Line chart in Excel You can now download the Excel template for free. Calculating the Mean in Excel template is among the topics covered in detail in the 365 Data Science program.
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Export Data as csv in R Template
The Export Data as csv in R template shows how to export a data set from R and save it as an csv file. The file in question contains an employee database. Some other related topics you might be interested in are Calculating Standard Deviation in R, Calculating Data Mean in R, Calculating Standard Deviation of Data in R, Exploring Data Skewness in R. You can now download the R template for free. Export Data as csv in R template is among the topics covered in detail in the 365 Data Science program.
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Adding a New Column to a Data Frame in R Template
The Adding a New Column to a Data Frame in R template shows how to create a dataframe in R and add additional columns to it. We create a Star Wars data frame containing movies and stats and include two additional columns to extend the dataframe. Some other related topics you might be interested are Adding a New Row to a Data Frame in R, Dealing with Missing Data in R, Read a csv File into R, Export Data as csv in R. You can now download the R template for free. Adding a New Column to a Data Frame in R template is among the topics covered in detail in the 365 Data Science program.
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Adding a New Row to a Data Frame in R Template
The Adding a New Row to a Data Frame in R template shows how to add a row in an R data frame. The file shows how to create a data frame object in R from scratch, containing information and stats about movies and then shows how to extend the data frame by adding new columns. Some other related topics you might be interested are Adding a New Column to a Data Frame in R, Dealing with Missing Data in R, Read a csv File into R, Export Data as csv in R. You can now download the R template for free. Adding a New Row to a Data Frame in R template is among the topics covered in detail in the 365 Data Science program.
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Read a csv File in R Template
The Read a csv File in R template shows how to import a csv file into R with the help of the read csv() function. The file in question contains a real estate data set detailing information on different properties. Some other related topics you might be interested are Scatter plot with ggplot2 in R, Regression Scatter with ggplot2 in R, and Correlation between Two Variables in R. You can now download the R template for free. The Read a csv File in R template is among the topics covered in detail in the 365 Data Science program.
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Linear Regression in R Template
The Linear Regression in R template shows how to perform a linear regression in R using lm() on real estate property data. Some other related topics you might be interested are Scatter plot with ggplot2 in R, Regression Scatter with ggplot2 in R, and Correlation between Two Variables in R. You can now download the R template for free. Linear Regression in R template is among the topics covered in detail in the 365 Data Science program.
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Correlation between Two Variables in R Template
The Correlation between Two Variables in R template shows how to calculate the correlation coefficient between two variables in a dataset with the help of the corr() function. Some other related topics you might be interested in checking are Calculating Data Variance in R, Calculating Data Mean in R, Calculating Standard Deviation of Data in R, and Exploring Data Skewness in R. You can now download the R template for free. Correlation between Two Variables in R is among the topics covered in detail in the 365 Data Science program.
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DELETE Statement in SQL
The DELETE Statement in SQL template shows you how to delete information from the table's columns. Download and unzip the .zip file in a new folder. Inside the folder you will find a .sql file. Load it into MySQL Workbench. Some other related topics you might be interested are Creating a Database, ORDER BY Clause, SELECT Statement, and INSERT Statement. You can now download the SQL template for free. DELETE Statement in SQL is among the topics covered in detail in the 365 Data Science 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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The Enumerate Function in Python
The following notebook demonstrates how to iterate through a list more effectively using the enumerate() built-in function in Python. Some other related topics you might be interested in are The zip function in Python, Defining functions in Python - the Fibonacci sequence, Recursion in Python - the Fibonacci sequence and Defining Classes in Python. The Enumerate Function in Python template is among the topics covered in detail in the 365 Data Science Program.
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Box and Whiskers Chart with ggplot2 in R
A box and whiskers chart graphically represents the distribution of data through their quartiles. It is often used in financial settings when analyzing the market volatility and can reveal the skewness of data or potential outliers. Тhis free .r template goes over the Titanic’s data set using the ggplot2 library in R, revealing interesting insights about e the survival rate based on age and sex. By following the outlined steps in this R template, you will learn how to convey the information professionally using the ggplot2 functionalities.
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Check out our most helpful downloadable resources according to 365 Data Science’s students and expert team of instructors.
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.
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.
Learn MoreThe Enumerate Function in Python
The following notebook demonstrates how to iterate through a list more effectively using the enumerate() built-in function in Python. Some other related topics you might be interested in are The zip function in Python, Defining functions in Python - the Fibonacci sequence, Recursion in Python - the Fibonacci sequence and Defining Classes in Python. The Enumerate Function in Python template is among the topics covered in detail in the 365 Data Science Program.
Learn MoreBox and Whiskers Chart with ggplot2 in R
A box and whiskers chart graphically represents the distribution of data through their quartiles. It is often used in financial settings when analyzing the market volatility and can reveal the skewness of data or potential outliers. Тhis free .r template goes over the Titanic’s data set using the ggplot2 library in R, revealing interesting insights about e the survival rate based on age and sex. By following the outlined steps in this R template, you will learn how to convey the information professionally using the ggplot2 functionalities.
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