Getting Started

Figure 1

screenshot of the JupyterLab for launching notebook
Launching a new Python 3 Notebook

Figure 2

screenshot of the Jupyter notebook dropdown to change a cell to Markdown
Changing a cell from Code to Markdown

Data visualization with Pandas and Matplotlib

Figure 1

Our first plot with Pandas, a scatter plot

Figure 2

Adding transparency to our previous scatter plot

Figure 3

Changing the color of the points to our previous scatter plot

Figure 4

Box plot of the hindfoot_length variable

Figure 5

Box plot of the hindfoot_length variable by each plot

Figure 6

Empty plot area in a Matplotlib plot

Figure 7

Adding our previous box plot to the plot area

Figure 8

Rotating x-axis labels to our previous box plot

Figure 9

Customizing our previous box plot adding axis labels and a title

Figure 10

A Matplotlib figure with two subplots, but empty still

Figure 11

Adding scatter and box plots to our figure with two subplots

Figure 12

Customizing title and labels for our figure with two subplots

Figure 13

A figure with three subplots: scatter, box, and histogram

Figure 14

A figure with three subplots: scatter, box, and histogram

Exploring and understanding data

Figure 1

Weight by Species Site

Figure 2

average weight across all species for each plot

Figure 3

total males versus total females for the entire dataset

Indexing, Slicing and Subsetting DataFrames

Figure 1

indexing diagramslicing diagram

Combining DataFrames

Figure 1

average weight for each year, grouped by sex

Figure 2

Inner join -- courtesy of codinghorror.com

Figure 3

Left Join

Figure 4

taxa per plot

Figure 5

taxa per plot

Figure 6

taxa per plot per sex

Figure 7

taxa per plot per sex

Figure 8

taxa per plot per sex

Figure 9

horizontal bar chart of diversity index by plot

Data Workflows and Automation