This app allows you to quickly make and customize plots visualizing continuous variables, with or without another grouping variable.

Currently, this app supports the following types of plots:

Box Plots

Violin Plots

Histograms

Scatterplots

Bar Plots

Density Plots

Column Plots

To make your own plots, make sure you have your dataset in .csv format and simply follow the instructions below.

1. Upload your data

2. Select which variables to plot

3. Select the plot type

4. Customize plot options and labels

5. Use the download button to save your plot

Please contact us if you have any questions at datascience@colgate.edu.

On this page, you'll find all the necessary details about the plots within this app.

Box plots visually show the distribution of numerical data and skewness through displaying the data quartiles (or percentiles) and averages.

Variable: Quantitative

Optional grouping: Categorical

A column plot is a chart that presents data summaries with rectangular bars with heights proportional to the values that they represent.

Variable: Quantitative

Optional groupin: Categorical

A histogram is an approximate representation of the distribution of numerical data.

Variable: Quantitative

Optional grouping: Categorical

A bar plot is a chart that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent.

Variable: Quantitative

Optional grouping: Categorical

A density curve is a curve on a graph that represents the distribution of values in a dataset.

Variable: Quantitative

Optional grouping: Categorical

On this page, you'll find all the necessary details about the plots within this app.

Box plots visually show the distribution of numerical data and skewness through displaying the data quartiles (or percentiles) and averages.

Variable: Quantitative

Optional grouping: Categorical

A violin plot is a method of plotting numeric data. It is similar to a box plot, with the addition of a rotated kernel density plot on each side. Violin plots are similar to box plots, except that they also show the probability density of the data at different values, usually smoothed by a kernel density estimator.

Variable: Quantitative

Grouping: Categorical

A scatter plot (aka scatter chart, scatter graph) uses dots to represent values for two different numeric variables. The position of each dot on the horizontal and vertical axis indicates values for an individual data point. Scatter plots are used to observe relationships between variables.

X variable: Quantitative

Y variable: Quantitative

On this page, you'll find all the necessary details about the plots within this app.

A bubble plot is a scatterplot where two more dimensions are added: 1) the value of an additional numeric variable is represented through the size of the dots 2) the categorical variable is represented through the color of the dots

X variable: Quantitative

Y variable: Quantitative

Size variable: Quantitative

Optional color variable: Categorical

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